Repository: louiskang-group/kang-2024-examples-concepts
Branch: main
Commit: 8800220a51f2
Files: 320
Total size: 78.0 MB

Directory structure:
gitextract_oceubnxc/

├── .gitignore
├── LICENSE.md
├── README.md
├── hippocampus/
│   ├── 1_pathways.ipynb
│   ├── 2a_hopfield.sh
│   ├── 2b_sweep.sh
│   ├── 2c_oscillation.sh
│   ├── 3_visualization.ipynb
│   ├── README.md
│   ├── out/
│   │   ├── hopfield/
│   │   │   ├── test_a.txt
│   │   │   ├── test_log.txt
│   │   │   ├── test_mclassic.txt
│   │   │   ├── test_mcustom.txt
│   │   │   ├── test_params.txt
│   │   │   ├── test_qcue.txt
│   │   │   ├── test_qmu.txt
│   │   │   ├── test_qnu.txt
│   │   │   └── test_wsample.txt
│   │   ├── oscillation/
│   │   │   ├── baseline_a.txt
│   │   │   ├── baseline_log.txt
│   │   │   ├── baseline_mcategory.txt
│   │   │   ├── baseline_mother.txt
│   │   │   ├── baseline_msparse.txt
│   │   │   ├── baseline_params.txt
│   │   │   ├── baseline_qcue.txt
│   │   │   ├── baseline_qmu.txt
│   │   │   ├── baseline_qnu.txt
│   │   │   ├── baseline_theta.txt
│   │   │   └── baseline_wsample.txt
│   │   ├── pathways/
│   │   │   ├── AE.pt
│   │   │   └── FF.pt
│   │   ├── sweep/
│   │   │   ├── bc-s001_a.txt
│   │   │   ├── bc-s001_log.txt
│   │   │   ├── bc-s001_mclassic.txt
│   │   │   ├── bc-s001_mcustom.txt
│   │   │   ├── bc-s001_params.txt
│   │   │   ├── bc-s001_qcue.txt
│   │   │   ├── bc-s001_qmu.txt
│   │   │   ├── bc-s001_qnu.txt
│   │   │   ├── bc-s001_wsample.txt
│   │   │   ├── bc-s003_a.txt
│   │   │   ├── bc-s003_log.txt
│   │   │   ├── bc-s003_mclassic.txt
│   │   │   ├── bc-s003_mcustom.txt
│   │   │   ├── bc-s003_params.txt
│   │   │   ├── bc-s003_qcue.txt
│   │   │   ├── bc-s003_qmu.txt
│   │   │   ├── bc-s003_qnu.txt
│   │   │   ├── bc-s003_wsample.txt
│   │   │   ├── bc-s010_a.txt
│   │   │   ├── bc-s010_log.txt
│   │   │   ├── bc-s010_mclassic.txt
│   │   │   ├── bc-s010_mcustom.txt
│   │   │   ├── bc-s010_params.txt
│   │   │   ├── bc-s010_qcue.txt
│   │   │   ├── bc-s010_qmu.txt
│   │   │   ├── bc-s010_qnu.txt
│   │   │   ├── bc-s010_wsample.txt
│   │   │   ├── bc-s030_a.txt
│   │   │   ├── bc-s030_log.txt
│   │   │   ├── bc-s030_mclassic.txt
│   │   │   ├── bc-s030_mcustom.txt
│   │   │   ├── bc-s030_params.txt
│   │   │   ├── bc-s030_qcue.txt
│   │   │   ├── bc-s030_qmu.txt
│   │   │   ├── bc-s030_qnu.txt
│   │   │   ├── bc-s030_wsample.txt
│   │   │   ├── bc-s100_a.txt
│   │   │   ├── bc-s100_log.txt
│   │   │   ├── bc-s100_mclassic.txt
│   │   │   ├── bc-s100_mcustom.txt
│   │   │   ├── bc-s100_params.txt
│   │   │   ├── bc-s100_qcue.txt
│   │   │   ├── bc-s100_qmu.txt
│   │   │   ├── bc-s100_qnu.txt
│   │   │   ├── bc-s100_wsample.txt
│   │   │   ├── bs-s001_a.txt
│   │   │   ├── bs-s001_log.txt
│   │   │   ├── bs-s001_mclassic.txt
│   │   │   ├── bs-s001_mcustom.txt
│   │   │   ├── bs-s001_params.txt
│   │   │   ├── bs-s001_qcue.txt
│   │   │   ├── bs-s001_qmu.txt
│   │   │   ├── bs-s001_qnu.txt
│   │   │   ├── bs-s001_wsample.txt
│   │   │   ├── bs-s003_a.txt
│   │   │   ├── bs-s003_log.txt
│   │   │   ├── bs-s003_mclassic.txt
│   │   │   ├── bs-s003_mcustom.txt
│   │   │   ├── bs-s003_params.txt
│   │   │   ├── bs-s003_qcue.txt
│   │   │   ├── bs-s003_qmu.txt
│   │   │   ├── bs-s003_qnu.txt
│   │   │   ├── bs-s003_wsample.txt
│   │   │   ├── bs-s010_a.txt
│   │   │   ├── bs-s010_log.txt
│   │   │   ├── bs-s010_mclassic.txt
│   │   │   ├── bs-s010_mcustom.txt
│   │   │   ├── bs-s010_params.txt
│   │   │   ├── bs-s010_qcue.txt
│   │   │   ├── bs-s010_qmu.txt
│   │   │   ├── bs-s010_qnu.txt
│   │   │   ├── bs-s010_wsample.txt
│   │   │   ├── bs-s030_a.txt
│   │   │   ├── bs-s030_log.txt
│   │   │   ├── bs-s030_mclassic.txt
│   │   │   ├── bs-s030_mcustom.txt
│   │   │   ├── bs-s030_params.txt
│   │   │   ├── bs-s030_qcue.txt
│   │   │   ├── bs-s030_qmu.txt
│   │   │   ├── bs-s030_qnu.txt
│   │   │   ├── bs-s030_wsample.txt
│   │   │   ├── bs-s100_a.txt
│   │   │   ├── bs-s100_log.txt
│   │   │   ├── bs-s100_mclassic.txt
│   │   │   ├── bs-s100_mcustom.txt
│   │   │   ├── bs-s100_params.txt
│   │   │   ├── bs-s100_qcue.txt
│   │   │   ├── bs-s100_qmu.txt
│   │   │   ├── bs-s100_qnu.txt
│   │   │   ├── bs-s100_wsample.txt
│   │   │   ├── dc-s001_a.txt
│   │   │   ├── dc-s001_log.txt
│   │   │   ├── dc-s001_mclassic.txt
│   │   │   ├── dc-s001_mcustom.txt
│   │   │   ├── dc-s001_params.txt
│   │   │   ├── dc-s001_qcue.txt
│   │   │   ├── dc-s001_qmu.txt
│   │   │   ├── dc-s001_qnu.txt
│   │   │   ├── dc-s001_wsample.txt
│   │   │   ├── dc-s003_a.txt
│   │   │   ├── dc-s003_log.txt
│   │   │   ├── dc-s003_mclassic.txt
│   │   │   ├── dc-s003_mcustom.txt
│   │   │   ├── dc-s003_params.txt
│   │   │   ├── dc-s003_qcue.txt
│   │   │   ├── dc-s003_qmu.txt
│   │   │   ├── dc-s003_qnu.txt
│   │   │   ├── dc-s003_wsample.txt
│   │   │   ├── dc-s010_a.txt
│   │   │   ├── dc-s010_log.txt
│   │   │   ├── dc-s010_mclassic.txt
│   │   │   ├── dc-s010_mcustom.txt
│   │   │   ├── dc-s010_params.txt
│   │   │   ├── dc-s010_qcue.txt
│   │   │   ├── dc-s010_qmu.txt
│   │   │   ├── dc-s010_qnu.txt
│   │   │   ├── dc-s010_wsample.txt
│   │   │   ├── dc-s030_a.txt
│   │   │   ├── dc-s030_log.txt
│   │   │   ├── dc-s030_mclassic.txt
│   │   │   ├── dc-s030_mcustom.txt
│   │   │   ├── dc-s030_params.txt
│   │   │   ├── dc-s030_qcue.txt
│   │   │   ├── dc-s030_qmu.txt
│   │   │   ├── dc-s030_qnu.txt
│   │   │   ├── dc-s030_wsample.txt
│   │   │   ├── dc-s100_a.txt
│   │   │   ├── dc-s100_log.txt
│   │   │   ├── dc-s100_mclassic.txt
│   │   │   ├── dc-s100_mcustom.txt
│   │   │   ├── dc-s100_params.txt
│   │   │   ├── dc-s100_qcue.txt
│   │   │   ├── dc-s100_qmu.txt
│   │   │   ├── dc-s100_qnu.txt
│   │   │   ├── dc-s100_wsample.txt
│   │   │   ├── ds-s001_a.txt
│   │   │   ├── ds-s001_log.txt
│   │   │   ├── ds-s001_mclassic.txt
│   │   │   ├── ds-s001_mcustom.txt
│   │   │   ├── ds-s001_params.txt
│   │   │   ├── ds-s001_qcue.txt
│   │   │   ├── ds-s001_qmu.txt
│   │   │   ├── ds-s001_qnu.txt
│   │   │   ├── ds-s001_wsample.txt
│   │   │   ├── ds-s003_a.txt
│   │   │   ├── ds-s003_log.txt
│   │   │   ├── ds-s003_mclassic.txt
│   │   │   ├── ds-s003_mcustom.txt
│   │   │   ├── ds-s003_params.txt
│   │   │   ├── ds-s003_qcue.txt
│   │   │   ├── ds-s003_qmu.txt
│   │   │   ├── ds-s003_qnu.txt
│   │   │   ├── ds-s003_wsample.txt
│   │   │   ├── ds-s010_a.txt
│   │   │   ├── ds-s010_log.txt
│   │   │   ├── ds-s010_mclassic.txt
│   │   │   ├── ds-s010_mcustom.txt
│   │   │   ├── ds-s010_params.txt
│   │   │   ├── ds-s010_qcue.txt
│   │   │   ├── ds-s010_qmu.txt
│   │   │   ├── ds-s010_qnu.txt
│   │   │   ├── ds-s010_wsample.txt
│   │   │   ├── ds-s030_a.txt
│   │   │   ├── ds-s030_log.txt
│   │   │   ├── ds-s030_mclassic.txt
│   │   │   ├── ds-s030_mcustom.txt
│   │   │   ├── ds-s030_params.txt
│   │   │   ├── ds-s030_qcue.txt
│   │   │   ├── ds-s030_qmu.txt
│   │   │   ├── ds-s030_qnu.txt
│   │   │   ├── ds-s030_wsample.txt
│   │   │   ├── ds-s100_a.txt
│   │   │   ├── ds-s100_log.txt
│   │   │   ├── ds-s100_mclassic.txt
│   │   │   ├── ds-s100_mcustom.txt
│   │   │   ├── ds-s100_params.txt
│   │   │   ├── ds-s100_qcue.txt
│   │   │   ├── ds-s100_qmu.txt
│   │   │   ├── ds-s100_qnu.txt
│   │   │   ├── ds-s100_wsample.txt
│   │   │   ├── sc-s001_a.txt
│   │   │   ├── sc-s001_log.txt
│   │   │   ├── sc-s001_mclassic.txt
│   │   │   ├── sc-s001_mcustom.txt
│   │   │   ├── sc-s001_params.txt
│   │   │   ├── sc-s001_qcue.txt
│   │   │   ├── sc-s001_qmu.txt
│   │   │   ├── sc-s001_qnu.txt
│   │   │   ├── sc-s001_wsample.txt
│   │   │   ├── sc-s003_a.txt
│   │   │   ├── sc-s003_log.txt
│   │   │   ├── sc-s003_mclassic.txt
│   │   │   ├── sc-s003_mcustom.txt
│   │   │   ├── sc-s003_params.txt
│   │   │   ├── sc-s003_qcue.txt
│   │   │   ├── sc-s003_qmu.txt
│   │   │   ├── sc-s003_qnu.txt
│   │   │   ├── sc-s003_wsample.txt
│   │   │   ├── sc-s010_a.txt
│   │   │   ├── sc-s010_log.txt
│   │   │   ├── sc-s010_mclassic.txt
│   │   │   ├── sc-s010_mcustom.txt
│   │   │   ├── sc-s010_params.txt
│   │   │   ├── sc-s010_qcue.txt
│   │   │   ├── sc-s010_qmu.txt
│   │   │   ├── sc-s010_qnu.txt
│   │   │   ├── sc-s010_wsample.txt
│   │   │   ├── sc-s030_a.txt
│   │   │   ├── sc-s030_log.txt
│   │   │   ├── sc-s030_mclassic.txt
│   │   │   ├── sc-s030_mcustom.txt
│   │   │   ├── sc-s030_params.txt
│   │   │   ├── sc-s030_qcue.txt
│   │   │   ├── sc-s030_qmu.txt
│   │   │   ├── sc-s030_qnu.txt
│   │   │   ├── sc-s030_wsample.txt
│   │   │   ├── sc-s100_a.txt
│   │   │   ├── sc-s100_log.txt
│   │   │   ├── sc-s100_mclassic.txt
│   │   │   ├── sc-s100_mcustom.txt
│   │   │   ├── sc-s100_params.txt
│   │   │   ├── sc-s100_qcue.txt
│   │   │   ├── sc-s100_qmu.txt
│   │   │   ├── sc-s100_qnu.txt
│   │   │   ├── sc-s100_wsample.txt
│   │   │   ├── ss-s001_a.txt
│   │   │   ├── ss-s001_log.txt
│   │   │   ├── ss-s001_mclassic.txt
│   │   │   ├── ss-s001_mcustom.txt
│   │   │   ├── ss-s001_params.txt
│   │   │   ├── ss-s001_qcue.txt
│   │   │   ├── ss-s001_qmu.txt
│   │   │   ├── ss-s001_qnu.txt
│   │   │   ├── ss-s001_wsample.txt
│   │   │   ├── ss-s003_a.txt
│   │   │   ├── ss-s003_log.txt
│   │   │   ├── ss-s003_mclassic.txt
│   │   │   ├── ss-s003_mcustom.txt
│   │   │   ├── ss-s003_params.txt
│   │   │   ├── ss-s003_qcue.txt
│   │   │   ├── ss-s003_qmu.txt
│   │   │   ├── ss-s003_qnu.txt
│   │   │   ├── ss-s003_wsample.txt
│   │   │   ├── ss-s010_a.txt
│   │   │   ├── ss-s010_log.txt
│   │   │   ├── ss-s010_mclassic.txt
│   │   │   ├── ss-s010_mcustom.txt
│   │   │   ├── ss-s010_params.txt
│   │   │   ├── ss-s010_qcue.txt
│   │   │   ├── ss-s010_qmu.txt
│   │   │   ├── ss-s010_qnu.txt
│   │   │   ├── ss-s010_wsample.txt
│   │   │   ├── ss-s030_a.txt
│   │   │   ├── ss-s030_log.txt
│   │   │   ├── ss-s030_mclassic.txt
│   │   │   ├── ss-s030_mcustom.txt
│   │   │   ├── ss-s030_params.txt
│   │   │   ├── ss-s030_qcue.txt
│   │   │   ├── ss-s030_qmu.txt
│   │   │   ├── ss-s030_qnu.txt
│   │   │   ├── ss-s030_wsample.txt
│   │   │   ├── ss-s100_a.txt
│   │   │   ├── ss-s100_log.txt
│   │   │   ├── ss-s100_mclassic.txt
│   │   │   ├── ss-s100_mcustom.txt
│   │   │   ├── ss-s100_params.txt
│   │   │   ├── ss-s100_qcue.txt
│   │   │   ├── ss-s100_qmu.txt
│   │   │   ├── ss-s100_qnu.txt
│   │   │   └── ss-s100_wsample.txt
│   │   └── visualization/
│   │       ├── oscillation.h5
│   │       └── sweep.h5
│   └── src/
│       ├── compile.sh
│       ├── dynamics.c
│       └── search.c
└── ml/
    ├── 1task-concept.ipynb
    ├── 1task-example.ipynb
    ├── 2tasks.ipynb
    ├── README.md
    ├── converted/
    │   ├── 1task-concept.py
    │   ├── 1task-example.py
    │   ├── 2tasks.py
    │   └── nb2script.sh
    ├── lib/
    │   ├── ml.py
    │   ├── train.py
    │   └── utils.py
    └── out/
        ├── 1task-concept.h5
        ├── 1task-example.h5
        └── 2tasks.h5

================================================
FILE CONTENTS
================================================

================================================
FILE: .gitignore
================================================
*.ipynb_checkpoints

# Large datasets; downloaded automatically or found in Google Drive repository
data

# C compiled binaries
*.o

# Auto-generated Python scripts for multiprocessing
*_nb.py


================================================
FILE: LICENSE.md
================================================
                    GNU GENERAL PUBLIC LICENSE
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================================================
FILE: README.md
================================================
## Overview

We share PyTorch and C code that produced our results in Kang L, Toyoizumi T. "Distinguishing examples while building concepts in hippocampal and artificial networks." *Nat Commun* 15, 647 (2024). [doi:10.1038/s41467-024-44877-0](https://doi.org/10.1038/s41467-024-44877-0).

<!--
> This GitHub repository contains code used for the manuscript. See our corresponding [Google Drive respository](https://drive.google.com/drive/folders/1TF9FIyp5DXVFqlpFIC_PlJckuJgUu9mK?usp=sharing) for large data files used for the manuscript, which must be placed in a `data` directory within the GitHub repository root.
-->

Our PyTorch code has been tested on a machine running Ubuntu 20.04 Linux with NVIDIA V100 GPUs. Our C code has been tested on machines running macOS 13 or Ubuntu 20.04 Linux with Intel CPUs.

## `hippocampus` and `ml` directories

Code concerning the biological model of hippocampal pathways to CA3 and autoassociation in CA3 (Figs. 1–3) is provided in the `hippocampus` directory. Code concerning the application of CA3-like encodings towards machine learning with the DeCorr and HalfCorr loss functions (Fig. 7) is provided in the `ml` directory. 

Further documentation is included in README files in each directory.


================================================
FILE: hippocampus/1_pathways.ipynb
================================================
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a9150c98-b2e6-42bb-b5d8-962e7e92d5cf",
   "metadata": {},
   "source": [
    "# General setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c996cc0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys\n",
    "import time\n",
    "import itertools\n",
    "\n",
    "import numpy as np\n",
    "from scipy.sparse import csr_matrix\n",
    "import matplotlib.pyplot as plt\n",
    "import h5py\n",
    "\n",
    "import torch\n",
    "from torch import nn\n",
    "import torch.nn.functional as F\n",
    "from torch.utils.data import Dataset, DataLoader, Subset\n",
    "from torchvision import datasets\n",
    "from torchvision.transforms import ToTensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6b7e303b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cuda device\n"
     ]
    }
   ],
   "source": [
    "device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
    "print(f\"Using {device} device\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7eed2152-e9e0-4b07-9c7b-074b6ba0bff6",
   "metadata": {},
   "source": [
    "# Basic utilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bf390b6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_time = None\n",
    "\n",
    "def start_timer():\n",
    "    global start_time\n",
    "    if device == 'cuda':\n",
    "        torch.cuda.synchronize()\n",
    "    start_time = time.time()\n",
    "\n",
    "def end_timer_and_print():\n",
    "    if device == 'cuda':\n",
    "        torch.cuda.synchronize()\n",
    "    end_time = time.time()\n",
    "    print(\"\\nTotal execution time {:.3f} sec\".format(end_time - start_time))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2d41efec-4a43-4bb3-a4f5-23f1bb886783",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_images(img_list, num=6, size=12):\n",
    "    if isinstance(img_list, tuple):\n",
    "        img_list = list(img_list)\n",
    "    elif isinstance(img_list, (np.ndarray, torch.Tensor)):\n",
    "        img_list = [img_list]\n",
    "    else:\n",
    "        raise Exception(\"input must be ndarray or sequence or list of ndarrays\")\n",
    "        \n",
    "    for i in range(len(img_list)):\n",
    "        if isinstance(img_list[i], torch.Tensor):\n",
    "            img_list[i] = img_list[i].cpu().numpy()\n",
    "            \n",
    "        depth = img_list[i].ndim\n",
    "        if depth == 4:\n",
    "            continue\n",
    "        elif depth == 3:\n",
    "            img_list[i] = np.expand_dims(img_list[i], 0)\n",
    "        elif depth == 2:\n",
    "            img_list[i] = np.expand_dims(img_list[i], (0,1))\n",
    "        else:\n",
    "            raise Exception(\"image arrays must have depth between 2 and 4, inclusive\")\n",
    "            \n",
    "    lengths = [imgs.shape[0] for imgs in img_list]\n",
    "    if lengths.count(lengths[0]) != len(lengths):\n",
    "        raise Exception(\"image arrays must have the same first dimension size\")\n",
    "    if num == -1 or num > lengths[0]:\n",
    "        num = lengths[0]\n",
    "    num_list = len(img_list)\n",
    "    \n",
    "    if num == 1:\n",
    "        plt.figure(figsize=(size, size/num_list))\n",
    "        for i, img in enumerate(img_list):\n",
    "            plt.subplot(1, num_list, i+1)\n",
    "            plt.imshow(img[0, 0], cmap='gray_r')\n",
    "            plt.axis('off')\n",
    "    else:\n",
    "        plt.figure(figsize=(size, size*num_list/num))\n",
    "        for i, imgs in enumerate(img_list):\n",
    "            for j, img in enumerate(imgs):\n",
    "                if j >= num: break\n",
    "                plt.subplot(num_list, num, num*i+j+1)\n",
    "                plt.imshow(img[0], cmap='gray_r')\n",
    "                plt.axis('off')\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "15917c02-9646-48b7-8e95-5b4cf5ce9039",
   "metadata": {},
   "outputs": [],
   "source": [
    "def pearson_correlation(x, y):\n",
    "    if x.shape != y.shape:\n",
    "        raise Exception(\"Arguments must have same shape\")\n",
    "    x = x - x.mean(-1, keepdim=True)\n",
    "    y = y - y.mean(-1, keepdim=True)\n",
    "    \n",
    "    return ( torch.sum(x * y, -1)\n",
    "             * torch.rsqrt(torch.sum(x**2, -1) * torch.sum(y**2, -1)) )\n",
    "\n",
    "def pairwise_correlation(first_tensor, second_tensor=None):\n",
    "    first_tensor = torch.as_tensor(first_tensor, dtype=torch.float, device=device)\n",
    "    if second_tensor is None:\n",
    "        second_tensor = first_tensor\n",
    "        replacement=False\n",
    "    else:\n",
    "        second_tensor = torch.as_tensor(second_tensor, dtype=torch.float, device=device)\n",
    "        replacement=True\n",
    "    if first_tensor.dim() != 2 or second_tensor.dim() != 2:\n",
    "        raise Exception(\"Arguments must be a 2D tensors\")\n",
    "    if first_tensor.shape != second_tensor.shape:\n",
    "        raise Exception(\"Arguments must have same shape\")\n",
    "        \n",
    "    inds_of_pairs = torch.combinations(torch.arange(len(first_tensor)), with_replacement=replacement)\n",
    "    max_inds = 50000\n",
    "    if len(inds_of_pairs) > max_inds:\n",
    "        inds_of_subsample = torch.multinomial(torch.ones(len(inds_of_pairs)), max_inds)\n",
    "        inds_of_pairs = inds_of_pairs[inds_of_subsample]\n",
    "        \n",
    "    inds_of_pairs = inds_of_pairs.to(device)\n",
    "    first_vectors = first_tensor.index_select(0, inds_of_pairs[:,0])\n",
    "    second_vectors = second_tensor.index_select(0, inds_of_pairs[:,1])\n",
    "    \n",
    "    correlations = pearson_correlation(first_vectors, second_vectors)\n",
    "    # Deleting variables to free up memory\n",
    "    del first_tensor, second_tensor, first_vectors, second_vectors\n",
    "    if device == 'cuda':\n",
    "        torch.cuda.empty_cache()\n",
    "    return correlations.mean().item()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0af8ea58",
   "metadata": {},
   "source": [
    "# Loading images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9da31f01",
   "metadata": {},
   "outputs": [],
   "source": [
    "img_data = datasets.FashionMNIST(\n",
    "    root=\"../data\",\n",
    "    train=True,\n",
    "    download=True,\n",
    "    transform=ToTensor()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "73433879",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of batches:  12\n",
      "Shape of X [N, C, H, W]:  torch.Size([128, 1, 28, 28])\n",
      "Shape of y:  torch.Size([128]) torch.int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x72 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# coats, trousers, sneakers\n",
    "class_inds = [4, 1, 7]\n",
    "num_classes = len(class_inds)\n",
    "class_size = 512\n",
    "batch_size = 128\n",
    "\n",
    "inds_by_class = [torch.where(img_data.targets == class_idx)[0][:class_size] \n",
    "                       for class_idx in class_inds]\n",
    "data_inds = torch.flatten(torch.stack(inds_by_class).T)\n",
    "\n",
    "AE_dataloader = DataLoader(Subset(img_data, data_inds),\n",
    "                           batch_size=batch_size, shuffle=True)\n",
    "\n",
    "print(\"Number of batches: \", len(AE_dataloader))\n",
    "\n",
    "for X, y in AE_dataloader:\n",
    "    print(\"Shape of X [N, C, H, W]: \", X.shape)\n",
    "    print(\"Shape of y: \", y.shape, y.dtype)\n",
    "    break\n",
    "    \n",
    "plot_images(next(iter(AE_dataloader))[0], num=12)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5062785a",
   "metadata": {},
   "source": [
    "# From images to EC through autoencoder"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72208a58-5add-49e1-8851-f6566245d46b",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c1535844-2596-4626-b7a4-f6d8eb219d5c",
   "metadata": {},
   "outputs": [],
   "source": [
    "EC_size = 1024\n",
    "EC_sp = 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "09c489fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "def step(x, x0):\n",
    "    return (x > x0).float()\n",
    "\n",
    "# Straight-through estimator for binarization and backpropagation\n",
    "class STEFunction(torch.autograd.Function):\n",
    "    @staticmethod\n",
    "    def forward(ctx, x):\n",
    "        return step(x, 0.)\n",
    "\n",
    "    @staticmethod\n",
    "    def backward(ctx, grad_output):\n",
    "        return F.hardtanh(grad_output)\n",
    "\n",
    "# Binarization layer with gradients propagated backwards by STE\n",
    "class Binarize(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "\n",
    "    def forward(self, x):\n",
    "        return STEFunction.apply(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6dbb7559",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Middle binary layer represents EC\n",
    "class Autoencoder(nn.Module):\n",
    "    def __init__(self, hidden_size=128):\n",
    "        super().__init__()\n",
    "        self.hidden_size = hidden_size\n",
    "        \n",
    "        self.encoder = nn.Sequential(\n",
    "            nn.Flatten(),\n",
    "            nn.Linear(28*28, hidden_size),\n",
    "            nn.BatchNorm1d(hidden_size),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(hidden_size, EC_size),\n",
    "            nn.BatchNorm1d(EC_size),\n",
    "            Binarize()\n",
    "        )\n",
    "        self.decoder = nn.Sequential(\n",
    "            nn.Linear(EC_size, hidden_size),\n",
    "            nn.BatchNorm1d(hidden_size),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(hidden_size, 28*28),\n",
    "            nn.Sigmoid(),\n",
    "            nn.Unflatten(-1, (1, 28, 28))\n",
    "        )\n",
    "        \n",
    "    def forward(self, x):\n",
    "        features = self.encoder(x)\n",
    "        x = self.decoder(features)\n",
    "        return x, features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f3e9ff0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loss function that enforces layer sparsity to be sp\n",
    "class SparseLoss(nn.Module):\n",
    "    def __init__(self, sp):\n",
    "        super().__init__()\n",
    "        self.sp = sp\n",
    "\n",
    "    def forward(self, features):\n",
    "        sp_hat = features.mean(1)\n",
    "        kl_divergence = -self.sp * torch.log(sp_hat) - (1-self.sp) * torch.log(1-sp_hat)\n",
    "        return kl_divergence.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e9dfa737",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def AE_train(dataloader, model,\n",
    "             err_criterion, sparse_criterion, sparse_strength,\n",
    "             optimizer, num_epochs, print_epochs=5):\n",
    "    \n",
    "    size = len(dataloader.dataset)\n",
    "    \n",
    "    print(f\"TRAINING -----------------------\")\n",
    "    model.train()\n",
    "    \n",
    "    for t in range(num_epochs):\n",
    "        mean_err = 0.\n",
    "        mean_sparse_loss = 0.\n",
    "        mean_sp = 0.\n",
    "        \n",
    "        for X, _ in dataloader:\n",
    "            X = X.to(device)\n",
    "            pred, features = model(X)\n",
    "            \n",
    "            err = err_criterion(pred, X)\n",
    "            sparse_loss = sparse_criterion(features)\n",
    "            mean_err += err.item() * len(X)\n",
    "            mean_sparse_loss += sparse_loss.item() * len(X)\n",
    "            mean_sp += features.detach().mean().item() * len(X)\n",
    "\n",
    "            loss = err + sparse_strength * sparse_loss\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "            optimizer.zero_grad(set_to_none=True)\n",
    "\n",
    "        mean_err = (mean_err / size)**0.5\n",
    "        mean_sparse_loss /= size\n",
    "        mean_sp /= size\n",
    "        if (print_epochs > 0\n",
    "            and ((t+1) % print_epochs == 0 or t == 0)):\n",
    "            print(f\"{t:>3d}\"\n",
    "                  f\"   RMSE: {mean_err:>6f}\"\n",
    "                  f\"   sp loss: {mean_sparse_loss:>6f}\"\n",
    "                  f\"   sparsity: {mean_sp:>6f}\")\n",
    "        \n",
    "    print(f\"\\nEVALUATING ---------------------\")\n",
    "    model.eval()\n",
    "    \n",
    "    mean_err = 0.\n",
    "    mean_sp = 0.\n",
    "    \n",
    "    X_list = []\n",
    "    y_list = []\n",
    "    pred_list = []\n",
    "    features_list = []\n",
    "    \n",
    "    with torch.no_grad():\n",
    "        for X, y in dataloader:\n",
    "            X, y = X.to(device), y.to(device)\n",
    "            pred, features = model(X)\n",
    "            \n",
    "            err = err_criterion(pred, X)\n",
    "            mean_err += err.item() * len(X)\n",
    "            mean_sp += features.detach().mean().item() * len(X)\n",
    "            \n",
    "            X_list.append(X.detach())\n",
    "            y_list.append(y.detach())\n",
    "            pred_list.append(pred.detach())\n",
    "            features_list.append(features.detach())\n",
    "            \n",
    "    mean_err = (mean_err / size)**0.5\n",
    "    mean_sp /= size\n",
    "    print(f\"RMSE: {mean_err:>5.4f}, sparsity: {mean_sp:>5.4f}\")\n",
    "    \n",
    "    return torch.cat(X_list), torch.cat(y_list), torch.cat(pred_list), torch.cat(features_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6bff088-5688-417c-a02c-c2132e0b791a",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "eb7bd2e7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autoencoder(\n",
      "  (encoder): Sequential(\n",
      "    (0): Flatten(start_dim=1, end_dim=-1)\n",
      "    (1): Linear(in_features=784, out_features=128, bias=True)\n",
      "    (2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "    (3): ReLU()\n",
      "    (4): Linear(in_features=128, out_features=1024, bias=True)\n",
      "    (5): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "    (6): Binarize()\n",
      "  )\n",
      "  (decoder): Sequential(\n",
      "    (0): Linear(in_features=1024, out_features=128, bias=True)\n",
      "    (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "    (2): ReLU()\n",
      "    (3): Linear(in_features=128, out_features=784, bias=True)\n",
      "    (4): Sigmoid()\n",
      "    (5): Unflatten(dim=-1, unflattened_size=(1, 28, 28))\n",
      "  )\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "AE_model = Autoencoder(hidden_size=128).to(device)\n",
    "print(AE_model)\n",
    "\n",
    "AE_criterion = nn.MSELoss(reduction='mean')\n",
    "sparse_criterion = SparseLoss(EC_sp)\n",
    "sparse_strength = 1\n",
    "\n",
    "AE_optimizer = torch.optim.Adam(AE_model.parameters(), lr=1e-3, weight_decay=1e-5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e1791447",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRAINING -----------------------\n",
      "  0   RMSE: 0.378512   sp loss: 0.684878   sparsity: 0.494619\n",
      "  4   RMSE: 0.178297   sp loss: 0.662436   sparsity: 0.480245\n",
      "  9   RMSE: 0.146092   sp loss: 0.626792   sparsity: 0.456149\n",
      " 14   RMSE: 0.131650   sp loss: 0.591926   sparsity: 0.431087\n",
      " 19   RMSE: 0.122876   sp loss: 0.556157   sparsity: 0.403680\n",
      " 24   RMSE: 0.116282   sp loss: 0.520992   sparsity: 0.374735\n",
      " 29   RMSE: 0.111021   sp loss: 0.485655   sparsity: 0.343352\n",
      " 34   RMSE: 0.106291   sp loss: 0.454223   sparsity: 0.312860\n",
      " 39   RMSE: 0.103967   sp loss: 0.423421   sparsity: 0.280257\n",
      " 44   RMSE: 0.102184   sp loss: 0.399215   sparsity: 0.251656\n",
      " 49   RMSE: 0.099856   sp loss: 0.376661   sparsity: 0.221720\n",
      " 54   RMSE: 0.097394   sp loss: 0.358593   sparsity: 0.194167\n",
      " 59   RMSE: 0.095532   sp loss: 0.347202   sparsity: 0.173417\n",
      " 64   RMSE: 0.095125   sp loss: 0.336368   sparsity: 0.149597\n",
      " 69   RMSE: 0.094613   sp loss: 0.331445   sparsity: 0.135012\n",
      " 74   RMSE: 0.092800   sp loss: 0.328929   sparsity: 0.125338\n",
      " 79   RMSE: 0.091522   sp loss: 0.326986   sparsity: 0.114805\n",
      " 84   RMSE: 0.090232   sp loss: 0.326327   sparsity: 0.108768\n",
      " 89   RMSE: 0.090927   sp loss: 0.326356   sparsity: 0.104328\n",
      " 94   RMSE: 0.089531   sp loss: 0.326073   sparsity: 0.105778\n",
      " 99   RMSE: 0.091478   sp loss: 0.326310   sparsity: 0.100140\n",
      "\n",
      "EVALUATING ---------------------\n",
      "RMSE: 0.0908, sparsity: 0.1051\n",
      "\n",
      "Total execution time 11.912 sec\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "num_epochs = 100\n",
    "start_timer()\n",
    "AE_X, AE_y, AE_pred, AE_features = AE_train(\n",
    "    AE_dataloader, AE_model, AE_criterion,\n",
    "    sparse_criterion, sparse_strength, AE_optimizer, num_epochs\n",
    ")\n",
    "end_timer_and_print()\n",
    "print(\"Done!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "672478eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "AE_inds_by_class = [torch.where(AE_y == class_idx)[0] for class_idx in class_inds]\n",
    "\n",
    "X_by_class = [AE_X.index_select(0, inds) for inds in AE_inds_by_class]\n",
    "pred_by_class = [AE_pred.index_select(0, inds) for inds in AE_inds_by_class]\n",
    "features_by_class = [AE_features.index_select(0, inds) for inds in AE_inds_by_class]\n",
    "\n",
    "for X, pred in zip(X_by_class, pred_by_class):\n",
    "    plot_images((X, pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e47cc4ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlations by class:\n",
      "[0.14004182815551758, 0.1108851358294487, 0.11416365206241608]\n",
      "Cross-correlations:\n",
      "[-0.0009373852517455816, -0.017022987827658653, -0.038788385689258575]\n"
     ]
    }
   ],
   "source": [
    "print(\"Correlations by class:\")\n",
    "print([pairwise_correlation(features) for features in features_by_class])\n",
    "\n",
    "print(\"Cross-correlations:\")\n",
    "print([pairwise_correlation(features_by_class[i], features_by_class[j])\n",
    "       for i, j in [(0,1), (0,2), (1,2)]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b16c7266-3eec-4fd2-b738-4616398750f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x144 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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cHC8tLeW2Zy198sknuX306NGiTzMfPcstuhdTiWtk7xpj6e1j6nPw1VdfFX3Ly8u5ffDgwaLvzJkzjed47733iuPz58/n9srKStH3xRdf5HYX6SGKbV9ZqQnedAEAKsKkCwBQESZdAICKbJu1ilgAALMMb7oAABVh0gUAqAiTLgBARZh0AQAqwqQLAFARJl0AgIr8DyCa1H/q+5TzAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x144 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x144 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_concepts = [X.mean(0) for X in X_by_class]\n",
    "X_shape = X_concepts[0].shape\n",
    "pred_concepts = [pred.mean(0) for pred in pred_by_class]\n",
    "\n",
    "def sparse_binarize(vector, sp):\n",
    "    return (vector >= vector.quantile(1-sp)).float()\n",
    "\n",
    "features_means = [sparse_binarize(features.mean(0), EC_sp) for features in features_by_class]\n",
    "\n",
    "AE_model.eval()\n",
    "with torch.no_grad():\n",
    "    features_concepts = [AE_model.decoder(features.unsqueeze(0)).squeeze(0)\n",
    "                         for features in features_means]\n",
    "    \n",
    "for X, pred, features in zip(X_concepts, pred_concepts, features_concepts):\n",
    "    plot_images((X, pred, features), size=6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "24755c03",
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save({\n",
    "    'model_state_dict': AE_model.state_dict(),\n",
    "    'class_inds': class_inds,\n",
    "    'X_by_class': X_by_class,\n",
    "    'pred_by_class': pred_by_class,\n",
    "    'features_by_class': features_by_class,\n",
    "    'X_concepts': X_concepts,\n",
    "    'pred_concepts': pred_concepts,\n",
    "    'features_concepts': features_concepts\n",
    "}, f\"out/pathways/AE.pt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "921131d8-c0e7-4c57-983f-db14ce3818c0",
   "metadata": {},
   "source": [
    "# From EC to CA3 through random connectivity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aee9ba22-bd9c-4e39-b01f-f27b188d073e",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "939f2e94-9232-4844-9769-8875201e43e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of neurons\n",
      "EC: 1024,  DG: 8192,  CA3: 2048\n",
      "\n",
      "Number of inputs per postsynaptic neuron\n",
      "DG: 205,  PP: 205,  MF: 8\n",
      "\n",
      "Number of active neurons\n",
      "DG: 41,  PP: 410,  MF: 41\n"
     ]
    }
   ],
   "source": [
    "DG_size = EC_size * 8\n",
    "CA3_size = EC_size * 2\n",
    "\n",
    "print(f\"Number of neurons\")\n",
    "print(f\"EC: {EC_size},  DG: {DG_size},  CA3: {CA3_size}\")\n",
    "\n",
    "DG_conn = 0.2\n",
    "PP_conn = 0.2\n",
    "MF_conn = 0.001\n",
    "\n",
    "DG_per_post = round(DG_conn * EC_size)\n",
    "PP_per_post = round(PP_conn * EC_size)\n",
    "MF_per_post = round(MF_conn * DG_size)\n",
    "\n",
    "print(f\"\\nNumber of inputs per postsynaptic neuron\")\n",
    "print(f\"DG: {DG_per_post},  PP: {PP_per_post},  MF: {MF_per_post}\")\n",
    "\n",
    "DG_sp = 0.005\n",
    "PP_sp = 0.2\n",
    "MF_sp = 0.02\n",
    "\n",
    "DG_active = round(DG_sp * DG_size)\n",
    "PP_active = round(PP_sp * CA3_size)\n",
    "MF_active = round(MF_sp * CA3_size)\n",
    "\n",
    "print(f\"\\nNumber of active neurons\")\n",
    "print(f\"DG: {DG_active},  PP: {PP_active},  MF: {MF_active}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6ce9f2d4-f2e7-44a3-bf60-bdc2cb1d48cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Random connectivities stored as sparse matrices\n",
    "def create_synapses(pre_size, post_size, inputs_per_post):\n",
    "    data = np.ones(post_size * inputs_per_post, dtype=int)\n",
    "    indices = np.concatenate([np.random.choice(pre_size, inputs_per_post, replace=False)\n",
    "                              for _ in range(post_size)])\n",
    "    indptr = np.arange(post_size+1) * inputs_per_post\n",
    "    return csr_matrix((data, indices, indptr), shape=(post_size, pre_size))\n",
    "\n",
    "DG_synapses = create_synapses(EC_size, DG_size, DG_per_post)\n",
    "MF_synapses = create_synapses(DG_size, CA3_size, MF_per_post)\n",
    "PP_synapses = create_synapses(EC_size, CA3_size, PP_per_post)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "35f68cf8-36fd-42da-9ff4-438146430a3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# k-winners-take-all implicitly sets an activity threshold\n",
    "def kWTA(inputs, k):\n",
    "    tiebreaker = np.random.rand(inputs.size)\n",
    "    inds = np.lexsort((tiebreaker, inputs))\n",
    "    output = np.zeros_like(inputs)\n",
    "    np.put(output, inds[-k:], 1)\n",
    "    return output\n",
    "\n",
    "# Apply connectivity matrix then apply kWTA\n",
    "def feedforward_WTA(pre_patterns, synapses, post_active):\n",
    "    post_inputs = synapses.dot(pre_patterns.T).T\n",
    "    return np.apply_along_axis(kWTA, 1, post_inputs, k=post_active)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9c8037c-5b96-4158-97fd-7a566ebd6671",
   "metadata": {},
   "source": [
    "## Evaluation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "aa251217-a0b5-4ddb-83d6-55b563b29485",
   "metadata": {},
   "outputs": [],
   "source": [
    "EC_patterns = [features.cpu().numpy().astype(int)\n",
    "               for features in features_by_class]\n",
    "\n",
    "DG_patterns = [feedforward_WTA(patterns, DG_synapses, DG_active)\n",
    "               for patterns in EC_patterns]\n",
    "MF_patterns = [feedforward_WTA(patterns, MF_synapses, MF_active)\n",
    "               for patterns in DG_patterns]\n",
    "PP_patterns = [feedforward_WTA(patterns, PP_synapses, PP_active)\n",
    "               for patterns in EC_patterns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "cf09ae63-dcf7-45c0-964c-a1b852913463",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EC sparsity:\n",
      "[0.0920867919921875, 0.11387062072753906, 0.10946083068847656]\n",
      "\n",
      "DG sparsity:\n",
      "[0.0050048828125, 0.0050048828125, 0.0050048828125]\n",
      "\n",
      "MF sparsity:\n",
      "[0.02001953125, 0.02001953125, 0.02001953125]\n",
      "\n",
      "PP sparsity:\n",
      "[0.2001953125, 0.2001953125, 0.2001953125]\n"
     ]
    }
   ],
   "source": [
    "print(\"EC sparsity:\")\n",
    "print([patterns.mean() for patterns in EC_patterns])\n",
    "print(\"\\nDG sparsity:\")\n",
    "print([patterns.mean() for patterns in DG_patterns])\n",
    "print(\"\\nMF sparsity:\")\n",
    "print([patterns.mean() for patterns in MF_patterns])\n",
    "print(\"\\nPP sparsity:\")\n",
    "print([patterns.mean() for patterns in PP_patterns])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a61d6b4b-78d0-46a6-8cde-e4f3500c4e8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EC correlation:\n",
      "[0.14128278195858002, 0.10953570902347565, 0.1142825037240982]\n",
      "\n",
      "DG correlation:\n",
      "[0.0160285085439682, 0.011178869754076004, 0.009731627069413662]\n",
      "\n",
      "MF correlation:\n",
      "[0.008485962636768818, 0.0056800334714353085, 0.005038905888795853]\n",
      "\n",
      "PP correlation:\n",
      "[0.07799788564443588, 0.060584306716918945, 0.06145378574728966]\n"
     ]
    }
   ],
   "source": [
    "print(\"EC correlation:\")\n",
    "print([pairwise_correlation(patterns) for patterns in EC_patterns])\n",
    "print(\"\\nDG correlation:\")\n",
    "print([pairwise_correlation(patterns) for patterns in DG_patterns])\n",
    "print(\"\\nMF correlation:\")\n",
    "print([pairwise_correlation(patterns) for patterns in MF_patterns])\n",
    "print(\"\\nPP correlation:\")\n",
    "print([pairwise_correlation(patterns) for patterns in PP_patterns])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e38864aa-37b0-478d-97ca-e08e8d45c395",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "MF cross-correlation:\n",
      "[0.0002359234931645915, -0.0004186440201010555, -0.0006570757832378149]\n",
      "\n",
      "PP cross-correlation:\n",
      "[0.00026348436949774623, -0.006878686137497425, -0.01947462558746338]\n"
     ]
    }
   ],
   "source": [
    "print(\"\\nMF cross-correlation:\")\n",
    "print([pairwise_correlation(MF_patterns[i], MF_patterns[j])\n",
    "       for i, j in [(0,1), (0,2), (1,2)]])\n",
    "print(\"\\nPP cross-correlation:\")\n",
    "print([pairwise_correlation(PP_patterns[i], PP_patterns[j])\n",
    "       for i, j in [(0,1), (0,2), (1,2)]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7716b6d0-2f82-4b68-8c3b-6562ffa22996",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "category sparsity:\n",
      "[0.2001953125, 0.2001953125, 0.2001953125]\n"
     ]
    }
   ],
   "source": [
    "# PP concepts are represented by the most active neurons up to PP sparsity\n",
    "def category_WTA(patterns, num_active):\n",
    "    return kWTA(patterns.sum(0), k=num_active)\n",
    "\n",
    "cat_patterns = [category_WTA(patterns, PP_active) for patterns in PP_patterns]\n",
    "print(\"category sparsity:\")\n",
    "print([patterns.mean() for patterns in cat_patterns])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "66be66a5-0ede-4b75-8647-7da0b5e94cfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We save patterns as packed binary arrays\n",
    "def save_patterns_binary(pattern_list, file):\n",
    "    binfile = open(file, 'w')\n",
    "    for patterns in pattern_list:\n",
    "        bindata = np.packbits(patterns)\n",
    "        bindata.tofile(binfile)\n",
    "    binfile.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "dacacc31-0eb2-4702-8b8d-a5c02941b968",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "out/pathways/N2048-p3-s512-a02-2\n"
     ]
    }
   ],
   "source": [
    "# Directory name is used by the Hopfield simulation to recognize pattern statistics\n",
    "pattern_dir = f\"out/pathways/\" \\\n",
    "              f\"N{CA3_size}-p{num_classes}-s{class_size}\" \\\n",
    "              f\"-a{str(MF_sp).split('0.')[1]}-{str(PP_sp).split('0.')[1]}\"\n",
    "print(pattern_dir)\n",
    "if not os.path.exists(pattern_dir):\n",
    "    os.mkdir(pattern_dir)\n",
    "save_patterns_binary(MF_patterns, f\"{pattern_dir}/x_sparse.dat\")\n",
    "save_patterns_binary(PP_patterns, f\"{pattern_dir}/x_dense.dat\")\n",
    "save_patterns_binary(cat_patterns, f\"{pattern_dir}/x_cat.dat\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b9914c9-4726-4791-a13d-3aab99516fca",
   "metadata": {},
   "source": [
    "# From CA3 to EC through feedforward network "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22aff263-5086-40a0-9481-22d5192ae08b",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ec5ca33b-5713-432e-912d-0f51ff77e09f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of batches:  12\n",
      "Shape of X:  torch.Size([128, 2048]) torch.float32\n",
      "Shape of Y:  torch.Size([128, 1024]) torch.float32\n"
     ]
    }
   ],
   "source": [
    "sparse_patterns = torch.as_tensor(np.concatenate(MF_patterns), dtype=torch.float)\n",
    "dense_patterns = torch.as_tensor(np.concatenate(PP_patterns), dtype=torch.float)\n",
    "AE_features = torch.cat(features_by_class).cpu()\n",
    "\n",
    "class FeedforwardDataset(Dataset):\n",
    "    def __init__(self, X, Y, transform=None):\n",
    "        self.X = X\n",
    "        self.Y = Y\n",
    "        self.transform = transform\n",
    "        if len(X) != len(Y):\n",
    "            raise Exception(\"input and output patterns must have same length\")\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.X)\n",
    "        \n",
    "    def __getitem__(self, idx):\n",
    "        if torch.is_tensor(idx):\n",
    "            idx = idx.tolist()\n",
    "            \n",
    "        X_sample = self.X[idx]\n",
    "        Y_sample = self.Y[idx]\n",
    "        \n",
    "        if self.transform:\n",
    "            X_sample = self.transform(X_sample)\n",
    "            Y_sample = self.transform(Y_sample)\n",
    "        \n",
    "        return (X_sample, Y_sample)\n",
    "    \n",
    "sparse_data = FeedforwardDataset(sparse_patterns, AE_features)\n",
    "dense_data = FeedforwardDataset(dense_patterns, AE_features)\n",
    "\n",
    "batch_size = 128\n",
    "FF_dataloaders = (DataLoader(sparse_data, batch_size=batch_size, shuffle=True),\n",
    "                  DataLoader(dense_data, batch_size=batch_size, shuffle=True))\n",
    "\n",
    "print(\"Number of batches: \", len(FF_dataloaders[0]))\n",
    "\n",
    "for X, Y in FF_dataloaders[0]:\n",
    "    print(\"Shape of X: \", X.shape, X.dtype)\n",
    "    print(\"Shape of Y: \", Y.shape, Y.dtype)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f610557b-77c2-4671-81ed-545ec0506d41",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Feedforward(nn.Module):\n",
    "    def __init__(self, hidden_size=2*CA3_size):\n",
    "        super().__init__()\n",
    "        self.hidden_size = hidden_size\n",
    "        \n",
    "        self.feedforward = nn.Sequential(\n",
    "            nn.Linear(CA3_size, self.hidden_size),\n",
    "            nn.BatchNorm1d(self.hidden_size),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(self.hidden_size, EC_size),\n",
    "            nn.Sigmoid()\n",
    "        )\n",
    "        \n",
    "    def forward(self, x):\n",
    "        return self.feedforward(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "36769f7b-fbb0-4931-b2f1-9e9e9234a8ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "def FF_train(dataloaders, model, err_criterion, optimizer,\n",
    "             num_epochs, print_epochs=5):\n",
    "    \n",
    "    size = len(dataloaders[0].dataset)\n",
    "    \n",
    "    print(f\"TRAINING -----------------------\")\n",
    "    model.train()\n",
    "    \n",
    "    for t in range(num_epochs):\n",
    "        mean_loss = np.array([0., 0.], dtype=float)\n",
    "        mean_overlap = np.array([0., 0.], dtype=float)\n",
    "        mean_sparsity = np.array([0., 0.], dtype=float)\n",
    "    \n",
    "        for tt, dataloader in enumerate(dataloaders):\n",
    "            for X, Y in dataloader:\n",
    "                X, Y = X.to(device), Y.to(device)\n",
    "                output = model(X)\n",
    "\n",
    "                loss = err_criterion(Y, output)\n",
    "                mean_loss[tt] += loss.item() * len(Y)\n",
    "                # binarizing the outputs for EC representations\n",
    "                pred = step(output.detach(), 0.5)\n",
    "                with torch.no_grad():\n",
    "                    overlaps = (Y * pred).sum(1) / Y.sum(1)\n",
    "                    mean_overlap[tt] += overlaps.sum().item()\n",
    "                    sparsities = pred.mean(1)\n",
    "                    mean_sparsity[tt] += sparsities.sum().item()\n",
    "\n",
    "                loss.backward()\n",
    "                optimizer.step()\n",
    "                optimizer.zero_grad(set_to_none=True)\n",
    "        \n",
    "        mean_loss = (mean_loss / size)**0.5\n",
    "        mean_overlap = mean_overlap / size\n",
    "        mean_sparsity = mean_sparsity / size\n",
    "        if (print_epochs > 0\n",
    "            and ((t+1) % print_epochs == 0 or t == 0)):\n",
    "            print(f\"{t:>3d}\"\n",
    "                  f\"   RMSE: {mean_loss[0]:>5.4f} {mean_loss[1]:>5.4f}\"\n",
    "                  f\"   overlap: {mean_overlap[0]:>5.4f} {mean_overlap[1]:>5.4f}\"\n",
    "                  f\"   sparsity: {mean_sparsity[0]:>4.3f} {mean_sparsity[1]:>4.3f}\")\n",
    "\n",
    "    print(f\"\\nEVALUATING ---------------------\")\n",
    "    model.eval()\n",
    "\n",
    "    Y_list = [[], []]\n",
    "    pred_list = [[], []]\n",
    "    \n",
    "    mean_overlap = np.array([0., 0.], dtype=float)\n",
    "    mean_sparsity = np.array([0., 0.], dtype=float)\n",
    "    \n",
    "    with torch.no_grad():\n",
    "        for tt, dataloader in enumerate(dataloaders):\n",
    "            for X, Y in dataloader:\n",
    "                X, Y = X.to(device), Y.to(device)\n",
    "                output = model(X)\n",
    "                # binarizing the outputs for EC representations\n",
    "                pred = step(output.detach(), 0.5)\n",
    "\n",
    "                overlaps = (Y * pred).sum(1) / Y.sum(1)\n",
    "                mean_overlap[tt] += overlaps.sum().item()\n",
    "                sparsities = pred.mean(1)\n",
    "                mean_sparsity[tt] += sparsities.sum().item()\n",
    "        \n",
    "            Y_list[tt].append(Y.detach())\n",
    "            pred_list[tt].append(pred)   \n",
    "            \n",
    "    mean_overlap = mean_overlap / size\n",
    "    mean_sparsity = mean_sparsity / size\n",
    "    print(f\"overlap: {mean_overlap[0]:>5.4f} {mean_overlap[1]:>5.4f},  \", end='')\n",
    "    print(f\"sparsity: {mean_sparsity[0]:>4.3f} {mean_sparsity[1]:>4.3f}\")\n",
    "    \n",
    "    Y_list = [torch.cat(Y) for Y in Y_list]\n",
    "    pred_list = [torch.cat(pred) for pred in pred_list]\n",
    "\n",
    "    return Y_list, pred_list"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd9d0f67-ba73-4e5d-bfa7-e5fcd31e96e7",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "f35475ea-0d94-45ba-bfa1-e9e1014745fb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feedforward(\n",
      "  (feedforward): Sequential(\n",
      "    (0): Linear(in_features=2048, out_features=4096, bias=True)\n",
      "    (1): BatchNorm1d(4096, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "    (2): ReLU()\n",
      "    (3): Linear(in_features=4096, out_features=1024, bias=True)\n",
      "    (4): Sigmoid()\n",
      "  )\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "FF_model = Feedforward(hidden_size=2*CA3_size).to(device)\n",
    "print(FF_model)\n",
    "\n",
    "FF_criterion = nn.MSELoss(reduction='mean')\n",
    "FF_optimizer = torch.optim.Adam(FF_model.parameters(), lr=1e-4, weight_decay=1e-5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "76df9cdf-d1cc-4754-bfe3-18fdae346544",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRAINING -----------------------\n",
      "  0   RMSE: 0.3952 0.3056   overlap: 0.1088 0.0011   sparsity: 0.109 0.000\n",
      "  4   RMSE: 0.2799 0.2468   overlap: 0.0541 0.3246   sparsity: 0.006 0.038\n",
      "  9   RMSE: 0.2326 0.1992   overlap: 0.3339 0.6363   sparsity: 0.036 0.070\n",
      " 14   RMSE: 0.1911 0.1663   overlap: 0.6201 0.7950   sparsity: 0.066 0.085\n",
      " 19   RMSE: 0.1584 0.1405   overlap: 0.8020 0.8927   sparsity: 0.085 0.094\n",
      " 24   RMSE: 0.1328 0.1204   overlap: 0.9077 0.9468   sparsity: 0.096 0.100\n",
      " 29   RMSE: 0.1130 0.1043   overlap: 0.9613 0.9765   sparsity: 0.101 0.103\n",
      " 34   RMSE: 0.0975 0.0919   overlap: 0.9853 0.9898   sparsity: 0.104 0.104\n",
      " 39   RMSE: 0.0864 0.0817   overlap: 0.9941 0.9956   sparsity: 0.105 0.105\n",
      " 44   RMSE: 0.0780 0.0742   overlap: 0.9976 0.9979   sparsity: 0.105 0.105\n",
      " 49   RMSE: 0.0715 0.0685   overlap: 0.9990 0.9989   sparsity: 0.105 0.105\n",
      " 54   RMSE: 0.0663 0.0647   overlap: 0.9995 0.9994   sparsity: 0.105 0.105\n",
      " 59   RMSE: 0.0627 0.0607   overlap: 0.9997 0.9996   sparsity: 0.105 0.105\n",
      " 64   RMSE: 0.0602 0.0584   overlap: 0.9999 0.9998   sparsity: 0.105 0.105\n",
      " 69   RMSE: 0.0585 0.0625   overlap: 0.9999 0.9975   sparsity: 0.105 0.105\n",
      " 74   RMSE: 0.0569 0.0560   overlap: 0.9999 0.9999   sparsity: 0.105 0.105\n",
      " 79   RMSE: 0.0546 0.0534   overlap: 1.0000 0.9999   sparsity: 0.105 0.105\n",
      " 84   RMSE: 0.0539 0.0536   overlap: 1.0000 1.0000   sparsity: 0.105 0.105\n",
      " 89   RMSE: 0.0587 0.0649   overlap: 1.0000 0.9958   sparsity: 0.105 0.105\n",
      " 94   RMSE: 0.0532 0.0510   overlap: 1.0000 1.0000   sparsity: 0.105 0.105\n",
      " 99   RMSE: 0.0516 0.0510   overlap: 1.0000 1.0000   sparsity: 0.105 0.105\n",
      "\n",
      "EVALUATING ---------------------\n",
      "overlap: 0.9931 1.0000,  sparsity: 0.107 0.105\n",
      "\n",
      "Total execution time 7.975 sec\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "num_epochs = 100\n",
    "start_timer()\n",
    "FF_Y, FF_pred = FF_train(\n",
    "    FF_dataloaders, FF_model, FF_criterion, FF_optimizer, num_epochs\n",
    ")\n",
    "end_timer_and_print()\n",
    "print(\"Done!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "41ada376-0e70-4170-9b05-b6f6652c90c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save({\n",
    "    'model_state_dict': FF_model.state_dict()\n",
    "}, f\"out/pathways/FF.pt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d9e60062-1eac-4cc1-bcbf-b492bd681cd9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.2"
  },
  "toc-autonumbering": false,
  "toc-showcode": false,
  "toc-showmarkdowntxt": true
 },
 "nbformat": 4,
 "nbformat_minor": 5
}


================================================
FILE: hippocampus/2a_hopfield.sh
================================================
#!/bin/bash

# This sample script runs a Hopfield network simulation. Additional flags can
# be provided at the command line and are appended to the end of the command.

if [[ $# -lt 1 ]]; then
  echo "Usage: ./2a_hopfield.sh fileroot [-flag value ...]"
  exit 1
fi

src/search.o \
  -fileroot "out/$1" \
  -X_dir "out/pathways/N2048-p3-s512-a02-2" \
  -p 3 \
  -gamma 0.05 \
  -incomp 0. -inacc 0.01 -beta 100. \
  -n_cue 30 -T_sim 10 -T_rec 10 \
  -save_activity \
  "${@:2}"


================================================
FILE: hippocampus/2b_sweep.sh
================================================
#!/bin/bash

if [[ $# -lt 1 ]]; then
  echo "Usage: ./2b_sweep.sh s1 [s2 ...]"
  exit 1
fi

ss=${@:1}
cue_types=( "sparse" "dense" "both" )
target_types=( "sparse" "category" )

args=()

for cue in "${cue_types[@]}"; do
  for target in "${target_types[@]}"; do

    root="${cue:0:1}${target:0:1}"

    case "$target" in
      "sparse"   ) theta=0.5 ;;
      "category" ) theta=0.0 ;;
    esac

  for s in ${ss[@]}; do

      arg="./2a_hopfield.sh sweep/$root-s$s -s $s"
      arg+=" -${cue}_cue -${target}_target -theta $theta"
      arg+=" -no_search -no_shuffle"
      args+=("$arg")

    done

  done
done

if [[ $(uname -s) == "Darwin" ]]
then
  ncores=$(sysctl -n hw.physicalcpu)
else
  ncores=$(nproc)
fi

echo
parallel --dry-run ::: "${args[@]}"
echo
echo -n "run simulations (y/n)? "
read a;
if [[ "$a" == "y" ]]; then
  parallel --ungroup -j "$ncores" ::: "${args[@]}"
fi



================================================
FILE: hippocampus/2c_oscillation.sh
================================================
#!/bin/bash

if [[ $# -ne 0 ]]; then
  echo "Usage: ./$0"
  exit 1
fi

src/dynamics.o \
  -fileroot "out/oscillation/baseline" \
  -X_dir "out/pathways/N2048-p3-s512-a02-2" \
  -p 3 -s 50 \
  -gamma 0.05 \
  -square -theta_range 0.6 0.2 20 \
  -incomp 0. -inacc 0.01 -beta 100 \
  -n_cue 30 -T_sim 120 -T_rec -2 \
  -save_activity


================================================
FILE: hippocampus/3_visualization.ipynb
================================================
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4ca42b76-e8a3-4d6e-bbf2-9f00fe3081d6",
   "metadata": {},
   "source": [
    "# General setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "038dd237-255d-4243-ba05-d2a10e0e6d22",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys\n",
    "import time\n",
    "import re\n",
    "from glob import glob\n",
    "import itertools\n",
    "\n",
    "import numpy as np\n",
    "from scipy.sparse import csr_matrix\n",
    "import matplotlib.pyplot as plt\n",
    "import h5py\n",
    "import csv\n",
    "\n",
    "import torch\n",
    "from torch import nn\n",
    "import torch.nn.functional as F\n",
    "from torch.utils.data import Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3797ead0-74bf-4579-9e39-520f8f017f7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cuda device\n"
     ]
    }
   ],
   "source": [
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
    "print(f\"Using {device} device\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fae8c65-e95e-4e0c-9977-d59a04bc7832",
   "metadata": {},
   "source": [
    "# Basic utilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "992ab758-c454-4bcf-840c-f774e9ee3fc6",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_time = None\n",
    "\n",
    "def start_timer():\n",
    "    global start_time\n",
    "    if device == 'cuda':\n",
    "        torch.cuda.synchronize()\n",
    "    start_time = time.time()\n",
    "\n",
    "def end_timer_and_print():\n",
    "    if device == 'cuda':\n",
    "        torch.cuda.synchronize()\n",
    "    end_time = time.time()\n",
    "    print(\"\\nTotal execution time {:.3f} sec\".format(end_time - start_time))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "68a9492d-9f3a-4e38-9d64-0f3c9e313302",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_images(img_list, num=6, size=12):\n",
    "    if isinstance(img_list, tuple):\n",
    "        img_list = list(img_list)\n",
    "    elif isinstance(img_list, (np.ndarray, torch.Tensor)):\n",
    "        img_list = [img_list]\n",
    "    else:\n",
    "        raise Exception(\"input must be ndarray or sequence or list of ndarrays\")\n",
    "        \n",
    "    for i in range(len(img_list)):\n",
    "        if isinstance(img_list[i], torch.Tensor):\n",
    "            img_list[i] = img_list[i].cpu().numpy()\n",
    "            \n",
    "        depth = img_list[i].ndim\n",
    "        if depth == 4:\n",
    "            continue\n",
    "        elif depth == 3:\n",
    "            img_list[i] = np.expand_dims(img_list[i], 0)\n",
    "        elif depth == 2:\n",
    "            img_list[i] = np.expand_dims(img_list[i], (0,1))\n",
    "        else:\n",
    "            raise Exception(\"image arrays must have depth between 2 and 4, inclusive\")\n",
    "            \n",
    "    lengths = [imgs.shape[0] for imgs in img_list]\n",
    "    if lengths.count(lengths[0]) != len(lengths):\n",
    "        raise Exception(\"image arrays must have the same first dimension size\")\n",
    "    if num == -1 or num > lengths[0]:\n",
    "        num = lengths[0]\n",
    "    num_list = len(img_list)\n",
    "    \n",
    "    if num == 1:\n",
    "        plt.figure(figsize=(size, size/num_list))\n",
    "        for i, img in enumerate(img_list):\n",
    "            plt.subplot(1, num_list, i+1)\n",
    "            plt.imshow(img[0, 0], cmap='gray_r')\n",
    "            plt.axis('off')\n",
    "    else:\n",
    "        plt.figure(figsize=(size, size*num_list/num))\n",
    "        for i, imgs in enumerate(img_list):\n",
    "            for j, img in enumerate(imgs):\n",
    "                if j >= num: break\n",
    "                plt.subplot(num_list, num, num*i+j+1)\n",
    "                plt.imshow(img[0], cmap='gray_r')\n",
    "                plt.axis('off')\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87e1dd35-29cf-4e92-9d58-7191c858057a",
   "metadata": {},
   "source": [
    "# Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc5d6980-5c80-4402-ba25-0e0aaf7d960d",
   "metadata": {},
   "source": [
    "## Defining models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cb1cb390-fad6-4a50-aa50-c58d33f6339d",
   "metadata": {},
   "outputs": [],
   "source": [
    "CA3_size = 2048\n",
    "EC_size = 1024\n",
    "sparse_sp = 0.02\n",
    "dense_sp = 0.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "674655d2-da23-436d-ad81-a6797f2671c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def step(x, x0):\n",
    "    return (x > x0).float()\n",
    "\n",
    "class STEFunction(torch.autograd.Function):\n",
    "    @staticmethod\n",
    "    def forward(ctx, x):\n",
    "        return step(x, 0.)\n",
    "\n",
    "    @staticmethod\n",
    "    def backward(ctx, grad_output):\n",
    "        return F.hardtanh(grad_output)\n",
    "\n",
    "class Binarize(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "\n",
    "    def forward(self, x):\n",
    "        return STEFunction.apply(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "040c9625-20d3-453b-8337-5d2daec94bd6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Autoencoder between images and EC\n",
    "class Autoencoder(nn.Module):\n",
    "    def __init__(self, hidden_size=128):\n",
    "        super().__init__()\n",
    "        self.hidden_size = hidden_size\n",
    "        \n",
    "        self.encoder = nn.Sequential(\n",
    "            nn.Flatten(),\n",
    "            nn.Linear(28*28, hidden_size),\n",
    "            nn.BatchNorm1d(hidden_size),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(hidden_size, EC_size),\n",
    "            nn.BatchNorm1d(EC_size),\n",
    "            Binarize()\n",
    "        )\n",
    "        self.decoder = nn.Sequential(\n",
    "            nn.Linear(EC_size, hidden_size),\n",
    "            nn.BatchNorm1d(hidden_size),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(hidden_size, 28*28),\n",
    "            nn.Sigmoid(),\n",
    "            nn.Unflatten(-1, (1, 28, 28))\n",
    "        )\n",
    "        \n",
    "    def forward(self, x):\n",
    "        features = self.encoder(x)\n",
    "        x = self.decoder(features)\n",
    "        return x, features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "771966ad-30c9-44f8-814c-87bab99a6f56",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feedforward visualization pathway from MF and PP patterns to EC\n",
    "class Feedforward(nn.Module):\n",
    "    def __init__(self, hidden_size=2*CA3_size):\n",
    "        super().__init__()\n",
    "        self.hidden_size = hidden_size\n",
    "        \n",
    "        self.feedforward = nn.Sequential(\n",
    "            nn.Linear(CA3_size, self.hidden_size),\n",
    "            nn.BatchNorm1d(self.hidden_size),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(self.hidden_size, EC_size),\n",
    "            nn.Sigmoid()\n",
    "        )\n",
    "        \n",
    "    def forward(self, x):\n",
    "        return self.feedforward(x)\n",
    "\n",
    "class FeedforwardDataset(Dataset):\n",
    "    def __init__(self, X, Y, transform=None):\n",
    "        self.X = X\n",
    "        self.Y = Y\n",
    "        self.transform = transform\n",
    "        if len(X) != len(Y):\n",
    "            raise Exception(\"input and output patterns must have same length\")\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.X)\n",
    "        \n",
    "    def __getitem__(self, idx):\n",
    "        if torch.is_tensor(idx):\n",
    "            idx = idx.tolist()\n",
    "            \n",
    "        X_sample = self.X[idx]\n",
    "        Y_sample = self.Y[idx]\n",
    "        \n",
    "        if self.transform:\n",
    "            X_sample = self.transform(X_sample)\n",
    "            Y_sample = self.transform(Y_sample)\n",
    "        \n",
    "        return (X_sample, Y_sample)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "437d7a75-0c9d-4266-8a73-f4e27879ff2b",
   "metadata": {},
   "source": [
    "## Loading trained models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1eb9217e-287b-4fdd-a451-f19f31ea691a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AE_data = torch.load(f\"out/pathways/AE.pt\", map_location=torch.device(device))\n",
    "AE_model = Autoencoder(hidden_size=128).to(device)\n",
    "AE_model.load_state_dict(AE_data['model_state_dict'])\n",
    "\n",
    "true_imgs = torch.cat(AE_data['X_by_class'])\n",
    "true_categories = torch.stack(AE_data['X_concepts'])\n",
    "\n",
    "FF_data = torch.load(f\"out/pathways/FF.pt\", map_location=torch.device(device))\n",
    "FF_model = Feedforward(hidden_size=2*CA3_size).to(device)\n",
    "FF_model.load_state_dict(FF_data['model_state_dict'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "59770f67-d626-4c29-b363-3564b99c5bcc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x72 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 216x72 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_images(true_imgs, num=12)\n",
    "plot_images(true_categories, size=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "337a2e45-dec3-4386-9a1f-8e251a0bc2c9",
   "metadata": {},
   "source": [
    "## Loading Hopfield data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fec0af14-8408-4e13-a42b-ce163951176e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_binary_patterns(pattern_file, pattern_size=CA3_size):\n",
    "    binfile = open(pattern_file, 'rb')\n",
    "    bindata = np.fromfile(binfile, dtype=np.uint8)\n",
    "    binfile.close()\n",
    "    patterns = torch.as_tensor(np.unpackbits(bindata).reshape((-1, pattern_size)),\n",
    "                               dtype=torch.float)\n",
    "    return patterns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "42533d71-9f12-4579-b067-9d70a73d0e0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "pattern_dir = \"out/pathways/N2048-p3-s512-a02-2\"\n",
    "dense_patterns = read_binary_patterns(f\"{pattern_dir}/x_dense.dat\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "d2a75e33-4191-4f88-8b75-38f6fac35446",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_fileroots(dataset_dir):\n",
    "    files = sorted(glob(f\"{dataset_dir}/*_params.txt\"))\n",
    "    return [file.split('_params.txt')[0] for file in files]\n",
    "\n",
    "def get_params(fileroot):\n",
    "    params = {}\n",
    "    with open(f\"{fileroot}_params.txt\", 'r') as file:\n",
    "        reader = csv.reader(file, delimiter='=')\n",
    "        for line in reader:\n",
    "            if line:\n",
    "                params[line[0].strip()] = line[1].strip()\n",
    "    \n",
    "    return params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "23f1f238-fcf2-40fe-94b0-51c275133224",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Returns cue and target information\n",
    "def get_info(fileroot):\n",
    "    params = get_params(fileroot)\n",
    "    num_examples = params['s']\n",
    "    \n",
    "    pattern_dict = {'0': 'sparse', '1': 'dense', '2': 'cat', '3': 'both'}\n",
    "    cue_type = pattern_dict[params['cue_type']]\n",
    "    target_type = pattern_dict[params['target_type']]\n",
    "    \n",
    "    return (cue_type, target_type, num_examples)\n",
    "\n",
    "def get_category_ids(fileroot):\n",
    "    params = get_params(fileroot)\n",
    "    num_examples = int(params['s'])\n",
    "    cue_inds = np.genfromtxt(f\"{fileroot}_qcue.txt\", dtype='int')\n",
    "    \n",
    "    return cue_inds // num_examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2e3f03c6-cbe8-45ca-8251-250b29309cf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# True target images for each Hopfield network cue\n",
    "def get_target_images(fileroot):\n",
    "    params = get_params(fileroot)\n",
    "    num_categories = int(params['p'])\n",
    "    num_examples = int(params['s'])\n",
    "    max_examples = int(re.search('-s\\d+', params['X_dir']).group(0)[2:])\n",
    "    \n",
    "    cue_inds = np.genfromtxt(f\"{fileroot}_qcue.txt\", dtype='int')\n",
    "    mu_inds = np.genfromtxt(f\"{fileroot}_qmu.txt\", dtype='int')\n",
    "    nu_inds = np.genfromtxt(f\"{fileroot}_qnu.txt\", dtype='int')\n",
    "    \n",
    "    storage_inds = np.hstack([mu*max_examples + nu_inds for mu in mu_inds])\n",
    "    if 'target_type' in params and params['target_type'] == '2':\n",
    "        target_inds = cue_inds // num_examples\n",
    "        target_imgs = true_categories[target_inds]\n",
    "    else:\n",
    "        target_inds = storage_inds[cue_inds]\n",
    "        target_imgs = true_imgs[target_inds]\n",
    "    \n",
    "    return target_imgs.cpu().numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cae7a477-4591-4a91-bf3a-2e09423b2de0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read in classic overlaps\n",
    "def get_overlaps(fileroot):\n",
    "    overlaps = np.genfromtxt(f\"{fileroot}_mclassic.txt\")[:,-1]\n",
    "    \n",
    "    return overlaps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d00fafc6-f2c7-4b63-b558-2149192ad713",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Images encoded by the Hopfield network\n",
    "def get_hopfield_images(fileroot):\n",
    "    params = get_params(fileroot)\n",
    "    num_cues = int(params['n_cue'])\n",
    "    activities = read_binary_patterns(f\"{fileroot}_s.dat\")\n",
    "    \n",
    "    FF_model.eval()\n",
    "    AE_model.eval()\n",
    "    with torch.no_grad():\n",
    "        # Binarize FF outputs before presenting to AE\n",
    "        imgs = AE_model.decoder(step(FF_model(\n",
    "            activities.to(device)\n",
    "        ), 0.5))\n",
    "        imgs = imgs.view((num_cues, -1, *imgs.shape[-3:]))\n",
    "        \n",
    "    return imgs.cpu().numpy()\n",
    "\n",
    "# Images encoded by the Hopfield network with all neurons flipped from active and inactive.\n",
    "# The inversions of dense patterns can also be equivalent stable Hopfield states.\n",
    "def get_reversed_images(fileroot):\n",
    "    params = get_params(fileroot)\n",
    "    num_cues = int(params['n_cue'])\n",
    "    activities = read_binary_patterns(f\"{fileroot}_s.dat\")\n",
    "    \n",
    "    FF_model.eval()\n",
    "    AE_model.eval()\n",
    "    with torch.no_grad():\n",
    "        # Binarize FF outputs before presenting to AE\n",
    "        imgs = AE_model.decoder(step(FF_model(\n",
    "            1.-activities.to(device)\n",
    "        ), 0.5))\n",
    "        imgs = imgs.view((num_cues, -1, *imgs.shape[-3:]))\n",
    "        \n",
    "    return imgs.cpu().numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b28f6dad-8a0b-4c32-b64c-af09047b7a55",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get fileroots of simulations PP concept targets to also perform PP example analysis\n",
    "def get_dense_fileroots(dataset_dir):\n",
    "    files = sorted(glob(f\"{dataset_dir}/out/?c*_params.txt\"))\n",
    "    return [file.split('_params.txt')[0] for file in files]\n",
    "\n",
    "# Classic overlap\n",
    "def calculate_overlap(activity, pattern, sp, pattern_size=CA3_size):\n",
    "    overlap = np.dot(activity, pattern-sp)\n",
    "    overlap /= pattern_size * sp * (1.-sp)\n",
    "\n",
    "    return overlap\n",
    "\n",
    "# True PP example patterns\n",
    "pattern_dir = \"out/pathways/N2048-p3-s512-a02-2\"\n",
    "dense_patterns = read_binary_patterns(f\"{pattern_dir}/x_dense.dat\")\n",
    "\n",
    "# Overlaps with PP examples, which are retrieved at the same theta as PP concepts.\n",
    "def get_dense_overlaps(fileroot):\n",
    "    params = get_params(fileroot)\n",
    "    num_cues = int(params['n_cue'])\n",
    "    num_categories = int(params['p'])\n",
    "    num_examples = int(params['s'])\n",
    "    max_examples = int(re.search('-s\\d+', params['X_dir']).group(0)[2:])\n",
    "    \n",
    "    cue_inds = np.genfromtxt(f\"{fileroot}_qcue.txt\", dtype='int')\n",
    "    mu_inds = np.genfromtxt(f\"{fileroot}_qmu.txt\", dtype='int')\n",
    "    nu_inds = np.genfromtxt(f\"{fileroot}_qnu.txt\", dtype='int')\n",
    "    storage_inds = np.hstack([mu*max_examples + nu_inds for mu in mu_inds])\n",
    "    \n",
    "    activities = read_binary_patterns(f\"{fileroot}_s.dat\")\n",
    "    cue_storage_inds = np.repeat([storage_inds[idx] for idx in cue_inds],\n",
    "                                 len(activities) // num_cues) \n",
    "    \n",
    "    overlaps = [calculate_overlap(activity, dense_patterns[idx], dense_sp)\n",
    "                for activity, idx in zip(activities, cue_storage_inds)]\n",
    "    \n",
    "    overlaps = np.array(overlaps).reshape(num_cues, -1)[:,-1]\n",
    "    \n",
    "    return overlaps"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf4f9d20-7368-4a89-9f9f-4f3610c0451f",
   "metadata": {},
   "source": [
    "# Results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce4a4c11-4f21-4683-8498-855e093e8a5d",
   "metadata": {},
   "source": [
    "## Parameter sweep from `2b_sweep.sh`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "0749b124-360b-439d-b329-5be6906ff457",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_dir = 'sweep'\n",
    "fileroots = get_fileroots('out/'+dataset_dir)\n",
    "\n",
    "info = [get_info(root) for root in fileroots]\n",
    "category_ids = [get_category_ids(root) for root in fileroots]\n",
    "overlaps = [get_overlaps(root) for root in fileroots]\n",
    "target_imgs = [get_target_images(root) for root in fileroots]\n",
    "hopfield_imgs = [get_hopfield_images(root) for root in fileroots]\n",
    "reversed_imgs = [get_reversed_images(root) for root in fileroots]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "051bc810-ff95-4b83-8444-782fb4b7c20b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# While overlaps with PP concepts were computed and saved during the Hopfield simulations,\n",
    "# overlaps with PP examples are computed here.\n",
    "dense_info = [get_info(root) for root in fileroots]\n",
    "dense_overlaps = [get_dense_overlaps(root) for root in fileroots]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "60d7b213-3bc4-483b-9169-cf7f1425dd77",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving data for further analysis\n",
    "h5file = h5py.File(f'out/visualization/{dataset_dir}.h5', 'w')\n",
    "\n",
    "h5file.create_dataset(\"info\", data=info)\n",
    "h5file.create_dataset(\"category_ids\", data=category_ids)\n",
    "h5file.create_dataset(\"overlaps\", data=overlaps)\n",
    "h5file.create_dataset(\"target_imgs\",\n",
    "                      data=target_imgs, compression='gzip')\n",
    "h5file.create_dataset(\"hopfield_imgs\",\n",
    "                      data=hopfield_imgs, compression='gzip')\n",
    "h5file.create_dataset(\"reversed_imgs\",\n",
    "                      data=reversed_imgs, compression='gzip')\n",
    "\n",
    "h5file.create_dataset(\"dense_info\", data=dense_info)\n",
    "h5file.create_dataset(\"dense_overlaps\", data=dense_overlaps)\n",
    "\n",
    "h5file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "0cc7d216-467a-499e-8d69-9c6814c4f32d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('both', 'cat', '1')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'cat', '3')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'cat', '10')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'cat', '30')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'cat', '100')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'sparse', '1')\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'sparse', '3')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'sparse', '10')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'sparse', '30')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('both', 'sparse', '100')\n"
     ]
    },
    {
     "data": {
      "image/png": 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VamFnZwc7OzuwLAuhUGhgDEcZK84vZpylUgn/9V//hWeffRaJRGIiXpy2gX8PC5w0T3qM9TwblZ3o+43jb6TR1fgob2iaJrxe70CUQSaDwaAY14sXL0qxLBaLScRMvNbn80kxpl6vo16vwzAMhEKhgVaSYQJ1TganIeOgGYaBfr+PcDgsWFaxWEQ+n0cmk4FpmhI5aWVg9Efl4jXHpfFucILTm7oNSq/XQ7vdRrFYxN7eHj755BPcuHEDu7u7SKfTmJubQyaTwcLCAjKZjES80WgUL7/8MmZnZ0fy5aRGo4G7d++KAae8NHHsGe3SaAAQReVzbW1tIZ/PDyxuOY/hNU0TW1tbEuXr+2rcXX/OH2LfdAS2bePWrVuSzZyFH+e40aHqjA4YbDPighzbtnH37l3cvHkT9+7dQyKRwMsvv4wf/OAHAnXQwVL2hOnOgj0DD7H5zc1N2LYtgQ1wCkFFIhF0u12kUilEIhF0Oh3RiVgshkwmg3a7jVarhVarhVwuh8XFRTG654EXAKDZbGJrawvValV64Akl6MjfCcVp/dFzjF0PzPDG8TLMYThbMrXz1EaZRXfKMRgMPlIr4vV0RszrjrITY3NSPfkosHA4jHa7LREqDTEZ7na7+PLLL8WzaiHxOBrVYDCIWq0Gy7JEidhPqPsxneQUpnMQNGDOnly/349IJIKnn34a7733Hn74wx+iXC5L37EzotODwoiCkdcontw8uTNl0UaYA9dsNnH37l1cv34de3t7ODk5QbVaRTAYlOj31q1bIlOfz4eZmRn0ej2sra2NG0q5HyMRLn4gNqqjMLfn0pNKGzg6zlqtJo7gPES+Dg4O0G63BZMnjKLlCQDRaFQct1YkHXFWKhU0Gg3Ytj00c3Ljw01mwMNiqb4f5VetVtFut/H222/jv//7v1Gr1VAsFhEMBqUOsri4KJHn0dERjo+P0el0MDs7i2effXZsxuKM1jh39/b2AADZbBahUEgMBfvhKS/CVyxeU0+og8RRic1zPjhrFaP4Y1a8v78vET/l7waxcC5r2EC3jPb7fVmA5SycjqNh0bWOaql/7XYbtVpNdJ26EYlEkEqlkEqlHomUtf5qiGQUje1e0BFfp9NBu92G1+tFrVaTdJ3M8yG9Xi8uXLgAj8cjBpQdA1yKaJqmpLRM+3Rnw3miJKcx40CyMEf8aGZmBvfv38fGxoYUzHSkqzsXdHTDVTOT8sLfzkFy4kmMzO7fv4+33noLN2/ehG3bME0T7XZbIjW2/vB6nU4HR0dHSKVS+Pu///uJ5cT7sfPA6eV16stJpJVXR/88zrIsVCoVtNvtM0dFWjadTgelUkkKmywUakfHSELj3M4og/c3TVOw4fNAC6MyFmYn1WoVR0dHuHHjBra3t3H37l3s7u4iEAigWq1Kq9vy8jKefPJJRCIR1Go1fP3118jn84jFYnjmmWfw+OOPjzS6TmPFz9rtNk5OTuDxeHB8fCyF6WAwKD26hAqZRWoHS0MYjUZRqVTQ6XQe6ZM/a/TNrI2BmtYp5/NoQ6UzGn1cs9mUYj0/GwfFjDK0/J+6kMvlsLW1hcPDQ8zOziIcDgvUl06nsbGxIZkz5xeLySz2WZaFaDQqS6uH0UQr0ugNLMtCp9ORflsaUY3tMgrmwgN9La/XKx6Waa02IK1Wa+BhRglUC9E5APzc7/cjHA5LfyIAWTlXqVRQKBSktU03hzsjCX42qad3ToZhnzF7qFar+Oyzz/D+++/j9u3byOVywq/f7x/okQVOs4N6vY5SqYReryepJc+ZhEcubtFRq9tEBR4Wz3TkQSWmEnQ6HdTrdeFx2HOP4okTWDfPc34xGgIwADvoZdGMNHQ0xYhZz8WzklZWyocth3t7e/jyyy/xxRdf4IsvvpA+1Ha7jWAwKHqzv7+Pa9eu4datW1LsYgF5dXVVCqczMzMjeXEaLsqsXq8jHA4jm80iEonIvA+HwwiFQmK4DMMQo8tIl8XtaDSKer0uDu+8S7zpPAuFgjg7J1Spr0l4SH9Op8pxY9Zz1natUbrHVbV7e3v46quvcPfuXfR6PVy5cgW9Xg/5fB7ZbBZzc3PodrtSnORcpNzK5TKOjo5Qq9WQyWRw9erVkTyNhRcoMC6VpVXnpGPqrvHdTqeDcrmMhYUFxGIxGIZxerNvPC5xLKbr5XIZnU5HDCLTTJ43jj+ngDlowWAQkUhkYMkxMVwaiWAwiHQ6LX2dzufm5CMc4owAJuHLmfryuqZp4uTkBPfv38e///u/49atW/D5fAORHWVQrVal/a7f7w/8v7e3h0ajMXFa3+120Wq1JIImb5QRedaYmNMhOZvIKU/d2nVWogFhcROAyENH2lRkQkZsC9TjzucgbONseRtFznHSDpK6kM/ncXh4iM8//xz/8z//g9/97newbVta3FqtlkBb7DC5ffs27ty5I0HF3Nwc1tfXYds2KpUKstnswLLqcfzR+LdaLXQ6HczMzKDVagHAQHsmgxyfzycQAyEqZlTUC2ZXTuN23kiX59KI6nYsBlg0Ys4uGm10aX8mhRd0tqZ/aLfK5TK2t7dx//59bG5uYmdnB81mE6urq9J+d3R0hHw+L3uMhMNhLCwsIJFIIBAICBZ+cHCAzc1N5PN5LC4u4umnnx4JZY01upwglmWh0WigXC5L9BAKhWQhhGmaUijz+/1YX1/H6urqQCsTB5sTBYB4YhbQ6IFN0xzp9d1SBxoO4FRZQ6EQer3TfQVM00Sv18Pi4qI4Do356giJysVdyPQST70ayo0nvUDC2cvJidtsNtFoNLC1tYUPP/wQH3/8MSqVivRScnJx4nm9XpimKZCOjjL7/T4KhQKOj48xPz8/bjhlTBmNaRk6ja5zDvB7PgvHlkaiXC6LnM+yeohEmRNeIqwRj8cHHAT5o2zoIOn4g8EgGo2GRCONRmPAMI8jGlxmdsT36FhM08S1a9fwm9/8BkdHR3LtXq8nCznIu47UgYetiPz/+PgYjUYDlUoF8Xgczz333MiuHY0nc2xo4OPxuHTgUM/a7TbS6bS0IRqGIREj4aNutyswRyqVkmx2UgzcbRwty5JaD2FDwmPAoL5qJ6PnPWtBDNQ4jrq7YNR40kGy573T6aDZbGJnZweffvop3nvvPRwcHGBtbQ2rq6uyiOvevXu4du2azMF6vS597evr63jmmWfg9/tRr9dxcnKCvb09ZLNZNJtNyWDi8fhQvsbuMubxeIRhGs1oNAq/34+DgwOUy2WEw2HUajXxlox22MzMyQ883DoQABKJhIDrbNYOBoNSVBtGOjojn26tNCcnJ9ja2kKn00E6nZb9H6LRKEqlEo6Pj2XFDqusGlPWoL7TqA+Tl15koQ0PJ3e1WsUnn3yCBw8e4N69e7h//75EPblcDuFwWJSm2Wzi5ORkYEUYAOk39nhOt8qr1WrSGjeO6O3pOMkfedVLjvXk1ufrH/18TniBx58VYtBRayAQECeksWQAoswaFnHDpNmmOCkx4t7d3cX29jZyuRwKhQLu3r2LO3fuSKthLBaT8aJTYLbG/UUI+egskcZY966nUilks9mx6bMTV6fRjcfjMAxDVnBpgxUOh1GpVABAMON+vy/dQjry5fWcEeVZI11GlJynGvrS84vRrnb4+ns9ljS6kxANbi6Xk+6oo6Mj3Lx5Ez/72c9gWRaefPJJvPrqq1hcXEShUMCNGzewubmJS5cuSScKx6tUKqFYLOKdd97BE088IfLQizs8ntPNhHK53MjC9kija5qm7DbFdG5+fh7xeBy///3vpRhGwUYiEfEMHo9HUljuYuT3+6WNpVqtwjRNtFot7O7uotVqSbsZ+zNHDaqzlw7AQCRGY5TNZuHxeKQfsVqtIpfLwefzyT4DnJic0DoFYjQ4rLKvidVOKgOvAZy2aN27d0+w23g8jmQyiXQ6jd3dXeRyOXi9XqnS6qgNgEQoXCwBQFb3+P1+3Lt3Dz/4wQ9GDacQG8+1IaLz0xg2lUJ3Nuh+Xt3X3O12Zb3/KBmNIip8s9l8xFnpSJay1Y5IGyNGl+Q1n8+jXq9P7ABqtRp+8pOf4KuvvkK5XJa5yoiWmKnf70e73ZZ5zEItsVJmJlwwwnlN3lKplMzXer2OXC43Mn3WwYaGeLhijwsHEokEIpGILLsn/GcYhmRIlGUoFEIsFpNCt94HhfPA6WAnGUdGfSS9KpD2Qhtdt9qJhvK63dMtKXVwMYqfUqmEf/3Xf0U+n0coFEK9Xsf9+/eRzWbxwgsvYGFhAZcvX8be3h4+++wzFItFVKtV9Ho9ZLNZ5HI5JBIJVCoVaRdjVrmzs4NwOIz5+XkYhiHb1sbjcRwdHY0NgMYaXd6MhoQFr16vh4WFBUnN6TFpoAg9pFIpJBIJKZLRYBC3DYfDUvEjyB+Px0cWPnSfpFZwKiEVk5ugmKaJcDiMixcvYmFhAQCwtraGlZUV+P3+gYhFe1fgYcTgLN65EffqZVTT6XRgmiYODw8l/SiVSiKDcrkshorRPh0UDQ8b3Ov1ujgkAAPGxrZtfPXVV6OGcoAoF5IuGlIBOI78TblrHJdFLPJSLBbRaDQGlOUsUS4LQrwP55bGYxnd9no9cZTaKPj9fhiGIdkZnSvhrEno9ddfx69//Wtpo+JzsCDLFY46+uY2oSygRaNRiWKphBoj5rPy2ZiujiPnyjyey7539vtyMQIjMEbvtVpNsGf22nNDeMI7LDyexdCSGO0TR+/3+wPdE84sCoAYNT2/QqGQ1DPoiE5OTiSbHkcffvgh3n77belxZ+DFDbYqlQq+/PJLyQA4z8LhsLQ/cs5w+TKzQa7CLZfLMAwDiUQCqVQK4XBYHN0oGml0ySA9F/sOWZBKJpPi2ZkyEfNMJpMyQbkzFSdEp9MRGIFbPNLo6hRnGGlPSHJ6Y+KyGhsKh8OIRCLY2NiQ1I/FNu7FoJ0M8Gj70Dh4gb229Mr1eh3FYlHechAIBKSNCYAYV0YUdERa5qlUCrZti+MiL5Q3ABQKhVFDOfAMxDmdrTk6ctSkV6zxGgAEB+c5Gl5wVtknIT4jMUqd8tLR8l7O1kKnEhOW8Hq9qFQqaLVaE0fgfr8fmUxGDCuzNMqOCqkDCF1s1nLVzlGPMQsxHo8H0WgUS0tLWFtbO1N1XgdDfr9f9InRIg0ZWx0ZLLGDiM/DH0JsNJjnLaYxOOO+IZSfjrLpPBhsuGWR7D7ifDgLvLC8vIy//uu/BnAaPObzeVSrVVSrVZTLZamh7O/vDwRBhEu50MTr9WJhYUG6Fvx+v2wMxHmi34ZDhzGKxq5I48NHo1FZ0RWPx9Hr9RCJRKTqHwwGpYo6OzuLfv90306mPOwb5LGGYcieAcRVdYV61F4C7H4g6VRUg/OxWEx65sLhsKRRnOAUVDqdFgHzx2lgJ5lwXu/pcs+NjQ2kUilUKhWUSqWBXcyY5upeQUZReskyeWCvIKvKlKOuBgeDQTz22GNj+aNjYpSlC2nObgRndE95OHFTOlUAMv7OZ5uENNasHa4TxtCpta5281geo7Fp50Yr4+i5557DK6+8gs3NTezv76NUKg3AMdrZ8X9+Rn693tNXHHHzp0wmA8MwEA6HkUwmpf2I6f3c3JxkXuPkRNIFq0ajgWQyKZkPx9IpI0afjEBDoZA4l0ql8kj94CzE6+pCrdZNp+PTjkjPK/2cekzPYnTn5ubw9NNPy6q/5eVlXLx4EaZpolgsitPc399HLBaT1XrtdlvgIBbDuHUtedbdWGzNoxHu9/tju4hGjjAnEze0YdqUTqeFOVb8dITIbgSdnrIzgfhpt9uVyak3zGGKOKqQxqjCrbePRKPLdJ14sV57zshaY6e8lsbM9N+jJiMFvra2hsXFRdl3lj2YnU4H2WxWsLxutysFyEAggFqtJrIghqgNGB0dI2byGY1Gx/YGOse12WwOTHZmHm7RoJYH5e+UOaMmXRk/T/cCOwV4fiAQEGV1KqT+zPk5jRdhJhqiSdr9NjY28KMf/Uhe9VQoFFCpVCRiPjg4QLValUyQ1w4Gg0gmk5LGErOfm5tDOp2WwIL7jMTjcVFW3Us+ipxOj46KETYXa9CBc0UY03JGjd1uVyJeZqe1Wu2RTM9p/CYhZ3sXddo5RvqaWo/1b90bzmeZJGOhwaSj1P3IlEUgEECxWBRboOGaQCCAcDgsWbl2pnw+ks74CFGMorEtY/TwjUYDR0dHgmMUi0VJDQAMbEXIjW9YNNDRisZ42FJCgdIQjEtN2ff4yMN8cy89oNz4g4IgvlWv15FKpcQoOiulJG1k9bpxN9KOJBKJIBaLDSiIbduyqIHGpVarSfRrWdZAwYwOS3cYMHKnDH2+0w1NMpnMyHHUk51jpWECKptzC0XKzGl0+Zmz3Uc7pvNWvEmEf9yO03AHP9f31c/E7yaN3gzDwIsvvognn3xSUm3LslAoFFAul3Hz5k2USiUYhiEK6fWe7q63tLSEixcvIpVKSWal96yg7DhHOWe4vei4Ni2nUdKyovzYJ0x4gV0SHHvg4batnAfsdyYOrHH1SRyonl/kQ89h58IIyoJzyu36PF7LyQ32cCNGoAxu9LnJZFJ4ymQyYjR1wZbZtIbxmJnrRWJaRznHUqnUSN5GGt1QKCTes1QqYXt7G4eHh/B6vbh16xbW1tZEMUzTlJS12+0im81idnZWWp9qtZqk+BQ21zkzwuXk1sUTN2LPn06VnK1NwOmCgkKhIK1ojUYD7XYbjUZD+hJZjKHRpbci6TSSfA4jDU04V/WEQiFxQvqtw5ygLGawSMRBZgsSjaGGUDhRms3mxGkXo51KpSJKwefXz8cJpCe927U0PueMbiYljhvHH3iYumkD5YR7dI8u5a+NEqM49pBPSszGiHv3ej3E43HMz88jGAzilVdeER4pK+2wOf7slqGMKUd2MgCQQi/v9dJLLw3lS8uCz81rE+YzDEN2CWMWR8fMLR+Bh4UjYrnMujqdjhgUZ0/wpEQjr/H3YR0oJOfCCAYA5L/b7T6yr/IooiHVBlF3Nnk8HnlO/s9CIiEW7QBZJ3CuntNOg/If5zjHRroE5pkCsepJvJRKyUIR8FBhq9WqwAfcrCKVSsnCCsMwZL0+BZVOp+Uaw4jGjBVa3bzP4pnX68Xs7KzgcZyI4XAYs7OzWFlZwfr6ukQnLKZpvFArM1OOUZVJYtc6ddeGqNVqycThfSzLQrlcFuOqK6CcpBwDRusas+QknGSXMc0Td/FiEzx7M3VUqJWOc0ArPMdcGz9GBWeFF+gM2KLF4lC9XpeuAKdRJwSj9/8gL8S9+f2kERLwsBtgdnYWqVRKcMC9vT1sbW1he3sb/X5fNoWh0WQxltg9+6k5V7l8m+OXTCYBnCr04uIinn/++ZFRks7CnJg7HQzHicaAy70jkcjA5jPxeFyWB9OpABDIgcZlEjjGyR/3C2H3BvvgGfRoCAmAHKf1GMBAJqEjzkngBSecofnTc5Y4uHOuuvX9u7UnktygkqG8jfqSkQYNGSGGtbU1HB0dYXZ2VtZ6sw0jn8/D5/Nhe3tbWmsikYjs0zkzM4N6vS7Xy+fzYmiq1SpardbYl9DpDcadggAeGmxiy71eD4ZhIBKJiNNYWVnBysqKFDEikYh4MBb0dOrAgR/VvcDom8URnVLSWxM7ouftdruykkg3q9PgEaTXhlbzA5z9VT3MFJiSMgpnX6WzVYy8a69OzItOlD2ozmLbWdJSZgFcgaZbv/QSXPKhq/N6rFggYlqpHQXvNY4v7eRisRjm5+fx5JNP4o/+6I8GMD1dQHOuydfvjNNGUqfN/F9HZaNkpTMkYvNcmEEslxEwI04WeAjzEVZgoUt3FrDwpIuqepzGEceBRUPqA7Fv8q3nMbNhfU+2nTIyp75o5zlqHLVsaWx1dsTPnfrtdo5+fs49BnhuBngcje1e4O7tiUQCFy5cgGVZSCaT2NjYkHSLxk23hzz99NNStaXA2bLF6OzSpUsAIArPyIkGYRRfGmfUD6yNYiqVQiaTQb1el5Y08sc9aTm4esLrAdITgc83ivRGP7weuwwYCev78IeplIYoSM7Xp2g58LNxVW99PxoypkTcHnJYSumM7vWEXFpaknY1OumzRLp06sDDtDQQCCCVSuGJJ57AwcEBcrncgKLqFi7KVs+JUCiEK1eu4Pj4WLIzZz/vJERj6jSWel8DysOp5Foh9bnDlFM7n1H88bo6HW40Gjg4OBDIiJAgv+ceHbpnl21kXLRAKIQdN8yEztpvDTxcfEPZX7x4EbZt4+TkZCBw0Y5GQzUABBJ59tlnUSwW4fP5ZCXspIVabdidRpW/nbrmHEtn8OD87XbNcTTR24C1l2I0s7a2JssdA4GApAIcJKZ2TGFocKkwfFne7OysLLXTm5iPYp4Tx83gUrEYXRJS0MUM8tNsNmWHMe0BiatqHsYZW31/57Ea/9HYpDa6HFym8PpcZ6StsTFGxZPwp6/b7/fFcCSTScHXNS/O9IkdI/3+w1Yk/SZoPv9Z4QWtEEzFY7EYVlZWUCqVRGaUg8bfh12P0WmhUJCs46w9sOO+0wrpNLrDlJD883OnARknMz3veW4kEsGFCxfQ7XaxtLSEZDKJeDw+MJ5M3flGFi5aMgwD6XQavd7pnsyZTGYg0+ScmyQzcOoiA7Hl5WWUy2XX1yvpjNItm8pkMkin09J6OW5stJzceHYzls6x058757HzbzcYYpysxr6uhxEFB40FHirGrVu35P1LOmUmKM90hQLWm+IYhiGRNBWVGOM4wTqjRR1h6L/16jAWNzi4bgsEnNGum4ccx5PTuOmJNGwC8zttXEZdX/99VtyNETcj6+XlZRwcHMjCF1215Tl6D1YS25/m5uak7/EsHl/zBDzExAldzM7Oyp4CuneXzonbiBIPZBTKpebz8/OyW90kmYCmYWMwTKncot1JnnnUvdx40nOJP7FYDAsLC6jVagAevtWDMALhslQqJbUDypk6wj782dnZRyr5k5CO1FnH4XxhRryzszMAE7FVzdl2CkDemZhOpzE/Py+B2SSypXzceHNCBs5ruem6WzeOG/TgvMYwGmt0NWaqt0js9/sS4bDAwWO4tFa3JREyoAejx+VSY6bfkyw/HOZ5+MA6EuBS3GAwKJ0TdA40uvo5R91jUmXSERk/09dx8546Cna7j3YoTj4nVVqSLoRaloWNjQ1UKhUZAzpBjUlzzPR92Oi/tLQkrYTa8J6VmFKm02mEQiHMzc0JfMC0klAHU1c6bcqNPeGGYWBlZQWVSkWKqJNkA5omVfBh5zrH2G1en1VWzuOJX3N+9/t9qZ5rSKHf7w90DgGD8Ek6nRYHdx5ZaeI40sivrKzI3hCsWTCD1gV5Rrs6M06lUlheXkapVJI++0kdlHPstE66dTu56el5xv9bRbrE/2hsuZKMUVIkEsHS0tJAiwqFd+nSJdTrdXk/GtN8KoXf75dmbEZJuqF90shkVEQIPMSXiOfyubjCa1SKcFaF0FGtNv5uUfOo59GDrSEIjWnq4yfhVadzhmFgYWEBa2traLfbeOaZZ5DL5XB4eCiy190bVBjdvcAex5WVFXi9XtlaUr8me1Ii/6FQCJlMBo8//jgCgQDW1taQSqUG3k/F+aXnkzMl1cXRfD4vG5OcZ0w1jYpyef9hnzkj22+jzBpaAE6Nq2maiEajWFlZkdZM9up6PKcFNMIJXDhEaM3vP30r8M2bN9FoNFwd7CS86SwqnU7j8ccfR6PRwOXLl1GpVBCLxWRfB45jLBZDPB4XB8CgyDAMZDIZLC4u4vLly8hms1hcXBxotxxFwyAbp06Oc4TDMF59nNu4j6KR2sGX2LGlA3j4sjv+XlxclH5XAKII9HDcXEO3oLBTIZ/Pi5LoohVToGGkiyZOg6aNnt5TVAP0AOTdWuTJLcI8j6JoLEzz62yg1jwzguNqNH7Pz3XhQaf/miZVEK4dv3Lliuxs9sorr0iUVKlUEAgEpNjGH110oYHc2NjAK6+8ggcPHqBarWJ9fR0LCwsDb36dlLxeL5LJJB577DFpcXrqqafwJ3/yJyiVStjc3ESlUpGVVjMzM0gmk7JiknNmdnYWzz//PF588UVks1kUCgVsbGxgZmZmYPe4UeQ2znquaSfI4/X84BhqZ6CP09c7C+m2SI0Fsy1seXkZf/d3fydznZ0NvKcuQrFLRK8OffPNN3F4eIgrV64MQIoadx1FDAgSiQQuXryI73//++h2u/j+97+PeDyORqOB7e1taR1jq1oqlUI8HhcoEgAymQxeeuklvPDCC4hEIjg5OcFjjz2GVCo1tsuD5OYMneOkf+vz3MZJj72GCc8aEXtGHdxut/vf/Eaz2UShUMDBwQFOTk6QTCZx9epVMQJMDdgUzfYf7mUZDAaRSCQQi8Xk3VH7+/v4+uuvEY/Hsbi4iAsXLiCTyaDb7TLydZVsr9fruxlITii9Sc+9e/dwcnKCaDQqrzI3DAPvv/8+9vf3ceHCBTzxxBNYWloSpWTBiOQSWQ7ly6mAmj+9QsrlXNeUblTUra/1jQMZNhP7+hy2GtXrdcFlbduW19AzO+CG3QCk5U7vk8H0kKv66IgZPSk6E1+Mtrj/ca1Wk9cr5fN5tFotzM/PI5VKSQ+v1+uVZd+JREJeWkloiYGCw3AMHUfNlxzsGax2D3N8WjGdnz8iAJdMyOv1uvLVPyWZ61z9ubu7i88//xyLi4t47bXXBvq5aVBZm+E8cwYalmXh2rVr2N3dxfe+9z088cQT8tp4lU2daRwrlQq8Xq+sluQWmFxI1Ww2EY/HB7aTJFbPojrfLMOsma+OHze/ut1u3xmBal0hlKkhNB0MuRlUnucW9Dlp2BgCY4zulKY0pSlN6Q9L50fLpzSlKU1pSmemqdGd0pSmNKXvkKZGd0pTmtKUvkOaGt0pTWlKU/oOaWp0pzSlKU3pO6Sp0Z3SlKY0pe+Q/g/cxB2XhEdt5QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'cat', '1')\n"
     ]
    },
    {
     "data": {
      "image/png": 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3ai3TLwbdZfpFOykUCigWizJCWS6XBQdmRUOYgtfWOgtgoSL6NcgQWON0tbPg0pgRna+Z6rPJ9t577+Gzzz6D7/totVpot9sIggDZbFYUxnXd18oO3dBJWjoD1XirpkvTzOj77rvv4h//+AcymQxarRYuLi7kAIKGSJhd6r0Sm07imeYdFZZ4L7PBdDqNfD4vTTQAuH//Ph49eoRsNot+v49+vy+ltlaS6XQqJTf3qXHWdbwy+aWdHP+WJXs6ncZHH32Ev//977h7967QValUZK6SBsLDCOQZy9ckOZp4IIOlNjBtZPP5XMrPDz/8EB9//DGq1apULaVSSZw/My02PzjEv06OGh7SPCNfTJvQrxkcf/rpJ/zzn//Eixcv0Gq1hGbS+f3330ujy3EcBEGAKIpw7969lbzSdqYzdq33mle0U2L3v/nNb/DXv/4V9Xod/X5fEg+NB+vMVGeuhJBW0aWzRn1vypHVJ3DdcGd/4sGDB/jkk0/QaDTQ6/XQbrcX6OL1qPMMCkxaltF1W2UIbAgvkBAK1RQusxsyYT6fo1qtwnVdPH/+HDs7O4LP6BJbZzM0hjiOxQltQhdp0+McfK0ViM69WCxiPp/j559/liOkuizjCJXpkIjvrKOLfNKZAhUSgCiwWdYEQYDxeIzHjx8jm82KI6Py6xKGn+fv1nVMl/FLVyx0PoQFiDPH8dXxzFQqhefPn+Pw8HChaUrF1/iZziTMwzWr+MWldcB0HlqOk8kEu7u7AIBnz57JUXOOsRFaMuEh3RXfdC3LiLhP8z127J88eYI///nP+Prrr4WWyWQi5TL/cTY6DEMcHx+jUCjgj3/841paNA1a37WDIe7P4FMul4Vfd+/eRRRFglUSDtABz8Q1C4XCSrp0s03DaiZdDAA6MalUKkilUgt0DYdDwVBZgbLRZ+ruup7BbZMhcIPpBRKkDUJjibqcZImSzWYFGLdtG4VCAUEQiCLQAWlh8b5JToT3XhUINL6nIy6zTE4R8LSM53lSZtG5EdPSCrQJXby/6Qj5mtkXcSo2CKjcx8fHOD09he/78H0fQRBIs0vjWeQfm4+b0LSMX3pPehpCZ4qktdvtSoZI2Ia8oRy5V+rDpvzSPDLlqDvWpIWyHY1G6HQ6wguW1Vq/dJXBzNAcP1pGk5l0JDVtZrMZut0uvvnmG3z22Wd4/PgxTk5OJAtKp9ML90yn00in0+j1emi1WgjDED/++ONCM9Jcy5Ig8k2X99wfnaiurlg2ky8szzWvmJ1qvd9kaUetnS99gqlrDMrpdBqTyQQXFxfSe2HiMZ1ORWa0HzrbdfZ4G2UI3GB6QTNTY6rs5mUyGXG2ehwpCAIAVwpTLpfx1ltvyYkrGrV2BNycbuYk0aUbSybWS4hCZ1w8AFCv18XJlMtl3L9/X46UUqgUMJXRdV0Zz9mUX6TLdGg8yUXnz0iqx8Lq9Tru3LkjR6n1HnSZRQVeh1OuoovX4EhfFEXIZrMSybPZLCqVihhREATY29tDoVAQeeumpm68EOvdhC4ahdlLoDOlPDkGWCwW5eRjHMcoFovY39+H53kL/QFt/JZlSdDdRL/M19q5Uf+GwyHOz8/xn//8B3/605/w+PFjABAHog+YjEYjjEYjuWan05Hj6q9evcJgMIDneYl0mbCL1i/i1dwrHR4naIIgkEzf8zwcHBxIP0Y7cfJMT4Csk6OuCkmX6SdIJ+2MdPm+L3QFQYBGoyETPWaVyOuwwk6i6zbKcCNMV0ct4onMNGioZACdbblcFqHzvUKhIEdMmaUQtNYzswDWlvJmEKDT4nW0gGmUqVQKtVpNggT34Xke9vf3UavVYFnWwmEO7pN0hWGYWGppnpEulut0GjSIwWCA8/NzDIdDvPfee/LQnVQqJSeyeDyYpRbLQh7bpDNmMEniF+Vozh1aliXzr7w3qxOWpZQjMdparSZPRmMpz6yE1yRdSd3cVXTxOtSbTCYjyk7Ygzg8sXc+aaxcLgucxMBJvaAjToIYGLR15bWsCTMcDtHr9fDzzz/j888/x1dffYV+vy8P32HTU+Pc7XYbrVZL6NDTB+12G6enpwKdLFu6bNf2SP0kv/j8jji+wvvL5TLm8zmy2azwulAoYH9/H9VqVeRI7JW2TTr181LWyVEfgiLPs9ks8vk8MpmMNNABoFqtCl2sRLLZLOr1OiqVivgJJkHaTyTp122W4Vqny7JXp/aMUgCEuWEYSqYGQDIv/fnBYCDNIV3KEMdldruuu6yxJuB6vIsQAnEZvs/MkOWVnnjgHjirqGeFeQ/d1EvKjuhsSQOweIwWuHo2wKtXr/DTTz+h2WxiOp0iCAIRHunig4TOz8/R7/flwAZlwq48FUs/4GWVHIm/6myUdNLg9Dy1LmE17jcYDNDtduU6dN7EwwFIs3Rd03GZHHW1wdGdZrOJbrcrJR35SXzZsizBAjU8QXnwgTAcHVvXdGTQAxabjqwq2u22dLSfPHmCp0+fYjabIQgCDAYDcW681uXlpQQ0OhdWMJR9v98XZ7RscV/6BBkdJJ0xAw0DFPVZ8yifz8NxHGmK6qyPOkgsVc/6biJH0sQSmwkP6Wm32wjDEEEQvDaVMxwOBTfl7Dz1m6fTOHuvM9BfkwyBNU5XnzJjJKPS68YOhW5ZV6M9ZByzNJaovu9LY0YbM42dYHnS+BM/wyFkGiqdGxWS1yHjs9ksptMper2e7GM+n8v4Fk/D0FD18WUylcJbtahsutQmf2j4nU5HIiXHTNLpNAaDgTzSTp+8qlQqC6e/yHc+lo/GkIQjcS9ajgxCehCe0xCUJSdOCoWCwA3ZbBa5XE5Op9FIeQ+dJa1bDNaUYxzHMqnB6+pqBrgKehwPY1bHp2QVCgXJ1jUmyaCvmzFJ9GmnprH5OL56Kte///1vPHr0CF988QV830exWESxWMSLFy9wenqKOI7R6XSkWtD8yOfzolcM4ByJSqVS+OGHH/D73/9+JV3kF/WLUyukmTitnpUlVsrRTMoxk8lIVqz5zQDMHgKzxk3kSJ7pE5hadlzMCi8uLkTfRqORjEhquqijuifDe60aZbutMgQ2cLp6lIQCISHEcbUj5llrnsCq1WrwPA/z+RyZTGbhUY+cweM1mMInzQRSyBrDYinJCKMfikIj7fV6ACCPeKzVajKuxXleTRezQjqjTYIBswkd7VkuA0ChUBDe8Shru92G53kIggBnZ2eo1+vY398XGkul0oJy8VqkxyyjkvilJzJ0I5FNC57e42ENyiWOY9TrdSn12BTVDQ5iXDQ23QlPoovwjaaLPGL2zkYGD7sAELzv7t27GI/HMt7med6C/jCLZpBJGvLnGo/HODo6WqjgeKz97OxMMjbq/+XlJZrNJnq9HlKpFMbjsZTGzLDJr/F4jEKhsHA4Rfcevvvuu5V00R51xsasVusmKwF9iorHajm8z0SFWS8dE3WYctxU7/l3tF8mBsB11ZPL5ZBOp9Fut8WBZrNZjEYjlEolkTcbtcD1SUrqij4Npg8G/VpkCKxxunpulZkMT2/RWJhBELOcTqdyTp9NMT2/CUDAb2J2AOQBGNqRbEIXmcqmj57tc10XuVxOMh/P8wSHpBEzeDBbp6LxGqSLAk5yItw/y6DxeCwzorrb7ziOZGg8aMBHUPL6zExIOx0FnaTO2tY10fScrx75olPVzbRcLieZJysAOkBip+Q/+UVMmH+n+bWJfmm6qMjMZvh3HAuL41imYNiobbfbsCxr4TGAWg/odHTzcZ0jGQ6H+OGHH3BxcSED+xcXF+K8LcuS0hzAwmhTHMcy08lSvdfrIQiCheO3wHXXnNk4T2UtWxqm0kGd+qHtsVAoSCLBoJ7JZKQhGsexZL7MmHWCZer9JvYIXFfHPGjBBijpZ9U0n8+Rz+flObqVSkWe6cLDQqxI6WxpJ5v6idsoQ2CDh5gTE2KGQIZx8yxRWG4S12PWUSqVBHSmEbAEJcE6gpHZSYuOiwA3HTefjkU6SVc6nRackoB+pVLB5eWlOApmdAwmukTSxpq06DA0vxhYeCqKNNA58DPaUNgQ5DW0cunsWytP0mKmrPnF8pQ84wNufN+XB6fTSPgs29PTU8GxyA8dTClH/lsXpDRd3CsdgNYvln88Ckwesht/eXkp92KlQUNnJaR1bN2yLAvVahX37t1DqVRCp9PBxcWFwERxHEu2pstWjTGyCqAB8xtDGIz1Q12oF67r4v79+7+IX6Ycy+UyOp2O6FKxWEShUECj0UCz2ZQEhfqlsVHSpLPWdfql95tOp5HL5ZDJZATG4Km4UqkkD6UntFcoFLC7u4ujoyPRUa1fTLB0Jr0uCbqtMgTWOF1iPIyG3AyjDzvZZByxDmaPdHC9Xk8IYqlBIoHrc956g8SBli3iT9qw9VgH78/Mlg9tZtmSz+fheZ50d+kUSZceESNd5EESXeaIGfdCJ8IOe7lcFpiG2QCdiH5ilt6P3h/5pXmYFBA0zq0bCzRcGgozona7jX6/v+B0Pc9Du91GFEUiW7Orq/nFIJHEL93QI13a6PT0Ah/KzfKXMmMlQzyYGTflyFLZlGOSI2EWyO9b47Nd+RU3YRji5OQElUpFspzBYIDBYIB8Po92uy0Okc0h3pNGn8/nJXiRtlwuh48++ihRvzS/dIAnv3TvhM8GoBOk7muHpvVeX4tNbg39bEIXF/nOa/F52/w2Gdov9Ug/6lFXUxp+ohxJV5KfuK0yBNY4XeJ7dDZ8kpMpKApEC1+P6GisRr+vo5YW7DqjMOki8K+NS+NeutupH+TBRhCFrJtlOpqyIaO7+cuW4zgCqLMkYUOC0drzPDGGIAiklCZP9QQFwXsqoxYuAw8z1nXZrn5INTEuzS9+XmfDpgFyflrzk/yi89X0rJOjZVmS6RPfJ3bHDrOpX6SZwYKBgdAIMUodEKhfWnZJcqROEbIoFovyBYqklcdoCYuwb5BKpaTzTb3kXrVsiT3r4Mdvekjil24QUY4a56SesXoy+QVc6722U8pR672WXZIcHccRObIpPhgMXnvmBflO/aJj5p501s0pEy1H3UDktVbJ8bbKENjgiyl1Y0ljuvxn2zbOz89xdHSEs7OzhdNVzEI0nEDD1w9vYUOAsMU6J0K6OEtL5WOnlE7q/PwcL1++xMnJicwl6uc8UChUVFORdQec0w5JdBH/Ib7DQw9UpDi+Go85OzvDs2fPcHJyIk9nq9fraLVauLy8lIyYuBixYDaFOAIEXE8tJJXN5IeWI0fqaMCWZeH8/BzPnz/H8fGxNA7YkCQkoZWc8Ig+fMLxMfJinRxJF/mmIRrqDGcfW62W3IN80d/Rxn+ky5y84T3X0aWDNhu9hJxYNvPevI5umuqynN134uGkRScFvDYzqnX8MidGKD/y7Pz8HM+ePcPR0ZFAb5QRcV5g8aukiFPqCR4mBJvYo6aLvCAvee+LiwtpZNGhEsIsFAro9XpSSdGxUb+oExz5pJ9YheneVhkCG8zpmsTrrI/lQ7lcRrlclmfAsgHE0pSZCNNxYkm5XG5hbldHtKThdRMG4DgWl6aLM3c8P84yml/jA0DKemaVmUxGslQT30oazYrjeGESgJmvbs6lUikcHBzInlutFjzPQ7VaRSaTwbvvvotqtYogCHD37l35ZluWURzLIl/50Jl1uBuzilVytG0bQRCgUqlgMBggjmNporGEYkdZZ8AsUdnh1Zkxg2kSv5jJcG/agTAL4xeL8rkKxWJR8EBihaSPBsusgyODOuu17eTDETRqTmSwYUt9IDTEPfN6bOhRDxhwuSfif9QRJgi8Pve6jl/sFbDE1vxyXRfVahX1el2cBCcW2GMZjUbodrvwPO81e+SYmTkpkCRH6gSzWk4tUA+oP3t7ezg8PBQHxW8F1yceJ5OJ6Dz3wwkHQkikDVg9KnlbZQiscbr6OZb662vm87k8YBu4dnK6OWNirfl8XphJpWGXlIRTGNpBLFt6TljPEwIQgFs7E0ZL0wmw7GJHVTsS7oVKx0xp3ZSAPnSh4QFGWpY7+Xx+AediF5cncXZ2drC7u4tisShfQ82969la3WRI4hf3oA9IkC+M+gxgg8EAtm3Ls371iBn3aU4o0OCoH8wmkzJwypF0MdMFIF92yn1NJhMJ0OQHjZQnG+k8tLx0WcvqCLjOzpYtno4inqzhCQZePhBIVwt6NJKZGOVuwkTkD2k1m1nr+MWKkj9T56izLPO1DTBTZCDSY2Fm9qurBs3HZYv6rXFm7oXPwwUgcIOe6Sc/eH3aBJ2uDuwmpJmkX7dVhsAGjTQaNInXDGXEKZfLqNVqUk77vi/f3Pr222+LUbODSoJ5XQpXdyiTiKfhkBF0/rpBQLrq9bpkdkEQYGdnR7qa+klaHFMBFh2IdqAaH1zHL0Y/nZXQgZM/URSJs6UjvnPnjkxXFItFcTy8LwOSFjgVcxN+salCflFxmenW63WZk61UKqhWq6hUKjg8PJTSi888oNPV42zkgYnXr+IX6WKzjrRQDqSrWq3KjG65XJZA1Wg05LF7DGT687ozTbrW8QuAOHYNP1GupFfjp7wHD8foClEHbPMz/D2dWxJdml+U47ImWBAE8u3XPLIdBAF838fBwQHCMES/35eAzmSHFRNf68CZ5HRJF30DD2foisd1r75NemdnR4I6j5L7vo+9vT1xgJou8or8JHyxCV23UYbABg+8IaEkXMMAuqxlJ5mKTXyUqTxLeBqhHtEiE3XpkIQhMdKZdGlQmxGXo2McGSNdrnt1oIJdXR1IGOEIARAD1s54HV3knW4EaMFzWoEZOHA9v6wPbFDxWGZpp8YMIcmxabp0NsPPkzYGQU6i6Md0Uo7kGzvgwPWXHTKQEp75Jfwy9UsH53w+L0ZEekkPewPUH8qR/OI1+Pt1/OLvdaDTZbw2SNNg6bB09sZrmP9rKEV/PolfpEPzSzfMeE3aG/+G5a9lWQuVARMVZpXMWgEIv2hnSUvTBVwnKayKdHnO6QXuh/PXbL7pvXA6Sj/fQOvXr02GwJpvA9aenmk2mUWjZKnLEpHn39lws21bvtlVg/QUJInWgiWDVi2d0mu6SAMjIu/F0yjdbnfha4N4Tp9/rx0593VTupaVZ7yeFjB/x6FtYmnsBDOj1WWyLpt5Lx3F1/GLdJn8ohx1k7Pdbss8JWXO8p5KqRVOZ97kgab3pnSRX3wNXDXQ+AxYjttpDFE3zbR+mVnLJvzS8Jjej6ZbG6+WhZkA8GfTeenPaPqS6NL6ZfJLN3mo991uV+yRvFjFL+20/zfkCFyfVtPNTE4KmH6Ckz8MEmaGq2VA+ayi67bKENjgebra4egskozSToR4EUFmblJne2ZKrsuEmxqFppGfNenSuB8nEJbdQ2eCmi597XV08W+4by0AKrymi91SBiN+DrjGucwMwpTJJsv8vFk26QAWx7EcqfZ9f6FzzBI0SY6aX+toTKLL7Ezz/jRMMxjpB+GYGRf11rzfumWWljqI6n3rn/kZbZymnpm6a97vJvziezoYaufGzv0y/dJZIGkzndA6fefn9Z6WydHkgW5kUndYZXLiwtRR7fw2XbdNhsAG0wv6YuYTtsgALbQoihYOTwCQE1/8Ww1L6Pd1Y2gTo+C19KksM71nFsCIS+PjXK85CL6MLg0NbOro6Ag04K+dEgOXdmR6LMyEWeho9HumsictrVDmKTYd5YHrB+SY/DJp0sbEUvam/NIOe5kczWsCWJCbbdtyuES/p0tkU47r+KV1yCw9SU9ShsX/zc/S4DXfzc/eRI66EtI0a3s05RbH11NH2ulqvf+lcuSedHJj0qX5ohufunmlpyY0pEDZEkJKKuVvsww3+mJKbpxKrfFOMpklAOf9iOdw6oED0brs08uMjkmE8/dkBpWI96GysMHD8RDCHKlUSp6LoLFRTZdZbpDpmxir6WiBxW+xYKbILFLPAp+fn0tjUN9/mXPVxpUUYTW/yJdlpTgx1MFggFarhW63K+NDPK3DhzOTLq0HZtWxLkvSdDGgkDdaBxikx+Mxut2uPCmO/QJCI1oOGlYws8J1+sVrm3vQ8JOmUesHnZz+vYblyDs9u66vn4RTmiU1+cXrkzY9GtjpdORhTzyIwAe4a8eq+QVggXdJzs2ky7Is6YHo/oNOajiyRriKhxFGoxGKxeKCo9O6zWxX07VKjrdVhsAap2uWZHQQ5kOTAcD3fTQaDaRSKZRKJVQqFfi+jwcPHmA4HKJSqcgoCOEHrTy6qaMZlkQXN81mCbFQ0hXHMcrlsnz7gu/7MgP74MEDjMdjlMtl6ZYyk9eO12waJtGlnaSZ/QPXJ/IAyGMb2QRh1/mjjz5Ct9uF7/sL0d2ck9TlFl9vwi/SxS4wFZCTHLu7u3jvvfdQLpfRaDRQr9dRLpfxwQcfYDAYyLdGcPwPgIwg6ckAZsGbyJH8NscAgevnEZdKJezt7SGdvvpGjSAIUCgU8Pbbb+Ply5coFAqoVqsiS8uyXqNLyzGJX8tgHb5PHdAVi86elsFCfJ8/c+98bTqZVTxbViovs8coilCr1fD222+jVCrJvLrneXjnnXdwdnaGXC6HnZ0dOZZLfpE2XcqvSzZMKIF4P3Fmy7o+lVqr1XB4eIhCoSBfR1Uul/HgwQPMZjOUy+UFOQKQRht1QfuJVXTdVhkCgLUJZrNd27Vd27Vd/ztrc0R6u7Zru7Zru/7rtXW627Vd27Vdb3Btne52bdd2bdcbXFunu13btV3b9QbX1ulu13Zt13a9wbV1utu1Xdu1XW9w/Q/q+jd4FjGp3AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'cat', '3')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'cat', '10')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'cat', '30')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'cat', '100')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'sparse', '1')\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'sparse', '3')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'sparse', '10')\n"
     ]
    },
    {
     "data": {
      "image/png": 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XisYxp0VufnCC6U39JsXzPClM7e3t4U9/+hNu376N3d1dFAoFLC0toVgsYnl5GcViUSLeVCqFV155BYuLixN58ovEmL7RCdLJmXg6U3oaNeAM02URq9lsYjQ6K8jt7Ozgxo0bsgHlPGQuZm2EFhcXEY/Hpcoei8UQDofxL//yL3j77bdlnhn9ZzKZsbEmpYlB5BetEePX0aY2vEyLh8Mh7t+/jzt37uDhw4fIZrN45ZVXcPPmTXEedLCEbQjTUd/OI7fBYICtrS0Mh0MJbICzDCGZTMJ1XeTzeSSTSQwGA9GJdDqNYrGIfr+PXq+HXq+HcrmMlZUVMbp+umbSpA1BpqwZ+OhawXA4xMsvv4y3335bggnK2Qy6pmWafu81+TZbMrXz1EaZBT/KMRqNjs0Nf/NZtHGeluFNhRf04iPmF4/H0e/3JUKlISbDruvi3XffFc+q+z35PhrVaDSKZrMpis/GaHrrSWQK05wMvVuLrU9sObp+/Tp+97vf4Z/+6Z9Qq9Wk79jsVtCTwoiCKVoQT1pZOZbppbUR5sR1u13cv38fb7zxhjT+NxoNRKNRiX7v3r0rMg2Hw1hYWIDnedjY2Jg2lWPRVbfbxc7OjhTpAEghShfnGLVqz8/XtQKNRiPs7OygVqthfX194rxM409/hv8vLi4ilUqJgWch8caNG1K8zWazAl1dvHhxYjQzi+L6ZSIaIjAV13VdSYf7/T5+9atf4be//S2azSYqlQqi0ajUQVZWViTyLJVKUsBaXFzESy+9FJix+D0D1+7e3h4A4PDwELFYTAwFoSEASKVSktLHYjGp2XieJzpYLpfR7/elu4FrdVIa7ycvkpaRZZ3hytR7XnNdFzdu3MDPf/5z9Ho9+axt27h06dIHgjlMHkzHDjyzE6wBcY1RL1zXRTKZRD6fRz6ff279aP1lEPqBIl0z4mPhJBQKodlsiqci83zIUCiE1dVVWJYlBjQWi8nijMVi6HQ6gi8xbdWdDe9H2KYxY+GJhTnP8xCNRrGwsIDt7W1cuXJFCmY60tUYp45uXNcNdAQmL/xtTpLmkZPGyPO//uu/cOfOHQyHQ3Q6HfT7fcGd2frD8QaDAUqlEvL5PL71rW9N5MUvSqHR5fMxA9E4LoAxJdHtdbqDguvg6dOnaDQaU+99HtkBQDqdFoyd9w6Hw7hw4YIoB7tQXNfFwsLC1HsEQQzmfPGaOXfMThqNBkqlEm7fvo2dnR3cv38fu7u7iEQiaDQa0hVw6dIlXLt2DclkEs1mEw8ePMDx8THS6TRefPFFfPSjH50KE/ld6/f7ODk5gWVZODo6ksJ0NBqVriJChcwiNcxBh5pKpVCv16Vz5bwtk5NkSb7pCOi4aDOuXr2KdDot7YrAWTC2trY2UQbnzVT0Z3lfrXvlchmPHj3CwcGBZFaE+gqFAq5cuSIZFQNHrsd+vy9tjKlUSrZWT6KZdqRRQI7jSOtQt9sVI6qxXUbB3HigxwqFQuJhmUpoA9Lr9cYeJkigWoimYvM6W4nYnwhAWozq9TpOT0+ltU03h5uRBK/NWhQyF8SkazR2jUYDf/7zn/HHP/4R77zzDsrlsvBr27YoLX9Ho1G0Wi1Uq1V4niepJT/jJy9z8fV6Pezv7485u2g0OiZ3/ZqGlBjp6QwGAE5OTqRt7Dxp4DRiyyF5CIfDkjrzWbjoR6ORRCSzjj+NtLLqaH8wGGBvbw/vvvsu/vrXv+Kvf/0ryuUyer0e+v2+yJO9w7du3cLdu3el2MUC8vr6uhROpzkM04lT6VutFuLxOA4PD5FMJmXdE45hdsNokxAR+fM8D6lUCq1WSzp59HoPkmPQfOvsj5G3xnUty5IzWXidwdHS0tJzc2BmkNMoSPe4q3Zvbw/vvfce7t+/D8/z8PGPfxye5+H4+BiHh4dYWlqC67pSnGSWSbnVajWUSiU0m00Ui0XcuHEjkKep8AKNLrfK0qpz0eldS4yUBoMBarWa9AMmEomzm/3d4xLHYrpeq9UwGAzEIFKR+Llp/JkCpoGMRqOSMtPTE8Nly1E0GkWhUEA2mx3z7NrZ6Mq9GQHMwpeZZnHcTqeDk5MTbG9v42c/+xnu3r0rxSLegzJoNBrSfkcMlf/v7e2h3W4jlUpN5Ys0GAxwfHw8ZpDj8bg4Ui7Mfr8/ZmA5z8R6uXsNODv4qNvtzqwYWiHNa/onlUohkUjAtm1xoCzmcT1pR0vs3nTO+u9Z+NJYHx0kdeH4+BgHBwf4y1/+gj/84Q94++23MRwOkUwm0W630ev1BNpih8k777yDe/fuSVCxtLSEzc1NDIdD1Ot1HB4e4uLFi1PXl5ab67oS5S8sLEiKrtszGeSEw2GBGAhRMaOiXjC7MoOeWZ1XkHx1EMRWznA4jHw+LzsaNY6q6xRBmckkPvx+aLdqtRp2dnawvb2Nra0tPHnyBN1uF+vr69J+VyqVcHx8LGeMxONxLC8vI5vNIhKJCBa+v7+Pra0tHB8fY2VlBdevX5/YBADMYHS5QBzHQbvdRq1WQ7/flyo1N0J0Oh0plNm2jc3NTayvr4+1MnGyuVAAiCdmAY0K3el0Ar2+X+rAaBqARENsjep0OvA8DysrK+I4NOZL5dDKxb5PvcWTKdoknszqv+aNC7Hb7aLdbuPRo0d4/fXX8eabb6Jer0svJdNkGrtQKIROpyOQDvkg9HN6eoqjoyNcuHBhIl8m9DIcDuVsCqbsTKn8CkZUBh1Bmk6OW7y1Y3q/0IKWJyM3Fg85NzT8wDOHHgqFUCgUnuOT483CEw0uMztCGHTUnU4Ht27dwq9//WuUSiUxIJ53tqWajooHKdFBAM9aEfn/0dER2u026vU6MpkMXn755cCuHbNXlbrE9k1G+9Szfr+PQqEgbYjsceYcE1ojzJHP5yWbDTIck+ZMkxllhsNhZLNZOQOFzxKJRGQDB/t4E4mE73o2HXrQXNJBsud9MBig2+3iyZMneOutt/C73/0O+/v72NjYwPr6umRUDx8+xK1bt2T8VqsFz/NQrVaxubmJF198EbZto9Vq4eTkBHt7ezg8PES325UMRhdzTZp6yphlWcIwjWYqlYJt29jf30etVkM8Hkez2RRvyV0nPOiGoTgAaREDgGw2KxgPm7Up+FkOvNFK5NdKc3JygkePHmEwGKBQKMj5D6lUCtVqFUdHRxJFNRoNwTWJKesigmnUJ8lLb7LQmwm4uBuNBv70pz/h8ePHePjwIba3tyXqKZfL0uMaiUTQ7XblFC2mMgCk39iyznaKNZtNaY2bRV4AxICQz3g8PgYJ6Wfmc2ssi9AQ8VTCSlR6jalNUgw/SMjv9UgkIimyTn0jkYh0xgDPOlb04Sl+zz4tamLKvru7i52dHZTLZZyenuL+/fu4d++etBqm02mZL+LuzNZ4vgidgs4SaYx17zp7joNgNT4jn4HOstfrIZPJIJFIoNVqAXjWKcC5rdfrACCY8Wg0km4hHflyPI3Zm3MVRPp92ijy70wmg1wuJzaAgU4ymZS1Rb61DZhkYCetLxrccrks3VGlUgl37tzBD37wAziOg2vXruHVV1/FysoKTk9Pcfv2bWxtbeGFF16QThTOV7VaRaVSwW9+8xt87GMfk3syW6A+RKNRlMvlwMJ2oNHtdDpoNBqysKLRKC5cuIBMJoO//e1vUgyjQCg4KnOv10O9XpdTjBiZJJNJNBoNdDod9Ho97O7uotfrSbvZYDCY2rlg9tJxAhn90RgdHh7CsizpR2w0GiiXywiHw6jVamJQ9K4uvSOl3+9LRGCmwiax2qkLTZycdruNhw8fCnbLxVcoFLC7u4tyuYxQKCTHZDKNZ7TBCIWbJQDIITS2bePhw4e4efOmL1/aUZjKyjRJwwdc9Fq+LMDQ0Gr4g/h8t9sdOxdhFjINs+aBZBp6y7KkvYp8kh/2oZI0dqgdSJARaTab+N73vof33nsPtVpN1iojWkbetm3LyWaM8Nklw44A6gWjdH6OaTXXa6vVQrlcfs7YmbLib86R53lyxnAsFkMoFEI2m0UymYTjOLJeKDNmSFxfPBaThW59Dooptw+Cj3OMYrGIhYWFsWM69TrXc6SzJT/dCwqCqtUqfvrTn+L4+BixWAytVgvb29s4PDzEJz/5SSwvL+Pq1avY29vDn//8Z1QqFTQaDXieh8PDQ5TLZWSzWdTrdWkXY1b55MkTxONxXLhwQWCvbDaLTCaDUqkUGAABMxhd3oyKyoKX53lYXl6W1JwekwaK0EM+n0c2m5UimRYuIyRW/AjyZzKZwPMXdNqrJ4LRIKPK4XAoShGPx3H58mUsLy8DADY2NrC2tgbbtsciFh3hARgzRub9TOJZvYxqBoMBOp0ODg4OJP2oVqsiA57UxdOgHMcRB9XtdiUyCIfDaLVa4pCAZ8aEmOZ77703kS9TYXTxhBEXFzUzDhpaFkX5PIyGNPzBYhvXhuM4M+PxfgZWG2DOAc9d5jXCWjTINC46uqR8/JQ1yID8/Oc/x3//939LGxV5IZ7MHY40mDS23W5XCmipVEpkQSXUGDGLX1znTFenkX4evUbZ985+X7b60VExem82m4I9U57cgkvYhj2q5zW0ppz9PlsoFJDP58egBQDI5/NjGDTXj86atAOYND7p9ddfx69+9SvpcWfgxQO26vU63n33XckAeN5wPB5Hq9VCs9kUCLTZbErXFnUyEomgVqtJu2I+n5de8iDHCUwxumSQPaTsO2RBKpfLiWdnykTMM5fLyQIdDAZjC2IwGAiMwAo0ja5OcSaRbkwnmd6YuCzxNMuy5FCUK1euiHJSUXkWg3Yy5sTOAi+w17ZSqaDb7aLVaqFSqUiKHIlE0Ol0RBFpXLmg6Ii0zPP5vKTx2vjrw29OT08D+dILlfLl59n5QKNhOjVGsmbkwQVYLpdFsTnGLDRLumhZZ+2GzAzoIIjbcv1wbsyOCr97TstYWIyjYeW4dEpUSB1A6GKz7srRzlHPMR2aZZ0VCi9evIiNjY2p8IIpKwZD3KzCbJORom51ZLDEQqR2so7jCMSmNylMmy/Ni4m3+lE2m5XNM6PRSJzD5cuXx7bg89xk0wHPSpcuXcLXvvY1AGfB4/HxMRqNBhqNBmq1mtRQnj59OhYEES7lRpNQKITl5WXpWrBtG0tLS2L3isXi2Lfh8JmCaOqONOBsEaZSKakKZzIZeJ6HZDIpVf9oNCpVVJ6BubCwICkP+wb5XkZPHJtRrpni+xG7H0gaN9WpSTqdlp45fqVLLBaTBU5BFQoFEbBOq2dtmSFxu+eVK1eQz+dRr9dRrVbFIRF60UadRoaREp+dPLBXkFVlypGGgBX9j3zkI1P54z0ZZTFSA87wd21wTYUj7qePS9SH7egOEbNV8LwK42d4zUic5wMkk0mRD9emmQX5RbpB9PLLL+Ozn/0stra28PTpU1SrVYFNAIw5O/7Pa5b17OutksmkHP5ULBaRSCQQj8eRy+Wk/Yjp/dLSkmRe02RDYsbS6XTQbreRy+Uk89HFUP0Z3ZlCuI/OpV6vP1c/mJUmOVC+ZkI7/JubMDY3NwVSJOQQNJ6+5nfvpaUlXL9+XYKLS5cu4fLly+h0OqhUKuI0nz59inQ6Lbv1+v2+wEEshvHoWgBS5APGuzH0NvlpXUSBM8zFxANt6IEKhYIwx4qfjhDZjcBrLG4Qg2Mkx8WpD8xhyhpUSKPCm9vytJGk0WW6TrxY7z1nZK0xJY6lMTP9d9BipMA3NjawsrKCdruNdrstPZiDwQCHh4eC5bmuKwXISCSCZrMpsiCGaDZyM0LXxaJUKhXYG2gaGaa85AEAMpnM2NF7ZhpnRviMbM0ODcIV+n3TKCjy5OfZPdNut9HpdMSZ8quEePwj8PwRm9MiW5OuXLmCL33pS/JVT6enp/L9XWwRajQakgnSyEWjUeRyOUljidkvLS2hUChIYMFzRjKZjCir7iUPIjPNZocCI2xu1qADZ3GTRW52OriuKxEvs9Nms/lcpjdLKm+m/37v5TUGRFxTPCtieXl57KyFoPvMQjSYXIsaUqMsIpEIKpWK2AIN10QiEcTjccnKtTNlRkOiXdOBSBBNrXbQw7fbbZRKJcExKpWK4JAAxo4i5ME3LBqQYe1h2QbFiI6VXT+czyT2PT73MOo0en6eB39oL8o2snw+L0bRrNaTtJHV/aB+pB1JMplEOp0eU5DhcCibGtiG1Gw2JfolFsqCGR2WXrA0NpQhDzQpFovTpnIMmqCxZcQRjUZRr9flebmA+F6N6TMa02PQCTLbmYW0ogbxbFmWRCiM6thOyM0j9XpdHDWjqUlraFr0nUgk8OlPfxrXrl2TVNtxHJyenqJWq+HOnTuoVqtIJBKikIzaLl68iMuXLyOfz0tmxYCDctVrlGuGx4tOa9OalG6zEEYor9frCbzALgnOE+VGQ0SdZIukLgjTCE+DFkz+/Hgkhks9jUajsnOVOGnQuPr/aTwxAmVgoc+kzuVyEijyC1bpiDg/zKY1jMfMXG8S0zrKoCyfz0/kC5hidGOxmHjParWKnZ0dHBwcIBQK4e7du9jY2BBctNPpyG4W13VxeHiIxcVFaX1qNpuS4jNC0nvp+aDclhtUSOMGAp0q+RVMGo2GHJIejUbRbrfR7/fRbrelL5HpMY0ujQ1Jp5HkcxJpaMLc1cNDYwincBwqCosZ3GDCSWYnAJ2bhlC4ULrd7kyGjgtX7yTkNRpSGnLOI4srNLbEvlk1J+Skxw2aOz9++PckopNsNBrSxqNho16vh1arJd8SouGI80a5lEE8Hke73RZFzWQyuHDhAqLRKD772c8CeAaBmQ6b889uGZ1WE77hfLHQy3t95jOfmSov/uZ96Yy5TZWnhDGL0yeNMTWmjhHLZdbFueZznxca0rz6ke4vD4VCsgFCH7Cjo2xtXE08Pog3GlJz6/poNBLnwufk/1zrhFi0A+RmE8pTB0LkhfKf5jinRroE5qlwrHoSL6UgWCgCnlVpmfKxeOS6Z6cdcWNFIpFAvV6XqDUcDqNQKMgYk4jGjCA8jQONJ6PAxcVFweO4EOPxOBYXF7G2tobNzU2JTlhMY9SityITP2XD+SRixMiInRPMz/R6PWnv4X0cx0GtVhv7BgRWQLnoOQeM1uldGR0DCDxljJ8hMd3kQiEey/sy8tLFSOAZlq67VJhFMEU1Md1ZI6RpiuS6rkALg8FAsEB+DRPTZbMA62dwpxkSGqvFxUXk83mJsvf29vDo0SPs7OxgNBoJDzSadEjE7tlPzbXK7duUHQtK0WgUKysr+MQnPhEYJZmQj85cCBNQV2kM+F2G/OJOzmsmk5HeZzoVylMb61l2X5KfWZwbj+GkXWBBVJ8HQT0y4UPz2YOiXX00gSk/1plGo5Hg4OY4fn3/fpue9PP7/e3LW9CLPI+AikeIYWNjA6VSCYuLi7LXm20Yx8fHCIfD2NnZkdaaZDIp53QuLCyg1WrJeMfHx2JoGMkQD55E+oBxUxDAM4NNbNnzPCQSCSSTSXEaa2trWFtbkyJGMpmUSaYR0qmDBv+D5MVOgHQ6PZZSMtUjdkTP67qu7CTSzeo0uATptaE1Pf6sikFiJwR3/hFnpKcHIMpLQ6vPYCCPLJpmMhn5ni3Af2u2H/mljPo1TcykeK4B12ar1ZLojIe+a2NkjqMzoyDSTi6dTuPChQu4du0aPv/5z49herqAZu7JpxPneObf+n8dlU0i/Tx0bt1uVzZmEMulUySswAIPYT7CCnqLN9ciC08cw29uJvE2jbieyQ+AsfMV+GxmjYh/+40XtLb4W0fM1GteN/Xb7zP6+XTdwKxpzEpTuxf4zZ3ZbBarq6tSOb5y5YqkWzRuTHlt28b169elakvlZcsWo7MXXngBAOT0LEbL3BocxBcFZcIKWpny+TyKxSJarZa0pJE/nknLnmK94PUE6cXH5wsivauL4+lzArQi6nSUsIqGKEjm16doOWicfFbiYqYMl5eXsbm5iTt37oy1i9Gx6V1qGuu1LAv/8A//gO3tbdlFyPdPw9w0mVGC+T/nhxG4lh3njZG2xu61fM2xZ1ESGlPTWOpzDTiWqeRaIfVnJ92X16fJjePqdLjdbmN/fx/1en2sP52v84wO3bPLNjJuMiEUwo4bOrDzbOc2jZbf55ht8j3MFqgfdALmQfhaNqYMJ/GmAxQ/nvzsxyQ4Q1/Tv/3GnEYzfRswjSYnKhQKYWNjQ7Y7RiIRwTI4ScStmMLQ4NLoJRIJwX251U4fYh7EPBeOn8GlktFDcpJ1MYP8dLtdOWFMe0DiqpqHacZW39+ves7XOdHkQ3tUGk8/I6QjbfJGPk0FnyQz3ou4K6GQbDY79j11JDNC0GkYYYlcLodsNouDgwPhR3cvBJFWJnPha2XnuL1eT5wzZcAojYb+PN9aMQtvQa/pe5hGd5IScu3yOh3nrEqr1z0/m0wmsbq6Ctd1cfHiReRyOWQymbH5I1zFw+q5aSmRSKBQKMDzzs5kLhaLY5km19x55OgnH/JLWJFrigVgBkAMTAh3TJLNtGxlEh7tZyzNudPXzTVk/u0HQ0yT1dSv62EqoCvYxGTT6TTu3r0r37+kU2aC8kxXKCR9KA63kFJxaBCYTgeRGS3qidV/691hxP4YzbF44SdUvzR+mjCnLQ5O0qTFoA1b0IIxF8os8IKWpy5mAGftNdeuXcOlS5dkLojBM9oj5KKzGu7yY5eGmQnMksb78Wk+O/E/y7LEkVMGGp/j7sJpFBRx6vf4zcEkpfKLdoPIhFJmMWpaybUzTqfTWF5elgOMOG90gJy7fD4vtQNG69QR9uEvLi4+V8n/v0k0+oxsWRDlOrYsS3qZzWc39TBofZk6yN8mZGDOk5+uT9ooZRpwc4xJNNXoasxUN8CPRmc9qcS3aMjYEpJOp6UdBXh2mhgVmMLnVmNOwiyp6STPwwfWkQC34kajUemcoHOg0dXPGXSPWZWJyjCp19HPe+oo2O8+2qGYfE5TWr90jD/D4RCFQkHwSn7FUq1Wk7mlgQUgR3Wyg4QbQfRza8MQREHy1I6Uxp5GQht3YvHMwswDpE14wYxM3y9/s3zWnGO/dX1eo2a+n6k41/do9OxrbjSkwFReZ0UaPikUCnJoDjffnIenoJRfy582ggU7zhevc12xSG+OYdIkWzGJJ23PphlcP6M8C32gSHc0Go15Su4kI4yQTCZx8eLFsRYVeqwXXngBrVZLToFims+01LZtacbm7hDd/zkrRhkUEQLPNgIQz+VzcYdXUIpwXoXQnlcbf7+oOeh59GRrCEKn+vr9s/Cq760zGM/zUCgUsLq6iq985SvSRqQzlVAoJLts+K27LBrxAJNJrWJBDtR8Vl7zex8NAR08C1lMVWlAzN1A+rnfrwGd9ix+0ZGfAvvxdB7SY+laAxv+U6kU1tbWpDWTvbqWdVZAI5zAjUOE1mz77FuB79y5g3a7PXa40axyCYr2TOfDLqhQKCQ7Cxnh0sborcLaAZ+HJ7/M09TJaY7QHMcv4p7FOWgKtGz8Ejse3AE8+7I7/l5ZWZF+VwBiWB3HwdramhyuoVtQ2KlwfHw8djyfrroGGV2/XkwdFfHh9Zmi9HBMxfmlmOTJL8J8P4qisTDNr9lArXlm5M1CFF/ndV0x5f9BkYVJOvKmjDhWNBpFsViUr4wh6a2trMT7YdKWZUm0wsxm1ihpkjPyywL00YM8lhKAKC/nlwUu7YhmNe6aLz8ZakU1HaNp3HVE6ZfhvB/Dq9siNRbMtrBLly7hm9/8psiCnQ28JzdEMEvV7X6O4+C1117DwcEBPv7xj2M0egYp6k6eScR7aL78HE4oFJLvHONhSrxOO5LL5bC0tPRc54Kpm9MMsZ8z9HPCfg7Db5703GuY8LwRcaDR1af+8AsQR6MRnjx5glwuh4sXL2J5eVlAcLac8Pxafv0Hv6GBBxgzvbh58yYePHiAVCqFlZUVrK6uolAoiDGYRH6KqhciIzme9B4On52Yz5PEUqkUXn31VTx9+hQLCwtjZz4AGDvcBcBzkWUQX36LgIqi+xCB8TYUv910Gt/lNc2XVn6OP4koF8/zsLq6ii996UtypvC//du/jWUaAARX1ymoyQv5/+IXv4hSqYRCoYB//dd/lXMg3k8KP0lZP/OZz6BcLiOTyeAjH/kIvvCFLwAAvvzlL2N/fx9PnjzBzZs38Y//+I8iD47xfiMS/V5zXv3+NiMqP5jFz5GbzmeS3HSxl9ljoVCQMwZWVlaQzWbH+rlpUHVmo4tWvKfjOPjc5z6H3d1dyV6pF7NmfWYmZj4rDetLL72Er371q6jVatKXbFkW/vmf/xm2bePy5cu4cuXKWFHZL8qc5jhNo2h+VndnmMHQpDF1pKzvM2sEDgDWB0255jSnOc1pTrPT+UrLc5rTnOY0pw9Ec6M7pznNaU4fIs2N7pzmNKc5fYg0N7pzmtOc5vQh0tzozmlOc5rTh0hzozunOc1pTh8i/R8t3oZZqsr6pgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'sparse', '30')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('dense', 'sparse', '100')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'cat', '1')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'cat', '3')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'cat', '10')\n"
     ]
    },
    {
     "data": {
      "image/png": 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TvxgNsUvmwYMHePHixQx2z84BnUm9CaZrwgs666BhoIPUwzZffvnljDPlerMflf2gGjNfRV6m86Q8yAPbECORiMhrPB4jGo2iWCxif39fMgTgWh9piAaDAWKx2Eq8+MlJk15Htobp7Ilr+/jxYzx79kycPL+obwxWNHy4jD+/TiPKZzgcSoGTdQsGXpPJRDKWi4sL2aP9fl+MKw2vdvbzZOBHK/Xp6gvqDcvvTEm5+DQkt27dwpMnT2bAc70JdOVZA9LLNiyNq96YOtJjJKIjJqYVHEyoVqtSPLJtG/fu3UM2mxVDy4LHdDqVCSMAsqnnkVmgM7sRNNRBXglveJ6H//3vfxJNxWIxDIdD3L59WwogjOaBa9iGHlo7ML91NCNKnfpxY8bjcTEUg8FApnLq9TpisZhEQI7jyNpZliXFPnY+6AhjGSRDfky5UQ6pVArRaFT+R17ffvttfPjhhwAw08/M3mfLsl6DPG5Cmid2e9DA6mlBbsJUKoV6vS7RJiNdnZWxV9Wv53yVqjxJ1wwI8XA/ApCuCtu2sb29jW63K9Ewn01HghpiM9dtFSNnpth8Zg6LhEKhGceVz+fx7rvv4i9/+Ys4ckJFHNhYtC7z/j9P58kPjSzvxdcRy00mk7i6uoJlWdJTzPWijmu82dSxRcHZWpGuFip71ZiaMgrkzeltqaRaQDptMKPmVQpWfp6O79URJZ0ChQO8qrrv7e3hP//5D3q9HqbTKeLxOEajEYrFohgVLg4n2gaDAWzbRrFYnMvXvEU2Ny35oxNgsWgwGGBvbw/AdYplWRYePXqEXC4nRpcOhREuU59FfJnrqDerjriZvpM/yrbdbqPRaMiaMvLg//W1uD6rGFuTL9NZARC8jfgusxBONuqWKACIx+OvyVxfb12IQT+jblVjD6fuaGAk1Ov10Ol0BIOOxWIz0TKxez0Ov+70nH4+HdUT5tHrSMyZnQSEHUaj0czEI4u2b7KO5E3vaWZN1C/+LZ1OY3d3V3Sb8AYAJBIJ0XFzL627hjqL0l1EdIyDwUBgMsqj1WoJXDkajdBsNsWWBAKBmbZX3mMVWS01uvOMiI5SmQ5w8fk3bhZGaQzlGYGYBld7ulXSLB1967+ZkTgLGN1uF8+ePcM///lPfPrpp4JppdNp2LaNhw8fSlTCReh0OqKo8XgcDx8+XCpUk0+98Ym/9ft91Go16ZOsVqtwHAflchnBYFAKII7j4OTkBOl0GuFwWIYlUqnUTPvbOuvI33X1lVE4FXAymaDRaCAajSKTyWA8fjWowHuxCs+zBgaDgWCFGq9bxpPpqHTlnIaIuLZeY3bIsEjEDUUnpF9vFmFusmF1Rqbx+el0Ks6p2WzOtEO5risRJ4t6lBcjYxpu8+yDdfnS2SIxWq5vp9NBOp2W6JaYsjaAGlaj4TVbLteVGa/J69Ae6E6BTCYjRVldKwoGg0gmk2Iv/AKHm8ALvD6jXTpAtko2m00EAgGBRHlEgGW9amGj3nP9eKaFxo+/N0zX9DR6oTXWyYW3bRuFQkEWmy01iURiJu3T0YPerIuEynuY1UMqCg0tjVu73cbl5SVevnyJv/3tb/j000/RbreRy+UERkgkEjg4OMBwOEQmk0Gj0UCtVpPUw3VdFItFiRrmyUjLSj8fHZLrumi1Wri4uMDLly9xcnKCly9fotls4s6dOzP9uLZto1Kp4MWLF6KgjUYD2WwW29vbiEajosDFYnEhvGCuI/miHHXa22q14Lourq6ukMlkZPTRLFay4Z9GJplMiiHk2s3jievsp2N6s9IBMSLk+9hBEQ6HZzoYaKR1+qwNuZbHqgU+HSVRBsRQ6Zg979X4aiwWk/oAgBljRkfL7ga+lpnfulAM36P3EuXADJP1E8JV5EtH3RxCIbREvnSx9iZZi4YMHcdBIpGYwUBt20YymZT0nbANOy9SqZRM+vmt1aJ19AvIdEZAQ8vott1uYzKZyJ4Hrs/QGA6Hgnt3Oh3UajWxe/F4XIwu77NI54EVja6psDpEJ8ap28N4UlCxWJQTjChkLqjG7PxwN9NLmfxQsbR3JthNL0TMdn9/H1988QWOj4/lwBQaTt3yZts2nj59imQyiWaziXq9jnv37iGdTkv0XqvVkMvl5vIFXG80PqMu2jWbTbx8+RJffvkl9vb2cHZ2JkVFFhJc1xXPOxqN8M033+Dq6grZbBaj0Qg7OzuYTCaSXjPVWYY1awxcp6UsgLqui2q1Koe3TKdTlEolpNNpKeZxzYLBIFzXxfPnz+VUpkQigUwmIwaScNNNMN3pdCoQCyMkOmPCWYlEYubMAAAzqbyGc9Yh7fC1I6Dec7O6rit6orM+GhIaNcJBo9EI5XIZk8lE5vxTqdRrBnoZTmnKTPPG39k+RucaCASQSCSQSqXEuDHrcl0X5XIZAKRwyqLoKh1Fi/jiXtVGFIDoEPWGZy9QDuRXd1Fo3QAWO03e1wzK2L3Q6XRm2uzYr9vr9VAqlRCLxcQJcS90Oh059iCXyyGRSIh+6qK2DiD9aC1MVxtGLrRuUyF8MBqNkEgkEAqFkEwmZ9rCQqGQeHedvlBQAER5FxG9OJWd+Gir1UIgEMCTJ0/w73//G1999RXOz89hWRbu37+PUqk0816mX/v7+zg/PxfPyq6GZrOJBw8eIBaL4fDwUFLJeaT7etn/WK1WcXZ2hkajgaOjIzx9+hTPnj3D1dWVFAxu3bo1o1iUA1McNr9zDVKpFAKBAKLRqDSRzyM/g0sjy6GI09NTfPPNNzg6OkKz2UQ8Hkc2m8Xdu3dn2o4IKzHl132nzWYTnU4H8XhcnPCqRk9vDp3p6L5k6hwAgVvC4bAUP9i9wDMj9LMzZV23m0LLi0VYDiHweel0AoEA0un0TOsc15L7Q09h6sEXneIv40vLjM/W7XYFQuPwBkfzLevV8aqMdHUPMQ0ijW8kEpnJtvzS9Hnr58evhk6Y8TJDCIVCyGQyYriazeZrU6MMrrinGAnzueY5Ay1PHSh2u10ZBrm8vES5XBZ4jzpdKBQkKOPa6AnccrksmUs8Hpdn0C2zi2gtTFcTJ6jy+bxsBH5nEYG4EavjjH4I4A8Gg5mDXjR+s2ih6Z14HSobTyfa29vDX//6V9TrdUSjUezs7GB3dxfT6RQHBwfY398Xz8tqN4svvGYikZAoplqtwvM8HB8fywEnfjQej+W5Obl0eXmJo6MjHBwc4Pz8HOVyWeb1s9mswBc6vRsOh5Jy0ZHxddzMVCjPe3WehV8zPkkrHzd7p9ORTODk5ATn5+cyjTMej6Vjg1NnbJEhTzrdp6HVI5vUnWUK6Bfhch1YB9BwgYavyAeJkTE7BVjsNXuul5EJDzECqtfr4qRc1xUDQb0102meF8vKN6O8Xq+HQCAgk2nkaZnR1fzpqJs8+Z3RwSyDfOrBJWadxOH1yYC8jhkI+JHer1rOvA/1lkZJD7JQVvyZtoCDHdRxvY6ar2Uy0p0dHHevVquoVCpotVozcEY0Gp05zIYwKNcvnU5Llt7r9WacKHn3G3oxaWnLmN/PWjj08PF4XDYqrb4G9BmiM43XQwZ62oi/L6Jms4nT01N0u130ej2BEJ49e4bT01PpBb5165Z4oUajIU6hWCwiGo2iUChIKhOPx+G6LkKhkFyTWCE3H3GnedRoNOQQFOJ3R0dHeP78uZxkxD5Fpt7dbleUg4fzAJipktIx0ds6joNGoyFpLBVhHum2FraotVotVCoV6VnmmaasIvPejH7Yu6gzG/ZZU8FZfGTquMzAMZIiaWMH4LWhBho2QlpsEeN7Genyf7rW4GeIFvGl8Xgat06nI2mp2TlDOIT6H4lEZg4DItbMw/PNaSvdX76IL36n0XVdV3jSU4F8ZmKPWjbaaTMCZ1eK+bWKgTPXkX+jMQKu9zTXk61tzHoZWXJoiPaDXRjrFvKow/ziuPvp6SkuLy/RaDRmsGrdQsasiFCMlhWhLjpinsOgHfwbRbp+uBaVhYzo8TmO702nU/GojNTYQqY/EYH3oHB1BXeZkKvVqlT/eU7v2dkZACCVSknKB1xvIvIWj8dF4bmRmTZmMhmcn5+j0+lIMUJ7Wq1IJtEDEg7gvLku9DAVbLVa8gkIjuNIsa/X66Hb7YocXNdFJpNBNBqVFCgYDMoBIXoqbxFpBaTxpKHQZz8Q56VcGBVz7ckT5cLfgesJPyrdsnX0awUy38tollgjNwo3KSvcnAijsWWUpLOrVavwlKdOTanzNGIAZhyibp3UTtXsLODotL4Xr8XnXraOGlagcdH1FUaOweD1OcgshOqinX7GUCgkB4vPS9cXraN+Fm20dcRLXdPthixCxePxGRno/mK/LGWVdTR1XkOK5swA11kPsnBvEQphtwN7dClTbR9WKTquhOlqbEZvUmKKGkRm6pDL5ZDJZLC1tQXP86Q1i1gvp79oqNfZFIxI2R2RSqWQSqVw//59qb5+++230jHBKJFV72QyKdVjOoPpdIpKpYJSqYRsNivKVyqV8ODBA2xvb8OyLBQKhYW80TDwfAB2GnQ6HSl48bxathHRqxLmGA6HiEQi8vvu7i62t7dxdXWFVCqFTCaDR48e4e7duzLGuayIpvExc10ByJQSDSr/xpRJT/kxMgqHw8hkMuj3+8jlckilUhK5aMx+EV/A6/25TNGob3rj8Gfib9y0ZlTG95kGYRUy9VDzB2AmeuZm1tGZTqspR8IyXF8OCuhgY5WCo3ZUNBo0YNyb5IkBEo2YCRfQSViWJRNsLJ7p+y3jS2OrptHWMJE28uSdxpZtY/qa2mjrNdHf562ryTcdJKcbWWfSHRrULdon6lY4HJYicTqdlgNxtM5ryG2ZDVu5kMaH0DP59Pg0XGSU8/qpVArZbFbm0HXUYbaHrdO9wOovr8EqMKMsFg6Aa+yZxRYef9fv9wXPYpvT1dUVcrmc4DXj8avzI27fvo1isQjLspBIJOYL87uUm3DKePxqHJpGVhs2puDEve/evYt79+6h0+mgXq9LpTmdTuPu3bvY2dmRlqR4PI47d+5I25g+m2De2unxSTpNZhzE9AjNED8OBAIoFAooFArIZrMCNWQyGezu7qJUKqFQKKDb7SKXy6FYLArMtE4P8byNpXF+3RY1mUyQSqVkWk6n5boAMy9qW4UfHWnpLxN/NJ+BkE8ymZSD4NkqqU9tY6uRNrqrjJjP+6LBZxStjTEAadeigeCz0HlyopR6um6Prja4+ovPpp9Vw4iZTEaCDvYN672/zOjP483McLhu1HdtTOPxODqdjsCe+Xwe+XwexWIRzWYTkUgExWIRt27dQqlUQiKRQK/XQy6XQy6Xe82BvpHRNY2g6fEZiuvTxVj9pOXnBqax0RNVi4ooi4wulZjXBSB8EDO7d++eeHPCBJPJqzFHFh2YticSCfl4GhppFkIcx0E2m5UBgUUKEIlEpAhh269OdEomk+IgOPlGB8C2Itu28eDBAzx48ACDwUA+/oVO686dO8jn83IdHtXHDbNskU3FZfGQbTrEhC8uLuSAeUYht2/fxs7OjowiO46DfD4vH9SXzWbRbDbF2HDDaox+GWmHrh2ILnJqXNJxHKTTaXEAGkrQWZif4ViVJ7159IZlZsfojIaV65/L5eSDMsvlskBr3NzxeFxgAJ3lrZrpmbIib4RggOsJPkIJLBqz0s6WOv1MfL8+vpP3Wsfwah61M9EFUa0fNLasD7D2o3VWZy2rriP51lg/n5F2Ih6PS7bMomc4HMb29rZ8GGWj0YBt20in00in0yI/QlzMDFbJCEhLMV2N0+gCgO4/1K1H/FwyXVBhyqhTQ3pWYjx6kZYtMjeablfSvZP1el3gBC18Auo0euzr1T2gbD0jbko5cJ5ffxqoSaFQCOl0Wg5D0el8p9ORQ4HIG40wr6vnuyk/XXAhX9PpVNp6CCssarGjPLUyU9H1WGuhUEAmk3ntcG5GfKxuh0IhkQ0AOaPB74DuVVNT/bs2sHRk1Bl2vND40RHpMwN0twN58IumF/Gkf2Z1m1Eqg4OtrS1sbW1JFTwcDsv5HTxND7g+k5VZANfLhNWW8WYaNRoznuDHzydkD2k0GhVMl/elwdVj03QAxKv99uIqRtcMlLTR1fg3ZUI5MINkdsFslYbZD2ow18kkHbgRbtJnfVOnmaXr7goGZ57nCc4dDAaRy+VmbAP3gf40jlWM78rDEfoh6SVpdMmk/sBFLiT7QfkaClqPDmvjyOsvEiihDU4lpdNpFAoFiRp1xVID5QDkvAUaCkaNoVBImsaJxxJmyOfzcvYBo5p5C61TPUYRxJA5LsvImed5jsdj3LlzB7u7uwBeORUqYi6Xw9bWFlKplPCgMXNim7p1ah5pg0sjxkjD8zzp9qhWq/JJDZlMBtlsVmAGy3o1/UbIJZfLSfEmlUpJWj1vfHOebmkd0xV3poEAZOySG4bGlzCNbjWiEzLHWdchnbrTcOhT1BjdM62nYWUaz0N6iAcy2tUj3tzs2sCsyptum6PRDQQC2N7eRrFYxNXVlThm/o3rxrNGWC/I5/MiQ66hNkSL+FqWEfP9+qgAtlXSycZiMVl7OgPqAAM3M3VfFT7S8wE8ZJ7OhT3qujFgZ2cHOzs7eOedd+QDGorFIh49eoQ7d+4gkUjIsY75fB7ZbFb0wAwi/Ghlo2tGqzxblf2KlmVJL5zneajVamKEeeISuwqA688f4kdCa4B9WSVXj3ha1jUADsz2OtJA0nsCQDabFf4ZAZhndwIQo8NNT+O2CHczPTALPbwnTw1LJpPI5/PiFCzLwvb2NlKpFBKJBHZ2dqRImUgkpOGer2fKqicB1zFuusWJ0eJwOESxWESpVJIzfUOhkCjg7u4uqtUqAKBUKmF3d1eMNDcHsa11HKjmietIxWUWQuPGteImYsqo6wSUjV/RcF3SMtMYISNIrg2zm3g8Li182WwWqVRK6g98LT/Bgbpxk/MzzO4FFs4YTRLGoL7RCRGuIQRHKIeOwjSS+p6rypAZpW6F4zPyvsziWEgGIJEln0d3Luj2M7NXdxXSXVfM6mjkCRnwcBtOxzEiTqVS8DxP5MlMRusb7dWqxdqlRtds4THDfkaNzWYTzWZTBMk0k5VdDkMMh0PBbXS7DdtsVjUiZhjPTca02Jy9172LAGZOE9LDB3oCiqQ39zKjqz2djuA1oE8wPxAIiNLplhqNi+o0Ty/uOsUGklnxZopJBdftZMxOWq2WZDF0mPqTNnTrkd9n3q2blnINdOSucV5uZD35Z8qFFXttnAhlrdqa5ccbDYh5HUZoflE7vzPdpeHx6x9+k2hcG252oPAQoul0OtPGqE/OY68vedH7cR2nRRlonszCGiNovUf47LrQS1mbhlW3eK1LJjTB6xOipG5T5zncxF7rcDgsr2XEzpZKLSutj/NoqdH1E7ZlWZI+tVotANdHFfLwj1arJU3brVYLjuOI0dWFNj9oYRWe9ILqrgr20mqjq6No/swoWBvd0Wg0c3Qh/8/K5DoGhHxxo2p+dbpKA8L3aqOuW1q0Q9LRw02Mhy5Y8tl5qAdxNX0eg8bLtVyYHrLTQxsSjcGtIitNGv+j/GmE9YE7dNT6fYyENZ5o8rEsSpqXIlJehInYAWJZlqTM/CKvwPU6cn011rtOyuzHF3WDmQ+nKVl85Ot1YMOghDUE3UvPCHidQqjmW/OnYRONn1qWJTrPoIwQkp4Q0y1Yuttp1SzKT1YcxGDmyCCHvOhP4SD2bbbdccCEMCufcdXo+0afHEEIQEelZIhMd7tdWJYlKZROOah89Pqm0q1CWvDa+7HCrqMMDT8A1xNw7JE1F9Sv+n6TKES/T3tA3R7Ehm3+XXti02CYmYaWw02J60AclQVA9kJTRnq2XEffAOR1pgFZ1UmZa25Gf7rpn2vtuq78j3qonZSWl7l2q8Ad8/SQes9GenaQ6AyC0IEuTumqPXB9qMs6OjYPK+Wz00ERu4xGo+h0OvJ+Xb1ngEFMXDuGm6wj+dM/a3nQFhCCoh0gjKf1i45cO1TN1zpZlB9pqIPOhkUxZst8jZaJxt/p4PyynmW0MqbrtwhaABSYbu3gIrONjNfS1zM3xjrGzXw9r03g3UxvzPTCjDg1XqS916qtIMt41CmTNvZ6Q+q2Kf7M95lQxTpKZ0Yh2njr6jIjJm1cqZjE/RgZaf79jMgqPAH+EYl2pjQmhEA0DKQb/HVEZBooE59dR1ZaXnqtWDgjZkrDwcJQLBaTojJrAtrxrisvU278WUe0Jg7OqFHjtywEaYycz8cs702cuZa7DojYaaGnUWkvdG2F8loVMluUGWgyM2IN9UWjUemn594jjstPBCEezj1hBkB+9/SjpS1j+iK6TYWRo96cOmLUDfKsLpttHxrLWVcJdYpMpdPpk4nFaYOlDZ9pwHTl9CatMzrN0Aae99ZZAjscNH5LpSN/ulF9XY+qedI/63Vkdd9sqaHx5TpS6SaTifQQ6yiTm/UmDsrPiGh5kzdGmHpIQkc/jHzN7IA0D3Odx5MJCemhEfLEYgsHWvRYq5585CSmhnBu0rFA/rUjZ/slf9frpftjGW0yCKLR0Y4LgC9fq8Ae+rvOhPka7aR0axhTdq4dnbx2oNpm3ERWWud1YBaJRKQY6rquTM06jiNry6NXeX4z9cC0IcvkRFoJ06VwdOGLSsPeQ92moz+eh9gbsTjiOuao6LreVfOlUz4ujPa0THP4nmAwOHMakDaIvCYjFDMaWyfy9TOUdBBMbSgzLQf+rCNe4q7kj2Qq+yo8ES7gxiN+ls1mUSqVUC6X0W63ZbIwHo9Li5rnechmszIEkEwm0ev1ZKT7TaI3/fxcU0aMuVwOhUJBmugZbTOiY2sem9eJBwKvf3DnqnKiTHWBE4BsPLb0FQoFtFot6U5gpJlMJqUFi3Lk8AwxdD/ncBO+dLSoz7PmwUiEEYj3TiYTJJNJ6bJg9GtmLOvyxZ81PKajSnYG0PjxXvybxpdNp75usKF5Iz+8HovjuVwO29vbciYy5RGLxZDJZKQ7J5fLIZ/Py7ATi8g30XdrieeYArO4qe6jY/W93W7j8PAQT548wfPnzzEej/H73/8e9+/fx9HREZ49eyanfj1+/BgPHz6caefSntXwsr5PM5lMhGkaMN2Kwl483ROoeQ6Hw9IWpVMsej+NM+vhDbWAvnxNlTC1sWfRgEbc7OawLEumuVhxZprINN62bXk+KrEP5jtv9afaCemhC0YZtm3LtN75+TkqlQoA4OHDh8jlcnIcXiDwanQzn88jnU7LQSAcWqBBMjKIuXxp/dJf1AXKqlKpYG9vD19//TWi0Sh++9vfYmtrC5eXl3j69Ck6nQ7y+TwePnyIUqkkvcfcGGYnyCp8mevIYIPRzWg0QqPRQLlclinC+/fvI5VKodFo4OTkBJPJRCbUdE80i71++rWKvKj37OKg02NQVKvVcHJygkqlglgshnfeeQfJZFIOiOI+2drakk93oTPQffQ34Uvzp6PK4XCIk5MTfP7553jx4gWy2Sz+8Ic/oFQqoVKp4JNPPsHFxQVu3bqFX/ziF7h3757g5Ro+8cla/fia0Xk92EVZsR+fZ+vyMwB3dnaQSCTQbrdxfn6O6XQqjoxHBrB2RTmZEe+CvbjU6G5oQxva0Ia+R7p5hWhDG9rQhja0Nm2M7oY2tKEN/YC0Mbob2tCGNvQD0sbobmhDG9rQD0gbo7uhDW1oQz8gbYzuhja0oQ39gPT/AFZ5dXdoaKk9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'cat', '30')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'cat', '100')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'sparse', '1')\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'sparse', '3')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'sparse', '10')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'sparse', '30')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "('sparse', 'sparse', '100')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x48 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for hopfield, item in zip(hopfield_imgs, info):\n",
    "    print(f\"{item}\")\n",
    "    plot_images(hopfield[:,-1], num=9, size=6)\n",
    "    if torch.cuda.is_available(): torch.cuda.synchronize()\n",
    "    print(f\"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bed17c0-f115-47d7-afa7-a50d5128e5aa",
   "metadata": {},
   "source": [
    "## Oscillating threshold from `2c_oscillation.sh`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "b55e4215-38bf-4ad4-a190-abd3a7a50587",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "dataset_dir = 'oscillation'\n",
    "fileroots = get_fileroots('out/'+dataset_dir)\n",
    "\n",
    "info = [os.path.basename(root) for root in fileroots]\n",
    "category_ids = [get_category_ids(root) for root in fileroots]\n",
    "hopfield_imgs = [get_hopfield_images(root) for root in fileroots]\n",
    "target_imgs = [get_target_images(root) for root in fileroots]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "ed19ed19-088a-4ca0-9825-d6e9b20297d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving data for further analysis\n",
    "h5file = h5py.File(f'out/visualization/{dataset_dir}.h5', 'w')\n",
    "\n",
    "h5file.create_dataset(\"info\", data=info)\n",
    "h5file.create_dataset(\"category_ids\", data=category_ids)\n",
    "h5file.create_dataset(\"hopfield_imgs\",\n",
    "                      data=hopfield_imgs, compression='gzip')\n",
    "h5file.create_dataset(\"target_imgs\",\n",
    "                      data=target_imgs, compression='gzip')\n",
    "\n",
    "h5file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "3da3e72a-51d1-4a2e-b16b-bd8798be226e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "baseline\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1872 with 78 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for hopfield, item in zip(hopfield_imgs, info):\n",
    "    print(f\"{item}\")\n",
    "    plot_images(\n",
    "        tuple([hopfield[::5,t] for t in range(0, hopfield.shape[1], 20)]),\n",
    "        num=-1)\n",
    "    if torch.cuda.is_available(): torch.cuda.synchronize()\n",
    "    print(f\"\\n\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.2"
  },
  "toc-autonumbering": false,
  "toc-showcode": false,
  "toc-showmarkdowntxt": true
 },
 "nbformat": 4,
 "nbformat_minor": 5
}


================================================
FILE: hippocampus/README.md
================================================
# Overview

This directory contains
- PyTorch code that produces MF and PP encodings of memories,
- C code for simulating Hopfield networks that store these encodings,
- and PyTorch code for visualizing patterns retrieved in the Hopfield network.

Note that "category" or "class" in the code refers to "concept" in our manuscript.

Subdirectories:
- `out`: Neural network and Hopfield network output files
- `src`: C source code for Hopfield networks


# Requirements

### Python packages

Required python packages are listed below, with versions checked in parentheses.
- python (3.9)
- numpy
- scipy
- pytorch (1.8.1)
- cudatoolkit (11.1.1; now superseded by pytorch-cuda)
- torchvision (0.9.1)
- matplotlib
- jupyterlab (or jupyter or a different notebook viewer)
- h5py

### Intel MKL for C code

This code requires the [Intel oneAPI Math Kernel Library](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-download.html), which provides optimized BLAS routines for Intel CPUs. After installation, environmental variables must be set by running
```console
$ source /opt/intel/oneapi/setvars.sh

:: initializing oneAPI environment ...
...
```
Alternatively, to set these variables quietly, run
```console
$ source /opt/intel/oneapi/mkl/latest/env/vars.sh
```
Either of these commands can be added to your shell's startup files.

Successful installation and setting of environmental variables can be assessed by running `echo "${MKLROOT}"`:
```console
$ echo "${MKLROOT}"
/opt/intel/oneapi/mkl/2023.0.0
```
If an alternative BLAS library is desired, the source code can be relatively easily modified by substituting the `#include "mkl.h"` statement and replacing a few `mkl_calloc` calls with `calloc`. The compilation script `compile.sh` then must be modified to link the appropriate BLAS libraries.

### GNU parallel for C code

Parallel execution of scripts is achieved with [GNU parallel](https://www.gnu.org/software/parallel/): O. Tange (2018): GNU Parallel 2018, March 2018, https://doi.org/10.5281/zenodo.1146014. It can be installed on Ubuntu with
```console
$ sudo apt install parallel
```
and on macOS with Homebrew with
```console
$ brew install parallel
```


# Compiling C code

On macOS, the default Clang compiler `gcc` was tested, and on Linux, the default GNU Compiler Collection `gcc` was tested. Remember to enable execution of scripts with `chmod +x` commands.

To compile the C source code, navigate to the `src` directory and run
```console
$ ./compile.sh search.c
$ ./compile.sh dynamics.c
```

If errors are produced related to MKL libraries, try replacing the MKL-related flags in `compile.sh` with those recommended by the [Intel MKL Link Line Advisor](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-link-line-advisor.html). The link flags provided were obtained by choosing the "Dynamic" linking and "Sequential" threading (i.e., no multithreading) options.


# Simulations

Pre-generated outputs for each simulation file have been provided, so they can be run in any order. To follow the simulation pipeline and regenerate outputs, run the files in sequence from `1_pathways.ipynb` to `4_visualization.ipynb`. Outputs are stored in corresponding `out_*` directories.


### `1_pathways.ipynb`

This Jupyter notebook generates MF and PP encodings by
- downloading the FashionMNIST dataset,
- training an autoencoder on FashionMNIST images whose middle layer represents EC,
- propagating EC encodings forward to DG, MF, and PP,
- and training a feedforward decoder to revert MF and PP encodings back to EC.

### `2a_hopfield.sh`

`2a_hopfield.sh` is a base script for running a Hopfield network simulation. At least the filename root must be provided as an argument. One can run a test simulation with example load 100, sparse cues, sparse targets, and a search over theta values to maximize target overlaps:
```console
$ ./2a_hopfield.sh hopfield/test -s 100 -sparse_cue -sparse_target -theta_mid 0.5 -n_round 2 -n_value 7

STARTING SIMULATION FOR out/hopfield/test
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenesses detected: 0.020 and 0.200
...

```


### `2b_sweep.sh`

`2b_sweep.sh` is a sample script for sweeping through cue types, target types, and example loads. It calls `2a_hopfield.sh` with different parameters in parallel. It sweeps through MF examples, PP examples, and combined examples as cues. It sweeps through MF examples and PP concepts as targets. For example, to run simulations with 1, 3, 10, 30, and 100 examples stored per concept, run
```console
$ ./2b_sweep.sh 001 003 010 030 100

./2a_hopfield.sh sweep/ss-s001 -s 001 -sparse_cue -sparse_target -theta 0.5 -no_search -no_shuffle
./2a_hopfield.sh sweep/ss-s003 -s 003 -sparse_cue -sparse_target -theta 0.5 -no_search -no_shuffle
...

```


### `2c_oscillation.sh`

`2c_oscillation.sh` is a sample script for running a Hopfield network simulation with oscillatory theta. It has example load 40, oscillation period 20, and sharp changes between theta values of 0.6 and 0.2. Run
```console
$ ./2c_oscillation.sh

STARTING SIMULATION FOR out/oscillation/baseline
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenesses detected: 0.020 and 0.200
...

```


### `3_visualization.ipynb`

This Jupyter notebook generates visualizations of Hopfield network activity generated by `2b_sweep.sh` and `2c_oscillation.sh` by
- loading networks trained in `1_pathways.ipynb`
- passing Hopfield network activity through the feedforward decoder to obtain EC representations
- and passing the EC representations through the decoding layers of the autoencoder.


================================================
FILE: hippocampus/out/hopfield/test_a.txt
================================================
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.78e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 


================================================
FILE: hippocampus/out/hopfield/test_log.txt
================================================

STARTING SIMULATION FOR out/hopfield/test
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 100 examples
Testing 30 cues
Maximizing overlap w.r.t. theta using 2 rounds of 7 values
Theta search range from 0.290 to 0.710

STARTING THETA SEARCH ROUND 1 of 2

Round 1, theta = 0.320: done in 0.06 s, mean overlap 0.846
Round 1, theta = 0.380: done in 0.05 s, mean overlap 0.960
Round 1, theta = 0.440: done in 0.04 s, mean overlap 0.996
Round 1, theta = 0.500: done in 0.05 s, mean overlap 1.001
Round 1, theta = 0.560: done in 0.04 s, mean overlap 1.001
Round 1, theta = 0.620: done in 0.04 s, mean overlap 1.001
Round 1, theta = 0.680: done in 0.04 s, mean overlap 1.001
Maximum overlap achieved by multiple theta values, reporting mean
Full overlap of 1.000 achieved by theta = 0.620 in round 1

THETA SEARCH: 0.620 ACHIEVES MAXIMUM MEAN OVERLAP 1.001

STARTING FINAL SIMULATION
Done in 0.23 s
Mean overlap 0.985 --> 1.001 achieved by theta = 0.620

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/hopfield/test_mclassic.txt
================================================
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.943  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 


================================================
FILE: hippocampus/out/hopfield/test_mcustom.txt
================================================
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 


================================================
FILE: hippocampus/out/hopfield/test_params.txt
================================================
seed             = 54636429

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 100
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 1
n_cue            = 30
cue_type         = 0
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 1
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 7
T_search         = 3
n_search         = 20

theta_max    = 0.620000


================================================
FILE: hippocampus/out/hopfield/test_qcue.txt
================================================
0 12 16 23 27 35 41 44 53 63 65 69 73 74 79 106 117 125 128 150 159 167 220 222 237 254 273 277 292 299 

================================================
FILE: hippocampus/out/hopfield/test_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/hopfield/test_qnu.txt
================================================
4 13 17 21 28 36 37 42 43 45 51 54 65 69 71 96 103 104 105 125 128 129 138 144 151 158 159 163 166 175 177 185 188 195 201 203 211 212 214 220 222 234 239 246 265 266 267 268 276 277 282 285 286 299 300 307 310 311 313 333 336 339 343 359 368 369 373 375 387 389 391 401 406 414 416 431 435 436 447 448 452 457 459 460 463 469 471 476 479 486 487 488 491 493 496 504 505 506 507 509 

================================================
FILE: hippocampus/out/hopfield/test_wsample.txt
================================================
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================================================
FILE: hippocampus/out/oscillation/baseline_a.txt
================================================
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2.98e-02 2.54e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.10e-02 2.20e-02 2.59e-02 3.61e-02 5.57e-02 9.33e-02 1.26e-01 1.79e-01 2.01e-01 2.32e-01 2.41e-01 2.65e-01 2.74e-01 2.77e-01 2.82e-01 2.88e-01 2.90e-01 2.95e-01 3.03e-01 3.07e-01 2.33e-01 1.49e-01 1.25e-01 9.62e-02 8.06e-02 6.45e-02 5.27e-02 4.15e-02 2.98e-02 2.20e-02 2.05e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.00e-02 2.34e-02 3.52e-02 6.88e-02 1.26e-01 1.56e-01 2.01e-01 2.18e-01 2.46e-01 2.50e-01 2.62e-01 2.66e-01 2.71e-01 2.76e-01 2.81e-01 2.78e-01 2.84e-01 2.84e-01 2.84e-01 2.84e-01 2.87e-01 2.22e-01 1.40e-01 1.18e-01 8.98e-02 7.76e-02 6.54e-02 5.96e-02 5.27e-02 5.13e-02 4.79e-02 4.54e-02 4.10e-02 3.86e-02 3.76e-02 3.76e-02 3.76e-02 3.76e-02 3.76e-02 3.76e-02 3.76e-02 5.86e-02 1.13e-01 1.56e-01 2.13e-01 2.31e-01 2.48e-01 2.51e-01 2.69e-01 2.76e-01 2.82e-01 2.85e-01 2.87e-01 2.91e-01 2.96e-01 2.97e-01 2.96e-01 3.00e-01 3.01e-01 3.01e-01 3.05e-01 2.29e-01 1.46e-01 1.26e-01 1.00e-01 8.84e-02 7.42e-02 7.08e-02 6.59e-02 6.45e-02 6.40e-02 6.45e-02 6.05e-02 5.62e-02 5.03e-02 4.98e-02 4.74e-02 4.25e-02 4.00e-02 3.96e-02 3.86e-02 5.18e-02 1.18e-01 1.58e-01 2.24e-01 2.45e-01 2.78e-01 2.84e-01 2.92e-01 2.92e-01 2.98e-01 2.98e-01 3.01e-01 3.03e-01 3.06e-01 3.07e-01 3.06e-01 3.06e-01 3.08e-01 3.10e-01 3.13e-01 2.34e-01 1.46e-01 1.30e-01 1.03e-01 9.08e-02 8.15e-02 7.76e-02 6.93e-02 6.64e-02 6.30e-02 6.01e-02 5.42e-02 5.27e-02 5.37e-02 5.42e-02 5.62e-02 5.62e-02 5.62e-02 5.62e-02 5.62e-02 9.18e-02 1.60e-01 1.91e-01 2.43e-01 2.58e-01 2.84e-01 2.94e-01 2.98e-01 3.00e-01 3.01e-01 3.01e-01 3.05e-01 3.10e-01 3.12e-01 3.12e-01 3.14e-01 3.14e-01 3.16e-01 3.17e-01 3.20e-01 2.41e-01 1.47e-01 1.23e-01 9.18e-02 8.35e-02 7.42e-02 6.84e-02 6.30e-02 5.81e-02 5.47e-02 5.37e-02 5.42e-02 5.42e-02 5.76e-02 5.86e-02 5.91e-02 5.91e-02 5.86e-02 5.91e-02 5.91e-02 9.03e-02 1.59e-01 2.03e-01 2.56e-01 2.65e-01 2.81e-01 2.89e-01 2.96e-01 2.93e-01 3.00e-01 3.01e-01 3.07e-01 3.09e-01 3.10e-01 3.10e-01 3.10e-01 3.12e-01 3.11e-01 3.11e-01 3.08e-01 


================================================
FILE: hippocampus/out/oscillation/baseline_log.txt
================================================

STARTING SIMULATION FOR out/oscillation/baseline
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 50 examples
Theta values: 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 
Testing 30 cues

STARTING SIMULATION
Done in 3.91 s
Mean sparse   overlaps: 0.981 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 1.001 0.992 0.959 0.885 0.801 0.720 0.651 0.597 0.546 0.511 0.483 0.337 0.233 0.152 0.108 0.077 0.067 0.038 0.033 0.026 0.025 0.060 0.167 0.187 0.184 0.182 0.179 0.166 0.153 0.153 0.150 0.111 0.082 0.053 0.036 0.029 0.023 0.019 0.015 0.013 0.013 0.028 0.077 0.110 0.115 0.109 0.107 0.108 0.104 0.110 0.112 0.088 0.059 0.036 0.025 0.017 0.014 0.013 0.011 0.010 0.010 0.031 0.058 0.065 0.061 0.057 0.062 0.069 0.073 0.071 0.072 0.058 0.040 0.028 0.018 0.014 0.009 0.009 0.009 0.009 0.009 0.029 0.051 0.050 0.056 0.057 0.061 0.070 0.071 0.071 0.074 0.053 0.046 0.026 0.023 0.013 0.010 0.007 0.007 0.007 0.007 0.024 0.056 0.072 0.078 0.080 0.082 0.080 0.082 0.082 0.084 
Mean category overlaps: 0.009 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.013 0.033 0.080 0.136 0.172 0.194 0.204 0.210 0.217 0.220 0.131 0.093 0.074 0.055 0.035 0.023 0.011 0.007 0.006 0.006 0.039 0.076 0.104 0.119 0.127 0.131 0.138 0.140 0.141 0.141 0.090 0.069 0.054 0.040 0.027 0.018 0.011 0.008 0.007 0.007 0.040 0.068 0.083 0.088 0.092 0.095 0.098 0.100 0.101 0.103 0.061 0.042 0.033 0.022 0.015 0.012 0.010 0.009 0.009 0.009 0.048 0.072 0.079 0.084 0.085 0.086 0.087 0.088 0.087 0.088 0.051 0.036 0.028 0.020 0.012 0.009 0.008 0.008 0.008 0.008 0.046 0.069 0.075 0.080 0.083 0.085 0.087 0.089 0.089 0.090 0.053 0.039 0.028 0.020 0.013 0.009 0.008 0.008 0.008 0.007 0.045 0.072 0.080 0.083 0.084 0.086 0.088 0.088 0.088 0.088 

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/oscillation/baseline_mcategory.txt
================================================
 0.013  0.004 -0.002 
 0.007 -0.005 -0.008 
 0.009 -0.004 -0.007 
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 0.045 -0.007 -0.016 
 0.082  0.018 -0.034 
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================================================
FILE: hippocampus/out/oscillation/baseline_mother.txt
================================================
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 0.017  0.466 -0.007 -0.057 -0.207 -0.032  0.017  0.167  0.067 -0.082 -0.082 -0.057 -0.007  0.017  0.067  0.117  0.142 -0.132 -0.107 -0.107  0.042  0.017  0.067 -0.107 -0.007 -0.007  0.117 -0.182  0.042 -0.057 -0.032 -0.032 -0.182 -0.157  0.042 -0.132  0.117 -0.007  0.042 -0.082 -0.107  0.167  0.516 -0.007 -0.057  0.391 -0.182 -0.007 -0.132 -0.182 -0.157 -0.157  0.042 -0.182  0.092  0.192  0.067 -0.057 -0.107 -0.032 -0.082  0.117 -0.157 -0.057 -0.057 -0.032 -0.182  0.092 -0.032 -0.082 -0.207  0.092  0.117  0.416  0.217  0.690  0.192  0.491 -0.082 -0.057 -0.232 -0.207 -0.107 -0.057 -0.007  0.192 -0.057 -0.082 -0.082 -0.282  0.017 -0.107  0.142 -0.082  0.341  0.192 -0.007  0.042 -0.057 -0.032 
 0.079  0.428 -0.020 -0.070 -0.220 -0.020 -0.020  0.154  0.104 -0.070 -0.020 -0.045 -0.020 -0.020  0.054  0.104  0.154 -0.145 -0.095 -0.070  0.054  0.029  0.129 -0.095  0.004  0.004  0.154 -0.195  0.054 -0.045 -0.020  0.004 -0.195 -0.170  0.029 -0.120  0.104 -0.020  0.004 -0.070 -0.070  0.154  0.403 -0.020 -0.070  0.403 -0.170 -0.020 -0.170 -0.195 -0.120 -0.120 -0.020 -0.195  0.104  0.154  0.104 -0.045 -0.120  0.004 -0.095  0.104 -0.145 -0.070 -0.095  0.004 -0.170  0.079 -0.070 -0.095 -0.195  0.079  0.129  0.403  0.204  0.677  0.204  0.503 -0.095 -0.045 -0.220 -0.220 -0.095 -0.070  0.004  0.279 -0.070 -0.095 -0.070 -0.294  0.054 -0.095  0.129 -0.070  0.254  0.204  0.004  0.079 -0.070 -0.020 
 0.082  0.356 -0.042 -0.092 -0.217 -0.017 -0.042  0.107  0.157  0.007 -0.017  0.007  0.007  0.007  0.057  0.082  0.182 -0.167 -0.092 -0.092  0.057  0.007  0.082 -0.117 -0.067  0.032  0.257 -0.217  0.057 -0.067 -0.017  0.007 -0.192 -0.217  0.057 -0.142  0.082 -0.017  0.057 -0.042 -0.042  0.157  0.381  0.032 -0.167  0.406 -0.192 -0.017 -0.167 -0.192 -0.067 -0.142 -0.042 -0.217  0.107  0.082  0.107 -0.042 -0.217 -0.042 -0.092  0.107 -0.167 -0.067 -0.167  0.007 -0.192  0.032 -0.067 -0.042 -0.192  0.057  0.132  0.356  0.232  0.580  0.257  0.456 -0.117 -0.117 -0.242 -0.192 -0.067 -0.092  0.007  0.331 -0.092 -0.117 -0.067 -0.267 -0.017 -0.067  0.157 -0.092  0.207  0.207  0.057  0.107 -0.117 -0.042 
 0.079  0.353  0.004 -0.096 -0.195 -0.021 -0.046  0.104  0.178  0.054 -0.021  0.029 -0.046  0.004  0.054  0.079  0.178 -0.170 -0.096 -0.121  0.079  0.004  0.079 -0.145 -0.046  0.054  0.253 -0.245  0.104 -0.096  0.004  0.004 -0.195 -0.245  0.079 -0.170  0.079 -0.046  0.079 -0.021 -0.046  0.153  0.328  0.029 -0.170  0.427 -0.170  0.004 -0.170 -0.170 -0.096 -0.145 -0.071 -0.220  0.104  0.054  0.104 -0.046 -0.220 -0.046 -0.121  0.104 -0.170 -0.096 -0.170  0.004 -0.195  0.029 -0.071 -0.046 -0.195  0.054  0.153  0.353  0.228  0.602  0.228  0.427 -0.121 -0.121 -0.245 -0.195 -0.071 -0.096  0.029  0.353 -0.096 -0.121 -0.071 -0.270 -0.046 -0.071  0.153 -0.096  0.178  0.129  0.054  0.153 -0.121 -0.046 
 0.099  0.323 -0.000 -0.100 -0.150 -0.000 -0.050  0.099  0.149  0.124 -0.025  0.074 -0.025 -0.000  0.049  0.074  0.174 -0.175 -0.025 -0.200  0.074 -0.025  0.074 -0.150 -0.075  0.074  0.298 -0.250  0.099 -0.050  0.049 -0.000 -0.175 -0.225  0.099 -0.225  0.099 -0.050  0.099  0.024 -0.050  0.124  0.274  0.024 -0.200  0.498 -0.175 -0.000 -0.175 -0.175 -0.075 -0.150 -0.075 -0.275  0.124  0.024  0.099 -0.050 -0.225 -0.050 -0.100  0.099 -0.175 -0.100 -0.175 -0.025 -0.175  0.049 -0.025 -0.025 -0.200  0.024  0.149  0.323  0.224  0.572  0.249  0.348 -0.100 -0.125 -0.275 -0.150 -0.075 -0.100  0.024  0.348 -0.100 -0.125 -0.075 -0.275 -0.050 -0.050  0.124 -0.150  0.149  0.124  0.074  0.199 -0.100 -0.100 
 0.096  0.320 -0.004 -0.104 -0.153 -0.029 -0.104  0.096  0.145  0.145 -0.029  0.096  0.046 -0.004  0.046  0.046  0.195 -0.153 -0.004 -0.178  0.096 -0.029  0.071 -0.153 -0.054  0.071  0.295 -0.228  0.096 -0.029  0.096 -0.029 -0.153 -0.228  0.096 -0.228  0.071 -0.054  0.096 -0.004 -0.029  0.121  0.170 -0.004 -0.203  0.494 -0.153  0.021 -0.178 -0.178 -0.054 -0.153 -0.104 -0.278  0.121  0.021  0.096 -0.054 -0.228 -0.079 -0.129  0.096 -0.178 -0.104 -0.203 -0.029 -0.203  0.021 -0.004  0.021 -0.228  0.021  0.121  0.345  0.245  0.569  0.345  0.345 -0.104 -0.104 -0.278 -0.153 -0.079 -0.104  0.021  0.345 -0.104 -0.153 -0.054 -0.253 -0.079 -0.054  0.121 -0.153  0.145  0.121  0.071  0.220 -0.104 -0.104 
 0.068  0.292 -0.006 -0.081 -0.156 -0.031 -0.106  0.068  0.143  0.193 -0.031  0.093  0.068  0.018  0.018  0.018  0.193 -0.181 -0.006 -0.181  0.118 -0.031  0.093 -0.131 -0.056  0.043  0.292 -0.256  0.093 -0.031  0.143 -0.056 -0.156 -0.231  0.093 -0.231  0.093 -0.031  0.093 -0.006 -0.031  0.118  0.068 -0.006 -0.206  0.492 -0.156  0.043 -0.181 -0.181 -0.056 -0.131 -0.131 -0.281  0.118  0.018  0.093 -0.056 -0.231 -0.081 -0.106  0.118 -0.181 -0.081 -0.206 -0.031 -0.206 -0.006 -0.006  0.043 -0.231 -0.031  0.068  0.342  0.243  0.542  0.417  0.342 -0.106 -0.106 -0.281 -0.106 -0.081 -0.131  0.018  0.342 -0.106 -0.156 -0.056 -0.256 -0.106 -0.031  0.143 -0.181  0.093  0.168  0.068  0.218 -0.106 -0.106 
 0.067  0.291  0.017 -0.083 -0.133 -0.033 -0.108  0.067  0.142  0.216 -0.033  0.092  0.067  0.042  0.017  0.017  0.191 -0.157 -0.008 -0.182  0.142 -0.033  0.117 -0.157 -0.058  0.042  0.291 -0.257  0.067 -0.033  0.142 -0.058 -0.157 -0.232  0.166 -0.257  0.092 -0.033  0.092 -0.008 -0.033  0.117  0.042 -0.008 -0.207  0.490 -0.182  0.067 -0.182 -0.182 -0.033 -0.133 -0.133 -0.257  0.117  0.042  0.092 -0.058 -0.232 -0.083 -0.133  0.117 -0.182 -0.058 -0.207 -0.033 -0.207  0.017 -0.008  0.042 -0.232 -0.033  0.067  0.316  0.241  0.540  0.416  0.341 -0.108 -0.083 -0.282 -0.108 -0.083 -0.133  0.017  0.341 -0.083 -0.157 -0.033 -0.232 -0.108 -0.033  0.166 -0.182  0.092  0.142  0.067  0.216 -0.108 -0.108 
 0.093  0.242  0.018 -0.082 -0.132 -0.057 -0.107  0.068  0.118  0.217  0.068  0.093  0.068  0.043  0.043 -0.007  0.192 -0.181 -0.032 -0.206  0.142 -0.032  0.118 -0.156 -0.057  0.043  0.292 -0.231  0.043 -0.032  0.192 -0.082 -0.156 -0.231  0.167 -0.231  0.093  0.018  0.118 -0.007 -0.032  0.043  0.043  0.018 -0.206  0.516 -0.181  0.093 -0.206 -0.181  0.018 -0.132 -0.156 -0.256  0.118  0.018  0.068 -0.057 -0.231 -0.107 -0.156  0.118 -0.156 -0.057 -0.206 -0.057 -0.206 -0.007 -0.007  0.043 -0.231 -0.032  0.068  0.292  0.192  0.441  0.441  0.317 -0.107 -0.057 -0.256 -0.107 -0.057 -0.156  0.018  0.342 -0.107 -0.156 -0.032 -0.206 -0.107 -0.057  0.192 -0.206  0.093  0.142  0.068  0.217 -0.107 -0.132 
 0.094  0.219  0.019 -0.105 -0.130 -0.055 -0.105  0.069  0.119  0.219  0.094  0.144  0.069  0.044  0.044 -0.005  0.169 -0.180 -0.055 -0.205  0.144 -0.030  0.094 -0.155 -0.055  0.044  0.318 -0.230  0.019 -0.030  0.194 -0.055 -0.180 -0.230  0.169 -0.230  0.094  0.019  0.119 -0.005 -0.030  0.044  0.044  0.019 -0.205  0.518 -0.180  0.069 -0.205 -0.180  0.019 -0.105 -0.155 -0.280  0.119  0.019  0.069 -0.055 -0.230 -0.080 -0.180  0.119 -0.155 -0.030 -0.205 -0.030 -0.230 -0.005 -0.005  0.044 -0.255 -0.030  0.069  0.269  0.194  0.393  0.443  0.269 -0.105 -0.030 -0.255 -0.105 -0.080 -0.180  0.019  0.368 -0.105 -0.180 -0.030 -0.205 -0.105 -0.080  0.219 -0.205  0.094  0.144  0.069  0.194 -0.130 -0.130 
 0.095  0.169  0.020 -0.105 -0.130 -0.055 -0.105  0.070  0.120  0.219  0.095  0.169  0.070  0.045  0.020 -0.030  0.169 -0.179 -0.055 -0.204  0.144 -0.030  0.095 -0.154 -0.055  0.045  0.319 -0.229  0.020 -0.030  0.244 -0.080 -0.179 -0.229  0.194 -0.229  0.095  0.020  0.120  0.020 -0.030  0.045  0.045  0.045 -0.204  0.493 -0.204  0.070 -0.204 -0.179  0.095 -0.105 -0.154 -0.254  0.120  0.020  0.070 -0.005 -0.229 -0.030 -0.204  0.144 -0.105 -0.030 -0.204 -0.055 -0.229 -0.005  0.020  0.045 -0.254 -0.030  0.045  0.244  0.194  0.344  0.443  0.244 -0.105 -0.030 -0.254 -0.105 -0.080 -0.179  0.020  0.369 -0.130 -0.179 -0.030 -0.204 -0.105 -0.080  0.269 -0.204  0.070  0.194  0.070  0.194 -0.130 -0.179 
 0.095  0.144  0.020 -0.105 -0.130 -0.055 -0.105  0.070  0.120  0.219  0.095  0.169  0.070  0.045  0.020 -0.030  0.194 -0.179 -0.055 -0.179  0.144 -0.030  0.095 -0.154 -0.055  0.045  0.319 -0.229  0.020 -0.030  0.244 -0.080 -0.179 -0.229  0.194 -0.229  0.070  0.020  0.120  0.020 -0.030  0.045  0.045  0.045 -0.204  0.468 -0.204  0.070 -0.204 -0.179  0.095 -0.105 -0.154 -0.254  0.120  0.020  0.070 -0.005 -0.229 -0.030 -0.204  0.144 -0.105 -0.030 -0.204 -0.080 -0.204 -0.005  0.020  0.045 -0.254 -0.030  0.045  0.244  0.219  0.344  0.443  0.269 -0.105 -0.055 -0.254 -0.105 -0.080 -0.179  0.020  0.369 -0.130 -0.179 -0.030 -0.204 -0.105 -0.080  0.269 -0.204  0.070  0.194  0.070  0.194 -0.130 -0.179 
 0.143  0.143  0.018 -0.106 -0.131 -0.056 -0.106  0.068  0.118  0.218  0.093  0.143  0.043  0.043  0.018 -0.031  0.193 -0.181 -0.056 -0.181  0.143 -0.031  0.093 -0.131 -0.056  0.043  0.317 -0.231  0.018 -0.006  0.243 -0.106 -0.181 -0.231  0.193 -0.231  0.068  0.018  0.118  0.018 -0.031  0.043  0.043  0.043 -0.206  0.467 -0.206  0.068 -0.206 -0.181  0.093 -0.106 -0.156 -0.256  0.143  0.018  0.068  0.018 -0.206 -0.031 -0.181  0.093 -0.081 -0.031 -0.181 -0.081 -0.181 -0.006  0.018  0.043 -0.256 -0.031  0.043  0.243  0.218  0.268  0.442  0.268 -0.131 -0.031 -0.256 -0.081 -0.081 -0.181  0.018  0.367 -0.131 -0.181 -0.031 -0.206 -0.106 -0.106  0.292 -0.206  0.068  0.193  0.093  0.193 -0.131 -0.206 
 0.143  0.143  0.019 -0.106 -0.131 -0.056 -0.106  0.069  0.119  0.218  0.094  0.143  0.044  0.044  0.019 -0.031  0.193 -0.180 -0.056 -0.180  0.143 -0.031  0.094 -0.131 -0.056  0.044  0.318 -0.230  0.019 -0.006  0.243 -0.106 -0.180 -0.230  0.193 -0.230  0.069  0.019  0.119  0.019 -0.031  0.044  0.044  0.044 -0.205  0.467 -0.205  0.069 -0.205 -0.180  0.094 -0.106 -0.155 -0.255  0.143  0.019  0.069  0.019 -0.205 -0.031 -0.155  0.094 -0.081 -0.031 -0.180 -0.081 -0.180 -0.006  0.019  0.044 -0.255 -0.031  0.019  0.243  0.218  0.243  0.442  0.268 -0.131 -0.031 -0.255 -0.081 -0.081 -0.180  0.019  0.368 -0.131 -0.180 -0.031 -0.205 -0.106 -0.106  0.293 -0.205  0.044  0.193  0.094  0.193 -0.131 -0.205 
 0.169  0.144  0.020 -0.105 -0.130 -0.030 -0.105  0.045  0.120  0.194  0.120  0.144  0.045  0.045  0.020 -0.030  0.169 -0.179 -0.055 -0.179  0.144 -0.030  0.095 -0.105 -0.055  0.045  0.319 -0.229  0.020 -0.005  0.244 -0.105 -0.179 -0.229  0.194 -0.229  0.070  0.020  0.120  0.020 -0.030  0.045  0.045  0.070 -0.204  0.468 -0.204  0.070 -0.204 -0.179  0.120 -0.105 -0.154 -0.254  0.144 -0.005  0.070  0.020 -0.204 -0.030 -0.105  0.070 -0.080 -0.055 -0.179 -0.080 -0.229 -0.005  0.020  0.020 -0.254 -0.055  0.020  0.244  0.169  0.169  0.443  0.219 -0.130 -0.030 -0.254 -0.055 -0.080 -0.154  0.020  0.369 -0.130 -0.179 -0.030 -0.204 -0.105 -0.105  0.319 -0.204  0.020  0.194  0.095  0.194 -0.130 -0.204 
 0.136  0.111  0.036 -0.138 -0.063 -0.013 -0.038  0.036  0.136  0.111  0.136  0.036  0.086  0.011 -0.038 -0.013  0.136 -0.188 -0.063 -0.138  0.086 -0.038  0.036 -0.063 -0.063  0.011  0.236 -0.188  0.011 -0.038  0.186 -0.088 -0.188 -0.188  0.136 -0.213  0.011  0.086  0.086  0.011 -0.013 -0.013  0.011  0.036 -0.163  0.460 -0.163 -0.013 -0.163 -0.188  0.111 -0.038 -0.138 -0.188  0.011 -0.013  0.086  0.036 -0.163  0.011 -0.063  0.086 -0.063 -0.063 -0.188 -0.038 -0.213 -0.063  0.011 -0.063 -0.238 -0.013  0.011  0.136  0.136  0.136  0.310  0.136 -0.088 -0.038 -0.213 -0.138 -0.038 -0.138  0.061  0.310 -0.138 -0.138 -0.013 -0.213 -0.038 -0.063  0.335 -0.188  0.061  0.186  0.136  0.211 -0.113 -0.188 
 0.147  0.048  0.073 -0.077 -0.052  0.023 -0.077  0.023  0.172 -0.002  0.123 -0.002  0.098  0.023  0.023  0.048  0.098 -0.127 -0.077 -0.077  0.098 -0.052  0.073 -0.027 -0.027  0.048  0.197 -0.102 -0.002 -0.002  0.123 -0.052 -0.127 -0.151  0.048 -0.127 -0.002  0.123  0.073 -0.002 -0.002  0.048  0.023 -0.002 -0.102  0.422 -0.127 -0.027 -0.077 -0.102  0.073 -0.002 -0.052 -0.151  0.048 -0.027  0.123  0.048 -0.102  0.023 -0.052  0.123 -0.027 -0.027 -0.102 -0.002 -0.127 -0.027  0.048 -0.151 -0.151 -0.002 -0.027  0.147  0.073  0.123  0.297  0.123 -0.002 -0.027 -0.151 -0.176  0.023 -0.077  0.048  0.297 -0.077 -0.102 -0.077 -0.151 -0.027 -0.077  0.272 -0.127  0.123  0.197  0.073  0.172 -0.077 -0.151 
 0.170  0.020  0.095 -0.079 -0.054 -0.004 -0.054  0.070  0.145 -0.054  0.070  0.045  0.095  0.020  0.045  0.070  0.070 -0.104 -0.104 -0.054  0.145 -0.029  0.045 -0.029 -0.004  0.045  0.120 -0.079 -0.004  0.020  0.095 -0.004 -0.129 -0.154  0.070 -0.104 -0.029  0.095  0.020 -0.004  0.020  0.070  0.020  0.020 -0.079  0.319 -0.104 -0.004 -0.054 -0.104  0.070  0.020 -0.029 -0.129  0.045 -0.029  0.145  0.020 -0.104 -0.004 -0.079  0.145 -0.004 -0.029 -0.079 -0.004 -0.104 -0.029  0.020 -0.154 -0.104  0.020 -0.004  0.170  0.045  0.120  0.294  0.095 -0.004 -0.004 -0.129 -0.154  0.020 -0.079  0.045  0.245 -0.054 -0.079 -0.079 -0.154 -0.029 -0.104  0.270 -0.079  0.120  0.195  0.045  0.070 -0.054 -0.129 
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 0.009  0.009  0.134 -0.040 -0.040 -0.040 -0.040  0.059  0.159 -0.015  0.034 -0.065  0.034  0.009  0.009  0.109 -0.015 -0.065 -0.065 -0.015  0.034  0.009 -0.015 -0.015 -0.040  0.084  0.009 -0.065 -0.040 -0.040  0.059 -0.015 -0.090 -0.090 -0.015 -0.040 -0.040  0.159  0.009  0.059 -0.065  0.134  0.034 -0.015 -0.015  0.134 -0.040 -0.015 -0.065 -0.065  0.109  0.009 -0.015 -0.090 -0.040 -0.015  0.159 -0.065 -0.015  0.034 -0.040  0.159  0.009 -0.015 -0.015  0.009 -0.090  0.034  0.059 -0.090 -0.090  0.034 -0.015  0.084  0.059  0.184  0.209  0.084  0.034  0.009 -0.065 -0.090  0.009 -0.040 -0.015  0.084 -0.015 -0.065 -0.065 -0.090  0.009 -0.015  0.184 -0.040  0.034  0.109  0.084  0.109  0.009 -0.090 
-0.005  0.020  0.120 -0.030 -0.030 -0.055 -0.030  0.070  0.169 -0.030  0.020 -0.055  0.045  0.020  0.020  0.120 -0.030 -0.055 -0.055 -0.005 -0.030  0.020 -0.005 -0.005 -0.030  0.070  0.020 -0.055 -0.030 -0.030  0.070 -0.055 -0.080 -0.080 -0.030 -0.030 -0.030  0.144  0.020  0.070 -0.080  0.144  0.020 -0.005 -0.005  0.144 -0.030 -0.030 -0.030 -0.055  0.095 -0.005 -0.005 -0.080 -0.055 -0.030  0.144 -0.055 -0.005  0.020 -0.080  0.194 -0.005 -0.030 -0.005  0.020 -0.080 -0.005  0.070 -0.080 -0.080  0.045 -0.030  0.020  0.070  0.194  0.120  0.070  0.020  0.020 -0.055 -0.080  0.020 -0.030 -0.005  0.095 -0.005 -0.055 -0.080 -0.080  0.020 -0.005  0.144 -0.055  0.045  0.095  0.045  0.070  0.020 -0.080 
-0.018  0.031  0.106 -0.018 -0.043 -0.043 -0.018  0.081  0.131 -0.018  0.031 -0.043  0.031  0.031  0.031  0.106 -0.018 -0.043 -0.068  0.006 -0.018  0.031  0.006  0.006 -0.018  0.056  0.006 -0.043 -0.018 -0.018  0.056 -0.068 -0.068 -0.068 -0.018 -0.018 -0.043  0.131  0.031  0.081 -0.068  0.156  0.031 -0.018  0.006  0.156 -0.018 -0.018 -0.018 -0.068  0.056  0.006  0.006 -0.068 -0.043 -0.043  0.131 -0.043 -0.018  0.006 -0.068  0.181 -0.018 -0.043  0.006  0.006 -0.068 -0.018  0.031 -0.068 -0.068  0.031 -0.043  0.006  0.081  0.181  0.106  0.056  0.031  0.006 -0.043 -0.068  0.006 -0.043  0.006  0.056 -0.018 -0.043 -0.068 -0.068  0.031 -0.018  0.106 -0.018  0.056  0.056  0.056  0.056  0.006 -0.068 
-0.008  0.042  0.092 -0.008 -0.033 -0.033 -0.008  0.092  0.092 -0.008  0.042 -0.033  0.017  0.017  0.042  0.117 -0.008 -0.033 -0.058  0.017 -0.008  0.042  0.017 -0.008 -0.033  0.067  0.017 -0.033 -0.008 -0.033  0.042 -0.058 -0.058 -0.058 -0.008 -0.033 -0.033  0.142  0.042  0.092 -0.058  0.142  0.042 -0.008  0.017  0.142 -0.008 -0.008 -0.033 -0.058  0.042 -0.008  0.017 -0.058 -0.033 -0.033  0.117 -0.033 -0.008 -0.008 -0.058  0.117 -0.033 -0.033 -0.008 -0.008 -0.058 -0.033  0.017 -0.058 -0.058  0.042 -0.033  0.017  0.042  0.142  0.092  0.067  0.042  0.017 -0.033 -0.058 -0.008 -0.033  0.017  0.042  0.017 -0.033 -0.058 -0.058  0.017 -0.033  0.092 -0.008  0.042  0.067  0.017  0.067  0.017 -0.058 
 0.008  0.008  0.058  0.008 -0.016 -0.016  0.008  0.058  0.008 -0.016  0.033 -0.016 -0.016  0.033  0.058  0.108  0.008 -0.016 -0.041  0.033 -0.041  0.033  0.008 -0.016 -0.041  0.033 -0.016 -0.016  0.008 -0.016 -0.041 -0.041 -0.041 -0.041 -0.016 -0.041 -0.041  0.108  0.008  0.033 -0.041  0.108  0.058 -0.016  0.008  0.133 -0.016 -0.016 -0.016 -0.041  0.008 -0.041  0.033 -0.041 -0.016 -0.041  0.108 -0.016  0.008 -0.016 -0.041  0.033 -0.016 -0.041  0.008 -0.016 -0.041 -0.041 -0.016 -0.041 -0.041  0.033 -0.016 -0.016  0.008  0.108  0.083  0.058  0.033  0.008 -0.041 -0.041  0.008 -0.041 -0.041  0.008  0.033 -0.016 -0.041 -0.041  0.033 -0.041  0.058 -0.041  0.033  0.008  0.008  0.033  0.008 -0.041 
 0.021  0.021  0.046  0.021 -0.004 -0.029  0.021  0.046  0.021 -0.004  0.021 -0.004 -0.004  0.046  0.021  0.121  0.021 -0.004 -0.029  0.021 -0.029  0.046  0.021 -0.004 -0.029  0.021 -0.004 -0.004  0.021 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.029 -0.029  0.071  0.021 -0.004 -0.029  0.096  0.046 -0.004 -0.029  0.096 -0.029 -0.029 -0.004 -0.029 -0.004 -0.029  0.046 -0.029 -0.004 -0.029  0.096 -0.029 -0.004 -0.029 -0.029  0.021 -0.004 -0.029 -0.004 -0.004 -0.029 -0.029 -0.004 -0.029 -0.029  0.046 -0.004 -0.029  0.021  0.071  0.071  0.046  0.046 -0.004 -0.029 -0.029  0.021 -0.029 -0.029 -0.004  0.021 -0.029 -0.029 -0.029  0.046 -0.029  0.071 -0.029  0.046  0.021  0.021  0.021  0.021 -0.029 
 0.015  0.015 -0.009  0.015 -0.009 -0.009  0.015  0.015 -0.009 -0.009  0.015 -0.009 -0.009  0.015  0.015  0.040 -0.009 -0.009 -0.009 -0.009 -0.009  0.015 -0.009 -0.009 -0.009  0.015 -0.009 -0.009  0.015 -0.009 -0.009 -0.009 -0.009 -0.009  0.015 -0.009 -0.009  0.040  0.015 -0.009 -0.009  0.015  0.015  0.015 -0.009  0.040 -0.009 -0.009 -0.009 -0.009 -0.009 -0.009  0.015 -0.009 -0.009 -0.009  0.040 -0.009 -0.009 -0.009 -0.009 -0.009 -0.009 -0.009 -0.009  0.015 -0.009 -0.009  0.015 -0.009 -0.009  0.015 -0.009 -0.009  0.015  0.015  0.040  0.015 -0.009 -0.009 -0.009 -0.009  0.015 -0.009 -0.009 -0.009  0.015 -0.009 -0.009 -0.009 -0.009 -0.009  0.015 -0.009  0.040  0.015  0.040  0.015  0.015 -0.009 
 0.018  0.018 -0.007  0.018 -0.007 -0.007  0.018  0.018 -0.007 -0.007  0.018 -0.007 -0.007  0.018  0.018  0.043 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007  0.018  0.018 -0.007 -0.007  0.018  0.018 -0.007 -0.007  0.018 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007 -0.007  0.018 -0.007 -0.007  0.018 -0.007 -0.007  0.018 -0.007 -0.007  0.018 -0.007  0.043  0.018 -0.007 -0.007 -0.007 -0.007  0.018 -0.007 -0.007 -0.007  0.018 -0.007 -0.007 -0.007 -0.007 -0.007  0.018 -0.007  0.043  0.018  0.018 -0.007  0.018 -0.007 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 0.053  0.003  0.028 -0.021  0.003  0.003 -0.046 -0.046 -0.021  0.053 -0.021 -0.021 -0.046  0.003  0.028 -0.021  0.028  0.003  0.053 -0.046  0.003 -0.021 -0.021  0.028 -0.046  0.003 -0.046 -0.021  0.003 -0.021  0.053 -0.021 -0.046 -0.021  0.078 -0.021 -0.021 -0.021  0.053  0.003  0.028 -0.021  0.003 -0.021 -0.046  0.028  0.003  0.053 -0.046  0.028  0.003  0.003 -0.046  0.103  0.003  0.003 -0.021 -0.021 -0.021  0.003 -0.021  0.003  0.003  0.028  0.028 -0.021  0.053  0.028 -0.021 -0.046  0.028 -0.021  0.028  0.078  0.003  0.103 -0.021 -0.021  0.028  0.003  0.028 -0.021 -0.021 -0.021  0.028  0.352 -0.046 -0.046 -0.046  0.003  0.003 -0.021 -0.046 -0.021  0.078  0.053 -0.046 -0.021  0.028 -0.046 
 0.064 -0.010  0.014 -0.010 -0.035  0.064 -0.085 -0.060  0.014  0.064  0.014  0.014 -0.060  0.014  0.014 -0.035  0.064 -0.035  0.039 -0.035  0.039 -0.060 -0.010  0.039 -0.035 -0.035 -0.035  0.014 -0.035  0.139  0.114 -0.060 -0.035 -0.060  0.064 -0.010 -0.035 -0.060  0.064 -0.010  0.039  0.064 -0.035 -0.010 -0.060  0.014  0.014  0.064 -0.060 -0.010  0.064 -0.010 -0.085  0.139 -0.035  0.014 -0.010  0.014 -0.010  0.014 -0.060 -0.035 -0.010  0.114  0.014 -0.060  0.014  0.014  0.014 -0.085  0.014 -0.060  0.039  0.114 -0.035  0.089 -0.060 -0.010  0.039 -0.010  0.064 -0.035 -0.060 -0.060 -0.010  0.612 -0.060 -0.060 -0.035 -0.010 -0.035 -0.035 -0.035 -0.035  0.064  0.089 -0.060 -0.060 -0.010 -0.085 
 0.101  0.051 -0.024  0.001  0.026  0.051 -0.124  0.026 -0.024  0.076  0.026  0.026 -0.074  0.026 -0.024 -0.049  0.051 -0.024  0.001 -0.024  0.001 -0.074  0.076  0.051 -0.024 -0.024  0.001 -0.024 -0.024  0.150  0.175 -0.024 -0.074 -0.074  0.026 -0.049 -0.074 -0.099  0.101  0.026  0.101  0.026 -0.024  0.026 -0.049  0.001  0.001  0.051 -0.099 -0.024  0.101  0.051 -0.124  0.175 -0.074 -0.024  0.076 -0.024  0.026  0.001 -0.049 -0.024 -0.049  0.150 -0.024 -0.099  0.076  0.001  0.051 -0.124  0.026 -0.099  0.001  0.126  0.026  0.126 -0.024  0.026  0.001 -0.024  0.051 -0.049 -0.049 -0.074  0.001  0.699 -0.074 -0.074 -0.024 -0.024 -0.074 -0.049 -0.074  0.026  0.126  0.101 -0.074 -0.024  0.026 -0.099 
 0.030  0.080  0.030 -0.020  0.030  0.030 -0.144  0.030  0.080  0.030  0.080  0.005 -0.045 -0.020 -0.020 -0.020  0.030 -0.020 -0.045 -0.070  0.055 -0.045  0.055  0.005 -0.020 -0.095  0.055 -0.095  0.030  0.105  0.304 -0.045 -0.095 -0.120 -0.020 -0.120 -0.045 -0.020  0.179  0.030  0.055  0.030 -0.045  0.055 -0.095  0.154 -0.045  0.030 -0.169 -0.045  0.130  0.055 -0.144  0.154 -0.120  0.030  0.105  0.005 -0.020  0.005 -0.070 -0.020 -0.095  0.130 -0.120 -0.070  0.030  0.005  0.030 -0.169 -0.020 -0.169  0.030  0.105 -0.020  0.179  0.055  0.055  0.055 -0.070  0.005 -0.095 -0.045 -0.045 -0.070  0.827 -0.120 -0.095 -0.045 -0.070 -0.095 -0.095 -0.070  0.005  0.080  0.154 -0.095 -0.070  0.030 -0.070 
 0.048  0.073  0.048 -0.026 -0.001 -0.001 -0.151  0.048  0.098 -0.001  0.148  0.023 -0.026 -0.076 -0.051  0.073  0.023 -0.026 -0.051 -0.101  0.098  0.023  0.073 -0.026 -0.001 -0.101  0.123 -0.076  0.023  0.098  0.322 -0.026 -0.151 -0.151  0.023 -0.151 -0.076 -0.026  0.273 -0.001  0.023  0.023 -0.026  0.123 -0.126  0.198 -0.026  0.048 -0.201 -0.051  0.148  0.023 -0.101  0.123 -0.051  0.048  0.073  0.023 -0.026  0.023 -0.101 -0.051 -0.101  0.148 -0.151 -0.051 -0.001 -0.026  0.073 -0.176 -0.051 -0.176  0.023  0.123 -0.001  0.198  0.123  0.073  0.098 -0.051 -0.026 -0.101 -0.076 -0.101 -0.076  0.796 -0.126 -0.101 -0.026 -0.101 -0.101 -0.051 -0.076 -0.001  0.023  0.173 -0.076 -0.076  0.073 -0.076 
-0.002  0.047  0.072 -0.077 -0.027 -0.052 -0.177  0.022  0.072 -0.027  0.147  0.047 -0.002 -0.102 -0.102  0.047  0.022 -0.002 -0.102 -0.152  0.147  0.047  0.147 -0.052 -0.077 -0.077  0.172 -0.127  0.022  0.072  0.296 -0.077 -0.177 -0.177  0.022 -0.177 -0.152 -0.002  0.346 -0.002 -0.002 -0.027  0.047  0.147 -0.152  0.247 -0.027  0.072 -0.202 -0.027  0.172 -0.002 -0.127  0.047 -0.052  0.047  0.122  0.047 -0.052  0.047 -0.152 -0.027 -0.077  0.122 -0.152 -0.102 -0.002 -0.077  0.097 -0.177 -0.127 -0.077  0.047  0.122  0.022  0.222  0.097  0.122  0.097 -0.027 -0.052 -0.127 -0.127 -0.102 -0.077  0.720 -0.127 -0.077 -0.002 -0.202 -0.127 -0.027 -0.052 -0.052 -0.002  0.197 -0.027 -0.052  0.047 -0.127 
-0.039  0.085  0.085 -0.089 -0.064 -0.039 -0.189  0.035  0.060 -0.014  0.160  0.060  0.010 -0.114 -0.064  0.060  0.010 -0.064 -0.089 -0.164  0.210  0.085  0.185 -0.039 -0.089 -0.089  0.185 -0.139  0.010  0.035  0.284 -0.064 -0.139 -0.189  0.010 -0.189 -0.114  0.010  0.309 -0.039  0.060 -0.039  0.010  0.185 -0.164  0.309 -0.064  0.060 -0.189 -0.064  0.185 -0.039 -0.139  0.085  0.010  0.010  0.160  0.060 -0.089  0.010 -0.164 -0.039 -0.064  0.085 -0.139 -0.039 -0.064 -0.139  0.110 -0.189 -0.164 -0.114  0.035  0.160 -0.014  0.210  0.135  0.160  0.060  0.010 -0.089 -0.139 -0.139 -0.139 -0.089  0.608 -0.139 -0.114 -0.014 -0.189 -0.089 -0.039  0.035 -0.089  0.035  0.210  0.010  0.035  0.035 -0.139 
 0.010  0.085  0.085 -0.139 -0.114 -0.039 -0.164  0.010  0.060  0.010  0.160  0.135  0.060 -0.064 -0.089  0.035 -0.014 -0.114 -0.089 -0.189  0.185  0.085  0.185 -0.014 -0.089 -0.089  0.210 -0.139  0.010  0.010  0.260 -0.064 -0.164 -0.139 -0.039 -0.214 -0.114  0.035  0.284 -0.089  0.060 -0.039 -0.014  0.235 -0.189  0.309 -0.089  0.085 -0.189 -0.114  0.185 -0.039 -0.114  0.060  0.085  0.060  0.185  0.035 -0.114  0.035 -0.139  0.010  0.035  0.060 -0.164 -0.039 -0.089 -0.139  0.135 -0.189 -0.164 -0.114  0.010  0.185 -0.039  0.185  0.210  0.160  0.035  0.035 -0.114 -0.039 -0.089 -0.139 -0.064  0.559 -0.114 -0.064  0.010 -0.239 -0.064 -0.039  0.160 -0.114  0.035  0.235  0.085  0.110  0.060 -0.164 
 0.012  0.112  0.087 -0.137 -0.137 -0.037 -0.112  0.012  0.087  0.012  0.162  0.137  0.062 -0.062 -0.087  0.037  0.012 -0.137 -0.087 -0.187  0.187  0.087  0.162 -0.012 -0.087 -0.062  0.262 -0.137  0.012  0.012  0.262 -0.062 -0.137 -0.137 -0.037 -0.237 -0.112  0.037  0.286 -0.112  0.062 -0.037 -0.012  0.237 -0.187  0.311 -0.137  0.087 -0.187 -0.162  0.137 -0.037 -0.112  0.037  0.137  0.062  0.162  0.012 -0.137  0.012 -0.137  0.012  0.037  0.062 -0.212 -0.037 -0.137 -0.137  0.112 -0.162 -0.162 -0.112  0.012  0.187 -0.037  0.187  0.262  0.187  0.012  0.037 -0.112 -0.062 -0.087 -0.137 -0.062  0.561 -0.112 -0.087  0.037 -0.237 -0.062 -0.037  0.162 -0.112  0.037  0.212  0.087  0.112  0.062 -0.162 
 0.107  0.107  0.057 -0.142 -0.142 -0.042 -0.117  0.007  0.107  0.032  0.157  0.107  0.082 -0.042 -0.067  0.032  0.007 -0.167 -0.067 -0.192  0.182  0.082  0.157 -0.042 -0.117 -0.042  0.257 -0.117  0.032  0.007  0.257 -0.042 -0.167 -0.142 -0.017 -0.217 -0.117  0.032  0.282 -0.142  0.107 -0.042 -0.017  0.207 -0.167  0.356 -0.142  0.082 -0.167 -0.142  0.132 -0.092 -0.092 -0.042  0.157  0.032  0.157  0.007 -0.142  0.007 -0.142  0.057  0.107  0.007 -0.217 -0.042 -0.167 -0.117  0.032 -0.142 -0.142 -0.092 -0.017  0.232  0.007  0.157  0.331  0.182 -0.042  0.032 -0.142 -0.017 -0.067 -0.142 -0.042  0.481 -0.117 -0.117  0.032 -0.242 -0.067 -0.042  0.182 -0.117  0.057  0.207  0.082  0.132  0.032 -0.167 
 0.132  0.107  0.057 -0.142 -0.142 -0.042 -0.117  0.007  0.107  0.057  0.157  0.107  0.057 -0.042 -0.067  0.032  0.007 -0.167 -0.067 -0.192  0.207  0.082  0.157 -0.042 -0.092 -0.017  0.257 -0.117  0.057  0.007  0.257 -0.017 -0.142 -0.142 -0.017 -0.217 -0.092  0.032  0.232 -0.142  0.107 -0.042  0.007  0.207 -0.167  0.356 -0.167  0.057 -0.167 -0.142  0.132 -0.092 -0.117 -0.067  0.182  0.032  0.132  0.007 -0.192  0.007 -0.142  0.057  0.107  0.007 -0.217 -0.017 -0.192 -0.117  0.032 -0.117 -0.142 -0.092 -0.017  0.257  0.007  0.132  0.381  0.157 -0.067  0.032 -0.167 -0.017 -0.067 -0.142 -0.042  0.456 -0.117 -0.117  0.032 -0.242 -0.092 -0.092  0.182 -0.117  0.032  0.232  0.082  0.132  0.032 -0.217 
 0.156  0.082  0.057 -0.142 -0.142 -0.018 -0.093  0.007  0.107  0.057  0.156  0.107  0.057 -0.068 -0.018  0.032  0.082 -0.142 -0.068 -0.192  0.206  0.082  0.156 -0.043 -0.043 -0.018  0.256 -0.142  0.057  0.007  0.256 -0.018 -0.142 -0.142  0.007 -0.217 -0.118  0.032  0.206 -0.118  0.107 -0.043  0.007  0.206 -0.167  0.356 -0.192  0.032 -0.167 -0.142  0.107 -0.093 -0.118 -0.118  0.181  0.032  0.132  0.007 -0.192  0.007 -0.118  0.057  0.132  0.007 -0.217 -0.043 -0.192 -0.118  0.057 -0.068 -0.118 -0.093 -0.018  0.281  0.057  0.132  0.430  0.156 -0.093  0.032 -0.167 -0.018 -0.093 -0.142 -0.043  0.381 -0.118 -0.118  0.057 -0.217 -0.093 -0.068  0.231 -0.118  0.032  0.231  0.082  0.156  0.032 -0.217 
 0.103  0.053  0.028 -0.121 -0.146 -0.046 -0.071  0.003  0.103  0.078  0.153  0.128  0.053 -0.046 -0.021  0.028  0.153 -0.146 -0.046 -0.196  0.153  0.103  0.153 -0.046 -0.021 -0.021  0.278 -0.146  0.053  0.003  0.253 -0.071 -0.146 -0.146  0.028 -0.246 -0.071  0.028  0.153 -0.121  0.103 -0.021  0.003  0.203 -0.171  0.352 -0.221  0.028 -0.171 -0.146  0.103 -0.096 -0.146 -0.146  0.153  0.028  0.128  0.028 -0.196 -0.021 -0.121  0.053  0.103  0.003 -0.196 -0.046 -0.171 -0.096  0.078 -0.046 -0.121 -0.096 -0.021  0.278  0.053  0.128  0.402  0.203 -0.121  0.028 -0.171 -0.046 -0.071 -0.146 -0.021  0.352 -0.071 -0.121  0.053 -0.196 -0.096 -0.071  0.253 -0.121  0.028  0.228  0.078  0.153  0.028 -0.196 
 0.099  0.049  0.024 -0.100 -0.150 -0.050 -0.075  0.049  0.099  0.099  0.124  0.149  0.074 -0.050 -0.025  0.024  0.174 -0.150 -0.025 -0.200  0.149  0.074  0.149 -0.075 -0.025 -0.025  0.274 -0.150  0.074 -0.025  0.274 -0.125 -0.150 -0.150  0.049 -0.250 -0.075  0.024  0.149 -0.125  0.074  0.024  0.024  0.199 -0.175  0.348 -0.225  0.074 -0.175 -0.150  0.099 -0.125 -0.150 -0.175  0.149  0.024  0.124  0.024 -0.200 -0.025 -0.125  0.049  0.099 -0.025 -0.200 -0.050 -0.175 -0.075  0.074 -0.025 -0.125 -0.100 -0.050  0.298  0.049  0.124  0.398  0.199 -0.125  0.024 -0.175 -0.050 -0.050 -0.150 -0.000  0.323 -0.075 -0.100 -0.000 -0.200 -0.100 -0.050  0.274 -0.150  0.024  0.224  0.074  0.149 -0.000 -0.175 
 0.123  0.048  0.023 -0.101 -0.151 -0.001 -0.076  0.048  0.098  0.148  0.123  0.148  0.073 -0.051 -0.001  0.023  0.148 -0.151 -0.051 -0.201  0.148  0.098  0.148 -0.101 -0.026 -0.001  0.273 -0.151  0.048 -0.026  0.273 -0.126 -0.151 -0.151  0.048 -0.251 -0.076  0.023  0.148 -0.101  0.073  0.048  0.023  0.198 -0.176  0.347 -0.226  0.073 -0.176 -0.151  0.123 -0.126 -0.151 -0.176  0.148  0.023  0.123  0.023 -0.201 -0.026 -0.126  0.048  0.098 -0.026 -0.201 -0.051 -0.201 -0.076  0.073 -0.001 -0.126 -0.076 -0.051  0.273  0.048  0.123  0.397  0.173 -0.126  0.023 -0.176 -0.076 -0.076 -0.151 -0.001  0.322 -0.076 -0.101 -0.001 -0.201 -0.101 -0.051  0.273 -0.151  0.023  0.223  0.073  0.148 -0.001 -0.176 
 0.148  0.074 -0.001 -0.101 -0.150 -0.026 -0.076  0.049  0.099  0.173  0.124  0.173  0.074 -0.051 -0.001  0.024  0.148 -0.126 -0.051 -0.200  0.148  0.074  0.148 -0.101 -0.026 -0.001  0.298 -0.175  0.049 -0.001  0.273 -0.126 -0.150 -0.150  0.099 -0.250 -0.051  0.024  0.124 -0.101  0.049  0.049  0.024  0.198 -0.175  0.348 -0.225  0.074 -0.200 -0.150  0.148 -0.126 -0.150 -0.250  0.148 -0.001  0.124  0.024 -0.200 -0.026 -0.126  0.049  0.099 -0.051 -0.200 -0.051 -0.225 -0.051  0.049 -0.001 -0.150 -0.051 -0.026  0.273  0.049  0.099  0.398  0.198 -0.126  0.024 -0.200 -0.076 -0.076 -0.150 -0.001  0.323 -0.076 -0.126 -0.001 -0.200 -0.101 -0.051  0.273 -0.150  0.024  0.198  0.074  0.148 -0.051 -0.200 
 0.171  0.071 -0.003 -0.103 -0.153 -0.028 -0.053  0.046  0.096  0.171  0.121  0.171  0.071 -0.053 -0.003  0.021  0.146 -0.103 -0.053 -0.203  0.146  0.071  0.146 -0.078 -0.028  0.021  0.295 -0.178  0.046 -0.003  0.271 -0.128 -0.153 -0.153  0.121 -0.253 -0.053  0.021  0.121 -0.128  0.046  0.021  0.021  0.196 -0.178  0.345 -0.228  0.096 -0.203 -0.128  0.121 -0.128 -0.128 -0.253  0.146 -0.003  0.096  0.021 -0.203 -0.028 -0.128  0.046  0.096 -0.053 -0.203 -0.053 -0.253 -0.053  0.071 -0.003 -0.153 -0.053 -0.003  0.271  0.046  0.096  0.395  0.196 -0.128  0.021 -0.203 -0.053 -0.078 -0.153 -0.003  0.320 -0.078 -0.103 -0.003 -0.203 -0.103 -0.053  0.295 -0.153  0.021  0.196  0.096  0.171 -0.078 -0.203 
 0.197  0.097 -0.002 -0.102 -0.152 -0.027 -0.052  0.047  0.097  0.222  0.122  0.172  0.072 -0.052 -0.002  0.022  0.147 -0.077 -0.052 -0.177  0.097  0.047  0.172 -0.077 -0.027  0.022  0.296 -0.177  0.022 -0.002  0.272 -0.127 -0.152 -0.152  0.147 -0.252 -0.052  0.022  0.122 -0.102  0.047 -0.002  0.047  0.197 -0.177  0.371 -0.227  0.097 -0.202 -0.127  0.097 -0.127 -0.127 -0.252  0.147 -0.002  0.097  0.022 -0.202 -0.027 -0.127  0.047  0.097 -0.052 -0.177 -0.052 -0.252 -0.052  0.072 -0.002 -0.177 -0.052  0.022  0.272  0.047  0.097  0.396  0.197 -0.127  0.022 -0.202 -0.052 -0.077 -0.152 -0.027  0.346 -0.077 -0.077 -0.002 -0.202 -0.102 -0.052  0.296 -0.152  0.022  0.197  0.097  0.197 -0.102 -0.202 
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 0.093  0.068  0.068 -0.082 -0.032 -0.057 -0.057  0.167  0.093 -0.032  0.043  0.043  0.093  0.018 -0.007  0.068  0.068 -0.082 -0.107 -0.057  0.118 -0.032  0.068  0.018 -0.007  0.043  0.043 -0.057  0.093  0.043  0.043 -0.007 -0.156 -0.156  0.093 -0.082 -0.032  0.118  0.018 -0.007 -0.057  0.068  0.018  0.018 -0.082  0.167 -0.107 -0.032 -0.082 -0.107  0.118 -0.032 -0.057 -0.156  0.093 -0.032  0.167 -0.032 -0.082  0.043 -0.057  0.167  0.018 -0.032 -0.082  0.018 -0.107 -0.032  0.018 -0.107 -0.107 -0.007  0.018  0.192  0.093  0.192  0.267  0.142 -0.032 -0.007 -0.107 -0.007  0.018 -0.032  0.068  0.142 -0.032 -0.082 -0.107 -0.132 -0.032 -0.082  0.242 -0.057  0.142  0.142  0.043  0.118 -0.032 -0.132 
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 0.073  0.023  0.073 -0.077 -0.027 -0.027 -0.077  0.073  0.123 -0.052  0.048  0.023  0.073 -0.002 -0.002  0.073 -0.027 -0.077 -0.102 -0.027  0.098 -0.002 -0.002 -0.002 -0.077  0.073  0.023 -0.052  0.023  0.048  0.023 -0.027 -0.127 -0.127 -0.027 -0.052 -0.052  0.123 -0.027  0.023 -0.052  0.098  0.073  0.048 -0.052  0.172 -0.077 -0.027 -0.027 -0.077  0.147 -0.002 -0.027 -0.127  0.048 -0.002  0.172 -0.052 -0.027  0.073 -0.077  0.172  0.023 -0.027 -0.077 -0.002 -0.077 -0.002  0.048 -0.127 -0.102  0.023 -0.027  0.172  0.073  0.247  0.222  0.147 -0.002  0.023 -0.077 -0.102  0.048 -0.002  0.048  0.073 -0.027 -0.052 -0.077 -0.127 -0.027 -0.052  0.222 -0.052  0.147  0.123  0.048  0.073 -0.027 -0.102 
 0.013  0.038  0.063 -0.062 -0.037 -0.062 -0.062  0.038  0.138 -0.037  0.038 -0.037  0.038  0.013 -0.012  0.088 -0.062 -0.062 -0.087 -0.012  0.038  0.013  0.013  0.013 -0.062  0.063  0.013 -0.037  0.013  0.013  0.038 -0.037 -0.112 -0.112 -0.037 -0.037 -0.037  0.138 -0.012  0.038 -0.087  0.113  0.038  0.038 -0.037  0.138 -0.062 -0.012 -0.012 -0.062  0.162 -0.012 -0.037 -0.112  0.038  0.013  0.187 -0.062 -0.037  0.088 -0.062  0.162  0.038 -0.037 -0.062 -0.012 -0.062  0.013  0.063 -0.112 -0.087  0.038 -0.012  0.138  0.038  0.237  0.237  0.113  0.013 -0.012 -0.062 -0.087  0.013 -0.012 -0.012  0.088 -0.037 -0.062 -0.062 -0.112 -0.012 -0.037  0.237 -0.037  0.063  0.113  0.063  0.088 -0.012 -0.112 
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 0.003  0.078  0.078 -0.047 -0.047 -0.072 -0.047  0.053  0.152 -0.047  0.028 -0.047  0.028  0.003  0.003  0.103 -0.047 -0.047 -0.072 -0.022  0.003  0.003  0.003  0.028 -0.047  0.053  0.003 -0.047  0.003  0.003  0.053 -0.047 -0.097 -0.097 -0.047 -0.022 -0.047  0.152  0.003  0.053 -0.097  0.128  0.053  0.053 -0.022  0.128 -0.047 -0.022 -0.022 -0.072  0.078 -0.022 -0.022 -0.097  0.028 -0.047  0.177 -0.072 -0.022  0.078 -0.097  0.152  0.053 -0.072 -0.047  0.003 -0.097  0.003  0.053 -0.097 -0.097  0.053 -0.022  0.053  0.053  0.227  0.128  0.078  0.028  0.003 -0.047 -0.097  0.028 -0.047 -0.022  0.053 -0.022 -0.072 -0.047 -0.097  0.003 -0.047  0.152 -0.022  0.078  0.103  0.053  0.028  0.003 -0.097 
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-0.016  0.083  0.108 -0.016 -0.066 -0.041 -0.016  0.083  0.133 -0.016  0.083 -0.016  0.008  0.033  0.033  0.108 -0.016 -0.016 -0.066  0.008 -0.016  0.058  0.008 -0.041 -0.041  0.108 -0.041  0.008 -0.016  0.008  0.008 -0.041 -0.066 -0.066 -0.016  0.033 -0.066  0.183  0.033  0.083 -0.066  0.158  0.058  0.058  0.033  0.183  0.033 -0.016 -0.041 -0.066  0.008 -0.041  0.008 -0.041 -0.066 -0.041  0.033 -0.041 -0.041  0.008 -0.066  0.108 -0.041 -0.041 -0.016  0.008 -0.066 -0.016 -0.016 -0.066 -0.066  0.008 -0.016 -0.041  0.033  0.208  0.033  0.058  0.058 -0.016  0.008 -0.066  0.058 -0.041  0.083  0.058  0.008 -0.041 -0.066 -0.066 -0.016 -0.066  0.033 -0.016  0.033  0.083 -0.016  0.008 -0.016 -0.016 
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 0.006  0.056  0.031  0.006 -0.043 -0.018 -0.018  0.056 -0.018 -0.043  0.031  0.006 -0.018  0.056  0.031  0.081 -0.043 -0.018 -0.043  0.006 -0.043  0.031 -0.018 -0.018 -0.018  0.056 -0.043  0.006  0.006  0.006 -0.018 -0.018 -0.043 -0.043  0.006  0.006 -0.043  0.181 -0.018  0.006 -0.043  0.106  0.006  0.031  0.006  0.131  0.031 -0.018 -0.018 -0.043  0.031 -0.043  0.006 -0.018 -0.043 -0.018  0.006 -0.018 -0.018 -0.018 -0.043  0.056 -0.018 -0.018 -0.018 -0.018 -0.043 -0.018 -0.018 -0.043 -0.043  0.006 -0.043 -0.018  0.006  0.106  0.031  0.031  0.006 -0.043  0.006 -0.043  0.031 -0.018  0.006  0.006 -0.018 -0.043 -0.043 -0.043 -0.043 -0.018  0.006 -0.018  0.031  0.031 -0.018 -0.018 -0.018  0.031 
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 0.006  0.031 -0.018  0.006 -0.018 -0.018 -0.018  0.006 -0.018 -0.018  0.006 -0.018 -0.018  0.006 -0.018  0.056 -0.018 -0.018 -0.018  0.006 -0.018  0.006 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018  0.006 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018  0.031  0.006  0.006 -0.018  0.056  0.006 -0.018  0.006  0.106 -0.018  0.006 -0.018 -0.018  0.006 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018  0.006 -0.018 -0.018  0.006  0.006  0.006  0.006  0.006 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018  0.006 -0.018  0.031  0.006  0.006 -0.018 -0.018 -0.018 -0.018  0.031 -0.018 -0.018  0.006  0.006 -0.018 -0.018 -0.018 -0.018  0.006 -0.018  0.006  0.031  0.006 -0.018 -0.018  0.006  0.006 
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 0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.054  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020 -0.020 -0.020 -0.020 
 0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.054  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020 -0.020 -0.020 -0.020 
 0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.054  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020 -0.020 -0.020 -0.020 
 0.028  0.028 -0.021  0.003 -0.021  0.003 -0.021 -0.021 -0.021 -0.021 -0.021  0.003  0.003 -0.021 -0.021  0.028  0.003 -0.021 -0.021 -0.021  0.028 -0.021  0.003  0.003 -0.021 -0.021  0.003  0.028  0.053  0.003  0.003 -0.021  0.003  0.003 -0.021  0.028 -0.021  0.078  0.003  0.003 -0.021 -0.021 -0.021 -0.021 -0.021  0.028  0.028 -0.021 -0.021  0.003  0.053  0.003  0.003 -0.021 -0.021  0.003  0.053  0.003 -0.021  0.003 -0.021 -0.021  0.028  0.003  0.003 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021  0.003  0.003  0.028  0.003 -0.021  0.028  0.003 -0.021 -0.021 -0.021  0.003  0.003 -0.021  0.028  0.003  0.003  0.028  0.003  0.003 -0.021  0.003 -0.021  0.028  0.003  0.053 -0.021 -0.021 -0.021 -0.021 
 0.028  0.028 -0.022  0.003 -0.022  0.003 -0.022 -0.022 -0.022 -0.022 -0.022  0.003  0.003 -0.022 -0.022  0.028  0.003 -0.022 -0.022 -0.022  0.028 -0.022  0.003  0.003 -0.022 -0.022  0.003  0.028  0.053  0.003  0.003 -0.022  0.003  0.003 -0.022  0.028 -0.022  0.078  0.003  0.003 -0.022 -0.022 -0.022 -0.022 -0.022  0.028  0.028 -0.022 -0.022  0.003  0.053  0.003  0.003 -0.022 -0.022  0.003  0.053  0.028 -0.022  0.003 -0.022 -0.022  0.028  0.003  0.003 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022  0.003  0.003  0.028  0.003 -0.022  0.028  0.003 -0.022 -0.022 -0.022  0.003  0.003 -0.022  0.028  0.003  0.003  0.028  0.003  0.003 -0.022  0.003 -0.022  0.028  0.028  0.053 -0.022 -0.022 -0.022 -0.022 
 0.022  0.022 -0.028  0.022 -0.028 -0.003 -0.028 -0.028 -0.028 -0.028 -0.028  0.047  0.022 -0.028 -0.028  0.022  0.047 -0.003 -0.028 -0.028  0.022 -0.028 -0.003 -0.003 -0.028 -0.028 -0.003  0.022  0.097 -0.003  0.022 -0.028 -0.003 -0.003 -0.028  0.022 -0.028  0.072 -0.003 -0.003 -0.028 -0.003 -0.028 -0.028 -0.003  0.022  0.022 -0.028 -0.028 -0.003  0.047 -0.003 -0.003 -0.028 -0.028 -0.003  0.072  0.022 -0.028 -0.003 -0.003 -0.028  0.047 -0.003 -0.003 -0.028 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.003  0.047  0.022 -0.028  0.022 -0.003 -0.028 -0.003 -0.028 -0.003  0.047 -0.028  0.022 -0.003  0.022  0.047 -0.003 -0.003 -0.028 -0.003 -0.028  0.022  0.047  0.072 -0.028 -0.028 -0.028 -0.028 
 0.022  0.022 -0.053  0.022 -0.053 -0.028 -0.028 -0.053 -0.028 -0.028 -0.053  0.097  0.047 -0.053 -0.053  0.022  0.122  0.022 -0.003 -0.053  0.022 -0.028 -0.028 -0.003 -0.003 -0.028 -0.028  0.097  0.097  0.047  0.122 -0.003  0.072 -0.028 -0.028  0.022 -0.053  0.047 -0.003 -0.028  0.022 -0.003 -0.053 -0.003 -0.003  0.022  0.022 -0.028 -0.053 -0.028  0.072 -0.003 -0.028 -0.053 -0.053 -0.003  0.072  0.047 -0.028  0.047 -0.028  0.022  0.022 -0.003 -0.028 -0.053 -0.028 -0.028 -0.053 -0.028 -0.053 -0.028 -0.003  0.047 -0.003 -0.003  0.022 -0.028 -0.003 -0.028  0.022  0.022  0.072 -0.028  0.022 -0.028  0.022  0.072  0.022 -0.003 -0.028  0.022 -0.028 -0.003  0.047  0.246 -0.053 -0.053 -0.028 -0.028 
 0.029  0.029 -0.046  0.004 -0.046 -0.021 -0.046 -0.071  0.004 -0.046 -0.071  0.129  0.029 -0.071 -0.046  0.004  0.129  0.079  0.004 -0.071  0.004 -0.046  0.029 -0.021 -0.021 -0.021 -0.021  0.079  0.104  0.029  0.153  0.004  0.079 -0.021 -0.046  0.004 -0.071  0.029 -0.021 -0.046  0.029 -0.021  0.004  0.004 -0.021  0.054  0.029 -0.021 -0.046 -0.046  0.104  0.029 -0.021 -0.071 -0.071  0.004  0.054  0.029 -0.021  0.129 -0.021  0.029  0.029  0.029 -0.046 -0.021 -0.046 -0.046 -0.071 -0.046 -0.071 -0.046  0.004  0.104 -0.021  0.029  0.004 -0.046 -0.021  0.029  0.029  0.029  0.079 -0.046  0.004  0.054  0.029  0.054  0.029 -0.021 -0.046  0.029 -0.046 -0.021  0.104  0.403 -0.046 -0.046 -0.021 -0.046 
 0.056  0.081 -0.043  0.031 -0.043 -0.068 -0.093 -0.043 -0.043 -0.093 -0.118  0.181 -0.018 -0.093 -0.043 -0.043  0.156  0.081  0.006 -0.093  0.056 -0.043  0.006  0.056 -0.018 -0.068 -0.068  0.056  0.156  0.031  0.231 -0.043  0.056 -0.043 -0.018 -0.018 -0.093 -0.018  0.031 -0.068  0.006 -0.043 -0.043  0.056 -0.043  0.181  0.006 -0.043 -0.043 -0.068  0.156  0.081 -0.068 -0.093 -0.093  0.006  0.081  0.006  0.006  0.156 -0.018  0.006  0.031 -0.018 -0.068 -0.018 -0.018 -0.068 -0.068 -0.043 -0.118 -0.068 -0.018  0.156  0.056  0.031 -0.018 -0.043  0.006  0.006  0.006 -0.018  0.106 -0.043 -0.018  0.106  0.006  0.131  0.031 -0.068 -0.093  0.031 -0.068 -0.018  0.131  0.853 -0.043 -0.093 -0.043 -0.093 
 0.069  0.119 -0.030  0.019  0.019 -0.005 -0.130 -0.080 -0.030 -0.105 -0.130  0.119 -0.005 -0.105 -0.005 -0.030  0.219  0.044 -0.005 -0.080  0.044 -0.080 -0.005  0.094 -0.055 -0.080 -0.105  0.069  0.144  0.044  0.244 -0.080  0.069 -0.055 -0.080 -0.030 -0.130 -0.055  0.119 -0.105 -0.005 -0.005 -0.005  0.094 -0.055  0.144  0.019 -0.030 -0.030 -0.105  0.244  0.044 -0.105 -0.105 -0.105  0.019  0.144  0.044  0.019  0.244 -0.030 -0.030  0.044 -0.055 -0.080 -0.030 -0.005 -0.080 -0.080 -0.055 -0.155 -0.055 -0.055  0.393  0.069  0.044 -0.030 -0.030 -0.030 -0.030  0.019 -0.005  0.094 -0.030 -0.030  0.144 -0.030  0.094 -0.005 -0.105 -0.105  0.044 -0.080 -0.080  0.144  0.842 -0.055 -0.105 -0.055 -0.130 
 0.086  0.111 -0.039  0.011 -0.014 -0.014 -0.089 -0.039 -0.039 -0.139 -0.139  0.136 -0.039 -0.089  0.011 -0.064  0.185  0.036  0.011 -0.139  0.061 -0.064  0.036  0.086 -0.114 -0.064 -0.064  0.036  0.185  0.036  0.210 -0.089  0.036 -0.064 -0.114 -0.014 -0.188 -0.014  0.136 -0.089 -0.014 -0.014 -0.039  0.136 -0.039  0.210  0.086 -0.039 -0.014 -0.089  0.235 -0.014 -0.064 -0.089 -0.114 -0.014  0.235  0.061  0.011  0.235 -0.064 -0.014  0.086 -0.064 -0.064 -0.064 -0.064 -0.089 -0.089 -0.089 -0.163 -0.039 -0.064  0.434  0.086  0.086  0.011  0.011  0.036 -0.039  0.061 -0.014  0.086 -0.064 -0.039  0.185 -0.039  0.111  0.011 -0.163 -0.139  0.061 -0.089 -0.114  0.210  0.808 -0.089 -0.114 -0.064 -0.114 
 0.111  0.086 -0.064  0.036 -0.014  0.036 -0.114 -0.039 -0.014 -0.139 -0.114  0.111 -0.014 -0.089  0.036 -0.064  0.185  0.011 -0.039 -0.139  0.061 -0.014  0.036  0.111 -0.139 -0.064 -0.089  0.011  0.160  0.036  0.210 -0.114 -0.014 -0.089 -0.139 -0.014 -0.213  0.086  0.160 -0.114 -0.014  0.036 -0.064  0.136 -0.064  0.185  0.111 -0.014 -0.039 -0.114  0.235 -0.064 -0.089 -0.114 -0.114  0.011  0.235  0.036 -0.014  0.210 -0.114 -0.014  0.160 -0.089 -0.089 -0.064 -0.089 -0.039 -0.114 -0.089 -0.139 -0.064 -0.089  0.434  0.061  0.061  0.061  0.011  0.011 -0.039  0.011  0.036  0.061 -0.089  0.036  0.185 -0.039  0.061  0.011 -0.188 -0.163  0.036 -0.139 -0.139  0.210  0.709 -0.064 -0.114 -0.089 -0.139 
 0.123  0.073 -0.027 -0.002 -0.052  0.023 -0.077 -0.002  0.073 -0.077 -0.052  0.098 -0.027 -0.077 -0.027 -0.027  0.172  0.023 -0.027 -0.151  0.098  0.073  0.098  0.073 -0.102 -0.027 -0.052 -0.027  0.073  0.023  0.172 -0.077 -0.077 -0.151 -0.127 -0.052 -0.176  0.147  0.172 -0.127  0.023  0.048 -0.052  0.172 -0.127  0.247  0.098  0.048 -0.027 -0.127  0.197 -0.102 -0.151 -0.102 -0.077 -0.027  0.247  0.023  0.023  0.147 -0.127  0.023  0.172 -0.102 -0.127 -0.102 -0.077 -0.052 -0.052 -0.102 -0.127 -0.077 -0.127  0.322  0.098  0.073  0.048  0.098  0.023 -0.002 -0.002  0.023  0.023 -0.151 -0.027  0.247 -0.027  0.023 -0.002 -0.226 -0.102 -0.027 -0.052 -0.151  0.172  0.596 -0.077 -0.077 -0.102 -0.176 
 0.281  0.057 -0.043 -0.018 -0.093  0.007 -0.068  0.032  0.082 -0.093  0.007  0.082 -0.018 -0.093  0.007  0.032  0.181 -0.018 -0.068 -0.167  0.082  0.082  0.132  0.032 -0.142 -0.043 -0.043 -0.043  0.057 -0.018  0.206 -0.068 -0.093 -0.142 -0.118 -0.043 -0.192  0.181  0.231 -0.118  0.032  0.032  0.007  0.156 -0.142  0.281  0.057  0.057 -0.018 -0.167  0.206 -0.093 -0.093 -0.142 -0.018 -0.043  0.256  0.007 -0.018  0.132 -0.118  0.057  0.181 -0.068 -0.118 -0.118 -0.093 -0.068 -0.043 -0.043 -0.167 -0.093 -0.118  0.281  0.132  0.082  0.032  0.082  0.007  0.007 -0.018  0.032  0.032 -0.167 -0.018  0.256 -0.043  0.007 -0.018 -0.192 -0.068 -0.068  0.032 -0.142  0.156  0.580 -0.068 -0.018 -0.118 -0.192 
 0.266  0.042 -0.058  0.017 -0.108 -0.008 -0.058  0.042  0.142 -0.083  0.042  0.067 -0.033 -0.083  0.017  0.017  0.191 -0.058 -0.083 -0.207  0.067  0.092  0.142  0.042 -0.133 -0.058  0.042 -0.058  0.017 -0.033  0.191 -0.083 -0.108 -0.157 -0.108 -0.083 -0.182  0.166  0.191 -0.108  0.067  0.042 -0.008  0.216 -0.133  0.291  0.042  0.092 -0.083 -0.133  0.216 -0.133 -0.083 -0.182  0.017 -0.033  0.216  0.017 -0.108  0.067 -0.083  0.042  0.216 -0.058 -0.133 -0.133 -0.133 -0.083  0.042 -0.033 -0.157 -0.083 -0.108  0.191  0.117  0.092  0.042  0.092 -0.008 -0.008 -0.058  0.017 -0.033 -0.182 -0.033  0.316 -0.058 -0.058 -0.033 -0.207 -0.058 -0.108  0.117 -0.182  0.142  0.440 -0.033  0.042 -0.108 -0.182 
 0.210  0.060 -0.039  0.035 -0.139 -0.014 -0.064  0.035  0.135 -0.089  0.060  0.060 -0.039 -0.089 -0.014  0.035  0.185 -0.064 -0.089 -0.214  0.085  0.110  0.160  0.035 -0.139 -0.064  0.060 -0.089  0.010 -0.014  0.185 -0.064 -0.064 -0.164 -0.064 -0.089 -0.189  0.160  0.260 -0.114  0.085  0.060  0.010  0.210 -0.139  0.309  0.035  0.085 -0.114 -0.139  0.210 -0.089 -0.064 -0.164  0.010 -0.064  0.210  0.010 -0.114  0.010 -0.089  0.085  0.210 -0.064 -0.164 -0.114 -0.139 -0.089  0.060 -0.039 -0.164 -0.089 -0.114  0.185  0.110  0.085  0.035  0.060 -0.014  0.010 -0.114  0.010 -0.014 -0.164 -0.014  0.309 -0.064 -0.039 -0.014 -0.214 -0.064 -0.089  0.110 -0.139  0.135  0.434 -0.039  0.060 -0.089 -0.189 
 0.177  0.053 -0.022  0.003 -0.146 -0.022 -0.047  0.028  0.128 -0.097  0.078  0.028 -0.022 -0.097 -0.047  0.053  0.202 -0.072 -0.122 -0.221  0.128  0.152  0.152  0.028 -0.122 -0.047  0.103 -0.122  0.003 -0.047  0.227 -0.072 -0.097 -0.146 -0.072 -0.122 -0.146  0.152  0.227 -0.122  0.128  0.053  0.053  0.202 -0.122  0.327  0.003  0.103 -0.122 -0.146  0.227 -0.097 -0.072 -0.171  0.028 -0.097  0.177  0.028 -0.146  0.003 -0.097  0.078  0.202 -0.072 -0.146 -0.097 -0.171 -0.122  0.103 -0.022 -0.146 -0.097 -0.122  0.202  0.103  0.078  0.028  0.053 -0.047  0.003 -0.122  0.003 -0.047 -0.171 -0.022  0.302 -0.072  0.003  0.003 -0.246 -0.047 -0.072  0.128 -0.097  0.078  0.352 -0.022  0.078 -0.047 -0.171 
 0.176  0.102 -0.023  0.002 -0.147 -0.023 -0.048  0.027  0.127 -0.073  0.102  0.027 -0.023 -0.098 -0.048  0.052  0.176 -0.073 -0.123 -0.197  0.127  0.151  0.151  0.002 -0.123 -0.048  0.127 -0.123  0.027 -0.023  0.276 -0.073 -0.098 -0.123  0.027 -0.123 -0.123  0.151  0.226 -0.123  0.127  0.052  0.052  0.201 -0.123  0.301 -0.023  0.127 -0.098 -0.147  0.201 -0.098 -0.073 -0.197  0.052 -0.073  0.176  0.077 -0.147  0.002 -0.098  0.052  0.201 -0.073 -0.147 -0.073 -0.147 -0.098  0.151 -0.023 -0.147 -0.073 -0.098  0.201  0.102  0.127  0.052  0.052 -0.048  0.027 -0.123  0.002 -0.098 -0.172  0.027  0.301 -0.073  0.002 -0.023 -0.222 -0.048 -0.073  0.151 -0.098  0.052  0.326 -0.023  0.077 -0.023 -0.147 
 0.178  0.128  0.003 -0.021 -0.146 -0.021 -0.046  0.053  0.128 -0.046  0.103  0.003  0.003 -0.096 -0.046  0.053  0.078 -0.071 -0.096 -0.196  0.103  0.153  0.153 -0.021 -0.096 -0.046  0.128 -0.121  0.053 -0.021  0.278 -0.071 -0.146 -0.146  0.028 -0.146 -0.121  0.103  0.228 -0.146  0.103  0.028  0.053  0.203 -0.121  0.302 -0.071  0.103 -0.146 -0.146  0.228 -0.096 -0.096 -0.171  0.053 -0.071  0.178  0.078 -0.146  0.003 -0.121  0.053  0.153 -0.071 -0.146 -0.071 -0.196 -0.046  0.178 -0.021 -0.121 -0.046 -0.071  0.203  0.103  0.153  0.078  0.028 -0.071  0.028 -0.121 -0.021 -0.096 -0.146  0.053  0.302 -0.071  0.003 -0.021 -0.196 -0.096 -0.096  0.203 -0.096  0.053  0.278  0.003  0.078 -0.046 -0.146 
 0.200  0.125  0.000 -0.074 -0.149 -0.024 -0.049  0.050  0.125  0.000  0.100  0.000  0.000 -0.049 -0.049  0.050  0.075 -0.074 -0.074 -0.199  0.100  0.150  0.150 -0.024 -0.049 -0.024  0.125 -0.124  0.050  0.000  0.275 -0.099 -0.174 -0.124  0.050 -0.199 -0.049  0.100  0.200 -0.149  0.100  0.050  0.050  0.175 -0.124  0.299 -0.074  0.100 -0.174 -0.124  0.225 -0.099 -0.099 -0.174  0.050 -0.074  0.175  0.050 -0.149  0.000 -0.149  0.050  0.125 -0.074 -0.149 -0.049 -0.174 -0.049  0.200 -0.024 -0.099 -0.049 -0.049  0.200  0.075  0.150  0.125  0.025 -0.074  0.050 -0.124 -0.024 -0.099 -0.174  0.075  0.299 -0.074  0.025 -0.024 -0.199 -0.074 -0.099  0.200 -0.099  0.050  0.275  0.025  0.050 -0.049 -0.149 
 0.223  0.124 -0.001 -0.126 -0.150 -0.026 -0.051  0.049  0.124  0.024  0.099 -0.001  0.049 -0.051 -0.076  0.049  0.024 -0.076 -0.076 -0.175  0.074  0.173  0.148 -0.026 -0.001 -0.026  0.124 -0.126  0.049 -0.001  0.273 -0.101 -0.175 -0.126  0.049 -0.200 -0.051  0.099  0.198 -0.150  0.099  0.024  0.049  0.173 -0.150  0.298 -0.076  0.074 -0.175 -0.126  0.223 -0.101 -0.076 -0.175  0.099 -0.051  0.148  0.049 -0.175 -0.001 -0.150  0.024  0.124 -0.076 -0.150 -0.051 -0.175 -0.051  0.223 -0.026 -0.101 -0.051 -0.051  0.223  0.074  0.148  0.223  0.024 -0.076  0.074 -0.126 -0.026 -0.076 -0.175  0.074  0.273 -0.076  0.024 -0.026 -0.200 -0.051 -0.051  0.223 -0.126  0.049  0.273  0.049  0.049 -0.051 -0.150 
 0.198  0.124 -0.001 -0.126 -0.150 -0.026 -0.051  0.049  0.124  0.024  0.074 -0.001  0.049 -0.051 -0.076  0.049  0.024 -0.051 -0.076 -0.175  0.074  0.148  0.148 -0.026 -0.001 -0.026  0.124 -0.126  0.049 -0.001  0.273 -0.126 -0.175 -0.126  0.049 -0.200 -0.051  0.099  0.173 -0.150  0.074  0.074  0.049  0.173 -0.150  0.298 -0.126  0.074 -0.175 -0.126  0.223 -0.126 -0.076 -0.175  0.099 -0.026  0.173  0.049 -0.175 -0.001 -0.150  0.024  0.124 -0.076 -0.150 -0.051 -0.175 -0.051  0.198 -0.026 -0.101 -0.076 -0.051  0.223  0.049  0.148  0.248  0.024 -0.101  0.074 -0.150 -0.026 -0.076 -0.175  0.049  0.273 -0.076  0.024 -0.051 -0.200 -0.051 -0.051  0.223 -0.150  0.049  0.248  0.049  0.049 -0.076 -0.150 
 0.199  0.125  0.000 -0.125 -0.149 -0.025 -0.075  0.050  0.125  0.025  0.075 -0.025  0.075 -0.050 -0.075  0.050  0.025 -0.050 -0.075 -0.174  0.050  0.149  0.125 -0.075  0.025 -0.025  0.125 -0.125  0.050  0.000  0.249 -0.100 -0.149 -0.100  0.050 -0.199 -0.050  0.100  0.174 -0.149  0.000  0.100  0.050  0.125 -0.149  0.299 -0.125  0.075 -0.174 -0.125  0.224 -0.125 -0.100 -0.199  0.100  0.000  0.174  0.050 -0.174  0.000 -0.149  0.050  0.100 -0.075 -0.149 -0.050 -0.174 -0.050  0.199 -0.025 -0.125 -0.075 -0.050  0.249  0.025  0.125  0.299  0.050 -0.100  0.050 -0.149 -0.025 -0.100 -0.174  0.050  0.274 -0.075  0.025 -0.050 -0.199 -0.075 -0.025  0.224 -0.149  0.050  0.249  0.050  0.050 -0.125 -0.125 
 0.147  0.048 -0.052 -0.127 -0.127  0.023 -0.027  0.098  0.147  0.048  0.073 -0.002  0.048 -0.077 -0.027  0.023  0.098 -0.052 -0.077 -0.102  0.098  0.073  0.048 -0.077  0.023 -0.027  0.172 -0.102  0.048  0.048  0.197 -0.077 -0.151 -0.151  0.098 -0.151 -0.052  0.098  0.098 -0.102  0.048  0.098  0.073  0.073 -0.102  0.272 -0.151  0.048 -0.102 -0.077  0.172 -0.052 -0.077 -0.151  0.048 -0.052  0.172  0.098 -0.127  0.023 -0.077  0.048 -0.002 -0.052 -0.077  0.023 -0.127 -0.002  0.222 -0.102 -0.176 -0.052 -0.027  0.197  0.098  0.147  0.222  0.073 -0.102  0.023 -0.176 -0.102 -0.027 -0.102  0.073  0.297 -0.052 -0.002 -0.127 -0.151 -0.052 -0.027  0.297 -0.102  0.048  0.197  0.048  0.048 -0.102 -0.151 
 0.129  0.079  0.004 -0.070 -0.095 -0.020  0.004  0.079  0.179 -0.020  0.079 -0.020  0.054 -0.020  0.004  0.054  0.154 -0.070 -0.120 -0.070  0.104  0.029  0.054  0.004  0.029  0.004  0.104 -0.070  0.054  0.079  0.104 -0.070 -0.145 -0.145  0.054 -0.095 -0.045  0.129  0.054 -0.020  0.029  0.079  0.029  0.104 -0.095  0.179 -0.120  0.004 -0.045 -0.095  0.129  0.004 -0.045 -0.170 -0.020 -0.045  0.229  0.054 -0.095  0.079 -0.020  0.104  0.029 -0.095 -0.070  0.029 -0.095 -0.045  0.154 -0.145 -0.120  0.004 -0.020  0.129  0.129  0.179  0.204  0.129 -0.020 -0.020 -0.120 -0.120  0.054 -0.070  0.054  0.229 -0.045 -0.070 -0.120 -0.120  0.004 -0.045  0.279 -0.070  0.104  0.204  0.004  0.004 -0.045 -0.170 
 0.046  0.071  0.021 -0.053 -0.078 -0.028 -0.053 -0.003  0.196 -0.028  0.071 -0.003  0.071 -0.003  0.021  0.046  0.096 -0.078 -0.128 -0.053  0.121 -0.003  0.046  0.021 -0.003  0.021  0.046 -0.053  0.071  0.096  0.071 -0.078 -0.128 -0.153  0.021 -0.078 -0.028  0.096  0.021 -0.003  0.021  0.071  0.021  0.121 -0.078  0.146 -0.103  0.021 -0.028 -0.103  0.146 -0.003 -0.053 -0.153 -0.028 -0.053  0.196  0.071 -0.078  0.096 -0.003  0.121 -0.003 -0.103 -0.078  0.046 -0.078 -0.028  0.121 -0.153 -0.128  0.021 -0.003  0.146  0.096  0.196  0.171  0.096 -0.028 -0.028 -0.103 -0.103  0.071 -0.053  0.021  0.146 -0.078 -0.078 -0.103 -0.128 -0.003 -0.028  0.196 -0.078  0.121  0.196  0.021 -0.003 -0.053 -0.153 
 0.020  0.045  0.045 -0.030 -0.055 -0.080 -0.055  0.020  0.194 -0.030  0.045  0.020  0.045  0.045 -0.005  0.070 -0.030 -0.055 -0.105 -0.055  0.120 -0.030  0.020  0.045 -0.005  0.045  0.020 -0.055  0.095  0.070  0.095 -0.055 -0.130 -0.130 -0.005 -0.055 -0.005  0.120  0.045  0.020 -0.055  0.095  0.045  0.144 -0.055  0.120 -0.080 -0.005 -0.080 -0.105  0.120 -0.005 -0.055 -0.130 -0.005 -0.055  0.219 -0.005 -0.055  0.095 -0.005  0.120  0.020 -0.080 -0.055  0.045 -0.080 -0.005  0.095 -0.130 -0.105  0.045 -0.005  0.144  0.095  0.219  0.144  0.095 -0.005 -0.005 -0.080 -0.080  0.045 -0.080 -0.005  0.095 -0.055 -0.105 -0.080 -0.130 -0.005 -0.055  0.169 -0.055  0.045  0.169  0.045  0.020 -0.030 -0.130 
 0.028  0.053  0.053 -0.072 -0.072 -0.072 -0.047  0.028  0.177 -0.022  0.028  0.053  0.028  0.053 -0.022  0.078 -0.072 -0.047 -0.097 -0.047  0.128 -0.022  0.003  0.053  0.003  0.053  0.003 -0.047  0.078  0.053  0.053 -0.047 -0.122 -0.122 -0.022 -0.047 -0.022  0.128 -0.022  0.028 -0.097  0.103  0.028  0.152 -0.047  0.103 -0.072 -0.047 -0.072 -0.097  0.103  0.003 -0.047 -0.097 -0.022 -0.047  0.227 -0.047 -0.047  0.078  0.003  0.128  0.028 -0.022 -0.047  0.028 -0.097  0.003  0.078 -0.122 -0.122  0.053  0.003  0.152  0.078  0.202  0.177  0.103  0.028  0.003 -0.072 -0.122  0.028 -0.072 -0.022  0.177 -0.047 -0.097 -0.072 -0.122  0.003 -0.047  0.202 -0.047  0.028  0.152  0.053  0.053  0.003 -0.122 
 0.015  0.040  0.065 -0.059 -0.059 -0.084 -0.034  0.040  0.165 -0.059  0.040  0.040  0.040  0.040 -0.009  0.090 -0.059 -0.034 -0.084 -0.034  0.065 -0.009 -0.009  0.065 -0.034  0.065  0.015 -0.034  0.065  0.040  0.040 -0.059 -0.109 -0.109 -0.059 -0.034 -0.034  0.140 -0.009  0.040 -0.109  0.115  0.040  0.140 -0.034  0.115 -0.059 -0.059 -0.059 -0.084  0.090 -0.009 -0.034 -0.084 -0.034 -0.059  0.165 -0.059 -0.034  0.090 -0.034  0.140  0.040 -0.009 -0.034 -0.009 -0.084 -0.009  0.040 -0.109 -0.109  0.040  0.015  0.115  0.065  0.215  0.165  0.065  0.040  0.015 -0.059 -0.109  0.040 -0.084 -0.034  0.165 -0.034 -0.084 -0.059 -0.109 -0.009 -0.059  0.165 -0.034  0.040  0.140  0.040  0.040  0.015 -0.109 
 0.023  0.048  0.073 -0.051 -0.051 -0.076 -0.051  0.048  0.148 -0.051  0.023 -0.051  0.023  0.048 -0.001  0.098 -0.051 -0.026 -0.076 -0.026  0.048 -0.001 -0.001  0.073 -0.026  0.048  0.023 -0.051  0.073  0.023  0.048 -0.051 -0.101 -0.101 -0.076 -0.026 -0.026  0.123 -0.001  0.048 -0.101  0.123  0.023  0.098 -0.026  0.123 -0.051 -0.051 -0.051 -0.076  0.048 -0.051 -0.026 -0.076 -0.026 -0.051  0.123 -0.051 -0.051  0.048 -0.026  0.148  0.023 -0.026 -0.026 -0.001 -0.076 -0.001 -0.001 -0.101 -0.101  0.048  0.023  0.098  0.048  0.223  0.148  0.073  0.023 -0.001 -0.051 -0.101  0.023 -0.076 -0.051  0.123 -0.051 -0.076 -0.051 -0.101 -0.001 -0.076  0.073 -0.026  0.048  0.148  0.023  0.023 -0.001 -0.101 
 0.037  0.087  0.087 -0.037 -0.037 -0.062 -0.037  0.062  0.162 -0.062  0.012 -0.037  0.037  0.012  0.012  0.087 -0.037 -0.037 -0.062 -0.012 -0.012 -0.012  0.012  0.012 -0.012  0.062 -0.012 -0.037  0.037  0.012  0.062 -0.037 -0.087 -0.087 -0.062 -0.012 -0.062  0.137  0.012  0.062 -0.087  0.112  0.012  0.087 -0.012  0.137 -0.037 -0.037 -0.037 -0.062  0.062 -0.062 -0.012 -0.087 -0.062 -0.037  0.037 -0.062 -0.037  0.012 -0.062  0.162 -0.012 -0.062 -0.062  0.012 -0.087  0.012  0.012 -0.087 -0.087  0.037 -0.012  0.062  0.062  0.212  0.112  0.062  0.037 -0.012 -0.037 -0.087  0.037 -0.037 -0.037  0.062 -0.037 -0.062 -0.062 -0.087 -0.012 -0.062  0.012 -0.012  0.062  0.162 -0.012 -0.012 -0.012 -0.087 
-0.028  0.096  0.096 -0.028 -0.053 -0.053 -0.028  0.071  0.146 -0.053  0.021 -0.028 -0.003  0.021  0.021  0.096 -0.028 -0.028 -0.053 -0.003 -0.003 -0.003  0.021 -0.028 -0.028  0.046 -0.003 -0.028  0.021 -0.003  0.046 -0.028 -0.078 -0.078 -0.053 -0.003 -0.053  0.146  0.021  0.071 -0.078  0.121  0.021  0.071 -0.003  0.146 -0.028 -0.028 -0.053 -0.078  0.021 -0.053 -0.003 -0.078 -0.028 -0.053  0.046 -0.053 -0.028 -0.028 -0.078  0.121 -0.053 -0.053 -0.053 -0.003 -0.078 -0.003 -0.003 -0.078 -0.078  0.021 -0.003 -0.028  0.046  0.196  0.096  0.071  0.046 -0.003 -0.028 -0.078  0.046 -0.028 -0.028  0.071 -0.028 -0.053 -0.078 -0.078 -0.003 -0.078  0.021 -0.003  0.046  0.171 -0.003 -0.003 -0.003 -0.078 
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 0.172  0.048 -0.002 -0.002 -0.052 -0.102 -0.052  0.023  0.098 -0.002  0.147 -0.002 -0.077  0.123 -0.077 -0.077 -0.002 -0.102 -0.052 -0.077  0.048 -0.102 -0.027 -0.102  0.098  0.073 -0.052 -0.151  0.023 -0.002  0.073 -0.002 -0.176 -0.077  0.172 -0.052  0.023  0.222 -0.002 -0.002 -0.102  0.048 -0.052  0.073 -0.052  0.397 -0.052 -0.027 -0.027 -0.027  0.197  0.197 -0.077 -0.077 -0.002 -0.027  0.023  0.123 -0.052 -0.102  0.048  0.172 -0.027  0.023 -0.002  0.073 -0.027  0.172  0.795 -0.002 -0.052  0.073  0.098 -0.002  0.322  0.172  0.521  0.197  0.123 -0.052 -0.052 -0.052  0.222 -0.002  0.671  0.023 -0.102 -0.002 -0.027 -0.027  0.123 -0.052  0.272  0.073 -0.027 -0.102  0.023 -0.077 -0.052 -0.052 
 0.217  0.117  0.042 -0.007 -0.082 -0.157 -0.082 -0.032  0.167 -0.007  0.192 -0.082 -0.032  0.092 -0.082 -0.107  0.017 -0.157 -0.107 -0.082  0.017 -0.082 -0.057 -0.032  0.092  0.042 -0.032 -0.157 -0.007  0.017  0.242  0.017 -0.232 -0.107  0.167 -0.057  0.042  0.291  0.017 -0.057 -0.082  0.042 -0.007  0.067 -0.132  0.366 -0.032 -0.007 -0.057 -0.057  0.167  0.217 -0.107 -0.132 -0.007 -0.057 -0.007  0.067 -0.132 -0.032  0.067  0.192  0.017 -0.032  0.042  0.042 -0.057  0.142  0.740  0.067 -0.132  0.092  0.117 -0.007  0.366  0.316  0.665  0.192  0.117 -0.057 -0.107 -0.007  0.117 -0.032  0.690  0.017 -0.082 -0.007 -0.082 -0.082  0.167 -0.032  0.366 -0.007 -0.057 -0.032  0.042 -0.057 -0.057 -0.057 
 0.225  0.150  0.025 -0.024 -0.099 -0.174 -0.049 -0.049  0.175 -0.024  0.200 -0.024 -0.024  0.075 -0.099 -0.124  0.025 -0.174 -0.074 -0.124  0.050 -0.049 -0.074 -0.049  0.100  0.050 -0.049 -0.149 -0.024  0.025  0.250  0.000 -0.224 -0.124  0.150 -0.049  0.050  0.250  0.000 -0.074 -0.099  0.025  0.000  0.075 -0.149  0.324 -0.074  0.000 -0.074 -0.074  0.175  0.200 -0.124 -0.149  0.000 -0.074  0.025  0.075 -0.124 -0.049  0.050  0.175  0.025 -0.049 -0.024  0.025 -0.074  0.150  0.673  0.050 -0.149  0.100  0.100  0.025  0.374  0.374  0.673  0.175  0.100 -0.074 -0.124 -0.024  0.125 -0.049  0.673  0.075 -0.099 -0.024 -0.074 -0.074  0.150 -0.049  0.349 -0.074 -0.049  0.000  0.100 -0.074 -0.049 -0.074 
 0.196  0.121  0.021 -0.053 -0.128 -0.178 -0.078 -0.053  0.146 -0.053  0.196 -0.053  0.046  0.046 -0.103 -0.128 -0.003 -0.178 -0.103 -0.128  0.046 -0.053 -0.103 -0.003  0.071  0.046 -0.078 -0.128 -0.028  0.096  0.246 -0.028 -0.253 -0.178  0.096 -0.053  0.021  0.246  0.021 -0.078 -0.128 -0.028 -0.028  0.096 -0.153  0.271 -0.078 -0.053 -0.053 -0.128  0.121  0.221 -0.153 -0.203  0.096 -0.053  0.096  0.121 -0.128 -0.078  0.046  0.146  0.096 -0.003 -0.103  0.071 -0.103  0.146  0.619  0.021 -0.178  0.121  0.071  0.021  0.295  0.395  0.644  0.146  0.096 -0.053 -0.153 -0.053  0.046 -0.028  0.594  0.171 -0.078 -0.003 -0.028 -0.103  0.096 -0.078  0.395 -0.153 -0.028  0.071  0.071  0.046 -0.053 -0.153 
 0.193  0.118  0.018 -0.031 -0.156 -0.156 -0.056 -0.081  0.143 -0.056  0.218 -0.081  0.093  0.043 -0.106 -0.156 -0.006 -0.156 -0.131 -0.131  0.043 -0.031 -0.106  0.018  0.068  0.018 -0.081 -0.106 -0.006  0.068  0.243 -0.056 -0.256 -0.256  0.093 -0.056  0.018  0.218  0.018 -0.081 -0.156 -0.031 -0.031  0.118 -0.156  0.268 -0.056 -0.056 -0.056 -0.131  0.118  0.193 -0.156 -0.206  0.143 -0.031  0.093  0.118 -0.131 -0.081  0.043  0.143  0.093 -0.031 -0.106  0.018 -0.131  0.168  0.542 -0.006 -0.231  0.093  0.043  0.043  0.268  0.367  0.591  0.093  0.043 -0.056 -0.156 -0.031  0.018 -0.056  0.467  0.243 -0.081  0.018 -0.031 -0.106  0.068 -0.081  0.367 -0.206 -0.006  0.093  0.068  0.093 -0.056 -0.131 
 0.262  0.138  0.063 -0.062 -0.186 -0.112 -0.087 -0.087  0.138 -0.062  0.187 -0.087  0.088  0.038 -0.062 -0.087 -0.037 -0.161 -0.161 -0.161  0.038 -0.037 -0.087  0.013  0.063 -0.012 -0.062 -0.112  0.013  0.063  0.262 -0.037 -0.261 -0.286  0.088 -0.062  0.038  0.212  0.038 -0.062 -0.161 -0.037 -0.037  0.162 -0.186  0.262 -0.087 -0.012 -0.062 -0.137  0.088  0.162 -0.137 -0.261  0.212  0.038  0.088  0.162 -0.161 -0.062  0.063  0.113  0.088 -0.062 -0.087  0.013 -0.137  0.162  0.412 -0.012 -0.236  0.038  0.013  0.038  0.237  0.237  0.536  0.063 -0.012 -0.037 -0.186 -0.037  0.013 -0.087  0.337  0.287 -0.112  0.038 -0.012 -0.161  0.038 -0.087  0.362 -0.211  0.013  0.138  0.038  0.187 -0.087 -0.112 
 0.289  0.140  0.015 -0.060 -0.184 -0.085 -0.085 -0.060  0.115 -0.035  0.140 -0.110  0.090 -0.010 -0.035 -0.010 -0.010 -0.159 -0.159 -0.159  0.065  0.015 -0.085  0.015  0.090  0.015 -0.060 -0.110  0.015  0.065  0.239 -0.035 -0.259 -0.284  0.065 -0.085  0.040  0.214  0.065 -0.060 -0.135 -0.035 -0.035  0.140 -0.159  0.239 -0.085  0.015 -0.085 -0.135  0.090  0.115 -0.110 -0.259  0.239  0.040  0.090  0.140 -0.184 -0.060  0.040  0.090  0.090 -0.085 -0.110  0.015 -0.135  0.164  0.414 -0.010 -0.209  0.040  0.040  0.140  0.239  0.189  0.538  0.065 -0.010 -0.035 -0.184 -0.010  0.040 -0.085  0.289  0.264 -0.110  0.040 -0.010 -0.159  0.015 -0.085  0.314 -0.184  0.015  0.140  0.040  0.164 -0.085 -0.110 
 0.311  0.137  0.037 -0.063 -0.162 -0.013 -0.088 -0.013  0.112 -0.038  0.137 -0.113  0.112 -0.013 -0.013  0.012 -0.013 -0.162 -0.113 -0.162  0.062  0.012 -0.088  0.012  0.062  0.012 -0.013 -0.138  0.012  0.037  0.211 -0.038 -0.237 -0.287  0.087 -0.138  0.062  0.211  0.087 -0.063 -0.138 -0.038 -0.038  0.137 -0.162  0.236 -0.113  0.012 -0.088 -0.138  0.087  0.062 -0.113 -0.262  0.236  0.037  0.112  0.137 -0.187 -0.038  0.037  0.062  0.112 -0.088 -0.113 -0.013 -0.162  0.112  0.336 -0.013 -0.212  0.037 -0.038  0.161  0.236  0.161  0.535  0.062 -0.013 -0.038 -0.212  0.012  0.037 -0.088  0.186  0.261 -0.138  0.062 -0.013 -0.187  0.012 -0.113  0.311 -0.187  0.012  0.137  0.062  0.161 -0.063 -0.113 
 0.307  0.133  0.033 -0.066 -0.166  0.008 -0.116 -0.016  0.108 -0.041  0.133 -0.116  0.108 -0.016  0.008  0.008 -0.016 -0.166 -0.141 -0.191  0.058  0.033 -0.066  0.008  0.058  0.033  0.008 -0.141  0.008  0.033  0.208 -0.041 -0.241 -0.290  0.058 -0.166  0.058  0.208  0.108 -0.066 -0.166 -0.041 -0.041  0.108 -0.166  0.233 -0.116  0.008 -0.091 -0.141  0.108  0.033 -0.091 -0.266  0.258  0.058  0.108  0.108 -0.166 -0.041  0.033  0.083  0.108 -0.091 -0.116 -0.016 -0.166  0.083  0.307  0.033 -0.216  0.033 -0.041  0.158  0.208  0.158  0.532  0.083 -0.016 -0.066 -0.216 -0.016  0.008 -0.116  0.183  0.258 -0.141  0.058 -0.041 -0.191  0.008 -0.091  0.307 -0.166  0.008  0.158  0.058  0.158 -0.091 -0.066 
 0.305  0.156  0.006 -0.093 -0.168  0.006 -0.118  0.006  0.106 -0.018  0.106 -0.093  0.106 -0.018  0.031  0.031 -0.018 -0.143 -0.118 -0.193  0.031  0.031  0.006  0.006  0.056  0.031  0.006 -0.118  0.006  0.006  0.231 -0.043 -0.243 -0.268  0.056 -0.168  0.056  0.181  0.181 -0.068 -0.168 -0.018 -0.018  0.106 -0.168  0.256 -0.118  0.006 -0.118 -0.143  0.131  0.006 -0.093 -0.292  0.231  0.056  0.106  0.106 -0.143 -0.043  0.031  0.081  0.131 -0.068 -0.118 -0.043 -0.168  0.081  0.231  0.031 -0.218  0.031 -0.043  0.156  0.156  0.181  0.505  0.106 -0.043 -0.093 -0.218 -0.018  0.006 -0.118  0.181  0.256 -0.093  0.056 -0.043 -0.193 -0.018 -0.093  0.305 -0.193  0.006  0.181  0.081  0.156 -0.118 -0.093 
 0.281  0.156  0.006 -0.118 -0.168  0.031 -0.118  0.006  0.106 -0.018  0.106 -0.093  0.106 -0.018  0.031  0.031 -0.018 -0.143 -0.143 -0.193  0.031  0.031  0.056  0.006  0.056  0.056  0.081 -0.093  0.006  0.006  0.231 -0.043 -0.218 -0.243  0.056 -0.168  0.056  0.181  0.156 -0.043 -0.168 -0.018  0.006  0.106 -0.168  0.305 -0.143  0.006 -0.093 -0.143  0.131  0.006 -0.093 -0.268  0.231  0.056  0.106  0.106 -0.168 -0.043  0.006  0.081  0.131 -0.068 -0.118 -0.043 -0.168  0.081  0.256  0.056 -0.218  0.006 -0.043  0.181  0.131  0.181  0.505  0.106 -0.093 -0.093 -0.243 -0.018  0.006 -0.118  0.156  0.231 -0.093  0.081 -0.018 -0.193 -0.043 -0.118  0.305 -0.193  0.006  0.206  0.081  0.156 -0.118 -0.118 
 0.280  0.155  0.005 -0.119 -0.169  0.005 -0.119  0.005  0.105 -0.019  0.105 -0.094  0.105 -0.019  0.055  0.030 -0.019 -0.144 -0.144 -0.194  0.030  0.030  0.055  0.005  0.055  0.055  0.105 -0.094  0.030  0.005  0.255 -0.044 -0.194 -0.244  0.080 -0.169  0.055  0.180  0.180 -0.069 -0.169 -0.019  0.005  0.105 -0.144  0.304 -0.144  0.030 -0.094 -0.144  0.130 -0.019 -0.094 -0.269  0.205  0.055  0.105  0.080 -0.194 -0.044 -0.019  0.080  0.105 -0.069 -0.119 -0.044 -0.169  0.055  0.255  0.055 -0.219 -0.019 -0.044  0.180  0.130  0.180  0.504  0.105 -0.094 -0.069 -0.219 -0.044  0.005 -0.119  0.130  0.230 -0.069  0.080 -0.019 -0.194 -0.069 -0.119  0.329 -0.219  0.005  0.205  0.105  0.155 -0.119 -0.144 
 0.307  0.133  0.008 -0.116 -0.166  0.008 -0.116  0.008  0.108 -0.016  0.108 -0.091  0.083 -0.016  0.058  0.033 -0.041 -0.141 -0.141 -0.191  0.033 -0.016  0.033  0.008  0.058  0.083  0.108 -0.091  0.033  0.008  0.258 -0.041 -0.191 -0.266  0.058 -0.166  0.033  0.183  0.208 -0.091 -0.166 -0.041  0.008  0.108 -0.141  0.307 -0.116  0.008 -0.116 -0.141  0.083 -0.041 -0.091 -0.266  0.183  0.033  0.108  0.058 -0.191 -0.041 -0.066  0.083  0.108 -0.066 -0.116 -0.066 -0.166  0.033  0.258  0.033 -0.216  0.008 -0.041  0.233  0.158  0.183  0.507  0.108 -0.091 -0.066 -0.216 -0.041  0.008 -0.166  0.133  0.233 -0.091  0.083 -0.041 -0.191 -0.091 -0.116  0.332 -0.216  0.008  0.208  0.108  0.158 -0.116 -0.141 
 0.306  0.132  0.007 -0.118 -0.167  0.007 -0.093  0.007  0.132  0.032  0.107 -0.093  0.057  0.007  0.057  0.032 -0.043 -0.142 -0.142 -0.192  0.057 -0.018  0.032  0.007  0.057  0.082  0.156 -0.093  0.032  0.007  0.281 -0.043 -0.192 -0.267  0.057 -0.167  0.032  0.132  0.206 -0.118 -0.093 -0.043  0.007  0.107 -0.142  0.306 -0.118  0.007 -0.118 -0.142  0.082 -0.043 -0.093 -0.242  0.156  0.032  0.082  0.057 -0.192 -0.043 -0.093  0.082  0.132 -0.068 -0.118 -0.068 -0.167  0.032  0.256  0.007 -0.217  0.007 -0.043  0.231  0.132  0.181  0.505  0.107 -0.093 -0.068 -0.217 -0.043 -0.018 -0.167  0.132  0.231 -0.093  0.082 -0.043 -0.192 -0.093 -0.118  0.331 -0.217  0.007  0.206  0.107  0.156 -0.142 -0.142 
 0.274  0.125  0.075 -0.075 -0.125 -0.025 -0.050 -0.025  0.149  0.000  0.125 -0.050  0.050 -0.050  0.025  0.050 -0.025 -0.125 -0.174 -0.149  0.075  0.000  0.025  0.025  0.050  0.075  0.174 -0.100  0.025  0.050  0.125 -0.025 -0.174 -0.224  0.075 -0.125 -0.050  0.100  0.149 -0.075 -0.025  0.025 -0.025  0.100 -0.125  0.274 -0.149  0.000 -0.075 -0.100  0.100 -0.025 -0.075 -0.199  0.149  0.000  0.050  0.000 -0.174 -0.025 -0.075  0.125  0.025 -0.025 -0.100 -0.025 -0.125  0.000  0.174 -0.125 -0.199  0.000 -0.050  0.224  0.100  0.100  0.473  0.050 -0.125 -0.025 -0.199 -0.025  0.025 -0.125  0.100  0.199 -0.125  0.000 -0.025 -0.149 -0.100 -0.100  0.299 -0.199  0.050  0.125  0.050  0.100 -0.100 -0.174 
 0.131  0.081  0.056 -0.044 -0.069  0.006 -0.094  0.056  0.155 -0.044  0.081 -0.019  0.106  0.006  0.006  0.006 -0.019 -0.094 -0.143 -0.069  0.081 -0.019  0.006  0.006  0.006  0.031  0.081 -0.044  0.006  0.031  0.081 -0.044 -0.168 -0.168  0.031 -0.094 -0.069  0.081  0.056 -0.019 -0.019  0.081  0.006  0.155 -0.069  0.205 -0.119 -0.019 -0.119 -0.094  0.155 -0.019 -0.094 -0.168  0.056 -0.019  0.081 -0.044 -0.094  0.056 -0.069  0.131  0.056 -0.019 -0.094  0.006 -0.094  0.006  0.131 -0.143 -0.119  0.006 -0.044  0.155  0.081  0.131  0.405  0.056 -0.044 -0.019 -0.119 -0.069  0.056 -0.069  0.031  0.180 -0.044 -0.069 -0.069 -0.143 -0.069 -0.044  0.305 -0.119  0.081  0.131  0.081  0.081 -0.094 -0.143 
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 0.029  0.029  0.104 -0.020 -0.120 -0.195 -0.145  0.054  0.079 -0.045 -0.195  0.079  0.104 -0.120 -0.145  0.154 -0.045 -0.045 -0.070 -0.145  0.004  0.079  0.079  0.054  0.079 -0.070  0.004 -0.120  0.503  0.029  0.104 -0.020 -0.170 -0.120 -0.145 -0.070 -0.195  0.079  0.104  0.079 -0.220  0.054 -0.070  0.054 -0.220  0.229  0.079 -0.145 -0.220 -0.070  0.104  0.229 -0.095 -0.195  0.254  0.229  0.204  0.104 -0.195 -0.020 -0.120  0.154  0.004  0.004 -0.070 -0.020  0.004 -0.020  0.428 -0.170 -0.045  0.054 -0.070  0.229  0.229  0.229  0.428  0.054  0.328 -0.045 -0.145  0.029 -0.070 -0.195  0.179  0.279 -0.045  0.154  0.104 -0.270 -0.095  0.029  0.129 -0.020 -0.095  0.254  0.079  0.279 -0.070 -0.120 
 0.079  0.054  0.104 -0.045 -0.120 -0.195 -0.120  0.079  0.104 -0.070 -0.170  0.079  0.129 -0.120 -0.145  0.154  0.004 -0.045 -0.070 -0.145  0.004  0.104  0.054  0.054  0.079 -0.070  0.004 -0.095  0.453  0.029  0.129 -0.020 -0.195 -0.120 -0.120 -0.070 -0.220  0.104  0.104  0.029 -0.195  0.029 -0.070  0.054 -0.220  0.204  0.079 -0.095 -0.245 -0.095  0.104  0.204 -0.095 -0.220  0.229  0.229  0.204  0.104 -0.195 -0.020 -0.120  0.179  0.004  0.004 -0.070 -0.045 -0.020 -0.095  0.328 -0.145 -0.070  0.029 -0.095  0.204  0.229  0.254  0.453  0.054  0.303 -0.045 -0.145  0.054 -0.045 -0.195  0.179  0.303 -0.045  0.154  0.154 -0.270 -0.120  0.029  0.129 -0.045 -0.095  0.279  0.104  0.229 -0.020 -0.120 
 0.098  0.073  0.123 -0.051 -0.101 -0.126 -0.126 -0.001  0.098 -0.076 -0.101  0.123  0.148 -0.051 -0.101  0.148  0.048 -0.026 -0.051 -0.101  0.073  0.148  0.073 -0.001  0.098 -0.026  0.023 -0.076  0.397 -0.001  0.073 -0.001 -0.176 -0.126 -0.126 -0.126 -0.151  0.098  0.098  0.023 -0.151  0.023 -0.001  0.073 -0.176  0.123  0.048 -0.076 -0.201 -0.051  0.098  0.148 -0.051 -0.151  0.223  0.148  0.223  0.098 -0.151 -0.001 -0.076  0.173  0.023 -0.026 -0.076 -0.076 -0.051 -0.126  0.372 -0.101 -0.051  0.023 -0.076  0.223  0.248  0.273  0.422  0.073  0.248 -0.051 -0.076 -0.001 -0.026 -0.126  0.098  0.322  0.023  0.148  0.023 -0.201 -0.076 -0.001  0.173 -0.101 -0.026  0.273  0.048  0.148 -0.101 -0.151 
 0.054  0.129  0.054 -0.120 -0.095 -0.095 -0.120  0.004  0.129 -0.045 -0.070  0.054  0.129  0.004 -0.045  0.104 -0.020 -0.045 -0.095 -0.070  0.129  0.129  0.129  0.004  0.029 -0.045  0.029 -0.095  0.229 -0.020  0.104 -0.070 -0.145 -0.170 -0.120 -0.120 -0.095  0.104  0.004  0.004 -0.120  0.079  0.029  0.104 -0.095  0.104  0.004 -0.045 -0.120 -0.070  0.104  0.154 -0.095 -0.120  0.129  0.029  0.254  0.029 -0.095  0.054 -0.045  0.129  0.029 -0.020 -0.020 -0.020 -0.020 -0.070  0.254 -0.120 -0.120  0.054 -0.045  0.104  0.179  0.229  0.403  0.129  0.104 -0.020 -0.070 -0.095  0.029 -0.095  0.154  0.229 -0.045  0.054  0.029 -0.145 -0.070 -0.045  0.179 -0.095  0.054  0.254  0.104  0.079 -0.070 -0.095 
 0.071  0.121  0.071 -0.104 -0.104 -0.079 -0.104 -0.004  0.145 -0.054 -0.054 -0.004  0.096 -0.004 -0.029  0.121 -0.004 -0.054 -0.079 -0.054  0.145  0.145  0.121 -0.004 -0.004 -0.029  0.046 -0.104  0.121 -0.029  0.121 -0.054 -0.129 -0.153 -0.129 -0.104 -0.079  0.121 -0.004 -0.004 -0.104  0.071  0.046  0.046 -0.079  0.121 -0.029 -0.029 -0.104 -0.079  0.071  0.096 -0.079 -0.104  0.121  0.021  0.270  0.046 -0.079  0.071 -0.054  0.145  0.046 -0.029 -0.004 -0.029 -0.029 -0.054  0.245 -0.104 -0.104  0.071 -0.054  0.096  0.170  0.220  0.370  0.145  0.071 -0.004 -0.079 -0.104  0.021 -0.104  0.096  0.195 -0.029  0.046  0.046 -0.153 -0.054 -0.029  0.170 -0.079  0.046  0.195  0.096  0.071 -0.054 -0.104 
 0.046  0.170  0.046 -0.079 -0.079 -0.079 -0.079 -0.004  0.170 -0.029 -0.029 -0.004  0.021 -0.004 -0.029  0.145 -0.054 -0.029 -0.104 -0.029  0.071  0.170  0.046 -0.004 -0.029  0.021  0.046 -0.104  0.046 -0.054  0.071 -0.054 -0.104 -0.129 -0.104 -0.079 -0.054  0.145 -0.029  0.021 -0.104  0.096  0.046  0.071 -0.054  0.096 -0.004 -0.004 -0.079 -0.054  0.071  0.096 -0.054 -0.079  0.071  0.021  0.270  0.021 -0.054  0.071 -0.029  0.121  0.046 -0.004 -0.004 -0.004 -0.029 -0.029  0.170 -0.079 -0.079  0.071 -0.029  0.121  0.096  0.245  0.295  0.145  0.071  0.021 -0.079 -0.129  0.046 -0.104  0.096  0.096 -0.029 -0.054  0.021 -0.129 -0.029 -0.029  0.195 -0.054  0.021  0.195  0.046  0.071 -0.029 -0.079 
 0.031  0.206  0.031 -0.068 -0.068 -0.068 -0.068  0.006  0.181 -0.043 -0.018  0.006 -0.018  0.006 -0.018  0.156 -0.043 -0.043 -0.093 -0.018  0.056  0.156  0.031 -0.018 -0.018  0.031  0.056 -0.093  0.006 -0.043  0.081 -0.043 -0.093 -0.118 -0.093 -0.068 -0.043  0.131 -0.018  0.031 -0.093  0.106  0.031  0.081 -0.043  0.106 -0.018 -0.018 -0.068 -0.068  0.056  0.081 -0.043 -0.068  0.031  0.006  0.256 -0.043 -0.068  0.006 -0.043  0.131  0.031 -0.018  0.006 -0.018 -0.018 -0.018  0.106 -0.068 -0.068  0.031 -0.018  0.106  0.081  0.206  0.305  0.106  0.056  0.031 -0.068 -0.118  0.056 -0.068  0.081  0.106 -0.018 -0.043 -0.043 -0.118 -0.018 -0.068  0.156 -0.043  0.031  0.206  0.056  0.081 -0.018 -0.093 
 0.023  0.198  0.048 -0.051 -0.051 -0.051 -0.051  0.023  0.198 -0.026 -0.001  0.023 -0.026 -0.001 -0.001  0.098 -0.076 -0.026 -0.076 -0.076  0.048  0.048  0.048 -0.026 -0.001  0.048  0.048 -0.101 -0.001 -0.026  0.073 -0.026 -0.101 -0.101 -0.076 -0.026 -0.026  0.123 -0.001  0.023 -0.076  0.098 -0.001  0.048 -0.026  0.123 -0.001 -0.026 -0.051 -0.076  0.098  0.073 -0.026 -0.076 -0.026 -0.026  0.248 -0.051 -0.051 -0.001 -0.051  0.123 -0.026  0.023 -0.001 -0.001 -0.076 -0.026  0.048 -0.051 -0.076 -0.026 -0.001  0.073  0.048  0.198  0.248  0.098  0.023  0.023 -0.101 -0.101  0.048 -0.051 -0.001  0.123 -0.051 -0.076 -0.101 -0.101 -0.001 -0.051  0.098 -0.026  0.048  0.223  0.073  0.123 -0.001 -0.101 
 0.032  0.107  0.057 -0.042 -0.042 -0.042 -0.042  0.032  0.207 -0.017  0.007  0.007 -0.017  0.007  0.007  0.082 -0.067 -0.017 -0.092 -0.067  0.032  0.007  0.032 -0.042  0.007  0.057  0.007 -0.092 -0.017 -0.017  0.082 -0.017 -0.092 -0.092 -0.067 -0.017 -0.042  0.107  0.007  0.007 -0.067  0.082  0.007  0.057 -0.042  0.132  0.007 -0.017 -0.042 -0.067  0.107  0.057 -0.017 -0.067 -0.017 -0.017  0.207 -0.067 -0.042  0.007 -0.042  0.132 -0.017  0.032 -0.042  0.007 -0.092 -0.042  0.057 -0.067 -0.092 -0.042 -0.017  0.057  0.057  0.182  0.207  0.082  0.032  0.032 -0.092 -0.092  0.057 -0.042 -0.017  0.132 -0.042 -0.067 -0.092 -0.092  0.007 -0.042  0.082 -0.017  0.057  0.207  0.082  0.132 -0.042 -0.092 
 0.048  0.048  0.048 -0.027 -0.027 -0.027 -0.027  0.023  0.098 -0.027  0.023 -0.002 -0.027  0.023  0.023  0.073 -0.052 -0.027 -0.077 -0.052  0.023  0.023  0.023 -0.027 -0.002  0.048  0.023 -0.077 -0.002 -0.027  0.098 -0.027 -0.077 -0.077 -0.052 -0.002 -0.027  0.098  0.023 -0.002 -0.052  0.073  0.023 -0.002 -0.027  0.147  0.023 -0.027 -0.027 -0.077  0.123  0.073 -0.002 -0.052 -0.002 -0.052  0.172 -0.052 -0.027 -0.002 -0.027  0.147 -0.027  0.048 -0.052  0.023 -0.077 -0.027  0.048 -0.052 -0.077 -0.027 -0.002 -0.002  0.048  0.172  0.098  0.098  0.048 -0.002 -0.077 -0.077  0.048 -0.052 -0.027  0.123 -0.052 -0.077 -0.077 -0.077 -0.002 -0.052  0.098 -0.027  0.073  0.197  0.048  0.147 -0.052 -0.077 
 0.055  0.055  0.030 -0.019 -0.019 -0.019 -0.019  0.030  0.055 -0.044  0.030  0.005 -0.019  0.030  0.030  0.055 -0.044 -0.019 -0.069 -0.044  0.030  0.005  0.030 -0.019  0.005  0.055  0.030 -0.069  0.005 -0.019  0.080 -0.019 -0.069 -0.069 -0.044  0.005 -0.019  0.080  0.030 -0.019 -0.044  0.055  0.030  0.005 -0.019  0.105  0.005 -0.019 -0.019 -0.069  0.105  0.080  0.005 -0.044  0.005 -0.044  0.155 -0.044 -0.044 -0.019 -0.019  0.155 -0.044  0.030 -0.044  0.005 -0.069 -0.044  0.030 -0.069 -0.069 -0.019  0.005  0.005  0.030  0.155  0.080  0.080  0.005 -0.019 -0.069 -0.069  0.055 -0.044 -0.019  0.105 -0.044 -0.069 -0.069 -0.069  0.005 -0.044  0.105 -0.019  0.055  0.205  0.030  0.105 -0.044 -0.069 
 0.068 -0.006  0.018 -0.006 -0.006 -0.006 -0.006  0.018 -0.031 -0.031  0.018 -0.006 -0.031  0.043  0.018  0.068 -0.031 -0.006 -0.056 -0.031  0.018  0.018  0.018 -0.006  0.018  0.043  0.018 -0.056  0.018 -0.006  0.043 -0.006 -0.056 -0.056 -0.031 -0.006 -0.006  0.043 -0.031 -0.006 -0.031  0.043  0.018 -0.031 -0.006  0.093 -0.006 -0.031 -0.006 -0.056  0.068  0.068  0.018 -0.031  0.018 -0.031  0.118 -0.031 -0.031 -0.031 -0.006  0.168 -0.031  0.018 -0.056 -0.006 -0.056 -0.031 -0.006 -0.056 -0.056 -0.031  0.018 -0.006  0.018  0.143  0.043  0.043  0.018 -0.031 -0.056 -0.056  0.018 -0.031 -0.006  0.118 -0.031 -0.056 -0.056 -0.056  0.018 -0.031  0.093 -0.006  0.043  0.168  0.018  0.093 -0.031 -0.056 
 0.077 -0.023 -0.023 -0.023  0.002  0.002  0.002  0.027 -0.048 -0.023  0.027 -0.023 -0.023  0.027  0.002  0.077 -0.023 -0.023 -0.048 -0.023  0.027  0.027  0.052  0.002  0.027  0.027  0.002 -0.048  0.002  0.002  0.002  0.002 -0.048 -0.023 -0.023  0.002  0.002  0.052 -0.023  0.027 -0.023  0.052  0.027 -0.023  0.002  0.052  0.002 -0.048  0.002 -0.048  0.077  0.027  0.002 -0.023  0.027 -0.048  0.127 -0.048 -0.023 -0.023 -0.048  0.151 -0.023  0.002 -0.048  0.002 -0.048 -0.023  0.002 -0.048 -0.048 -0.023  0.027 -0.023  0.002  0.102  0.052  0.027  0.002 -0.023 -0.048 -0.048 -0.023 -0.023  0.002  0.102 -0.023 -0.048 -0.048 -0.048  0.027 -0.023  0.102  0.027  0.027  0.127  0.027  0.077 -0.023 -0.048 
 0.043 -0.006 -0.031 -0.031 -0.006 -0.006 -0.006  0.018 -0.031 -0.031 -0.006 -0.031 -0.006  0.018  0.018  0.043 -0.006 -0.031 -0.031 -0.031  0.043  0.043  0.043  0.018 -0.006  0.018 -0.031 -0.031 -0.006  0.018 -0.006 -0.031 -0.031 -0.006 -0.031  0.018  0.018 -0.006 -0.031  0.043 -0.031  0.018  0.043 -0.031  0.018  0.018  0.018 -0.031 -0.006 -0.031 -0.006 -0.006 -0.006 -0.006  0.043 -0.031  0.068 -0.031 -0.006 -0.006 -0.031  0.093 -0.031 -0.006 -0.031 -0.006 -0.031 -0.031 -0.006 -0.031 -0.031 -0.006  0.018 -0.031 -0.006  0.043  0.018  0.018 -0.006 -0.006 -0.031 -0.031 -0.031 -0.031 -0.006  0.018 -0.031 -0.031 -0.031 -0.031  0.043 -0.031  0.043  0.018  0.018  0.093  0.043  0.018 -0.006 -0.031 
 0.001 -0.023 -0.023 -0.023  0.001  0.001  0.001 -0.023 -0.023 -0.023 -0.023 -0.023  0.001  0.001  0.001  0.026  0.001 -0.023 -0.023 -0.023  0.026  0.001  0.026  0.001  0.001  0.001  0.001 -0.023  0.001  0.026 -0.023 -0.023 -0.023  0.001 -0.023  0.001  0.001  0.001 -0.023  0.051 -0.023  0.026  0.051 -0.023  0.001  0.026  0.026 -0.023  0.001 -0.023  0.001 -0.023  0.001  0.001  0.051 -0.023  0.001 -0.023  0.001  0.001 -0.023  0.051 -0.023  0.001 -0.023  0.026 -0.023 -0.023  0.001 -0.023 -0.023 -0.023 -0.023 -0.023 -0.023  0.001  0.026  0.001 -0.023  0.001 -0.023 -0.023 -0.023 -0.023 -0.023  0.026 -0.023 -0.023 -0.023 -0.023  0.026  0.001 -0.023  0.026  0.026  0.076  0.001 -0.023  0.001 -0.023 
 0.009 -0.015  0.009 -0.015  0.009  0.034 -0.015 -0.015 -0.015 -0.015 -0.015  0.009  0.009 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015  0.034 -0.015  0.034  0.009  0.009  0.009  0.009 -0.015  0.009  0.009 -0.015 -0.015 -0.015  0.009 -0.015 -0.015 -0.015 -0.015 -0.015  0.059 -0.015 -0.015  0.009 -0.015 -0.015  0.009  0.034 -0.015  0.009 -0.015 -0.015  0.009 -0.015  0.009  0.059 -0.015 -0.015 -0.015  0.009  0.009 -0.015  0.034 -0.015  0.034 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015 -0.015 -0.015  0.009  0.009 -0.015  0.009 -0.015  0.059  0.009 -0.015 -0.015 -0.015 
 0.008 -0.016  0.033 -0.016  0.008  0.033 -0.016 -0.016 -0.016 -0.016 -0.016  0.008  0.008 -0.016 -0.016 -0.016 -0.016 -0.016  0.008 -0.016  0.033 -0.016  0.033  0.008  0.008  0.008  0.008 -0.016  0.008  0.008 -0.016 -0.016 -0.016  0.008 -0.016 -0.016 -0.016 -0.016 -0.016  0.058 -0.016 -0.016  0.008 -0.016 -0.016  0.033  0.033 -0.016  0.008 -0.016 -0.016  0.008 -0.016  0.008  0.058 -0.016 -0.016 -0.016  0.008  0.008 -0.016  0.033 -0.016  0.033 -0.016  0.008 -0.016 -0.016  0.008 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016  0.008 -0.016 -0.016  0.008 -0.016 -0.016  0.008 -0.016 -0.016  0.008 -0.016 -0.016 -0.016 -0.016  0.008  0.008 -0.016  0.008 -0.016  0.058  0.008 -0.016  0.008 -0.016 
 0.004 -0.020  0.029  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029 -0.020  0.054 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.054 -0.020  0.054  0.004  0.004  0.004 -0.020 
 0.004 -0.020  0.029  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029 -0.020  0.054 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.054 -0.020  0.054  0.004  0.004  0.004 -0.020 
 0.004 -0.020  0.029  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029 -0.020  0.054 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.054 -0.020  0.054  0.004  0.004  0.004 -0.020 
 0.004 -0.020  0.029  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029 -0.020  0.054 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.054 -0.020  0.054  0.004  0.004  0.004 -0.020 
 0.004 -0.020  0.029  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029 -0.020  0.054 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.054 -0.020  0.054  0.004  0.004  0.004 -0.020 
 0.002 -0.022  0.052  0.002  0.002  0.027 -0.022 -0.022 -0.022 -0.022 -0.022  0.002  0.002 -0.022 -0.022 -0.022  0.002 -0.022  0.002  0.002  0.027 -0.022  0.027  0.002  0.002  0.002  0.002 -0.022  0.002  0.027  0.027 -0.022 -0.022  0.052 -0.022 -0.022 -0.022 -0.022  0.002  0.077  0.002 -0.022  0.002 -0.022 -0.022  0.027  0.027 -0.022  0.002 -0.022 -0.022  0.002 -0.022  0.002  0.052  0.002 -0.022 -0.022  0.002  0.027  0.002  0.027 -0.022  0.077 -0.022  0.027 -0.022  0.027  0.002 -0.022  0.002 -0.022 -0.022 -0.022 -0.022 -0.022  0.002 -0.022  0.002  0.002 -0.022 -0.022  0.002 -0.022 -0.022  0.002 -0.022 -0.022 -0.022 -0.022  0.002  0.002 -0.022  0.052 -0.022  0.077  0.002  0.027  0.002 -0.022 
 0.013 -0.037  0.063 -0.012 -0.012  0.038 -0.012 -0.012 -0.012 -0.037 -0.037 -0.012 -0.012 -0.037 -0.012 -0.037  0.013 -0.037  0.013 -0.012  0.038 -0.037  0.038 -0.012 -0.012  0.013 -0.012 -0.037 -0.012  0.063  0.013 -0.037 -0.037  0.038 -0.037 -0.037 -0.037 -0.037  0.038  0.063 -0.012 -0.037 -0.012 -0.037 -0.012  0.038  0.038 -0.012 -0.012 -0.012 -0.037  0.038 -0.037 -0.012  0.038 -0.012 -0.037 -0.037 -0.012  0.013 -0.012  0.063  0.013  0.063 -0.037  0.013 -0.037  0.013 -0.012 -0.037 -0.012 -0.012 -0.037 -0.037 -0.037 -0.012  0.013 -0.037 -0.012  0.013 -0.037 -0.012 -0.012 -0.037 -0.037  0.038 -0.037 -0.037  0.013 -0.037 -0.012 -0.012 -0.037  0.063 -0.037  0.063  0.088  0.013 -0.012 -0.037 
 0.036 -0.063  0.111  0.011 -0.038  0.011 -0.038 -0.013 -0.038 -0.063 -0.063 -0.038 -0.013 -0.063 -0.013 -0.038  0.086 -0.038  0.036 -0.038  0.086 -0.063  0.036  0.011 -0.013  0.036 -0.013 -0.063  0.036  0.061  0.036 -0.063 -0.063  0.036 -0.038 -0.038 -0.063 -0.063  0.011  0.186 -0.038 -0.063  0.036 -0.063 -0.013  0.061  0.036 -0.038 -0.038  0.011 -0.038  0.011 -0.013 -0.013  0.036 -0.038 -0.038 -0.063 -0.038  0.011 -0.013  0.111  0.111  0.036 -0.038  0.011 -0.063  0.011 -0.038 -0.063  0.061  0.036 -0.063 -0.063 -0.013  0.036  0.061 -0.013 -0.038 -0.013 -0.038  0.011 -0.038 -0.063 -0.013  0.086 -0.038 -0.063  0.036 -0.063  0.011 -0.013 -0.063  0.061 -0.038  0.061  0.111 -0.013 -0.013 -0.063 
 0.021 -0.053  0.146 -0.028 -0.103 -0.003 -0.078 -0.028  0.021 -0.053 -0.078 -0.103  0.021 -0.078  0.096 -0.053  0.096 -0.078  0.021 -0.053  0.196 -0.103  0.096 -0.003 -0.028  0.021  0.021 -0.078  0.096  0.021  0.096 -0.053 -0.103 -0.028 -0.053 -0.053 -0.128 -0.128  0.046  0.196 -0.053 -0.053  0.021 -0.103 -0.028  0.071  0.021 -0.053 -0.028 -0.053 -0.053 -0.003 -0.078 -0.028 -0.028 -0.103 -0.003 -0.128 -0.103 -0.028 -0.053  0.196  0.171  0.021 -0.078 -0.003 -0.103  0.021 -0.028 -0.053  0.021  0.046 -0.053 -0.003  0.021  0.046  0.171 -0.003 -0.053 -0.078 -0.103 -0.003 -0.053 -0.078 -0.028  0.196 -0.103 -0.128  0.021 -0.128 -0.003 -0.003 -0.028  0.021 -0.078  0.121  0.146  0.021 -0.003 -0.103 
 0.020 -0.005  0.169 -0.055 -0.105 -0.005 -0.080 -0.055  0.070 -0.080 -0.005 -0.130  0.070 -0.055  0.095 -0.005  0.095 -0.130 -0.005 -0.055  0.194 -0.055  0.120  0.045  0.045 -0.005  0.045 -0.105  0.070  0.070  0.244  0.020 -0.080 -0.055 -0.080 -0.080 -0.055 -0.154  0.070  0.219 -0.030 -0.080 -0.030 -0.130  0.020  0.144 -0.030 -0.055 -0.030 -0.080 -0.105  0.120 -0.105 -0.080 -0.005 -0.130 -0.055 -0.130 -0.154 -0.030 -0.030  0.269  0.219 -0.030 -0.030 -0.005 -0.130 -0.030  0.020 -0.005 -0.005  0.045 -0.080  0.095 -0.005  0.070  0.269 -0.030 -0.055 -0.105 -0.130 -0.080 -0.055 -0.130  0.020  0.294 -0.105 -0.179  0.120 -0.154 -0.005 -0.005  0.070  0.020 -0.080  0.194  0.169  0.095 -0.005 -0.154 
 0.064  0.064  0.139 -0.061 -0.160 -0.011 -0.086 -0.061  0.039 -0.036  0.014 -0.111  0.089 -0.011  0.114  0.014  0.089 -0.160 -0.036 -0.111  0.213 -0.011  0.139 -0.011  0.114 -0.036  0.089 -0.136  0.114  0.089  0.313  0.039 -0.086 -0.086 -0.111 -0.111  0.039 -0.061  0.114  0.188 -0.011 -0.036 -0.011 -0.061 -0.011  0.213 -0.111 -0.111 -0.036 -0.136 -0.136  0.064 -0.136 -0.160 -0.036 -0.061 -0.036 -0.061 -0.235 -0.111 -0.061  0.238  0.163 -0.061 -0.086 -0.011 -0.160 -0.061  0.114 -0.011 -0.061 -0.011 -0.086  0.114  0.114  0.089  0.388  0.014 -0.111 -0.136 -0.185 -0.086 -0.061 -0.136  0.039  0.338 -0.185 -0.160  0.188 -0.210 -0.061 -0.086  0.089 -0.036 -0.011  0.238  0.213  0.163 -0.036 -0.210 
 0.086  0.061  0.111 -0.038 -0.188 -0.088 -0.113 -0.038  0.011 -0.038  0.061 -0.138  0.086  0.011  0.061  0.036  0.086 -0.188 -0.038 -0.113  0.186 -0.038  0.111 -0.013  0.061 -0.063  0.136 -0.138  0.111  0.061  0.310  0.011 -0.088 -0.113 -0.088 -0.163  0.036 -0.013  0.061  0.111 -0.063 -0.063 -0.063  0.011  0.011  0.285 -0.113 -0.113 -0.088 -0.163 -0.113  0.086 -0.163 -0.163 -0.038 -0.088 -0.063  0.011 -0.238 -0.113 -0.088  0.211  0.111 -0.063 -0.088  0.011 -0.188 -0.038  0.086 -0.013 -0.113 -0.063 -0.113  0.111  0.086  0.061  0.360  0.036 -0.138 -0.088 -0.213 -0.038 -0.063 -0.163  0.061  0.335 -0.188 -0.138  0.186 -0.238 -0.063 -0.113  0.061 -0.088  0.011  0.285  0.211  0.261 -0.063 -0.213 
 0.089  0.064  0.089 -0.061 -0.185 -0.111 -0.111 -0.036  0.064 -0.061  0.114 -0.160  0.064 -0.011  0.014  0.014  0.089 -0.160  0.014 -0.136  0.188 -0.061  0.089 -0.036  0.039 -0.061  0.163 -0.185  0.139 -0.011  0.288 -0.036 -0.111 -0.086 -0.086 -0.185  0.039 -0.011  0.089  0.114 -0.061  0.014 -0.111  0.039 -0.061  0.338 -0.160 -0.136 -0.086 -0.210 -0.086  0.064 -0.160 -0.235 -0.036 -0.086  0.039  0.039 -0.235 -0.111 -0.136  0.188  0.114 -0.086 -0.111 -0.011 -0.235 -0.061  0.064 -0.036 -0.136 -0.086 -0.086  0.114  0.089  0.039  0.363  0.039 -0.160 -0.011 -0.235 -0.061 -0.061 -0.160  0.039  0.338 -0.185 -0.136  0.163 -0.260 -0.061 -0.111  0.139 -0.111  0.039  0.263  0.188  0.288 -0.086 -0.210 
 0.110  0.110  0.085 -0.064 -0.214 -0.114 -0.089  0.010  0.060 -0.014  0.135 -0.139  0.060 -0.014  0.035  0.035  0.160 -0.164  0.010 -0.139  0.185 -0.039  0.060 -0.039  0.010 -0.039  0.135 -0.189  0.135 -0.064  0.284 -0.064 -0.114 -0.089 -0.014 -0.214  0.010  0.035  0.110  0.085  0.035 -0.014 -0.114  0.060 -0.064  0.334 -0.164 -0.089 -0.114 -0.164 -0.039  0.060 -0.164 -0.264 -0.014 -0.114  0.060  0.060 -0.239 -0.064 -0.139  0.185  0.035 -0.064 -0.114 -0.014 -0.239 -0.039  0.060 -0.039 -0.139 -0.089 -0.089  0.110  0.085  0.035  0.359  0.035 -0.164 -0.014 -0.239 -0.064 -0.064 -0.164  0.035  0.334 -0.139 -0.139  0.160 -0.239 -0.039 -0.089  0.210 -0.114  0.035  0.260  0.160  0.284 -0.089 -0.214 
 0.083  0.133  0.058 -0.067 -0.191 -0.117 -0.092  0.033  0.108  0.083  0.108 -0.117  0.033 -0.017  0.008  0.033  0.182 -0.191  0.033 -0.166  0.157 -0.042  0.058 -0.042  0.033 -0.017  0.108 -0.241  0.083 -0.092  0.282 -0.067 -0.142 -0.092  0.033 -0.216  0.008  0.033  0.108  0.083  0.008 -0.017 -0.092  0.058 -0.067  0.382 -0.166 -0.117 -0.191 -0.166  0.008  0.008 -0.166 -0.291  0.058 -0.142  0.108  0.058 -0.216 -0.017 -0.142  0.207  0.058 -0.067 -0.117 -0.017 -0.241 -0.017  0.033  0.008 -0.142 -0.067 -0.067  0.157  0.083  0.058  0.382  0.083 -0.117 -0.017 -0.241 -0.067 -0.067 -0.166  0.058  0.357 -0.117 -0.142  0.108 -0.216 -0.042 -0.067  0.257 -0.142  0.008  0.207  0.157  0.282 -0.117 -0.241 
 0.108  0.133  0.033 -0.067 -0.191 -0.117 -0.092  0.033  0.108  0.058  0.108 -0.117  0.008 -0.017  0.008  0.033  0.182 -0.191  0.008 -0.166  0.157 -0.042  0.058 -0.042  0.033  0.008  0.108 -0.241  0.083 -0.092  0.282 -0.067 -0.166 -0.092  0.058 -0.216  0.008  0.058  0.133  0.083  0.033 -0.017 -0.092  0.058 -0.092  0.382 -0.142 -0.117 -0.191 -0.166  0.033 -0.017 -0.166 -0.291  0.083 -0.166  0.108  0.058 -0.216 -0.017 -0.142  0.182  0.083 -0.067 -0.117 -0.017 -0.216 -0.017  0.033  0.008 -0.142 -0.067 -0.067  0.182  0.083  0.058  0.407  0.083 -0.117 -0.017 -0.241 -0.067 -0.067 -0.166  0.108  0.357 -0.117 -0.142  0.083 -0.216 -0.042 -0.092  0.257 -0.142 -0.017  0.207  0.157  0.282 -0.142 -0.266 
 0.128  0.152  0.003 -0.097 -0.196 -0.072 -0.097  0.028  0.103  0.103  0.078 -0.122  0.003 -0.047  0.003  0.053  0.202 -0.196  0.003 -0.171  0.152  0.003  0.103 -0.047  0.053  0.028  0.177 -0.271  0.078 -0.097  0.277 -0.072 -0.171 -0.122  0.053 -0.221  0.078  0.053  0.128  0.028  0.028  0.003 -0.072  0.028 -0.122  0.377 -0.146 -0.122 -0.196 -0.171  0.028 -0.022 -0.146 -0.296  0.177 -0.146  0.103  0.053 -0.221 -0.022 -0.122  0.177  0.078 -0.072 -0.122 -0.022 -0.196  0.003  0.028  0.003 -0.146 -0.072 -0.047  0.202  0.078  0.053  0.402  0.078 -0.122  0.003 -0.271 -0.072 -0.072 -0.171  0.103  0.377 -0.122 -0.146  0.053 -0.221 -0.047 -0.097  0.252 -0.146  0.028  0.202  0.152  0.277 -0.171 -0.246 
 0.123  0.148 -0.001 -0.101 -0.176 -0.076 -0.101  0.023  0.098  0.098  0.073 -0.126  0.023 -0.051 -0.001  0.023  0.198 -0.201 -0.026 -0.151  0.148 -0.001  0.098 -0.051  0.048  0.023  0.173 -0.276  0.073 -0.101  0.248 -0.076 -0.176 -0.151  0.048 -0.226  0.098  0.098  0.123 -0.001  0.023  0.073 -0.076  0.023 -0.101  0.372 -0.151 -0.026 -0.201 -0.176  0.048 -0.026 -0.151 -0.300  0.173 -0.126  0.098  0.048 -0.226 -0.026 -0.151  0.173  0.073 -0.076 -0.126 -0.026 -0.201 -0.001  0.048 -0.001 -0.151 -0.051 -0.051  0.223  0.123  0.048  0.422  0.073 -0.126  0.023 -0.276 -0.076 -0.051 -0.176  0.098  0.372 -0.126 -0.151  0.048 -0.201 -0.051 -0.101  0.248 -0.151  0.023  0.198  0.148  0.273 -0.176 -0.251 
 0.122  0.146 -0.003 -0.103 -0.177 -0.053 -0.103  0.022  0.122  0.097  0.072 -0.078  0.072 -0.053 -0.003  0.022  0.171 -0.177 -0.078 -0.128  0.146 -0.003  0.097 -0.053  0.022  0.047  0.221 -0.252  0.097 -0.078  0.246 -0.103 -0.152 -0.152  0.047 -0.227  0.097  0.122  0.122 -0.078 -0.003  0.122 -0.053  0.022 -0.103  0.396 -0.152 -0.028 -0.202 -0.152  0.072 -0.053 -0.152 -0.302  0.196 -0.103  0.122  0.047 -0.227 -0.028 -0.152  0.146  0.072 -0.078 -0.128 -0.053 -0.227 -0.003  0.047  0.022 -0.152 -0.053 -0.053  0.221  0.072  0.022  0.421  0.097 -0.128  0.047 -0.277 -0.078 -0.078 -0.177  0.072  0.346 -0.128 -0.152 -0.003 -0.202 -0.053 -0.053  0.246 -0.152  0.047  0.171  0.097  0.296 -0.177 -0.252 
 0.150  0.150  0.000 -0.099 -0.174 -0.024 -0.099  0.025  0.125  0.100  0.075 -0.049  0.050 -0.049  0.000  0.000  0.175 -0.174 -0.099 -0.124  0.150  0.025  0.100 -0.049  0.025  0.050  0.225 -0.224  0.075 -0.074  0.250 -0.099 -0.149 -0.149  0.050 -0.249  0.100  0.125  0.125 -0.074  0.000  0.100 -0.049  0.050 -0.124  0.399 -0.149 -0.024 -0.199 -0.149  0.075 -0.074 -0.149 -0.298  0.175 -0.124  0.100  0.050 -0.224 -0.024 -0.149  0.150  0.075 -0.074 -0.124 -0.049 -0.224  0.000  0.050  0.025 -0.149 -0.049 -0.049  0.225  0.025  0.025  0.424  0.075 -0.124  0.075 -0.249 -0.074 -0.074 -0.174  0.075  0.349 -0.124 -0.199  0.000 -0.199 -0.049 -0.074  0.250 -0.149  0.025  0.150  0.075  0.299 -0.174 -0.249 
 0.151  0.151  0.001 -0.098 -0.173 -0.023 -0.098  0.026  0.151  0.151  0.076 -0.048  0.051 -0.048  0.001  0.001  0.201 -0.148 -0.098 -0.148  0.176  0.076  0.126 -0.073  0.001  0.051  0.251 -0.223  0.076 -0.073  0.251 -0.098 -0.173 -0.123  0.076 -0.248  0.101  0.101  0.126 -0.073  0.026  0.101 -0.048  0.051 -0.198  0.400 -0.148 -0.023 -0.198 -0.148  0.101 -0.098 -0.148 -0.273  0.176 -0.123  0.101  0.026 -0.223 -0.023 -0.148  0.126  0.076 -0.073 -0.123 -0.048 -0.223  0.001  0.026  0.051 -0.123 -0.048 -0.073  0.226  0.026  0.026  0.425  0.076 -0.123  0.076 -0.248 -0.048 -0.073 -0.173  0.051  0.325 -0.123 -0.198  0.001 -0.198 -0.048 -0.073  0.251 -0.123  0.026  0.151  0.076  0.300 -0.148 -0.248 
 0.150  0.150  0.001 -0.099 -0.173 -0.024 -0.099  0.026  0.150  0.175  0.076 -0.049  0.076 -0.049  0.001  0.001  0.200 -0.148 -0.099 -0.148  0.175  0.076  0.126 -0.099  0.001  0.051  0.250 -0.223  0.076 -0.049  0.225 -0.124 -0.173 -0.124  0.101 -0.248  0.101  0.101  0.126 -0.074  0.026  0.101 -0.049  0.051 -0.198  0.400 -0.148 -0.024 -0.198 -0.148  0.101 -0.099 -0.148 -0.273  0.175 -0.124  0.101  0.026 -0.223 -0.049 -0.148  0.126  0.076 -0.074 -0.148 -0.049 -0.248  0.001  0.026  0.051 -0.124 -0.049 -0.049  0.225  0.026  0.026  0.425  0.076 -0.124  0.076 -0.248 -0.049 -0.074 -0.173  0.026  0.325 -0.124 -0.198  0.001 -0.198 -0.049 -0.049  0.250 -0.124  0.026  0.150  0.076  0.275 -0.148 -0.248 
 0.125  0.150  0.000 -0.099 -0.174 -0.024 -0.099  0.025  0.150  0.200  0.075 -0.049  0.075 -0.049  0.000  0.000  0.200 -0.149 -0.099 -0.149  0.175  0.075  0.125 -0.099  0.000  0.050  0.250 -0.224  0.075 -0.049  0.225 -0.124 -0.199 -0.099  0.150 -0.249  0.100  0.100  0.125 -0.049  0.025  0.100 -0.049  0.050 -0.199  0.399 -0.149 -0.024 -0.199 -0.149  0.100 -0.124 -0.149 -0.274  0.150 -0.149  0.100  0.025 -0.224 -0.049 -0.149  0.125  0.075 -0.099 -0.149 -0.049 -0.249  0.000  0.025  0.050 -0.124 -0.049 -0.049  0.225  0.025  0.025  0.424  0.075 -0.124  0.075 -0.249 -0.049 -0.074 -0.174  0.000  0.324 -0.124 -0.199  0.000 -0.199 -0.049 -0.049  0.250 -0.124  0.025  0.150  0.075  0.275 -0.149 -0.249 
 0.101  0.150  0.001 -0.099 -0.173 -0.024 -0.099  0.026  0.150  0.200  0.076 -0.024  0.076 -0.024  0.001  0.001  0.200 -0.148 -0.099 -0.148  0.175  0.076  0.126 -0.099 -0.024  0.051  0.275 -0.198  0.076 -0.049  0.225 -0.124 -0.198 -0.099  0.126 -0.248  0.101  0.101  0.126 -0.074  0.026  0.101 -0.049  0.051 -0.198  0.425 -0.148 -0.024 -0.198 -0.148  0.101 -0.124 -0.148 -0.273  0.150 -0.148  0.101  0.026 -0.223 -0.049 -0.148  0.101  0.076 -0.099 -0.148 -0.049 -0.248  0.001  0.026  0.051 -0.124 -0.049  0.001  0.250  0.026  0.026  0.425  0.076 -0.124  0.076 -0.248 -0.049 -0.074 -0.173  0.001  0.325 -0.124 -0.198  0.001 -0.198 -0.049 -0.049  0.250 -0.124  0.026  0.150  0.076  0.250 -0.148 -0.248 
 0.101  0.151  0.001 -0.098 -0.173 -0.023 -0.098  0.026  0.151  0.201  0.076 -0.023  0.076 -0.023  0.001  0.001  0.151 -0.123 -0.098 -0.148  0.176  0.101  0.126 -0.098 -0.023  0.051  0.276 -0.173  0.101 -0.048  0.226 -0.123 -0.173 -0.123  0.151 -0.248  0.076  0.076  0.126 -0.073  0.026  0.151 -0.048  0.051 -0.173  0.400 -0.198  0.001 -0.198 -0.148  0.126 -0.148 -0.148 -0.273  0.151 -0.148  0.126  0.001 -0.223 -0.048 -0.148  0.051  0.076 -0.098 -0.173 -0.048 -0.248  0.001  0.026  0.051 -0.123 -0.048  0.001  0.251  0.026  0.026  0.425  0.076 -0.123  0.076 -0.248 -0.048 -0.073 -0.173 -0.023  0.325 -0.098 -0.198  0.001 -0.198 -0.073 -0.048  0.251 -0.123  0.026  0.151  0.076  0.226 -0.148 -0.248 
 0.142  0.092  0.042 -0.057 -0.107 -0.032 -0.032  0.017  0.167  0.117  0.092 -0.032  0.117  0.042 -0.032 -0.007  0.092 -0.132 -0.107 -0.132  0.167  0.167  0.142 -0.082 -0.057  0.042  0.192 -0.157 -0.007 -0.057  0.142 -0.157 -0.132 -0.157  0.142 -0.182 -0.007  0.092  0.117 -0.032 -0.007  0.117 -0.032  0.017 -0.132  0.316 -0.132 -0.032 -0.132 -0.107  0.142 -0.082 -0.107 -0.232  0.142 -0.082  0.117  0.042 -0.182 -0.007 -0.107  0.092 -0.057 -0.057 -0.107 -0.107 -0.182 -0.007 -0.007 -0.007 -0.207  0.017 -0.007  0.242  0.042  0.042  0.391  0.092 -0.082 -0.057 -0.207 -0.032 -0.057 -0.132  0.017  0.291 -0.082 -0.157 -0.007 -0.207 -0.107 -0.057  0.291 -0.132  0.067  0.167  0.092  0.217 -0.082 -0.182 
 0.125  0.100  0.075 -0.100 -0.050  0.000  0.000  0.050  0.174  0.000  0.075  0.000  0.075  0.000  0.000  0.000  0.100 -0.125 -0.100 -0.075  0.100  0.025  0.100 -0.025 -0.075  0.050  0.174 -0.100  0.050 -0.025  0.075 -0.100 -0.149 -0.174  0.100 -0.125 -0.050  0.125  0.050 -0.025  0.000  0.075  0.000  0.025 -0.100  0.299 -0.125  0.000 -0.050 -0.125  0.100  0.000 -0.100 -0.174  0.025 -0.050  0.125  0.025 -0.100  0.050 -0.025  0.125  0.000 -0.050 -0.050 -0.025 -0.100 -0.075  0.025 -0.100 -0.149  0.000 -0.025  0.149  0.075  0.075  0.249  0.100 -0.050 -0.025 -0.149 -0.050  0.025 -0.075  0.075  0.224 -0.075 -0.100 -0.075 -0.174 -0.050 -0.100  0.224 -0.100  0.125  0.149  0.075  0.174 -0.050 -0.149 
 0.113  0.113  0.088 -0.087 -0.062 -0.037  0.013  0.038  0.162 -0.037  0.088 -0.012  0.063  0.013 -0.012  0.013  0.113 -0.112 -0.087 -0.062  0.088  0.038  0.013  0.013 -0.062  0.038  0.138 -0.087  0.013 -0.012  0.088 -0.087 -0.137 -0.161  0.088 -0.112 -0.037  0.138  0.038 -0.012 -0.012  0.088  0.013  0.063 -0.087  0.237 -0.112  0.013 -0.037 -0.112  0.113  0.013 -0.087 -0.161 -0.012 -0.037  0.113  0.038 -0.087  0.063 -0.062  0.113  0.013 -0.062 -0.037 -0.012 -0.087 -0.062  0.038 -0.112 -0.137 -0.012 -0.037  0.162  0.038  0.088  0.237  0.088 -0.037 -0.012 -0.137 -0.112  0.038 -0.062  0.088  0.187 -0.062 -0.087 -0.087 -0.161 -0.062 -0.087  0.237 -0.087  0.113  0.162  0.038  0.162 -0.037 -0.161 
 0.109  0.109  0.084 -0.091 -0.066 -0.041 -0.016  0.034  0.134 -0.066  0.059 -0.016  0.084  0.034 -0.016  0.084  0.084 -0.091 -0.091 -0.041  0.109  0.009 -0.016  0.009 -0.066  0.059  0.109 -0.041  0.009 -0.016  0.084 -0.066 -0.141 -0.141  0.084 -0.091 -0.016  0.158 -0.016  0.009 -0.016  0.109  0.059  0.109 -0.066  0.158 -0.091  0.009 -0.016 -0.091  0.134 -0.016 -0.041 -0.141 -0.066 -0.041  0.134 -0.016 -0.066  0.084 -0.066  0.158  0.009 -0.041 -0.016  0.009 -0.066 -0.016  0.034 -0.116 -0.116  0.009 -0.041  0.158  0.059  0.158  0.208  0.134 -0.016  0.009 -0.091 -0.116  0.034 -0.041  0.084  0.134 -0.066 -0.066 -0.091 -0.141 -0.016 -0.066  0.183 -0.066  0.134  0.134  0.034  0.084 -0.016 -0.141 
 0.116  0.066  0.091 -0.083 -0.058 -0.058 -0.033  0.041  0.141 -0.058  0.041 -0.008  0.091  0.041 -0.008  0.066  0.041 -0.083 -0.108 -0.033  0.091  0.016 -0.008  0.016 -0.058  0.066  0.091 -0.033  0.016 -0.033  0.066 -0.058 -0.133 -0.133  0.016 -0.083 -0.008  0.141 -0.008  0.016 -0.008  0.091  0.066  0.066 -0.058  0.141 -0.083  0.016 -0.008 -0.083  0.116 -0.008 -0.033 -0.133 -0.008 -0.008  0.166 -0.008 -0.083  0.066 -0.083  0.141  0.016 -0.033 -0.058  0.016 -0.083 -0.008  0.016 -0.133 -0.108  0.016 -0.033  0.166  0.041  0.191  0.216  0.116 -0.008 -0.008 -0.083 -0.108  0.016 -0.033 -0.008  0.091 -0.083 -0.058 -0.083 -0.133 -0.008 -0.083  0.191 -0.058  0.141  0.141  0.041  0.066 -0.008 -0.133 
 0.105  0.055  0.105 -0.070 -0.070 -0.045 -0.045  0.055  0.130 -0.045  0.005  0.005  0.105  0.030  0.005  0.080  0.005 -0.095 -0.095 -0.045  0.030  0.005  0.005  0.005 -0.045  0.080  0.005 -0.020 -0.020  0.005  0.055 -0.045 -0.120 -0.120  0.005 -0.045  0.005  0.154 -0.020  0.030 -0.020  0.105  0.055  0.055 -0.045  0.154 -0.070  0.030 -0.020 -0.070  0.130  0.005 -0.020 -0.120  0.005 -0.020  0.204 -0.095 -0.070  0.055 -0.070  0.154  0.005 -0.020 -0.045  0.030 -0.095  0.005  0.005 -0.120 -0.095  0.030 -0.020  0.154  0.055  0.204  0.204  0.105  0.005  0.005 -0.070 -0.095  0.030 -0.020 -0.020  0.080 -0.070 -0.070 -0.070 -0.120  0.005 -0.070  0.179 -0.045  0.130  0.154  0.055  0.080  0.005 -0.120 
 0.112  0.062  0.112 -0.063 -0.063 -0.038 -0.038  0.062  0.137 -0.038  0.012  0.012  0.112  0.012  0.012  0.087  0.012 -0.088 -0.088 -0.038  0.012 -0.013  0.012  0.012 -0.038  0.087  0.012 -0.038 -0.038  0.012  0.062 -0.038 -0.113 -0.113  0.012 -0.038  0.012  0.161 -0.013  0.037 -0.013  0.112  0.062  0.062 -0.038  0.112 -0.063  0.012 -0.038 -0.088  0.112  0.012 -0.013 -0.113 -0.013 -0.038  0.211 -0.088 -0.063  0.037 -0.063  0.161 -0.013 -0.013 -0.038  0.037 -0.088  0.012 -0.013 -0.113 -0.088  0.037 -0.013  0.137  0.062  0.211  0.211  0.112  0.012  0.012 -0.063 -0.088  0.037 -0.038 -0.013  0.087 -0.063 -0.088 -0.088 -0.113  0.012 -0.063  0.112 -0.038  0.112  0.161  0.062  0.087  0.012 -0.113 
 0.069  0.069  0.094 -0.055 -0.055 -0.030 -0.030  0.044  0.144 -0.030  0.019 -0.005  0.094 -0.005  0.019  0.094 -0.030 -0.055 -0.080 -0.030 -0.005 -0.005 -0.005  0.019 -0.030  0.094  0.019 -0.030 -0.055  0.019  0.044 -0.055 -0.105 -0.105 -0.030 -0.030 -0.030  0.144 -0.005  0.044 -0.030  0.119  0.069  0.069 -0.030  0.119 -0.055 -0.030 -0.030 -0.080  0.119 -0.005 -0.005 -0.105 -0.005 -0.030  0.194 -0.080 -0.055  0.044 -0.055  0.169 -0.030 -0.030 -0.030 -0.005 -0.105 -0.005 -0.005 -0.105 -0.105  0.044 -0.005  0.069  0.069  0.244  0.144  0.094  0.019  0.019 -0.055 -0.080  0.019 -0.030 -0.005  0.069 -0.030 -0.080 -0.080 -0.105 -0.005 -0.055  0.094 -0.030  0.094  0.119  0.069  0.094  0.019 -0.105 
 0.051  0.076  0.101 -0.049 -0.049 -0.074 -0.024  0.051  0.150 -0.049  0.026 -0.024  0.076  0.001  0.001  0.101 -0.024 -0.049 -0.074 -0.024  0.001  0.001  0.001  0.026 -0.024  0.076  0.001 -0.024 -0.049  0.026  0.051 -0.074 -0.099 -0.099 -0.049 -0.024 -0.049  0.150  0.001  0.051 -0.099  0.101  0.051  0.076 -0.024  0.126 -0.049 -0.024 -0.074 -0.074  0.126 -0.049 -0.024 -0.099 -0.024 -0.024  0.175 -0.074 -0.049  0.026 -0.049  0.126 -0.024 -0.074 -0.024  0.001 -0.099  0.001  0.001 -0.099 -0.099  0.051 -0.024  0.051  0.051  0.200  0.126  0.051  0.026  0.001 -0.049 -0.074  0.026 -0.049  0.001  0.051 -0.024 -0.074 -0.074 -0.099  0.001 -0.074  0.051 -0.024  0.076  0.126  0.076  0.001  0.026 -0.099 
 0.038  0.088  0.113 -0.036 -0.036 -0.061 -0.011  0.063  0.163 -0.036 -0.011 -0.011  0.038  0.013  0.013  0.113 -0.036 -0.036 -0.061 -0.011  0.013 -0.011  0.013  0.013 -0.011  0.038  0.013 -0.011 -0.036  0.038  0.013 -0.061 -0.086 -0.086 -0.061 -0.011 -0.086  0.113  0.013  0.063 -0.086  0.113  0.063  0.088 -0.011  0.138 -0.036 -0.036 -0.061 -0.086  0.088 -0.061 -0.011 -0.086 -0.011 -0.011  0.063 -0.061 -0.036  0.013 -0.061  0.088 -0.011 -0.061 -0.011  0.013 -0.086  0.013 -0.011 -0.086 -0.086  0.013 -0.011  0.013  0.038  0.188  0.088  0.063  0.038  0.013 -0.036 -0.086  0.038 -0.061  0.013  0.063 -0.036 -0.061 -0.086 -0.086 -0.011 -0.061 -0.011 -0.011  0.063  0.113 -0.011 -0.011  0.038 -0.086 
 0.025  0.100  0.125 -0.024 -0.049 -0.049 -0.024  0.050  0.150 -0.024  0.000 -0.024  0.025  0.025  0.025  0.100 -0.024 -0.024 -0.049  0.000  0.025 -0.024  0.025  0.000  0.000  0.050  0.000 -0.024 -0.024  0.000  0.000 -0.074 -0.074 -0.074 -0.049  0.000 -0.074  0.125  0.000  0.075 -0.074  0.125  0.050  0.075  0.000  0.150 -0.024 -0.024 -0.049 -0.074  0.050 -0.049  0.000 -0.074  0.000 -0.024 -0.024 -0.049 -0.024  0.000 -0.074  0.075 -0.024 -0.049  0.000  0.025 -0.074  0.000  0.000 -0.074 -0.074  0.000  0.000  0.025  0.050  0.150  0.075  0.075  0.050  0.025 -0.024 -0.074  0.025 -0.049 -0.024  0.050 -0.024 -0.049 -0.074 -0.074 -0.024 -0.049  0.000 -0.024  0.075  0.075  0.000  0.000  0.025 -0.074 
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 0.054 -0.021  0.004 -0.046 -0.071  0.054  0.079  0.029  0.403  0.702 -0.021  0.452  0.153 -0.021  0.153  0.054  0.303 -0.021  0.153  0.004 -0.046  0.104  0.004  0.104 -0.071  0.178  0.378  0.029  0.153  0.004  0.527 -0.071 -0.096  0.427  0.801 -0.071 -0.021  0.054  0.004  0.228  0.278  0.004  0.702  0.253 -0.145  0.153 -0.021  0.153 -0.021 -0.096 -0.046 -0.021  0.129 -0.021  0.079  0.452  0.004 -0.071 -0.021 -0.096 -0.145 -0.046 -0.145 -0.071 -0.021 -0.096 -0.096 -0.046  0.004 -0.071 -0.121  0.751  0.004 -0.195  0.353  0.029 -0.071  0.303 -0.071  0.054 -0.071 -0.046 -0.121 -0.170  0.403 -0.021 -0.145  0.004  0.079 -0.046 -0.096 -0.145  0.004  0.178 -0.021 -0.121 -0.021  0.129 -0.071 -0.170 
 0.021 -0.053  0.021  0.021 -0.053  0.021  0.171  0.096  0.470  0.744  0.021  0.520  0.196 -0.003  0.146  0.046  0.370 -0.028  0.146  0.021 -0.053  0.171  0.096  0.096 -0.103  0.196  0.445 -0.003  0.121 -0.003  0.644 -0.003 -0.103  0.420  0.769 -0.078 -0.028  0.121  0.046  0.246  0.370 -0.003  0.719  0.271 -0.078  0.221 -0.053  0.121 -0.028 -0.128 -0.078  0.121  0.096 -0.028  0.071  0.594 -0.053 -0.053 -0.053 -0.128 -0.128 -0.028 -0.153 -0.003 -0.053 -0.128 -0.053 -0.053  0.071 -0.103 -0.153  0.569 -0.028 -0.203  0.345  0.021 -0.053  0.295 -0.078  0.071 -0.103 -0.053 -0.153 -0.178  0.445 -0.003 -0.178 -0.003  0.096 -0.078 -0.128 -0.153  0.071  0.196 -0.028 -0.103 -0.078  0.196 -0.028 -0.203 
 0.034 -0.065  0.009  0.034 -0.090  0.009  0.259  0.109  0.483  0.732  0.159  0.433  0.184  0.034  0.159  0.059  0.383 -0.040  0.109 -0.015 -0.040  0.184  0.084  0.084 -0.090  0.184  0.508 -0.015  0.109  0.009  0.657 -0.040 -0.090  0.408  0.732 -0.090 -0.040  0.159  0.084  0.333  0.408 -0.015  0.707  0.308 -0.090  0.259 -0.065  0.109 -0.040 -0.140 -0.090  0.109  0.109 -0.015  0.059  0.582 -0.090 -0.065 -0.065 -0.140 -0.115  0.009 -0.165  0.009 -0.065 -0.140 -0.065 -0.040  0.059 -0.090 -0.165  0.582  0.009 -0.215  0.383  0.034 -0.065  0.234 -0.090  0.109 -0.140 -0.040 -0.190 -0.190  0.483  0.034 -0.190 -0.015  0.059 -0.090 -0.140 -0.140  0.134  0.159 -0.040 -0.065 -0.090  0.184 -0.040 -0.215 
 0.071 -0.079 -0.004  0.021 -0.029 -0.004  0.295  0.195  0.594  0.694  0.245  0.395  0.220  0.071  0.145  0.046  0.444 -0.054  0.121 -0.004 -0.054  0.170  0.096  0.071  0.021  0.245  0.544 -0.029  0.096 -0.054  0.694 -0.054 -0.129  0.370  0.694 -0.054 -0.004  0.170  0.096  0.370  0.420 -0.029  0.669  0.320 -0.079  0.295 -0.079  0.121 -0.029 -0.104 -0.104  0.096  0.071 -0.054  0.046  0.569 -0.129 -0.029 -0.079 -0.153 -0.104  0.021 -0.178 -0.004 -0.079 -0.153 -0.104 -0.029  0.046 -0.079 -0.178  0.519  0.021 -0.228  0.370  0.071 -0.079  0.145 -0.079  0.096 -0.178 -0.029 -0.203 -0.203  0.444  0.021 -0.178 -0.004  0.046 -0.129 -0.129 -0.153  0.145  0.170 -0.054 -0.054 -0.104  0.220 -0.054 -0.228 
 0.046 -0.078  0.021  0.021 -0.028 -0.003  0.320  0.246  0.594  0.694  0.295  0.395  0.246  0.121  0.146  0.021  0.445 -0.053  0.121 -0.003 -0.028  0.146  0.096  0.071  0.096  0.246  0.569 -0.003  0.071 -0.078  0.669 -0.053 -0.128  0.370  0.694 -0.053  0.021  0.146  0.071  0.395  0.420 -0.028  0.644  0.295 -0.078  0.295 -0.103  0.146 -0.028 -0.103 -0.103  0.096  0.071 -0.053  0.046  0.569 -0.153 -0.028 -0.103 -0.153 -0.103  0.046 -0.153 -0.003 -0.078 -0.153 -0.103 -0.103  0.021 -0.078 -0.153  0.445  0.021 -0.228  0.345  0.046 -0.078  0.146 -0.078  0.096 -0.178 -0.028 -0.203 -0.203  0.420  0.021 -0.153 -0.003  0.046 -0.128 -0.103 -0.178  0.121  0.146 -0.053 -0.053 -0.128  0.246 -0.053 -0.203 
 0.088 -0.087  0.038  0.063  0.038  0.063  0.387  0.237  0.636  0.661  0.387  0.436  0.287  0.138  0.187 -0.012  0.436 -0.087  0.138  0.013 -0.037  0.138  0.088  0.063  0.113  0.237  0.561 -0.012  0.038 -0.062  0.636 -0.037 -0.161  0.362  0.661 -0.012  0.013  0.162  0.063  0.412  0.412 -0.087  0.611  0.287 -0.037  0.337 -0.112  0.162 -0.037 -0.112 -0.087  0.088  0.063 -0.087  0.038  0.561 -0.186 -0.012 -0.112 -0.161 -0.112  0.038 -0.137 -0.012 -0.087 -0.161 -0.112 -0.112  0.013 -0.087 -0.161  0.412  0.013 -0.236  0.312  0.063 -0.087  0.138 -0.087  0.088 -0.186 -0.037 -0.211 -0.211  0.362  0.038 -0.161 -0.037  0.038 -0.161 -0.112 -0.186  0.138  0.138 -0.062 -0.062 -0.137  0.262 -0.012 -0.186 
 0.108 -0.091  0.033  0.083  0.033  0.083  0.407  0.258  0.631  0.656  0.457  0.457  0.283  0.133  0.183 -0.016  0.432 -0.091  0.133  0.008 -0.041  0.133  0.083  0.108  0.108  0.258  0.557  0.008  0.008 -0.041  0.606 -0.041 -0.166  0.283  0.656  0.033  0.008  0.183  0.058  0.407  0.407 -0.091  0.606  0.307  0.008  0.332 -0.116  0.158 -0.016 -0.116 -0.091  0.108  0.058 -0.116  0.033  0.532 -0.191 -0.016 -0.116 -0.166 -0.116  0.083 -0.091  0.033 -0.091 -0.166 -0.116 -0.116  0.008 -0.066 -0.166  0.407  0.008 -0.241  0.258  0.033 -0.091  0.133 -0.091  0.058 -0.191 -0.066 -0.191 -0.216  0.332  0.058 -0.166 -0.016  0.008 -0.166 -0.116 -0.191  0.133  0.133 -0.016 -0.066 -0.166  0.258 -0.016 -0.191 
 0.170 -0.104 -0.004  0.045  0.020  0.095  0.419  0.245  0.643  0.643  0.519  0.444  0.294  0.170  0.195 -0.029  0.444 -0.104  0.045  0.020 -0.004  0.120  0.070  0.120  0.095  0.270  0.568 -0.054  0.020 -0.004  0.544 -0.054 -0.179  0.245  0.618  0.145 -0.004  0.170  0.045  0.369  0.394 -0.104  0.568  0.294  0.020  0.319 -0.079  0.195 -0.029 -0.154 -0.104  0.095  0.070 -0.104  0.020  0.469 -0.229 -0.029 -0.129 -0.154 -0.129  0.095 -0.104  0.070 -0.104 -0.179 -0.104 -0.129 -0.004 -0.079 -0.179  0.369  0.045 -0.204  0.220  0.020 -0.054  0.145 -0.104  0.045 -0.229 -0.104 -0.204 -0.229  0.294  0.070 -0.229 -0.029 -0.079 -0.204 -0.104 -0.179  0.120  0.120 -0.029 -0.079 -0.154  0.245 -0.029 -0.204 
 0.165 -0.109 -0.009  0.115  0.015  0.090  0.414  0.265  0.613  0.613  0.588  0.439  0.314  0.165  0.215 -0.034  0.414 -0.134  0.015  0.040 -0.009  0.140  0.065  0.115  0.090  0.265  0.539 -0.059  0.040 -0.009  0.514 -0.059 -0.184  0.190  0.539  0.140 -0.034  0.240  0.040  0.364  0.389 -0.009  0.489  0.339  0.115  0.314 -0.084  0.215 -0.084 -0.184 -0.109  0.090  0.015 -0.109  0.015  0.439 -0.234 -0.034 -0.134 -0.159 -0.134  0.115 -0.084  0.065 -0.109 -0.209 -0.109 -0.159 -0.009 -0.084 -0.184  0.364  0.040 -0.209  0.215  0.040 -0.059  0.115 -0.059  0.065 -0.234 -0.109 -0.209 -0.259  0.289  0.065 -0.234 -0.059 -0.084 -0.209 -0.109 -0.184  0.115  0.115 -0.009 -0.059 -0.159  0.240 -0.034 -0.184 
 0.155 -0.069 -0.019  0.130  0.005  0.055  0.404  0.255  0.578  0.603  0.603  0.429  0.304  0.230  0.205 -0.094  0.379 -0.169 -0.019  0.005 -0.019  0.130  0.055  0.155  0.205  0.255  0.529 -0.069  0.030 -0.019  0.479 -0.069 -0.194  0.105  0.479  0.205 -0.069  0.205  0.055  0.354  0.379 -0.019  0.454  0.404  0.230  0.280 -0.044  0.255 -0.144 -0.194 -0.119  0.055  0.005 -0.144  0.030  0.379 -0.269 -0.019 -0.144 -0.169 -0.169  0.105 -0.094  0.030 -0.119 -0.244 -0.144 -0.194  0.030 -0.044 -0.194  0.329  0.030 -0.194  0.255  0.005  0.030  0.105 -0.144  0.055 -0.244 -0.119 -0.219 -0.269  0.230  0.080 -0.244 -0.069 -0.119 -0.194 -0.144 -0.219  0.055  0.055 -0.019 -0.069 -0.144  0.230 -0.019 -0.194 
 0.204 -0.020 -0.020  0.029 -0.045  0.079  0.328  0.229  0.503  0.553  0.528  0.453  0.328  0.204  0.229 -0.020  0.279 -0.095 -0.070 -0.070  0.029  0.104  0.054  0.104  0.129  0.229  0.428 -0.120  0.004  0.004  0.453  0.004 -0.170  0.029  0.428  0.179 -0.095  0.254  0.004  0.378  0.229  0.004  0.478  0.303  0.179  0.254 -0.045  0.204 -0.145 -0.195 -0.070  0.029  0.079 -0.095 -0.020  0.254 -0.195 -0.070 -0.120 -0.095 -0.120  0.054 -0.095  0.079 -0.120 -0.195 -0.095 -0.120  0.029  0.004 -0.170  0.378 -0.020 -0.145  0.179 -0.020  0.054  0.129 -0.095  0.104 -0.170 -0.095 -0.170 -0.195  0.279  0.129 -0.195 -0.070 -0.095 -0.145 -0.070 -0.145  0.054  0.054 -0.020 -0.020 -0.120  0.204  0.029 -0.195 
 0.197  0.022  0.022 -0.002 -0.052  0.072  0.247  0.197  0.471  0.471  0.496  0.371  0.222  0.097  0.122 -0.052  0.272 -0.077 -0.127 -0.052  0.047  0.122  0.047 -0.027  0.097  0.247  0.346 -0.077 -0.027  0.022  0.421 -0.052 -0.102 -0.002  0.421  0.172 -0.052  0.122  0.047  0.321  0.272 -0.027  0.446  0.247  0.097  0.247 -0.002  0.122 -0.077 -0.102 -0.002  0.047  0.047 -0.052 -0.002  0.097 -0.127 -0.002 -0.077 -0.027 -0.077  0.072 -0.027  0.022 -0.077 -0.127 -0.077 -0.052  0.022  0.022 -0.102  0.272 -0.027 -0.127  0.147  0.022 -0.002  0.172 -0.077  0.072 -0.102 -0.102 -0.077 -0.127  0.047  0.097 -0.127 -0.102 -0.052 -0.077 -0.052 -0.077  0.097  0.047  0.022  0.022 -0.077  0.172  0.072 -0.102 
 0.191  0.041 -0.008 -0.008 -0.033  0.091  0.191  0.216  0.440  0.415  0.490  0.290  0.216  0.041  0.091 -0.033  0.266 -0.058 -0.108 -0.033  0.016  0.091  0.066 -0.008  0.066  0.166  0.315 -0.058 -0.058  0.041  0.365 -0.033 -0.083  0.016  0.365  0.166 -0.033  0.116 -0.008  0.315  0.216 -0.058  0.365  0.241  0.066  0.241 -0.008  0.066 -0.033 -0.083 -0.008  0.041  0.066 -0.033  0.016  0.116 -0.108  0.016 -0.058 -0.008 -0.058  0.016 -0.058  0.041 -0.133 -0.108 -0.083 -0.033  0.066  0.041 -0.083  0.266 -0.008 -0.083  0.141  0.016  0.016  0.191 -0.058  0.066 -0.108 -0.083 -0.058 -0.108  0.016  0.116 -0.108 -0.083 -0.033 -0.108 -0.083 -0.058  0.091  0.016  0.041  0.066 -0.058  0.191  0.041 -0.108 
 0.166  0.041  0.016 -0.058 -0.008  0.091  0.116  0.191  0.365  0.415  0.440  0.241  0.191 -0.008  0.066 -0.008  0.241 -0.058 -0.108 -0.008 -0.008  0.041  0.091  0.016  0.041  0.116  0.290 -0.033 -0.033  0.066  0.315 -0.033 -0.083  0.016  0.365  0.141 -0.033  0.066  0.016  0.266  0.191 -0.033  0.266  0.216  0.066  0.141 -0.008  0.016 -0.008 -0.083  0.016  0.016  0.041 -0.058  0.041  0.066 -0.083  0.016 -0.033  0.041 -0.033  0.041 -0.058 -0.008 -0.108 -0.058 -0.058 -0.033  0.066  0.041 -0.083  0.241  0.016 -0.058  0.041  0.016  0.016  0.216 -0.058  0.066 -0.083 -0.058 -0.083 -0.083 -0.008  0.141 -0.108 -0.083 -0.008 -0.083 -0.058 -0.033  0.116  0.016  0.041  0.091 -0.033  0.216  0.041 -0.108 
 0.153  0.054  0.029 -0.046  0.004  0.104  0.178  0.104  0.328  0.353  0.427  0.129  0.153 -0.021  0.054  0.004  0.228 -0.021 -0.096 -0.021  0.004  0.029  0.104  0.029 -0.021  0.129  0.178 -0.021 -0.021  0.079  0.303 -0.021 -0.071  0.004  0.278  0.129 -0.021  0.054  0.029  0.203  0.228 -0.021  0.253  0.228  0.054  0.104 -0.046  0.029  0.004 -0.071  0.004  0.004  0.079 -0.071  0.029  0.004 -0.071  0.029 -0.046  0.054 -0.046  0.054 -0.046 -0.046 -0.096 -0.046 -0.096 -0.021  0.104 -0.021 -0.071  0.178 -0.021 -0.046 -0.021  0.029  0.029  0.203 -0.071  0.054 -0.071 -0.046 -0.071 -0.071 -0.021  0.104 -0.096 -0.046 -0.021 -0.071 -0.046 -0.046  0.079  0.004  0.054  0.104 -0.021  0.153  0.079 -0.096 
 0.168  0.069  0.044 -0.031 -0.006  0.143  0.218  0.119  0.243  0.218  0.293  0.094  0.119 -0.031  0.069  0.019  0.218  0.019 -0.081 -0.006  0.019  0.044  0.069  0.069 -0.056  0.119  0.119 -0.006 -0.006  0.069  0.143 -0.006 -0.056 -0.056  0.243  0.044 -0.031  0.019 -0.006  0.143  0.193  0.019  0.243  0.243 -0.006  0.019 -0.056 -0.006  0.019 -0.056  0.019  0.019  0.094 -0.056  0.019 -0.031 -0.056  0.019 -0.031  0.069 -0.056  0.044 -0.031 -0.031 -0.081 -0.031 -0.081 -0.006  0.119 -0.006 -0.056  0.168 -0.031 -0.031 -0.006  0.019  0.044  0.193 -0.056  0.044 -0.056 -0.056 -0.056 -0.056 -0.006  0.119 -0.081 -0.031 -0.031 -0.081 -0.031 -0.031  0.069 -0.006  0.069  0.119 -0.006  0.143  0.069 -0.081 
 0.177  0.077  0.052 -0.022 -0.022  0.127  0.227  0.127  0.227  0.177  0.177  0.077  0.127 -0.022  0.077  0.027  0.227  0.027 -0.072  0.002  0.002  0.002  0.052  0.052 -0.047  0.127  0.077  0.002 -0.022  0.052  0.102 -0.022 -0.047 -0.047  0.277  0.027 -0.047  0.002  0.002  0.152  0.177  0.027  0.202  0.227 -0.022 -0.022 -0.047  0.002  0.027 -0.047  0.027 -0.022  0.102 -0.072  0.002 -0.022 -0.047  0.002 -0.047  0.077 -0.072  0.052 -0.022 -0.022 -0.072 -0.022 -0.072  0.002  0.052 -0.022 -0.047  0.152 -0.022 -0.022 -0.022  0.002  0.052  0.127 -0.047  0.027 -0.047 -0.047 -0.047 -0.047  0.002  0.102 -0.072 -0.022 -0.047 -0.072 -0.022 -0.022  0.027 -0.022  0.077  0.102 -0.022  0.102  0.052 -0.072 
 0.144  0.094  0.044 -0.030 -0.030  0.119  0.194  0.119  0.169  0.044  0.069  0.019  0.144 -0.030  0.044  0.019  0.169  0.019 -0.055 -0.005 -0.030  0.019  0.069  0.044 -0.030  0.094  0.044  0.019 -0.005  0.019  0.019 -0.005 -0.030 -0.030  0.219  0.019 -0.005  0.019 -0.005  0.069  0.169  0.044  0.144  0.194 -0.005 -0.005 -0.030  0.019  0.044 -0.030  0.019 -0.005  0.119 -0.055  0.019 -0.030 -0.030 -0.030 -0.030  0.069 -0.055  0.019 -0.005 -0.030 -0.055  0.019 -0.055  0.019  0.019 -0.005 -0.055  0.119 -0.005 -0.030 -0.005  0.019  0.044  0.094 -0.030  0.019 -0.030 -0.030 -0.030 -0.055  0.019  0.069 -0.055 -0.005 -0.030 -0.055 -0.005 -0.030  0.044 -0.030  0.119  0.119 -0.005  0.019  0.069 -0.055 
 0.132  0.107  0.032 -0.018 -0.018  0.107  0.206  0.082  0.107  0.057 -0.018  0.007  0.082 -0.043  0.057 -0.018  0.132  0.032 -0.043  0.007 -0.043  0.032  0.057  0.057 -0.018  0.057  0.057  0.032  0.032 -0.018  0.007 -0.018 -0.018 -0.018  0.132  0.007  0.007  0.007  0.007  0.082  0.132  0.007  0.107  0.156 -0.043 -0.018 -0.018  0.007  0.032 -0.018  0.032  0.007  0.107 -0.043  0.007 -0.043 -0.018 -0.018 -0.018  0.057 -0.043 -0.018  0.007 -0.043 -0.043  0.032 -0.043  0.032  0.007 -0.018 -0.043  0.107  0.007 -0.018 -0.018  0.007  0.057  0.057 -0.018  0.007 -0.018 -0.018 -0.018 -0.043 -0.018  0.057 -0.043  0.007 -0.018 -0.043 -0.018 -0.018  0.032 -0.018  0.107  0.132  0.007  0.032  0.082 -0.043 
 0.099  0.099 -0.025 -0.025 -0.000  0.074  0.074  0.024  0.074 -0.000 -0.000 -0.000  0.024 -0.025 -0.000 -0.000  0.074  0.024 -0.025  0.024 -0.025  0.049  0.024  0.049 -0.025  0.024  0.024  0.049 -0.000 -0.000  0.024 -0.025 -0.025 -0.000  0.049  0.024 -0.000 -0.000 -0.000 -0.000  0.049  0.024  0.049  0.074 -0.025 -0.000 -0.000  0.024  0.049 -0.000  0.049 -0.000  0.074 -0.025  0.024 -0.025 -0.000 -0.000 -0.025 -0.000 -0.025 -0.025 -0.000 -0.000 -0.025 -0.025 -0.025 -0.000  0.024 -0.000 -0.025  0.124 -0.000 -0.000 -0.000 -0.000 -0.025  0.049 -0.000 -0.025 -0.000 -0.000 -0.025 -0.025 -0.000  0.024 -0.025  0.024 -0.000 -0.025 -0.025 -0.025 -0.000 -0.025  0.024  0.024 -0.000 -0.025 -0.000 -0.025 
 0.078  0.028 -0.022 -0.022  0.003  0.078  0.053  0.003  0.053  0.003  0.003  0.003  0.003 -0.022  0.003 -0.022  0.028  0.028  0.003  0.003  0.003  0.053  0.028  0.053 -0.022  0.028  0.028  0.028  0.003  0.003  0.028 -0.022 -0.022  0.003 -0.022  0.028 -0.022  0.003  0.003  0.003  0.053  0.003  0.003  0.053 -0.022  0.003  0.003  0.028  0.053  0.003  0.053  0.003  0.078  0.003  0.028 -0.022  0.003  0.003 -0.022  0.003 -0.022 -0.022  0.003  0.003 -0.022 -0.022 -0.022 -0.022  0.003 -0.022 -0.022  0.078  0.003  0.003  0.003  0.003 -0.022  0.053  0.003 -0.022  0.003  0.003 -0.022 -0.022 -0.022  0.028 -0.022  0.028  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.028  0.028  0.003 -0.022  0.003 -0.022 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.125  0.000 -0.024 -0.024  0.000  0.150  0.075 -0.024  0.050  0.000  0.050  0.000  0.025 -0.024  0.050 -0.024  0.025  0.025  0.000  0.000  0.000  0.075  0.025  0.025 -0.024  0.025  0.025  0.025  0.000  0.000  0.000 -0.024 -0.024  0.000 -0.024  0.025 -0.024  0.000  0.000  0.000  0.050  0.025  0.025  0.100 -0.024  0.000  0.000  0.000  0.100  0.000  0.050  0.000  0.075  0.025  0.050  0.000  0.000  0.000 -0.024  0.000  0.050 -0.024  0.000  0.000 -0.024 -0.024 -0.024  0.000  0.000 -0.024 -0.024  0.025  0.000  0.000 -0.024  0.000 -0.024  0.050  0.000 -0.024  0.000  0.000 -0.024 -0.024 -0.024  0.025 -0.024  0.025  0.000 -0.024 -0.024  0.000  0.000 -0.024  0.000  0.000 -0.024  0.000  0.000 -0.024 
 0.192  0.017 -0.032 -0.032 -0.007  0.192  0.167 -0.032  0.067 -0.007  0.067 -0.007  0.017 -0.032  0.092 -0.032  0.017  0.017 -0.007 -0.007 -0.007  0.067  0.042  0.017 -0.032  0.017  0.017  0.017 -0.007 -0.007 -0.007 -0.032 -0.032 -0.007 -0.032  0.017 -0.032 -0.007 -0.007  0.017  0.067  0.017  0.042  0.217 -0.032 -0.007 -0.007 -0.007  0.142 -0.007  0.067 -0.007  0.067  0.042  0.067  0.017  0.017 -0.007 -0.032 -0.007  0.042 -0.032 -0.007  0.017 -0.032 -0.032 -0.032  0.017  0.042 -0.032 -0.032  0.017 -0.007 -0.007 -0.032 -0.007  0.017  0.092 -0.007 -0.007 -0.007 -0.007 -0.032 -0.032 -0.007  0.067 -0.032  0.017 -0.007 -0.032 -0.032 -0.007  0.017 -0.032  0.017 -0.007 -0.032  0.017  0.042 -0.032 
 0.363  0.014 -0.061 -0.061 -0.036  0.487  0.437 -0.036  0.139 -0.011  0.039  0.014  0.039 -0.011  0.089 -0.061  0.089  0.039 -0.036  0.014 -0.011  0.089  0.064  0.014 -0.061  0.014  0.039  0.089 -0.036  0.039  0.089 -0.061 -0.036 -0.036 -0.061  0.064 -0.061 -0.036 -0.036  0.014  0.089  0.014  0.114  0.363 -0.061 -0.036 -0.036  0.039  0.114 -0.036  0.114 -0.011  0.039  0.064  0.089  0.163  0.014 -0.036 -0.061  0.064  0.039 -0.061  0.014  0.039 -0.061 -0.061 -0.036 -0.011  0.039 -0.011 -0.061  0.064  0.014 -0.036 -0.061  0.014  0.039  0.089 -0.036  0.014 -0.036  0.039 -0.061 -0.036  0.064  0.064 -0.061  0.064 -0.036 -0.036 -0.036  0.064  0.064 -0.061  0.064  0.064 -0.011 -0.011  0.089 -0.036 
 0.544  0.095 -0.104 -0.104 -0.004  0.818  0.693 -0.054  0.145  0.020  0.170  0.070  0.120  0.020  0.220 -0.054  0.120  0.070 -0.104  0.070 -0.029  0.070  0.020 -0.004 -0.079  0.045  0.045  0.170 -0.004  0.145  0.095 -0.029 -0.054 -0.079  0.095  0.145 -0.029  0.095 -0.029 -0.004  0.195 -0.029  0.294  0.867  0.070 -0.079 -0.079  0.195  0.095 -0.004  0.145  0.045  0.195  0.195  0.145  0.270 -0.054 -0.054 -0.104  0.095 -0.004 -0.079 -0.029  0.045 -0.079 -0.029 -0.029  0.070  0.045 -0.029 -0.079  0.120  0.095  0.020 -0.079  0.045  0.045  0.170 -0.104 -0.029 -0.054  0.070 -0.129 -0.104  0.070  0.245 -0.079  0.120 -0.079  0.020 -0.054  0.045  0.120 -0.104  0.095  0.095  0.045 -0.004  0.095 -0.079 
 0.702  0.104 -0.095 -0.120 -0.045  0.802  0.652  0.004  0.179  0.054  0.303  0.154  0.254  0.054  0.353 -0.070  0.104  0.154 -0.145  0.104 -0.020  0.054  0.079  0.104 -0.045  0.029  0.079  0.179 -0.020  0.154  0.129 -0.070 -0.045 -0.120  0.204  0.303 -0.045  0.079  0.004  0.029  0.179 -0.045  0.303  0.852  0.154 -0.070 -0.045  0.279  0.079 -0.020  0.179  0.029  0.204  0.154  0.154  0.279 -0.070 -0.045 -0.170  0.079 -0.045 -0.045  0.004  0.054 -0.070 -0.070 -0.020  0.029  0.079  0.004 -0.120  0.129  0.079  0.054 -0.095  0.029  0.129  0.154 -0.120 -0.095 -0.070  0.079 -0.120 -0.145  0.079  0.254 -0.095  0.154 -0.120  0.029 -0.095  0.004  0.279 -0.120  0.129  0.129  0.129 -0.045  0.154 -0.095 
 0.714  0.066 -0.058 -0.108 -0.008  0.789  0.689  0.091  0.191  0.216  0.515  0.116  0.266  0.041  0.565 -0.033  0.191  0.116 -0.208  0.141  0.066 -0.008  0.066  0.141  0.016 -0.008  0.141  0.216 -0.058  0.315  0.116 -0.008 -0.083 -0.133  0.315  0.465 -0.058  0.091  0.066  0.116  0.191 -0.033  0.415  0.789  0.216 -0.133 -0.083  0.266 -0.008 -0.058  0.141  0.016  0.166  0.191  0.241  0.315 -0.083 -0.008 -0.183  0.066 -0.033 -0.058 -0.033  0.041 -0.083 -0.108 -0.083  0.016  0.091  0.091 -0.108  0.166  0.091  0.066 -0.083  0.041  0.166  0.141 -0.133 -0.108 -0.133  0.041 -0.183 -0.133  0.091  0.266 -0.108  0.091 -0.133  0.016 -0.108 -0.058  0.365 -0.133  0.116  0.191  0.241 -0.033  0.191 -0.133 
 0.693  0.045 -0.030 -0.055 -0.005  0.668  0.618  0.169  0.294  0.319  0.568  0.120  0.244  0.020  0.618 -0.030  0.194  0.045 -0.229  0.144  0.095  0.045  0.070  0.120  0.045 -0.005  0.169  0.244 -0.130  0.294  0.095 -0.005 -0.105 -0.154  0.269  0.518 -0.055  0.144  0.045  0.144  0.194 -0.055  0.419  0.742  0.294 -0.154 -0.080  0.244 -0.030 -0.105  0.120  0.020  0.144  0.194  0.269  0.394 -0.105  0.020 -0.179  0.045  0.020 -0.080 -0.055  0.020 -0.130 -0.105 -0.130 -0.030  0.095  0.095 -0.130  0.219  0.120  0.095 -0.080 -0.005  0.194  0.194 -0.154 -0.105 -0.179  0.020 -0.179 -0.154  0.070  0.219 -0.130  0.070 -0.130 -0.080 -0.130 -0.080  0.369 -0.154  0.070  0.169  0.269 -0.005  0.169 -0.154 
 0.642  0.019 -0.006 -0.006 -0.031  0.642  0.592  0.193  0.467  0.318  0.592  0.193  0.318 -0.006  0.617 -0.031  0.243 -0.006 -0.255  0.119  0.069  0.094  0.019  0.119  0.143  0.119  0.218  0.268 -0.155  0.293  0.143  0.019 -0.106 -0.155  0.318  0.542 -0.056  0.193  0.193  0.143  0.218 -0.081  0.492  0.667  0.318 -0.081 -0.081  0.218 -0.006 -0.131  0.019  0.019  0.119  0.119  0.268  0.393 -0.131  0.069 -0.155  0.019 -0.006 -0.106 -0.081  0.044 -0.131 -0.106 -0.131 -0.081  0.119  0.119 -0.155  0.268  0.119  0.044 -0.031 -0.031  0.218  0.193 -0.205 -0.081 -0.205 -0.031 -0.205 -0.155  0.044  0.143 -0.131  0.069 -0.155 -0.106 -0.155 -0.081  0.393 -0.155  0.094  0.143  0.343  0.019  0.119 -0.180 
 0.625  0.002  0.027  0.052 -0.022  0.625  0.600  0.202  0.551  0.351  0.625  0.252  0.301  0.002  0.600 -0.047  0.252 -0.022 -0.272  0.102  0.077  0.102  0.002  0.127  0.252  0.127  0.227  0.252 -0.147  0.252  0.202  0.027 -0.122 -0.147  0.351  0.551 -0.072  0.177  0.227  0.252  0.227 -0.072  0.476  0.625  0.326 -0.072 -0.097  0.202 -0.022 -0.122  0.002  0.002  0.127  0.052  0.252  0.351 -0.147  0.052 -0.172  0.002  0.002 -0.122 -0.072  0.052 -0.172 -0.097 -0.147 -0.122  0.127  0.102 -0.172  0.252  0.127  0.002  0.027 -0.022  0.252  0.177 -0.222 -0.047 -0.222 -0.047 -0.222 -0.172  0.002  0.102 -0.147  0.077 -0.147 -0.097 -0.172 -0.097  0.376 -0.147  0.077  0.127  0.301  0.052  0.102 -0.172 
 0.558  0.010 -0.015  0.085 -0.040  0.608  0.558  0.259  0.583  0.384  0.633  0.259  0.334 -0.015  0.583 -0.040  0.259 -0.115 -0.264  0.035  0.135  0.135 -0.015  0.135  0.359  0.209  0.234  0.209 -0.164  0.234  0.284  0.010 -0.140 -0.164  0.359  0.508 -0.065  0.135  0.209  0.334  0.209 -0.115  0.458  0.583  0.433  0.035 -0.115  0.135 -0.090 -0.115 -0.065 -0.015  0.135 -0.015  0.184  0.359 -0.214  0.060 -0.214 -0.040 -0.015 -0.065 -0.065  0.035 -0.189 -0.090 -0.164 -0.140  0.135  0.135 -0.189  0.259  0.110  0.010  0.135 -0.040  0.234  0.159 -0.214 -0.065 -0.239 -0.065 -0.239 -0.189 -0.015  0.085 -0.164  0.110 -0.140 -0.164 -0.189 -0.115  0.334 -0.115  0.060  0.085  0.309  0.085  0.060 -0.189 
 0.528  0.029  0.004  0.079 -0.045  0.577  0.503  0.303  0.577  0.403  0.627  0.328  0.328  0.029  0.553 -0.045  0.279 -0.095 -0.270  0.029  0.129  0.129  0.079  0.154  0.453  0.204  0.254  0.154 -0.120  0.179  0.328  0.004 -0.220 -0.145  0.353  0.503 -0.045  0.104  0.179  0.328  0.229 -0.095  0.478  0.553  0.478  0.029 -0.070  0.079 -0.120 -0.120 -0.070 -0.045  0.129 -0.045  0.154  0.328 -0.220 -0.020 -0.220 -0.045  0.004 -0.070 -0.045  0.029 -0.195 -0.095 -0.170 -0.145  0.104  0.154 -0.220  0.279  0.079  0.004  0.154 -0.045  0.204  0.179 -0.220 -0.070 -0.245 -0.070 -0.245 -0.220 -0.020  0.054 -0.170  0.104 -0.145 -0.195 -0.195 -0.120  0.328 -0.095  0.054  0.054  0.328  0.104  0.004 -0.220 
 0.474  0.025  0.025  0.075 -0.049  0.549  0.424  0.299  0.573  0.424  0.623  0.324  0.349  0.100  0.499 -0.049  0.275 -0.124 -0.274  0.025  0.125  0.125  0.100  0.175  0.499  0.200  0.275  0.175 -0.099  0.125  0.349  0.000 -0.249 -0.099  0.324  0.499  0.000  0.125  0.175  0.324  0.225 -0.099  0.474  0.524  0.499  0.050 -0.074  0.075 -0.149 -0.124 -0.099 -0.049  0.100 -0.074  0.150  0.324 -0.274 -0.074 -0.249 -0.074  0.000 -0.024 -0.049  0.050 -0.174 -0.099 -0.174 -0.149  0.100  0.150 -0.224  0.275  0.050  0.025  0.175 -0.049  0.225  0.175 -0.224 -0.074 -0.274 -0.049 -0.224 -0.249  0.000  0.075 -0.174  0.050 -0.149 -0.224 -0.199 -0.149  0.299 -0.099  0.000  0.025  0.324  0.125  0.000 -0.224 
 0.443  0.045  0.045  0.070 -0.030  0.493  0.419  0.294  0.568  0.419  0.593  0.344  0.344  0.120  0.493 -0.055  0.294 -0.154 -0.329 -0.055  0.095  0.120  0.070  0.194  0.468  0.219  0.269  0.169 -0.080  0.095  0.369  0.020 -0.254 -0.105  0.344  0.493  0.045  0.120  0.169  0.319  0.219 -0.105  0.468  0.518  0.493  0.095 -0.080  0.070 -0.154 -0.130 -0.105 -0.030  0.095 -0.105  0.169  0.269 -0.279 -0.080 -0.254 -0.080 -0.005 -0.005 -0.055  0.045 -0.154 -0.130 -0.179 -0.154  0.095  0.169 -0.229  0.269  0.045  0.020  0.144 -0.030  0.194  0.120 -0.229 -0.080 -0.279 -0.055 -0.204 -0.229  0.020  0.070 -0.179 -0.005 -0.154 -0.254 -0.179 -0.179  0.294 -0.080 -0.030 -0.005  0.319  0.219 -0.030 -0.229 
 0.413  0.014  0.064  0.064 -0.036  0.487  0.388  0.313  0.562  0.437  0.587  0.338  0.313  0.139  0.487 -0.061  0.313 -0.136 -0.335 -0.061  0.114  0.139  0.064  0.188  0.487  0.213  0.238  0.163 -0.086  0.064  0.413  0.014 -0.260 -0.111  0.338  0.487  0.089  0.114  0.163  0.338  0.213 -0.111  0.462  0.462  0.487  0.139 -0.086  0.089 -0.160 -0.160 -0.136 -0.036  0.089 -0.111  0.114  0.263 -0.285 -0.086 -0.260 -0.086 -0.011 -0.011 -0.061  0.039 -0.160 -0.136 -0.160 -0.160  0.114  0.163 -0.235  0.263  0.039  0.014  0.188 -0.036  0.188  0.139 -0.235 -0.061 -0.285 -0.136 -0.210 -0.235  0.039  0.064 -0.185 -0.011 -0.185 -0.260 -0.185 -0.185  0.288 -0.086 -0.036 -0.011  0.288  0.213 -0.036 -0.235 
 0.385  0.036  0.061  0.061 -0.038  0.485  0.385  0.310  0.560  0.435  0.584  0.335  0.310  0.161  0.485 -0.063  0.310 -0.138 -0.337 -0.063  0.086  0.186  0.061  0.161  0.485  0.211  0.236  0.161 -0.088  0.061  0.410  0.036 -0.263 -0.113  0.335  0.485  0.086  0.111  0.161  0.335  0.211 -0.088  0.460  0.435  0.485  0.161 -0.088  0.111 -0.138 -0.163 -0.138 -0.038  0.086 -0.113  0.111  0.261 -0.263 -0.088 -0.263 -0.138 -0.013  0.036 -0.063  0.036 -0.113 -0.138 -0.163 -0.188  0.111  0.186 -0.238  0.261  0.036 -0.013  0.186 -0.038  0.161  0.111 -0.238 -0.063 -0.287 -0.138 -0.213 -0.238  0.061  0.061 -0.188 -0.013 -0.188 -0.263 -0.188 -0.188  0.261 -0.088 -0.038 -0.013  0.261  0.211 -0.038 -0.238 
 0.386  0.037  0.062  0.037 -0.037  0.486  0.361  0.336  0.561  0.436  0.561  0.336  0.311  0.162  0.436 -0.062  0.262 -0.137 -0.336 -0.062  0.062  0.187  0.012  0.162  0.486  0.187  0.237  0.137 -0.087  0.037  0.436  0.012 -0.262 -0.137  0.336  0.486  0.087  0.137  0.187  0.336  0.212 -0.062  0.436  0.411  0.486  0.162 -0.062  0.112 -0.162 -0.137 -0.137 -0.062  0.087 -0.137  0.087  0.262 -0.262 -0.087 -0.262 -0.137 -0.037  0.037 -0.087  0.037 -0.112 -0.162 -0.187 -0.162  0.112  0.162 -0.237  0.262  0.037  0.012  0.187 -0.037  0.137  0.037 -0.212 -0.062 -0.286 -0.137 -0.212 -0.237  0.112  0.062 -0.212 -0.012 -0.187 -0.262 -0.162 -0.187  0.237 -0.062 -0.037 -0.012  0.286  0.187 -0.037 -0.262 
 0.386  0.037  0.062  0.037 -0.063  0.485  0.361  0.336  0.560  0.435  0.560  0.336  0.311  0.161  0.435 -0.063  0.261 -0.138 -0.337 -0.063  0.062  0.186  0.012  0.161  0.485  0.186  0.236  0.137 -0.088  0.012  0.460 -0.013 -0.262 -0.113  0.336  0.460  0.087  0.137  0.186  0.336  0.211 -0.063  0.411  0.411  0.485  0.161 -0.063  0.112 -0.162 -0.138 -0.138 -0.063  0.087 -0.162  0.087  0.236 -0.262 -0.088 -0.262 -0.138 -0.038  0.037 -0.088  0.037 -0.113 -0.162 -0.187 -0.162  0.112  0.161 -0.237  0.261  0.012  0.012  0.186 -0.038  0.137  0.037 -0.212 -0.063 -0.287 -0.138 -0.212 -0.237  0.112  0.062 -0.212 -0.013 -0.187 -0.262 -0.162 -0.187  0.236 -0.063 -0.038 -0.013  0.286  0.186 -0.038 -0.262 
 0.386  0.012  0.062  0.062 -0.063  0.460  0.336  0.361  0.560  0.411  0.560  0.336  0.311  0.161  0.411 -0.063  0.236 -0.162 -0.337 -0.063  0.062  0.186 -0.013  0.161  0.485  0.186  0.286  0.112 -0.088  0.037  0.485 -0.013 -0.262 -0.138  0.336  0.460  0.062  0.137  0.186  0.336  0.211 -0.038  0.311  0.386  0.485  0.161 -0.063  0.137 -0.162 -0.138 -0.138 -0.063  0.087 -0.187  0.087  0.236 -0.237 -0.088 -0.262 -0.113 -0.063  0.037 -0.088  0.012 -0.113 -0.187 -0.187 -0.162  0.112  0.161 -0.237  0.261 -0.013 -0.013  0.186 -0.038  0.112  0.037 -0.212 -0.063 -0.287 -0.138 -0.212 -0.237  0.112  0.062 -0.237 -0.013 -0.187 -0.262 -0.162 -0.187  0.236 -0.088 -0.038 -0.013  0.336  0.211 -0.038 -0.262 
 0.359 -0.015  0.060  0.060 -0.015  0.384  0.359  0.359  0.558  0.409  0.558  0.359  0.309  0.159  0.409 -0.090  0.234 -0.164 -0.339 -0.065  0.035  0.209 -0.015  0.159  0.483  0.184  0.284  0.110 -0.090  0.060  0.483  0.010 -0.239 -0.140  0.334  0.483  0.060  0.135  0.184  0.334  0.209 -0.040  0.309  0.384  0.508  0.209 -0.040  0.135 -0.164 -0.140 -0.140 -0.065  0.035 -0.164  0.085  0.209 -0.239 -0.090 -0.264 -0.115 -0.065  0.085 -0.090  0.010 -0.090 -0.214 -0.189 -0.164  0.110  0.135 -0.239  0.234 -0.015 -0.015  0.184 -0.065  0.110  0.035 -0.214 -0.065 -0.289 -0.189 -0.214 -0.239  0.085  0.035 -0.239 -0.065 -0.164 -0.264 -0.164 -0.214  0.234 -0.065 -0.040 -0.015  0.334  0.234 -0.040 -0.239 
 0.356 -0.018  0.057  0.057  0.007  0.381  0.356  0.406  0.555  0.406  0.555  0.356  0.306  0.156  0.406 -0.093  0.206 -0.167 -0.342 -0.043  0.007  0.206 -0.018  0.156  0.455  0.206  0.281  0.107 -0.093  0.057  0.480  0.007 -0.242 -0.167  0.331  0.480  0.057  0.156  0.181  0.331  0.206 -0.018  0.306  0.381  0.505  0.206  0.007  0.132 -0.167 -0.142 -0.142 -0.068  0.032 -0.192  0.082  0.181 -0.242 -0.093 -0.267 -0.118 -0.093  0.107 -0.068  0.007 -0.093 -0.217 -0.192 -0.167  0.107  0.132 -0.242  0.206 -0.043 -0.018  0.181 -0.068  0.107  0.032 -0.217 -0.068 -0.292 -0.217 -0.217 -0.242  0.107  0.032 -0.242 -0.068 -0.167 -0.267 -0.167 -0.217  0.231 -0.068 -0.043 -0.018  0.331  0.231 -0.043 -0.242 
 0.305  0.031  0.081  0.081 -0.068  0.405  0.281  0.305  0.555  0.455  0.579  0.281  0.256  0.081  0.380 -0.068  0.156 -0.118 -0.268 -0.043  0.056  0.131  0.031  0.081  0.455  0.081  0.256  0.131 -0.093  0.031  0.505 -0.018 -0.218 -0.118  0.330  0.405  0.031  0.156  0.181  0.206  0.156  0.031  0.181  0.405  0.505  0.206 -0.043  0.131 -0.118 -0.093 -0.118 -0.068  0.056 -0.143  0.056  0.031 -0.168 -0.068 -0.193 -0.068 -0.093  0.106 -0.018 -0.018 -0.043 -0.143 -0.143 -0.143  0.156  0.056 -0.193  0.256 -0.118  0.031  0.156 -0.093  0.131  0.106 -0.143  0.006 -0.243 -0.168 -0.168 -0.243  0.081  0.031 -0.168 -0.018 -0.118 -0.218 -0.118 -0.143  0.256 -0.018 -0.018 -0.043  0.330  0.181 -0.018 -0.193 
 0.211  0.062  0.087  0.062 -0.063  0.311  0.236  0.261  0.535  0.336  0.560  0.211  0.137  0.062  0.186 -0.063  0.137 -0.063 -0.162 -0.013 -0.013  0.087  0.087  0.062  0.435  0.112  0.112  0.062 -0.063  0.062  0.411  0.037 -0.113 -0.038  0.311  0.361 -0.038  0.112  0.062  0.211  0.161  0.012  0.161  0.336  0.510  0.137 -0.013  0.087 -0.013 -0.088 -0.038 -0.038  0.087 -0.138  0.037  0.012 -0.113  0.012 -0.113 -0.038 -0.113  0.087 -0.013  0.012 -0.113 -0.063 -0.113 -0.038  0.137 -0.013 -0.113  0.062 -0.063 -0.013  0.037 -0.088  0.137  0.037 -0.063  0.062 -0.138 -0.113 -0.088 -0.138  0.012  0.112 -0.088 -0.038 -0.063 -0.138 -0.113 -0.038  0.137 -0.013  0.037  0.012  0.186  0.161  0.062 -0.162 
 0.138  0.088  0.113  0.013 -0.037  0.262  0.237  0.212  0.536  0.262  0.536  0.113  0.138 -0.037  0.113 -0.062  0.063 -0.037 -0.137 -0.012 -0.062  0.088  0.088  0.088  0.262  0.162  0.038  0.013 -0.037  0.088  0.412  0.038 -0.087 -0.012  0.312  0.387 -0.062  0.088  0.063  0.212  0.162  0.038  0.138  0.312  0.461  0.113 -0.012  0.088 -0.037 -0.087 -0.012  0.013  0.088 -0.112  0.013  0.038 -0.087  0.038 -0.087 -0.012 -0.087  0.088  0.038 -0.012 -0.087 -0.037 -0.087 -0.012  0.138 -0.012 -0.087  0.088 -0.087 -0.037 -0.012 -0.087  0.063 -0.037 -0.037  0.038 -0.112 -0.087 -0.062 -0.112 -0.012  0.088 -0.112 -0.012 -0.037 -0.112 -0.087 -0.062  0.088  0.013  0.038  0.063  0.063  0.113  0.088 -0.137 
 0.162  0.063  0.088  0.013 -0.037  0.162  0.187  0.138  0.511  0.162  0.486 -0.012  0.113 -0.012  0.088 -0.037  0.038 -0.037 -0.112 -0.012 -0.037  0.063  0.088  0.088  0.162  0.162  0.038 -0.012 -0.037  0.113  0.362  0.013 -0.062  0.013  0.287  0.287 -0.037  0.063  0.013  0.187  0.162  0.038  0.138  0.262  0.387  0.088  0.013  0.013 -0.012 -0.062  0.013  0.013  0.113 -0.087 -0.012 -0.012 -0.062  0.063 -0.062  0.013 -0.062  0.038  0.038 -0.037 -0.087 -0.037 -0.062 -0.037  0.138 -0.012 -0.087  0.063 -0.037 -0.062 -0.012 -0.087 -0.012 -0.012 -0.012  0.038 -0.087 -0.062 -0.037 -0.087 -0.037  0.038 -0.087 -0.012 -0.062 -0.087 -0.062 -0.037  0.063 -0.012  0.013  0.113  0.013  0.113  0.113 -0.112 
 0.147  0.048  0.073  0.023 -0.027  0.147  0.197  0.123  0.471  0.098  0.471 -0.002  0.123 -0.027  0.048 -0.027  0.048 -0.027 -0.102 -0.002 -0.002  0.073  0.073  0.098  0.098  0.147  0.048 -0.002 -0.027  0.098  0.322 -0.027 -0.052 -0.002  0.272  0.272 -0.052  0.073  0.023  0.197  0.172  0.048  0.147  0.222  0.272  0.098  0.048 -0.002 -0.002 -0.052  0.023  0.023  0.123 -0.077 -0.027 -0.027 -0.052  0.048 -0.052  0.023 -0.052  0.023  0.048 -0.052 -0.077 -0.027 -0.052 -0.027  0.147 -0.002 -0.077  0.073 -0.077 -0.052 -0.027 -0.077 -0.002 -0.002 -0.002  0.048 -0.077 -0.052 -0.027 -0.077 -0.027  0.023 -0.102 -0.027 -0.052 -0.077 -0.052 -0.027  0.073 -0.002  0.023  0.098 -0.002  0.098  0.123 -0.102 
 0.168  0.043  0.043  0.018 -0.006  0.118  0.193  0.043  0.417  0.043  0.417 -0.006  0.118 -0.006  0.043 -0.056  0.068 -0.006 -0.081  0.018  0.018  0.043  0.093  0.093  0.043  0.118  0.043 -0.006 -0.031  0.093  0.268 -0.031 -0.056 -0.006  0.118  0.193 -0.056  0.068  0.018  0.093  0.168  0.043  0.118  0.193  0.168  0.093  0.018 -0.006 -0.006 -0.056  0.018  0.043  0.093 -0.056 -0.006 -0.031 -0.031  0.018 -0.031  0.043 -0.031  0.043 -0.006 -0.056 -0.056 -0.031 -0.081 -0.031  0.068  0.018 -0.056  0.043 -0.056 -0.056 -0.031 -0.056 -0.031  0.018  0.018  0.068 -0.056 -0.031 -0.056 -0.056 -0.006  0.043 -0.081 -0.031 -0.031 -0.056 -0.056 -0.031  0.093 -0.031  0.043  0.093 -0.006  0.043  0.093 -0.081 
 0.178  0.054  0.054 -0.021  0.004  0.129  0.153  0.054  0.303  0.029  0.303  0.004  0.104  0.004  0.054 -0.046  0.079  0.004 -0.071  0.029  0.004  0.054  0.054  0.079  0.004  0.129  0.054  0.004 -0.021  0.104  0.079 -0.021 -0.046 -0.046  0.054  0.228 -0.046  0.029  0.004  0.029  0.129  0.029  0.104  0.178  0.079  0.054  0.029 -0.021  0.004 -0.046  0.029  0.054  0.104 -0.071  0.004 -0.021 -0.021  0.004 -0.021  0.054 -0.046  0.029 -0.021 -0.071 -0.046 -0.021 -0.071 -0.046  0.054  0.029 -0.071  0.054 -0.046 -0.046 -0.021 -0.046 -0.021  0.029  0.004  0.079 -0.046 -0.021 -0.046 -0.071  0.004  0.054 -0.071 -0.021 -0.021 -0.071 -0.046 -0.046  0.104 -0.046  0.054  0.104  0.004  0.054  0.104 -0.071 
 0.098  0.048  0.023 -0.027 -0.002  0.098  0.123  0.023  0.172 -0.002  0.197 -0.002  0.098 -0.002  0.048 -0.027  0.023  0.023 -0.052 -0.002  0.023  0.023  0.073  0.073 -0.027  0.147  0.073  0.023 -0.002  0.073 -0.002 -0.027 -0.027 -0.027 -0.002  0.098 -0.052  0.048 -0.002  0.023  0.073  0.048  0.073  0.147  0.023  0.048  0.023 -0.027  0.023 -0.027  0.023 -0.002  0.098 -0.052  0.048 -0.002 -0.002 -0.027 -0.002  0.098 -0.027  0.048 -0.002 -0.052 -0.052 -0.002 -0.052 -0.052  0.048 -0.027 -0.052  0.073 -0.002 -0.027 -0.027 -0.002 -0.002  0.073 -0.027  0.048 -0.027 -0.027 -0.027 -0.052  0.023  0.048 -0.052 -0.002 -0.002 -0.052 -0.027 -0.027  0.073 -0.027  0.048  0.098 -0.002 -0.002  0.073 -0.052 
 0.103  0.053  0.003 -0.021  0.003  0.103  0.053  0.003  0.153  0.003  0.153  0.003  0.078  0.003  0.028 -0.021  0.003  0.003 -0.046  0.003  0.028  0.028  0.078  0.078 -0.046  0.128  0.003  0.028  0.003  0.078  0.003 -0.021 -0.046 -0.021 -0.021  0.103 -0.046  0.028  0.003  0.003  0.028  0.053  0.053  0.128  0.028  0.053  0.028  0.003  0.028 -0.021  0.028  0.003  0.103 -0.046  0.053  0.003  0.003 -0.021  0.003  0.078 -0.021  0.003  0.003 -0.046 -0.046  0.003 -0.046 -0.046  0.053 -0.021 -0.046  0.078 -0.021 -0.021 -0.021  0.003  0.003  0.078 -0.021  0.053 -0.021 -0.021 -0.046 -0.046  0.003  0.053 -0.046  0.003  0.003 -0.046 -0.021 -0.021  0.003 -0.021  0.053  0.078  0.003  0.003  0.053 -0.046 
 0.118  0.018  0.018 -0.006 -0.006  0.093  0.043 -0.006  0.068 -0.006 -0.006 -0.006  0.068 -0.031 -0.006 -0.006  0.018  0.018 -0.006 -0.006  0.018  0.018  0.043  0.068 -0.031  0.118  0.018  0.018  0.043  0.068 -0.006 -0.031 -0.031 -0.006 -0.006  0.068 -0.031  0.018  0.018 -0.006  0.043  0.018  0.018  0.093  0.018  0.018  0.018 -0.006  0.043 -0.006  0.043 -0.006  0.118 -0.006  0.018 -0.006 -0.006 -0.006 -0.031  0.068 -0.031  0.018  0.018 -0.006 -0.031  0.018 -0.031 -0.031  0.018 -0.031 -0.031  0.018 -0.006 -0.006 -0.031  0.018 -0.031  0.018 -0.006 -0.031 -0.006 -0.006 -0.031 -0.031 -0.006 -0.006 -0.031  0.018 -0.006 -0.031 -0.031  0.018 -0.006 -0.031  0.018  0.043 -0.006 -0.006  0.018 -0.031 
 0.101  0.001 -0.023 -0.023  0.001  0.076  0.051 -0.023  0.051  0.001  0.001  0.001  0.026 -0.023  0.001 -0.023  0.026  0.026  0.001  0.001  0.001  0.051  0.026  0.051 -0.023  0.051  0.026  0.026  0.001  0.051  0.001 -0.023 -0.023  0.001 -0.023  0.051 -0.023  0.001  0.001 -0.023  0.051  0.001  0.026  0.076 -0.023  0.001  0.001  0.001  0.051  0.001  0.051  0.001  0.076  0.001  0.026  0.001  0.001  0.001 -0.023  0.026 -0.023 -0.023  0.001  0.001 -0.023  0.001 -0.023 -0.023  0.001 -0.023 -0.023  0.026  0.001  0.001 -0.023  0.001 -0.023  0.026  0.001 -0.023  0.001  0.001 -0.023 -0.023 -0.023  0.001 -0.023  0.026  0.001 -0.023 -0.023  0.001 -0.023 -0.023  0.001  0.001 -0.023 -0.023  0.026 -0.023 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.079  0.004 -0.020 -0.020  0.004  0.079  0.054 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.029  0.029  0.004  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.054  0.004  0.004  0.054 -0.020  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020 
 0.104  0.004 -0.021 -0.021  0.004  0.104  0.054 -0.021  0.029  0.004  0.004  0.004  0.004 -0.021  0.029 -0.021  0.029  0.029  0.004  0.004  0.004  0.054  0.029  0.029 -0.021  0.029  0.029  0.029  0.004  0.004  0.004 -0.021 -0.021  0.004 -0.021  0.029 -0.021  0.004  0.004 -0.021  0.054  0.004  0.004  0.054 -0.021  0.004  0.004  0.004  0.054  0.004  0.054  0.004  0.079  0.004  0.029 -0.021  0.004  0.004 -0.021  0.004 -0.021 -0.021  0.004  0.004 -0.021 -0.021 -0.021 -0.021  0.004 -0.021 -0.021  0.029  0.004  0.004 -0.021  0.004 -0.021  0.029  0.004 -0.021  0.004  0.004 -0.021 -0.021 -0.021  0.029 -0.021  0.029  0.004 -0.021 -0.021  0.004 -0.021 -0.021  0.004  0.004 -0.021 -0.021  0.004 -0.021 
 0.126  0.026 -0.024 -0.024  0.001  0.150  0.101 -0.024  0.026  0.001  0.051  0.001  0.001 -0.024  0.026 -0.024  0.026  0.026  0.001  0.001  0.001  0.076  0.051  0.026 -0.024  0.026  0.026  0.026  0.001  0.001  0.001 -0.024 -0.024  0.001 -0.024  0.026 -0.024  0.001  0.001  0.001  0.051  0.026  0.026  0.101 -0.024  0.001  0.001  0.001  0.051  0.001  0.051  0.001  0.076  0.001  0.026  0.001  0.001  0.001 -0.024  0.001 -0.024 -0.024  0.001  0.001 -0.024 -0.024 -0.024  0.001  0.001 -0.024 -0.024  0.026  0.001  0.001 -0.024  0.001 -0.024  0.051  0.001 -0.024  0.001  0.001 -0.024 -0.024 -0.024  0.026 -0.024  0.026  0.001 -0.024 -0.024  0.001 -0.024 -0.024  0.026  0.001 -0.024 -0.024  0.026 -0.024 
 0.146  0.021 -0.028 -0.028 -0.003  0.196  0.121 -0.003  0.071  0.021  0.071 -0.003  0.021 -0.003  0.021 -0.028  0.021  0.046 -0.003 -0.003 -0.003  0.071  0.046  0.021 -0.028  0.021  0.021  0.021 -0.003 -0.003 -0.003 -0.028 -0.028 -0.003 -0.028  0.046 -0.028 -0.003 -0.003  0.021  0.046  0.021  0.021  0.146 -0.003 -0.003 -0.003 -0.003  0.046 -0.003  0.046 -0.003  0.071  0.021  0.021  0.021 -0.003 -0.003 -0.028 -0.003 -0.003 -0.028 -0.003 -0.003 -0.028 -0.028 -0.028 -0.003 -0.003 -0.028 -0.003  0.021 -0.003 -0.003 -0.028  0.021 -0.028  0.046 -0.003 -0.028 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 -0.028  0.021 -0.003 -0.028 -0.003 -0.003 -0.028 -0.028  0.046 -0.003 -0.028 -0.028  0.046 -0.028 
 0.193  0.068 -0.056 -0.056 -0.006  0.317  0.243 -0.031  0.143  0.018  0.093  0.068  0.118  0.018  0.043 -0.006  0.068  0.093 -0.031 -0.006 -0.031  0.043  0.118 -0.006 -0.006  0.018  0.043  0.068 -0.006  0.043 -0.006 -0.056 -0.031 -0.031 -0.006  0.143 -0.031 -0.006 -0.031  0.018  0.093  0.043  0.193  0.367 -0.006 -0.031 -0.031 -0.006  0.068 -0.031  0.018  0.018  0.168  0.043  0.043  0.018 -0.031  0.043 -0.056 -0.006 -0.031 -0.056 -0.031  0.018 -0.056 -0.006 -0.056 -0.031 -0.006 -0.056 -0.006  0.143 -0.031 -0.031 -0.056  0.043 -0.006  0.118 -0.031  0.018 -0.031  0.018 -0.031 -0.056 -0.006  0.118 -0.031  0.043 -0.006 -0.056  0.018 -0.031 -0.006 -0.056  0.068 -0.006 -0.031 -0.006  0.143 -0.056 
 0.208  0.083 -0.091 -0.066  0.008  0.532  0.382 -0.041  0.083  0.008  0.108  0.133  0.158  0.058  0.108 -0.016  0.108  0.058 -0.066  0.033 -0.066  0.033  0.083 -0.016 -0.016  0.033  0.008  0.233 -0.041  0.058  0.033 -0.066 -0.041 -0.041  0.008  0.208 -0.041  0.008 -0.041  0.008  0.108  0.008  0.332  0.656  0.058 -0.041 -0.041 -0.016  0.033 -0.066  0.008  0.008  0.183  0.083  0.083  0.108 -0.041  0.008 -0.091 -0.016 -0.041 -0.066 -0.016  0.008 -0.091 -0.041 -0.016 -0.041 -0.016 -0.091 -0.016  0.283 -0.016 -0.041 -0.066  0.033 -0.016  0.108 -0.066 -0.041 -0.041  0.008 -0.066 -0.091 -0.041  0.158 -0.016  0.133 -0.016 -0.041 -0.016 -0.041 -0.016 -0.016  0.083  0.008 -0.041 -0.041  0.233 -0.091 
 0.362  0.138 -0.036 -0.036 -0.011  0.811  0.636  0.063  0.138  0.038  0.263  0.337  0.287  0.063  0.238 -0.011  0.163  0.038 -0.136  0.038 -0.061  0.038  0.138  0.013  0.013  0.063  0.038  0.287 -0.036  0.238  0.038  0.013 -0.086 -0.061  0.113  0.387 -0.086 -0.011 -0.011  0.063  0.238 -0.011  0.462  0.836  0.188 -0.086 -0.061 -0.036 -0.036 -0.011  0.038  0.013  0.188  0.138  0.088  0.113 -0.061  0.038 -0.111  0.063 -0.111 -0.061 -0.011  0.088 -0.061 -0.011 -0.061 -0.011  0.013 -0.061 -0.061  0.337  0.063 -0.036 -0.011 -0.011  0.013  0.113 -0.136 -0.111 -0.111 -0.011 -0.136 -0.136 -0.011  0.188 -0.011  0.063 -0.036 -0.036 -0.061 -0.011  0.038 -0.011  0.038  0.063  0.088 -0.061  0.362 -0.111 
 0.392  0.118 -0.006 -0.006  0.043  0.791  0.716  0.168  0.193  0.118  0.392  0.317  0.342  0.018  0.392 -0.031  0.143  0.043 -0.181 -0.006  0.043  0.043  0.093  0.043  0.018  0.068  0.118  0.342 -0.056  0.243  0.093 -0.006 -0.106 -0.081  0.268  0.442 -0.106 -0.006  0.068  0.093  0.243  0.068  0.492  0.816  0.218 -0.131 -0.106  0.018 -0.031 -0.031  0.018  0.018  0.143  0.292  0.068  0.143 -0.106  0.043 -0.156  0.018 -0.081 -0.081 -0.031  0.068 -0.106 -0.031 -0.056 -0.031  0.093  0.043 -0.106  0.317  0.068 -0.081 -0.006 -0.006 -0.006  0.168 -0.156 -0.131 -0.156 -0.056 -0.156 -0.131 -0.006  0.193 -0.031  0.043 -0.056 -0.081 -0.106 -0.056 -0.006 -0.056  0.043  0.093  0.118 -0.006  0.342 -0.131 
 0.539  0.090 -0.009  0.040  0.015  0.763  0.663  0.165  0.389  0.215  0.588  0.289  0.389 -0.034  0.539 -0.009  0.165 -0.009 -0.234 -0.009  0.040  0.015  0.065  0.040  0.115  0.265  0.240  0.289 -0.084  0.289  0.165 -0.034 -0.109 -0.109  0.364  0.489 -0.109  0.040  0.115  0.140  0.265  0.065  0.514  0.738  0.364 -0.084 -0.134  0.090 -0.009 -0.034 -0.009 -0.009  0.140  0.215  0.040  0.190 -0.159  0.040 -0.209 -0.009 -0.059 -0.084 -0.059  0.040 -0.109 -0.084 -0.109 -0.059  0.065  0.115 -0.159  0.339  0.040 -0.134  0.040 -0.059 -0.059  0.115 -0.209 -0.109 -0.184 -0.034 -0.159 -0.159 -0.059  0.215 -0.084  0.065 -0.109 -0.084 -0.159 -0.109  0.140 -0.084 -0.009  0.090  0.215 -0.009  0.240 -0.159 
 0.568  0.095 -0.005  0.020 -0.005  0.742  0.618  0.169  0.468  0.319  0.618  0.294  0.394 -0.055  0.618 -0.030  0.244 -0.030 -0.254 -0.005  0.020  0.070  0.095  0.045  0.144  0.244  0.269  0.269 -0.055  0.269  0.219 -0.055 -0.130 -0.055  0.369  0.468 -0.179  0.095  0.144  0.169  0.319  0.020  0.493  0.668  0.369 -0.080 -0.154  0.120 -0.030 -0.080 -0.030 -0.030  0.120  0.219  0.045  0.194 -0.179  0.045 -0.154 -0.005 -0.080 -0.080 -0.055  0.020 -0.130 -0.080 -0.154 -0.080  0.095  0.120 -0.154  0.319 -0.005 -0.154  0.020 -0.080 -0.030  0.095 -0.229 -0.055 -0.204 -0.055 -0.179 -0.154 -0.080  0.194 -0.105  0.045 -0.130 -0.105 -0.179 -0.105  0.095 -0.105 -0.030  0.070  0.344  0.020  0.194 -0.154 
 0.549  0.101  0.051  0.126  0.001  0.649  0.549  0.250  0.574  0.400  0.624  0.300  0.375 -0.049  0.599 -0.049  0.250 -0.074 -0.273  0.001 -0.024  0.150  0.101  0.051  0.200  0.325  0.250  0.275 -0.099  0.225  0.250 -0.074 -0.173 -0.074  0.400  0.499 -0.148  0.150  0.150  0.175  0.300  0.026  0.474  0.574  0.474 -0.049 -0.099  0.150 -0.099 -0.099 -0.024 -0.074  0.101  0.076  0.076  0.250 -0.223  0.001 -0.173 -0.049 -0.074 -0.074 -0.099  0.026 -0.173 -0.099 -0.173 -0.148  0.076  0.175 -0.198  0.275  0.001 -0.124  0.051 -0.148  0.026  0.101 -0.223 -0.049 -0.248 -0.074 -0.198 -0.223 -0.074  0.175 -0.124  0.051 -0.173 -0.124 -0.198 -0.173  0.101 -0.099  0.001  0.026  0.375  0.026  0.051 -0.223 
 0.535  0.087  0.112  0.112  0.012  0.610  0.535  0.311  0.585  0.411  0.635  0.311  0.361  0.037  0.585 -0.063  0.261 -0.088 -0.262 -0.013  0.012  0.236  0.112  0.037  0.311  0.311  0.311  0.286 -0.113  0.211  0.286 -0.063 -0.187 -0.088  0.411  0.485 -0.138  0.137  0.137  0.236  0.286  0.037  0.460  0.560  0.460  0.012 -0.113  0.211 -0.113 -0.113 -0.088 -0.088  0.087  0.062  0.062  0.236 -0.262  0.012 -0.187 -0.063 -0.013 -0.088 -0.113  0.012 -0.162 -0.088 -0.187 -0.162  0.062  0.186 -0.187  0.261  0.012 -0.113  0.062 -0.162  0.012  0.087 -0.212 -0.063 -0.262 -0.113 -0.237 -0.237 -0.038  0.161 -0.138  0.037 -0.187 -0.138 -0.212 -0.162  0.137 -0.088 -0.013  0.012  0.361  0.062  0.037 -0.237 
 0.522  0.049  0.198  0.099  0.024  0.572  0.472  0.323  0.572  0.447  0.647  0.323  0.323  0.099  0.522 -0.051  0.298 -0.126 -0.250 -0.001  0.024  0.248  0.099  0.049  0.373  0.323  0.323  0.273 -0.126  0.198  0.373 -0.051 -0.200 -0.076  0.472  0.497 -0.101  0.173  0.124  0.223  0.323  0.074  0.447  0.547  0.472  0.024 -0.101  0.273 -0.126 -0.126 -0.101 -0.076  0.074 -0.001  0.074  0.223 -0.275 -0.051 -0.200 -0.076 -0.026 -0.051 -0.126 -0.001 -0.175 -0.101 -0.200 -0.175  0.049  0.198 -0.225  0.248  0.024 -0.126  0.049 -0.150 -0.001  0.074 -0.200 -0.076 -0.275 -0.101 -0.250 -0.225 -0.026  0.099 -0.150 -0.001 -0.200 -0.200 -0.200 -0.150  0.124 -0.051 -0.026  0.024  0.348  0.148  0.024 -0.250 
 0.466  0.068  0.192  0.093  0.018  0.566  0.466  0.342  0.566  0.491  0.641  0.342  0.317  0.093  0.491 -0.082  0.317 -0.156 -0.256 -0.032  0.018  0.242  0.118  0.068  0.466  0.317  0.367  0.267 -0.132  0.167  0.392 -0.007 -0.231 -0.082  0.466  0.491 -0.082  0.192  0.118  0.217  0.342  0.118  0.417  0.541  0.466  0.043 -0.107  0.317 -0.107 -0.132 -0.107 -0.082  0.043 -0.032  0.093  0.217 -0.281 -0.057 -0.206 -0.082 -0.032 -0.007 -0.082 -0.007 -0.181 -0.107 -0.206 -0.181  0.043  0.242 -0.231  0.242 -0.007 -0.107  0.068 -0.156  0.018  0.068 -0.206 -0.082 -0.281 -0.107 -0.231 -0.231 -0.007  0.068 -0.156 -0.057 -0.156 -0.156 -0.206 -0.132  0.142 -0.032 -0.032  0.018  0.367  0.142  0.018 -0.231 
 0.412  0.088  0.188  0.088  0.013  0.537  0.412  0.362  0.562  0.487  0.636  0.337  0.312  0.063  0.487 -0.086  0.312 -0.161 -0.261 -0.036  0.013  0.238  0.088  0.088  0.512  0.312  0.337  0.188 -0.136  0.138  0.412 -0.011 -0.261 -0.086  0.437  0.487 -0.086  0.188  0.163  0.238  0.362  0.063  0.387  0.462  0.462  0.088 -0.111  0.287 -0.136 -0.136 -0.111 -0.086  0.063 -0.086  0.088  0.213 -0.285 -0.061 -0.211 -0.111 -0.061 -0.011 -0.061 -0.011 -0.136 -0.136 -0.211 -0.161  0.038  0.312 -0.236  0.238 -0.061 -0.111  0.113 -0.136  0.038  0.038 -0.211 -0.086 -0.285 -0.111 -0.236 -0.261  0.013  0.063 -0.161 -0.086 -0.186 -0.186 -0.236 -0.161  0.138 -0.036 -0.036 -0.011  0.337  0.138  0.013 -0.236 
 0.409  0.060  0.185  0.085  0.010  0.484  0.409  0.409  0.559  0.509  0.633  0.334  0.284  0.035  0.484 -0.089  0.309 -0.164 -0.264 -0.039  0.010  0.235  0.110  0.110  0.534  0.334  0.334  0.185 -0.139  0.135  0.459  0.010 -0.264 -0.039  0.434  0.484 -0.064  0.185  0.160  0.235  0.359  0.060  0.409  0.409  0.459  0.110 -0.114  0.284 -0.139 -0.139 -0.114 -0.089  0.035 -0.089  0.110  0.210 -0.288 -0.089 -0.214 -0.139 -0.064 -0.014 -0.064 -0.014 -0.139 -0.164 -0.214 -0.164  0.035  0.309 -0.264  0.210 -0.064 -0.114  0.135 -0.164  0.060  0.035 -0.214 -0.089 -0.288 -0.139 -0.239 -0.264 -0.014  0.060 -0.164 -0.114 -0.189 -0.189 -0.239 -0.164  0.135 -0.039 -0.039 -0.014  0.334  0.160 -0.014 -0.239 
 0.379  0.055  0.155  0.080 -0.019  0.479  0.404  0.404  0.554  0.504  0.628  0.329  0.304  0.080  0.454 -0.094  0.304 -0.169 -0.293 -0.044 -0.019  0.205  0.105  0.130  0.554  0.304  0.329  0.130 -0.119  0.130  0.479  0.005 -0.269 -0.044  0.429  0.504 -0.044  0.105  0.155  0.230  0.354  0.005  0.404  0.404  0.454  0.155 -0.119  0.255 -0.144 -0.144 -0.144 -0.094  0.030 -0.144  0.105  0.205 -0.269 -0.119 -0.219 -0.144 -0.069  0.055 -0.094  0.030 -0.119 -0.194 -0.219 -0.169  0.005  0.304 -0.269  0.230 -0.094 -0.119  0.180 -0.169  0.055  0.030 -0.219 -0.069 -0.293 -0.144 -0.219 -0.269  0.005  0.055 -0.219 -0.119 -0.194 -0.194 -0.194 -0.194  0.130 -0.044 -0.044 -0.019  0.329  0.180 -0.044 -0.244 
 0.378  0.029  0.178  0.104 -0.021  0.452  0.403  0.353  0.552  0.502  0.627  0.328  0.328  0.104  0.452 -0.096  0.303 -0.170 -0.295 -0.046 -0.021  0.203  0.079  0.129  0.527  0.328  0.328  0.129 -0.121  0.104  0.477  0.004 -0.270 -0.046  0.427  0.502 -0.021  0.104  0.178  0.228  0.353  0.004  0.403  0.378  0.452  0.129 -0.121  0.253 -0.145 -0.145 -0.145 -0.096  0.029 -0.145  0.104  0.203 -0.270 -0.121 -0.220 -0.145 -0.071  0.079 -0.096  0.029 -0.121 -0.195 -0.220 -0.170  0.004  0.303 -0.270  0.228 -0.096 -0.121  0.153 -0.170  0.104  0.029 -0.220 -0.096 -0.295 -0.145 -0.220 -0.270 -0.021  0.054 -0.220 -0.121 -0.195 -0.195 -0.170 -0.195  0.129 -0.046 -0.046  0.004  0.328  0.178 -0.046 -0.220 
 0.377 -0.021  0.153  0.103 -0.046  0.377  0.402  0.352  0.552  0.477  0.626  0.327  0.302  0.103  0.427 -0.096  0.253 -0.171 -0.295 -0.046 -0.021  0.203  0.078  0.128  0.527  0.302  0.427  0.103 -0.071  0.053  0.477  0.003 -0.271 -0.046  0.452  0.502  0.003  0.103  0.228  0.228  0.377  0.003  0.402  0.377  0.452  0.128 -0.121  0.253 -0.171 -0.171 -0.146 -0.096  0.003 -0.196  0.078  0.153 -0.271 -0.121 -0.221 -0.146 -0.096  0.078 -0.096 -0.021 -0.146 -0.221 -0.196 -0.196  0.003  0.302 -0.271  0.203 -0.071 -0.121  0.153 -0.121  0.103  0.028 -0.221 -0.096 -0.295 -0.146 -0.196 -0.246 -0.021  0.053 -0.221 -0.121 -0.196 -0.221 -0.146 -0.196  0.103 -0.046 -0.046  0.003  0.302  0.178 -0.046 -0.221 
 0.401 -0.022  0.152  0.102 -0.047  0.376  0.401  0.376  0.551  0.451  0.625  0.326  0.277  0.102  0.426 -0.097  0.252 -0.172 -0.296 -0.047 -0.022  0.202  0.052  0.127  0.526  0.301  0.426  0.102 -0.072  0.027  0.476  0.002 -0.272 -0.047  0.451  0.501  0.002  0.102  0.227  0.227  0.376  0.002  0.401  0.376  0.426  0.127 -0.122  0.252 -0.172 -0.172 -0.147 -0.097  0.002 -0.197  0.077  0.152 -0.247 -0.122 -0.222 -0.147 -0.122  0.077 -0.097 -0.022 -0.172 -0.222 -0.197 -0.197  0.002  0.277 -0.272  0.177 -0.072 -0.122  0.177 -0.122  0.102  0.002 -0.222 -0.097 -0.296 -0.147 -0.197 -0.247 -0.022  0.052 -0.222 -0.122 -0.197 -0.222 -0.147 -0.197  0.077 -0.047 -0.047  0.002  0.326  0.202 -0.072 -0.222 
 0.402 -0.021  0.153  0.053 -0.046  0.377  0.402  0.402  0.552  0.402  0.601  0.327  0.278  0.103  0.427 -0.096  0.178 -0.171 -0.295 -0.046 -0.046  0.203  0.053  0.128  0.502  0.302  0.427  0.103 -0.071 -0.021  0.477  0.003 -0.271 -0.071  0.452  0.477  0.003  0.128  0.228  0.228  0.352  0.003  0.377  0.352  0.427  0.153 -0.096  0.228 -0.171 -0.171 -0.146 -0.121  0.003 -0.221  0.078  0.153 -0.246 -0.121 -0.221 -0.146 -0.121  0.078 -0.096 -0.021 -0.171 -0.221 -0.196 -0.196  0.003  0.253 -0.271  0.178 -0.046 -0.121  0.228 -0.121  0.103  0.003 -0.221 -0.071 -0.295 -0.146 -0.221 -0.246  0.003  0.028 -0.221 -0.121 -0.196 -0.246 -0.146 -0.196  0.078 -0.071 -0.046  0.003  0.327  0.203 -0.071 -0.246 
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 0.110  0.085  0.085  0.010  0.010  0.160  0.110  0.235  0.509  0.284  0.608  0.110  0.135  0.010  0.060 -0.014  0.185 -0.014 -0.114 -0.039  0.010  0.085  0.085  0.085  0.509  0.185  0.185 -0.014 -0.039  0.135  0.384  0.035 -0.064  0.010  0.384  0.160 -0.014  0.085  0.035  0.260  0.135  0.010  0.185  0.160  0.384  0.135  0.035  0.010 -0.064 -0.014  0.010  0.010  0.060 -0.064 -0.039 -0.039 -0.064 -0.039 -0.089  0.010 -0.064  0.010  0.035  0.035 -0.089 -0.039 -0.039 -0.064  0.160  0.010 -0.064  0.110 -0.039 -0.089 -0.039 -0.064  0.035  0.085 -0.014  0.010 -0.089 -0.064 -0.064 -0.089 -0.039  0.085 -0.114 -0.064 -0.064 -0.089 -0.064 -0.014  0.135 -0.014  0.060  0.035 -0.014  0.210  0.010 -0.114 
 0.125  0.100  0.025 -0.050 -0.050  0.149  0.125  0.125  0.523  0.299  0.573  0.025  0.149  0.000  0.050 -0.025  0.149 -0.025 -0.100 -0.025  0.025  0.075  0.050  0.100  0.498  0.174  0.125  0.000 -0.025  0.149  0.324  0.025 -0.050 -0.025  0.349  0.174  0.000  0.050  0.000  0.274  0.125  0.000  0.199  0.149  0.349  0.075  0.050  0.000 -0.050  0.000  0.025  0.025  0.050 -0.075 -0.050 -0.025 -0.050 -0.050 -0.075  0.025 -0.050  0.025  0.050 -0.050 -0.075 -0.025 -0.050 -0.050  0.174  0.025 -0.075  0.100 -0.025 -0.075 -0.050 -0.075 -0.025  0.025 -0.025  0.000 -0.075 -0.050 -0.050 -0.075 -0.025  0.075 -0.100 -0.075 -0.050 -0.075 -0.050  0.000  0.149 -0.050  0.050  0.050  0.000  0.199  0.000 -0.100 
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-0.003  0.022 -0.003 -0.003 -0.003  0.022 -0.003 -0.003  0.097  0.022  0.047 -0.003  0.022 -0.003  0.022 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003 -0.003  0.022 -0.003 -0.003  0.022 -0.003 -0.003 -0.003  0.022 -0.003 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003  0.047 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.072 -0.003  0.022  0.022 -0.003 -0.003 -0.003 -0.003 
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 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 0.076  0.001  0.001  0.051  0.001  0.001 -0.023  0.176 -0.023  0.026  0.001  0.001  0.001 -0.023  0.051 -0.023  0.026 -0.023  0.001  0.001  0.001 -0.023 -0.023  0.001  0.001 -0.023 -0.023  0.001 -0.023 -0.023  0.001  0.001 -0.023 -0.023  0.026  0.001  0.001  0.026  0.001  0.026  0.001 -0.023 -0.023  0.001  0.001  0.001 -0.023  0.001  0.001 -0.023 -0.023 -0.023  0.001 -0.023  0.026  0.026 -0.023  0.051  0.001  0.001  0.026  0.001 -0.023  0.026  0.001 -0.023 -0.023  0.001  0.001  0.026  0.001  0.026  0.001  0.001  0.026  0.026 -0.023  0.026 -0.023  0.026 -0.023 -0.023 -0.023  0.001 -0.023  0.001 -0.023  0.001  0.001 -0.023  0.001 -0.023 -0.023  0.001  0.051  0.051  0.051  0.001 -0.023 -0.023 
 0.069  0.069 -0.006  0.044 -0.006 -0.006 -0.031  0.193 -0.006  0.044 -0.006 -0.006 -0.006 -0.031  0.044 -0.031  0.019 -0.031 -0.006 -0.006  0.019 -0.031 -0.031 -0.006 -0.006 -0.031 -0.031  0.019 -0.031 -0.031  0.069 -0.006 -0.031 -0.031  0.019 -0.006 -0.006  0.019  0.019  0.069  0.019 -0.031 -0.031  0.019 -0.006 -0.006 -0.031  0.019 -0.006 -0.031 -0.031 -0.031 -0.006 -0.031  0.019  0.019 -0.031  0.069 -0.006 -0.006  0.019 -0.006 -0.006  0.019 -0.006 -0.031 -0.031  0.019 -0.006  0.019 -0.006  0.019 -0.006 -0.006  0.019  0.044  0.069  0.044 -0.031  0.019 -0.006 -0.031 -0.006  0.019 -0.031  0.019 -0.006 -0.006 -0.006 -0.031 -0.006 -0.006 -0.031  0.019  0.069  0.069  0.069 -0.006 -0.031 -0.031 
 0.037  0.087 -0.013  0.137 -0.038 -0.013 -0.063  0.336  0.062  0.037  0.012  0.012  0.037 -0.063  0.037 -0.038  0.012 -0.038 -0.038 -0.038  0.012 -0.063 -0.013  0.012  0.012  0.012 -0.063 -0.013 -0.013 -0.013  0.186  0.012 -0.063 -0.063  0.012 -0.013 -0.038  0.087  0.087  0.037 -0.013 -0.063  0.012  0.112  0.012  0.062 -0.038  0.012 -0.013 -0.063 -0.038 -0.063  0.012 -0.063  0.012  0.037 -0.063  0.087 -0.013  0.012 -0.013  0.012 -0.013  0.062 -0.013 -0.063 -0.063  0.037  0.012 -0.013 -0.038 -0.013 -0.038 -0.038  0.062  0.012  0.087  0.062 -0.063  0.037 -0.038 -0.063  0.037  0.062  0.112  0.137 -0.013 -0.038 -0.038 -0.063 -0.038  0.012 -0.013 -0.013  0.112  0.062  0.062  0.012 -0.063 -0.013 
 0.014  0.064  0.039  0.089 -0.086 -0.011 -0.086  0.587  0.238  0.039  0.089 -0.011  0.064 -0.111  0.014 -0.061 -0.036 -0.086 -0.061  0.014  0.014 -0.111 -0.036  0.064 -0.036  0.039 -0.061 -0.061  0.014 -0.011  0.263 -0.011 -0.061 -0.136  0.064 -0.011 -0.086  0.213  0.064  0.014 -0.011  0.039 -0.011  0.114 -0.011  0.163 -0.061  0.039 -0.061 -0.136 -0.061 -0.086 -0.011 -0.136 -0.036  0.188 -0.086  0.114 -0.011 -0.036 -0.011  0.114  0.089  0.089 -0.011 -0.036 -0.111  0.039  0.064 -0.086 -0.111 -0.061 -0.111  0.014  0.139  0.089  0.163  0.114 -0.036  0.039 -0.086 -0.086  0.014  0.064  0.238  0.163 -0.086 -0.011 -0.111 -0.086 -0.036 -0.011  0.014 -0.061  0.238  0.089  0.089  0.014  0.014  0.014 
 0.009  0.059  0.034  0.134 -0.116 -0.066 -0.066  0.607  0.308 -0.016  0.208 -0.016  0.084 -0.116 -0.041 -0.091 -0.066 -0.116 -0.066 -0.016  0.059 -0.091 -0.041  0.034 -0.016  0.034 -0.041 -0.091 -0.041  0.084  0.333  0.059 -0.091 -0.165  0.034 -0.041 -0.066  0.283  0.059 -0.041 -0.066  0.084 -0.066  0.109 -0.041  0.208 -0.116  0.134 -0.041 -0.165  0.034 -0.091 -0.066 -0.190 -0.066  0.208 -0.116  0.158 -0.066 -0.066 -0.041  0.158  0.183  0.134 -0.016  0.059 -0.141  0.084  0.134 -0.116 -0.165 -0.066 -0.116 -0.041  0.134  0.059  0.183  0.208 -0.066  0.009 -0.116 -0.116  0.009  0.009  0.258  0.208 -0.141 -0.041 -0.116 -0.066 -0.016 -0.041  0.059 -0.066  0.258  0.059  0.034  0.009  0.034  0.009 
 0.064  0.089 -0.036  0.114 -0.160 -0.061 -0.086  0.587  0.338  0.039  0.288 -0.036  0.114 -0.160 -0.061 -0.036 -0.011 -0.160 -0.061 -0.061  0.114 -0.036 -0.036 -0.011 -0.036 -0.036 -0.011 -0.111 -0.036  0.089  0.388  0.089 -0.136 -0.235  0.114 -0.111 -0.036  0.263  0.089 -0.086  0.014  0.089 -0.011  0.114 -0.086  0.213 -0.111  0.163 -0.061 -0.210  0.064 -0.111 -0.111 -0.210 -0.061  0.213 -0.061  0.114 -0.111 -0.136 -0.136  0.064  0.313  0.139 -0.061  0.039 -0.136  0.089  0.163 -0.136 -0.185  0.064 -0.061 -0.011  0.188  0.163  0.188  0.238 -0.061  0.014 -0.185 -0.160 -0.036 -0.061  0.238  0.238 -0.061 -0.061 -0.160 -0.136 -0.011 -0.111  0.114 -0.111  0.188  0.039  0.039  0.139  0.014  0.064 
 0.069  0.094 -0.081  0.119 -0.131 -0.056 -0.106  0.418  0.293  0.019  0.293 -0.056  0.119 -0.155 -0.056 -0.031 -0.006 -0.180 -0.031 -0.106  0.094  0.019 -0.056 -0.031  0.044 -0.031  0.069 -0.106 -0.081  0.119  0.418  0.094 -0.180 -0.255  0.119 -0.131  0.019  0.193  0.119 -0.106 -0.006  0.069  0.019  0.094 -0.131  0.243 -0.106  0.143 -0.081 -0.205  0.069 -0.106 -0.081 -0.180 -0.031  0.119 -0.031  0.044 -0.106 -0.056 -0.106  0.044  0.293  0.119 -0.056  0.019 -0.131  0.044  0.243 -0.106 -0.205  0.069  0.019  0.168  0.168  0.168  0.143  0.218 -0.031  0.044 -0.180 -0.155 -0.031 -0.081  0.218  0.268 -0.081 -0.056 -0.155 -0.155  0.044 -0.081  0.218 -0.131  0.094  0.069  0.069  0.143 -0.006  0.069 
 0.073  0.098 -0.052  0.098 -0.151 -0.077 -0.077  0.222  0.247  0.073  0.222 -0.052  0.123 -0.102 -0.077  0.023  0.023 -0.176 -0.052 -0.127  0.123 -0.002 -0.052 -0.027  0.023 -0.002  0.073 -0.077 -0.052  0.073  0.397  0.048 -0.251 -0.276  0.147 -0.176  0.048  0.172  0.123 -0.151  0.023  0.023  0.073  0.098 -0.151  0.247 -0.127  0.197 -0.102 -0.226  0.048 -0.102 -0.102 -0.176 -0.052  0.073  0.048 -0.002 -0.127 -0.002 -0.052  0.073  0.222 -0.077 -0.052 -0.002 -0.151  0.023  0.222 -0.102 -0.201  0.073 -0.027  0.247  0.147  0.197  0.172  0.172 -0.027  0.023 -0.176 -0.151 -0.027 -0.077  0.147  0.247 -0.102 -0.002 -0.127 -0.176  0.023 -0.077  0.222 -0.151  0.073  0.073  0.098  0.222 -0.002  0.048 
 0.099  0.099 -0.051  0.124 -0.150 -0.076 -0.026  0.198  0.248  0.074  0.223 -0.051  0.099 -0.101 -0.051  0.049  0.049 -0.126 -0.076 -0.150  0.124  0.024 -0.026 -0.026  0.024 -0.026  0.074 -0.076 -0.051  0.074  0.398  0.049 -0.225 -0.275  0.148 -0.150  0.049  0.173  0.148 -0.150  0.099  0.024  0.074  0.099 -0.101  0.298 -0.126  0.173 -0.101 -0.200  0.049 -0.076 -0.076 -0.225 -0.051  0.074  0.074 -0.001 -0.126 -0.001 -0.051  0.049  0.198 -0.101 -0.051 -0.026 -0.150 -0.001  0.223 -0.101 -0.225  0.074 -0.026  0.248  0.173  0.173  0.173  0.148 -0.026  0.024 -0.200 -0.150 -0.051 -0.101  0.124  0.273 -0.101 -0.001 -0.101 -0.175 -0.001 -0.076  0.248 -0.126  0.074  0.074  0.099  0.248 -0.026  0.024 
 0.161  0.087 -0.038  0.112 -0.138 -0.038 -0.038  0.112  0.211  0.112  0.211 -0.013  0.062 -0.088 -0.063  0.037  0.087 -0.113 -0.063 -0.187  0.087  0.012 -0.013  0.012  0.062  0.012  0.161 -0.088 -0.013  0.062  0.361  0.012 -0.212 -0.262  0.112 -0.162  0.062  0.137  0.137 -0.162  0.112  0.012  0.087  0.137 -0.113  0.311 -0.138  0.137 -0.138 -0.187  0.037 -0.088 -0.088 -0.237 -0.038  0.037  0.087  0.037 -0.138 -0.013 -0.013  0.037  0.161 -0.113 -0.063 -0.038 -0.162 -0.013  0.236  0.012 -0.212  0.037 -0.038  0.236  0.186  0.161  0.186  0.161 -0.063  0.012 -0.212 -0.063 -0.088 -0.113  0.112  0.261 -0.113 -0.013 -0.088 -0.187  0.012 -0.063  0.261 -0.138  0.062  0.137  0.087  0.236 -0.063 -0.013 
 0.160  0.111 -0.014  0.111 -0.139 -0.039 -0.039  0.111  0.210  0.136  0.185 -0.014  0.061 -0.089 -0.064  0.061  0.086 -0.114 -0.089 -0.188  0.086  0.011 -0.014  0.011  0.061  0.011  0.160 -0.089 -0.014  0.036  0.360  0.011 -0.213 -0.263  0.111 -0.188  0.061  0.111  0.160 -0.163  0.086  0.011  0.086  0.136 -0.089  0.310 -0.139  0.111 -0.139 -0.139  0.086 -0.089 -0.064 -0.238 -0.014  0.036  0.111  0.036 -0.139 -0.014 -0.014  0.061  0.160 -0.114 -0.039 -0.039 -0.163 -0.014  0.235  0.011 -0.213  0.036 -0.039  0.235  0.160  0.160  0.185  0.160 -0.064  0.011 -0.213 -0.064 -0.089 -0.114  0.111  0.260 -0.089 -0.014 -0.039 -0.188  0.011 -0.064  0.260 -0.139  0.061  0.160  0.086  0.235 -0.064  0.011 
 0.159  0.134  0.009  0.109 -0.140 -0.040 -0.040  0.084  0.134  0.184  0.159 -0.015  0.059 -0.090 -0.065  0.009  0.109 -0.115 -0.090 -0.190  0.084  0.009  0.009  0.009  0.059  0.009  0.209 -0.115  0.009  0.034  0.358 -0.040 -0.215 -0.215  0.084 -0.190  0.034  0.084  0.184 -0.140  0.084 -0.015  0.059  0.134 -0.090  0.333 -0.140  0.109 -0.140 -0.140  0.084 -0.090 -0.065 -0.215 -0.015  0.034  0.134  0.034 -0.140 -0.015 -0.015  0.059  0.159 -0.090 -0.040 -0.040 -0.165 -0.015  0.234  0.034 -0.190 -0.015 -0.040  0.209  0.109  0.159  0.209  0.159 -0.065  0.009 -0.215 -0.040 -0.090 -0.115  0.084  0.284 -0.115 -0.015 -0.040 -0.190  0.009 -0.065  0.259 -0.140  0.059  0.159  0.084  0.259 -0.065 -0.015 
 0.155  0.131  0.006  0.106 -0.143 -0.044 -0.044  0.081  0.155  0.180  0.155  0.056  0.081 -0.094 -0.069  0.006  0.106 -0.119 -0.069 -0.193  0.081  0.056  0.006  0.031  0.056  0.006  0.205 -0.119  0.006  0.031  0.355 -0.069 -0.218 -0.193  0.081 -0.193  0.031  0.081  0.180 -0.143  0.081 -0.019  0.056  0.155 -0.094  0.330 -0.119  0.106 -0.143 -0.143  0.081 -0.094 -0.069 -0.218 -0.019  0.006  0.131  0.031 -0.143 -0.044 -0.019  0.056  0.155 -0.069 -0.094 -0.044 -0.168 -0.019  0.230  0.031 -0.193 -0.019 -0.044  0.230  0.106  0.155  0.205  0.155 -0.069  0.006 -0.218 -0.019 -0.094 -0.119  0.081  0.305 -0.119 -0.019 -0.019 -0.193  0.006 -0.044  0.255 -0.119  0.056  0.180  0.081  0.255 -0.069 -0.044 
 0.154  0.129  0.004  0.079 -0.145 -0.045 -0.045  0.054  0.179  0.204  0.154  0.054  0.079 -0.070 -0.095  0.004  0.129 -0.120 -0.070 -0.195  0.079  0.054  0.054  0.029  0.029  0.004  0.229 -0.120  0.029  0.029  0.353 -0.070 -0.220 -0.170  0.104 -0.195  0.029  0.104  0.179 -0.095  0.079 -0.020  0.054  0.154 -0.095  0.328 -0.120  0.129 -0.145 -0.145  0.079 -0.095 -0.070 -0.220 -0.020  0.004  0.129  0.029 -0.145 -0.045 -0.020  0.054  0.154 -0.070 -0.095 -0.045 -0.170 -0.020  0.229  0.004 -0.195 -0.045 -0.045  0.229  0.054  0.154  0.204  0.129 -0.070  0.004 -0.195 -0.020 -0.095 -0.120  0.079  0.303 -0.120 -0.020 -0.020 -0.195  0.004 -0.045  0.254 -0.120  0.054  0.179  0.079  0.279 -0.070 -0.045 
 0.178  0.128  0.003  0.078 -0.146 -0.021 -0.046  0.053  0.178  0.203  0.153  0.078  0.078 -0.046 -0.071  0.003  0.128 -0.146 -0.071 -0.196  0.078  0.053  0.053  0.028  0.028  0.003  0.253 -0.096  0.028  0.028  0.352 -0.071 -0.221 -0.171  0.103 -0.196  0.028  0.103  0.178 -0.096  0.103 -0.021  0.053  0.178 -0.096  0.327 -0.121  0.153 -0.146 -0.146  0.078 -0.096 -0.071 -0.221 -0.021  0.003  0.128  0.028 -0.121 -0.046 -0.021  0.053  0.153 -0.071 -0.096 -0.046 -0.171 -0.021  0.228  0.003 -0.196 -0.046 -0.021  0.228  0.053  0.153  0.253  0.128 -0.096  0.003 -0.196 -0.021 -0.096 -0.121  0.078  0.278 -0.121  0.028 -0.021 -0.196  0.003 -0.046  0.253 -0.121  0.053  0.203  0.078  0.278 -0.071 -0.046 
 0.177  0.103  0.003  0.053 -0.146 -0.022 -0.047  0.053  0.177  0.202  0.152  0.078  0.078 -0.022 -0.072  0.003  0.128 -0.146 -0.072 -0.196  0.078  0.053  0.053  0.003  0.028  0.003  0.277 -0.097  0.028  0.028  0.352 -0.097 -0.221 -0.171  0.103 -0.221  0.003  0.103  0.152 -0.097  0.103  0.003  0.053  0.177 -0.097  0.327 -0.122  0.152 -0.146 -0.122  0.078 -0.097 -0.072 -0.221 -0.022  0.003  0.128  0.028 -0.122 -0.047 -0.022  0.053  0.128 -0.072 -0.097 -0.047 -0.171 -0.022  0.227 -0.022 -0.196 -0.047 -0.022  0.227  0.053  0.152  0.252  0.152 -0.097  0.003 -0.171 -0.022 -0.097 -0.122  0.078  0.277 -0.097  0.028 -0.022 -0.196  0.003 -0.047  0.252 -0.122  0.028  0.202  0.078  0.277 -0.072 -0.047 
 0.176  0.077  0.002  0.027 -0.147 -0.023 -0.048  0.052  0.176  0.226  0.127  0.102  0.077 -0.023 -0.073  0.002  0.151 -0.123 -0.073 -0.197  0.077  0.027  0.052  0.002  0.027  0.002  0.276 -0.098  0.027  0.002  0.351 -0.123 -0.222 -0.172  0.127 -0.222  0.002  0.102  0.151 -0.073  0.077 -0.023  0.052  0.176 -0.098  0.326 -0.123  0.151 -0.172 -0.123  0.077 -0.123 -0.073 -0.222 -0.023  0.002  0.127  0.027 -0.123 -0.048 -0.073  0.052  0.127 -0.073 -0.098 -0.048 -0.172 -0.048  0.226 -0.023 -0.197 -0.048 -0.023  0.226  0.052  0.151  0.251  0.151 -0.098  0.002 -0.172 -0.023 -0.098 -0.147  0.077  0.276 -0.073  0.027 -0.073 -0.197 -0.023 -0.048  0.251 -0.147  0.027  0.201  0.077  0.276 -0.098 -0.048 
 0.175  0.076  0.001  0.001 -0.148 -0.024 -0.049  0.051  0.175  0.200  0.126  0.101  0.076 -0.024 -0.074  0.001  0.150 -0.124 -0.074 -0.198  0.076  0.026  0.051  0.001  0.051  0.001  0.275 -0.124  0.026  0.001  0.350 -0.124 -0.198 -0.173  0.150 -0.223  0.001  0.101  0.150 -0.074  0.076 -0.024  0.051  0.175 -0.099  0.325 -0.124  0.150 -0.173 -0.124  0.076 -0.124 -0.074 -0.223 -0.024  0.001  0.126  0.026 -0.124 -0.049 -0.074  0.026  0.126 -0.074 -0.099 -0.049 -0.173 -0.049  0.225  0.001 -0.198 -0.049 -0.024  0.250  0.051  0.150  0.275  0.150 -0.099  0.001 -0.173 -0.024 -0.074 -0.148  0.076  0.275 -0.074  0.026 -0.074 -0.198 -0.024 -0.049  0.275 -0.148  0.026  0.200  0.051  0.275 -0.099 -0.049 
 0.174  0.074 -0.000 -0.000 -0.150 -0.025 -0.050  0.049  0.174  0.224  0.124  0.074  0.074 -0.025 -0.075 -0.000  0.124 -0.125 -0.075 -0.200  0.074  0.024  0.074 -0.000  0.049 -0.000  0.274 -0.125 -0.000 -0.000  0.348 -0.125 -0.125 -0.175  0.149 -0.250 -0.000  0.099  0.149 -0.100  0.074 -0.025  0.049  0.174 -0.125  0.323 -0.125  0.149 -0.200 -0.125  0.074 -0.125 -0.075 -0.250 -0.025 -0.000  0.124  0.024 -0.125 -0.050 -0.075  0.024  0.124 -0.075 -0.100 -0.050 -0.175 -0.050  0.174 -0.000 -0.200 -0.050 -0.025  0.249  0.049  0.149  0.274  0.149 -0.100  0.024 -0.175 -0.025 -0.075 -0.150  0.074  0.274 -0.100  0.024 -0.075 -0.200 -0.025 -0.025  0.274 -0.150  0.024  0.199  0.049  0.274 -0.100 -0.050 
 0.172  0.073 -0.002 -0.027 -0.151 -0.027 -0.052  0.048  0.172  0.222  0.123  0.073  0.073 -0.027 -0.077 -0.002  0.123 -0.127 -0.052 -0.201  0.073  0.023  0.073 -0.002  0.048 -0.002  0.272 -0.127 -0.002 -0.002  0.347 -0.127 -0.127 -0.176  0.147 -0.251 -0.002  0.098  0.147 -0.102  0.073 -0.027  0.048  0.172 -0.151  0.347 -0.127  0.147 -0.201 -0.127  0.073 -0.127 -0.102 -0.251 -0.027 -0.002  0.123  0.023 -0.127 -0.052 -0.077  0.023  0.123 -0.077 -0.102 -0.052 -0.176 -0.052  0.172 -0.002 -0.201 -0.052 -0.027  0.247  0.048  0.147  0.297  0.147 -0.102  0.023 -0.176 -0.027 -0.077 -0.151  0.073  0.272 -0.102  0.023 -0.052 -0.201 -0.052 -0.027  0.272 -0.151  0.023  0.197  0.048  0.272 -0.102 -0.052 
 0.214  0.064 -0.010 -0.060 -0.135 -0.010 -0.035  0.064  0.164  0.139  0.064  0.039 -0.010  0.039 -0.060  0.039  0.014 -0.160 -0.035 -0.160  0.114 -0.010  0.064  0.014  0.064 -0.010  0.139 -0.135  0.014  0.039  0.264 -0.085 -0.135 -0.210  0.164 -0.210 -0.010  0.089  0.039 -0.085 -0.010  0.014  0.064  0.064 -0.135  0.264 -0.110  0.014 -0.135 -0.160  0.114 -0.085 -0.110 -0.210 -0.060 -0.035  0.114 -0.010 -0.135 -0.010 -0.035  0.064  0.039 -0.035 -0.110 -0.035 -0.160 -0.035  0.139 -0.035 -0.160 -0.035 -0.035  0.189  0.114  0.164  0.239  0.164 -0.060 -0.035 -0.135  0.014 -0.010 -0.135  0.089  0.214 -0.110  0.014 -0.035 -0.160 -0.060 -0.060  0.288 -0.135  0.089  0.164  0.064  0.214 -0.110 -0.060 
 0.127  0.027  0.052 -0.048 -0.073 -0.073 -0.073  0.077  0.176  0.002  0.027 -0.023  0.077  0.002 -0.023  0.052  0.002 -0.098 -0.073 -0.073  0.127  0.002  0.077  0.002  0.027  0.052  0.102 -0.073  0.052  0.052  0.052 -0.048 -0.123 -0.172  0.127 -0.123 -0.023  0.077  0.002 -0.023 -0.023  0.052  0.027  0.052 -0.098  0.251 -0.098 -0.023 -0.048 -0.123  0.127 -0.023 -0.073 -0.147  0.027 -0.023  0.127 -0.048 -0.098  0.027 -0.023  0.151 -0.023 -0.023 -0.073  0.027 -0.098 -0.048  0.077 -0.098 -0.123 -0.023  0.027  0.176  0.127  0.176  0.251  0.151 -0.048 -0.023 -0.098 -0.023  0.052 -0.073  0.052  0.176 -0.073 -0.073 -0.123 -0.147 -0.048 -0.023  0.226 -0.073  0.127  0.151  0.052  0.151 -0.048 -0.147 
 0.072  0.022  0.072 -0.078 -0.053 -0.078 -0.078  0.097  0.171 -0.028  0.022 -0.003  0.072 -0.003 -0.053  0.047 -0.003 -0.078 -0.078 -0.053  0.097 -0.003  0.072  0.022 -0.003  0.022  0.072 -0.053  0.072  0.022  0.072 -0.028 -0.128 -0.152  0.072 -0.078 -0.003  0.097 -0.028 -0.003 -0.053  0.072  0.022  0.022 -0.078  0.246 -0.078 -0.003 -0.028 -0.103  0.122 -0.028 -0.078 -0.152  0.022 -0.003  0.146 -0.053 -0.078  0.022 -0.003  0.171 -0.003 -0.028 -0.053 -0.003 -0.078 -0.028  0.022 -0.103 -0.103 -0.003 -0.003  0.122  0.122  0.196  0.221  0.171 -0.028 -0.003 -0.103 -0.028  0.047 -0.053  0.022  0.122 -0.078 -0.053 -0.103 -0.152 -0.028 -0.053  0.196 -0.053  0.122  0.146  0.047  0.097 -0.053 -0.128 
 0.017  0.042  0.092 -0.082 -0.032 -0.057 -0.082  0.092  0.142 -0.032  0.042  0.017  0.042 -0.007 -0.032  0.067 -0.032 -0.082 -0.107 -0.032  0.117 -0.007  0.017 -0.057 -0.032  0.042  0.017 -0.032  0.067 -0.007  0.042 -0.007 -0.132 -0.132  0.042 -0.057 -0.007  0.117 -0.032  0.017 -0.107  0.092  0.042  0.017 -0.057  0.192 -0.082 -0.007 -0.032 -0.082  0.142 -0.007 -0.057 -0.132  0.067 -0.007  0.167 -0.057 -0.057  0.017 -0.032  0.167  0.017 -0.007 -0.057  0.017 -0.082 -0.007  0.042 -0.132 -0.107  0.017 -0.007  0.092  0.117  0.217  0.242  0.142 -0.007  0.017 -0.082 -0.057  0.042 -0.032  0.042  0.067 -0.082 -0.057 -0.082 -0.132 -0.007 -0.057  0.192 -0.057  0.117  0.142  0.042  0.067 -0.032 -0.107 
 0.025  0.050  0.075 -0.075 -0.050 -0.050 -0.075  0.100  0.125 -0.050  0.025  0.000  0.025  0.000 -0.025  0.075 -0.075 -0.075 -0.100 -0.025  0.125  0.000  0.000 -0.050 -0.050  0.050  0.025 -0.025  0.050  0.000  0.050 -0.050 -0.125 -0.125  0.050 -0.050  0.000  0.125 -0.025  0.025 -0.100  0.100  0.050  0.025 -0.050  0.174 -0.075 -0.025 -0.025 -0.075  0.149  0.000 -0.050 -0.125  0.050  0.000  0.149 -0.075 -0.050  0.025 -0.050  0.174  0.025  0.000 -0.050  0.025 -0.075  0.000  0.050 -0.125 -0.100  0.025  0.000  0.100  0.075  0.224  0.249  0.125  0.000  0.025 -0.075 -0.050  0.050 -0.025  0.050  0.075 -0.075 -0.075 -0.075 -0.125  0.000 -0.050  0.199 -0.050  0.100  0.149  0.050  0.075 -0.025 -0.100 
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 0.146 -0.128 -0.103 -0.128 -0.053 -0.178 -0.078 -0.153 -0.103  0.246  0.221 -0.078 -0.203  0.021  0.096 -0.103  0.221 -0.103  0.196  0.046 -0.028 -0.078 -0.228 -0.078 -0.028  0.021 -0.103 -0.028  0.121  0.271 -0.153 -0.128 -0.228  0.021 -0.153 -0.128 -0.103 -0.028 -0.153 -0.028 -0.178 -0.078 -0.028  0.021  0.096 -0.003 -0.178  0.221 -0.053 -0.103 -0.128  0.744  0.545  0.021 -0.228  0.246  0.046  0.071  0.046  0.171 -0.053  0.171 -0.103  0.644  0.669  0.146  0.669 -0.003  0.171 -0.003  0.221 -0.028  0.146 -0.103 -0.178 -0.153 -0.028  0.121  0.221 -0.078 -0.003 -0.028 -0.103 -0.078  0.271  0.669 -0.053  0.146 -0.003 -0.078  0.046  0.146  0.071 -0.028 -0.203 -0.103 -0.153  0.644 -0.003  0.271 
 0.168 -0.131 -0.106 -0.131 -0.056 -0.181 -0.081 -0.131 -0.131  0.243  0.268 -0.081 -0.131  0.018  0.093 -0.106  0.218 -0.081  0.193  0.018 -0.031 -0.081 -0.206 -0.056 -0.056  0.068 -0.106 -0.031  0.143  0.268 -0.156 -0.106 -0.231  0.043 -0.156 -0.131 -0.106 -0.031 -0.156 -0.031 -0.181 -0.106 -0.006  0.018  0.093  0.043 -0.181  0.243 -0.056 -0.106 -0.131  0.741  0.542  0.018 -0.231  0.268  0.043  0.068  0.043  0.193 -0.056  0.168 -0.056  0.641  0.691  0.143  0.666 -0.006  0.168 -0.006  0.218 -0.031  0.143 -0.106 -0.181 -0.131 -0.006  0.168  0.218 -0.056  0.018 -0.031 -0.106 -0.081  0.268  0.666 -0.031  0.143 -0.006 -0.081  0.118  0.168  0.068 -0.031 -0.181 -0.106 -0.156  0.616 -0.006  0.292 
 0.166 -0.133 -0.133 -0.133 -0.058 -0.183 -0.083 -0.133 -0.133  0.241  0.290 -0.083 -0.133  0.016  0.091 -0.108  0.166 -0.083  0.216  0.041 -0.033 -0.083 -0.208 -0.033 -0.058  0.091 -0.108 -0.008  0.141  0.266 -0.158 -0.133 -0.233  0.041 -0.158 -0.133 -0.108 -0.008 -0.158 -0.033 -0.183 -0.133  0.016 -0.033  0.066  0.016 -0.183  0.241 -0.058 -0.108 -0.133  0.739  0.565  0.016 -0.233  0.266  0.041  0.066  0.041  0.216 -0.058  0.216 -0.033  0.639  0.664  0.141  0.664 -0.008  0.166 -0.033  0.216 -0.008  0.141 -0.108 -0.133 -0.133 -0.008  0.166  0.216 -0.058 -0.008 -0.033 -0.133 -0.058  0.266  0.664 -0.008  0.191  0.016 -0.083  0.116  0.216  0.041 -0.008 -0.183 -0.108 -0.158  0.614 -0.008  0.315 
 0.143 -0.106 -0.106 -0.106 -0.006 -0.156 -0.031 -0.081 -0.081  0.168  0.292 -0.006 -0.081  0.093  0.068 -0.081  0.168 -0.106  0.168  0.018 -0.006 -0.056 -0.156 -0.131 -0.006  0.118 -0.056  0.043  0.093  0.243 -0.131 -0.106 -0.156 -0.031 -0.131 -0.081 -0.031  0.043 -0.081 -0.006 -0.156 -0.106  0.068 -0.006  0.068  0.043 -0.181  0.193 -0.031 -0.156 -0.081  0.791  0.317 -0.006 -0.156  0.143  0.043  0.068 -0.006  0.218 -0.056  0.093 -0.106  0.567  0.641  0.118  0.641  0.018  0.218  0.018  0.218 -0.031  0.093 -0.156 -0.131 -0.081  0.043  0.068  0.243 -0.081 -0.006 -0.056 -0.131 -0.006  0.268  0.567  0.018  0.143  0.043 -0.031  0.093  0.218  0.068  0.043 -0.131 -0.056 -0.131  0.492 -0.031  0.243 
 0.109 -0.065 -0.015 -0.065  0.009 -0.090 -0.015 -0.065 -0.040  0.134  0.184  0.009 -0.065  0.109  0.009 -0.040  0.109 -0.090  0.109 -0.015 -0.065 -0.065 -0.090 -0.090  0.059  0.059 -0.015  0.009  0.009  0.209 -0.065 -0.090 -0.090 -0.015 -0.065 -0.040 -0.065  0.084 -0.065 -0.015 -0.065 -0.065  0.034 -0.040  0.009 -0.090 -0.115  0.009 -0.015 -0.115 -0.015  0.757  0.209  0.009 -0.090  0.159 -0.015  0.059 -0.015  0.134 -0.040  0.034 -0.090  0.483  0.558  0.034  0.533  0.034  0.259  0.034  0.184 -0.040  0.034 -0.090 -0.090 -0.040  0.059  0.009  0.134 -0.040  0.009  0.009 -0.090 -0.065  0.259  0.383 -0.015  0.109  0.059 -0.015  0.059  0.034  0.084  0.059 -0.090 -0.040 -0.065  0.358  0.009  0.234 
 0.032 -0.042 -0.042 -0.067  0.007 -0.067 -0.017 -0.042 -0.017  0.057  0.182  0.007 -0.067  0.107  0.032 -0.017  0.082 -0.067  0.057 -0.017 -0.067 -0.042 -0.067 -0.067  0.057  0.082  0.007 -0.042  0.007  0.107 -0.042 -0.067 -0.067  0.007 -0.042 -0.042 -0.042  0.032 -0.042  0.007 -0.042 -0.067  0.007 -0.017  0.032 -0.067 -0.092 -0.017 -0.042 -0.092 -0.042  0.755  0.207  0.007 -0.067  0.182 -0.042  0.032  0.007  0.082 -0.017  0.007 -0.067  0.431  0.431  0.057  0.506  0.032  0.282 -0.042  0.132 -0.017  0.057 -0.092 -0.092 -0.042  0.082  0.032  0.082 -0.017  0.007 -0.017 -0.067 -0.042  0.257  0.207 -0.017  0.107  0.082  0.007  0.032  0.032  0.107  0.082 -0.067 -0.017 -0.042  0.232  0.032  0.157 
 0.014 -0.035 -0.010 -0.060  0.014 -0.035 -0.010 -0.010 -0.010  0.014  0.164  0.014 -0.035  0.039  0.064 -0.010  0.039 -0.035  0.039 -0.010 -0.060 -0.010 -0.035 -0.010  0.064  0.064 -0.010 -0.010 -0.010  0.089 -0.035 -0.060 -0.035 -0.035 -0.035 -0.060 -0.060 -0.010 -0.010  0.014 -0.035 -0.060 -0.010  0.014  0.014 -0.060 -0.060 -0.035 -0.010 -0.060 -0.010  0.861  0.114  0.014 -0.035  0.114 -0.035  0.064 -0.035  0.014 -0.010 -0.010 -0.035  0.288  0.338  0.039  0.363  0.039  0.264 -0.035  0.064 -0.060 -0.010 -0.060 -0.060 -0.010  0.064 -0.010  0.039 -0.010  0.014 -0.060 -0.010 -0.035  0.214  0.139 -0.010  0.139  0.089  0.014 -0.010 -0.060  0.089  0.089 -0.035  0.014 -0.010  0.139  0.039  0.039 
 0.023 -0.026 -0.001 -0.051  0.023 -0.026 -0.026 -0.001 -0.001  0.023  0.148 -0.001 -0.026 -0.001  0.023 -0.001  0.048 -0.026  0.048 -0.001 -0.051 -0.001 -0.026  0.023  0.048  0.073 -0.001  0.023 -0.001  0.048 -0.026 -0.051 -0.026 -0.026 -0.001 -0.051 -0.051 -0.026 -0.001  0.023 -0.026 -0.051 -0.001  0.048 -0.001 -0.051 -0.051 -0.026 -0.026 -0.051 -0.001  0.945  0.123  0.023 -0.026  0.123 -0.026  0.073 -0.026  0.023 -0.001 -0.026 -0.026  0.223  0.297  0.023  0.347  0.048  0.198 -0.026  0.023 -0.051 -0.001 -0.051 -0.051 -0.001  0.048 -0.051 -0.001 -0.001 -0.001 -0.051 -0.001 -0.026  0.148  0.148 -0.001  0.148  0.098 -0.001 -0.001 -0.051  0.098  0.048 -0.051 -0.001 -0.001  0.098  0.048  0.048 
 0.017 -0.007  0.017 -0.032  0.017 -0.007 -0.007 -0.007  0.017 -0.007  0.067  0.017 -0.032 -0.032  0.042  0.017  0.067 -0.007  0.042 -0.007 -0.032  0.017 -0.007  0.042  0.067  0.017 -0.032  0.017 -0.007  0.042 -0.032 -0.032 -0.032 -0.007  0.017 -0.032 -0.032 -0.032  0.017  0.017 -0.007 -0.032 -0.007  0.042 -0.032 -0.032 -0.032 -0.007 -0.007 -0.032  0.017  0.989  0.017  0.017 -0.032  0.117 -0.007  0.092 -0.007 -0.007 -0.007 -0.032 -0.032  0.117  0.167  0.017  0.242  0.017  0.217 -0.007 -0.007 -0.032 -0.032 -0.032 -0.032  0.017  0.042 -0.032 -0.032 -0.007 -0.007 -0.032  0.017 -0.032  0.142  0.067  0.017  0.142  0.092 -0.007 -0.007 -0.032  0.067 -0.007 -0.032  0.017  0.017  0.092  0.042 -0.007 
 0.024 -0.001  0.024 -0.026  0.024 -0.001 -0.001 -0.026 -0.026 -0.001  0.074  0.024 -0.026 -0.026  0.049  0.024  0.049 -0.001  0.049 -0.001 -0.026 -0.001 -0.001  0.049  0.074  0.024 -0.026  0.024 -0.026  0.024 -0.026 -0.026 -0.026 -0.001 -0.001 -0.026 -0.026 -0.026  0.024 -0.001 -0.001 -0.026 -0.001  0.049 -0.026 -0.026 -0.026 -0.001 -0.001 -0.026  0.024  0.995 -0.001  0.024 -0.026  0.099 -0.001  0.099 -0.001 -0.026 -0.026 -0.026 -0.026  0.049  0.148  0.024  0.173  0.024  0.173 -0.001 -0.026 -0.026 -0.026 -0.026 -0.026  0.024  0.049 -0.026 -0.026 -0.001 -0.001 -0.026  0.024 -0.026  0.148  0.049 -0.001  0.124  0.099 -0.026 -0.001 -0.026  0.074 -0.001 -0.026  0.024  0.024  0.099  0.049 -0.026 
 0.028  0.003  0.003 -0.021  0.028  0.003 -0.021 -0.021 -0.021  0.003  0.078  0.003 -0.021 -0.021  0.053  0.028  0.028  0.003  0.053  0.003 -0.021 -0.021 -0.021  0.053  0.078  0.028 -0.021  0.028 -0.021  0.028 -0.021 -0.021 -0.021  0.003  0.003 -0.021 -0.021 -0.021  0.028  0.003  0.003 -0.021 -0.021  0.053 -0.021 -0.021 -0.021 -0.021  0.003 -0.021  0.003  1.000 -0.021  0.028 -0.021  0.103  0.003  0.103  0.003 -0.021 -0.021 -0.021 -0.021  0.028  0.003  0.003  0.103  0.028  0.153  0.003 -0.021 -0.021 -0.021 -0.021 -0.021  0.028  0.053 -0.021 -0.021 -0.021  0.003 -0.021  0.028 -0.021  0.128  0.053  0.003  0.103  0.078 -0.021  0.003 -0.021  0.078  0.003 -0.021  0.028  0.028  0.078  0.028 -0.021 
 0.028  0.003  0.003 -0.021  0.028  0.003 -0.021 -0.021 -0.021  0.003  0.078  0.003 -0.021 -0.021  0.053  0.028  0.028  0.003  0.053  0.003 -0.021 -0.021 -0.021  0.053  0.078  0.028 -0.021  0.028 -0.021  0.028 -0.021 -0.021 -0.021  0.003  0.003 -0.021 -0.021 -0.021  0.028  0.003  0.003 -0.021 -0.021  0.053 -0.021 -0.021 -0.021 -0.021  0.003 -0.021  0.003  1.000 -0.021  0.028 -0.021  0.103  0.003  0.103  0.003 -0.021 -0.021 -0.021 -0.021  0.028  0.003  0.003  0.103  0.028  0.153  0.003 -0.021 -0.021 -0.021 -0.021 -0.021  0.028  0.053 -0.021 -0.021 -0.021  0.003 -0.021  0.028 -0.021  0.128  0.053  0.003  0.103  0.078 -0.021  0.003 -0.021  0.078  0.003 -0.021  0.028  0.028  0.078  0.028 -0.021 
 0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  1.001 -0.020  0.029 -0.020  0.079  0.004  0.104  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.079  0.029  0.104  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.104  0.054  0.004  0.079  0.079 -0.020  0.004 -0.020  0.054  0.004 -0.020  0.029  0.029  0.079  0.029 -0.020 
 0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  1.001 -0.020  0.029 -0.020  0.079  0.004  0.104  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.079  0.029  0.104  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.104  0.054  0.004  0.079  0.079 -0.020  0.004 -0.020  0.054  0.004 -0.020  0.029  0.029  0.079  0.029 -0.020 
 0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  1.001 -0.020  0.029 -0.020  0.079  0.004  0.104  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.079  0.029  0.104  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.104  0.054  0.004  0.079  0.079 -0.020  0.004 -0.020  0.054  0.004 -0.020  0.029  0.029  0.079  0.029 -0.020 
 0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  1.001 -0.020  0.029 -0.020  0.079  0.004  0.104  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.079  0.029  0.104  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.104  0.054  0.004  0.079  0.079 -0.020  0.004 -0.020  0.054  0.004 -0.020  0.029  0.029  0.079  0.029 -0.020 
 0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  1.001 -0.020  0.029 -0.020  0.079  0.004  0.104  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.079  0.029  0.104  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020  0.104  0.054  0.004  0.079  0.079 -0.020  0.004 -0.020  0.054  0.004 -0.020  0.029  0.029  0.079  0.029 -0.020 
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 0.354 -0.070 -0.269 -0.169  0.080 -0.095 -0.194 -0.144 -0.169  0.030  0.130  0.105  0.105  0.080  0.179 -0.045  0.453 -0.144  0.005 -0.144 -0.144 -0.045 -0.244 -0.144  0.105  0.005 -0.095  0.080  0.030  0.055  0.005 -0.269 -0.244 -0.194 -0.045 -0.045  0.055 -0.144 -0.169 -0.095 -0.095 -0.120 -0.144  0.229 -0.169 -0.144 -0.194 -0.020 -0.144 -0.144  0.204  0.678  0.179  0.404 -0.020  0.229  0.653  0.578  0.503  0.678  0.055  0.578  0.005  0.404  0.428  0.354  0.678  0.030  0.553 -0.194  0.653 -0.020  0.005  0.204 -0.070  0.154 -0.020  0.055  0.204  0.030  0.453  0.030  0.379  0.154  0.653  0.329  0.179  0.603 -0.045  0.080  0.154  0.628  0.404  0.105  0.055  0.204 -0.045  0.254  0.105  0.304 
 0.351 -0.097 -0.272 -0.147  0.102 -0.097 -0.197 -0.147 -0.172  0.027  0.102  0.127  0.102  0.102  0.227 -0.097  0.451 -0.122 -0.022 -0.147 -0.147 -0.022 -0.247 -0.147  0.127  0.002 -0.047  0.077  0.027  0.077 -0.022 -0.247 -0.247 -0.197  0.027 -0.047  0.052 -0.122 -0.197 -0.097 -0.072 -0.097 -0.147  0.227 -0.172 -0.122 -0.197 -0.072 -0.097 -0.147  0.227  0.650  0.177  0.401 -0.022  0.227  0.675  0.551  0.501  0.675  0.052  0.575  0.002  0.401  0.451  0.401  0.650  0.027  0.551 -0.197  0.650  0.002  0.077  0.227 -0.097  0.152 -0.022  0.052  0.252  0.002  0.401  0.027  0.401  0.152  0.625  0.326  0.202  0.625 -0.022  0.052  0.177  0.625  0.401  0.102  0.102  0.227 -0.047  0.252  0.102  0.376 
 0.379 -0.094 -0.269 -0.144  0.105 -0.094 -0.194 -0.169 -0.144  0.030  0.080  0.130  0.080  0.105  0.230 -0.094  0.454 -0.094 -0.019 -0.144 -0.169  0.005 -0.244 -0.144  0.105  0.005 -0.044  0.105  0.030  0.080 -0.019 -0.244 -0.244 -0.194  0.055 -0.044  0.055 -0.119 -0.144 -0.094 -0.044 -0.119 -0.144  0.230 -0.144 -0.119 -0.194 -0.119 -0.094 -0.144  0.255  0.653  0.180  0.354 -0.019  0.280  0.678  0.554  0.479  0.678  0.030  0.554 -0.019  0.379  0.454  0.429  0.653  0.055  0.529 -0.219  0.653  0.030  0.155  0.255 -0.094  0.155 -0.019  0.055  0.230  0.005  0.429  0.030  0.404  0.155  0.578  0.379  0.280  0.628 -0.019  0.055  0.155  0.628  0.354  0.105  0.105  0.230 -0.069  0.255  0.105  0.404 
 0.378 -0.096 -0.245 -0.145  0.104 -0.071 -0.195 -0.170 -0.145  0.029  0.079  0.153  0.079  0.129  0.228 -0.096  0.452 -0.071 -0.021 -0.145 -0.170  0.029 -0.245 -0.145  0.079  0.004 -0.021  0.104  0.029  0.079 -0.046 -0.245 -0.245 -0.195  0.054 -0.046 -0.021 -0.121 -0.121 -0.096 -0.021 -0.145 -0.121  0.228 -0.121 -0.121 -0.195 -0.121 -0.096 -0.145  0.278  0.652  0.178  0.353 -0.021  0.303  0.677  0.527  0.452  0.677  0.029  0.552 -0.021  0.378  0.452  0.452  0.652  0.029  0.527 -0.220  0.652  0.029  0.203  0.253 -0.096  0.153  0.004  0.054  0.228  0.004  0.427  0.029  0.452  0.178  0.502  0.403  0.303  0.627 -0.021  0.054  0.203  0.652  0.328  0.104  0.104  0.253 -0.071  0.228  0.104  0.427 
 0.354 -0.095 -0.244 -0.144  0.105 -0.070 -0.194 -0.169 -0.144  0.030  0.080  0.154  0.080  0.154  0.229 -0.095  0.453 -0.070 -0.020 -0.144 -0.169  0.055 -0.244 -0.144  0.080  0.005 -0.020  0.105  0.030  0.080 -0.045 -0.244 -0.244 -0.194  0.055 -0.045 -0.020 -0.120 -0.120 -0.095 -0.020 -0.144 -0.120  0.229 -0.120 -0.120 -0.194 -0.120 -0.095 -0.144  0.254  0.653  0.179  0.354 -0.020  0.304  0.678  0.528  0.478  0.678  0.030  0.528 -0.020  0.379  0.453  0.453  0.653  0.030  0.528 -0.219  0.653  0.030  0.204  0.254 -0.095  0.154  0.005  0.055  0.229  0.005  0.428  0.030  0.428  0.179  0.478  0.404  0.304  0.628 -0.020  0.055  0.204  0.653  0.304  0.105  0.105  0.254 -0.070  0.229  0.105  0.428 
 0.328 -0.095 -0.245 -0.120  0.104 -0.070 -0.195 -0.170 -0.145  0.004  0.129  0.154  0.079  0.154  0.229 -0.120  0.428 -0.070 -0.020 -0.145 -0.170  0.054 -0.245 -0.170  0.104  0.004 -0.020  0.104  0.029  0.079 -0.045 -0.245 -0.245 -0.195  0.079 -0.045 -0.020 -0.145 -0.095 -0.095 -0.020 -0.120 -0.120  0.254 -0.120 -0.095 -0.195 -0.095 -0.120 -0.145  0.254  0.627  0.154  0.353  0.004  0.303  0.677  0.478  0.478  0.677  0.079  0.503 -0.020  0.353  0.453  0.453  0.652  0.029  0.553 -0.220  0.652  0.029  0.204  0.254 -0.070  0.179  0.004  0.054  0.254  0.004  0.428  0.054  0.428  0.204  0.453  0.403  0.303  0.627 -0.020  0.104  0.229  0.652  0.303  0.104  0.104  0.254 -0.070  0.204  0.104  0.453 
 0.301 -0.048 -0.197 -0.147  0.077 -0.023 -0.123 -0.147 -0.098 -0.023  0.127  0.102  0.052  0.201  0.176 -0.073  0.351 -0.073  0.027 -0.123 -0.197 -0.023 -0.222 -0.147  0.151 -0.048  0.002 -0.048  0.077 -0.023 -0.023 -0.197 -0.197 -0.123  0.027  0.027 -0.048 -0.172 -0.147 -0.147 -0.023 -0.098 -0.123  0.251 -0.073 -0.123 -0.197 -0.147 -0.123 -0.123  0.201  0.650  0.176  0.301  0.052  0.251  0.575  0.351  0.450  0.724  0.102  0.475  0.002  0.226  0.475  0.401  0.575  0.027  0.450 -0.147  0.600  0.052  0.127  0.251 -0.073  0.226  0.002  0.027  0.251  0.052  0.475  0.002  0.401  0.251  0.401  0.351  0.276  0.550 -0.048 -0.023  0.201  0.625  0.351  0.027  0.102  0.176 -0.023  0.276  0.102  0.450 
 0.217 -0.007 -0.132 -0.107  0.068 -0.007 -0.107 -0.132 -0.082 -0.057  0.043  0.018 -0.057  0.093  0.043 -0.007  0.142 -0.032  0.093 -0.057 -0.156 -0.007 -0.132 -0.082  0.118 -0.057 -0.032 -0.057  0.118  0.018 -0.007 -0.132 -0.132 -0.082  0.068  0.068 -0.057 -0.107 -0.082 -0.107  0.018 -0.057 -0.082  0.118 -0.057 -0.082 -0.156 -0.082 -0.057 -0.057  0.192  0.691  0.217  0.267  0.018  0.118  0.516  0.267  0.417  0.740  0.093  0.292  0.043  0.217  0.417  0.367  0.491  0.018  0.466 -0.082  0.541  0.043  0.018  0.217 -0.057  0.217  0.043  0.018  0.142 -0.007  0.516 -0.007  0.167  0.242  0.342  0.292  0.192  0.541 -0.057  0.018  0.217  0.566  0.367  0.018 -0.007  0.118 -0.007  0.267  0.118  0.392 
 0.240 -0.009 -0.109 -0.084  0.066  0.016 -0.084 -0.109 -0.059 -0.034  0.041 -0.009 -0.059  0.041  0.016  0.016  0.041 -0.009  0.091 -0.059 -0.134  0.016 -0.109 -0.059  0.116 -0.034 -0.009 -0.034  0.091  0.016 -0.034 -0.109 -0.109 -0.059  0.016  0.066 -0.059 -0.109 -0.059 -0.084 -0.009 -0.059 -0.059  0.091 -0.059 -0.084 -0.134 -0.059 -0.084 -0.034  0.190  0.689  0.240  0.240  0.041  0.116  0.489  0.165  0.415  0.763  0.091  0.240  0.041  0.190  0.439  0.290  0.464  0.041  0.439 -0.059  0.390 -0.059 -0.009  0.116 -0.084  0.165  0.041  0.016  0.066 -0.009  0.564 -0.009  0.091  0.165  0.315  0.165  0.190  0.514 -0.034 -0.034  0.215  0.589  0.365  0.041 -0.034  0.066 -0.034  0.165  0.141  0.365 
 0.219  0.020 -0.080 -0.055  0.020 -0.030 -0.080 -0.080 -0.055 -0.030  0.045 -0.055 -0.080 -0.005 -0.055 -0.005 -0.030 -0.005  0.120 -0.030 -0.105 -0.005 -0.080 -0.055  0.095 -0.005 -0.005 -0.005  0.070 -0.005 -0.055 -0.080 -0.105 -0.080  0.045  0.020 -0.055 -0.080 -0.055 -0.055  0.020 -0.030 -0.030  0.070 -0.080 -0.080 -0.105 -0.080 -0.055 -0.030  0.169  0.643  0.244  0.244  0.045  0.144  0.369  0.194  0.419  0.767  0.020  0.020  0.045  0.144  0.443  0.244  0.419  0.020  0.419 -0.030  0.319 -0.030 -0.080  0.070 -0.080  0.070  0.070  0.020  0.020 -0.005  0.593 -0.005  0.020  0.120  0.144  0.070  0.169  0.468 -0.055 -0.005  0.169  0.568  0.269 -0.005 -0.005 -0.005 -0.030  0.144  0.144  0.394 
 0.175  0.026 -0.074 -0.049  0.026 -0.024 -0.099 -0.074 -0.049 -0.024  0.026 -0.049 -0.099 -0.049 -0.049  0.001 -0.049  0.026  0.126 -0.024 -0.099  0.001 -0.099 -0.049  0.051  0.001  0.001  0.026  0.076  0.001 -0.074 -0.074 -0.099 -0.099  0.051  0.001 -0.049 -0.074 -0.049 -0.049  0.051 -0.024 -0.024  0.026 -0.074 -0.074 -0.099 -0.074 -0.074 -0.024  0.150  0.624  0.225  0.200  0.051  0.150  0.300  0.200  0.375  0.823  0.026 -0.024  0.026  0.150  0.449  0.225  0.425  0.026  0.375 -0.024  0.225 -0.024 -0.074  0.051 -0.074  0.026  0.076  0.026  0.001  0.001  0.624  0.001  0.026  0.076  0.076  0.051  0.175  0.499 -0.049 -0.024  0.150  0.624  0.225  0.001  0.001  0.001 -0.049  0.051  0.126  0.425 
 0.160  0.035 -0.064 -0.064  0.035 -0.014 -0.089 -0.064 -0.039 -0.014  0.010 -0.039 -0.089 -0.064 -0.039 -0.014 -0.039  0.035  0.060 -0.014 -0.089  0.010 -0.089 -0.064  0.060  0.010 -0.014  0.035  0.085  0.010 -0.064 -0.064 -0.089 -0.089  0.060 -0.014 -0.064 -0.064 -0.039 -0.064  0.035 -0.014 -0.014  0.035 -0.064 -0.064 -0.089 -0.064 -0.064 -0.014  0.085  0.633  0.235  0.085  0.010  0.160  0.260  0.160  0.309  0.833 -0.014 -0.064  0.035  0.160  0.459  0.185  0.409 -0.014  0.384 -0.014  0.110 -0.014 -0.064  0.035 -0.064 -0.039  0.060 -0.039  0.010  0.010  0.633 -0.014 -0.039  0.035  0.085  0.035  0.135  0.459 -0.014 -0.064  0.160  0.633  0.185  0.010 -0.014  0.010 -0.039  0.035  0.085  0.434 
 0.163  0.039 -0.061 -0.061  0.039 -0.011 -0.086 -0.061 -0.061 -0.011  0.014 -0.011 -0.086 -0.061 -0.036 -0.011 -0.036  0.039  0.064 -0.011 -0.086  0.014 -0.086 -0.061  0.064  0.014 -0.011  0.039  0.089  0.014 -0.061 -0.061 -0.086 -0.086  0.064 -0.036 -0.061 -0.061 -0.036 -0.061  0.039 -0.011 -0.011  0.039 -0.061 -0.061 -0.086 -0.061 -0.061 -0.011  0.064  0.637  0.238  0.089 -0.011  0.163  0.188  0.163  0.263  0.836 -0.036 -0.086  0.014  0.139  0.437  0.163  0.363 -0.011  0.388 -0.036  0.089 -0.036 -0.061  0.039 -0.061 -0.036  0.064 -0.061  0.014  0.014  0.612 -0.011 -0.036  0.039  0.089  0.014  0.139  0.462 -0.011 -0.061  0.163  0.687  0.188 -0.011 -0.036  0.014 -0.036  0.039  0.064  0.413 
 0.145  0.021 -0.054 -0.054  0.046 -0.004 -0.079 -0.054 -0.054 -0.029  0.021 -0.029 -0.079 -0.079 -0.029 -0.029 -0.029  0.046  0.046 -0.004 -0.079 -0.004 -0.079 -0.029  0.071 -0.004 -0.004  0.071  0.071  0.021 -0.054 -0.054 -0.079 -0.079  0.071 -0.029 -0.054 -0.054 -0.029 -0.004  0.046 -0.004 -0.004  0.071 -0.054 -0.054 -0.079 -0.054 -0.054 -0.004  0.046  0.694  0.195  0.096 -0.004  0.170  0.096  0.170  0.195  0.843 -0.029 -0.079 -0.004  0.096  0.420  0.121  0.295 -0.004  0.395 -0.029  0.021 -0.029 -0.054  0.046 -0.054 -0.054  0.071 -0.079  0.021 -0.004  0.619 -0.004 -0.029 -0.004  0.096  0.021  0.096  0.345  0.021 -0.054  0.170  0.743  0.195 -0.029 -0.029 -0.004 -0.029  0.071  0.021  0.395 
 0.122  0.022 -0.053 -0.053  0.022  0.022 -0.078 -0.053 -0.053 -0.003  0.022 -0.028 -0.078 -0.078 -0.003 -0.028 -0.028  0.047  0.047 -0.003 -0.078 -0.003 -0.078 -0.028  0.072 -0.003 -0.003  0.097  0.072 -0.003 -0.053 -0.053 -0.078 -0.078  0.072 -0.028 -0.053 -0.053 -0.028  0.022  0.047 -0.003  0.022  0.072 -0.053 -0.053 -0.078 -0.053 -0.053 -0.003  0.047  0.695  0.196  0.122 -0.003  0.171  0.097  0.122  0.196  0.869 -0.028 -0.078 -0.003  0.097  0.371  0.097  0.296 -0.003  0.396 -0.028  0.022 -0.028 -0.053  0.047 -0.053 -0.053  0.072 -0.078  0.022 -0.003  0.645 -0.003 -0.028 -0.003  0.097  0.022  0.097  0.321  0.022 -0.053  0.171  0.769  0.196 -0.028 -0.028 -0.003 -0.028  0.072  0.022  0.371 
 0.127  0.027 -0.048 -0.048  0.027  0.027 -0.073 -0.048 -0.048  0.002  0.052 -0.023 -0.048 -0.073  0.002 -0.023 -0.048  0.052  0.052  0.002 -0.073  0.027 -0.073 -0.023  0.077  0.002  0.002  0.102  0.077 -0.023 -0.048 -0.048 -0.073 -0.048  0.077 -0.023 -0.073 -0.048  0.002  0.027  0.052  0.002  0.002  0.077 -0.073 -0.073 -0.073 -0.023 -0.048  0.002  0.027  0.724  0.151  0.102  0.002  0.176  0.052  0.102  0.176  0.924 -0.023 -0.073  0.002  0.027  0.301  0.077  0.226  0.002  0.401 -0.023  0.002 -0.023 -0.048  0.052 -0.048 -0.023  0.077 -0.073  0.027  0.002  0.625 -0.023 -0.023  0.002  0.127  0.027  0.102  0.301  0.027 -0.048  0.151  0.774  0.201 -0.023 -0.023  0.002  0.002  0.077  0.002  0.251 
 0.103  0.028 -0.046 -0.046  0.028  0.003 -0.071 -0.046 -0.046  0.003  0.053 -0.021 -0.046 -0.071  0.003 -0.021 -0.046  0.053  0.028  0.003 -0.071  0.028 -0.071 -0.021  0.078  0.003  0.003  0.078  0.053 -0.021 -0.071 -0.046 -0.071 -0.046  0.103 -0.021 -0.071 -0.046  0.003  0.028  0.078  0.003 -0.021  0.103 -0.071 -0.071 -0.071 -0.021 -0.046  0.003  0.028  0.751  0.128  0.103  0.003  0.178  0.053  0.103  0.153  0.950 -0.046 -0.071 -0.021  0.028  0.253  0.078  0.203  0.003  0.402 -0.021  0.003 -0.021 -0.046  0.053 -0.046  0.003  0.053 -0.046  0.003  0.003  0.601 -0.021  0.003  0.003  0.128  0.003  0.103  0.302  0.028 -0.046  0.103  0.776  0.228 -0.021 -0.021  0.003  0.003  0.078  0.003  0.203 
 0.105  0.030 -0.044 -0.044  0.005  0.005 -0.069 -0.019 -0.069  0.005  0.055  0.005 -0.044 -0.069  0.005 -0.019 -0.044  0.055  0.030  0.005 -0.069  0.055 -0.069 -0.019  0.105 -0.019  0.005  0.080  0.055 -0.019 -0.069 -0.044 -0.069 -0.044  0.080  0.005 -0.069 -0.044  0.030  0.005  0.080  0.005 -0.019  0.105 -0.069 -0.069 -0.069 -0.019 -0.044  0.005  0.030  0.778  0.055  0.105  0.005  0.155  0.055  0.105  0.155  0.952 -0.044 -0.069 -0.019  0.005  0.155  0.080  0.180  0.005  0.379 -0.019  0.005 -0.019 -0.044  0.080 -0.044  0.030  0.055 -0.044  0.005 -0.019  0.628 -0.019  0.005  0.005  0.155  0.005  0.105  0.230  0.030 -0.044  0.105  0.828  0.205  0.005 -0.019  0.005  0.005  0.080  0.005  0.105 
 0.130  0.030 -0.045 -0.045  0.005  0.030 -0.070 -0.045 -0.070  0.005  0.055  0.005 -0.045 -0.070  0.005 -0.020 -0.045  0.055  0.055  0.005 -0.070  0.030 -0.070 -0.020  0.105 -0.020  0.005  0.105  0.055 -0.020 -0.070 -0.045 -0.070 -0.045  0.055  0.005 -0.070 -0.045  0.030  0.030  0.055  0.005 -0.020  0.080 -0.070 -0.070 -0.070 -0.020 -0.045  0.005  0.030  0.802  0.055  0.105  0.005  0.154  0.055  0.105  0.154  0.952 -0.045 -0.070 -0.020  0.005  0.154  0.080  0.179  0.005  0.354 -0.020  0.005 -0.020 -0.045  0.080 -0.045  0.030  0.055 -0.045  0.005 -0.020  0.628 -0.020  0.005  0.005  0.154  0.005  0.105  0.229  0.030 -0.045  0.105  0.852  0.179  0.030 -0.020  0.005  0.005  0.080  0.005  0.105 
 0.131  0.031 -0.044 -0.044  0.006  0.031 -0.069 -0.044 -0.069  0.006  0.031  0.006 -0.044 -0.069  0.006 -0.019 -0.044  0.031  0.031  0.006 -0.069  0.031 -0.044  0.006  0.106 -0.019 -0.019  0.106  0.056 -0.019 -0.069 -0.044 -0.069 -0.044  0.031 -0.019 -0.069 -0.044  0.031  0.031  0.031  0.006 -0.019  0.056 -0.069 -0.069 -0.069 -0.019 -0.044 -0.019  0.031  0.803  0.031  0.106  0.006  0.106  0.056  0.106  0.155  0.953 -0.044 -0.069 -0.019  0.006  0.081  0.056  0.131  0.006  0.330  0.006  0.006 -0.019 -0.044  0.081 -0.044  0.031  0.056 -0.044  0.006  0.006  0.629  0.006  0.006  0.006  0.155  0.006  0.106  0.230  0.031 -0.044  0.106  0.928  0.180  0.031 -0.019  0.006  0.006  0.081  0.006  0.081 
 0.129  0.029 -0.046 -0.046  0.004  0.029 -0.071 -0.046 -0.071  0.004  0.029  0.004 -0.046 -0.071  0.004 -0.021 -0.021  0.029  0.054  0.004 -0.071  0.029 -0.046  0.004  0.104 -0.021 -0.021  0.104  0.054  0.004 -0.071 -0.046 -0.071 -0.046  0.004 -0.021 -0.046 -0.046  0.029  0.029  0.004  0.004 -0.021  0.054 -0.071 -0.046 -0.071 -0.021 -0.046 -0.021  0.029  0.901  0.029  0.104  0.004  0.104  0.054  0.104  0.153  0.951 -0.046 -0.046 -0.021  0.004  0.079  0.054  0.129  0.004  0.303  0.004  0.004 -0.021 -0.046  0.079 -0.046  0.029  0.054 -0.046  0.004  0.004  0.627  0.004  0.004  0.029  0.153  0.004  0.104  0.203  0.029 -0.046  0.104  0.951  0.178  0.029 -0.021  0.004  0.004  0.079  0.004  0.079 
 0.129  0.029 -0.045 -0.045  0.004  0.029 -0.070 -0.020 -0.070  0.004  0.054  0.004 -0.045 -0.070  0.004 -0.020 -0.020  0.029  0.054  0.004 -0.070  0.054 -0.045  0.004  0.104  0.004 -0.020  0.104  0.054  0.004 -0.070 -0.045 -0.070 -0.045  0.004 -0.020 -0.045 -0.045  0.029  0.029  0.004  0.004 -0.020  0.054 -0.070 -0.045 -0.070 -0.020 -0.045 -0.020  0.029  0.926  0.029  0.104  0.004  0.104  0.054  0.104  0.154  0.951 -0.045 -0.045 -0.020  0.004  0.054  0.029  0.129  0.004  0.229  0.004 -0.020 -0.020 -0.045  0.079 -0.070  0.029  0.054 -0.045  0.004  0.004  0.652  0.004  0.004  0.029  0.154  0.004  0.079  0.179  0.029 -0.045  0.104  0.951  0.179  0.029 -0.020  0.029  0.004  0.079  0.004  0.079 
 0.129  0.029 -0.046 -0.046  0.004  0.029 -0.071 -0.021 -0.071  0.004  0.054  0.004 -0.046 -0.071  0.004 -0.021 -0.021  0.029  0.054  0.004 -0.071  0.054 -0.046  0.004  0.104  0.004 -0.021  0.104  0.054  0.004 -0.071 -0.046 -0.071 -0.046  0.004 -0.021 -0.046 -0.046  0.029  0.029  0.004  0.004 -0.021  0.054 -0.071 -0.046 -0.071 -0.021 -0.046 -0.021  0.029  0.926  0.029  0.104  0.004  0.104  0.054  0.104  0.153  0.951 -0.046 -0.046 -0.021  0.004  0.054  0.029  0.129  0.004  0.228  0.004 -0.021 -0.021 -0.046  0.079 -0.071  0.029  0.054 -0.046  0.004  0.004  0.677  0.004  0.004  0.029  0.153  0.004  0.079  0.178  0.029 -0.046  0.104  0.951  0.178  0.029 -0.021  0.029  0.004  0.079  0.004  0.079 
 0.107  0.032 -0.043 -0.043  0.007  0.007 -0.068 -0.018 -0.068  0.007  0.057  0.007 -0.043 -0.068  0.007 -0.043 -0.018  0.032  0.057  0.007 -0.068  0.032 -0.043  0.007  0.107  0.007 -0.018  0.082  0.057  0.007 -0.068 -0.043 -0.068 -0.043  0.007 -0.018 -0.043 -0.043  0.032 -0.018  0.007  0.007 -0.043  0.057 -0.068 -0.043 -0.068 -0.043 -0.043 -0.043  0.032  0.929  0.032  0.107 -0.018  0.057  0.057  0.107  0.156  0.929 -0.043 -0.043 -0.018  0.007  0.032  0.032  0.082  0.007  0.156  0.007 -0.018 -0.018 -0.043  0.057 -0.068  0.007  0.032 -0.068  0.007  0.007  0.630  0.007  0.007  0.032  0.132  0.007  0.082  0.132  0.032 -0.043  0.107  0.954  0.156  0.032 -0.018  0.032  0.007  0.082  0.007  0.082 
 0.106  0.031 -0.043 -0.043  0.006  0.006 -0.068 -0.018 -0.068  0.006  0.056  0.006 -0.043 -0.068  0.006 -0.043 -0.018  0.031  0.056  0.006 -0.068  0.031 -0.043  0.006  0.106  0.006 -0.018  0.081  0.056  0.006 -0.068 -0.043 -0.068 -0.043  0.006 -0.018 -0.043 -0.043  0.031 -0.018  0.006  0.006 -0.043  0.056 -0.068 -0.043 -0.068 -0.043 -0.043 -0.043  0.031  0.928  0.031  0.106 -0.018  0.056  0.056  0.106  0.156  0.928 -0.043 -0.043 -0.018  0.006  0.031  0.031  0.081  0.006  0.156  0.006 -0.018 -0.018 -0.043  0.056 -0.068  0.006  0.031 -0.068  0.006  0.006  0.654  0.006  0.006  0.031  0.131  0.006  0.081  0.131  0.031 -0.043  0.106  0.953  0.156  0.031 -0.018  0.031  0.006  0.081  0.006  0.081 
 0.106  0.031 -0.044 -0.044  0.006  0.031 -0.069 -0.019 -0.069  0.006  0.056  0.006 -0.044 -0.069  0.006 -0.044  0.006  0.031  0.056  0.006 -0.069  0.031 -0.044  0.031  0.106  0.006 -0.019  0.106  0.056  0.006 -0.069 -0.044 -0.069 -0.044  0.006 -0.019 -0.044 -0.044  0.031  0.006  0.006  0.006 -0.044  0.056 -0.069 -0.044 -0.069 -0.044 -0.019 -0.044  0.031  0.953  0.031  0.106 -0.019  0.056  0.056  0.106  0.155  0.928 -0.044 -0.044 -0.019  0.006  0.031  0.031  0.081  0.006  0.155  0.006 -0.019 -0.019 -0.044  0.056 -0.069  0.006  0.031 -0.069  0.006  0.006  0.654  0.006  0.006  0.031  0.131  0.006  0.081  0.106  0.031 -0.044  0.106  0.953  0.155  0.031 -0.019  0.031  0.006  0.106  0.006  0.081 
 0.117  0.017 -0.082 -0.057 -0.032  0.017 -0.082 -0.032 -0.107 -0.007  0.042  0.017 -0.057 -0.007  0.017 -0.057  0.017  0.042  0.067 -0.032 -0.107 -0.007 -0.082 -0.007  0.117 -0.007 -0.007  0.117  0.092 -0.032 -0.082 -0.057 -0.082 -0.082  0.042 -0.032 -0.082 -0.082  0.042  0.017  0.067 -0.032 -0.082  0.142 -0.082 -0.032 -0.082 -0.082 -0.057 -0.007  0.017  0.914  0.067  0.092 -0.032  0.092  0.067  0.192  0.242  0.914 -0.057 -0.057 -0.032  0.042  0.192  0.042  0.192 -0.032  0.391 -0.032 -0.007 -0.057 -0.032  0.042 -0.082  0.017  0.067 -0.082  0.042 -0.032  0.815 -0.032  0.067  0.017  0.167 -0.032  0.067  0.267 -0.007 -0.007  0.167  0.914  0.242  0.067 -0.057  0.067 -0.007  0.117  0.017  0.242 
 0.241 -0.033 -0.108 -0.008 -0.033 -0.033 -0.108 -0.083 -0.158 -0.058  0.091 -0.008 -0.083 -0.008 -0.008 -0.108 -0.008 -0.008  0.116 -0.108 -0.158  0.041 -0.133 -0.033  0.116 -0.008 -0.058  0.066  0.141 -0.008 -0.083 -0.133 -0.158 -0.158 -0.008 -0.033 -0.133 -0.083 -0.008 -0.008  0.066 -0.058 -0.083  0.166 -0.133 -0.008 -0.133 -0.083 -0.108 -0.058  0.066  0.839  0.141  0.241  0.016  0.116  0.166  0.340  0.490  0.839 -0.033 -0.108 -0.033  0.091  0.515  0.191  0.540 -0.008  0.589 -0.083  0.141 -0.108 -0.083  0.116 -0.133  0.066  0.041 -0.033  0.066  0.016  0.839 -0.058  0.066  0.116  0.191 -0.033  0.091  0.440 -0.058 -0.058  0.216  0.839  0.365  0.116 -0.108  0.091 -0.058  0.116  0.041  0.415 
 0.252 -0.072 -0.171 -0.047 -0.047 -0.072 -0.171 -0.097 -0.146 -0.022  0.128 -0.022 -0.097  0.028 -0.022 -0.097  0.003 -0.047  0.128 -0.146 -0.171  0.028 -0.171 -0.072  0.177 -0.022 -0.072  0.028  0.103 -0.022 -0.097 -0.171 -0.196 -0.196  0.003 -0.072 -0.146 -0.122 -0.047 -0.022  0.028 -0.097 -0.072  0.202 -0.196 -0.047 -0.171 -0.047 -0.097 -0.072  0.078  0.800  0.227  0.277  0.003  0.128  0.202  0.352  0.701  0.800 -0.022 -0.022  0.028  0.177  0.476  0.277  0.701 -0.022  0.576 -0.097  0.327 -0.072 -0.122  0.202 -0.146  0.078  0.028  0.028  0.078 -0.022  0.775  0.003  0.078  0.103  0.152 -0.022  0.128  0.601 -0.097 -0.022  0.227  0.800  0.377  0.128 -0.122  0.053 -0.097  0.202  0.103  0.501 
 0.285 -0.039 -0.188 -0.039 -0.089 -0.114 -0.213 -0.114 -0.163 -0.064  0.136 -0.014 -0.089  0.036  0.061 -0.139 -0.014 -0.039  0.086 -0.163 -0.188  0.061 -0.213 -0.114  0.185 -0.014 -0.089  0.011  0.061 -0.039 -0.089 -0.188 -0.188 -0.238 -0.039 -0.039 -0.139 -0.139 -0.114 -0.039  0.011 -0.139 -0.114  0.136 -0.188 -0.114 -0.188  0.011 -0.114 -0.064  0.061  0.733  0.260  0.310 -0.014  0.210  0.310  0.335  0.684  0.758  0.011  0.011 -0.014  0.285  0.509  0.310  0.733 -0.014  0.559 -0.114  0.509 -0.014 -0.139  0.235 -0.188  0.036  0.061  0.061  0.136 -0.039  0.733  0.036  0.111  0.210  0.210  0.036  0.185  0.758 -0.139  0.086  0.260  0.758  0.385  0.185 -0.114  0.036 -0.089  0.260  0.185  0.559 
 0.270 -0.054 -0.178 -0.029 -0.104 -0.129 -0.178 -0.129 -0.153 -0.054  0.121 -0.004 -0.054  0.046  0.046 -0.129  0.021 -0.054  0.071 -0.129 -0.203  0.096 -0.228 -0.129  0.170 -0.029 -0.079 -0.029  0.046 -0.029 -0.079 -0.178 -0.228 -0.228 -0.029 -0.029 -0.153 -0.153 -0.129 -0.054 -0.004 -0.153 -0.129  0.121 -0.203 -0.129 -0.178 -0.004 -0.129 -0.079  0.071  0.718  0.245  0.345 -0.029  0.195  0.420  0.320  0.669  0.743 -0.004  0.145 -0.029  0.270  0.519  0.320  0.718  0.021  0.519 -0.129  0.594 -0.029 -0.153  0.220 -0.203  0.046  0.046  0.046  0.195 -0.029  0.718  0.121  0.145  0.270  0.270  0.071  0.195  0.718 -0.153  0.096  0.245  0.743  0.370  0.220 -0.079  0.021 -0.104  0.270  0.245  0.569 
 0.305 -0.044 -0.218 -0.044 -0.094 -0.168 -0.193 -0.119 -0.168 -0.094  0.106 -0.019 -0.044  0.056  0.106 -0.094 -0.019 -0.069  0.031 -0.143 -0.218  0.081 -0.243 -0.143  0.131 -0.044 -0.094 -0.069  0.081 -0.044 -0.044 -0.193 -0.243 -0.243 -0.019 -0.044 -0.168 -0.168 -0.143 -0.119 -0.019 -0.143 -0.143  0.081 -0.168 -0.143 -0.193  0.006 -0.168 -0.143  0.031  0.679  0.255  0.355 -0.044  0.230  0.429  0.230  0.679  0.704  0.031  0.180 -0.019  0.305  0.504  0.355  0.704  0.006  0.504 -0.094  0.629  0.006 -0.069  0.305 -0.218  0.081  0.056  0.056  0.280  0.006  0.629  0.131  0.205  0.280  0.280  0.180  0.230  0.679 -0.143  0.205  0.305  0.704  0.355  0.355  0.006  0.006 -0.094  0.230  0.255  0.604 
 0.325 -0.074 -0.223 -0.074 -0.074 -0.173 -0.198 -0.148 -0.173 -0.124  0.101  0.026 -0.049  0.026  0.126 -0.099 -0.024 -0.099  0.026 -0.148 -0.223  0.051 -0.248 -0.148  0.126 -0.049 -0.074 -0.049  0.076 -0.049 -0.049 -0.223 -0.248 -0.248  0.001 -0.049 -0.173 -0.173 -0.099 -0.124 -0.024 -0.148 -0.148  0.051 -0.148 -0.173 -0.223 -0.024 -0.173 -0.148  0.026  0.674  0.250  0.375  0.026  0.225  0.474  0.200  0.674  0.699  0.051  0.200 -0.024  0.300  0.499  0.350  0.674  0.026  0.474 -0.099  0.674  0.026 -0.024  0.300 -0.223  0.076  0.026  0.051  0.300  0.026  0.549  0.126  0.325  0.275  0.300  0.175  0.275  0.674 -0.124  0.250  0.300  0.699  0.325  0.350  0.051  0.001 -0.124  0.225  0.250  0.624 
 0.339 -0.085 -0.234 -0.085 -0.085 -0.159 -0.209 -0.159 -0.135 -0.135  0.090  0.040 -0.060  0.015  0.115 -0.110 -0.035 -0.110  0.015 -0.184 -0.209  0.065 -0.259 -0.159  0.140 -0.035 -0.085 -0.060  0.065 -0.035 -0.035 -0.209 -0.259 -0.259  0.015 -0.060 -0.135 -0.135 -0.110 -0.159  0.015 -0.159 -0.159  0.040 -0.135 -0.184 -0.234 -0.035 -0.184 -0.159  0.065  0.663  0.239  0.364  0.015  0.264  0.513  0.164  0.663  0.688  0.040  0.189  0.040  0.264  0.488  0.364  0.663  0.040  0.463 -0.110  0.688  0.040  0.040  0.264 -0.234  0.090  0.040  0.065  0.314  0.040  0.513  0.115  0.364  0.339  0.314  0.189  0.289  0.663 -0.135  0.314  0.289  0.688  0.314  0.389  0.140 -0.010 -0.135  0.214  0.264  0.638 
 0.336 -0.087 -0.237 -0.087 -0.087 -0.162 -0.212 -0.162 -0.137 -0.162  0.062  0.062 -0.062  0.037  0.087 -0.112 -0.037 -0.112  0.012 -0.187 -0.212  0.087 -0.262 -0.187  0.137 -0.062 -0.087 -0.087  0.062 -0.012 -0.012 -0.212 -0.262 -0.262  0.012 -0.062 -0.137 -0.112 -0.112 -0.187  0.037 -0.162 -0.137  0.012 -0.112 -0.162 -0.237 -0.037 -0.187 -0.137  0.062  0.610  0.237  0.361  0.012  0.311  0.511  0.187  0.660  0.685  0.062  0.162  0.037  0.286  0.486  0.361  0.660  0.062  0.461 -0.112  0.685  0.037  0.137  0.262 -0.237  0.062  0.037  0.062  0.336  0.012  0.511  0.112  0.361  0.361  0.311  0.212  0.286  0.660 -0.112  0.336  0.286  0.685  0.311  0.411  0.137 -0.037 -0.137  0.187  0.262  0.635 
 0.307 -0.091 -0.191 -0.066 -0.091 -0.166 -0.141 -0.166 -0.141 -0.166  0.058  0.108 -0.066  0.033  0.108 -0.091 -0.016 -0.116  0.008 -0.191 -0.216  0.108 -0.266 -0.191  0.108 -0.066 -0.116 -0.091  0.008 -0.016 -0.016 -0.216 -0.266 -0.266  0.033 -0.066 -0.166 -0.091 -0.091 -0.191  0.033 -0.166 -0.091  0.008 -0.091 -0.166 -0.241 -0.041 -0.191 -0.141  0.058  0.606  0.233  0.357  0.033  0.307  0.507  0.183  0.606  0.681  0.083  0.133  0.033  0.283  0.482  0.332  0.656  0.083  0.482 -0.066  0.656  0.058  0.133  0.258 -0.216  0.033  0.033  0.083  0.332  0.008  0.482  0.083  0.382  0.357  0.307  0.208  0.307  0.656 -0.066  0.382  0.307  0.681  0.332  0.457  0.108 -0.041 -0.141  0.158  0.258  0.631 
 0.329 -0.070 -0.194 -0.070 -0.070 -0.169 -0.169 -0.169 -0.144 -0.120  0.080  0.105 -0.070  0.055  0.130 -0.095 -0.020 -0.120  0.005 -0.194 -0.219  0.105 -0.269 -0.194  0.105 -0.045 -0.120 -0.095  0.005 -0.020 -0.020 -0.219 -0.269 -0.269  0.030 -0.070 -0.169 -0.095 -0.095 -0.194  0.030 -0.169 -0.095  0.005 -0.095 -0.169 -0.244 -0.045 -0.194 -0.144  0.055  0.628  0.254  0.354  0.030  0.304  0.528  0.179  0.603  0.678  0.080  0.130  0.030  0.304  0.478  0.329  0.628  0.080  0.478 -0.070  0.653  0.080  0.130  0.254 -0.219  0.030  0.030  0.080  0.329  0.030  0.478  0.080  0.379  0.354  0.304  0.254  0.304  0.653 -0.070  0.428  0.304  0.678  0.329  0.453  0.080 -0.020 -0.144  0.130  0.254  0.628 
 0.328 -0.071 -0.195 -0.071 -0.046 -0.145 -0.170 -0.170 -0.145 -0.121  0.079  0.104 -0.145  0.104  0.178 -0.096 -0.021 -0.121  0.004 -0.195 -0.220  0.104 -0.295 -0.220  0.104 -0.046 -0.096 -0.121 -0.021 -0.046 -0.021 -0.220 -0.270 -0.270  0.029 -0.071 -0.220 -0.096 -0.071 -0.195  0.029 -0.170 -0.096 -0.021 -0.071 -0.170 -0.270 -0.096 -0.195 -0.145  0.054  0.627  0.253  0.353  0.029  0.303  0.527  0.203  0.602  0.677  0.079  0.153  0.029  0.303  0.452  0.303  0.627  0.104  0.477 -0.096  0.652  0.079  0.178  0.253 -0.220  0.054  0.029  0.079  0.328  0.029  0.527  0.004  0.403  0.353  0.278  0.353  0.303  0.652 -0.046  0.452  0.303  0.652  0.353  0.452  0.104 -0.021 -0.145  0.129  0.253  0.627 
 0.326 -0.072 -0.172 -0.072 -0.047 -0.147 -0.172 -0.172 -0.147 -0.122  0.077  0.102 -0.147  0.152  0.202 -0.097  0.002 -0.122  0.002 -0.197 -0.222  0.102 -0.272 -0.222  0.077 -0.047 -0.097 -0.122 -0.022 -0.047 -0.022 -0.197 -0.272 -0.272  0.027 -0.072 -0.222 -0.097 -0.072 -0.197  0.027 -0.172 -0.097 -0.047 -0.072 -0.172 -0.272 -0.122 -0.197 -0.147  0.052  0.625  0.252  0.376  0.027  0.301  0.526  0.202  0.600  0.675  0.102  0.152  0.052  0.301  0.451  0.301  0.625  0.102  0.451 -0.097  0.650  0.077  0.202  0.252 -0.222  0.052  0.027  0.077  0.326  0.027  0.526  0.002  0.451  0.351  0.277  0.351  0.301  0.650 -0.047  0.426  0.301  0.650  0.351  0.451  0.127 -0.022 -0.147  0.127  0.252  0.625 
 0.325 -0.074 -0.173 -0.074 -0.024 -0.124 -0.173 -0.173 -0.148 -0.124  0.076  0.101 -0.173  0.150  0.200 -0.099  0.001 -0.124 -0.024 -0.198 -0.223  0.101 -0.273 -0.223  0.076 -0.024 -0.099 -0.148 -0.024 -0.074  0.001 -0.173 -0.298 -0.273  0.026 -0.074 -0.223 -0.099 -0.074 -0.198  0.026 -0.173 -0.099 -0.049 -0.074 -0.173 -0.273 -0.124 -0.198 -0.148  0.076  0.599  0.250  0.350  0.026  0.300  0.549  0.225  0.599  0.674  0.101  0.150  0.076  0.300  0.449  0.300  0.624  0.101  0.425 -0.099  0.649  0.076  0.200  0.250 -0.223  0.051  0.026  0.076  0.350  0.026  0.524 -0.024  0.449  0.350  0.275  0.350  0.300  0.649 -0.049  0.474  0.300  0.649  0.350  0.449  0.126  0.001 -0.148  0.126  0.250  0.624 
 0.325 -0.074 -0.173 -0.074 -0.024 -0.124 -0.173 -0.148 -0.148 -0.099  0.076  0.101 -0.198  0.150  0.200 -0.099  0.026 -0.124 -0.024 -0.198 -0.223  0.101 -0.273 -0.223  0.076 -0.024 -0.124 -0.148 -0.024 -0.074  0.001 -0.173 -0.298 -0.273  0.026 -0.074 -0.223 -0.099 -0.074 -0.198  0.026 -0.198 -0.099 -0.049 -0.049 -0.173 -0.273 -0.124 -0.198 -0.148  0.076  0.599  0.250  0.350  0.026  0.325  0.549  0.225  0.599  0.624  0.101  0.150  0.076  0.300  0.449  0.275  0.624  0.101  0.425 -0.124  0.649  0.076  0.200  0.225 -0.198  0.101  0.026  0.076  0.350  0.026  0.549 -0.024  0.449  0.375  0.275  0.375  0.300  0.649 -0.049  0.524  0.300  0.649  0.350  0.449  0.101 -0.024 -0.173  0.126  0.250  0.624 
 0.324 -0.074 -0.174 -0.074 -0.024 -0.124 -0.174 -0.149 -0.149 -0.099  0.075  0.100 -0.199  0.150  0.175 -0.099  0.025 -0.124 -0.024 -0.199 -0.224  0.100 -0.298 -0.224  0.075 -0.049 -0.124 -0.149 -0.024 -0.074 -0.024 -0.174 -0.298 -0.274  0.025 -0.074 -0.224 -0.099 -0.074 -0.199  0.025 -0.199 -0.099 -0.049 -0.049 -0.149 -0.274 -0.124 -0.199 -0.149  0.075  0.598  0.250  0.324  0.025  0.324  0.549  0.200  0.598  0.623  0.125  0.150  0.075  0.299  0.449  0.275  0.623  0.100  0.424 -0.149  0.648  0.075  0.200  0.200 -0.199  0.100  0.025  0.075  0.374  0.025  0.573 -0.024  0.449  0.399  0.275  0.374  0.299  0.648 -0.049  0.524  0.299  0.648  0.349  0.449  0.100 -0.024 -0.174  0.125  0.250  0.623 
 0.325 -0.073 -0.173 -0.073 -0.023 -0.123 -0.173 -0.123 -0.148 -0.098  0.076  0.101 -0.223  0.151  0.176 -0.098  0.026 -0.123 -0.023 -0.198 -0.223  0.101 -0.297 -0.223  0.076 -0.048 -0.123 -0.148 -0.023 -0.073 -0.023 -0.173 -0.297 -0.273  0.026 -0.073 -0.223 -0.098 -0.073 -0.198  0.026 -0.198 -0.098 -0.048 -0.048 -0.148 -0.273 -0.123 -0.198 -0.148  0.076  0.599  0.251  0.276  0.026  0.325  0.550  0.201  0.599  0.624  0.126  0.151  0.076  0.300  0.450  0.276  0.624  0.126  0.425 -0.148  0.649  0.076  0.201  0.201 -0.198  0.101  0.001  0.076  0.375  0.026  0.574 -0.023  0.425  0.450  0.276  0.375  0.300  0.649 -0.048  0.525  0.276  0.649  0.350  0.450  0.101 -0.023 -0.173  0.126  0.251  0.624 
 0.323 -0.075 -0.175 -0.075 -0.000 -0.125 -0.175 -0.125 -0.150 -0.100  0.074  0.099 -0.225  0.149  0.174 -0.100  0.024 -0.125 -0.025 -0.200 -0.225  0.124 -0.299 -0.225  0.074 -0.025 -0.125 -0.150 -0.025 -0.075 -0.000 -0.175 -0.299 -0.275  0.024 -0.075 -0.225 -0.100 -0.075 -0.200  0.024 -0.200 -0.100 -0.050 -0.050 -0.150 -0.275 -0.150 -0.175 -0.150  0.099  0.597  0.249  0.274  0.024  0.323  0.572  0.224  0.597  0.622  0.124  0.174  0.074  0.298  0.448  0.274  0.597  0.124  0.423 -0.150  0.647  0.074  0.199  0.199 -0.200  0.124 -0.000  0.074  0.373  0.024  0.572 -0.025  0.423  0.473  0.274  0.373  0.298  0.647 -0.050  0.523  0.274  0.647  0.348  0.448  0.099 -0.025 -0.175  0.124  0.249  0.622 
 0.323 -0.075 -0.175 -0.075 -0.000 -0.125 -0.175 -0.150 -0.150 -0.125  0.074  0.099 -0.225  0.149  0.174 -0.100  0.049 -0.125 -0.025 -0.200 -0.225  0.124 -0.299 -0.225  0.074 -0.025 -0.125 -0.150 -0.025 -0.075 -0.000 -0.175 -0.299 -0.275  0.024 -0.075 -0.225 -0.100 -0.075 -0.200  0.024 -0.200 -0.100 -0.050 -0.075 -0.150 -0.275 -0.150 -0.175 -0.150  0.099  0.597  0.249  0.274  0.024  0.323  0.572  0.224  0.597  0.622  0.124  0.174  0.074  0.298  0.448  0.274  0.597  0.124  0.423 -0.125  0.647  0.074  0.199  0.199 -0.200  0.124  0.024  0.074  0.348  0.024  0.572 -0.025  0.423  0.473  0.274  0.348  0.298  0.647 -0.050  0.523  0.298  0.647  0.348  0.448  0.099 -0.025 -0.175  0.124  0.249  0.622 
 0.296 -0.078 -0.177 -0.078  0.022 -0.103 -0.177 -0.152 -0.152 -0.128  0.072  0.097 -0.227  0.146  0.171 -0.103  0.047 -0.128 -0.028 -0.202 -0.227  0.122 -0.302 -0.227  0.072 -0.028 -0.128 -0.152 -0.028 -0.078 -0.003 -0.177 -0.302 -0.252  0.022 -0.078 -0.227 -0.103 -0.078 -0.202  0.022 -0.202 -0.103 -0.053 -0.078 -0.152 -0.277 -0.128 -0.177 -0.152  0.097  0.570  0.246  0.271  0.022  0.321  0.570  0.246  0.595  0.620  0.122  0.196  0.072  0.296  0.445  0.271  0.620  0.146  0.421 -0.128  0.645  0.072  0.196  0.221 -0.202  0.171  0.022  0.072  0.346  0.022  0.570 -0.028  0.421  0.470  0.271  0.346  0.296  0.645 -0.053  0.520  0.296  0.645  0.346  0.445  0.097 -0.003 -0.177  0.122  0.246  0.620 
 0.270 -0.004 -0.129 -0.029 -0.004 -0.104 -0.154 -0.154 -0.079 -0.104  0.020  0.045 -0.179  0.095  0.095 -0.129  0.045 -0.079  0.045 -0.154 -0.179  0.145 -0.229 -0.179  0.070 -0.104 -0.079 -0.129  0.045 -0.079  0.020 -0.179 -0.254 -0.229  0.020 -0.029 -0.179 -0.079 -0.104 -0.154  0.045 -0.154 -0.104 -0.004 -0.079 -0.129 -0.229 -0.129 -0.104 -0.104  0.095  0.544  0.319  0.294  0.020  0.245  0.469  0.220  0.519  0.618  0.070  0.170 -0.029  0.294  0.469  0.270  0.693  0.145  0.494 -0.129  0.544  0.070  0.145  0.245 -0.129  0.120  0.070  0.045  0.319  0.020  0.593 -0.029  0.319  0.444  0.245  0.294  0.294  0.618 -0.054  0.394  0.319  0.643  0.344  0.294  0.070 -0.029 -0.104  0.145  0.319  0.618 
 0.186 -0.013 -0.113 -0.088 -0.013 -0.063 -0.138 -0.113  0.012 -0.088 -0.063  0.037 -0.138  0.087  0.062 -0.038 -0.013  0.012  0.087 -0.113 -0.113  0.112 -0.138 -0.113  0.112 -0.038 -0.038 -0.063  0.087 -0.038  0.012 -0.113 -0.162 -0.138 -0.013  0.012 -0.113 -0.088 -0.013 -0.088  0.012 -0.088 -0.063  0.037 -0.063 -0.088 -0.162 -0.088 -0.138 -0.038  0.137  0.535  0.286  0.261  0.062  0.137  0.386  0.161  0.485  0.635  0.037  0.037 -0.013  0.161  0.460  0.236  0.535  0.087  0.485 -0.038  0.510  0.062  0.087  0.186 -0.113  0.037  0.087 -0.013  0.112  0.012  0.585  0.012  0.211  0.311  0.261  0.087  0.186  0.560 -0.113  0.211  0.311  0.660  0.261  0.186  0.087 -0.013 -0.063  0.112  0.286  0.660 
 0.180  0.006 -0.094 -0.069 -0.019 -0.069 -0.119 -0.094 -0.019 -0.069 -0.044  0.031 -0.119  0.056  0.006 -0.069 -0.019  0.031  0.081 -0.094 -0.119  0.081 -0.119 -0.094  0.056 -0.019 -0.044 -0.019  0.081 -0.044 -0.044 -0.094 -0.143 -0.143  0.006  0.031 -0.119 -0.094 -0.019 -0.094  0.031 -0.069 -0.069  0.056 -0.044 -0.119 -0.143 -0.119 -0.119 -0.019  0.106  0.554  0.255  0.255  0.056  0.131  0.355  0.155  0.454  0.604 -0.019 -0.019 -0.019  0.106  0.454  0.131  0.504  0.056  0.504 -0.019  0.529  0.031  0.106  0.205 -0.094  0.031  0.081 -0.019  0.006  0.031  0.579  0.031  0.155  0.205  0.180  0.031  0.180  0.554 -0.094  0.131  0.280  0.704  0.205  0.106  0.056 -0.019 -0.044  0.131  0.255  0.654 
 0.162  0.012 -0.062 -0.087  0.012 -0.037 -0.112 -0.087 -0.037 -0.037 -0.037 -0.012 -0.112 -0.012 -0.062 -0.037 -0.037  0.062  0.112 -0.062 -0.112  0.012 -0.087 -0.062  0.037 -0.012 -0.062  0.012  0.112 -0.037 -0.037 -0.087 -0.112 -0.112  0.037  0.037 -0.087 -0.087 -0.062 -0.062  0.037 -0.062 -0.037  0.062 -0.087 -0.087 -0.112 -0.087 -0.087 -0.012  0.087  0.536  0.187  0.262  0.037  0.112  0.286  0.162  0.461  0.610 -0.012 -0.037  0.012  0.112  0.486  0.062  0.461  0.037  0.461 -0.012  0.486 -0.012 -0.087  0.162 -0.062 -0.012  0.087 -0.012  0.012  0.037  0.610  0.012  0.012  0.137  0.112  0.012  0.162  0.461 -0.062  0.012  0.237  0.760  0.187  0.087 -0.012 -0.012 -0.037  0.112  0.162  0.635 
 0.098  0.023 -0.077 -0.077  0.023 -0.027 -0.102 -0.077 -0.027 -0.027 -0.027 -0.027 -0.102 -0.002 -0.052 -0.052 -0.027  0.048  0.098 -0.077 -0.102 -0.002 -0.077 -0.052  0.048 -0.002 -0.052  0.023  0.147 -0.027 -0.052 -0.077 -0.102 -0.102  0.048 -0.002 -0.077 -0.077 -0.052 -0.052  0.048 -0.052 -0.027  0.048 -0.102 -0.077 -0.102 -0.077 -0.077 -0.002  0.098  0.521  0.197  0.247  0.023  0.123  0.197  0.172  0.471  0.621 -0.002 -0.052 -0.027  0.098  0.471  0.073  0.471  0.023  0.446 -0.052  0.422 -0.027 -0.077  0.073 -0.052 -0.002  0.098 -0.002  0.023  0.048  0.621  0.023 -0.002  0.098  0.098  0.023  0.123  0.372 -0.052  0.023  0.222  0.770  0.197  0.048 -0.052 -0.002 -0.027  0.123  0.172  0.621 
 0.110  0.035 -0.064 -0.064  0.035 -0.014 -0.089 -0.064 -0.039 -0.014 -0.014 -0.064 -0.089 -0.039 -0.039 -0.039 -0.014  0.035  0.110 -0.064 -0.089  0.010 -0.089 -0.039  0.060  0.010 -0.039  0.035  0.135 -0.014 -0.064 -0.064 -0.089 -0.089  0.060  0.010 -0.064 -0.064 -0.039 -0.039  0.035 -0.039 -0.014  0.010 -0.089 -0.064 -0.089 -0.064 -0.064 -0.014  0.110  0.484  0.185  0.210  0.035  0.135  0.210  0.185  0.434  0.658  0.010 -0.064 -0.014  0.085  0.459  0.085  0.459  0.010  0.409 -0.039  0.309 -0.014 -0.064  0.060 -0.064 -0.039  0.110 -0.014  0.010  0.010  0.633 -0.039 -0.014  0.035  0.085  0.010  0.110  0.334 -0.039 -0.064  0.185  0.783  0.185  0.060 -0.039 -0.014 -0.039  0.060  0.135  0.459 
 0.116  0.041 -0.059 -0.059  0.016 -0.009 -0.084 -0.059 -0.034 -0.009 -0.034 -0.034 -0.084 -0.034 -0.034 -0.034 -0.034  0.041  0.066 -0.059 -0.084  0.016 -0.084 -0.059  0.066  0.016 -0.009  0.041  0.091 -0.009 -0.059 -0.059 -0.084 -0.084  0.066 -0.034 -0.059 -0.059 -0.034 -0.034  0.016 -0.009 -0.009  0.016 -0.084 -0.059 -0.084 -0.059 -0.059 -0.009  0.091  0.415  0.190  0.165  0.041  0.116  0.215  0.141  0.365  0.738  0.016 -0.084 -0.009  0.091  0.439  0.116  0.415 -0.034  0.415 -0.034  0.240 -0.034 -0.059  0.041 -0.059 -0.059  0.091 -0.059  0.016  0.016  0.664 -0.009 -0.034  0.041  0.091  0.016  0.116  0.340 -0.034 -0.059  0.190  0.763  0.141  0.041 -0.034  0.016 -0.059  0.041  0.141  0.439 
 0.102  0.052 -0.047 -0.047 -0.022  0.002 -0.072 -0.047 -0.022  0.002 -0.022 -0.022 -0.072 -0.072 -0.072 -0.047 -0.022  0.052  0.077 -0.047 -0.072  0.002 -0.072 -0.072  0.077  0.027  0.002  0.052  0.077 -0.022 -0.047 -0.047 -0.072 -0.072  0.052 -0.022 -0.047 -0.047 -0.022 -0.022  0.027  0.002  0.027  0.027 -0.072 -0.047 -0.072 -0.047 -0.047  0.002  0.052  0.301  0.177  0.152  0.027  0.127  0.127  0.127  0.252  0.800 -0.022 -0.072  0.002  0.052  0.351  0.102  0.326 -0.022  0.401 -0.022  0.102 -0.022 -0.047  0.052 -0.047 -0.047  0.077 -0.072  0.027  0.002  0.675  0.002 -0.047  0.052  0.102  0.002  0.127  0.301 -0.022 -0.047  0.177  0.800  0.127  0.052 -0.022  0.002 -0.047  0.027  0.127  0.401 
 0.111  0.086 -0.064 -0.039 -0.039  0.036 -0.064  0.011 -0.039  0.011  0.011 -0.014 -0.064 -0.064 -0.064 -0.039 -0.039  0.036  0.061 -0.014 -0.064  0.036 -0.064 -0.064  0.086  0.011  0.011  0.086  0.086 -0.014 -0.039 -0.039 -0.064 -0.064  0.061  0.011 -0.039 -0.039 -0.014  0.011  0.011  0.011  0.036  0.036 -0.064 -0.064 -0.039 -0.039 -0.039 -0.014  0.036  0.185  0.111  0.111  0.036  0.036  0.086  0.061  0.210  0.833 -0.014 -0.064  0.011 -0.039  0.160  0.061  0.285 -0.039  0.410 -0.014  0.061 -0.014 -0.039  0.061 -0.039 -0.014  0.086 -0.064  0.061  0.011  0.758  0.011 -0.039  0.036  0.111 -0.039  0.136  0.285 -0.014 -0.039  0.160  0.833  0.111  0.061 -0.014  0.011 -0.039  0.011  0.036  0.235 
 0.092  0.042 -0.057 -0.032 -0.032  0.042 -0.057  0.017 -0.057  0.017 -0.032 -0.007 -0.032 -0.057 -0.057 -0.032 -0.032  0.042  0.042 -0.007 -0.057  0.042 -0.032 -0.032  0.067 -0.032 -0.007  0.092  0.067 -0.007 -0.032 -0.032 -0.057 -0.057  0.042 -0.007 -0.057 -0.032 -0.007 -0.007  0.017  0.017  0.017  0.017 -0.057 -0.057 -0.032 -0.032 -0.032 -0.007  0.017  0.092  0.042  0.092  0.017  0.017  0.067  0.017  0.192  0.889 -0.032 -0.057  0.017 -0.032  0.067  0.042  0.142 -0.032  0.366 -0.007  0.017 -0.007 -0.032  0.092 -0.032 -0.007  0.067 -0.057  0.067 -0.007  0.765  0.017 -0.032  0.017  0.092 -0.032  0.117  0.217 -0.007 -0.032  0.142  0.914  0.092  0.042 -0.007 -0.007 -0.007  0.017 -0.007  0.167 
 0.094  0.044 -0.055 -0.030 -0.030  0.044 -0.055  0.019 -0.055  0.019 -0.030 -0.005 -0.030 -0.055 -0.055 -0.030 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.030 -0.055 -0.055  0.044 -0.005 -0.055 -0.030 -0.005  0.019  0.019  0.019 -0.005  0.019 -0.055 -0.055 -0.030 -0.030 -0.030 -0.005  0.019  0.019  0.044  0.094  0.019  0.019  0.069  0.019  0.144  0.916 -0.030 -0.055 -0.005 -0.030  0.044  0.019  0.119 -0.030  0.293 -0.005  0.019 -0.005 -0.030  0.094 -0.030  0.019  0.044 -0.030  0.044 -0.005  0.792  0.019 -0.030  0.019  0.069 -0.055  0.119  0.219 -0.030 -0.030  0.119  0.916  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.144 
 0.074  0.024 -0.051 -0.026 -0.026  0.024 -0.051 -0.001 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.049 -0.001 -0.001 -0.051  0.049 -0.026 -0.026  0.049 -0.026 -0.001  0.074  0.074 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.051 -0.026 -0.001  0.024 -0.001  0.024 -0.026 -0.001 -0.051 -0.051 -0.051 -0.026 -0.026 -0.026  0.024 -0.026  0.049  0.099  0.024 -0.026  0.074  0.024  0.148  0.971 -0.026 -0.051 -0.001 -0.026  0.024  0.024 -0.001 -0.026  0.074 -0.001 -0.001 -0.001 -0.026  0.074 -0.051  0.024 -0.001 -0.026  0.024  0.024  0.771  0.024 -0.026  0.024  0.024 -0.051  0.099  0.049 -0.051 -0.026  0.099  0.946  0.099  0.049 -0.001 -0.001 -0.001  0.024 -0.001  0.099 
 0.073  0.023 -0.051 -0.026 -0.026  0.023 -0.051 -0.001 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026 -0.001 -0.051 -0.026 -0.051 -0.026 -0.026 -0.026  0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.073 -0.001 -0.001 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.023  0.023  0.771  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.048 -0.001 -0.001 -0.001  0.023 -0.001  0.098 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.022 -0.002  0.022 -0.027  0.022 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027  0.022 -0.027  0.047  0.097  0.022 -0.027  0.072  0.022  0.147  0.969 -0.027 -0.027 -0.002 -0.027  0.022  0.022 -0.002 -0.027  0.072 -0.002 -0.002 -0.002 -0.027  0.072 -0.052  0.022 -0.002 -0.027  0.047  0.022  0.820  0.022 -0.027  0.047  0.022 -0.052  0.097  0.047 -0.052 -0.027  0.097  0.969  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004 -0.004  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054 -0.004  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.123  0.048 -0.052 -0.052 -0.052  0.023 -0.077  0.023 -0.077 -0.027 -0.052 -0.002 -0.027 -0.002 -0.052 -0.077 -0.027  0.023  0.023 -0.027 -0.077  0.023 -0.027 -0.002  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.077  0.048 -0.077 -0.077 -0.027  0.023 -0.052 -0.027 -0.002 -0.002 -0.027  0.023 -0.052  0.048 -0.027 -0.027 -0.027 -0.027 -0.052 -0.002 -0.002 -0.002  0.048  0.172 -0.002 -0.002  0.098 -0.002  0.123  0.945 -0.002 -0.027 -0.002 -0.052  0.048  0.073  0.023 -0.027  0.123 -0.002  0.073 -0.027 -0.002  0.222 -0.052 -0.002  0.048  0.048  0.048  0.048  0.945  0.023 -0.027  0.048  0.023 -0.077  0.197  0.048 -0.052 -0.002  0.197  0.945  0.098  0.073 -0.027 -0.027 -0.027  0.023  0.023  0.147 
 0.260  0.061 -0.114 -0.064  0.011 -0.014 -0.089 -0.014 -0.114 -0.064 -0.014 -0.014 -0.039 -0.039 -0.114 -0.114 -0.014  0.061  0.136 -0.064 -0.114  0.011 -0.064  0.011  0.086 -0.039 -0.014  0.011  0.136 -0.014 -0.114 -0.014 -0.139 -0.139 -0.014  0.011 -0.064 -0.064 -0.064 -0.039 -0.014  0.011 -0.039  0.011 -0.089 -0.039 -0.089  0.061 -0.089 -0.039  0.061  0.061  0.111  0.285 -0.014  0.011  0.285  0.036  0.385  0.883  0.036 -0.014  0.111 -0.064  0.185  0.260  0.136 -0.039  0.260 -0.039  0.285 -0.089  0.011  0.285 -0.089 -0.014  0.061 -0.014  0.136  0.036  0.883  0.011  0.086  0.160  0.011 -0.014  0.235  0.210 -0.114 -0.014  0.484  0.883  0.285  0.086 -0.039  0.011 -0.039  0.086  0.086  0.385 
 0.262  0.012 -0.162 -0.062 -0.012 -0.037 -0.087 -0.062 -0.137 -0.112 -0.012 -0.062  0.012 -0.037 -0.137 -0.112 -0.037  0.012  0.112 -0.112 -0.162 -0.012 -0.062 -0.037  0.137 -0.062  0.012 -0.012  0.087 -0.062 -0.062 -0.062 -0.137 -0.187 -0.037  0.012 -0.062 -0.112 -0.087 -0.037 -0.037 -0.062 -0.087  0.062 -0.112 -0.062 -0.112  0.087 -0.137 -0.087  0.087  0.137  0.212  0.286 -0.037  0.037  0.311  0.037  0.486  0.835  0.062 -0.037  0.112 -0.012  0.286  0.511  0.286 -0.012  0.411 -0.087  0.411 -0.037  0.037  0.361 -0.112  0.012  0.037  0.037  0.112  0.062  0.835  0.062  0.112  0.162 -0.012 -0.012  0.361  0.386 -0.137 -0.012  0.561  0.835  0.386  0.112 -0.087  0.062 -0.087  0.112  0.137  0.461 
 0.350 -0.024 -0.173 -0.099  0.001 -0.074 -0.148 -0.074 -0.173 -0.173  0.001 -0.024  0.051 -0.024 -0.074 -0.124 -0.049 -0.024  0.051 -0.124 -0.198  0.001 -0.124 -0.099  0.150 -0.074 -0.049 -0.024  0.150 -0.099 -0.099 -0.099 -0.198 -0.248 -0.024  0.051 -0.024 -0.124 -0.124 -0.049 -0.024 -0.099 -0.099  0.101 -0.148 -0.099 -0.148  0.076 -0.148 -0.124  0.101  0.275  0.250  0.350  0.001  0.101  0.400  0.126  0.649  0.773  0.101 -0.024  0.200  0.051  0.350  0.524  0.425  0.026  0.549 -0.074  0.624 -0.049  0.001  0.449 -0.173  0.026  0.026  0.026  0.150  0.026  0.773  0.051  0.200  0.250  0.001  0.026  0.474  0.524 -0.198  0.076  0.524  0.773  0.449  0.126 -0.024  0.101 -0.124  0.126  0.200  0.574 
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 0.095  0.045 -0.079 -0.054 -0.029 -0.004 -0.079 -0.054 -0.029 -0.004 -0.029 -0.029 -0.054 -0.079 -0.054 -0.029 -0.029  0.045  0.070 -0.054 -0.079 -0.004 -0.079 -0.054  0.070  0.020 -0.004  0.045  0.070 -0.004 -0.054 -0.054 -0.079 -0.079  0.070 -0.004 -0.054 -0.054 -0.029 -0.004  0.020 -0.004 -0.004  0.020 -0.054 -0.029 -0.079 -0.029 -0.054  0.020  0.070  0.245  0.270  0.220  0.045  0.095  0.095  0.145  0.270  0.892  0.020 -0.079 -0.004  0.045  0.319  0.220  0.369 -0.054  0.394 -0.029  0.195 -0.029 -0.054  0.045 -0.054  0.045  0.070 -0.029  0.045 -0.004  0.618 -0.004 -0.029  0.045  0.095 -0.029  0.120  0.319 -0.029 -0.054  0.245  0.768  0.120  0.045 -0.029 -0.004 -0.004  0.045  0.095  0.469 
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 0.111  0.061 -0.064 -0.039 -0.014  0.036 -0.064 -0.014 -0.039  0.011 -0.014 -0.014 -0.039 -0.064 -0.039 -0.039 -0.014  0.061  0.036 -0.014 -0.064  0.061 -0.064 -0.064  0.036  0.011 -0.014  0.086  0.086 -0.014 -0.039 -0.039 -0.064 -0.064  0.036 -0.014 -0.064 -0.039 -0.014  0.036  0.036  0.011 -0.014  0.011 -0.064 -0.064 -0.064 -0.014 -0.039  0.036  0.011  0.160  0.086  0.086  0.011  0.061  0.061  0.061  0.160  0.958 -0.014 -0.064  0.011 -0.014  0.185  0.086  0.235 -0.039  0.385 -0.014  0.011 -0.014 -0.039  0.086 -0.039  0.011  0.061 -0.039  0.011 -0.014  0.709 -0.014 -0.039  0.036  0.086 -0.064  0.111  0.235 -0.014 -0.039  0.210  0.883  0.136  0.061 -0.014 -0.014 -0.014  0.011  0.011  0.285 
 0.093  0.018 -0.057 -0.032 -0.032  0.018 -0.057 -0.007 -0.057  0.018 -0.032 -0.007 -0.032 -0.057 -0.032 -0.032 -0.032  0.043  0.018 -0.007 -0.057  0.068 -0.032 -0.032  0.043 -0.007 -0.007  0.093  0.068 -0.007 -0.057 -0.032 -0.057 -0.057 -0.007 -0.007 -0.057 -0.032 -0.007  0.018 -0.007  0.018 -0.007 -0.007 -0.057 -0.057 -0.057 -0.007 -0.032 -0.007  0.018  0.043  0.043  0.093  0.018  0.018  0.068  0.018  0.142  0.965 -0.032 -0.057 -0.007 -0.032  0.118  0.068  0.093 -0.032  0.292  0.018  0.018 -0.007 -0.032  0.093 -0.032  0.018  0.068 -0.032  0.018  0.018  0.765  0.018 -0.032  0.018  0.068 -0.057  0.118  0.142 -0.032 -0.032  0.118  0.940  0.118  0.068 -0.007 -0.007 -0.007  0.018  0.018  0.142 
 0.095  0.045 -0.054 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.029 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.054 -0.029 -0.004  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.054 -0.029 -0.029 -0.029 -0.004  0.020  0.020  0.045  0.095  0.020  0.020  0.070  0.020  0.145  0.967 -0.029 -0.054 -0.004 -0.029  0.020  0.020  0.045 -0.029  0.145  0.020 -0.004 -0.004 -0.029  0.095 -0.054  0.020  0.070 -0.029  0.045  0.020  0.843  0.020 -0.029  0.020  0.070 -0.054  0.095  0.095 -0.054 -0.004  0.095  0.942  0.120  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.004 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.021  0.021 -0.004  0.021 -0.029  0.021 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004 -0.029  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054  0.021  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
 0.070  0.045 -0.055 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005 -0.005  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
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 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
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 0.269 -0.030 -0.180 -0.030 -0.030 -0.105 -0.130 -0.130 -0.055 -0.105 -0.105  0.019 -0.180  0.069  0.169 -0.055 -0.030 -0.080  0.044 -0.205 -0.155  0.069 -0.230 -0.205  0.119 -0.080 -0.030 -0.030  0.119 -0.105  0.019 -0.180 -0.230 -0.155  0.169 -0.005 -0.130 -0.130 -0.030 -0.180 -0.005 -0.105 -0.180  0.094 -0.155 -0.055 -0.105 -0.080 -0.130 -0.105  0.194  0.493  0.169  0.194  0.044  0.219  0.443  0.368  0.543  0.642  0.119  0.293  0.044  0.069  0.393  0.493  0.568  0.169  0.493 -0.055  0.543  0.019  0.144  0.219 -0.130  0.293  0.019  0.119  0.493 -0.030  0.518  0.044  0.393  0.443  0.219  0.194  0.293  0.617 -0.105  0.343  0.343  0.592  0.318  0.194  0.169  0.069 -0.105  0.144  0.194  0.592 
 0.216 -0.008 -0.108 -0.033 -0.033 -0.033 -0.133 -0.133  0.017 -0.108 -0.058 -0.008 -0.133 -0.008  0.017 -0.058 -0.058 -0.033  0.042 -0.108 -0.133  0.042 -0.157 -0.108  0.117 -0.058  0.017 -0.008  0.092 -0.033 -0.008 -0.133 -0.157 -0.133  0.092  0.017 -0.058 -0.083 -0.058 -0.108 -0.033 -0.033 -0.083  0.067 -0.108 -0.083 -0.157 -0.033 -0.083 -0.058  0.166  0.540  0.266  0.117  0.092  0.092  0.366  0.216  0.540  0.690  0.092  0.117  0.017  0.166  0.416  0.490  0.515  0.067  0.440 -0.033  0.490 -0.033 -0.008  0.117 -0.083  0.241  0.017 -0.033  0.341  0.042  0.540 -0.008  0.216  0.391  0.092  0.117  0.216  0.565 -0.108  0.216  0.341  0.640  0.266  0.117  0.092  0.042 -0.083  0.067  0.166  0.565 
 0.211  0.012 -0.088 -0.013 -0.038 -0.013 -0.138 -0.088  0.012 -0.088 -0.038  0.012 -0.138  0.012 -0.063 -0.038 -0.038 -0.013  0.037 -0.088 -0.138  0.037 -0.138 -0.113  0.112 -0.038  0.037  0.012  0.087 -0.013  0.012 -0.113 -0.138 -0.113  0.112  0.037 -0.038 -0.088 -0.063 -0.088 -0.013 -0.013 -0.063  0.037 -0.113 -0.063 -0.138 -0.013 -0.088 -0.038  0.186  0.510  0.261  0.137  0.087  0.112  0.261  0.211  0.560  0.710  0.062  0.037  0.037  0.137  0.435  0.485  0.510  0.037  0.411 -0.038  0.510 -0.063 -0.063  0.037 -0.088  0.186  0.012 -0.038  0.286  0.062  0.560 -0.013  0.112  0.361  0.062  0.062  0.161  0.510 -0.088  0.186  0.286  0.610  0.087  0.062  0.112  0.062 -0.063  0.062  0.186  0.535 
 0.140  0.015 -0.060 -0.060 -0.010 -0.010 -0.110 -0.060 -0.035 -0.060 -0.035 -0.035 -0.110 -0.010 -0.060 -0.010 -0.010  0.015  0.065 -0.060 -0.110  0.040 -0.110 -0.085  0.065 -0.010  0.065  0.040  0.115  0.015 -0.035 -0.085 -0.110 -0.110  0.115  0.015 -0.035 -0.085 -0.085 -0.085 -0.035 -0.035 -0.035  0.015 -0.085 -0.060 -0.110 -0.035 -0.085 -0.010  0.189  0.463  0.264  0.164  0.040  0.090  0.264  0.140  0.563  0.712  0.040 -0.010  0.040  0.115  0.414  0.438  0.488  0.015  0.414 -0.035  0.438 -0.060 -0.085 -0.010 -0.085  0.065  0.015 -0.085  0.065  0.040  0.588 -0.010 -0.010  0.189  0.065  0.015  0.164  0.488 -0.060  0.065  0.264  0.588  0.115  0.015  0.065  0.015 -0.035  0.015  0.164  0.513 
 0.144  0.020 -0.080 -0.055 -0.005 -0.005 -0.105 -0.030 -0.030 -0.055 -0.030 -0.030 -0.105 -0.055 -0.080 -0.030 -0.005  0.045  0.070 -0.055 -0.105  0.070 -0.105 -0.080  0.070 -0.005  0.045  0.045  0.070  0.045 -0.030 -0.080 -0.105 -0.105  0.120  0.020 -0.080 -0.105 -0.055 -0.080 -0.005 -0.030 -0.030  0.020 -0.080 -0.055 -0.105 -0.030 -0.080 -0.005  0.095  0.419  0.269  0.144  0.020  0.095  0.269  0.144  0.593  0.717  0.045 -0.005  0.020  0.095  0.344  0.369  0.493 -0.030  0.419 -0.030  0.369 -0.055 -0.080 -0.005 -0.080  0.020  0.045 -0.080  0.020  0.045  0.618 -0.005 -0.005  0.144  0.070  0.020  0.144  0.493 -0.055  0.020  0.269  0.618  0.095  0.020  0.045 -0.005 -0.030 -0.005  0.144  0.493 
 0.110  0.035 -0.065 -0.065  0.010  0.010 -0.090 -0.040 -0.040 -0.015 -0.040 -0.040 -0.090 -0.065 -0.090 -0.040 -0.015  0.035  0.110 -0.065 -0.090  0.060 -0.090 -0.065  0.085  0.010  0.010  0.035  0.060  0.035 -0.015 -0.065 -0.090 -0.090  0.035 -0.015 -0.065 -0.090 -0.040 -0.040  0.010 -0.015 -0.015 -0.015 -0.065 -0.065 -0.090 -0.065 -0.065  0.010  0.085  0.334  0.284  0.159  0.035  0.085  0.234  0.135  0.608  0.757  0.010  0.010 -0.015  0.085  0.359  0.209  0.458 -0.040  0.409 -0.015  0.184 -0.040 -0.065  0.010 -0.065 -0.040  0.060 -0.090  0.010  0.010  0.658  0.010 -0.015  0.085  0.085  0.010  0.110  0.458 -0.040 -0.040  0.184  0.683  0.110  0.035 -0.015 -0.015 -0.040  0.010  0.135  0.409 
 0.116  0.041 -0.083 -0.058 -0.008  0.016 -0.083 -0.033 -0.058 -0.008 -0.033 -0.033 -0.083 -0.058 -0.083 -0.058 -0.033  0.041  0.041 -0.058 -0.083  0.066 -0.083 -0.083  0.091 -0.008 -0.008  0.041  0.066  0.041 -0.008 -0.058 -0.083 -0.083  0.041 -0.008 -0.058 -0.058 -0.033 -0.033  0.016 -0.008 -0.008 -0.008 -0.058 -0.058 -0.083 -0.058 -0.058 -0.008  0.091  0.241  0.241  0.141  0.041  0.091  0.166  0.091  0.614  0.789  0.016 -0.008 -0.008  0.066  0.315  0.116  0.415 -0.033  0.415 -0.033  0.091 -0.033 -0.058  0.041 -0.058 -0.033  0.066 -0.083  0.016  0.016  0.664  0.016 -0.033  0.091  0.091 -0.058  0.116  0.465 -0.033 -0.033  0.166  0.714  0.116  0.016 -0.033 -0.008 -0.058 -0.033  0.091  0.365 
 0.098  0.023 -0.077 -0.052 -0.027  0.023 -0.077 -0.027 -0.052 -0.002 -0.052 -0.027 -0.077 -0.052 -0.077 -0.052 -0.027  0.048  0.023 -0.052 -0.077  0.073 -0.077 -0.077  0.073 -0.027 -0.002  0.048  0.073 -0.027 -0.052 -0.052 -0.077 -0.077  0.048  0.023 -0.052 -0.052 -0.027 -0.027  0.023 -0.002 -0.027 -0.002 -0.077 -0.052 -0.077 -0.052 -0.052 -0.002  0.098  0.197  0.197  0.147  0.023  0.123  0.172  0.073  0.546  0.820 -0.002 -0.052 -0.002  0.023  0.272  0.073  0.422 -0.027  0.397 -0.027  0.048 -0.027 -0.052  0.048 -0.052 -0.027  0.048 -0.077 -0.002  0.023  0.671 -0.002 -0.052  0.048  0.098 -0.077  0.123  0.347 -0.027 -0.052  0.147  0.795  0.123  0.048 -0.027 -0.002 -0.052 -0.002  0.073  0.372 
 0.104  0.029 -0.071 -0.046 -0.021  0.029 -0.071 -0.021 -0.046  0.004 -0.046 -0.021 -0.071 -0.071 -0.071 -0.046 -0.046  0.054  0.029 -0.046 -0.071  0.079 -0.071 -0.071  0.054 -0.021  0.004  0.079  0.079 -0.021 -0.046 -0.046 -0.071 -0.071  0.054  0.029 -0.046 -0.046 -0.021  0.004  0.029  0.004 -0.021  0.004 -0.071 -0.046 -0.071 -0.046 -0.046  0.004  0.104  0.129  0.203  0.153  0.004  0.104  0.129  0.054  0.427  0.826 -0.021 -0.046  0.004  0.029  0.278  0.054  0.328 -0.021  0.378 -0.046  0.029 -0.021 -0.046  0.079 -0.046 -0.021  0.029 -0.071  0.004  0.004  0.702  0.004 -0.046  0.054  0.079 -0.071  0.104  0.328 -0.021 -0.046  0.129  0.826  0.129  0.054 -0.021  0.004 -0.046  0.004  0.079  0.328 
 0.113  0.013 -0.061 -0.036 -0.011  0.038 -0.061 -0.011 -0.061  0.013 -0.036 -0.011 -0.036 -0.061 -0.061 -0.036 -0.036  0.038  0.038 -0.036 -0.061  0.063 -0.061 -0.061  0.038 -0.011  0.013  0.088  0.088 -0.011 -0.036 -0.036 -0.061 -0.061  0.063  0.013 -0.061 -0.036 -0.011  0.013  0.013  0.013 -0.036 -0.011 -0.061 -0.036 -0.061 -0.011 -0.036 -0.011  0.038  0.088  0.113  0.113  0.013  0.013  0.113  0.038  0.263  0.910 -0.011 -0.036  0.013 -0.036  0.188  0.063  0.263 -0.036  0.312 -0.036  0.038 -0.011 -0.036  0.088 -0.036  0.013  0.038 -0.036  0.013  0.013  0.736  0.013 -0.036  0.013  0.063 -0.061  0.113  0.238 -0.011 -0.036  0.113  0.860  0.138  0.063 -0.011  0.013 -0.011  0.013  0.038  0.188 
 0.091  0.016 -0.058 -0.033 -0.033  0.041 -0.058 -0.008 -0.058  0.016 -0.033 -0.008 -0.033 -0.058 -0.033 -0.033 -0.033  0.041  0.016 -0.033 -0.058  0.066 -0.033 -0.033  0.041 -0.033  0.016  0.066  0.066 -0.033 -0.033 -0.033 -0.058 -0.058  0.066 -0.008 -0.058 -0.033 -0.008  0.016  0.016  0.016 -0.008 -0.008 -0.058 -0.033 -0.058 -0.008 -0.033 -0.008  0.041  0.066  0.116  0.116  0.016  0.016  0.091  0.041  0.241  0.938 -0.033 -0.058  0.016 -0.033  0.066  0.016  0.166 -0.033  0.266 -0.008  0.016 -0.008 -0.033  0.091 -0.033  0.016  0.041 -0.033  0.016  0.016  0.739  0.016 -0.033  0.016  0.066 -0.058  0.116  0.241 -0.033 -0.033  0.116  0.913  0.141  0.041 -0.008  0.016 -0.008  0.016  0.016  0.116 
 0.073  0.023 -0.051 -0.026 -0.026  0.023 -0.051 -0.001 -0.051  0.023 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.073 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.051 -0.026 -0.001  0.023 -0.001  0.023 -0.001 -0.001 -0.051 -0.051 -0.051 -0.001 -0.026 -0.026  0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.051 -0.001 -0.026  0.048  0.023  0.023 -0.026  0.123 -0.001  0.023 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.023  0.023  0.746  0.023 -0.026  0.023  0.023 -0.051  0.098  0.073 -0.051 -0.026  0.098  0.945  0.098  0.048 -0.001 -0.001 -0.001  0.023 -0.001  0.098 
 0.074  0.024 -0.051 -0.026 -0.026  0.024 -0.051 -0.001 -0.051  0.024 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.049 -0.001 -0.001 -0.051  0.074 -0.026 -0.026  0.049 -0.026 -0.001  0.074  0.074 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.051 -0.026 -0.001  0.024 -0.001  0.024 -0.001 -0.001 -0.051 -0.051 -0.051 -0.001 -0.026 -0.026  0.024 -0.026  0.049  0.099  0.024 -0.026  0.074  0.024  0.148  0.971 -0.026 -0.051 -0.001 -0.026  0.049  0.024  0.024 -0.026  0.124 -0.001  0.024 -0.001 -0.026  0.074 -0.051  0.024 -0.001 -0.026  0.024  0.024  0.721  0.024 -0.026  0.024  0.024 -0.051  0.099  0.074 -0.051 -0.026  0.099  0.946  0.099  0.024 -0.001 -0.001 -0.001  0.024 -0.026  0.099 
 0.073  0.048 -0.051 -0.026 -0.026  0.023 -0.051  0.023 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026  0.023 -0.051 -0.026 -0.026 -0.026 -0.026 -0.026  0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.073 -0.001 -0.001 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.048  0.023  0.771  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.023 -0.001 -0.001 -0.001  0.023 -0.026  0.098 
 0.073  0.048 -0.052 -0.027 -0.027  0.023 -0.052  0.023 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.023 -0.002  0.023 -0.027  0.023 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027  0.023 -0.027  0.048  0.098  0.023 -0.027  0.073  0.023  0.147  0.970 -0.027 -0.027 -0.002 -0.027  0.023  0.023 -0.002 -0.027  0.073 -0.002 -0.002 -0.002 -0.027  0.073 -0.052  0.023 -0.002 -0.027  0.048  0.023  0.795  0.023 -0.027  0.048  0.023 -0.052  0.098  0.048 -0.052 -0.027  0.098  0.970  0.098  0.023 -0.002 -0.002 -0.002  0.023 -0.027  0.098 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028  0.022 -0.028  0.047  0.097  0.022 -0.028  0.072  0.022  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.844  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.003  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004 -0.004  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054 -0.004  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
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-0.012  0.286 -0.037 -0.062  0.162  0.137  0.012  0.187  0.112 -0.087  0.137 -0.062  0.062 -0.012  0.311 -0.012 -0.037 -0.062  0.237  0.137 -0.087  0.062 -0.087  0.137  0.062  0.386  0.112 -0.062  0.137  0.062  0.087  0.012 -0.137  0.710  0.012 -0.037  0.112  0.012  0.112  0.062  0.660  0.461  0.311  0.311 -0.087  0.610  0.262  0.262 -0.162  0.685 -0.237  0.162  0.585 -0.187  0.012  0.162 -0.137  0.012 -0.187 -0.112 -0.087  0.162 -0.062  0.262  0.461 -0.037  0.012 -0.012  0.187  0.037 -0.187  0.062 -0.112  0.037  0.262 -0.012  0.262  0.037  0.062  0.137 -0.137 -0.187 -0.112 -0.137  0.162  0.087  0.112  0.162 -0.112 -0.187 -0.087 -0.062  0.286 -0.062  0.162  0.087  0.187  0.187 -0.162 -0.012 
 0.003  0.302  0.003 -0.022  0.227  0.128  0.028  0.227  0.128 -0.097  0.252 -0.047  0.028 -0.022  0.377  0.028  0.003  0.028  0.252  0.227 -0.097  0.053 -0.072  0.252  0.028  0.451  0.177 -0.047  0.152  0.128  0.053  0.003 -0.097  0.676  0.003  0.003  0.152  0.028  0.128  0.103  0.601  0.451  0.327  0.377 -0.097  0.626  0.277  0.302 -0.072  0.651 -0.196  0.252  0.601 -0.196  0.053  0.202 -0.171  0.028 -0.221 -0.146 -0.097  0.128 -0.072  0.302  0.451  0.028  0.003  0.028  0.152  0.003 -0.246  0.103 -0.122  0.152  0.302 -0.022  0.327  0.053  0.028  0.078 -0.171 -0.221 -0.146 -0.196  0.177  0.103  0.078  0.177 -0.122 -0.246 -0.047 -0.097  0.327 -0.047  0.128  0.078  0.152  0.177 -0.171 -0.022 
 0.065  0.289  0.015 -0.010  0.264  0.090  0.040  0.239  0.115 -0.110  0.364 -0.035  0.015  0.015  0.339  0.065  0.015  0.015  0.239  0.339 -0.110  0.090 -0.085  0.289  0.015  0.414  0.214 -0.060  0.164  0.264  0.040 -0.010 -0.110  0.638  0.015  0.015  0.164  0.065  0.115  0.164  0.513  0.438  0.314  0.438 -0.135  0.638  0.264  0.339 -0.085  0.638 -0.159  0.264  0.588 -0.209  0.065  0.214 -0.184 -0.035 -0.209 -0.159 -0.060  0.115 -0.085  0.339  0.438  0.065 -0.010 -0.010  0.140  0.015 -0.234  0.090 -0.060  0.164  0.289  0.015  0.339  0.090  0.015  0.065 -0.184 -0.234 -0.135 -0.209  0.164  0.189  0.065  0.164 -0.135 -0.259 -0.060 -0.110  0.339 -0.060  0.065  0.065  0.140  0.164 -0.159 -0.035 
 0.147  0.272  0.022  0.072  0.272  0.147  0.047  0.222  0.147 -0.127  0.471 -0.027  0.047 -0.052  0.371  0.072  0.072  0.022  0.247  0.471 -0.077  0.122 -0.052  0.346  0.022  0.446  0.296 -0.052  0.172  0.321  0.072 -0.002 -0.152  0.546  0.072  0.022  0.197  0.022  0.072  0.247  0.471  0.421  0.321  0.446 -0.177  0.546  0.247  0.371 -0.002  0.595 -0.152  0.222  0.521 -0.252  0.072  0.197 -0.177 -0.077 -0.227 -0.152 -0.052  0.147 -0.077  0.346  0.421  0.172 -0.002 -0.052  0.097  0.022 -0.252  0.097 -0.027  0.222  0.247 -0.002  0.396  0.072  0.022  0.022 -0.202 -0.252 -0.102 -0.227  0.172  0.296  0.047  0.147 -0.102 -0.252 -0.052 -0.127  0.346 -0.077  0.022  0.147  0.172  0.147 -0.177 -0.077 
 0.185  0.260 -0.014  0.085  0.284  0.185  0.085  0.235  0.185 -0.064  0.534  0.010  0.060 -0.064  0.359  0.110  0.060  0.035  0.235  0.484 -0.114  0.110 -0.039  0.359 -0.014  0.434  0.284  0.035  0.210  0.359  0.160 -0.014 -0.164  0.509  0.060  0.010  0.284  0.010  0.010  0.235  0.384  0.409  0.359  0.434 -0.164  0.509  0.235  0.384  0.085  0.583 -0.114  0.185  0.509 -0.264  0.060  0.135 -0.164 -0.139 -0.239 -0.164 -0.064  0.185 -0.039  0.334  0.409  0.235 -0.014 -0.114  0.085  0.010 -0.264  0.110  0.035  0.235  0.260 -0.039  0.459  0.060  0.035  0.035 -0.239 -0.239 -0.089 -0.214  0.160  0.284  0.010  0.135 -0.089 -0.239 -0.064 -0.139  0.309 -0.089  0.035  0.210  0.160  0.135 -0.164 -0.089 
 0.196  0.246 -0.028  0.097  0.321  0.246  0.072  0.271  0.146 -0.028  0.620  0.047  0.122 -0.078  0.396  0.122  0.097  0.047  0.246  0.520 -0.128  0.122 -0.003  0.346 -0.028  0.371  0.346  0.122  0.196  0.396  0.171 -0.028 -0.152  0.470  0.022  0.146  0.321  0.022 -0.003  0.246  0.296  0.421  0.296  0.495 -0.177  0.495  0.221  0.445  0.171  0.570 -0.078  0.171  0.470 -0.252  0.146  0.122 -0.177 -0.128 -0.277 -0.177 -0.028  0.146 -0.028  0.346  0.371  0.221 -0.028 -0.152  0.097  0.022 -0.277  0.171  0.022  0.246  0.271 -0.028  0.495  0.047  0.022  0.047 -0.277 -0.227 -0.103 -0.227  0.171  0.321 -0.003  0.097 -0.103 -0.227 -0.078 -0.152  0.296 -0.128  0.047  0.246  0.146  0.122 -0.177 -0.103 
 0.195  0.245 -0.004  0.095  0.419  0.245  0.045  0.294  0.145 -0.004  0.618  0.095  0.145 -0.104  0.394  0.145  0.095  0.045  0.245  0.519 -0.129  0.145  0.020  0.344 -0.054  0.369  0.344  0.120  0.220  0.444  0.170 -0.004 -0.179  0.444  0.020  0.220  0.319  0.020 -0.029  0.245  0.245  0.419  0.369  0.494 -0.154  0.494  0.270  0.494  0.220  0.568 -0.004  0.170  0.469 -0.254  0.145  0.095 -0.079 -0.154 -0.279 -0.179 -0.029  0.145 -0.029  0.270  0.294  0.220 -0.079 -0.154  0.095  0.020 -0.279  0.170  0.020  0.319  0.270 -0.004  0.494  0.045  0.045  0.020 -0.279 -0.204 -0.079 -0.229  0.145  0.369  0.020  0.070 -0.104 -0.229 -0.079 -0.154  0.294 -0.154  0.020  0.245  0.145  0.045 -0.179 -0.129 
 0.237  0.262 -0.037  0.137  0.461  0.262  0.112  0.286  0.137  0.012  0.610  0.162  0.137 -0.112  0.386  0.137  0.087  0.037  0.212  0.511 -0.162  0.162  0.062  0.311 -0.037  0.311  0.386  0.212  0.311  0.436  0.187  0.062 -0.162  0.386  0.012  0.336  0.336 -0.012 -0.062  0.286  0.237  0.386  0.386  0.511 -0.162  0.486  0.361  0.511  0.361  0.561  0.012  0.162  0.411 -0.286  0.112  0.062 -0.087 -0.137 -0.286 -0.187  0.012  0.137  0.037  0.187  0.212  0.212 -0.087 -0.162  0.112  0.037 -0.286  0.187  0.037  0.361  0.361  0.012  0.511  0.087  0.037  0.012 -0.262 -0.212 -0.087 -0.237  0.137  0.386 -0.012  0.112 -0.062 -0.237 -0.112 -0.162  0.262 -0.162  0.012  0.237  0.137  0.012 -0.162 -0.137 
 0.298  0.273 -0.076  0.148  0.373  0.248  0.173  0.173  0.173  0.024  0.547  0.124  0.198 -0.126  0.298  0.124  0.099 -0.026  0.148  0.447 -0.101  0.248  0.024  0.348 -0.001  0.273  0.373  0.173  0.373  0.398  0.223  0.074 -0.126  0.223  0.049  0.323  0.373 -0.001 -0.026  0.223  0.074  0.373  0.173  0.572 -0.101  0.423  0.323  0.547  0.348  0.522  0.049  0.223  0.323 -0.225  0.124 -0.026 -0.051 -0.051 -0.200 -0.101 -0.001  0.049 -0.051  0.099  0.124  0.148 -0.026 -0.076  0.173  0.099 -0.200  0.198  0.024  0.273  0.348  0.074  0.447  0.099  0.074 -0.026 -0.200 -0.126 -0.026 -0.200  0.099  0.298 -0.051  0.173 -0.051 -0.175 -0.051 -0.101  0.273 -0.076  0.049  0.223  0.099  0.049 -0.126 -0.126 
 0.237  0.287 -0.037  0.113  0.237  0.262  0.162  0.162  0.162  0.038  0.486  0.113  0.237 -0.037  0.187  0.113  0.138 -0.112 -0.012  0.387 -0.112  0.237 -0.012  0.337  0.063  0.337  0.387  0.187  0.362  0.337  0.237  0.013 -0.062  0.113  0.088  0.237  0.412 -0.062  0.013  0.162  0.013  0.412  0.063  0.511 -0.087  0.362  0.212  0.536  0.312  0.461  0.063  0.212  0.237 -0.161  0.063 -0.012 -0.062 -0.012 -0.112 -0.037 -0.062  0.063 -0.012  0.063  0.088  0.063  0.038 -0.012  0.187  0.063 -0.112  0.088 -0.037  0.113  0.187  0.138  0.387  0.063  0.063  0.013 -0.137 -0.112 -0.037 -0.112  0.138  0.187  0.013  0.187 -0.112 -0.161  0.013 -0.062  0.262 -0.062  0.088  0.212  0.088  0.038 -0.087 -0.112 
 0.185  0.260 -0.039  0.135  0.185  0.260  0.185  0.185  0.110  0.060  0.484  0.135  0.210 -0.039  0.185  0.085  0.110 -0.089 -0.039  0.409 -0.089  0.210 -0.064  0.260  0.085  0.284  0.309  0.185  0.284  0.309  0.260  0.035 -0.039  0.060  0.035  0.235  0.484 -0.014  0.035  0.160  0.010  0.409  0.085  0.459 -0.089  0.384  0.185  0.534  0.260  0.409  0.060  0.185  0.185 -0.139  0.035  0.010 -0.089  0.010 -0.089 -0.014 -0.089  0.060 -0.014  0.035  0.035  0.035 -0.014 -0.039  0.185  0.060 -0.089  0.085 -0.089  0.085  0.135  0.135  0.309  0.035  0.085  0.035 -0.114 -0.089 -0.039 -0.089  0.160  0.160  0.010  0.210 -0.114 -0.139  0.010 -0.039  0.160 -0.039  0.060  0.135  0.085  0.035 -0.064 -0.089 
 0.142  0.267 -0.007  0.093  0.167  0.267  0.142  0.118  0.018  0.093  0.417  0.093  0.217 -0.032  0.093  0.118  0.118 -0.057 -0.082  0.392 -0.057  0.192 -0.057  0.142  0.068  0.242  0.192  0.142  0.142  0.342  0.267  0.068 -0.007  0.068 -0.007  0.242  0.541 -0.032  0.018  0.142  0.043  0.367  0.018  0.392 -0.082  0.367  0.142  0.541  0.118  0.292  0.068  0.167  0.167 -0.107 -0.032 -0.007 -0.082  0.043 -0.057  0.018 -0.082  0.068 -0.007  0.018  0.068  0.068  0.018 -0.007  0.217  0.018 -0.082  0.043 -0.082  0.043  0.043  0.142  0.242  0.018  0.068  0.068 -0.082 -0.107 -0.007 -0.082  0.192  0.068 -0.057  0.093 -0.082 -0.107  0.043 -0.032  0.068 -0.032  0.093  0.118  0.043  0.043 -0.032 -0.057 
 0.081  0.256 -0.018  0.106  0.131  0.281  0.156  0.056 -0.018  0.081  0.405  0.081  0.231 -0.018  0.106  0.131  0.131 -0.043 -0.068  0.380 -0.043  0.206 -0.068  0.131  0.056  0.206  0.206  0.131  0.131  0.355  0.206  0.056 -0.018  0.081 -0.018  0.256  0.555 -0.043  0.031  0.106  0.031  0.330  0.031  0.355 -0.068  0.380  0.106  0.505  0.106  0.305  0.056  0.156  0.156 -0.093 -0.043 -0.018 -0.068  0.056 -0.043  0.031 -0.068  0.081 -0.018  0.006  0.081  0.081  0.006  0.031  0.231  0.006 -0.068  0.031 -0.068  0.031  0.031  0.206  0.231  0.056  0.031  0.031 -0.093 -0.093 -0.018 -0.068  0.206  0.081 -0.068  0.081 -0.068 -0.093  0.031 -0.018  0.056 -0.018  0.106  0.156  0.006  0.056 -0.043 -0.043 
 0.075  0.199 -0.025  0.075  0.125  0.299  0.149  0.050 -0.050  0.100  0.424  0.075  0.199 -0.050  0.100  0.100  0.125 -0.025 -0.050  0.349 -0.025  0.174 -0.075  0.125  0.025  0.224  0.100  0.125  0.100  0.424  0.125  0.075 -0.025  0.075  0.000  0.274  0.573 -0.025  0.025  0.075  0.000  0.324  0.050  0.299 -0.050  0.324  0.075  0.548  0.050  0.249  0.025  0.174  0.000 -0.075 -0.050 -0.025 -0.075  0.050 -0.050  0.050 -0.050  0.075  0.000 -0.025  0.075  0.050  0.000  0.050  0.174  0.000 -0.050  0.000 -0.050  0.050  0.000  0.174  0.224  0.025  0.025  0.000 -0.075 -0.075  0.000 -0.050  0.199  0.050 -0.075  0.025 -0.050 -0.075  0.000 -0.025  0.050  0.000  0.125  0.149  0.025  0.025 -0.025 -0.025 
 0.014  0.114 -0.011  0.064  0.139  0.288  0.163  0.039 -0.036  0.089  0.388  0.039  0.213 -0.036  0.089  0.089  0.139 -0.011 -0.036  0.363 -0.011  0.163 -0.061  0.139  0.039  0.163  0.089  0.139  0.089  0.413  0.064  0.014 -0.011  0.064 -0.011  0.213  0.562 -0.011 -0.011  0.039  0.014  0.263  0.064  0.238 -0.036  0.263  0.039  0.537  0.039  0.163  0.014  0.163 -0.011 -0.061 -0.036 -0.061 -0.061  0.039 -0.061 -0.011 -0.061  0.089  0.014 -0.011  0.064  0.039 -0.011  0.064  0.064  0.014 -0.036  0.014 -0.036 -0.011 -0.036  0.139  0.188  0.014 -0.011 -0.011 -0.061 -0.061 -0.011 -0.036  0.163  0.014 -0.061 -0.011 -0.036 -0.061 -0.036 -0.036  0.039  0.014  0.114  0.139  0.014  0.014 -0.011 -0.011 
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 0.061 -0.064 -0.114 -0.114  0.086 -0.014 -0.089 -0.089  0.160 -0.188  0.160  0.011  0.136 -0.089  0.136 -0.114 -0.014 -0.163  0.709 -0.039 -0.064  0.210 -0.114 -0.089  0.036  0.310  0.086 -0.114  0.011 -0.064 -0.039 -0.188 -0.188  0.310  0.185 -0.139  0.061  0.061  0.061 -0.014  0.111  0.011  0.160  0.410 -0.188  0.011  0.036  0.111  0.011  0.111  0.185  0.360  0.484 -0.163  0.136  0.086  0.111 -0.064 -0.188 -0.089  0.160  0.011 -0.139 -0.064  0.061  0.160  0.036  0.086  0.659  0.335 -0.114  0.061  0.011  0.285  0.160 -0.139  0.235  0.086 -0.114 -0.163  0.111 -0.139  0.036 -0.139  0.136  0.061  0.260  0.185 -0.089  0.011 -0.114 -0.064  0.758 -0.114  0.111  0.235  0.260 -0.014 -0.139 -0.014 
 0.135 -0.065 -0.090 -0.115  0.110 -0.015 -0.090 -0.065  0.135 -0.189  0.159 -0.040  0.110 -0.065  0.135 -0.115 -0.015 -0.164  0.583 -0.040 -0.040  0.234 -0.115 -0.090  0.035  0.359  0.085 -0.115  0.060 -0.065 -0.015 -0.189 -0.189  0.309  0.184 -0.140  0.060  0.035  0.035 -0.015  0.110  0.010  0.159  0.433 -0.164  0.035  0.035  0.110  0.010  0.085  0.184  0.334  0.483 -0.164  0.135  0.135  0.110 -0.065 -0.189 -0.065  0.259  0.035 -0.140 -0.090  0.085  0.184  0.085  0.110  0.658  0.359 -0.090  0.110  0.035  0.284  0.159 -0.140  0.234  0.085 -0.115 -0.164  0.110 -0.115  0.035 -0.140  0.135  0.060  0.259  0.209 -0.090  0.010 -0.115 -0.065  0.757 -0.065  0.110  0.309  0.284 -0.015 -0.115  0.010 
 0.100 -0.099 -0.124 -0.149  0.100  0.000 -0.049 -0.074  0.125 -0.199  0.250 -0.049  0.125 -0.049  0.150 -0.124 -0.024 -0.174  0.474  0.000 -0.024  0.225 -0.174 -0.074  0.100  0.374  0.050 -0.124  0.075 -0.024 -0.024 -0.174 -0.199  0.324  0.150 -0.174  0.150  0.000  0.025 -0.024  0.075  0.000  0.150  0.449 -0.149  0.050  0.000  0.075  0.000  0.075  0.175  0.324  0.449 -0.174  0.175  0.225  0.125 -0.074 -0.149 -0.024  0.324  0.025 -0.124 -0.049  0.150  0.275  0.050  0.150  0.648  0.449 -0.074  0.100  0.025  0.275  0.175 -0.099  0.250  0.075 -0.099 -0.174  0.100 -0.099  0.025 -0.124  0.150  0.050  0.225  0.175 -0.099  0.025 -0.124 -0.074  0.748 -0.024  0.125  0.349  0.299 -0.024 -0.124  0.100 
 0.096 -0.053 -0.128 -0.153  0.096 -0.003 -0.003 -0.078  0.121 -0.203  0.320 -0.053  0.121 -0.003  0.146 -0.128 -0.028 -0.178  0.445 -0.003 -0.003  0.246 -0.178 -0.078  0.146  0.370  0.071 -0.128  0.071 -0.028 -0.003 -0.153 -0.203  0.320  0.146 -0.178  0.196 -0.028 -0.003 -0.053  0.096 -0.003  0.171  0.445 -0.153  0.046 -0.003  0.096 -0.003  0.071  0.196  0.320  0.445 -0.178  0.171  0.271  0.146 -0.078 -0.153 -0.028  0.370  0.046 -0.128 -0.028  0.146  0.295  0.046  0.146  0.644  0.470 -0.053  0.096  0.021  0.271  0.171 -0.103  0.271  0.121 -0.103 -0.178  0.096 -0.103  0.046 -0.128  0.146  0.121  0.221  0.246 -0.128 -0.003 -0.128 -0.078  0.744 -0.028  0.121  0.370  0.320 -0.028 -0.128  0.096 
 0.092 -0.057 -0.132 -0.132  0.092  0.017  0.017 -0.082  0.117 -0.207  0.366 -0.032  0.142 -0.007  0.167 -0.132 -0.032 -0.157  0.366  0.017 -0.007  0.242 -0.157 -0.032  0.142  0.366  0.067 -0.132  0.067 -0.032 -0.007 -0.132 -0.207  0.291  0.117 -0.157  0.217 -0.057 -0.007 -0.082  0.142  0.017  0.167  0.466 -0.157  0.067 -0.032  0.092 -0.007  0.092  0.192  0.316  0.416 -0.182  0.167  0.366  0.142 -0.057 -0.182 -0.057  0.391  0.042 -0.107 -0.032  0.167  0.291  0.017  0.142  0.640  0.541 -0.057  0.092  0.067  0.291  0.192 -0.107  0.316  0.117 -0.107 -0.157  0.067 -0.082 -0.007 -0.132  0.142  0.117  0.242  0.291 -0.132 -0.007 -0.157 -0.057  0.740 -0.032  0.117  0.366  0.316 -0.032 -0.107  0.067 
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 0.085 -0.015 -0.115 -0.115  0.060  0.035  0.035 -0.090  0.085 -0.214  0.384 -0.040  0.159  0.010  0.209 -0.140 -0.040 -0.164  0.309  0.035  0.010  0.234 -0.140 -0.040  0.184  0.433  0.010 -0.140  0.060 -0.015  0.035 -0.115 -0.214  0.284  0.085 -0.140  0.309 -0.015 -0.015 -0.065  0.159  0.060  0.159  0.508 -0.164  0.110 -0.065  0.135 -0.015  0.110  0.184  0.309  0.384 -0.189  0.159  0.359  0.135 -0.015 -0.189 -0.065  0.433  0.010 -0.065 -0.065  0.184  0.284  0.010  0.135  0.633  0.533 -0.090  0.085  0.085  0.284  0.259 -0.115  0.309  0.110 -0.090 -0.164  0.035 -0.090 -0.065 -0.115  0.159  0.085  0.184  0.309 -0.140 -0.040 -0.115 -0.040  0.732 -0.040  0.110  0.458  0.284 -0.040 -0.115  0.035 
 0.108 -0.017 -0.117 -0.117  0.058  0.033  0.008 -0.092  0.083 -0.241  0.407  0.008  0.133 -0.042  0.232 -0.117  0.008 -0.166  0.307  0.033  0.008  0.232 -0.191 -0.042  0.207  0.456 -0.017 -0.142  0.083 -0.017  0.058 -0.117 -0.216  0.282  0.083 -0.117  0.332 -0.017 -0.042 -0.117  0.157  0.058  0.157  0.531 -0.166  0.133 -0.067  0.232  0.008  0.133  0.182  0.307  0.382 -0.191  0.157  0.357  0.133  0.033 -0.191 -0.092  0.431  0.033 -0.017 -0.067  0.182  0.282  0.008  0.157  0.606  0.531 -0.117  0.083  0.058  0.307  0.307 -0.117  0.332  0.108 -0.092 -0.166  0.033 -0.092 -0.092 -0.092  0.133  0.083  0.157  0.307 -0.117 -0.042 -0.117 -0.042  0.730 -0.042  0.108  0.456  0.282 -0.042 -0.117  0.058 
 0.178 -0.021 -0.121 -0.071  0.028  0.028  0.003 -0.096  0.053 -0.246  0.452  0.103  0.078 -0.046  0.253 -0.071  0.003 -0.096  0.228  0.003  0.003  0.228 -0.221 -0.046  0.203  0.452 -0.021 -0.171  0.053 -0.021  0.053 -0.121 -0.221  0.278  0.103 -0.096  0.327  0.003  0.003 -0.121  0.178  0.028  0.153  0.527 -0.171  0.128 -0.071  0.302  0.003  0.128  0.178  0.352  0.377 -0.196  0.153  0.352  0.128  0.028 -0.196 -0.121  0.427  0.028  0.078 -0.071  0.178  0.302  0.003  0.128  0.601  0.552 -0.121  0.078  0.028  0.302  0.327 -0.096  0.377  0.103 -0.096 -0.171  0.028 -0.096 -0.121 -0.096  0.178  0.103  0.203  0.377 -0.121 -0.046 -0.121  0.003  0.701 -0.071  0.103  0.452  0.253 -0.046 -0.121  0.103 
 0.180 -0.019 -0.119 -0.069  0.030  0.030 -0.019 -0.094  0.030 -0.244  0.454  0.105  0.055 -0.044  0.255 -0.069  0.005 -0.094  0.205  0.030  0.005  0.205 -0.219 -0.044  0.205  0.479 -0.019 -0.169  0.055 -0.019  0.055 -0.119 -0.219  0.280  0.080 -0.094  0.329  0.005  0.005 -0.119  0.180  0.030  0.155  0.529 -0.169  0.180 -0.069  0.329  0.005  0.130  0.180  0.379  0.379 -0.194  0.155  0.379  0.130  0.030 -0.219 -0.119  0.429  0.030  0.080 -0.069  0.180  0.304  0.005  0.130  0.603  0.529 -0.119  0.080  0.030  0.280  0.329 -0.094  0.379  0.130 -0.094 -0.169  0.005 -0.094 -0.119 -0.094  0.180  0.105  0.205  0.379 -0.094 -0.044 -0.119  0.005  0.703 -0.069  0.105  0.454  0.230 -0.069 -0.144  0.080 
 0.177 -0.022 -0.122 -0.072  0.027  0.027 -0.022 -0.097  0.027 -0.247  0.476  0.127  0.052 -0.047  0.252 -0.072  0.027 -0.097  0.202  0.052  0.002  0.202 -0.222 -0.047  0.202  0.501 -0.022 -0.172  0.052  0.002  0.027 -0.122 -0.222  0.301  0.077 -0.097  0.326  0.002  0.002 -0.122  0.177  0.027  0.152  0.526 -0.172  0.202 -0.072  0.401  0.002  0.102  0.177  0.376  0.376 -0.197  0.127  0.376  0.102  0.027 -0.247 -0.122  0.376  0.027  0.077 -0.022  0.177  0.351  0.002  0.102  0.600  0.526 -0.122  0.077  0.027  0.277  0.351 -0.097  0.376  0.127 -0.072 -0.172  0.002 -0.097 -0.122 -0.122  0.177  0.102  0.202  0.376 -0.122 -0.022 -0.122  0.002  0.700 -0.072  0.102  0.451  0.227 -0.072 -0.122  0.077 
 0.175 -0.024 -0.124 -0.074  0.025  0.025 -0.024 -0.099  0.025 -0.249  0.449  0.125  0.050 -0.049  0.250 -0.074  0.025 -0.099  0.200  0.050  0.000  0.200 -0.224 -0.049  0.225  0.499 -0.024 -0.174  0.050  0.000  0.050 -0.124 -0.224  0.299  0.075 -0.099  0.324  0.000  0.000 -0.124  0.175  0.025  0.150  0.524 -0.174  0.200 -0.074  0.399  0.000  0.125  0.175  0.399  0.374 -0.199  0.125  0.374  0.100  0.025 -0.249 -0.124  0.399  0.025  0.075 -0.049  0.200  0.349  0.000  0.125  0.598  0.524 -0.124  0.075  0.025  0.275  0.349 -0.099  0.374  0.125 -0.074 -0.174  0.025 -0.099 -0.124 -0.099  0.175  0.100  0.200  0.374 -0.099 -0.049 -0.124  0.000  0.698 -0.074  0.125  0.449  0.225 -0.074 -0.124  0.100 
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-0.002  0.147 -0.077  0.072  0.396 -0.127  0.047 -0.052  0.122 -0.152 -0.027 -0.177  0.122 -0.002  0.022 -0.052 -0.052 -0.152  0.197 -0.127 -0.002  0.321 -0.127 -0.052 -0.027  0.047  0.197  0.022 -0.002 -0.027  0.047 -0.152 -0.052  0.022  0.172 -0.102  0.247 -0.002  0.197  0.321  0.296  0.296 -0.002  0.172 -0.052  0.147  0.072  0.147  0.147  0.047  0.097  0.072  0.321 -0.052  0.197  0.022  0.147 -0.002 -0.102 -0.002  0.147 -0.027 -0.027 -0.102 -0.052  0.097  0.072 -0.052  0.595  0.172 -0.127  0.097  0.047  0.321 -0.077 -0.127  0.172  0.122 -0.027 -0.002 -0.002 -0.102 -0.077 -0.052  0.097  0.022  0.272  0.122 -0.102 -0.052 -0.102 -0.027  0.820 -0.127 -0.002 -0.052  0.172  0.097 -0.002  0.022 
 0.001  0.101 -0.099  0.051  0.400 -0.124  0.101 -0.074  0.150 -0.198 -0.024 -0.198  0.175 -0.024  0.026 -0.074 -0.099 -0.173  0.200 -0.099  0.001  0.400 -0.099 -0.024 -0.024  0.076  0.200  0.026  0.076 -0.024  0.150 -0.124 -0.099 -0.049  0.225 -0.124  0.325 -0.049  0.200  0.474  0.350  0.250  0.026  0.175 -0.049  0.126  0.051  0.150  0.150  0.076  0.150  0.051  0.325 -0.024  0.275  0.026  0.126  0.001 -0.124 -0.024  0.175 -0.049  0.026 -0.099 -0.049  0.076  0.026 -0.024  0.574  0.225 -0.173  0.200  0.101  0.350 -0.049 -0.124  0.250  0.150 -0.074 -0.074 -0.049 -0.099 -0.024 -0.099  0.101  0.051  0.300  0.200 -0.124 -0.049 -0.148  0.001  0.773 -0.173  0.026 -0.024  0.200  0.076  0.001 -0.049 
 0.010  0.085 -0.090  0.035  0.384 -0.065  0.110 -0.065  0.135 -0.214 -0.040 -0.189  0.159 -0.015  0.010 -0.090 -0.090 -0.189  0.184 -0.040  0.010  0.384 -0.115  0.060  0.010  0.110  0.209  0.060  0.085  0.035  0.159 -0.140 -0.115 -0.065  0.234 -0.115  0.359 -0.090  0.159  0.433  0.334  0.309  0.035  0.184 -0.040  0.135  0.085  0.234  0.159  0.135  0.184  0.035  0.309 -0.015  0.259  0.035  0.184 -0.015 -0.140 -0.040  0.359 -0.090  0.035 -0.090 -0.015  0.110  0.010  0.010  0.533  0.234 -0.189  0.259  0.135  0.334 -0.090 -0.140  0.284  0.159 -0.090 -0.090 -0.065 -0.090 -0.040 -0.090  0.135  0.060  0.284  0.159 -0.115 -0.065 -0.140 -0.015  0.757 -0.189  0.010  0.035  0.284  0.060 -0.015 -0.065 
 0.020  0.120 -0.080  0.045  0.369 -0.055  0.120 -0.080  0.095 -0.229 -0.005 -0.204  0.169 -0.005 -0.030 -0.080 -0.080 -0.204  0.194 -0.030  0.120  0.394 -0.105  0.045  0.020  0.095  0.219  0.070  0.169  0.045  0.144 -0.105 -0.154 -0.055  0.269 -0.105  0.468 -0.105  0.144  0.443  0.344  0.294  0.095  0.219 -0.055  0.120  0.095  0.294  0.169  0.169  0.244  0.020  0.294 -0.005  0.269  0.120  0.144 -0.030 -0.154 -0.080  0.394 -0.055  0.020 -0.130 -0.030  0.120 -0.030 -0.005  0.518  0.244 -0.229  0.344  0.169  0.319 -0.055 -0.154  0.344  0.120 -0.130 -0.130 -0.055 -0.055 -0.055 -0.105  0.120  0.120  0.244  0.144 -0.130 -0.130 -0.130 -0.030  0.717 -0.204 -0.005  0.095  0.319 -0.005 -0.030 -0.154 
 0.064  0.139 -0.061  0.014  0.338  0.014  0.114 -0.111  0.089 -0.210 -0.036 -0.111  0.163 -0.011 -0.061 -0.086 -0.086 -0.185  0.188 -0.011  0.188  0.338 -0.086  0.089  0.039  0.089  0.238  0.039  0.188  0.064  0.139 -0.111 -0.185 -0.061  0.313 -0.086  0.462 -0.086  0.114  0.462  0.338  0.288  0.114  0.263 -0.061  0.114  0.089  0.288  0.163  0.188  0.238  0.039  0.288 -0.061  0.288  0.213  0.114 -0.036 -0.160 -0.036  0.413 -0.036  0.039 -0.136 -0.011  0.114 -0.011 -0.011  0.462  0.263 -0.235  0.338  0.163  0.313 -0.011 -0.160  0.313  0.114 -0.136 -0.136 -0.086 -0.036 -0.086 -0.111  0.163  0.139  0.213  0.139 -0.136 -0.111 -0.136 -0.011  0.711 -0.185 -0.011  0.089  0.363 -0.011 -0.011 -0.210 
 0.054  0.129 -0.070  0.004  0.328  0.079  0.154 -0.095  0.054 -0.220 -0.045 -0.070  0.154  0.004 -0.045 -0.045 -0.095 -0.170  0.154  0.004  0.204  0.303 -0.095  0.079  0.004  0.129  0.279  0.029  0.254  0.079  0.129 -0.120 -0.170 -0.070  0.303 -0.095  0.478 -0.095  0.104  0.478  0.328  0.254  0.104  0.254 -0.070  0.154  0.079  0.279  0.129  0.204  0.254  0.029  0.254 -0.120  0.279  0.204  0.104 -0.045 -0.195 -0.045  0.428 -0.045  0.029 -0.170 -0.020  0.104 -0.020 -0.020  0.453  0.303 -0.245  0.328  0.104  0.303  0.079 -0.170  0.378  0.179 -0.145 -0.145 -0.095 -0.045 -0.145 -0.120  0.129  0.129  0.204  0.154 -0.170 -0.120 -0.145 -0.020  0.677 -0.195  0.004  0.129  0.378 -0.020 -0.045 -0.220 
 0.049  0.124 -0.075  0.049  0.348  0.099  0.149 -0.075  0.049 -0.200 -0.050 -0.100  0.149 -0.000 -0.050 -0.050 -0.100 -0.200  0.124  0.024  0.249  0.274 -0.075  0.124 -0.025  0.149  0.274  0.024  0.249  0.074  0.149 -0.125 -0.175 -0.050  0.274 -0.075  0.473 -0.125  0.099  0.498  0.298  0.249  0.099  0.298 -0.075  0.199  0.074  0.298  0.124  0.298  0.249 -0.000  0.249 -0.175  0.249  0.199  0.049 -0.100 -0.200 -0.075  0.423 -0.025  0.024 -0.150 -0.000  0.099  0.024 -0.025  0.423  0.298 -0.250  0.348  0.099  0.298  0.124 -0.175  0.373  0.174 -0.150 -0.150 -0.175 -0.050 -0.150 -0.125  0.124  0.099  0.174  0.199 -0.175 -0.150 -0.150 -0.050  0.647 -0.200 -0.000  0.124  0.323 -0.000 -0.075 -0.225 
 0.065  0.115 -0.084  0.090  0.339  0.115  0.140 -0.009  0.040 -0.159 -0.034 -0.084  0.115 -0.059 -0.059 -0.059 -0.084 -0.184  0.140  0.140  0.265  0.240 -0.084  0.140 -0.009  0.140  0.265  0.065  0.289  0.090  0.165 -0.134 -0.184 -0.084  0.289  0.040  0.464 -0.134  0.065  0.489  0.289  0.265  0.065  0.314 -0.109  0.215  0.115  0.339  0.115  0.339  0.240 -0.009  0.215 -0.184  0.240  0.165  0.040 -0.109 -0.209 -0.084  0.414 -0.009  0.015 -0.184 -0.034  0.115  0.015 -0.059  0.414  0.339 -0.259  0.339  0.065  0.289  0.190 -0.159  0.439  0.165 -0.134 -0.159 -0.184 -0.059 -0.134 -0.134  0.115  0.065  0.090  0.240 -0.184 -0.159 -0.159 -0.059  0.638 -0.209 -0.009  0.115  0.314  0.015 -0.059 -0.209 
 0.057  0.107 -0.068  0.082  0.331  0.107  0.156 -0.018  0.032 -0.167 -0.018 -0.093  0.107 -0.068 -0.068 -0.018 -0.093 -0.167  0.132  0.206  0.281  0.231 -0.093  0.181 -0.018  0.206  0.281  0.107  0.281  0.082  0.181 -0.142 -0.192 -0.093  0.306  0.057  0.455 -0.142  0.057  0.505  0.331  0.281  0.057  0.306 -0.118  0.231  0.132  0.356  0.107  0.406  0.206 -0.018  0.206 -0.192  0.231  0.181  0.032 -0.118 -0.217 -0.093  0.455  0.007  0.007 -0.167 -0.018  0.107  0.007 -0.068  0.406  0.356 -0.267  0.331  0.057  0.281  0.206 -0.142  0.430  0.156 -0.118 -0.167 -0.192 -0.068 -0.118 -0.118  0.107  0.057  0.082  0.231 -0.192 -0.192 -0.142 -0.068  0.630 -0.217 -0.018  0.107  0.306  0.007 -0.093 -0.217 
 0.104  0.079 -0.020  0.079  0.279  0.154  0.104 -0.020  0.079 -0.170  0.004 -0.070  0.079 -0.095  0.004  0.029 -0.070 -0.145  0.179  0.303  0.303  0.254 -0.095  0.204 -0.020  0.254  0.303  0.104  0.303  0.104  0.204 -0.120 -0.195 -0.095  0.328  0.079  0.403 -0.095  0.029  0.503  0.303  0.328  0.054  0.328 -0.170  0.303  0.154  0.403  0.079  0.478  0.204 -0.045  0.179 -0.220  0.229  0.229 -0.070 -0.120 -0.220 -0.095  0.453  0.004 -0.020 -0.145  0.004  0.104  0.004 -0.070  0.353  0.353 -0.270  0.353  0.054  0.229  0.279 -0.145  0.403  0.154 -0.145 -0.095 -0.220 -0.095 -0.095 -0.145  0.154  0.029  0.029  0.229 -0.195 -0.195 -0.170 -0.070  0.553 -0.170 -0.020  0.154  0.279  0.004 -0.120 -0.245 
 0.123  0.073 -0.002  0.123  0.297  0.172  0.098 -0.027  0.098 -0.151  0.023 -0.077  0.073 -0.102 -0.002  0.073 -0.052 -0.127  0.272  0.372  0.297  0.247 -0.102  0.197 -0.027  0.347  0.322  0.123  0.297  0.098  0.197 -0.077 -0.201 -0.127  0.372  0.123  0.397 -0.077  0.048  0.471  0.297  0.347  0.048  0.297 -0.176  0.297  0.197  0.397  0.098  0.546  0.197 -0.027  0.172 -0.226  0.247  0.222 -0.077 -0.127 -0.226 -0.102  0.422  0.023 -0.027 -0.151 -0.002  0.098 -0.002 -0.077  0.322  0.347 -0.276  0.347  0.048  0.197  0.297 -0.127  0.397  0.172 -0.151 -0.102 -0.226 -0.102 -0.102 -0.176  0.172  0.023  0.048  0.222 -0.201 -0.176 -0.176 -0.102  0.546 -0.151 -0.027  0.172  0.272  0.023 -0.127 -0.251 
 0.119  0.069  0.019  0.143  0.268  0.243  0.119 -0.006  0.143 -0.081  0.044 -0.056  0.094 -0.106  0.019  0.143 -0.031 -0.081  0.268  0.393  0.293  0.268 -0.081  0.218 -0.006  0.343  0.343  0.119  0.318  0.119  0.218 -0.056 -0.131 -0.131  0.393  0.168  0.418 -0.056  0.094  0.467  0.293  0.368  0.044  0.243 -0.180  0.343  0.193  0.418  0.168  0.592  0.193 -0.056  0.143 -0.255  0.243  0.218 -0.106 -0.131 -0.230 -0.106  0.442  0.019 -0.031 -0.155 -0.006  0.044 -0.031 -0.081  0.293  0.293 -0.280  0.343  0.044  0.168  0.318 -0.081  0.393  0.143 -0.155 -0.106 -0.230 -0.131 -0.106 -0.205  0.168  0.019  0.019  0.193 -0.205 -0.155 -0.155 -0.106  0.442 -0.155 -0.006  0.193  0.218 -0.006 -0.106 -0.255 
 0.142  0.068  0.043  0.167  0.267  0.242  0.118  0.018  0.142 -0.082  0.118 -0.032  0.142 -0.156  0.018  0.242 -0.032 -0.082  0.267  0.441  0.292  0.242 -0.107  0.217 -0.007  0.342  0.317  0.167  0.317  0.142  0.217 -0.057 -0.132 -0.132  0.367  0.167  0.441 -0.057  0.093  0.466  0.267  0.367  0.043  0.242 -0.181  0.342  0.167  0.417  0.167  0.591  0.192 -0.032  0.142 -0.256  0.242  0.217 -0.107 -0.132 -0.231 -0.107  0.466  0.043 -0.032 -0.132 -0.007  0.018 -0.057 -0.057  0.292  0.292 -0.281  0.342  0.043  0.167  0.342 -0.082  0.392  0.118 -0.156 -0.132 -0.231 -0.132 -0.082 -0.206  0.167  0.018  0.018  0.192 -0.206 -0.181 -0.156 -0.107  0.441 -0.156 -0.007  0.192  0.217 -0.007 -0.107 -0.256 
 0.190  0.090  0.040  0.240  0.240  0.265  0.165  0.040  0.165 -0.084  0.140  0.015  0.140 -0.159  0.015  0.240 -0.009 -0.109  0.265  0.464  0.314  0.215 -0.109  0.240 -0.009  0.339  0.339  0.190  0.314  0.190  0.215  0.015 -0.109 -0.109  0.364  0.190  0.439 -0.059  0.115  0.464  0.240  0.364  0.065  0.289 -0.209  0.339  0.165  0.414  0.190  0.588  0.190 -0.034  0.115 -0.284  0.240  0.190 -0.109 -0.109 -0.259 -0.109  0.439  0.065 -0.034 -0.134 -0.009  0.015 -0.059 -0.059  0.289  0.289 -0.284  0.339  0.015  0.140  0.339 -0.059  0.389  0.065 -0.159 -0.134 -0.234 -0.134 -0.084 -0.184  0.165  0.040 -0.059  0.190 -0.184 -0.184 -0.159 -0.134  0.439 -0.134 -0.009  0.240  0.190 -0.034 -0.109 -0.284 
 0.214  0.089  0.039  0.214  0.164  0.288  0.214  0.039  0.164 -0.060  0.239  0.114  0.139 -0.160  0.064  0.239  0.014 -0.110  0.239  0.463  0.388  0.239 -0.110  0.264  0.014  0.363  0.313  0.214  0.313  0.239  0.214 -0.010 -0.135 -0.110  0.388  0.189  0.438 -0.085  0.114  0.463  0.239  0.388  0.089  0.313 -0.210  0.338  0.164  0.413  0.214  0.587  0.189 -0.035  0.114 -0.284  0.239  0.189 -0.135 -0.085 -0.260 -0.110  0.438  0.089 -0.010 -0.060 -0.010  0.014 -0.060 -0.085  0.288  0.288 -0.260  0.338  0.014  0.139  0.338 -0.060  0.413  0.064 -0.160 -0.135 -0.235 -0.135 -0.085 -0.185  0.164  0.014 -0.085  0.164 -0.185 -0.185 -0.160 -0.135  0.413 -0.135 -0.010  0.239  0.189 -0.010 -0.135 -0.284 
 0.258  0.084  0.034  0.233  0.158  0.283  0.258  0.034  0.158 -0.041  0.308  0.134  0.134 -0.165  0.034  0.233  0.009 -0.116  0.233  0.482  0.383  0.208 -0.141  0.233  0.059  0.358  0.333  0.233  0.308  0.233  0.233 -0.016 -0.141 -0.091  0.358  0.183  0.432 -0.091  0.134  0.457  0.233  0.383  0.109  0.383 -0.215  0.333  0.183  0.408  0.333  0.582  0.158 -0.016  0.084 -0.290  0.233  0.158 -0.141 -0.066 -0.290 -0.116  0.432  0.084 -0.016 -0.066 -0.016  0.034 -0.066 -0.091  0.258  0.233 -0.265  0.308  0.034  0.134  0.308 -0.016  0.432  0.009 -0.165 -0.141 -0.265 -0.165 -0.091 -0.190  0.183  0.034 -0.091  0.134 -0.190 -0.215 -0.165 -0.190  0.383 -0.141 -0.041  0.233  0.183 -0.016 -0.116 -0.290 
 0.215  0.090  0.015  0.265  0.215  0.314  0.289  0.015  0.040 -0.034  0.190  0.090  0.115 -0.134  0.065  0.190 -0.034 -0.084  0.140  0.439  0.339  0.215 -0.109  0.190 -0.034  0.265  0.265  0.240  0.240  0.265  0.265 -0.034 -0.109 -0.034  0.364  0.165  0.414 -0.109  0.040  0.389  0.165  0.439  0.065  0.364 -0.184  0.314  0.190  0.389  0.314  0.514  0.140 -0.059  0.040 -0.209  0.289  0.215 -0.134 -0.084 -0.209 -0.109  0.389  0.115  0.040 -0.109 -0.034  0.015 -0.084 -0.059  0.265  0.165 -0.209  0.314 -0.009  0.115  0.140 -0.084  0.339 -0.034 -0.084 -0.109 -0.209 -0.109 -0.059 -0.159  0.165  0.040 -0.034  0.140 -0.159 -0.209 -0.109 -0.134  0.289 -0.134  0.015  0.115  0.115  0.015 -0.109 -0.234 
 0.165  0.140 -0.009  0.215  0.265  0.314  0.265  0.040  0.040  0.015  0.190 -0.009  0.115 -0.134  0.015  0.015 -0.009 -0.109  0.015  0.339  0.140  0.265 -0.059  0.190  0.015  0.240  0.289  0.190  0.215  0.265  0.215  0.040 -0.059 -0.034  0.314  0.265  0.389 -0.034  0.090  0.439  0.115  0.414  0.040  0.339 -0.134  0.339  0.215  0.439  0.240  0.389  0.090 -0.009  0.065 -0.159  0.215  0.115 -0.109 -0.009 -0.109 -0.034  0.140  0.065  0.065 -0.109  0.015 -0.009 -0.009  0.015  0.240  0.115 -0.134  0.090 -0.109  0.040  0.040 -0.009  0.190 -0.009 -0.034 -0.034 -0.134 -0.084 -0.034 -0.084  0.065  0.040 -0.009  0.090 -0.084 -0.109 -0.109 -0.059  0.265 -0.059  0.065  0.040  0.040 -0.009 -0.034 -0.134 
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 0.513  0.014 -0.185  0.089  0.014 -0.110 -0.185 -0.135 -0.010 -0.060  0.264  0.463 -0.035 -0.110  0.139 -0.035  0.164  0.039  0.014 -0.085 -0.260 -0.085 -0.135 -0.110  0.189  0.139 -0.035  0.039  0.089  0.064 -0.010 -0.110 -0.035 -0.085  0.089  0.064  0.014 -0.210 -0.185  0.014 -0.010  0.039  0.014  0.587 -0.210  0.189 -0.160  0.039 -0.160 -0.085  0.139  0.637  0.413  0.039  0.064  0.288  0.264  0.064  0.239  0.712  0.039  0.388  0.089  0.164  0.488  0.513  0.264 -0.110  0.612 -0.085  0.164  0.014  0.114  0.687 -0.035  0.214  0.513  0.039  0.064 -0.035  0.513  0.039  0.164  0.014  0.264  0.114  0.587  0.737 -0.060 -0.135  0.264  0.712  0.488 -0.035  0.014  0.264 -0.060  0.064  0.039  0.637 
 0.485  0.011 -0.188  0.036 -0.013 -0.113 -0.188 -0.138  0.011 -0.063  0.261  0.460 -0.013 -0.088  0.161 -0.063  0.161  0.036  0.011 -0.088 -0.263 -0.113 -0.138 -0.113  0.161  0.136 -0.013  0.086  0.086  0.086 -0.013 -0.113 -0.063 -0.113  0.061  0.086  0.011 -0.213 -0.188  0.036 -0.038  0.036 -0.013  0.584 -0.213  0.211 -0.163  0.036 -0.163 -0.088  0.136  0.634  0.410  0.061  0.086  0.310  0.261  0.161  0.211  0.709  0.061  0.460  0.086  0.236  0.510  0.510  0.310 -0.113  0.584 -0.088  0.186  0.011  0.111  0.684 -0.063  0.211  0.485  0.086  0.061 -0.038  0.510  0.036  0.186  0.036  0.261  0.136  0.510  0.734 -0.063 -0.163  0.285  0.709  0.485 -0.038  0.036  0.261 -0.088  0.061  0.061  0.634 
 0.456  0.008 -0.191  0.033  0.008 -0.092 -0.191 -0.142  0.033 -0.067  0.257  0.382 -0.042 -0.017  0.157 -0.117  0.157  0.008  0.008 -0.067 -0.266 -0.092 -0.142 -0.117  0.157  0.182 -0.017  0.058  0.083  0.083 -0.067 -0.117 -0.191 -0.117  0.058  0.058  0.058 -0.216 -0.191 -0.017 -0.042  0.033 -0.017  0.556 -0.241  0.207 -0.142  0.058 -0.166 -0.092  0.182  0.631  0.407  0.083  0.108  0.307  0.407  0.182  0.257  0.706  0.058  0.506  0.058  0.282  0.506  0.506  0.332 -0.117  0.556 -0.092  0.232  0.033  0.108  0.656 -0.067  0.257  0.382  0.083  0.083 -0.042  0.481  0.058  0.257  0.058  0.282  0.157  0.456  0.730 -0.092 -0.166  0.307  0.706  0.481 -0.042  0.033  0.282 -0.117  0.083  0.108  0.631 
 0.427  0.003 -0.196  0.003  0.003 -0.071 -0.196 -0.146  0.003 -0.121  0.253  0.377  0.028  0.003  0.153 -0.121  0.178 -0.021  0.003 -0.046 -0.271 -0.096 -0.146 -0.121  0.153  0.178 -0.046  0.053  0.078  0.078 -0.096 -0.146 -0.246 -0.121  0.028  0.028  0.053 -0.221 -0.146 -0.046 -0.021  0.028  0.003  0.527 -0.246  0.203 -0.146  0.053 -0.146 -0.121  0.178  0.626  0.402  0.103  0.128  0.302  0.452  0.178  0.253  0.701  0.103  0.502  0.028  0.302  0.502  0.477  0.377 -0.121  0.552 -0.096  0.302  0.028  0.128  0.576 -0.071  0.302  0.327  0.078  0.128 -0.046  0.477  0.078  0.253  0.103  0.302  0.228  0.452  0.726 -0.096 -0.171  0.327  0.701  0.477 -0.046  0.028  0.278 -0.121  0.153  0.103  0.626 
 0.422 -0.027 -0.176 -0.052  0.098 -0.077 -0.201 -0.151  0.023 -0.127  0.272  0.347  0.048  0.048  0.147 -0.127  0.197 -0.052 -0.002 -0.052 -0.276 -0.077 -0.176 -0.127  0.172  0.197 -0.052  0.023  0.098  0.048 -0.077 -0.151 -0.276 -0.127  0.023  0.023  0.073 -0.201 -0.127 -0.102 -0.027  0.023 -0.002  0.521 -0.201  0.197 -0.151  0.073 -0.127 -0.127  0.197  0.621  0.347  0.147  0.172  0.297  0.546  0.222  0.347  0.696  0.098  0.496  0.023  0.297  0.496  0.471  0.372 -0.102  0.546 -0.102  0.397  0.023  0.123  0.521 -0.077  0.322  0.297  0.048  0.172 -0.052  0.471  0.073  0.322  0.123  0.322  0.272  0.422  0.696 -0.127 -0.176  0.347  0.696  0.471 -0.052  0.023  0.272 -0.102  0.147  0.147  0.621 
 0.413  0.014 -0.136 -0.086  0.014 -0.011 -0.160 -0.160 -0.011 -0.086  0.139  0.238 -0.011  0.014  0.089 -0.061  0.064 -0.011  0.039 -0.061 -0.210 -0.061 -0.160 -0.136  0.163  0.089 -0.036 -0.011  0.139  0.064 -0.061 -0.086 -0.210 -0.061  0.039  0.039  0.064 -0.160 -0.111 -0.086  0.039  0.039 -0.011  0.512 -0.160  0.163 -0.185  0.039 -0.136 -0.086  0.238  0.612  0.313  0.139  0.064  0.238  0.437  0.188  0.388  0.687  0.089  0.437  0.014  0.313  0.512  0.462  0.363 -0.036  0.562 -0.086  0.388  0.039  0.163  0.462 -0.111  0.263  0.163  0.014  0.213  0.014  0.512 -0.036  0.238  0.163  0.288  0.263  0.437  0.687 -0.136 -0.111  0.313  0.687  0.512 -0.061 -0.011  0.288 -0.061  0.139  0.089  0.562 
 0.316 -0.007 -0.132 -0.107  0.067 -0.007 -0.132 -0.132 -0.082 -0.082  0.117  0.117 -0.032 -0.032  0.042  0.017  0.042 -0.007  0.117 -0.057 -0.157 -0.032 -0.082 -0.057  0.142 -0.007 -0.032 -0.032  0.142 -0.007 -0.082 -0.082 -0.157 -0.032  0.017  0.067  0.042 -0.132 -0.082 -0.032  0.067  0.067 -0.007  0.441 -0.132  0.017 -0.132 -0.032 -0.107 -0.057  0.167  0.590  0.291  0.092 -0.007  0.167  0.341  0.142  0.316  0.690  0.092  0.391  0.017  0.167  0.466  0.441  0.391 -0.007  0.566 -0.107  0.291  0.017  0.117  0.416 -0.057  0.192  0.142  0.042  0.117 -0.007  0.416 -0.007  0.217  0.092  0.291  0.142  0.466  0.690 -0.107 -0.032  0.291  0.665  0.491 -0.057 -0.057  0.242 -0.032  0.092 -0.007  0.466 
 0.312  0.013 -0.111 -0.086  0.088  0.013 -0.111 -0.111 -0.061 -0.061  0.088  0.038 -0.036 -0.036  0.013  0.013  0.013  0.013  0.138 -0.036 -0.136 -0.036 -0.111 -0.036  0.138  0.013 -0.011 -0.011  0.063  0.013 -0.086 -0.061 -0.136 -0.036  0.038  0.063  0.013 -0.111 -0.061 -0.036  0.063  0.088  0.013  0.437 -0.111  0.013 -0.111 -0.036 -0.086 -0.036  0.138  0.586  0.287  0.038 -0.011  0.138  0.312  0.088  0.287  0.686  0.088  0.287 -0.011  0.113  0.437  0.362  0.412  0.013  0.586 -0.111  0.163  0.013  0.113  0.362 -0.036  0.138  0.138  0.038  0.088 -0.011  0.437 -0.011  0.188  0.113  0.163  0.138  0.462  0.661 -0.086 -0.011  0.238  0.686  0.487 -0.061 -0.086  0.213 -0.011  0.013  0.013  0.462 
 0.215  0.041 -0.084 -0.059  0.116  0.016 -0.084 -0.084 -0.059 -0.059  0.041 -0.034 -0.059 -0.084 -0.059  0.016 -0.009  0.041  0.165 -0.009 -0.109 -0.009 -0.109 -0.009  0.091 -0.009  0.016  0.016  0.066 -0.009 -0.034 -0.059 -0.109 -0.084  0.066  0.041  0.016 -0.084 -0.084 -0.059  0.041  0.041  0.016  0.390 -0.084  0.016 -0.084 -0.084 -0.059 -0.034  0.091  0.489  0.240  0.041 -0.034  0.116  0.190  0.091  0.265  0.689  0.016  0.190  0.041  0.091  0.439  0.365  0.439  0.016  0.539 -0.084  0.091  0.016  0.066  0.290 -0.034  0.041  0.066 -0.034  0.016  0.016  0.464 -0.009  0.116  0.116  0.066  0.091  0.340  0.713 -0.059 -0.009  0.190  0.664  0.464 -0.059 -0.084  0.116 -0.009  0.016  0.016  0.415 
 0.227  0.052 -0.097 -0.047  0.127 -0.022 -0.072 -0.072 -0.047 -0.047  0.052 -0.022 -0.072 -0.072 -0.072 -0.022 -0.022  0.052  0.177  0.002 -0.097  0.002 -0.097 -0.047  0.077 -0.022  0.027  0.027  0.077 -0.022 -0.022 -0.047 -0.097 -0.097  0.077  0.027  0.002 -0.072 -0.072 -0.047  0.052  0.052  0.002  0.301 -0.072  0.002 -0.072 -0.047 -0.047 -0.022  0.052  0.426  0.227  0.002 -0.022  0.127  0.152  0.077  0.252  0.750  0.027  0.127  0.077  0.077  0.426  0.326  0.376  0.002  0.476 -0.072  0.027  0.002  0.052  0.277 -0.047  0.002  0.077 -0.072  0.027 -0.022  0.476  0.002  0.077  0.127  0.077  0.052  0.351  0.725 -0.047  0.002  0.177  0.575  0.476 -0.072 -0.072  0.102  0.002  0.002 -0.022  0.401 
 0.215  0.016 -0.084 -0.034  0.066 -0.009 -0.084 -0.059 -0.059 -0.034  0.016 -0.009 -0.084 -0.059 -0.084 -0.034 -0.009  0.066  0.165 -0.034 -0.084  0.016 -0.084 -0.059  0.041 -0.034  0.016  0.016  0.066 -0.009 -0.009 -0.059 -0.084 -0.084  0.066  0.041 -0.009 -0.059 -0.059 -0.059  0.066  0.016 -0.034  0.141 -0.059 -0.059 -0.084 -0.034 -0.059 -0.009 -0.009  0.340  0.240 -0.009 -0.009  0.141  0.091  0.041  0.215  0.813  0.016  0.016  0.091  0.066  0.390  0.290  0.365  0.016  0.489 -0.059  0.016 -0.009 -0.034  0.240 -0.059 -0.009  0.091 -0.059  0.016 -0.009  0.489 -0.009 -0.034  0.066  0.091  0.016  0.265  0.738 -0.034 -0.009  0.141  0.564  0.390 -0.034 -0.059  0.066  0.016  0.016 -0.034  0.415 
 0.221  0.022 -0.078 -0.028  0.072 -0.003 -0.078 -0.053 -0.053 -0.028  0.022 -0.003 -0.053 -0.078 -0.078 -0.053 -0.003  0.072  0.072 -0.028 -0.078  0.022 -0.078 -0.053  0.047 -0.028 -0.003  0.022  0.072 -0.003 -0.003 -0.053 -0.078 -0.078  0.072  0.047 -0.053 -0.053 -0.053 -0.053  0.072  0.022 -0.028  0.097 -0.053 -0.078 -0.078 -0.028 -0.053 -0.003 -0.028  0.346  0.246 -0.003 -0.003  0.146  0.097  0.022  0.221  0.844 -0.003 -0.028  0.097  0.047  0.346  0.271  0.346 -0.028  0.445 -0.053  0.022 -0.003 -0.028  0.196 -0.053 -0.003  0.097 -0.053  0.022 -0.003  0.495 -0.003 -0.053  0.047  0.072 -0.003  0.221  0.744 -0.028 -0.053  0.146  0.520  0.321 -0.028 -0.053  0.047  0.047  0.022 -0.028  0.421 
 0.205  0.005 -0.069  0.005  0.030  0.005 -0.069 -0.044 -0.044 -0.019 -0.019 -0.019 -0.044 -0.069 -0.069 -0.044 -0.019  0.080  0.030 -0.019 -0.069  0.030 -0.069 -0.069  0.030 -0.019  0.005  0.030  0.080  0.005 -0.019 -0.044 -0.069 -0.069  0.080  0.030 -0.069 -0.044 -0.044 -0.044  0.080  0.005 -0.044  0.055 -0.044 -0.069 -0.069 -0.019 -0.044  0.005 -0.019  0.230  0.255  0.005 -0.019  0.130  0.080  0.030  0.205  0.902 -0.044 -0.069  0.030  0.030  0.329  0.180  0.329 -0.069  0.404 -0.044  0.030 -0.019 -0.044  0.080 -0.019  0.005  0.055 -0.044  0.005  0.005  0.529  0.005 -0.044  0.005  0.055 -0.069  0.155  0.778 -0.019 -0.044  0.155  0.479  0.205 -0.019 -0.044  0.055  0.030  0.005 -0.019  0.404 
 0.181  0.007 -0.068  0.007  0.007  0.007 -0.068 -0.043 -0.043 -0.018 -0.018 -0.018 -0.043 -0.043 -0.068 -0.043 -0.018  0.032  0.032 -0.018 -0.068  0.032 -0.068 -0.068  0.032 -0.018  0.007  0.032  0.082 -0.018 -0.018 -0.043 -0.068 -0.068  0.107  0.032 -0.068 -0.043 -0.043 -0.018  0.057  0.007 -0.043  0.057 -0.043 -0.068 -0.068 -0.018 -0.043  0.007 -0.018  0.206  0.256  0.007  0.007  0.107  0.057  0.007  0.206  0.929 -0.043 -0.068  0.032  0.032  0.331  0.181  0.281 -0.068  0.381 -0.043  0.007 -0.018 -0.043  0.057 -0.043  0.032  0.057 -0.043  0.007 -0.018  0.530 -0.018 -0.043  0.007  0.032 -0.068  0.107  0.804 -0.018 -0.043  0.156  0.455  0.181 -0.018 -0.043  0.057  0.032  0.007 -0.018  0.406 
 0.186  0.012 -0.063  0.012 -0.013  0.037 -0.063 -0.038 -0.038 -0.038 -0.038  0.012 -0.038 -0.038 -0.013 -0.038 -0.013  0.037 -0.038 -0.013 -0.063  0.037 -0.063 -0.063  0.037 -0.013 -0.013  0.037  0.112 -0.038 -0.013 -0.038 -0.038 -0.063  0.087  0.012 -0.063 -0.038 -0.038  0.037  0.037  0.012 -0.038 -0.013 -0.063 -0.063 -0.063 -0.013 -0.038  0.037 -0.013  0.087  0.186  0.012  0.012  0.062  0.037  0.012  0.161  0.959 -0.038 -0.063  0.037 -0.013  0.286  0.087  0.236 -0.063  0.311 -0.038 -0.013 -0.013 -0.038  0.062 -0.038  0.037  0.062 -0.038 -0.013 -0.013  0.585 -0.013 -0.038  0.012  0.037 -0.063  0.112  0.884 -0.038 -0.038  0.161  0.435  0.112 -0.038 -0.013  0.062  0.012 -0.013 -0.038  0.311 
 0.189  0.014 -0.060  0.014 -0.010  0.039 -0.060 -0.010 -0.035 -0.035 -0.035  0.014 -0.035 -0.035 -0.010 -0.035 -0.035  0.014 -0.035 -0.010 -0.060  0.064 -0.060 -0.060  0.039 -0.010 -0.010  0.039  0.114 -0.035 -0.010 -0.035 -0.035 -0.060  0.064  0.014 -0.060 -0.035 -0.035  0.039  0.014  0.014 -0.035 -0.010 -0.060 -0.060 -0.060 -0.010 -0.035  0.014 -0.010  0.064  0.189  0.014  0.014  0.064  0.039  0.014  0.164  0.961 -0.035 -0.060  0.039 -0.010  0.214  0.064  0.164 -0.060  0.288 -0.060 -0.010 -0.010 -0.035  0.064 -0.010  0.039  0.039 -0.010 -0.010 -0.010  0.612 -0.010 -0.035  0.014  0.039 -0.060  0.114  0.911 -0.035 -0.035  0.139  0.438  0.114 -0.035 -0.010  0.064  0.014 -0.010 -0.035  0.239 
 0.146  0.022 -0.053  0.022 -0.028  0.047 -0.053 -0.003 -0.028 -0.028 -0.028  0.022 -0.028 -0.028 -0.003 -0.028 -0.028 -0.003 -0.028 -0.028 -0.053  0.072 -0.053 -0.053  0.047 -0.028 -0.003  0.047  0.097 -0.028 -0.028 -0.028 -0.028 -0.053  0.072  0.022 -0.053 -0.053 -0.053  0.047 -0.003  0.022 -0.028 -0.028 -0.053 -0.053 -0.053 -0.003 -0.028 -0.003 -0.003  0.072  0.122  0.022  0.022  0.022  0.047  0.022  0.146  0.969 -0.053 -0.028  0.022 -0.028  0.047  0.022  0.146 -0.053  0.196 -0.053 -0.003 -0.003 -0.028  0.022 -0.003  0.047  0.022 -0.003 -0.003 -0.003  0.595 -0.003 -0.028  0.022  0.047 -0.053  0.097  0.944 -0.028 -0.028  0.097  0.321  0.097 -0.053 -0.003  0.072  0.022 -0.003 -0.028  0.122 
 0.147  0.022 -0.052  0.022 -0.027  0.047 -0.052 -0.002 -0.027 -0.027 -0.027  0.022 -0.027 -0.027 -0.002 -0.027 -0.027 -0.002 -0.027 -0.027 -0.052  0.072 -0.052 -0.052  0.047 -0.027 -0.002  0.047  0.097 -0.027 -0.027 -0.002 -0.027 -0.052  0.072  0.022 -0.052 -0.052 -0.052  0.047 -0.002  0.022 -0.027 -0.027 -0.052 -0.052 -0.052 -0.002 -0.027 -0.002 -0.002  0.072  0.122  0.022  0.022  0.022  0.047  0.022  0.147  0.969 -0.052 -0.027 -0.002 -0.052  0.047 -0.002  0.122 -0.052  0.197 -0.052 -0.002 -0.002 -0.027  0.022 -0.002  0.047  0.022 -0.002 -0.002 -0.002  0.595 -0.002 -0.052  0.022  0.047 -0.052  0.097  0.969 -0.027 -0.027  0.097  0.272  0.097 -0.052 -0.002  0.072  0.022 -0.002 -0.027  0.122 
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 0.162  0.062 -0.062  0.012 -0.037  0.012 -0.062 -0.037 -0.037 -0.012  0.012  0.012 -0.037 -0.037 -0.012 -0.037 -0.012  0.087 -0.037 -0.037 -0.062  0.087 -0.062 -0.062  0.037  0.012 -0.012  0.012  0.087 -0.037 -0.012  0.012 -0.037 -0.062  0.087  0.162 -0.037 -0.062 -0.037  0.012  0.062 -0.012 -0.012  0.012 -0.062 -0.062 -0.062 -0.012 -0.037  0.037 -0.037  0.087  0.087 -0.012 -0.012  0.087  0.012 -0.012  0.262  0.959 -0.062 -0.012  0.062 -0.037  0.137  0.012  0.162 -0.062  0.187 -0.037  0.012 -0.012 -0.037  0.112 -0.012  0.062  0.062 -0.012  0.012  0.012  0.187 -0.012 -0.062  0.037  0.037 -0.062  0.137  0.959 -0.037 -0.037  0.212  0.411  0.062 -0.037 -0.037  0.062 -0.012 -0.012 -0.037  0.262 
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 0.345 -0.078 -0.203 -0.028 -0.028 -0.128 -0.203 -0.128 -0.128 -0.128  0.146  0.046 -0.178  0.021  0.046 -0.153 -0.053 -0.003  0.021 -0.153 -0.178 -0.028 -0.203 -0.078  0.146 -0.078 -0.078 -0.003  0.121  0.046 -0.103 -0.078 -0.153 -0.203  0.021  0.046 -0.153 -0.178 -0.153  0.021  0.021 -0.078 -0.128  0.121 -0.178 -0.078 -0.128 -0.003 -0.128 -0.053  0.046  0.594  0.271  0.295 -0.003  0.096  0.246  0.171  0.694  0.744  0.046 -0.003  0.071  0.271  0.594  0.395  0.669 -0.053  0.644 -0.028  0.569 -0.028 -0.078  0.520 -0.128  0.121  0.146  0.096 -0.028  0.021  0.594  0.021  0.071  0.121  0.121 -0.053  0.271  0.769 -0.128 -0.103  0.320  0.769  0.246  0.121 -0.028  0.096 -0.103  0.146  0.146  0.694 
 0.397 -0.102 -0.201 -0.027 -0.052 -0.151 -0.201 -0.127 -0.127 -0.102  0.172  0.048 -0.151  0.023  0.123 -0.176 -0.052 -0.027  0.023 -0.176 -0.176 -0.027 -0.201 -0.102  0.197 -0.027 -0.052  0.048  0.098  0.123 -0.102 -0.027 -0.176 -0.226  0.048 -0.002 -0.151 -0.151 -0.127 -0.002 -0.002 -0.077 -0.127  0.098 -0.201 -0.077 -0.102  0.023 -0.151 -0.077  0.023  0.671  0.272  0.272 -0.027  0.098  0.247  0.197  0.671  0.720  0.048 -0.002  0.098  0.322  0.596  0.571  0.671 -0.052  0.596 -0.052  0.671 -0.027 -0.077  0.496 -0.151  0.123  0.147  0.123  0.048  0.048  0.596  0.048  0.172  0.147  0.147 -0.077  0.297  0.745 -0.151 -0.002  0.347  0.745  0.247  0.172  0.048  0.098 -0.102  0.147  0.247  0.671 
 0.387 -0.087 -0.211 -0.037 -0.087 -0.137 -0.236 -0.112 -0.112 -0.112  0.162  0.088 -0.112  0.013  0.138 -0.186 -0.037 -0.062  0.013 -0.186 -0.161  0.013 -0.186 -0.112  0.187 -0.037 -0.037  0.063  0.113  0.113 -0.087 -0.037 -0.211 -0.236  0.063 -0.037 -0.137 -0.137 -0.137 -0.012 -0.012 -0.112 -0.137  0.088 -0.186 -0.087 -0.112  0.013 -0.161 -0.087  0.038  0.661  0.312  0.262 -0.037  0.113  0.237  0.212  0.661  0.710  0.038  0.063  0.138  0.312  0.611  0.586  0.661 -0.062  0.561 -0.062  0.710 -0.012 -0.062  0.486 -0.161  0.113  0.113  0.113  0.038  0.038  0.586  0.162  0.187  0.162  0.212 -0.087  0.312  0.735 -0.112  0.013  0.337  0.710  0.262  0.212  0.088  0.113 -0.112  0.138  0.287  0.636 
 0.382 -0.066 -0.216 -0.066 -0.091 -0.166 -0.241 -0.116 -0.091 -0.116  0.183  0.108 -0.116  0.008  0.133 -0.141  0.008 -0.091  0.008 -0.191 -0.166  0.008 -0.191 -0.116  0.158 -0.041 -0.041  0.033  0.083  0.108 -0.041 -0.041 -0.241 -0.191  0.108 -0.041 -0.116 -0.116 -0.141 -0.041 -0.016 -0.141 -0.141  0.058 -0.191 -0.116 -0.091  0.033 -0.166 -0.091  0.083  0.656  0.332  0.258 -0.041  0.083  0.283  0.233  0.606  0.706  0.033  0.083  0.183  0.332  0.557  0.631  0.656 -0.016  0.557 -0.066  0.706 -0.041 -0.066  0.482 -0.166  0.108  0.108  0.108  0.033  0.083  0.557  0.158  0.233  0.208  0.283 -0.091  0.332  0.706 -0.116  0.083  0.332  0.706  0.307  0.233  0.133  0.083 -0.116  0.158  0.332  0.631 
 0.376 -0.073 -0.222 -0.048 -0.098 -0.172 -0.247 -0.123 -0.098 -0.098  0.176  0.102 -0.123 -0.023  0.151 -0.123  0.027 -0.098  0.002 -0.197 -0.172  0.052 -0.197 -0.123  0.151 -0.048 -0.048  0.027  0.102  0.102 -0.048 -0.073 -0.247 -0.197  0.127 -0.048 -0.123 -0.123 -0.147 -0.048 -0.023 -0.147 -0.123  0.052 -0.197 -0.123 -0.098  0.027 -0.147 -0.098  0.077  0.650  0.326  0.251 -0.023  0.077  0.326  0.226  0.600  0.700  0.052  0.077  0.201  0.376  0.525  0.625  0.650 -0.023  0.575 -0.073  0.700 -0.048 -0.073  0.475 -0.147  0.102  0.102  0.102  0.052  0.102  0.525  0.151  0.326  0.226  0.301 -0.073  0.326  0.700 -0.123  0.127  0.326  0.700  0.326  0.301  0.176  0.077 -0.123  0.151  0.326  0.600 
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 0.335 -0.064 -0.188 -0.064 -0.114 -0.163 -0.263 -0.163 -0.089 -0.089  0.160  0.136 -0.213 -0.014  0.185 -0.064  0.086 -0.114  0.011 -0.213 -0.238  0.136 -0.238 -0.114  0.160 -0.039 -0.089  0.011  0.160  0.011 -0.039 -0.163 -0.238 -0.213  0.160 -0.064 -0.163 -0.114 -0.114 -0.139  0.011 -0.163 -0.089  0.086 -0.213 -0.163 -0.089  0.011 -0.163 -0.163  0.136  0.634  0.235  0.210  0.011  0.061  0.360  0.185  0.609  0.684  0.036  0.210  0.260  0.360  0.459  0.584  0.634 -0.014  0.559 -0.114  0.634  0.011  0.061  0.484 -0.139  0.111  0.086  0.086  0.136  0.136  0.484  0.185  0.410  0.310  0.285 -0.089  0.285  0.659 -0.089  0.185  0.310  0.684  0.310  0.410  0.210  0.011 -0.139  0.160  0.310  0.634 
 0.334 -0.064 -0.189 -0.064 -0.114 -0.164 -0.264 -0.164 -0.089 -0.089  0.160  0.135 -0.239 -0.014  0.185 -0.064  0.085 -0.114  0.010 -0.214 -0.239  0.135 -0.239 -0.114  0.160 -0.039 -0.089 -0.014  0.135  0.010 -0.039 -0.164 -0.264 -0.214  0.160 -0.064 -0.164 -0.114 -0.114 -0.139  0.010 -0.164 -0.089  0.085 -0.214 -0.164 -0.089  0.010 -0.164 -0.164  0.160  0.633  0.235  0.185 -0.014  0.085  0.359  0.185  0.583  0.683  0.035  0.260  0.260  0.359  0.459  0.583  0.633 -0.014  0.534 -0.114  0.633  0.010  0.060  0.484 -0.139  0.110  0.085  0.085  0.185  0.135  0.484  0.185  0.409  0.309  0.284 -0.064  0.284  0.658 -0.089  0.185  0.309  0.683  0.309  0.409  0.210  0.035 -0.139  0.160  0.309  0.633 
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 0.333 -0.066 -0.190 -0.041 -0.116 -0.190 -0.265 -0.165 -0.091 -0.091  0.183  0.134 -0.240 -0.016  0.183 -0.066  0.109 -0.116  0.009 -0.215 -0.240  0.134 -0.240 -0.116  0.158 -0.041 -0.091 -0.016  0.134  0.009 -0.041 -0.190 -0.265 -0.215  0.158 -0.066 -0.165 -0.116 -0.116 -0.141  0.009 -0.165 -0.091  0.109 -0.215 -0.165 -0.091  0.009 -0.165 -0.165  0.158  0.632  0.233  0.158 -0.016  0.134  0.383  0.183  0.582  0.682  0.034  0.258  0.233  0.358  0.457  0.582  0.632  0.009  0.507 -0.141  0.632  0.009  0.109  0.482 -0.116  0.158  0.084  0.084  0.208  0.134  0.482  0.158  0.408  0.308  0.283 -0.041  0.308  0.657 -0.091  0.183  0.308  0.682  0.308  0.408  0.208  0.059 -0.141  0.158  0.333  0.632 
 0.331 -0.067 -0.192 -0.042 -0.117 -0.192 -0.267 -0.167 -0.092 -0.092  0.182  0.132 -0.242  0.007  0.182 -0.067  0.132 -0.117  0.007 -0.217 -0.242  0.157 -0.242 -0.117  0.157 -0.067 -0.092 -0.017  0.132  0.007 -0.042 -0.192 -0.267 -0.217  0.157 -0.067 -0.167 -0.142 -0.117 -0.142  0.007 -0.167 -0.092  0.107 -0.192 -0.167 -0.092  0.007 -0.167 -0.167  0.157  0.630  0.207  0.157  0.007  0.182  0.381  0.182  0.580  0.680  0.057  0.257  0.232  0.356  0.456  0.580  0.630  0.007  0.481 -0.142  0.630  0.007  0.132  0.481 -0.117  0.182  0.082  0.082  0.207  0.132  0.481  0.157  0.431  0.306  0.282 -0.042  0.306  0.655 -0.092  0.207  0.306  0.680  0.306  0.381  0.207  0.057 -0.142  0.157  0.331  0.630 
 0.222 -0.027 -0.151 -0.052 -0.052 -0.151 -0.226 -0.151 -0.077 -0.077  0.197  0.073 -0.201  0.023  0.123 -0.027  0.147 -0.077  0.048 -0.176 -0.226  0.098 -0.176 -0.052  0.098 -0.077 -0.077 -0.052  0.123 -0.002 -0.002 -0.226 -0.201 -0.151  0.098 -0.002 -0.176 -0.127 -0.077 -0.151 -0.052 -0.102 -0.077  0.123 -0.176 -0.201 -0.077 -0.027 -0.151 -0.102  0.172  0.671  0.172  0.123  0.023  0.172  0.422  0.123  0.496  0.696  0.073  0.197  0.147  0.222  0.397  0.521  0.671 -0.002  0.446 -0.102  0.646  0.048  0.123  0.422 -0.127  0.172  0.023  0.023  0.272  0.123  0.471  0.123  0.422  0.322  0.272 -0.052  0.347  0.646 -0.052  0.222  0.272  0.621  0.247  0.322  0.147  0.048 -0.127  0.073  0.297  0.646 
 0.139 -0.011 -0.111 -0.061 -0.011 -0.061 -0.136 -0.086 -0.011 -0.111  0.064 -0.011 -0.136  0.014  0.089 -0.036  0.014 -0.036  0.114 -0.086 -0.160  0.014 -0.136 -0.086  0.114 -0.036 -0.011 -0.036  0.089 -0.061  0.064 -0.136 -0.160 -0.111  0.089  0.039 -0.086 -0.111 -0.061 -0.136 -0.011 -0.061 -0.061  0.114 -0.111 -0.111 -0.111 -0.036 -0.086 -0.036  0.163  0.612  0.213  0.163  0.039  0.064  0.338  0.139  0.487  0.662  0.039  0.114  0.089  0.139  0.388  0.462  0.587  0.039  0.487 -0.086  0.637  0.014 -0.011  0.263 -0.111  0.139  0.014 -0.061  0.089  0.064  0.512  0.039  0.238  0.288  0.213 -0.036  0.338  0.612 -0.061  0.139  0.313  0.637  0.263  0.213  0.114  0.039 -0.061  0.064  0.263  0.637 
 0.178  0.003 -0.096 -0.046  0.003 -0.046 -0.121 -0.071 -0.046 -0.096  0.003 -0.021 -0.121  0.003  0.028 -0.021  0.003  0.003  0.103 -0.096 -0.146 -0.021 -0.146 -0.096  0.053 -0.021  0.003 -0.046  0.103 -0.021  0.028 -0.121 -0.146 -0.121  0.078  0.028 -0.071 -0.096 -0.071 -0.121  0.003 -0.046 -0.046  0.103 -0.096 -0.096 -0.121 -0.046 -0.121  0.003  0.178  0.576  0.228  0.128  0.028  0.103  0.327  0.153  0.502  0.651  0.028  0.103  0.078  0.153  0.427  0.427  0.527  0.003  0.502 -0.071  0.651  0.003 -0.096  0.228 -0.096  0.103  0.028 -0.046  0.078  0.078  0.527  0.028  0.153  0.228  0.153  0.003  0.278  0.626 -0.071  0.128  0.302  0.576  0.253  0.078  0.128  0.028 -0.046  0.078  0.278  0.626 
 0.159  0.035 -0.090 -0.065  0.010 -0.040 -0.090 -0.065 -0.040 -0.065  0.010 -0.040 -0.090 -0.015 -0.040 -0.015 -0.015  0.060  0.085 -0.065 -0.115 -0.015 -0.115 -0.065  0.060 -0.015  0.010 -0.015  0.110  0.010 -0.015 -0.090 -0.115 -0.115  0.085  0.010 -0.040 -0.090 -0.065 -0.090  0.060 -0.015 -0.040  0.085 -0.065 -0.090 -0.115 -0.040 -0.090 -0.015  0.159  0.533  0.259  0.159  0.010  0.135  0.284  0.159  0.458  0.708  0.010 -0.015  0.085  0.135  0.433  0.334  0.483  0.035  0.483 -0.040  0.458 -0.065 -0.090  0.110 -0.065  0.085  0.060 -0.065  0.035  0.010  0.583  0.010  0.060  0.135  0.060  0.035  0.234  0.533 -0.065  0.035  0.284  0.583  0.259 -0.015  0.060  0.010 -0.040  0.060  0.184  0.633 
 0.146  0.047 -0.078 -0.078  0.022 -0.028 -0.103 -0.078 -0.028 -0.053 -0.003 -0.028 -0.103 -0.003 -0.053 -0.053 -0.003  0.047  0.097 -0.078 -0.103 -0.003 -0.103 -0.053  0.072 -0.003 -0.003  0.022  0.072  0.022 -0.078 -0.078 -0.103 -0.103  0.072 -0.003 -0.078 -0.078 -0.053 -0.053  0.072 -0.028 -0.028  0.097 -0.078 -0.078 -0.103 -0.028 -0.078 -0.003  0.097  0.470  0.271  0.196  0.022  0.146  0.271  0.171  0.445  0.719  0.022 -0.028  0.047  0.097  0.445  0.296  0.445 -0.028  0.445 -0.028  0.396 -0.053 -0.078  0.097 -0.078  0.022  0.072 -0.053  0.022  0.022  0.595  0.022 -0.028  0.047  0.072  0.022  0.221  0.495 -0.053 -0.003  0.196  0.645  0.196 -0.003 -0.003  0.022 -0.028  0.047  0.196  0.545 
 0.137  0.037 -0.062 -0.062  0.012 -0.012 -0.087 -0.062 -0.037 -0.012 -0.037 -0.037 -0.087 -0.037 -0.087 -0.037 -0.037  0.062  0.062 -0.062 -0.087  0.012 -0.087 -0.062  0.087  0.012 -0.012  0.037  0.062  0.037 -0.062 -0.062 -0.087 -0.087  0.087 -0.037 -0.062 -0.062 -0.037 -0.037  0.087 -0.012 -0.012  0.037 -0.062 -0.062 -0.087 -0.037 -0.062  0.012  0.087  0.386  0.286  0.187  0.012  0.137  0.237  0.187  0.361  0.785 -0.037 -0.087  0.012  0.087  0.411  0.187  0.436 -0.037  0.436 -0.012  0.212 -0.037 -0.062  0.062 -0.062 -0.012  0.062 -0.087  0.037 -0.012  0.635 -0.012 -0.062  0.037  0.087 -0.012  0.187  0.486 -0.037 -0.062  0.212  0.660  0.162  0.012 -0.012 -0.012 -0.037  0.012  0.137  0.486 
 0.094  0.044 -0.056 -0.056 -0.031 -0.006 -0.081 -0.031 -0.031 -0.006 -0.031 -0.006 -0.081 -0.081 -0.081 -0.031 -0.031  0.044  0.044 -0.056 -0.081  0.044 -0.081 -0.056  0.069  0.019 -0.006  0.044  0.094 -0.031 -0.056 -0.056 -0.081 -0.081  0.069 -0.031 -0.056 -0.056 -0.031 -0.031  0.019 -0.006 -0.006  0.019 -0.081 -0.056 -0.081 -0.056 -0.056 -0.006  0.094  0.318  0.218  0.193  0.019  0.119  0.143  0.168  0.318  0.816 -0.031 -0.081 -0.006  0.069  0.368  0.143  0.442 -0.031  0.393 -0.031  0.168 -0.031 -0.056  0.044 -0.056 -0.031  0.069 -0.081  0.019 -0.006  0.667 -0.006 -0.056  0.019  0.094 -0.006  0.119  0.492 -0.031 -0.056  0.193  0.716  0.119  0.019 -0.031  0.019 -0.056 -0.006  0.143  0.442 
 0.103  0.053 -0.072 -0.047 -0.022  0.003 -0.072 -0.022 -0.047  0.003 -0.022  0.003 -0.072 -0.072 -0.072 -0.047 -0.022  0.053  0.003 -0.047 -0.072  0.028 -0.072 -0.072  0.053  0.003  0.003  0.053  0.103 -0.022 -0.047 -0.047 -0.072 -0.072  0.053 -0.022 -0.072 -0.047 -0.022 -0.022  0.028  0.003 -0.047  0.003 -0.072 -0.047 -0.072 -0.047 -0.047  0.003  0.078  0.252  0.177  0.103 -0.022  0.128  0.128  0.103  0.202  0.825 -0.022 -0.072  0.003  0.028  0.327  0.078  0.402 -0.022  0.402 -0.022  0.053 -0.022 -0.047  0.053 -0.047 -0.047  0.053 -0.072  0.003  0.003  0.676  0.003 -0.047  0.028  0.103 -0.072  0.128  0.451 -0.022 -0.047  0.177  0.750  0.128 -0.022 -0.022  0.028 -0.047  0.003  0.028  0.402 
 0.107  0.032 -0.067 -0.042 -0.017  0.032 -0.067 -0.017 -0.042  0.007  0.007 -0.017 -0.042 -0.067 -0.067 -0.042 -0.042  0.057  0.032 -0.017 -0.067  0.032 -0.067 -0.067  0.057  0.007  0.007  0.082  0.082 -0.017 -0.042 -0.042 -0.067 -0.067  0.057  0.007 -0.067 -0.042 -0.017  0.007  0.032  0.007 -0.042  0.007 -0.067 -0.067 -0.067 -0.042 -0.042  0.007  0.007  0.232  0.157  0.082 -0.017  0.107  0.107  0.032  0.182  0.879 -0.017 -0.067  0.007  0.007  0.257  0.057  0.331 -0.017  0.381 -0.017  0.032 -0.017 -0.042  0.057 -0.042 -0.017  0.057 -0.067  0.007  0.007  0.705  0.007 -0.042  0.007  0.082 -0.067  0.107  0.431 -0.017 -0.042  0.157  0.830  0.107  0.032 -0.017  0.007 -0.017  0.007  0.007  0.282 
 0.111  0.011 -0.063 -0.038 -0.013  0.036 -0.063 -0.013 -0.038  0.011 -0.013 -0.013 -0.038 -0.063 -0.038 -0.038 -0.038  0.036  0.036 -0.013 -0.063  0.036 -0.038 -0.038  0.036 -0.013  0.011  0.086  0.086 -0.013 -0.038 -0.038 -0.063 -0.063  0.061  0.011 -0.063 -0.038 -0.013  0.036  0.011  0.011 -0.013  0.011 -0.063 -0.063 -0.063 -0.038 -0.038 -0.013  0.011  0.086  0.136  0.086  0.011  0.036  0.086  0.011  0.186  0.933 -0.013 -0.063  0.011 -0.038  0.161  0.036  0.261 -0.038  0.360 -0.013  0.036 -0.013 -0.038  0.086 -0.038  0.011  0.036 -0.038  0.011  0.036  0.709  0.036 -0.038  0.011  0.061 -0.063  0.111  0.335 -0.013 -0.038  0.136  0.933  0.111  0.036 -0.013  0.011 -0.013  0.011 -0.013  0.261 
 0.092  0.017 -0.058 -0.033 -0.033  0.042 -0.058 -0.008 -0.058  0.017 -0.033 -0.008 -0.033 -0.058 -0.033 -0.033 -0.033  0.042 -0.008 -0.008 -0.058  0.067 -0.033 -0.033  0.042 -0.033 -0.008  0.067  0.067 -0.033 -0.033 -0.033 -0.058 -0.058  0.042  0.017 -0.058 -0.033 -0.008  0.017  0.017  0.017 -0.008  0.017 -0.058 -0.058 -0.058 -0.008 -0.033 -0.008  0.017  0.067  0.042  0.092  0.017  0.042  0.067  0.017  0.191  0.964 -0.033 -0.058  0.017 -0.033  0.067  0.042  0.142 -0.033  0.291 -0.008  0.017 -0.008 -0.033  0.092 -0.033  0.017  0.042 -0.033  0.017  0.017  0.739  0.017 -0.033  0.017  0.067 -0.058  0.117  0.241 -0.033 -0.033  0.117  0.939  0.117  0.017 -0.008  0.017 -0.008  0.017 -0.033  0.166 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.029 -0.029  0.046 -0.004 -0.004 -0.054  0.071 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054  0.021 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.004  0.021 -0.054 -0.029 -0.029 -0.004 -0.029 -0.029  0.021 -0.004  0.046  0.096  0.021 -0.004  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.046  0.021  0.096 -0.029  0.170 -0.004 -0.004 -0.004 -0.029  0.071 -0.054  0.021  0.046 -0.029  0.046  0.021  0.793  0.021 -0.029  0.046  0.071 -0.054  0.096  0.121 -0.054 -0.029  0.096  0.968  0.121  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028  0.022 -0.003  0.047  0.097  0.022 -0.028  0.072  0.022  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022  0.022 -0.028  0.097 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022  0.022 -0.028  0.047  0.022  0.819  0.022 -0.028  0.047  0.047 -0.053  0.097  0.072 -0.053 -0.003  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.071  0.046 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004 -0.029  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054 -0.004  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.020 -0.004  0.020 -0.029  0.020 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.004  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054 -0.004  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.136  0.086 -0.063 -0.063 -0.038  0.011 -0.063  0.036 -0.088 -0.038 -0.013  0.061 -0.038 -0.038 -0.063 -0.063 -0.038  0.136  0.061 -0.038 -0.088  0.036 -0.063 -0.038  0.036 -0.013 -0.038  0.061  0.111 -0.013 -0.088 -0.013 -0.088 -0.088  0.036 -0.013 -0.038 -0.063 -0.013  0.011  0.061  0.011 -0.038  0.011 -0.063 -0.038 -0.063 -0.013 -0.063 -0.013  0.086  0.061  0.086  0.161  0.036 -0.038  0.111  0.111  0.310  0.933  0.011 -0.063  0.011 -0.013  0.036 -0.013  0.086 -0.013  0.161  0.011 -0.013 -0.038 -0.013  0.136 -0.063  0.036  0.111  0.011  0.061  0.036  0.933 -0.013 -0.038  0.061  0.011 -0.063  0.236  0.136 -0.063  0.036  0.211  0.933  0.285  0.036 -0.013 -0.013 -0.013  0.036  0.011  0.136 
 0.215  0.041 -0.084 -0.084  0.016 -0.034 -0.134 -0.034 -0.158 -0.084  0.016  0.041 -0.034 -0.034 -0.134 -0.084 -0.034  0.091  0.066 -0.109 -0.134  0.091 -0.109 -0.084  0.041 -0.059 -0.059  0.016  0.116 -0.034 -0.134 -0.059 -0.109 -0.158 -0.009  0.016 -0.109 -0.109 -0.059 -0.059  0.016  0.016 -0.059  0.066 -0.084 -0.059 -0.134 -0.034 -0.109 -0.059  0.165  0.165  0.190  0.290  0.116 -0.009  0.340  0.116  0.589  0.863  0.066 -0.059  0.066 -0.059  0.190  0.190  0.315 -0.009  0.464 -0.034  0.215 -0.059 -0.059  0.215 -0.109 -0.034  0.190 -0.009  0.116 -0.009  0.863 -0.059 -0.059  0.141  0.016 -0.059  0.340  0.365 -0.109  0.016  0.265  0.863  0.464  0.066 -0.034 -0.009 -0.034  0.016  0.066  0.390 
 0.248  0.023 -0.126 -0.076  0.023 -0.076 -0.176 -0.051 -0.151 -0.126  0.023  0.048 -0.051 -0.051 -0.101 -0.126 -0.026  0.048  0.073 -0.151 -0.176  0.073 -0.151 -0.101 -0.026 -0.051 -0.101 -0.026  0.098 -0.076 -0.101 -0.101 -0.151 -0.201  0.023 -0.026 -0.101 -0.126 -0.101 -0.051  0.023 -0.001 -0.101  0.073 -0.126 -0.101 -0.151 -0.026 -0.151 -0.101  0.173  0.322  0.223  0.347  0.098  0.023  0.397  0.223  0.696  0.821  0.073 -0.101  0.048 -0.026  0.273  0.297  0.372  0.023  0.571 -0.001  0.322 -0.101 -0.076  0.248 -0.151  0.023  0.173 -0.026  0.073  0.048  0.821 -0.026 -0.026  0.098 -0.001 -0.051  0.322  0.472 -0.151  0.023  0.297  0.821  0.571  0.048  0.048 -0.026 -0.076  0.023  0.223  0.497 
 0.261  0.011 -0.188 -0.063  0.086 -0.088 -0.188 -0.088 -0.163 -0.113  0.011  0.011 -0.063 -0.038 -0.013 -0.188 -0.063 -0.013  0.036 -0.188 -0.188  0.136 -0.213 -0.163 -0.013 -0.113 -0.088 -0.038  0.086 -0.113 -0.113 -0.138 -0.238 -0.263  0.036  0.011 -0.113 -0.138 -0.138 -0.063  0.011 -0.063 -0.113  0.061 -0.138 -0.113 -0.163  0.011 -0.138 -0.088  0.211  0.435  0.285  0.360  0.036  0.136  0.535  0.261  0.709  0.759  0.086 -0.063  0.011  0.036  0.410  0.535  0.584  0.036  0.609 -0.013  0.584  0.011 -0.063  0.360 -0.188  0.061  0.136  0.011  0.111  0.011  0.759  0.061  0.011  0.186 -0.013  0.061  0.360  0.659 -0.213  0.036  0.310  0.759  0.584  0.061  0.061  0.036 -0.063  0.061  0.261  0.609 
 0.272 -0.027 -0.176 -0.077  0.098 -0.077 -0.151 -0.077 -0.151 -0.127 -0.027 -0.027 -0.052 -0.027  0.048 -0.176 -0.077 -0.027  0.023 -0.176 -0.176  0.147 -0.226 -0.176  0.023 -0.127 -0.052 -0.052  0.098 -0.127 -0.127 -0.151 -0.251 -0.276  0.048  0.023 -0.102 -0.151 -0.151 -0.077 -0.002 -0.102 -0.127  0.048 -0.176 -0.102 -0.127  0.023 -0.151 -0.077  0.222  0.471  0.247  0.347 -0.002  0.172  0.571  0.322  0.696  0.745  0.098 -0.077  0.023  0.023  0.446  0.546  0.596  0.023  0.596 -0.027  0.646 -0.002 -0.102  0.422 -0.201  0.073  0.098 -0.002  0.123  0.023  0.720  0.098  0.023  0.272 -0.002  0.048  0.372  0.646 -0.176  0.048  0.297  0.720  0.546  0.098  0.073  0.048 -0.077  0.073  0.372  0.671 
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 0.129  0.029 -0.070 -0.070  0.004  0.004 -0.070 -0.070 -0.045 -0.020 -0.020 -0.045 -0.070 -0.020 -0.070 -0.020 -0.020  0.029  0.054 -0.070 -0.095  0.004 -0.095 -0.070  0.079  0.004  0.029  0.029  0.079  0.029 -0.045 -0.070 -0.095 -0.095  0.079 -0.020 -0.045 -0.070 -0.045 -0.070  0.029 -0.020 -0.020  0.054 -0.070 -0.070 -0.095 -0.045 -0.045  0.004  0.129  0.353  0.279  0.179  0.029  0.104  0.328  0.129  0.503  0.752  0.029  0.004  0.029  0.104  0.303  0.279  0.428 -0.020  0.453 -0.020  0.403 -0.045 -0.070  0.029 -0.070 -0.020  0.054 -0.095  0.079  0.004  0.627  0.004 -0.045  0.079  0.079  0.079  0.179  0.428 -0.045  0.029  0.229  0.627  0.229  0.004  0.004  0.004 -0.045  0.029  0.104  0.403 
 0.143  0.043 -0.056 -0.056  0.018 -0.006 -0.056 -0.056 -0.031 -0.006 -0.031 -0.006 -0.006 -0.056 -0.081 -0.031 -0.031  0.043  0.043 -0.056 -0.081  0.018 -0.081 -0.056  0.093  0.018 -0.006  0.068  0.068  0.018 -0.056 -0.056 -0.056 -0.081  0.043 -0.006 -0.056 -0.056 -0.031 -0.031  0.018 -0.006 -0.006  0.018 -0.081 -0.056 -0.081 -0.056 -0.056  0.018  0.068  0.268  0.292  0.243  0.043  0.043  0.292  0.093  0.392  0.841 -0.006 -0.031  0.043  0.093  0.292  0.193  0.342 -0.056  0.442 -0.006  0.218 -0.031 -0.056  0.043 -0.056 -0.031  0.068 -0.081  0.018 -0.006  0.641  0.018 -0.056  0.068  0.093 -0.006  0.143  0.392 -0.031 -0.031  0.218  0.691  0.168  0.018 -0.006 -0.006 -0.006 -0.006  0.118  0.392 
 0.152  0.052 -0.047 -0.047  0.027  0.002 -0.072 -0.047 -0.047  0.002  0.002  0.002 -0.022 -0.072 -0.072 -0.022 -0.022  0.027  0.027 -0.022 -0.072  0.002 -0.072 -0.047  0.102  0.027  0.002  0.077  0.077  0.002 -0.047 -0.047 -0.047 -0.072  0.052 -0.022 -0.047 -0.047 -0.022 -0.022  0.002  0.002  0.002  0.002 -0.072 -0.047 -0.072 -0.047 -0.047 -0.022  0.027  0.252  0.227  0.202  0.002  0.027  0.177  0.102  0.252  0.874 -0.022 -0.072  0.027  0.002  0.277  0.127  0.326 -0.047  0.451 -0.022  0.152 -0.022 -0.047  0.052 -0.047 -0.047  0.077 -0.072  0.027  0.002  0.650  0.002 -0.047  0.027  0.102 -0.022  0.152  0.376 -0.022 -0.047  0.177  0.725  0.127  0.027 -0.022  0.002  0.002  0.002  0.102  0.326 
 0.109  0.034 -0.065 -0.040 -0.015  0.009 -0.065 -0.015 -0.040  0.009  0.009 -0.015 -0.015 -0.065 -0.065 -0.040 -0.015  0.034  0.034 -0.015 -0.065  0.034 -0.065 -0.065  0.059  0.034  0.009  0.084  0.084 -0.015 -0.040 -0.040 -0.040 -0.065  0.059 -0.015 -0.065 -0.040 -0.015 -0.015  0.009  0.009 -0.040 -0.015 -0.065 -0.040 -0.065 -0.040 -0.040 -0.015  0.034  0.184  0.134  0.134 -0.015  0.009  0.109  0.084  0.209  0.881 -0.015 -0.065  0.009 -0.040  0.159  0.084  0.259 -0.040  0.433 -0.015  0.084 -0.015 -0.040  0.059 -0.040 -0.015  0.059 -0.065  0.009  0.009  0.707  0.009 -0.040  0.009  0.109 -0.065  0.134  0.333 -0.015 -0.040  0.184  0.832  0.109  0.084 -0.015  0.009 -0.015  0.009  0.059  0.284 
 0.090  0.040 -0.060 -0.035 -0.010  0.015 -0.060 -0.010 -0.035  0.015  0.015 -0.010 -0.035 -0.060 -0.060 -0.035 -0.010  0.040  0.040 -0.010 -0.060  0.040 -0.035 -0.035  0.040 -0.010  0.015  0.065  0.090 -0.010 -0.060 -0.035 -0.060 -0.060  0.065 -0.010 -0.060 -0.035 -0.010 -0.010  0.015  0.015 -0.035 -0.010 -0.060 -0.060 -0.060 -0.035 -0.035 -0.035  0.015  0.140  0.115  0.090 -0.010 -0.010  0.090  0.065  0.140  0.887 -0.010 -0.060 -0.010 -0.035  0.140  0.040  0.189 -0.035  0.364  0.015  0.065 -0.010 -0.035  0.040 -0.035 -0.010  0.065 -0.060  0.015  0.015  0.712  0.040 -0.035  0.015  0.090 -0.060  0.140  0.314 -0.010 -0.035  0.164  0.862  0.115  0.065 -0.010  0.015 -0.010  0.015  0.015  0.189 
 0.072  0.022 -0.053 -0.028 -0.028  0.022 -0.053 -0.003 -0.053  0.022 -0.028 -0.003 -0.028 -0.053 -0.028 -0.028 -0.028  0.047 -0.003 -0.003 -0.053  0.072 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053  0.022 -0.003 -0.053 -0.028 -0.003  0.022 -0.003  0.022 -0.003 -0.003 -0.053 -0.053 -0.053 -0.003 -0.028 -0.028  0.022 -0.003  0.047  0.097  0.022 -0.003  0.072  0.022  0.146  0.969 -0.028 -0.053 -0.003 -0.028  0.047  0.022  0.097 -0.028  0.221 -0.003  0.022 -0.003 -0.028  0.072 -0.028  0.022  0.047 -0.028  0.022  0.022  0.719  0.022 -0.028  0.022  0.072 -0.053  0.122  0.146 -0.053 -0.028  0.097  0.944  0.122  0.022 -0.003 -0.003 -0.003  0.022 -0.028  0.097 
 0.073  0.023 -0.052 -0.027 -0.027  0.023 -0.052 -0.002 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.027 -0.027  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.052 -0.027 -0.052 -0.052  0.023 -0.002 -0.027 -0.027 -0.002  0.023 -0.002  0.023 -0.027 -0.002 -0.052 -0.027 -0.052 -0.027 -0.027 -0.027  0.023 -0.027  0.048  0.098  0.023 -0.002  0.073  0.023  0.147  0.970 -0.027 -0.027 -0.002 -0.027  0.023  0.023  0.048 -0.027  0.123 -0.002 -0.002 -0.002 -0.027  0.073 -0.052  0.023  0.023 -0.027  0.023  0.023  0.745  0.023 -0.027  0.048  0.048 -0.052  0.098  0.073 -0.052 -0.027  0.098  0.970  0.123  0.023 -0.002 -0.002 -0.002  0.023 -0.027  0.098 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.022 -0.002  0.022 -0.027  0.022 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027  0.022 -0.027  0.047  0.097  0.022 -0.027  0.072  0.022  0.147  0.969 -0.027 -0.027 -0.002 -0.027  0.022  0.022 -0.002 -0.027  0.072 -0.002 -0.002 -0.002 -0.027  0.072 -0.052  0.022 -0.002 -0.027  0.047  0.022  0.820  0.022 -0.027  0.047  0.022 -0.052  0.097  0.047 -0.052 -0.027  0.097  0.969  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028  0.021 -0.028  0.046  0.096  0.021 -0.028  0.071  0.021  0.146  0.968 -0.028 -0.028 -0.003 -0.028  0.021  0.021 -0.003 -0.028  0.071 -0.003 -0.003 -0.003 -0.028  0.071 -0.053  0.021 -0.003 -0.028  0.046  0.021  0.868  0.021 -0.028  0.046  0.021 -0.053  0.096  0.046 -0.053 -0.003  0.096  0.968  0.096  0.046 -0.003 -0.003 -0.003  0.021 -0.003  0.096 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.004 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029  0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.029  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054 -0.004  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.004 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029  0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.029  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054 -0.004  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.180  0.006 -0.069 -0.044 -0.044 -0.019 -0.019  0.006 -0.094 -0.019 -0.069  0.006 -0.019 -0.019 -0.069 -0.094 -0.069  0.056 -0.044 -0.044 -0.069  0.056 -0.069 -0.069  0.081 -0.019 -0.044  0.056  0.081 -0.019 -0.069 -0.019 -0.094 -0.094 -0.019  0.006 -0.069 -0.044 -0.019 -0.019 -0.019  0.006 -0.044  0.056 -0.044  0.006 -0.069 -0.019 -0.044  0.006  0.081  0.031  0.180  0.180  0.006  0.031  0.106  0.031  0.454  0.928  0.006 -0.069  0.006 -0.044  0.155  0.106  0.081 -0.069  0.305 -0.019  0.106  0.006 -0.044  0.131 -0.069 -0.019  0.031 -0.019  0.031  0.006  0.928  0.056 -0.069  0.056  0.031 -0.094  0.155  0.180 -0.094  0.031  0.230  0.928  0.106  0.006 -0.044  0.031 -0.019  0.006  0.006  0.230 
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 0.268  0.044 -0.155 -0.081 -0.056 -0.031 -0.155 -0.056 -0.155 -0.131 -0.006  0.044 -0.056 -0.056 -0.006 -0.155 -0.081  0.019  0.019 -0.155 -0.155  0.069 -0.155 -0.106  0.119 -0.056 -0.081 -0.006  0.119 -0.056 -0.081 -0.081 -0.180 -0.205 -0.031  0.019 -0.131 -0.081 -0.131 -0.031 -0.006 -0.081 -0.081  0.069 -0.131 -0.031 -0.106 -0.006 -0.106 -0.081  0.069  0.193  0.318  0.442 -0.031  0.094  0.293  0.019  0.692  0.816  0.119 -0.081  0.069  0.044  0.343  0.343  0.268 -0.031  0.592 -0.056  0.368 -0.031 -0.031  0.368 -0.180 -0.006  0.044 -0.031  0.094 -0.006  0.816  0.119 -0.056  0.218  0.019 -0.056  0.318  0.542 -0.155  0.044  0.368  0.816  0.368  0.119 -0.081  0.069 -0.031 -0.031  0.168  0.567 
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 0.294 -0.079 -0.229 -0.054 -0.054 -0.129 -0.254 -0.154 -0.129 -0.104  0.095 -0.004 -0.179  0.045  0.070 -0.129 -0.004 -0.104 -0.004 -0.229 -0.254  0.095 -0.229 -0.254  0.020 -0.154 -0.104 -0.154  0.120 -0.104 -0.054 -0.229 -0.303 -0.254  0.070 -0.104 -0.154 -0.179 -0.079 -0.204 -0.004 -0.179 -0.129  0.020 -0.054 -0.104 -0.229 -0.104 -0.229 -0.129  0.120  0.618  0.195  0.145  0.070  0.319  0.469  0.170  0.668  0.643  0.220  0.245  0.120  0.120  0.369  0.494  0.593  0.145  0.419 -0.129  0.618  0.070  0.270  0.270 -0.204  0.394 -0.004  0.070  0.394 -0.004  0.519  0.020  0.419  0.519  0.245  0.120  0.319  0.643 -0.104  0.593  0.245  0.643  0.394  0.319  0.095  0.270 -0.204  0.095  0.220  0.618 
 0.223 -0.051 -0.175 -0.026 -0.051 -0.076 -0.200 -0.126 -0.101 -0.101  0.074  0.024 -0.175  0.074 -0.026 -0.076 -0.051 -0.051 -0.026 -0.150 -0.225  0.148 -0.175 -0.175  0.049 -0.126 -0.076 -0.126  0.173 -0.101 -0.001 -0.200 -0.250 -0.175  0.049 -0.051 -0.101 -0.126 -0.051 -0.175 -0.001 -0.101 -0.126  0.024 -0.001 -0.101 -0.250 -0.076 -0.150 -0.076  0.099  0.547  0.148  0.198  0.074  0.173  0.373  0.198  0.597  0.697  0.099  0.298  0.124  0.049  0.398  0.373  0.547  0.173  0.373 -0.076  0.572 -0.001  0.148  0.124 -0.200  0.373 -0.026 -0.001  0.373  0.024  0.497 -0.001  0.273  0.522  0.273  0.024  0.298  0.597 -0.026  0.522  0.248  0.697  0.323  0.248  0.074  0.198 -0.126  0.148  0.198  0.672 
 0.144 -0.005 -0.105 -0.080 -0.005 -0.005 -0.130 -0.105 -0.080 -0.105  0.045 -0.005 -0.130  0.045  0.045 -0.055 -0.030 -0.030  0.045 -0.130 -0.130  0.070 -0.130 -0.105  0.095 -0.055 -0.005 -0.030  0.120 -0.030 -0.030 -0.130 -0.154 -0.105  0.020  0.020 -0.055 -0.105 -0.005 -0.130 -0.005 -0.030 -0.080  0.045 -0.055 -0.080 -0.154 -0.030 -0.105 -0.055  0.144  0.518  0.169  0.169  0.070  0.095  0.319  0.169  0.568  0.693  0.070  0.070  0.045  0.120  0.468  0.344  0.394  0.169  0.419 -0.030  0.568 -0.030 -0.005  0.120 -0.130  0.244  0.020 -0.005  0.269  0.045  0.543 -0.005  0.120  0.419  0.194 -0.030  0.194  0.394 -0.105  0.394  0.294  0.668  0.269  0.169  0.095  0.070 -0.055  0.144  0.169  0.693 
 0.141  0.016 -0.084 -0.084  0.016  0.016 -0.134 -0.084 -0.084 -0.059  0.041 -0.009 -0.134  0.066 -0.034 -0.034 -0.009  0.016  0.016 -0.109 -0.109  0.066 -0.109 -0.109  0.091 -0.034 -0.009 -0.009  0.091 -0.009 -0.059 -0.109 -0.134 -0.084  0.041  0.041 -0.034 -0.084 -0.009 -0.134 -0.009 -0.009 -0.059  0.066 -0.059 -0.059 -0.134 -0.009 -0.109 -0.034  0.165  0.464  0.190  0.215  0.016  0.091  0.290  0.141  0.489  0.713  0.016  0.041  0.041  0.141  0.439  0.315  0.415  0.091  0.390 -0.009  0.589 -0.059 -0.034  0.116 -0.109  0.165 -0.009 -0.059  0.240  0.041  0.589  0.016  0.041  0.315  0.141 -0.034  0.215  0.390 -0.084  0.340  0.240  0.639  0.165  0.091  0.116  0.066 -0.034  0.116  0.165  0.689 
 0.142  0.017 -0.083 -0.058  0.017 -0.033 -0.108 -0.058 -0.058 -0.033  0.017 -0.058 -0.108  0.017 -0.058 -0.008 -0.033  0.042  0.042 -0.083 -0.108 -0.008 -0.108 -0.083  0.067 -0.008 -0.008  0.017  0.067  0.017 -0.033 -0.083 -0.108 -0.108  0.067  0.042 -0.033 -0.058 -0.033 -0.108 -0.008 -0.008 -0.033  0.067 -0.058 -0.033 -0.108 -0.058 -0.083 -0.008  0.142  0.416  0.241  0.191 -0.008  0.117  0.216  0.117  0.440  0.764 -0.008 -0.008 -0.008  0.092  0.391  0.216  0.440  0.042  0.391 -0.008  0.490 -0.058 -0.083  0.067 -0.083  0.042  0.017 -0.058  0.067  0.017  0.640  0.042 -0.008  0.291  0.067 -0.008  0.142  0.341 -0.058  0.216  0.241  0.640  0.166  0.092  0.042 -0.008 -0.008  0.117  0.166  0.714 
 0.125  0.025 -0.074 -0.024  0.025 -0.024 -0.099 -0.074 -0.074 -0.024  0.000 -0.049 -0.099  0.025 -0.049 -0.049 -0.024  0.050  0.000 -0.074 -0.099  0.000 -0.099 -0.074  0.075  0.000  0.000  0.025  0.075  0.000 -0.024 -0.074 -0.099 -0.099  0.050  0.050 -0.074 -0.049 -0.024 -0.099  0.000  0.000 -0.049  0.075 -0.099 -0.049 -0.099 -0.049 -0.074  0.000  0.125  0.374  0.200  0.200 -0.024  0.125  0.200  0.100  0.449  0.798  0.000 -0.024  0.000  0.075  0.399  0.200  0.424  0.000  0.399 -0.049  0.399 -0.049 -0.074  0.075 -0.074  0.000  0.000 -0.074  0.050  0.000  0.648  0.050 -0.024  0.225  0.075 -0.024  0.125  0.299 -0.049  0.075  0.250  0.648  0.150  0.050 -0.024  0.000 -0.024  0.075  0.150  0.673 
 0.091  0.016 -0.059 -0.009 -0.009 -0.009 -0.084 -0.034 -0.059 -0.009 -0.059 -0.034 -0.084 -0.059 -0.084 -0.034 -0.009  0.091 -0.009 -0.059 -0.084  0.041 -0.084 -0.059  0.091 -0.009  0.016  0.041  0.066 -0.009 -0.009 -0.059 -0.084 -0.084  0.041 -0.009 -0.059 -0.059 -0.034 -0.059  0.041 -0.009 -0.034  0.016 -0.084 -0.059 -0.084 -0.034 -0.059 -0.009  0.091  0.190  0.190  0.165 -0.009  0.066  0.190  0.066  0.439  0.813 -0.009 -0.009 -0.009  0.066  0.340  0.116  0.390 -0.059  0.415 -0.034  0.215 -0.034 -0.059  0.066 -0.059 -0.034  0.041 -0.084  0.041 -0.009  0.664  0.016 -0.034  0.116  0.091 -0.034  0.141  0.265 -0.034 -0.009  0.165  0.738  0.141  0.016 -0.034 -0.009 -0.034  0.041  0.141  0.664 
 0.075  0.025 -0.074  0.000 -0.024  0.000 -0.074 -0.024 -0.049  0.000 -0.049 -0.024 -0.074 -0.049 -0.074 -0.024 -0.024  0.075  0.000 -0.049 -0.074  0.050 -0.074 -0.049  0.050  0.000  0.025  0.050  0.075  0.000  0.000 -0.049 -0.074 -0.074  0.025  0.000 -0.074 -0.049 -0.024 -0.049  0.050  0.000 -0.024  0.025 -0.074 -0.049 -0.074 -0.024 -0.049 -0.024  0.075  0.100  0.100  0.125 -0.024  0.050  0.175  0.025  0.324  0.823 -0.024 -0.049  0.000  0.050  0.275  0.125  0.399 -0.049  0.349 -0.049  0.150 -0.024 -0.049  0.050 -0.049  0.000  0.025 -0.074  0.025  0.000  0.673  0.000 -0.049  0.075  0.075 -0.049  0.150  0.250 -0.024 -0.024  0.150  0.798  0.125  0.050 -0.024  0.000 -0.024  0.000  0.075  0.648 
 0.081  0.031 -0.069  0.006 -0.019  0.006 -0.069 -0.019 -0.069  0.006 -0.044 -0.019 -0.044 -0.069 -0.044 -0.019 -0.019  0.081  0.031 -0.044 -0.069  0.056 -0.069 -0.044  0.056 -0.019  0.031  0.056  0.081  0.006 -0.044 -0.044 -0.069 -0.069  0.031  0.006 -0.069 -0.044 -0.019 -0.044  0.056  0.006 -0.019  0.006 -0.069 -0.069 -0.069  0.006 -0.044 -0.019  0.056  0.081  0.056  0.081 -0.019  0.056  0.106  0.006  0.155  0.903 -0.019 -0.069  0.006  0.006  0.280  0.081  0.305 -0.044  0.330 -0.044  0.081 -0.019 -0.044  0.081 -0.044  0.006  0.031 -0.069  0.031  0.006  0.704  0.006 -0.044  0.031  0.081 -0.069  0.155  0.230 -0.019 -0.044  0.155  0.853  0.155  0.056 -0.019  0.006 -0.019  0.006  0.006  0.604 
 0.084  0.009 -0.065  0.009 -0.015  0.009 -0.065 -0.015 -0.065  0.009 -0.040 -0.015 -0.040 -0.065 -0.040 -0.015 -0.015  0.084  0.009 -0.040 -0.065  0.059 -0.065 -0.040  0.034 -0.015  0.034  0.034  0.084 -0.015 -0.040 -0.040 -0.065 -0.065  0.009  0.009 -0.065 -0.040 -0.015 -0.015  0.059  0.009 -0.015  0.009 -0.065 -0.065 -0.065  0.009 -0.040 -0.015  0.059  0.034  0.059  0.084  0.009  0.059  0.109  0.009  0.159  0.931 -0.015 -0.065  0.009  0.009  0.284  0.084  0.234 -0.040  0.259 -0.040  0.059 -0.015 -0.040  0.084 -0.040  0.034  0.034 -0.040  0.034 -0.015  0.682  0.009 -0.040  0.009  0.059 -0.065  0.134  0.234 -0.040 -0.040  0.159  0.856  0.134  0.009 -0.015  0.009 -0.015  0.009 -0.040  0.582 
 0.064  0.014 -0.060 -0.010 -0.010  0.014 -0.060 -0.010 -0.060  0.014 -0.035 -0.010 -0.035 -0.060 -0.035 -0.060 -0.010  0.039 -0.010 -0.010 -0.060  0.064 -0.035 -0.035  0.039 -0.010 -0.010  0.064  0.064 -0.010 -0.035 -0.035 -0.060 -0.060 -0.010  0.014 -0.060 -0.035 -0.010  0.014 -0.010  0.014 -0.010  0.014 -0.060 -0.060 -0.060  0.014 -0.035 -0.035  0.039 -0.010  0.039  0.089  0.014  0.014  0.064  0.014  0.164  0.961 -0.035 -0.060  0.014  0.014  0.189  0.089  0.089 -0.035  0.189 -0.010  0.014 -0.010 -0.035  0.064 -0.060  0.039  0.014 -0.035  0.039  0.014  0.712  0.014 -0.035  0.014  0.039 -0.060  0.089  0.114 -0.060 -0.035  0.164  0.936  0.114  0.014 -0.010 -0.010 -0.010  0.014 -0.035  0.488 
 0.068  0.043 -0.056 -0.006 -0.031  0.018 -0.056  0.018 -0.056 -0.006 -0.031 -0.006 -0.031 -0.056 -0.031 -0.056 -0.006  0.043 -0.006 -0.006 -0.056  0.043 -0.031 -0.031  0.043 -0.006 -0.006  0.068  0.068 -0.006 -0.031 -0.031 -0.056 -0.056 -0.006  0.018 -0.056 -0.031 -0.006  0.018 -0.006  0.018 -0.031  0.043 -0.056 -0.056 -0.031 -0.006 -0.031 -0.031  0.043 -0.031  0.043  0.093  0.018 -0.006  0.068  0.018  0.168  0.965 -0.031 -0.056  0.018 -0.006  0.093  0.068  0.018 -0.031  0.118 -0.006 -0.006 -0.006 -0.031  0.068 -0.056  0.043 -0.006 -0.031  0.068  0.018  0.741  0.018 -0.031  0.018  0.018 -0.056  0.093  0.043 -0.056 -0.031  0.168  0.940  0.093  0.018 -0.006 -0.006 -0.006  0.018 -0.031  0.367 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.004 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004  0.021 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.046 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.029  0.046  0.096  0.021 -0.004  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.046  0.046 -0.004 -0.029  0.071 -0.004 -0.004 -0.004 -0.029  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.818  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054 -0.029  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.170 
 0.069  0.044 -0.055 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.005 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005  0.019 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.044 -0.055 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.005  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.044  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.030  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.916  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.144 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
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 0.324 -0.074 -0.199 -0.124  0.125 -0.099 -0.199 -0.124 -0.099 -0.099  0.025  0.000 -0.099  0.050  0.200 -0.099 -0.074 -0.124  0.025 -0.249 -0.249  0.175 -0.199 -0.199  0.025 -0.149 -0.074 -0.074  0.050 -0.074 -0.049 -0.274 -0.298 -0.249  0.150 -0.074 -0.124 -0.149 -0.049 -0.199 -0.024 -0.199 -0.124 -0.024 -0.099 -0.099 -0.199  0.000 -0.174 -0.124  0.225  0.623  0.150  0.150  0.050  0.225  0.573  0.324  0.573  0.648  0.225  0.275  0.175  0.100  0.424  0.549  0.623  0.225  0.399 -0.049  0.573  0.025  0.275  0.225 -0.224  0.299 -0.024  0.075  0.374  0.000  0.524  0.025  0.424  0.474  0.299  0.275  0.299  0.623 -0.099  0.524  0.299  0.648  0.424  0.250  0.100  0.250 -0.149  0.075  0.324  0.598 
 0.299 -0.074 -0.199 -0.124  0.125 -0.099 -0.199 -0.124 -0.099 -0.099  0.025  0.000 -0.099  0.075  0.200 -0.099 -0.074 -0.124  0.025 -0.249 -0.249  0.175 -0.224 -0.224  0.025 -0.149 -0.074 -0.074  0.050 -0.049 -0.049 -0.274 -0.298 -0.249  0.150 -0.074 -0.124 -0.149 -0.049 -0.199 -0.024 -0.199 -0.124 -0.024 -0.099 -0.099 -0.199  0.000 -0.174 -0.124  0.200  0.623  0.150  0.150  0.050  0.225  0.573  0.324  0.573  0.648  0.225  0.275  0.175  0.100  0.424  0.549  0.623  0.225  0.399 -0.099  0.573  0.025  0.275  0.225 -0.224  0.299  0.000  0.075  0.374  0.000  0.524  0.000  0.424  0.474  0.299  0.275  0.275  0.623 -0.099  0.499  0.324  0.623  0.424  0.250  0.125  0.250 -0.149  0.075  0.324  0.598 
 0.299 -0.074 -0.199 -0.099  0.100 -0.099 -0.199 -0.124 -0.099 -0.099  0.025  0.000 -0.099  0.075  0.200 -0.099 -0.024 -0.124  0.025 -0.249 -0.249  0.175 -0.224 -0.249  0.025 -0.149 -0.074 -0.074  0.050 -0.049 -0.074 -0.274 -0.298 -0.249  0.150 -0.074 -0.124 -0.149 -0.049 -0.199  0.000 -0.199 -0.124 -0.024 -0.099 -0.074 -0.199 -0.024 -0.174 -0.124  0.175  0.623  0.150  0.150  0.050  0.275  0.573  0.324  0.573  0.648  0.225  0.299  0.100  0.100  0.424  0.549  0.623  0.225  0.424 -0.124  0.573  0.000  0.275  0.225 -0.199  0.374  0.025  0.075  0.374  0.000  0.524 -0.024  0.424  0.474  0.299  0.275  0.250  0.598 -0.099  0.499  0.299  0.623  0.399  0.275  0.125  0.250 -0.124  0.075  0.299  0.598 
 0.296 -0.028 -0.152 -0.128  0.097 -0.078 -0.128 -0.177 -0.028 -0.103 -0.028  0.022 -0.103  0.047  0.072 -0.053 -0.078 -0.078  0.072 -0.202 -0.202  0.221 -0.227 -0.177  0.072 -0.128 -0.053 -0.078  0.097 -0.078 -0.028 -0.202 -0.252 -0.177  0.171 -0.053 -0.103 -0.202 -0.028 -0.177  0.022 -0.152 -0.103 -0.003 -0.078 -0.152 -0.177  0.047 -0.128 -0.103  0.221  0.645  0.171  0.097  0.072  0.221  0.595  0.271  0.595  0.595  0.171  0.221  0.047  0.097  0.445  0.520  0.595  0.146  0.445 -0.053  0.545 -0.003  0.122  0.122 -0.128  0.321  0.047 -0.028  0.371  0.022  0.520 -0.028  0.296  0.421  0.271  0.221  0.221  0.570 -0.103  0.520  0.321  0.520  0.371  0.221  0.047  0.196 -0.128  0.122  0.271  0.545 
 0.240 -0.009 -0.109 -0.084  0.041 -0.009 -0.109 -0.109 -0.034 -0.084 -0.009 -0.009 -0.134 -0.009  0.041 -0.009 -0.059 -0.034  0.041 -0.109 -0.134  0.091 -0.134 -0.084  0.091 -0.059  0.016 -0.034  0.116 -0.034  0.066 -0.134 -0.158 -0.109  0.116  0.016 -0.084 -0.134 -0.034 -0.134 -0.034 -0.059 -0.059  0.016 -0.059 -0.109 -0.134 -0.009 -0.059 -0.034  0.240  0.564  0.240  0.116  0.091  0.041  0.564  0.116  0.539  0.614  0.141  0.041  0.041  0.141  0.415  0.464  0.514  0.116  0.464 -0.059  0.539 -0.009 -0.034  0.066 -0.109  0.165  0.016 -0.059  0.315  0.041  0.539 -0.009  0.190  0.464  0.215  0.116  0.215  0.489 -0.059  0.365  0.340  0.439  0.265  0.091  0.041  0.091 -0.059  0.041  0.265  0.564 
 0.212  0.013 -0.087 -0.062  0.013 -0.012 -0.112 -0.087 -0.062 -0.087 -0.012 -0.012 -0.112  0.013  0.038 -0.012 -0.037 -0.037  0.038 -0.087 -0.137  0.063 -0.137 -0.112  0.063 -0.037  0.038  0.013  0.113 -0.037  0.038 -0.112 -0.137 -0.112  0.063  0.038 -0.062 -0.112 -0.037 -0.137 -0.062 -0.012 -0.062  0.013 -0.087 -0.087 -0.137 -0.012 -0.062 -0.037  0.212  0.511  0.187  0.138  0.113  0.038  0.412  0.138  0.536  0.636  0.138  0.038  0.038  0.113  0.387  0.461  0.511  0.063  0.412 -0.062  0.536 -0.012 -0.037  0.013 -0.112  0.138 -0.012 -0.062  0.287  0.038  0.561  0.013  0.113  0.486  0.187  0.063  0.212  0.436 -0.062  0.262  0.362  0.536  0.212  0.038  0.038  0.013 -0.037  0.063  0.162  0.486 
 0.162  0.012 -0.062 -0.062 -0.012 -0.012 -0.087 -0.062 -0.037 -0.062 -0.012 -0.062 -0.087 -0.012 -0.037 -0.012 -0.012 -0.012  0.062 -0.062 -0.112  0.062 -0.112 -0.087  0.062 -0.012  0.062  0.037  0.112 -0.012  0.037 -0.087 -0.112 -0.112  0.087 -0.037 -0.037 -0.087 -0.062 -0.112 -0.062  0.012 -0.037  0.012 -0.062 -0.062 -0.112  0.012 -0.087 -0.012  0.212  0.486  0.212  0.162  0.037  0.062  0.336  0.137  0.561  0.660  0.087 -0.012  0.037  0.112  0.361  0.486  0.461  0.062  0.386 -0.037  0.536 -0.062 -0.087 -0.012 -0.087  0.012  0.012 -0.062  0.112  0.012  0.561  0.037  0.062  0.411  0.062  0.012  0.162  0.361 -0.037  0.162  0.311  0.561  0.137 -0.012  0.037 -0.012 -0.037  0.062  0.187  0.486 
 0.098  0.023 -0.052 -0.052 -0.027 -0.002 -0.102 -0.077 -0.052 -0.052 -0.027 -0.052 -0.102 -0.002 -0.027 -0.027 -0.002 -0.002  0.073 -0.077 -0.102  0.048 -0.102 -0.077  0.073 -0.002  0.073  0.048  0.073 -0.027  0.023 -0.077 -0.102 -0.102  0.098 -0.027 -0.027 -0.077 -0.077 -0.102 -0.077 -0.027 -0.027  0.023 -0.077 -0.052 -0.102 -0.002 -0.077 -0.002  0.222  0.496  0.222  0.147  0.023  0.073  0.297  0.147  0.546  0.696  0.073 -0.002  0.048  0.098  0.347  0.496  0.446  0.048  0.397 -0.027  0.422 -0.052 -0.077 -0.002 -0.077 -0.002  0.023 -0.077  0.098 -0.027  0.546  0.023 -0.002  0.272  0.073  0.023  0.172  0.322 -0.027  0.048  0.272  0.571  0.123 -0.002  0.023 -0.002 -0.027  0.048  0.123  0.471 
 0.062  0.037 -0.062 -0.037 -0.012  0.012 -0.087 -0.062 -0.037 -0.037 -0.012 -0.062 -0.087 -0.037 -0.087 -0.037 -0.012  0.012  0.087 -0.062 -0.087  0.062 -0.087 -0.062  0.087  0.012  0.062  0.062  0.062 -0.037 -0.037 -0.062 -0.087 -0.087  0.112 -0.012 -0.062 -0.087 -0.062 -0.087 -0.062 -0.012 -0.012  0.012 -0.062 -0.037 -0.087 -0.012 -0.062 -0.037  0.187  0.411  0.237  0.112  0.012  0.062  0.286  0.112  0.561  0.710  0.037  0.012  0.012  0.087  0.262  0.411  0.461  0.012  0.386 -0.012  0.237 -0.037 -0.062 -0.012 -0.062 -0.037  0.037 -0.087  0.037 -0.012  0.536  0.012 -0.012  0.212  0.087  0.012  0.112  0.311 -0.037 -0.012  0.286  0.585  0.112  0.012  0.012 -0.012 -0.037  0.012  0.137  0.411 
 0.072  0.047 -0.053 -0.028 -0.003  0.022 -0.078 -0.053 -0.028 -0.028 -0.003 -0.053 -0.078 -0.028 -0.078 -0.028 -0.028  0.022  0.072 -0.053 -0.078  0.072 -0.078 -0.053  0.072  0.022  0.072  0.072  0.047 -0.028 -0.028 -0.053 -0.078 -0.078  0.097 -0.003 -0.053 -0.078 -0.028 -0.078 -0.028 -0.003 -0.003  0.022 -0.053 -0.053 -0.078 -0.053 -0.053 -0.028  0.097  0.346  0.196  0.122  0.022  0.072  0.246  0.097  0.570  0.719 -0.003  0.022  0.022  0.047  0.246  0.296  0.445 -0.003  0.371 -0.003  0.146 -0.028 -0.053 -0.003 -0.053 -0.053  0.072 -0.078  0.022 -0.003  0.545  0.022 -0.053  0.146  0.097  0.022  0.122  0.271 -0.028 -0.003  0.196  0.620  0.122  0.022 -0.028 -0.003 -0.028 -0.003  0.122  0.421 
 0.078  0.053 -0.071 -0.046 -0.021  0.028 -0.071 -0.021 -0.046  0.003 -0.046 -0.046 -0.071 -0.046 -0.071 -0.021 -0.021  0.028  0.028 -0.046 -0.071  0.103 -0.071 -0.046  0.078  0.028 -0.021  0.078  0.053 -0.021 -0.046 -0.046 -0.071 -0.071  0.078  0.003 -0.046 -0.071 -0.021 -0.046 -0.021  0.003  0.003  0.003 -0.046 -0.046 -0.071 -0.046 -0.046 -0.021  0.078  0.253  0.153  0.153  0.028  0.053  0.253  0.053  0.552  0.801  0.003 -0.021  0.028  0.003  0.128  0.228  0.452  0.003  0.327  0.003  0.103 -0.021 -0.046  0.003 -0.046 -0.046  0.078 -0.071  0.028  0.003  0.576  0.028 -0.046  0.103  0.078 -0.046  0.128  0.278 -0.021 -0.021  0.203  0.651  0.128  0.003 -0.021  0.003 -0.021  0.003  0.078  0.302 
 0.081  0.056 -0.068 -0.043 -0.018  0.006 -0.068 -0.018 -0.068  0.006 -0.043 -0.043 -0.068 -0.043 -0.068 -0.043 -0.018  0.031  0.006 -0.043 -0.068  0.106 -0.068 -0.068  0.031  0.006 -0.018  0.056  0.081 -0.018 -0.043 -0.043 -0.068 -0.068  0.056  0.006 -0.068 -0.068 -0.018 -0.043  0.006  0.006 -0.043  0.006 -0.043 -0.043 -0.068 -0.018 -0.043 -0.018  0.081  0.206  0.156  0.156  0.006  0.031  0.181  0.056  0.505  0.853 -0.018 -0.018  0.031  0.006  0.131  0.181  0.405  0.006  0.305 -0.018  0.056 -0.018 -0.043  0.006 -0.043 -0.043  0.056 -0.068  0.006  0.006  0.629  0.031 -0.043  0.106  0.056 -0.068  0.131  0.281 -0.018 -0.018  0.206  0.654  0.156 -0.018 -0.018  0.006 -0.018  0.006  0.056  0.305 
 0.090  0.040 -0.060 -0.035 -0.035  0.015 -0.060 -0.010 -0.060  0.015 -0.060 -0.010 -0.035 -0.060 -0.060 -0.035 -0.035  0.040 -0.035 -0.035 -0.060  0.090 -0.060 -0.060  0.040 -0.010 -0.010  0.065  0.090 -0.010 -0.035 -0.035 -0.060 -0.060  0.015  0.015 -0.060 -0.035 -0.010 -0.035 -0.010  0.015 -0.035  0.015 -0.060 -0.035 -0.060 -0.010 -0.035 -0.035  0.065  0.090  0.090  0.164  0.015  0.015  0.140  0.040  0.414  0.887 -0.035 -0.010  0.015 -0.035  0.140  0.065  0.339 -0.035  0.289 -0.035  0.065 -0.035 -0.035  0.040 -0.035 -0.035  0.040 -0.060  0.015  0.015  0.663  0.040 -0.035  0.090  0.065 -0.060  0.140  0.214 -0.010 -0.010  0.140  0.737  0.140  0.015 -0.010  0.015 -0.010  0.015  0.090  0.214 
 0.095  0.045 -0.055 -0.030 -0.030 -0.005 -0.055 -0.005 -0.055 -0.005 -0.030 -0.005 -0.030 -0.055 -0.030 -0.030 -0.030  0.045 -0.005 -0.005 -0.055  0.095 -0.055 -0.055  0.045 -0.005 -0.005  0.070  0.095 -0.005 -0.055 -0.030 -0.055 -0.055 -0.005 -0.030 -0.055 -0.030 -0.005 -0.030 -0.005  0.020 -0.030 -0.005 -0.055 -0.055 -0.055 -0.005 -0.030 -0.030  0.045  0.070  0.095  0.120  0.020 -0.005  0.144  0.020  0.294  0.942 -0.005 -0.030 -0.005 -0.030  0.120  0.045  0.269 -0.030  0.169 -0.030  0.045 -0.005 -0.030  0.045 -0.055 -0.030  0.045 -0.055  0.020  0.020  0.643  0.045 -0.030  0.095  0.070 -0.055  0.120  0.169 -0.030 -0.005  0.095  0.767  0.144 -0.005 -0.005  0.020 -0.005  0.020  0.045  0.144 
 0.077  0.027 -0.047 -0.022 -0.022  0.002 -0.047  0.002 -0.047  0.002 -0.022  0.002 -0.022 -0.047 -0.022 -0.047 -0.022  0.052 -0.022  0.002 -0.047  0.052 -0.047 -0.047  0.052 -0.022  0.002  0.052  0.077 -0.022 -0.047 -0.022 -0.047 -0.047  0.002  0.002 -0.047 -0.022  0.002  0.002  0.002  0.027 -0.047  0.002 -0.047 -0.047 -0.047 -0.022 -0.022 -0.022  0.027 -0.022  0.052  0.102  0.027 -0.022  0.127  0.027  0.177  0.974 -0.022 -0.047  0.002 -0.022  0.027  0.027  0.052 -0.022  0.077 -0.022  0.027  0.002 -0.022  0.052 -0.047  0.027  0.002 -0.022  0.027  0.027  0.675  0.027 -0.022  0.052  0.027 -0.047  0.102  0.052 -0.047 -0.022  0.102  0.800  0.127  0.002  0.002  0.002  0.002  0.027 -0.022  0.102 
 0.076  0.026 -0.048 -0.023 -0.023  0.001 -0.048  0.001 -0.048  0.001 -0.023  0.001 -0.023 -0.048 -0.023 -0.048 -0.023  0.051 -0.023  0.001 -0.048  0.051 -0.023 -0.023  0.051 -0.023  0.001  0.051  0.076 -0.023 -0.048 -0.023 -0.048 -0.048  0.001  0.001 -0.048 -0.023  0.001  0.001  0.001  0.026 -0.048  0.001 -0.048 -0.048 -0.048 -0.023 -0.023 -0.023  0.026 -0.023  0.051  0.101  0.026 -0.023  0.101  0.026  0.151  0.973 -0.048 -0.048  0.001 -0.023  0.026  0.026  0.051 -0.023  0.076  0.001  0.026 -0.023 -0.023  0.076 -0.048  0.026  0.001 -0.023  0.026  0.051  0.649  0.051 -0.023  0.026  0.026 -0.048  0.101  0.026 -0.048 -0.023  0.101  0.898  0.126  0.026  0.001  0.001  0.001  0.026 -0.023  0.101 
 0.076  0.026 -0.049 -0.024 -0.024  0.026 -0.049  0.001 -0.049  0.001 -0.024  0.001 -0.024 -0.049 -0.024 -0.049 -0.024  0.051 -0.024  0.001 -0.049  0.051 -0.024 -0.024  0.051 -0.024  0.001  0.076  0.076 -0.024 -0.049 -0.024 -0.049 -0.049  0.001  0.001 -0.024 -0.024  0.001  0.026  0.001  0.026 -0.024  0.001 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.026 -0.024  0.051  0.101  0.026 -0.024  0.076  0.026  0.150  0.973 -0.049 -0.024  0.001 -0.024  0.026  0.026  0.001 -0.024  0.076  0.001  0.001 -0.024 -0.024  0.076 -0.049  0.026  0.001 -0.024  0.026  0.026  0.674  0.026 -0.024  0.051  0.026 -0.049  0.101  0.026 -0.049 -0.024  0.101  0.948  0.101  0.026  0.001  0.001  0.001  0.026 -0.024  0.101 
 0.076  0.026 -0.049 -0.024 -0.024  0.026 -0.049  0.001 -0.049  0.001 -0.024  0.001 -0.024 -0.049 -0.024 -0.049 -0.024  0.051  0.001  0.001 -0.049  0.051 -0.024 -0.024  0.051 -0.024  0.001  0.076  0.076 -0.024 -0.049 -0.024 -0.049 -0.049  0.001  0.001 -0.024 -0.024  0.001  0.026  0.001  0.026 -0.024  0.001 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.026 -0.024  0.051  0.101  0.026 -0.024  0.051  0.026  0.150  0.973 -0.024 -0.024  0.001 -0.024  0.026  0.026  0.001 -0.024  0.076  0.001  0.001  0.001 -0.024  0.076 -0.049  0.026  0.001 -0.024  0.026  0.026  0.649  0.026 -0.024  0.051  0.026 -0.049  0.101  0.026 -0.049 -0.024  0.101  0.973  0.101  0.026  0.001  0.001  0.001  0.026 -0.024  0.101 
 0.076  0.026 -0.048 -0.023 -0.023  0.026 -0.048  0.001 -0.048  0.001 -0.023  0.001 -0.023 -0.048 -0.023 -0.048 -0.023  0.051  0.001  0.001 -0.048  0.051 -0.023 -0.023  0.051 -0.023  0.001  0.076  0.076 -0.023 -0.048 -0.023 -0.048 -0.048  0.001  0.001 -0.023 -0.023  0.001  0.026  0.001  0.026 -0.023  0.001 -0.048 -0.023 -0.048 -0.023 -0.023 -0.023  0.001 -0.023  0.051  0.101  0.026 -0.023  0.051  0.026  0.151  0.973 -0.023 -0.023  0.001 -0.023  0.026  0.026  0.001 -0.023  0.051  0.001  0.001  0.001 -0.023  0.076 -0.048  0.026  0.001 -0.023  0.026  0.026  0.624  0.026 -0.023  0.051  0.026 -0.048  0.101  0.026 -0.048 -0.023  0.101  0.973  0.101  0.026  0.001  0.001  0.001  0.026 -0.023  0.101 
 0.077  0.027 -0.048 -0.023 -0.023  0.002 -0.048  0.002 -0.048  0.002 -0.023  0.002 -0.023 -0.048 -0.023 -0.048 -0.023  0.052  0.002  0.002 -0.048  0.052 -0.023 -0.023  0.052 -0.023  0.002  0.052  0.077 -0.023 -0.048 -0.023 -0.048 -0.048  0.002  0.002 -0.023 -0.023  0.002  0.002  0.002  0.027 -0.023  0.002 -0.048 -0.023 -0.048 -0.023 -0.023 -0.023  0.002 -0.023  0.052  0.102  0.027 -0.023  0.052  0.027  0.151  0.974 -0.023 -0.023  0.002 -0.023  0.027  0.027  0.002 -0.023  0.052  0.002  0.002  0.002 -0.023  0.077 -0.048  0.027  0.002 -0.023  0.027  0.027  0.600  0.027 -0.023  0.052  0.027 -0.048  0.102  0.027 -0.048 -0.023  0.102  0.974  0.102  0.027  0.002  0.002  0.002  0.027 -0.023  0.102 
 0.077  0.027 -0.048 -0.023 -0.023  0.002 -0.048  0.002 -0.048  0.002 -0.023  0.002 -0.023 -0.048 -0.023 -0.048 -0.023  0.052  0.002  0.002 -0.048  0.052 -0.023 -0.023  0.052 -0.023  0.002  0.052  0.077 -0.023 -0.048 -0.023 -0.048 -0.048  0.002  0.002 -0.023 -0.023  0.002  0.002  0.002  0.027 -0.023  0.002 -0.048 -0.023 -0.048 -0.023 -0.023 -0.023  0.002 -0.023  0.052  0.102  0.027 -0.023  0.052  0.027  0.151  0.974 -0.023 -0.023  0.002 -0.023  0.027  0.027  0.002 -0.023  0.052  0.002  0.002  0.002 -0.023  0.077 -0.048  0.027  0.002 -0.023  0.027  0.027  0.600  0.027 -0.023  0.052  0.027 -0.048  0.102  0.027 -0.048 -0.023  0.102  0.974  0.102  0.027  0.002  0.002  0.002  0.027 -0.023  0.102 
 0.078  0.028 -0.047 -0.022 -0.022  0.003 -0.047  0.003 -0.047  0.003 -0.022  0.003 -0.022 -0.047 -0.022 -0.047 -0.022  0.053  0.003  0.003 -0.047  0.053 -0.022 -0.022  0.053 -0.022  0.003  0.053  0.078 -0.022 -0.047 -0.022 -0.047 -0.047  0.003  0.003 -0.022 -0.022  0.003  0.003  0.003  0.028 -0.022  0.003 -0.047 -0.022 -0.047 -0.022 -0.022 -0.022  0.003 -0.022  0.053  0.103  0.028 -0.022  0.053  0.028  0.152  0.975 -0.022 -0.022  0.003 -0.022  0.028  0.028  0.003 -0.022  0.053  0.003  0.003  0.003 -0.022  0.078 -0.047  0.028  0.003 -0.022  0.028  0.028  0.551  0.028 -0.022  0.053  0.028 -0.047  0.103  0.028 -0.047 -0.022  0.103  0.975  0.103  0.003  0.003  0.003  0.003  0.028 -0.022  0.103 
 0.078  0.028 -0.047 -0.022 -0.022  0.003 -0.047  0.003 -0.047  0.003 -0.022  0.003 -0.022 -0.047 -0.022 -0.047 -0.022  0.053  0.003  0.003 -0.047  0.053 -0.022 -0.022  0.053 -0.022  0.003  0.053  0.078 -0.022 -0.047 -0.022 -0.047 -0.047  0.003  0.003 -0.022 -0.022  0.003  0.003  0.003  0.028 -0.022  0.003 -0.047 -0.022 -0.047 -0.022 -0.022 -0.022  0.003 -0.022  0.053  0.103  0.028 -0.022  0.053  0.028  0.152  0.975 -0.022 -0.022  0.003 -0.022  0.028  0.028  0.003 -0.022  0.053  0.003  0.003  0.003 -0.022  0.078 -0.047  0.028  0.003 -0.022  0.028  0.028  0.551  0.028 -0.022  0.053  0.028 -0.047  0.103  0.028 -0.047 -0.022  0.103  0.975  0.103  0.003  0.003  0.003  0.003  0.028 -0.022  0.103 
 0.064  0.014 -0.060 -0.010 -0.035  0.014 -0.085 -0.010 -0.085 -0.010 -0.060 -0.035 -0.010 -0.035 -0.060 -0.085 -0.010  0.014  0.014 -0.035 -0.085  0.039 -0.060 -0.035  0.014 -0.035  0.014  0.064  0.064 -0.035 -0.035 -0.010 -0.060 -0.085  0.039  0.064 -0.060 -0.035 -0.035 -0.010  0.039  0.039 -0.035  0.039 -0.060 -0.010 -0.085 -0.060 -0.060 -0.060  0.064  0.014  0.064  0.288  0.039 -0.010  0.139  0.064  0.463  0.936  0.039  0.014  0.039 -0.010  0.014  0.039  0.114 -0.035  0.164 -0.035  0.039 -0.010 -0.035  0.164 -0.085  0.039  0.064  0.014  0.039 -0.010  0.712  0.064  0.039  0.139 -0.010 -0.035  0.089  0.014 -0.085 -0.035  0.139  0.936  0.214 -0.010 -0.035 -0.035 -0.010  0.064  0.014  0.338 
 0.147  0.022 -0.102 -0.052 -0.052 -0.002 -0.152 -0.027 -0.127 -0.077 -0.077 -0.052 -0.002 -0.077 -0.052 -0.152 -0.052  0.047  0.072 -0.102 -0.127  0.047 -0.102 -0.077  0.072 -0.052  0.022 -0.002  0.197 -0.052 -0.077 -0.052 -0.127 -0.152  0.097  0.022 -0.077 -0.102 -0.077 -0.027  0.072 -0.027 -0.027  0.047 -0.102 -0.002 -0.077 -0.077 -0.127 -0.052  0.097  0.047  0.172  0.371 -0.002 -0.002  0.222  0.047  0.770  0.869  0.047 -0.002  0.097 -0.027  0.172  0.197  0.222 -0.077  0.421 -0.002  0.321 -0.052 -0.052  0.346 -0.152  0.047  0.072 -0.002  0.047  0.022  0.869  0.022  0.072  0.147  0.022 -0.052  0.222  0.172 -0.152 -0.027  0.247  0.869  0.247  0.022  0.022 -0.002 -0.052 -0.002  0.072  0.570 
 0.158  0.033 -0.116 -0.091 -0.016 -0.066 -0.166 -0.066 -0.091 -0.116 -0.116 -0.066  0.033 -0.091 -0.066 -0.141 -0.041  0.033  0.058 -0.141 -0.166  0.033 -0.116 -0.116  0.083 -0.016  0.008 -0.016  0.183 -0.066 -0.091 -0.066 -0.166 -0.191  0.058  0.008 -0.091 -0.141 -0.091 -0.066  0.033 -0.091 -0.066  0.033 -0.116  0.008 -0.091 -0.091 -0.116 -0.091  0.108  0.083  0.183  0.407 -0.041  0.008  0.332  0.083  0.756  0.831  0.058 -0.041  0.058 -0.041  0.233  0.233  0.357 -0.016  0.557  0.008  0.432 -0.066 -0.041  0.332 -0.141  0.108  0.033  0.083  0.058  0.058  0.831  0.133  0.083  0.307  0.058 -0.041  0.332  0.307 -0.191 -0.016  0.283  0.831  0.332  0.033  0.008  0.008 -0.091 -0.016  0.183  0.656 
 0.217  0.018 -0.156 -0.132  0.043 -0.132 -0.206 -0.057 -0.132 -0.132 -0.057 -0.057 -0.007 -0.082 -0.007 -0.156 -0.082 -0.057  0.043 -0.206 -0.206  0.043 -0.181 -0.132  0.068 -0.057 -0.057 -0.057  0.192 -0.107 -0.057 -0.132 -0.206 -0.231 -0.007  0.018 -0.156 -0.156 -0.156 -0.132 -0.007 -0.132 -0.107  0.068 -0.132 -0.057 -0.132  0.018 -0.156 -0.107  0.118  0.292  0.292  0.417 -0.057  0.167  0.466  0.118  0.740  0.765  0.068 -0.057  0.093  0.018  0.392  0.441  0.441 -0.032  0.591 -0.057  0.591 -0.032 -0.007  0.441 -0.181  0.142  0.043  0.093  0.142  0.068  0.740  0.142  0.093  0.392  0.018 -0.032  0.441  0.441 -0.206  0.142  0.392  0.765  0.417  0.167  0.167 -0.032 -0.107  0.018  0.267  0.691 
 0.278 -0.021 -0.171 -0.146  0.128 -0.146 -0.196 -0.071 -0.121 -0.121 -0.071 -0.046 -0.021 -0.046  0.003 -0.146 -0.096 -0.096  0.028 -0.171 -0.221  0.053 -0.196 -0.121  0.078 -0.071 -0.046 -0.071  0.203 -0.121 -0.071 -0.071 -0.196 -0.246 -0.021  0.003 -0.171 -0.171 -0.146 -0.171  0.003 -0.121 -0.121  0.053 -0.146 -0.071 -0.146  0.028 -0.121 -0.096  0.128  0.402  0.278  0.327 -0.046  0.178  0.502  0.153  0.726  0.751  0.103 -0.071  0.078  0.053  0.402  0.427  0.527  0.003  0.576 -0.046  0.626 -0.046  0.003  0.452 -0.171  0.178  0.028  0.078  0.153  0.078  0.726  0.128  0.128  0.477  0.003 -0.021  0.427  0.552 -0.171  0.178  0.352  0.726  0.427  0.153  0.153  0.003 -0.096  0.003  0.253  0.676 
 0.254 -0.045 -0.194 -0.144  0.154 -0.169 -0.169 -0.095 -0.095 -0.070 -0.045  0.005 -0.045 -0.020  0.030 -0.144 -0.120 -0.095  0.005 -0.169 -0.219  0.130 -0.194 -0.169  0.080 -0.095 -0.070 -0.095  0.204 -0.070 -0.070 -0.095 -0.219 -0.244 -0.020 -0.070 -0.194 -0.144 -0.144 -0.194 -0.020 -0.144 -0.120  0.055 -0.169 -0.070 -0.120  0.005 -0.144 -0.120  0.179  0.453  0.304  0.304 -0.070  0.154  0.578  0.179  0.703  0.727  0.080 -0.045  0.055  0.105  0.404  0.478  0.678  0.030  0.553 -0.045  0.628 -0.045  0.005  0.478 -0.194  0.154  0.030  0.055  0.179  0.080  0.703  0.130  0.179  0.528  0.030 -0.020  0.453  0.628 -0.169  0.154  0.304  0.703  0.404  0.204  0.154  0.005 -0.120  0.030  0.329  0.678 
 0.301 -0.048 -0.222 -0.123  0.151 -0.172 -0.172 -0.098 -0.098 -0.098 -0.048  0.002 -0.048 -0.023  0.027 -0.147 -0.123 -0.098  0.027 -0.172 -0.222  0.127 -0.172 -0.172  0.077 -0.098 -0.073 -0.098  0.151 -0.098 -0.073 -0.098 -0.222 -0.247 -0.023 -0.073 -0.197 -0.147 -0.147 -0.197 -0.023 -0.147 -0.123  0.052 -0.197 -0.073 -0.123  0.002 -0.147 -0.123  0.176  0.550  0.301  0.301 -0.073  0.176  0.575  0.176  0.700  0.724  0.077 -0.048  0.102  0.102  0.401  0.475  0.650  0.027  0.525 -0.048  0.625 -0.048 -0.023  0.475 -0.197  0.151  0.027  0.052  0.176  0.077  0.650  0.127  0.176  0.525  0.027 -0.023  0.450  0.650 -0.147  0.151  0.301  0.700  0.401  0.201  0.151  0.002 -0.123  0.027  0.326  0.675 
 0.321 -0.053 -0.227 -0.128  0.146 -0.128 -0.177 -0.078 -0.103 -0.103 -0.053  0.022 -0.053 -0.003  0.146 -0.078 -0.103 -0.103  0.022 -0.177 -0.227  0.097 -0.177 -0.177  0.047 -0.103 -0.078 -0.103  0.146 -0.103 -0.053 -0.128 -0.252 -0.252 -0.003 -0.078 -0.202 -0.152 -0.128 -0.202 -0.028 -0.152 -0.128  0.072 -0.202 -0.078 -0.128 -0.028 -0.152 -0.128  0.246  0.570  0.296  0.296 -0.053  0.196  0.595  0.196  0.695  0.695  0.097 -0.053  0.072  0.097  0.396  0.470  0.645  0.047  0.520 -0.053  0.645 -0.053 -0.003  0.470 -0.227  0.146  0.047  0.072  0.171  0.047  0.620  0.122  0.221  0.545  0.047 -0.053  0.421  0.670 -0.128  0.171  0.321  0.695  0.346  0.221  0.196  0.047 -0.128  0.022  0.346  0.670 
 0.321 -0.052 -0.227 -0.127  0.122 -0.127 -0.177 -0.077 -0.102 -0.102 -0.052  0.022 -0.052 -0.027  0.147 -0.077 -0.127 -0.102  0.022 -0.177 -0.227  0.097 -0.177 -0.177  0.022 -0.102 -0.077 -0.102  0.172 -0.102 -0.052 -0.152 -0.227 -0.252  0.022 -0.077 -0.202 -0.177 -0.127 -0.202 -0.027 -0.152 -0.127  0.072 -0.202 -0.077 -0.127 -0.052 -0.177 -0.102  0.272  0.570  0.296  0.296 -0.027  0.197  0.595  0.222  0.695  0.695  0.122 -0.052  0.072  0.097  0.396  0.471  0.645  0.047  0.496 -0.052  0.620 -0.052 -0.002  0.471 -0.227  0.147  0.047  0.072  0.172  0.047  0.595  0.122  0.296  0.546  0.072 -0.052  0.396  0.670 -0.127  0.172  0.321  0.695  0.346  0.222  0.197  0.072 -0.127  0.022  0.346  0.670 
 0.318 -0.081 -0.230 -0.131  0.119 -0.131 -0.180 -0.106 -0.106 -0.106 -0.006  0.094 -0.056 -0.031  0.143 -0.081 -0.131 -0.106  0.019 -0.205 -0.230  0.094 -0.180 -0.180  0.019 -0.106 -0.106 -0.106  0.168 -0.106 -0.056 -0.155 -0.230 -0.280  0.044 -0.056 -0.205 -0.180 -0.106 -0.205 -0.031 -0.155 -0.131  0.044 -0.205 -0.081 -0.131 -0.106 -0.180 -0.106  0.268  0.592  0.293  0.293  0.019  0.193  0.592  0.268  0.692  0.692  0.119 -0.031  0.044  0.119  0.393  0.492  0.642  0.044  0.492 -0.056  0.592 -0.056 -0.006  0.492 -0.230  0.143  0.069  0.069  0.168  0.044  0.542  0.119  0.318  0.542  0.069 -0.031  0.343  0.667 -0.106  0.268  0.318  0.692  0.318  0.293  0.193  0.069 -0.131  0.044  0.343  0.667 
 0.314 -0.084 -0.234 -0.109  0.115 -0.134 -0.184 -0.109 -0.084 -0.084  0.015  0.065 -0.059  0.015  0.165 -0.084 -0.134 -0.084  0.015 -0.209 -0.234  0.165 -0.159 -0.184  0.015 -0.109 -0.109 -0.084  0.165 -0.134 -0.059 -0.209 -0.234 -0.284  0.065 -0.034 -0.209 -0.184 -0.109 -0.209 -0.034 -0.159 -0.134  0.040 -0.184 -0.084 -0.134 -0.109 -0.184 -0.109  0.265  0.588  0.289  0.314  0.040  0.215  0.564  0.265  0.688  0.688  0.115 -0.009  0.040  0.115  0.389  0.514  0.663  0.065  0.464 -0.059  0.588 -0.059  0.015  0.489 -0.234  0.140  0.065  0.065  0.190  0.040  0.539  0.090  0.314  0.539  0.065 -0.034  0.339  0.663 -0.109  0.265  0.314  0.688  0.314  0.289  0.190  0.065 -0.134  0.065  0.339  0.663 
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 0.142  0.042 -0.008 -0.033  0.017  0.042 -0.008  0.017  0.017 -0.058  0.017  0.017 -0.008  0.042  0.067  0.017 -0.008  0.042 -0.008 -0.058 -0.058 -0.033 -0.033 -0.008 -0.008  0.017 -0.033 -0.033  0.142 -0.008 -0.033  0.017  0.017  0.964 -0.033 -0.008 -0.033 -0.033 -0.033 -0.033  0.042 -0.058  0.142 -0.033 -0.033  0.017 -0.033 -0.033 -0.058 -0.033 -0.058  0.042 -0.008 -0.058 -0.033 -0.008  0.017 -0.033 -0.058 -0.058 -0.008 -0.008 -0.033 -0.058 -0.033 -0.008 -0.033 -0.008 -0.033 -0.008 -0.033 -0.008  0.042  0.017 -0.008 -0.008 -0.008 -0.033 -0.033  0.017  0.067 -0.008 -0.008 -0.058  0.017 -0.033  0.092 -0.033 -0.033 -0.033  0.067 -0.033  0.017  0.042  0.042  0.117 -0.058 -0.008 -0.033  0.117 
 0.189  0.039  0.039 -0.035  0.039  0.014 -0.035 -0.010  0.039 -0.010  0.014  0.014 -0.035  0.014  0.139  0.014 -0.010  0.064 -0.035 -0.060 -0.060 -0.060 -0.060 -0.035 -0.035 -0.010  0.014 -0.060  0.239  0.014 -0.035  0.014  0.014  0.936 -0.035 -0.035 -0.060 -0.010 -0.035 -0.060  0.039 -0.060  0.288 -0.035 -0.060 -0.010 -0.035 -0.035 -0.085 -0.010 -0.060  0.089 -0.010 -0.060 -0.060 -0.035 -0.010 -0.060 -0.060 -0.035  0.039 -0.010 -0.060 -0.060 -0.010  0.014 -0.035 -0.010 -0.060 -0.035 -0.060 -0.010  0.139 -0.010 -0.010 -0.035 -0.035 -0.035 -0.060 -0.010  0.039 -0.035  0.039 -0.085 -0.010  0.039  0.139  0.014 -0.035 -0.060  0.064 -0.035  0.039  0.014  0.039  0.164 -0.060 -0.010 -0.060  0.089 
 0.248  0.023  0.073 -0.026 -0.001  0.073 -0.051  0.048  0.073 -0.026  0.073  0.048  0.073 -0.026  0.198 -0.001 -0.026  0.048 -0.051 -0.051 -0.051 -0.076 -0.051 -0.076 -0.076  0.048 -0.026 -0.101  0.347 -0.001 -0.051  0.048  0.023  0.895 -0.001  0.023  0.048 -0.001 -0.026 -0.026  0.123 -0.026  0.472  0.048 -0.101 -0.001 -0.051 -0.001 -0.076 -0.026 -0.101  0.123  0.073 -0.101 -0.101  0.048 -0.051 -0.101 -0.076 -0.076  0.048 -0.026 -0.026 -0.051  0.048  0.048  0.023 -0.026 -0.051  0.073 -0.026 -0.026  0.273 -0.001 -0.001 -0.001 -0.051 -0.001 -0.101 -0.001  0.023 -0.051 -0.001 -0.101 -0.051  0.073  0.123 -0.026 -0.051 -0.076  0.023 -0.076  0.073 -0.001  0.073  0.273 -0.051 -0.051 -0.026  0.123 
 0.371  0.072  0.047 -0.052  0.047  0.097 -0.027  0.047  0.047 -0.052  0.072 -0.002  0.147 -0.052  0.247 -0.052 -0.052  0.047 -0.027  0.022 -0.052 -0.052 -0.077 -0.052 -0.027  0.172 -0.077 -0.077  0.396  0.022 -0.077  0.072  0.097  0.869 -0.052  0.147  0.097 -0.002 -0.052 -0.027  0.147  0.047  0.695  0.147 -0.127 -0.002 -0.102 -0.002 -0.002 -0.052 -0.127  0.172  0.122 -0.127 -0.102  0.072 -0.052 -0.127 -0.102 -0.127  0.072 -0.027 -0.052 -0.052  0.247  0.022  0.022 -0.027 -0.027  0.097 -0.027 -0.027  0.197  0.022  0.022  0.022 -0.027 -0.002 -0.052 -0.027 -0.027 -0.052 -0.002 -0.127 -0.052  0.147  0.072  0.022 -0.002 -0.102 -0.002 -0.127  0.047 -0.002  0.072  0.396 -0.052 -0.077 -0.002  0.197 
 0.482  0.083  0.083 -0.091  0.058  0.183 -0.041  0.058  0.083 -0.016  0.158 -0.041  0.183 -0.066  0.307 -0.066  0.008  0.033 -0.016  0.008 -0.066 -0.016 -0.066 -0.041 -0.066  0.357 -0.066 -0.091  0.532  0.008 -0.091  0.108  0.083  0.831 -0.066  0.183  0.208 -0.041 -0.066 -0.016  0.158  0.133  0.831  0.233 -0.166  0.033 -0.141  0.058 -0.041 -0.041 -0.091  0.283  0.233 -0.166 -0.091  0.183 -0.091 -0.066 -0.116 -0.116  0.058 -0.041 -0.016  0.058  0.457  0.083  0.008 -0.041  0.058  0.108 -0.016 -0.016  0.183  0.083  0.008  0.133 -0.066  0.008 -0.066 -0.041 -0.091 -0.066  0.008 -0.141 -0.066  0.183  0.033  0.058  0.008 -0.141  0.008 -0.141  0.108 -0.041  0.108  0.532 -0.041 -0.066  0.008  0.258 
 0.512  0.088  0.063 -0.086  0.063  0.263 -0.036  0.038  0.138  0.038  0.263 -0.011  0.188 -0.086  0.337 -0.111 -0.011  0.013 -0.011  0.013 -0.086 -0.036 -0.061 -0.061 -0.061  0.362 -0.061 -0.086  0.636  0.013 -0.136  0.088  0.088  0.786 -0.061  0.312  0.213 -0.036 -0.086 -0.036  0.138  0.163  0.811  0.312 -0.186  0.113 -0.136  0.038 -0.036 -0.036 -0.086  0.312  0.213 -0.161 -0.111  0.238 -0.111 -0.036 -0.111 -0.086  0.038 -0.086 -0.061  0.088  0.537  0.138  0.013 -0.061  0.038  0.113 -0.061  0.013  0.138  0.138  0.013  0.138 -0.036 -0.011 -0.086 -0.011 -0.086 -0.086 -0.036 -0.136 -0.111  0.213  0.038  0.188  0.013 -0.161  0.013 -0.136  0.138 -0.036  0.113  0.611 -0.036 -0.061  0.038  0.312 
 0.504  0.080  0.055 -0.094  0.130  0.255 -0.069  0.030  0.130  0.080  0.379  0.030  0.205 -0.069  0.404 -0.119 -0.019  0.030 -0.019  0.105 -0.094 -0.044 -0.069  0.005  0.030  0.429 -0.044 -0.019  0.628  0.080 -0.169  0.155  0.080  0.728 -0.069  0.379  0.230 -0.044 -0.119 -0.019  0.180  0.280  0.778  0.379 -0.219  0.155 -0.169  0.005 -0.069  0.005 -0.094  0.404  0.329 -0.144 -0.144  0.280 -0.094 -0.044 -0.144 -0.069  0.080 -0.044 -0.094  0.255  0.653  0.180  0.005 -0.119  0.105  0.130 -0.094  0.055  0.105  0.255  0.105  0.130  0.005  0.080 -0.119  0.005 -0.094 -0.119 -0.044 -0.144 -0.069  0.280  0.055  0.354  0.055 -0.194  0.005 -0.119  0.180 -0.069  0.105  0.678 -0.044 -0.019  0.030  0.304 
 0.466  0.093  0.068 -0.082  0.167  0.267 -0.082  0.018  0.118  0.068  0.417  0.043  0.217 -0.107  0.441 -0.107 -0.032 -0.007 -0.057  0.192 -0.107 -0.032 -0.082 -0.007  0.043  0.441 -0.007  0.018  0.641  0.118 -0.181  0.142  0.068  0.641  0.018  0.367  0.267 -0.032 -0.132 -0.007  0.192  0.317  0.715  0.466 -0.231  0.217 -0.132 -0.007 -0.057  0.018 -0.007  0.417  0.342 -0.156 -0.132  0.367 -0.082 -0.032 -0.132 -0.032  0.093 -0.007 -0.107  0.292  0.691  0.217  0.018 -0.132  0.192  0.118 -0.082  0.118  0.118  0.267  0.118  0.118  0.043  0.093 -0.132 -0.007 -0.107 -0.156 -0.057 -0.156 -0.032  0.267  0.093  0.367  0.018 -0.206 -0.007 -0.082  0.267 -0.032  0.093  0.666 -0.057 -0.032  0.093  0.292 
 0.475  0.077  0.052 -0.048  0.151  0.301 -0.048  0.027  0.102  0.052  0.450  0.127  0.201 -0.123  0.475 -0.147 -0.048  0.002 -0.023  0.276 -0.098 -0.073 -0.098 -0.023  0.102  0.450  0.002  0.002  0.600  0.151 -0.098  0.151  0.027  0.625  0.002  0.401  0.301 -0.048 -0.147 -0.023  0.127  0.276  0.675  0.550 -0.247  0.251 -0.147 -0.048 -0.073  0.127 -0.023  0.426  0.401 -0.147 -0.048  0.376 -0.048  0.002 -0.172 -0.023  0.077  0.027 -0.073  0.326  0.724  0.251 -0.023 -0.147  0.301  0.127 -0.098  0.102  0.102  0.276  0.127  0.102  0.102  0.102 -0.147 -0.048 -0.098 -0.197 -0.048 -0.197 -0.048  0.226  0.151  0.426  0.027 -0.247  0.002 -0.073  0.251 -0.048  0.127  0.650  0.002  0.002  0.077  0.276 
 0.500  0.052  0.052 -0.048  0.077  0.376 -0.048  0.027  0.151  0.052  0.450  0.176  0.201 -0.073  0.450 -0.147  0.002  0.002 -0.023  0.401 -0.098 -0.123 -0.123  0.077  0.127  0.475  0.027  0.002  0.575  0.127 -0.073  0.127  0.002  0.600  0.027  0.401  0.326 -0.048 -0.123 -0.048  0.102  0.301  0.600  0.550 -0.247  0.276 -0.147 -0.073 -0.098  0.127 -0.048  0.426  0.401 -0.147 -0.023  0.351 -0.098  0.027 -0.172  0.002  0.052  0.027 -0.048  0.326  0.724  0.251  0.002 -0.147  0.301  0.127 -0.098  0.102  0.102  0.276  0.127  0.077  0.102  0.102 -0.147 -0.048 -0.098 -0.222 -0.048 -0.197 -0.048  0.251  0.151  0.475  0.027 -0.247  0.002 -0.073  0.276 -0.048  0.127  0.625  0.002  0.002  0.077  0.276 
 0.513  0.089  0.064 -0.010  0.039  0.388 -0.035  0.064  0.189  0.039  0.587  0.264  0.189 -0.085  0.438 -0.110  0.039 -0.035  0.014  0.463 -0.110 -0.160 -0.135  0.089  0.114  0.438  0.089  0.089  0.563  0.189 -0.110  0.164 -0.060  0.488  0.039  0.438  0.338 -0.085 -0.135 -0.035  0.089  0.288  0.538  0.563 -0.260  0.338 -0.135 -0.060 -0.135  0.214 -0.010  0.438  0.413 -0.160  0.014  0.313 -0.085  0.014 -0.185 -0.010 -0.010  0.089 -0.085  0.338  0.637  0.288 -0.010 -0.110  0.313  0.089 -0.110  0.089  0.089  0.288  0.139  0.114  0.239  0.114 -0.160 -0.085 -0.085 -0.235 -0.035 -0.185 -0.010  0.313  0.139  0.463  0.014 -0.235  0.014 -0.085  0.288 -0.110  0.089  0.563 -0.010 -0.010  0.014  0.264 
 0.507  0.084  0.059 -0.016  0.059  0.383 -0.016  0.059  0.208  0.034  0.632  0.308  0.208 -0.091  0.432 -0.116  0.059 -0.041  0.034  0.507 -0.091 -0.141 -0.141  0.084  0.134  0.432  0.084  0.109  0.557  0.258 -0.091  0.158 -0.091  0.457  0.059  0.457  0.333 -0.091 -0.116 -0.016  0.084  0.258  0.532  0.557 -0.265  0.333 -0.116 -0.066 -0.091  0.208  0.009  0.482  0.408 -0.165  0.009  0.308 -0.091  0.009 -0.215  0.009 -0.041  0.084 -0.041  0.333  0.607  0.308 -0.016 -0.116  0.308  0.084 -0.141  0.084  0.084  0.308  0.134  0.109  0.283  0.109 -0.141 -0.091 -0.091 -0.240 -0.041 -0.190  0.009  0.333  0.134  0.457  0.009 -0.240  0.009 -0.016  0.283 -0.091  0.109  0.532 -0.016 -0.016  0.009  0.308 
 0.550  0.127  0.077 -0.023  0.052  0.376 -0.073  0.052  0.226  0.002  0.625  0.301  0.201 -0.073  0.426 -0.123  0.127 -0.073  0.002  0.525 -0.073 -0.123 -0.123  0.176  0.127  0.426  0.176  0.102  0.525  0.326 -0.073  0.176 -0.098  0.426  0.176  0.475  0.326 -0.073 -0.123  0.027  0.052  0.276  0.500  0.550 -0.222  0.326 -0.123 -0.073 -0.073  0.301  0.027  0.500  0.376 -0.172  0.027  0.326 -0.073  0.002 -0.172  0.027 -0.048  0.102  0.027  0.376  0.550  0.301 -0.048 -0.123  0.276  0.102 -0.197  0.127  0.077  0.276  0.176  0.102  0.351  0.127 -0.123 -0.073 -0.073 -0.222 -0.048 -0.197  0.027  0.351  0.127  0.450  0.027 -0.247  0.027 -0.023  0.276 -0.098  0.102  0.525  0.027  0.002  0.002  0.301 
 0.512  0.114  0.089 -0.036  0.014  0.288 -0.036  0.039  0.064 -0.061  0.512  0.238  0.188 -0.011  0.437 -0.086  0.064 -0.011  0.014  0.487 -0.111 -0.111 -0.136  0.163  0.114  0.363  0.114  0.114  0.487  0.313 -0.036  0.139 -0.036  0.363  0.014  0.487  0.363 -0.086 -0.111  0.014  0.089  0.263  0.462  0.587 -0.185  0.263 -0.136 -0.036 -0.061  0.213  0.014  0.487  0.338 -0.111 -0.011  0.238 -0.061  0.014 -0.160 -0.011 -0.036  0.114  0.014  0.313  0.562  0.313  0.014 -0.086  0.288  0.089 -0.160  0.114  0.014  0.263  0.163  0.064  0.263  0.114 -0.086 -0.086 -0.011 -0.185 -0.036 -0.185  0.064  0.338  0.139  0.388  0.039 -0.210 -0.011 -0.011  0.288 -0.061  0.114  0.437  0.064  0.039 -0.036  0.188 
 0.381  0.057  0.057 -0.017  0.057  0.257  0.007  0.007  0.007 -0.017  0.431  0.182  0.157 -0.017  0.356 -0.017  0.007 -0.017  0.007  0.431 -0.117 -0.067 -0.117  0.157  0.132  0.381  0.132  0.057  0.282  0.157 -0.067  0.082 -0.067  0.257 -0.017  0.381  0.381 -0.042 -0.042 -0.017  0.032  0.207  0.356  0.630 -0.117  0.207 -0.142  0.007 -0.092  0.132 -0.017  0.381  0.381 -0.092 -0.017  0.182 -0.117  0.082 -0.117 -0.092 -0.067  0.057 -0.017  0.207  0.431  0.282  0.082 -0.092  0.306  0.007 -0.117  0.107  0.032  0.282  0.157  0.107  0.157  0.107 -0.092 -0.042 -0.017 -0.117 -0.017 -0.142  0.082  0.306  0.132  0.381 -0.042 -0.117  0.007 -0.042  0.157 -0.042  0.157  0.306  0.107 -0.017 -0.067  0.132 
 0.396  0.047  0.072 -0.028  0.047  0.196  0.022 -0.003 -0.028 -0.028  0.470  0.122  0.171 -0.053  0.396 -0.003  0.022 -0.028 -0.003  0.321 -0.103 -0.103 -0.103  0.146  0.146  0.371  0.072 -0.003  0.221  0.072 -0.078  0.097 -0.053  0.271 -0.003  0.346  0.421 -0.028 -0.028 -0.003  0.022  0.221  0.321  0.670 -0.128  0.171 -0.128 -0.003 -0.078  0.122 -0.003  0.371  0.321 -0.078 -0.053  0.196 -0.103  0.097 -0.128 -0.078 -0.053  0.047 -0.028  0.122  0.421  0.296  0.072 -0.078  0.321  0.022 -0.103  0.122  0.022  0.196  0.171  0.122  0.146  0.097 -0.103 -0.053 -0.003 -0.103 -0.003 -0.128  0.047  0.221  0.122  0.346 -0.028 -0.103  0.022 -0.053  0.171 -0.028  0.146  0.296  0.122 -0.003 -0.053  0.097 
 0.323  0.074 -0.026 -0.051  0.049  0.173  0.049 -0.026 -0.051 -0.026  0.423  0.049  0.148 -0.001  0.323  0.024  0.024 -0.026 -0.026  0.223 -0.101 -0.076 -0.076  0.099  0.148  0.348  0.074 -0.051  0.198  0.024 -0.051  0.124 -0.051  0.223 -0.001  0.298  0.472 -0.026 -0.051 -0.001  0.049  0.173  0.173  0.746 -0.101  0.173 -0.101  0.024 -0.076  0.049 -0.001  0.348  0.298 -0.076 -0.026  0.148 -0.051  0.049 -0.101 -0.051 -0.026  0.074 -0.026  0.024  0.398  0.298  0.099 -0.051  0.348  0.049 -0.076  0.124  0.024  0.173  0.198  0.124  0.148  0.074 -0.076 -0.026 -0.001 -0.076 -0.001 -0.101  0.049  0.099  0.148  0.323 -0.051 -0.101  0.024 -0.051  0.198 -0.026  0.148  0.248  0.173 -0.026 -0.101  0.049 
 0.262  0.063 -0.012 -0.037  0.063  0.187  0.038 -0.012 -0.062 -0.037  0.436 -0.012  0.138 -0.037  0.312  0.038  0.038 -0.037 -0.012  0.162 -0.087 -0.062 -0.062  0.088  0.113  0.287  0.088 -0.037  0.162 -0.012 -0.062  0.113 -0.037  0.212  0.013  0.237  0.436  0.013 -0.037  0.013  0.013  0.162  0.138  0.785 -0.087  0.162 -0.087  0.038 -0.062  0.013 -0.012  0.312  0.287 -0.062 -0.062  0.063 -0.037  0.063 -0.087 -0.037 -0.012  0.088 -0.012 -0.037  0.287  0.312  0.113 -0.037  0.337  0.088 -0.062  0.138  0.038  0.162  0.162  0.138  0.138  0.038 -0.062 -0.012  0.013 -0.062  0.013 -0.062  0.063  0.038  0.138  0.237 -0.012 -0.087  0.038 -0.012  0.187 -0.037  0.138  0.187  0.187 -0.037 -0.087 -0.037 
 0.108  0.033 -0.042 -0.042  0.033  0.133  0.033  0.008 -0.042 -0.042  0.307 -0.017  0.133 -0.017  0.307  0.008  0.008 -0.017 -0.017  0.058 -0.067 -0.042 -0.042  0.083  0.033  0.257  0.008 -0.017  0.108 -0.017 -0.042  0.083 -0.042  0.157  0.033  0.108  0.332  0.008 -0.042  0.033  0.008  0.157  0.058  0.805 -0.067  0.182 -0.067  0.058 -0.042  0.033  0.008  0.282  0.282 -0.042 -0.042  0.058 -0.017  0.008 -0.067 -0.042 -0.067  0.058  0.008 -0.042  0.133  0.257  0.108 -0.042  0.282  0.108 -0.042  0.033  0.033  0.182  0.083  0.108  0.133  0.033 -0.067 -0.042  0.033 -0.042 -0.017 -0.042  0.033  0.008  0.108  0.157  0.008 -0.067  0.033  0.008  0.182 -0.017  0.157  0.133  0.207 -0.017 -0.067 -0.042 
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 0.017  0.017 -0.033 -0.008  0.042  0.042  0.017 -0.008 -0.033 -0.033  0.067  0.017  0.017  0.017  0.142  0.017  0.017 -0.008 -0.008  0.017 -0.033 -0.033 -0.033  0.067 -0.033 -0.033  0.017 -0.008  0.067 -0.033 -0.033 -0.008 -0.008  0.092  0.017  0.042  0.191  0.017 -0.033  0.042  0.042  0.092 -0.008  0.964 -0.033  0.042 -0.008 -0.008 -0.008  0.017  0.042  0.092  0.042 -0.033 -0.008  0.017  0.017 -0.008 -0.033 -0.008 -0.033  0.067  0.042 -0.033  0.017  0.117  0.017 -0.033  0.067 -0.008 -0.008  0.017  0.042  0.067  0.042  0.017 -0.008 -0.008 -0.008 -0.008  0.042 -0.033  0.017 -0.033 -0.008 -0.033  0.042 -0.033  0.017 -0.008  0.017  0.017  0.117 -0.033  0.092  0.042  0.092  0.017 -0.033 -0.008 
 0.023  0.023 -0.027 -0.002  0.023  0.048  0.048 -0.002 -0.027 -0.027  0.023  0.023  0.023  0.048  0.048  0.023  0.023 -0.002 -0.002  0.023 -0.027 -0.027 -0.027  0.048 -0.027 -0.027 -0.002 -0.002  0.023 -0.027 -0.027 -0.027 -0.002  0.023  0.023  0.048  0.147 -0.002 -0.027  0.048  0.023  0.048 -0.002  0.994 -0.027  0.048 -0.002 -0.002 -0.002  0.023  0.048  0.048  0.023 -0.027 -0.002 -0.002  0.023 -0.002 -0.027 -0.027 -0.027  0.073  0.048 -0.027  0.023  0.073 -0.002 -0.027  0.073 -0.002 -0.002 -0.002  0.048  0.048 -0.002  0.023 -0.002 -0.002 -0.002 -0.027  0.048 -0.027  0.023 -0.027 -0.002 -0.027  0.048 -0.027 -0.002 -0.002  0.023  0.023  0.098 -0.027  0.073 -0.002  0.023 -0.002 -0.027 -0.002 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.079 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
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 0.027  0.052 -0.022  0.002  0.002  0.027  0.052  0.002 -0.022 -0.022  0.027  0.027  0.027  0.027  0.002  0.052  0.027 -0.022  0.002  0.052 -0.022 -0.022 -0.022  0.027 -0.022 -0.022  0.002  0.002 -0.022 -0.022 -0.022 -0.022  0.002 -0.022  0.002  0.052  0.177  0.002 -0.022  0.002  0.002  0.052  0.002  0.999 -0.022  0.052  0.002  0.002  0.002  0.002  0.052  0.052  0.002 -0.022  0.002  0.002  0.002 -0.022 -0.022 -0.022 -0.022  0.102  0.002 -0.022  0.002  0.027 -0.022  0.002  0.077  0.002  0.002  0.002  0.027  0.027  0.002  0.002  0.002 -0.022  0.002 -0.022  0.027 -0.022  0.027 -0.022  0.002 -0.022  0.027 -0.022  0.002  0.027 -0.022  0.027  0.127 -0.022  0.002  0.002  0.027  0.002 -0.022  0.027 
 0.065  0.065 -0.035  0.015 -0.010  0.015  0.090 -0.010 -0.010 -0.010  0.015  0.015  0.015  0.015  0.040  0.065  0.015 -0.035 -0.010  0.140 -0.035 -0.035 -0.010  0.015 -0.035 -0.035 -0.010 -0.010 -0.010 -0.035 -0.010 -0.010 -0.010 -0.035  0.090  0.065  0.438  0.015 -0.035 -0.010 -0.010  0.065  0.015  0.987 -0.035  0.040 -0.010  0.015 -0.010  0.015  0.065  0.090 -0.010 -0.035  0.015  0.040 -0.010 -0.035 -0.010  0.015 -0.035  0.090 -0.010 -0.010  0.015  0.040  0.015  0.040  0.289  0.015 -0.010 -0.010  0.015  0.065  0.065 -0.010  0.015 -0.035 -0.010 -0.035  0.015 -0.035  0.065 -0.035  0.040 -0.035  0.040  0.015 -0.010  0.040 -0.010  0.065  0.164 -0.035 -0.010 -0.010  0.015 -0.010 -0.035  0.065 
 0.084  0.134 -0.065 -0.015  0.009  0.034  0.059 -0.040 -0.040  0.034  0.059  0.059  0.034 -0.015  0.034  0.084 -0.015 -0.065 -0.015  0.284 -0.065 -0.015 -0.040 -0.015 -0.015 -0.015  0.009  0.084  0.059 -0.015 -0.015  0.034  0.009 -0.015  0.109  0.159  0.657  0.009 -0.040 -0.040  0.009  0.034  0.009  0.956 -0.065  0.009 -0.040  0.134 -0.015 -0.015  0.084  0.184 -0.015 -0.065  0.009  0.159 -0.040 -0.040 -0.040  0.059 -0.065  0.084 -0.040 -0.040  0.009  0.059  0.034  0.134  0.558  0.009  0.009  0.034  0.034  0.109  0.134  0.034  0.034 -0.040 -0.040  0.009  0.034 -0.065  0.034 -0.065  0.259  0.034  0.034  0.109 -0.015  0.009 -0.015  0.084  0.234 -0.040 -0.040 -0.040 -0.015 -0.040 -0.040  0.084 
 0.048  0.123 -0.102 -0.027  0.048  0.073  0.123 -0.052 -0.027  0.023  0.147  0.098  0.197 -0.002  0.073  0.098 -0.027 -0.077 -0.002  0.496 -0.077  0.023 -0.027  0.023  0.073  0.048 -0.002  0.147  0.098 -0.002  0.023  0.073 -0.027 -0.002  0.197  0.372  0.895 -0.002 -0.052 -0.027  0.048  0.098  0.073  0.895 -0.127  0.073 -0.077  0.197  0.023 -0.052  0.048  0.347  0.123 -0.052  0.048  0.247 -0.077 -0.027 -0.077  0.023 -0.127  0.147 -0.002 -0.002 -0.002  0.123  0.073  0.172  0.845  0.023  0.023  0.048  0.023  0.222  0.197  0.247  0.247  0.023 -0.077 -0.002  0.048 -0.077  0.023 -0.102  0.322  0.023  0.073  0.347 -0.077 -0.002 -0.077  0.098  0.422 -0.077  0.023 -0.002 -0.027 -0.077 -0.077  0.073 
 0.048  0.098 -0.102 -0.052  0.147  0.197  0.172 -0.052 -0.002  0.023  0.247  0.172  0.272 -0.002  0.172  0.073 -0.052 -0.052  0.073  0.720 -0.102  0.073 -0.052  0.073  0.098  0.098 -0.027  0.197  0.147  0.073  0.073  0.048 -0.052 -0.027  0.247  0.496  0.845 -0.002 -0.102 -0.052  0.098  0.147  0.123  0.845 -0.151  0.147 -0.077  0.297  0.023 -0.052  0.023  0.372  0.147 -0.077  0.123  0.297 -0.077 -0.077 -0.127 -0.002 -0.102  0.147 -0.027  0.048  0.023  0.123  0.048  0.147  0.795 -0.002 -0.052 -0.002 -0.027  0.372  0.247  0.397  0.496  0.147 -0.102 -0.052  0.023 -0.102  0.023 -0.127  0.372  0.147  0.098  0.397 -0.127 -0.077 -0.027  0.073  0.571 -0.077  0.048  0.073 -0.002 -0.052 -0.077  0.147 
 0.094  0.144 -0.105 -0.055  0.144  0.318  0.194 -0.080 -0.055  0.094  0.368  0.219  0.343 -0.055  0.244  0.144  0.044 -0.055  0.019  0.792 -0.055  0.019 -0.080  0.069  0.169  0.144  0.044  0.269  0.194  0.269  0.069  0.019 -0.055 -0.005  0.318  0.642  0.792 -0.055 -0.055 -0.055  0.144  0.169  0.194  0.792 -0.205  0.194 -0.005  0.318  0.094  0.019 -0.030  0.493  0.169 -0.105  0.169  0.318 -0.080 -0.005 -0.155  0.019 -0.105  0.119 -0.055  0.044  0.044  0.119  0.019  0.119  0.767 -0.030 -0.055 -0.005 -0.005  0.393  0.293  0.493  0.592  0.244 -0.030 -0.005  0.069 -0.080 -0.005 -0.130  0.418  0.219  0.094  0.393 -0.105 -0.130 -0.005  0.119  0.642 -0.005  0.144  0.144  0.019 -0.055 -0.080  0.194 
 0.192  0.142 -0.082  0.017  0.192  0.316  0.291 -0.082 -0.082  0.142  0.416  0.291  0.341 -0.082  0.316  0.192  0.067 -0.032 -0.007  0.765 -0.057  0.017 -0.107  0.067  0.242  0.117  0.067  0.242  0.217  0.291  0.117  0.067 -0.032 -0.032  0.341  0.615  0.740 -0.082 -0.057 -0.007  0.142  0.142  0.192  0.765 -0.232  0.192  0.092  0.291  0.117  0.092 -0.057  0.541  0.192 -0.132  0.217  0.341 -0.082 -0.007 -0.082  0.092 -0.107  0.142  0.017  0.067  0.117  0.117 -0.007  0.117  0.715 -0.082 -0.082  0.042  0.017  0.416  0.291  0.541  0.566  0.267 -0.007  0.017  0.067 -0.107 -0.007 -0.157  0.391  0.267  0.117  0.391 -0.032 -0.157  0.067  0.117  0.640 -0.032  0.117  0.192  0.042 -0.057 -0.082  0.192 
 0.288  0.188 -0.111  0.139  0.238  0.388  0.338  0.014 -0.111  0.139  0.587  0.338  0.388 -0.111  0.338  0.263  0.114 -0.036 -0.036  0.687 -0.036  0.064 -0.136  0.114  0.288  0.188  0.163  0.263  0.313  0.437  0.114  0.089 -0.061 -0.036  0.363  0.587  0.612 -0.111  0.014  0.089  0.139  0.114  0.188  0.736 -0.235  0.213  0.139  0.363  0.213  0.139 -0.011  0.512  0.238 -0.160  0.213  0.313  0.014  0.089 -0.061  0.089 -0.061  0.139  0.064  0.089  0.163  0.163 -0.011  0.089  0.637 -0.111 -0.111  0.039  0.064  0.487  0.288  0.512  0.637  0.213  0.014  0.014  0.114 -0.160 -0.061 -0.185  0.338  0.263  0.139  0.363 -0.011 -0.210  0.089  0.114  0.637 -0.086  0.139  0.238  0.089 -0.086 -0.111  0.163 
 0.401  0.226 -0.098  0.151  0.251  0.376  0.376  0.077 -0.123  0.127  0.600  0.351  0.401 -0.098  0.376  0.276  0.102 -0.048 -0.048  0.650  0.002  0.102 -0.147  0.102  0.276  0.201  0.201  0.251  0.351  0.426  0.151  0.127 -0.073 -0.023  0.376  0.525  0.600 -0.147 -0.023  0.102  0.151  0.127  0.201  0.724 -0.222  0.226  0.176  0.351  0.276  0.176  0.002  0.500  0.251 -0.172  0.201  0.326  0.052  0.151 -0.073  0.102 -0.073  0.151  0.077  0.127  0.176  0.151 -0.023  0.052  0.625 -0.123 -0.098  0.027  0.052  0.475  0.301  0.550  0.625  0.201  0.027  0.002  0.102 -0.172 -0.073 -0.197  0.351  0.276  0.151  0.351  0.027 -0.197  0.052  0.127  0.625 -0.073  0.127  0.251  0.102 -0.098 -0.098  0.151 
 0.411  0.261 -0.113  0.211  0.386  0.386  0.411  0.087 -0.113  0.186  0.585  0.386  0.435 -0.063  0.485  0.286  0.161 -0.063 -0.088  0.535  0.062  0.112 -0.162  0.161  0.261  0.186  0.261  0.236  0.411  0.435  0.186  0.186 -0.013 -0.038  0.386  0.510  0.485 -0.162 -0.013  0.186  0.161  0.186  0.211  0.710 -0.212  0.261  0.261  0.435  0.411  0.236  0.062  0.485  0.261 -0.187  0.236  0.311  0.161  0.161 -0.088  0.112 -0.038  0.137  0.087  0.161  0.186  0.211 -0.013  0.012  0.610 -0.138 -0.138  0.087  0.012  0.485  0.311  0.510  0.610  0.186  0.062 -0.013  0.087 -0.187 -0.088 -0.212  0.336  0.311  0.112  0.311  0.037 -0.212  0.087  0.137  0.535 -0.088  0.112  0.311  0.137 -0.063 -0.038  0.137 
 0.384  0.284 -0.114  0.235  0.434  0.384  0.409  0.110 -0.139  0.185  0.559  0.359  0.434 -0.064  0.484  0.309  0.160 -0.064 -0.114  0.484  0.060  0.110 -0.164  0.160  0.284  0.160  0.284  0.235  0.459  0.459  0.185  0.210 -0.014  0.010  0.384  0.509  0.409 -0.164  0.010  0.185  0.210  0.210  0.235  0.708 -0.189  0.260  0.334  0.434  0.434  0.284  0.085  0.484  0.210 -0.189  0.210  0.309  0.185  0.160 -0.089  0.110 -0.039  0.135  0.085  0.135  0.185  0.210 -0.014 -0.014  0.608 -0.139 -0.139  0.110  0.035  0.484  0.334  0.509  0.608  0.185  0.060 -0.014  0.010 -0.189 -0.064 -0.239  0.309  0.334  0.085  0.309  0.035 -0.239  0.085  0.110  0.509 -0.114  0.110  0.309  0.110 -0.064 -0.064  0.110 
 0.380  0.305 -0.119  0.230  0.479  0.405  0.405  0.106 -0.119  0.230  0.529  0.355  0.429 -0.069  0.529  0.330  0.180 -0.044 -0.119  0.454  0.081  0.131 -0.119  0.230  0.255  0.155  0.330  0.230  0.479  0.454  0.230  0.305 -0.019  0.006  0.429  0.504  0.405 -0.168  0.056  0.205  0.205  0.255  0.230  0.679 -0.193  0.230  0.355  0.479  0.504  0.330  0.081  0.454  0.205 -0.193  0.205  0.280  0.180  0.155 -0.094  0.106 -0.069  0.106  0.106  0.131  0.155  0.205  0.006 -0.044  0.554 -0.094 -0.168  0.155  0.031  0.479  0.330  0.454  0.604  0.180  0.031 -0.019  0.006 -0.168 -0.069 -0.243  0.280  0.330  0.081  0.330  0.031 -0.268  0.056  0.081  0.504 -0.119  0.106  0.280  0.106 -0.044 -0.069  0.106 
 0.381  0.281 -0.118  0.256  0.480  0.406  0.406  0.132 -0.118  0.231  0.530  0.356  0.430 -0.068  0.555  0.306  0.181 -0.018 -0.142  0.455  0.082  0.132 -0.118  0.281  0.256  0.156  0.356  0.256  0.505  0.455  0.256  0.306  0.007  0.032  0.430  0.480  0.406 -0.167  0.057  0.231  0.181  0.256  0.206  0.680 -0.192  0.231  0.381  0.455  0.505  0.356  0.057  0.455  0.231 -0.192  0.181  0.281  0.181  0.156 -0.093  0.107 -0.093  0.082  0.107  0.132  0.156  0.206 -0.018 -0.043  0.530 -0.093 -0.167  0.156  0.032  0.480  0.331  0.406  0.605  0.181  0.007 -0.043 -0.018 -0.167 -0.068 -0.242  0.256  0.331  0.057  0.306  0.032 -0.267  0.057  0.032  0.455 -0.142  0.107  0.281  0.132 -0.043 -0.068  0.132 
 0.429  0.280 -0.094  0.255  0.554  0.404  0.404  0.130 -0.094  0.205  0.429  0.379  0.429 -0.094  0.554  0.304  0.180  0.005 -0.144  0.429  0.080  0.130 -0.069  0.354  0.230  0.180  0.354  0.255  0.529  0.454  0.255  0.304  0.030  0.080  0.479  0.479  0.404 -0.169  0.080  0.230  0.180  0.255  0.230  0.678 -0.194  0.230  0.379  0.454  0.504  0.429  0.105  0.454  0.205 -0.194  0.155  0.280  0.180  0.155 -0.144  0.080 -0.094  0.080  0.105  0.080  0.080  0.205 -0.019 -0.044  0.504 -0.069 -0.169  0.130  0.030  0.479  0.329  0.280  0.603  0.130 -0.019 -0.044 -0.019 -0.144 -0.069 -0.244  0.230  0.304  0.055  0.304  0.030 -0.244  0.030  0.055  0.454 -0.144  0.080  0.255  0.180 -0.044 -0.019  0.130 
 0.429  0.280 -0.094  0.280  0.554  0.454  0.379  0.155 -0.044  0.205  0.429  0.404  0.429 -0.094  0.529  0.304  0.205  0.030 -0.144  0.429  0.080  0.130 -0.044  0.404  0.230  0.180  0.379  0.255  0.504  0.429  0.255  0.304  0.030  0.080  0.479  0.479  0.404 -0.169  0.055  0.230  0.180  0.255  0.230  0.678 -0.169  0.230  0.379  0.454  0.504  0.479  0.155  0.429  0.205 -0.194  0.130  0.280  0.180  0.155 -0.169  0.055 -0.144  0.080  0.080  0.030  0.055  0.180 -0.019 -0.044  0.504 -0.044 -0.194  0.180  0.005  0.454  0.354  0.280  0.578  0.155 -0.019 -0.044 -0.019 -0.119 -0.069 -0.244  0.230  0.304  0.055  0.280  0.055 -0.244  0.005  0.055  0.404 -0.144  0.080  0.230  0.205 -0.044 -0.019  0.105 
 0.451  0.327 -0.097  0.252  0.551  0.476  0.377  0.177  0.078  0.202  0.426  0.402  0.451 -0.097  0.476  0.327  0.227  0.028 -0.146  0.426  0.078  0.128 -0.022  0.426  0.202  0.202  0.352  0.302  0.501  0.451  0.227  0.302  0.053  0.103  0.501  0.476  0.426 -0.171  0.053  0.302  0.177  0.252  0.227  0.676 -0.171  0.252  0.402  0.476  0.501  0.501  0.152  0.402  0.177 -0.221  0.152  0.252  0.177  0.152 -0.196  0.053 -0.146  0.078  0.078  0.028  0.053  0.177 -0.022 -0.047  0.476 -0.022 -0.221  0.152  0.003  0.451  0.352  0.227  0.576  0.103 -0.022 -0.072 -0.047 -0.097 -0.072 -0.221  0.227  0.302  0.053  0.277  0.078 -0.246 -0.047  0.053  0.352 -0.146  0.078  0.227  0.252 -0.047 -0.047  0.028 
 0.426  0.352 -0.072  0.277  0.551  0.501  0.377  0.177  0.078  0.202  0.426  0.426  0.451 -0.097  0.501  0.327  0.202  0.028 -0.171  0.426  0.078  0.152 -0.022  0.426  0.152  0.252  0.352  0.302  0.501  0.476  0.252  0.302  0.003  0.103  0.501  0.476  0.426 -0.196  0.053  0.302  0.177  0.277  0.177  0.676 -0.171  0.277  0.426  0.451  0.501  0.476  0.128  0.402  0.152 -0.221  0.152  0.252  0.177  0.152 -0.196  0.053 -0.146  0.078  0.028  0.003  0.028  0.078 -0.047 -0.072  0.426  0.003 -0.246  0.103  0.003  0.402  0.302  0.227  0.601  0.078 -0.022 -0.097 -0.097 -0.072 -0.047 -0.196  0.227  0.302  0.053  0.252  0.078 -0.246 -0.047  0.028  0.327 -0.146  0.053  0.277  0.277 -0.047 -0.072  0.028 
 0.427  0.352 -0.071  0.278  0.527  0.502  0.377  0.153  0.128  0.228  0.427  0.427  0.427 -0.096  0.477  0.352  0.203  0.028 -0.146  0.427  0.078  0.178 -0.021  0.477  0.153  0.253  0.352  0.278  0.527  0.477  0.228  0.278 -0.021  0.128  0.552  0.477  0.427 -0.196  0.053  0.352  0.178  0.302  0.178  0.676 -0.146  0.278  0.427  0.452  0.502  0.477  0.128  0.402  0.078 -0.246  0.153  0.253  0.178  0.153 -0.196  0.028 -0.146  0.078  0.028  0.003  0.003  0.028 -0.046 -0.071  0.377  0.003 -0.246  0.053  0.003  0.352  0.302  0.203  0.576  0.053 -0.021 -0.096 -0.096 -0.096 -0.046 -0.196  0.203  0.302  0.028  0.253  0.078 -0.221 -0.046 -0.021  0.327 -0.146  0.053  0.302  0.253 -0.046 -0.096  0.003 
 0.446  0.346 -0.052  0.272  0.521  0.496  0.371  0.147  0.147  0.222  0.421  0.446  0.446 -0.102  0.471  0.396  0.197  0.022 -0.152  0.446  0.072  0.172 -0.027  0.570  0.097  0.272  0.346  0.272  0.521  0.471  0.222  0.296 -0.027  0.147  0.546  0.471  0.421 -0.202  0.097  0.346  0.172  0.296  0.147  0.670 -0.127  0.296  0.421  0.446  0.496  0.471  0.122  0.371  0.072 -0.252  0.147  0.247  0.147  0.147 -0.202  0.022 -0.152  0.072  0.022 -0.002  0.022  0.022 -0.052 -0.077  0.346 -0.002 -0.252  0.047 -0.002  0.346  0.296  0.197  0.570  0.047 -0.027 -0.102 -0.127 -0.077 -0.052 -0.202  0.172  0.296  0.047  0.247  0.097 -0.227 -0.027 -0.052  0.296 -0.152  0.047  0.296  0.247 -0.052 -0.102 -0.002 
 0.442  0.343 -0.031  0.268  0.517  0.542  0.393  0.119  0.218  0.218  0.418  0.467  0.442 -0.106  0.418  0.418  0.143  0.019 -0.155  0.442  0.069  0.143 -0.031  0.617  0.094  0.293  0.343  0.268  0.542  0.442  0.193  0.318  0.019  0.168  0.542  0.467  0.418 -0.180  0.094  0.343  0.143  0.268  0.143  0.667 -0.106  0.293  0.442  0.442  0.467  0.467  0.119  0.318  0.019 -0.255  0.168  0.168  0.143  0.119 -0.205 -0.006 -0.131  0.069  0.044 -0.031  0.019  0.019 -0.056 -0.081  0.318 -0.006 -0.255  0.044 -0.031  0.318  0.268  0.168  0.567  0.044 -0.031 -0.106 -0.131 -0.106 -0.056 -0.205  0.168  0.318  0.044  0.243  0.168 -0.230 -0.031 -0.081  0.293 -0.131  0.044  0.268  0.243 -0.006 -0.106 -0.006 
 0.439  0.290  0.016  0.290  0.439  0.564  0.439  0.165  0.190  0.215  0.415  0.464  0.365 -0.084  0.439  0.415  0.141  0.041 -0.158  0.439 -0.034  0.116 -0.109  0.539 -0.034  0.290  0.290  0.315  0.539  0.415  0.165  0.240  0.041  0.190  0.489  0.464  0.390 -0.134  0.116  0.365  0.141  0.290  0.141  0.614 -0.059  0.240  0.365  0.390  0.514  0.439  0.141  0.141 -0.034 -0.233  0.141  0.066  0.165  0.141 -0.134  0.016 -0.109  0.016 -0.009 -0.034  0.041 -0.009 -0.059 -0.109  0.265 -0.059 -0.183  0.066 -0.009  0.215  0.215  0.141  0.489  0.016 -0.009 -0.034 -0.109 -0.183 -0.034 -0.158  0.165  0.215  0.016  0.141  0.141 -0.183 -0.034 -0.084  0.240 -0.109  0.116  0.290  0.215  0.041 -0.109 -0.009 
 0.378  0.378 -0.045  0.229  0.279  0.478  0.353  0.129  0.079  0.129  0.378  0.254  0.303 -0.020  0.378  0.254  0.079 -0.045 -0.120  0.453 -0.020  0.179 -0.070  0.478  0.004  0.129  0.328  0.353  0.503  0.279  0.179  0.229 -0.070  0.154  0.478  0.478  0.378 -0.095  0.079  0.303  0.129  0.328  0.079  0.503 -0.120  0.254  0.353  0.328  0.478  0.353  0.154  0.104 -0.045 -0.170  0.029 -0.045  0.129  0.129 -0.095  0.029 -0.095  0.079  0.004 -0.020 -0.020  0.004 -0.020 -0.045  0.328 -0.070 -0.095  0.029 -0.045  0.129  0.179  0.104  0.428  0.004 -0.045  0.004 -0.095 -0.095  0.029 -0.120  0.129  0.154  0.029  0.054  0.004 -0.145 -0.020 -0.070  0.179 -0.045  0.104  0.254  0.129  0.054 -0.045 -0.095 
 0.242  0.392 -0.032  0.242  0.217  0.491  0.342  0.118  0.018  0.118  0.392  0.267  0.317 -0.007  0.342  0.217  0.093 -0.057 -0.132  0.441 -0.007  0.192 -0.057  0.441  0.018  0.118  0.292  0.342  0.466  0.267  0.167  0.242 -0.032  0.068  0.466  0.466  0.417 -0.057  0.068  0.267  0.118  0.367  0.068  0.516 -0.107  0.242  0.367  0.342  0.516  0.342  0.142  0.043 -0.057 -0.156  0.018 -0.057  0.068  0.093 -0.082  0.018 -0.057  0.068  0.018 -0.007 -0.007  0.018 -0.007 -0.032  0.317 -0.057 -0.082 -0.007 -0.082  0.192  0.118  0.118  0.441  0.018 -0.032 -0.007 -0.107 -0.082  0.043 -0.107  0.118  0.068 -0.082  0.068 -0.057 -0.132 -0.032 -0.032  0.167 -0.057  0.118  0.242  0.068  0.043 -0.057 -0.082 
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 0.171  0.371 -0.003  0.221  0.097  0.495  0.296  0.146 -0.028  0.122  0.221  0.196  0.321 -0.003  0.321  0.146  0.097 -0.028 -0.128  0.445 -0.003  0.196 -0.028  0.396 -0.003  0.122  0.296  0.371  0.346  0.196  0.097  0.221 -0.003  0.022  0.321  0.470  0.421 -0.028  0.022  0.196  0.072  0.396  0.072  0.545 -0.078  0.246  0.371  0.271  0.470  0.346  0.122 -0.028 -0.053 -0.128 -0.028 -0.028  0.047  0.022 -0.053  0.022 -0.053  0.072  0.022 -0.028 -0.053  0.047 -0.003 -0.003  0.146 -0.128 -0.053  0.022 -0.053  0.196  0.047  0.097  0.445  0.047 -0.003 -0.003 -0.078 -0.128 -0.003 -0.053  0.047  0.022 -0.053 -0.003 -0.078 -0.128 -0.053  0.022  0.146 -0.028  0.122  0.171  0.047  0.047 -0.028 -0.128 
 0.091  0.315  0.016  0.215  0.116  0.539  0.265  0.116  0.016  0.116  0.141  0.141  0.265 -0.009  0.215  0.091  0.091 -0.009 -0.109  0.464 -0.009  0.215 -0.059  0.439  0.016  0.141  0.315  0.390  0.190  0.190  0.116  0.091  0.016 -0.034  0.315  0.489  0.390 -0.034 -0.009  0.116  0.041  0.415  0.091  0.415 -0.059  0.265  0.365  0.265  0.439  0.340  0.116 -0.034 -0.034 -0.109 -0.034 -0.009 -0.034 -0.034 -0.034  0.041 -0.059  0.091  0.066 -0.009 -0.059  0.041 -0.034  0.016  0.116 -0.109 -0.059  0.016 -0.109  0.190  0.066  0.041  0.365  0.066  0.016  0.016 -0.059 -0.084  0.016 -0.034  0.041  0.041 -0.059 -0.059 -0.084 -0.109 -0.059  0.041  0.116 -0.009  0.116  0.116  0.041  0.041 -0.059 -0.109 
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-0.026 -0.001 -0.026 -0.001 -0.026  0.995  0.024  0.024  0.024  0.124 -0.001  0.173  0.124 -0.026  0.074 -0.026 -0.001 -0.026 -0.026  0.024  0.049 -0.026 -0.001  0.024 -0.026 -0.001 -0.001  0.198  0.049  0.049 -0.001 -0.001 -0.001  0.024  0.049  0.074 -0.026 -0.001  0.024  0.024 -0.026  0.049 -0.001  0.024 -0.026 -0.026 -0.026  0.074 -0.001  0.099  0.074 -0.001 -0.026 -0.026 -0.001 -0.001 -0.001  0.024  0.024 -0.001 -0.026  0.024 -0.026  0.024 -0.026 -0.001 -0.001 -0.001 -0.026 -0.026 -0.026 -0.026 -0.026 -0.001 -0.001  0.049 -0.001 -0.026 -0.001 -0.026 -0.001 -0.001  0.024  0.024 -0.001  0.024 -0.026  0.024 -0.001 -0.001 -0.026 -0.001 -0.026 -0.001  0.074  0.124 -0.026 -0.026 -0.001 -0.001 
-0.027 -0.002 -0.052 -0.027 -0.002  0.970  0.048  0.048 -0.002  0.322 -0.027  0.446  0.172 -0.052  0.073 -0.002 -0.002 -0.027 -0.002 -0.002  0.023 -0.027  0.023  0.023 -0.052 -0.002 -0.027  0.546  0.172  0.073 -0.027  0.023  0.048 -0.002  0.048  0.123 -0.002 -0.002 -0.002  0.098 -0.052  0.023 -0.027  0.023 -0.052 -0.052 -0.027  0.098 -0.002  0.172  0.172  0.023 -0.027  0.023 -0.002  0.023 -0.002  0.048  0.023  0.023 -0.052 -0.002 -0.052  0.023 -0.027 -0.002 -0.027 -0.027 -0.027 -0.027 -0.052 -0.052 -0.027  0.073 -0.027  0.023 -0.027 -0.052 -0.027 -0.002 -0.002 -0.027  0.023 -0.002 -0.002  0.023 -0.027  0.023  0.048 -0.002 -0.027 -0.002 -0.052  0.023  0.123  0.322 -0.052 -0.052  0.023 -0.002 
 0.077 -0.023 -0.098 -0.048  0.002  0.924  0.226  0.027  0.002  0.600 -0.048  0.625  0.351 -0.098  0.102  0.127  0.052 -0.048 -0.048  0.027  0.127  0.002 -0.023  0.002 -0.023  0.027 -0.048  0.749  0.201  0.102 -0.073  0.102  0.127 -0.048  0.027  0.102  0.002 -0.023 -0.023  0.301 -0.048 -0.023 -0.023  0.002 -0.098 -0.073  0.002  0.151 -0.023  0.226  0.226  0.052 -0.048  0.077 -0.023  0.052  0.052  0.151 -0.023  0.002 -0.048 -0.048 -0.023  0.052 -0.073  0.002  0.027 -0.048  0.002 -0.073 -0.098 -0.073  0.002  0.052  0.052  0.027 -0.023  0.002 -0.048 -0.023  0.002 -0.073  0.077 -0.048 -0.023  0.052 -0.073  0.077  0.176 -0.048 -0.048 -0.023 -0.073  0.002  0.127  0.650 -0.023 -0.098  0.077 -0.048 
 0.261  0.061 -0.088  0.011  0.136  0.858  0.410  0.061 -0.013  0.809 -0.088  0.858  0.560 -0.063  0.086  0.111  0.111 -0.088 -0.088  0.086  0.111  0.136 -0.088  0.061 -0.038  0.036 -0.038  0.858  0.535  0.161 -0.038  0.161  0.136 -0.063  0.086  0.236  0.111 -0.063  0.036  0.435  0.011 -0.013  0.161  0.061 -0.038 -0.088  0.011  0.261  0.186  0.310  0.335  0.061 -0.088  0.061 -0.063  0.036  0.161  0.186  0.036  0.111 -0.038 -0.038 -0.038  0.011  0.011  0.011  0.086 -0.063  0.011 -0.138 -0.138 -0.038 -0.013  0.061  0.011  0.136 -0.063  0.011 -0.063 -0.063 -0.038 -0.113  0.111 -0.088 -0.013  0.161 -0.038  0.061  0.136 -0.113 -0.113 -0.013 -0.113  0.011  0.086  0.858 -0.013 -0.063  0.061 -0.113 
 0.483  0.059 -0.090  0.034  0.134  0.832  0.408  0.034 -0.015  0.782 -0.090  0.832  0.657 -0.065  0.084  0.159  0.109 -0.115 -0.115  0.134  0.109  0.109 -0.115  0.109 -0.065  0.059  0.009  0.832  0.607  0.159 -0.015  0.184  0.134 -0.090  0.109  0.308  0.134 -0.090  0.009  0.558 -0.015  0.084  0.184  0.059 -0.090 -0.090  0.034  0.308  0.234  0.284  0.308  0.059 -0.090  0.059 -0.065  0.009  0.184  0.184  0.059  0.134 -0.090 -0.065 -0.015 -0.015 -0.015 -0.015  0.084 -0.090 -0.015 -0.140 -0.115 -0.065 -0.065  0.134  0.009  0.184 -0.065  0.034 -0.090 -0.065 -0.040 -0.115  0.084 -0.115 -0.015  0.159 -0.040  0.109  0.109 -0.140 -0.140 -0.015 -0.115 -0.015  0.084  0.832 -0.040 -0.065  0.034 -0.140 
 0.561  0.037 -0.012  0.062  0.286  0.785  0.486  0.062 -0.012  0.760 -0.087  0.785  0.735 -0.062  0.112  0.212  0.112 -0.062 -0.112  0.187  0.137  0.112 -0.112  0.212 -0.062  0.062  0.062  0.785  0.710  0.336 -0.012  0.262  0.162 -0.062  0.112  0.411  0.162 -0.137  0.012  0.635 -0.037  0.137  0.237  0.087 -0.087  0.012  0.112  0.436  0.336  0.336  0.336  0.037 -0.087  0.037 -0.062 -0.012  0.237  0.212  0.062  0.162 -0.087 -0.062  0.037 -0.012 -0.062 -0.062  0.087 -0.112  0.062 -0.187 -0.087 -0.062 -0.112  0.137  0.037  0.187  0.012  0.087 -0.062 -0.062  0.012 -0.137  0.037 -0.137  0.112  0.237 -0.062  0.087  0.087 -0.187 -0.162  0.012 -0.062 -0.062  0.037  0.785 -0.062 -0.087 -0.012 -0.162 
 0.662  0.114  0.014  0.189  0.313  0.737  0.538  0.064 -0.010  0.737 -0.035  0.737  0.712 -0.085  0.164  0.189  0.114 -0.085 -0.135  0.288  0.114  0.114 -0.060  0.264 -0.035  0.089  0.139  0.762  0.687  0.388  0.014  0.239  0.189 -0.060  0.164  0.488  0.214 -0.160  0.014  0.637 -0.035  0.164  0.214  0.239 -0.085  0.014  0.313  0.488  0.413  0.338  0.264  0.039 -0.085 -0.010 -0.010 -0.060  0.214  0.164  0.014  0.139 -0.110 -0.085  0.064 -0.035 -0.085 -0.085  0.039 -0.110  0.039 -0.135 -0.110 -0.085 -0.160  0.139  0.014  0.164  0.014  0.064 -0.060 -0.060  0.014 -0.185  0.039 -0.185  0.089  0.214 -0.035  0.114  0.089 -0.235 -0.135 -0.010 -0.010 -0.085  0.039  0.712 -0.060 -0.085 -0.010 -0.160 
 0.638  0.164  0.040  0.189  0.339  0.663  0.513  0.090  0.040  0.712  0.040  0.613  0.638 -0.060  0.214  0.264  0.239 -0.085 -0.159  0.463  0.065  0.140 -0.010  0.414 -0.010  0.164  0.214  0.688  0.638  0.463  0.090  0.264  0.189 -0.085  0.164  0.563  0.264 -0.209 -0.010  0.663 -0.035  0.289  0.214  0.264 -0.035  0.065  0.438  0.513  0.463  0.414  0.189  0.015 -0.135 -0.060  0.040 -0.060  0.239  0.140 -0.035  0.090 -0.110 -0.085  0.090 -0.010 -0.135 -0.060  0.015 -0.060  0.090 -0.159 -0.110 -0.085 -0.159  0.164  0.065  0.164  0.115  0.115 -0.035 -0.060  0.015 -0.159 -0.010 -0.184  0.115  0.289 -0.060  0.065  0.065 -0.259 -0.159 -0.010  0.015 -0.085  0.065  0.588 -0.085 -0.035 -0.010 -0.184 
 0.596  0.172  0.023  0.172  0.347  0.621  0.496  0.098  0.048  0.671  0.098  0.571  0.596 -0.077  0.222  0.247  0.247 -0.052 -0.176  0.446  0.098  0.147 -0.027  0.496 -0.002  0.147  0.297  0.671  0.621  0.446  0.098  0.272  0.197 -0.102  0.247  0.571  0.347 -0.226 -0.002  0.646 -0.027  0.297  0.172  0.422 -0.027  0.098  0.496  0.521  0.446  0.422  0.172 -0.002 -0.151 -0.077  0.023 -0.052  0.222  0.123 -0.052  0.073 -0.127 -0.027  0.098 -0.052 -0.127 -0.052 -0.027 -0.002  0.123 -0.176 -0.102 -0.077 -0.102  0.197  0.123  0.197  0.098  0.123 -0.052 -0.027 -0.027 -0.102 -0.002 -0.201  0.123  0.322 -0.077  0.048  0.098 -0.251 -0.176  0.023  0.098 -0.102  0.048  0.546 -0.002 -0.027 -0.002 -0.201 
 0.487  0.238  0.063  0.188  0.412  0.537  0.487  0.113  0.113  0.611  0.213  0.437  0.537 -0.036  0.263  0.337  0.287 -0.061 -0.161  0.512  0.038  0.138 -0.036  0.512 -0.011  0.138  0.387  0.611  0.537  0.437  0.163  0.312  0.188 -0.061  0.487  0.562  0.362 -0.186 -0.011  0.611  0.088  0.337  0.138  0.462 -0.011  0.138  0.636  0.537  0.462  0.437  0.138 -0.036 -0.161 -0.136  0.063 -0.061  0.188  0.088 -0.136  0.038 -0.161 -0.011  0.113 -0.011 -0.161 -0.036 -0.061 -0.036  0.213 -0.136 -0.111 -0.086 -0.111  0.213  0.113  0.188  0.188  0.113 -0.036  0.013 -0.136 -0.036 -0.011 -0.211  0.088  0.312 -0.086  0.013  0.113 -0.261 -0.161  0.013  0.113 -0.136  0.038  0.487  0.038  0.088 -0.011 -0.186 
 0.481  0.232  0.058  0.207  0.407  0.506  0.481  0.108  0.182  0.556  0.257  0.431  0.531 -0.042  0.282  0.407  0.307 -0.067 -0.142  0.531  0.033  0.133 -0.042  0.506 -0.017  0.133  0.382  0.581  0.556  0.382  0.157  0.332  0.182 -0.042  0.531  0.556  0.382 -0.166 -0.017  0.581  0.058  0.357  0.133  0.506 -0.017  0.207  0.631  0.556  0.456  0.407  0.157 -0.042 -0.166 -0.166  0.133 -0.042  0.182  0.083 -0.142  0.008 -0.166 -0.017  0.108 -0.042 -0.166 -0.042 -0.042 -0.017  0.257 -0.142 -0.117 -0.092 -0.092  0.257  0.133  0.207  0.307  0.133 -0.067  0.008 -0.142 -0.042 -0.017 -0.191  0.083  0.307 -0.067  0.008  0.108 -0.216 -0.142  0.008  0.207 -0.117  0.033  0.407  0.058  0.108  0.008 -0.166 
 0.474  0.250  0.025  0.225  0.474  0.499  0.474  0.125  0.175  0.474  0.275  0.424  0.499 -0.049  0.299  0.424  0.299 -0.074 -0.149  0.524 -0.024  0.150 -0.024  0.573 -0.024  0.150  0.374  0.549  0.549  0.399  0.200  0.349  0.150  0.050  0.549  0.549  0.374 -0.124 -0.024  0.499  0.075  0.324  0.100  0.573  0.000  0.225  0.648  0.524  0.474  0.399  0.150 -0.049 -0.149 -0.199  0.175 -0.024  0.175  0.050 -0.149  0.000 -0.149  0.025  0.100 -0.049 -0.174 -0.024 -0.074 -0.049  0.275 -0.099 -0.174 -0.049 -0.024  0.250  0.100  0.150  0.424  0.125 -0.074  0.025 -0.174 -0.024 -0.074 -0.174  0.100  0.275 -0.049  0.000  0.075 -0.224 -0.124  0.025  0.225 -0.149  0.025  0.299  0.100  0.100 -0.049 -0.149 
 0.425  0.250  0.076  0.225  0.474  0.499  0.449  0.126  0.175  0.474  0.275  0.400  0.499 -0.049  0.300  0.425  0.275 -0.074 -0.148  0.524 -0.074  0.150 -0.024  0.574 -0.024  0.175  0.375  0.524  0.549  0.400  0.225  0.375  0.150  0.051  0.574  0.549  0.375 -0.124 -0.024  0.499  0.076  0.325  0.101  0.599 -0.024  0.250  0.674  0.499  0.474  0.400  0.150 -0.024 -0.124 -0.198  0.175 -0.024  0.175  0.051 -0.148  0.001 -0.148  0.026  0.101 -0.074 -0.173 -0.049 -0.099 -0.049  0.275 -0.074 -0.173 -0.049 -0.049  0.250  0.076  0.126  0.425  0.126 -0.049  0.026 -0.173  0.001 -0.099 -0.173  0.101  0.300 -0.049  0.051  0.076 -0.223 -0.124  0.026  0.225 -0.148  0.026  0.300  0.101  0.101 -0.074 -0.148 
 0.422  0.297  0.073  0.247  0.471  0.496  0.446  0.098  0.147  0.446  0.272  0.397  0.521 -0.002  0.297  0.446  0.222 -0.077 -0.151  0.521 -0.077  0.147 -0.027  0.571 -0.027  0.147  0.372  0.471  0.546  0.397  0.222  0.397  0.123  0.048  0.596  0.521  0.422 -0.127 -0.002  0.496  0.098  0.297  0.098  0.596 -0.027  0.247  0.671  0.471  0.471  0.397  0.123 -0.027 -0.127 -0.226  0.172 -0.002  0.172  0.048 -0.151 -0.002 -0.151  0.023  0.098 -0.102 -0.176 -0.052 -0.102 -0.052  0.272 -0.052 -0.176 -0.052 -0.052  0.247  0.048  0.098  0.422  0.172 -0.052  0.023 -0.176 -0.002 -0.077 -0.176  0.098  0.297 -0.052  0.048  0.023 -0.226 -0.127  0.023  0.222 -0.151  0.023  0.272  0.073  0.098 -0.127 -0.127 
 0.419  0.294  0.070  0.245  0.494  0.469  0.444  0.095  0.145  0.419  0.270  0.394  0.519 -0.004  0.294  0.494  0.245 -0.079 -0.154  0.519 -0.079  0.145 -0.029  0.568 -0.029  0.145  0.369  0.469  0.544  0.419  0.220  0.444  0.120  0.070  0.593  0.544  0.419 -0.129 -0.004  0.494  0.095  0.294  0.095  0.593 -0.029  0.294  0.668  0.469  0.469  0.394  0.095 -0.029 -0.129 -0.254  0.195 -0.004  0.145  0.045 -0.154 -0.004 -0.154  0.020  0.095 -0.104 -0.179 -0.054 -0.129 -0.054  0.294 -0.054 -0.179 -0.054 -0.054  0.245  0.045  0.095  0.419  0.170 -0.054  0.045 -0.179 -0.004 -0.079 -0.179  0.095  0.294 -0.054  0.045  0.045 -0.229 -0.129  0.020  0.220 -0.154  0.020  0.245  0.070  0.095 -0.129 -0.129 
 0.393  0.293  0.069  0.244  0.493  0.468  0.443  0.094  0.144  0.418  0.269  0.368  0.518  0.019  0.269  0.543  0.244 -0.080 -0.180  0.493 -0.080  0.144 -0.005  0.592 -0.005  0.119  0.368  0.418  0.543  0.443  0.269  0.443  0.119  0.144  0.592  0.568  0.418 -0.130 -0.005  0.493  0.094  0.293  0.119  0.592 -0.030  0.318  0.667  0.468  0.468  0.368  0.069 -0.030 -0.130 -0.255  0.194 -0.005  0.144  0.044 -0.155 -0.005 -0.155  0.019  0.094 -0.130 -0.180 -0.055 -0.130 -0.055  0.293 -0.030 -0.180 -0.055 -0.055  0.244  0.044  0.094  0.418  0.194 -0.055  0.044 -0.180 -0.005 -0.080 -0.180  0.094  0.293 -0.055  0.044  0.044 -0.230 -0.080  0.019  0.219 -0.155  0.019  0.219  0.069  0.094 -0.130 -0.130 
 0.394  0.294  0.070  0.245  0.494  0.469  0.444  0.095  0.145  0.419  0.270  0.369  0.519  0.020  0.270  0.544  0.220 -0.079 -0.204  0.469 -0.079  0.170 -0.004  0.593 -0.004  0.120  0.369  0.369  0.544  0.444  0.270  0.444  0.120  0.145  0.593  0.544  0.419 -0.129 -0.004  0.494  0.095  0.294  0.120  0.568 -0.029  0.344  0.668  0.444  0.469  0.369  0.070 -0.054 -0.104 -0.254  0.195 -0.004  0.145  0.045 -0.154 -0.004 -0.154  0.020  0.095 -0.129 -0.179 -0.054 -0.154 -0.054  0.294 -0.029 -0.179 -0.054 -0.029  0.245  0.045  0.095  0.419  0.195 -0.054  0.045 -0.179 -0.004 -0.079 -0.179  0.095  0.294 -0.054  0.045  0.045 -0.229 -0.079  0.020  0.220 -0.179  0.020  0.220  0.070  0.095 -0.129 -0.129 
 0.394  0.294  0.045  0.244  0.493  0.468  0.468  0.120  0.144  0.419  0.269  0.344  0.518  0.045  0.269  0.543  0.219 -0.080 -0.229  0.468 -0.080  0.169 -0.005  0.593 -0.005  0.144  0.369  0.344  0.518  0.419  0.269  0.443  0.120  0.144  0.593  0.543  0.419 -0.130 -0.005  0.468  0.095  0.294  0.120  0.568 -0.005  0.369  0.668  0.443  0.468  0.369  0.070 -0.080 -0.105 -0.229  0.194 -0.005  0.144  0.045 -0.154 -0.005 -0.154  0.020  0.095 -0.130 -0.154 -0.055 -0.154 -0.055  0.244 -0.030 -0.179 -0.055 -0.005  0.244  0.045  0.095  0.419  0.194 -0.055  0.045 -0.179 -0.030 -0.080 -0.179  0.095  0.294 -0.055  0.045  0.020 -0.229 -0.080  0.020  0.219 -0.204  0.020  0.219  0.070  0.120 -0.154 -0.130 
 0.368  0.293  0.044  0.243  0.492  0.467  0.467  0.119  0.143  0.418  0.268  0.343  0.517  0.019  0.268  0.542  0.218 -0.081 -0.230  0.492 -0.081  0.168 -0.006  0.592 -0.006  0.143  0.368  0.368  0.517  0.418  0.268  0.442  0.119  0.143  0.592  0.542  0.418 -0.131 -0.006  0.467  0.094  0.293  0.119  0.567 -0.006  0.368  0.667  0.442  0.467  0.368  0.044 -0.081 -0.106 -0.230  0.193 -0.006  0.143  0.044 -0.155 -0.006 -0.155  0.019  0.094 -0.106 -0.155 -0.056 -0.131 -0.056  0.268 -0.031 -0.180 -0.056 -0.006  0.243  0.044  0.094  0.418  0.218 -0.056  0.044 -0.180 -0.031 -0.081 -0.180  0.094  0.293 -0.081  0.044  0.019 -0.230 -0.081  0.019  0.218 -0.205  0.019  0.218  0.069  0.119 -0.155 -0.131 
 0.367  0.292  0.043  0.242  0.491  0.466  0.441  0.118  0.142  0.417  0.267  0.367  0.516  0.018  0.267  0.541  0.217 -0.082 -0.231  0.491 -0.057  0.167 -0.007  0.591 -0.007  0.142  0.367  0.367  0.516  0.417  0.292  0.441  0.118  0.142  0.591  0.541  0.417 -0.132 -0.007  0.466  0.093  0.292  0.142  0.566 -0.007  0.367  0.666  0.441  0.466  0.367  0.043 -0.082 -0.107 -0.231  0.192  0.018  0.142  0.043 -0.156 -0.007 -0.156  0.018  0.093 -0.107 -0.156 -0.057 -0.132 -0.057  0.267 -0.032 -0.181 -0.057 -0.007  0.242  0.043  0.093  0.417  0.217 -0.057  0.043 -0.181 -0.032 -0.082 -0.181  0.093  0.292 -0.082  0.043  0.018 -0.231 -0.082  0.018  0.217 -0.206  0.018  0.217  0.068  0.142 -0.156 -0.132 
 0.344  0.369 -0.005  0.269  0.443  0.394  0.344  0.169  0.144  0.344  0.269  0.269  0.493  0.045  0.219  0.419  0.244 -0.055 -0.229  0.419 -0.030  0.169 -0.030  0.518  0.045  0.169  0.419  0.369  0.493  0.344  0.244  0.394  0.020  0.095  0.518  0.493  0.419 -0.105 -0.055  0.394  0.045  0.294  0.095  0.543  0.045  0.344  0.618  0.394  0.443  0.244  0.095 -0.005 -0.105 -0.154  0.244 -0.055  0.169 -0.030 -0.130  0.020 -0.105  0.095  0.020 -0.080 -0.080 -0.055 -0.105 -0.030  0.294 -0.080 -0.154 -0.030 -0.005  0.144  0.045  0.144  0.443  0.095 -0.030 -0.030 -0.130 -0.030 -0.005 -0.130  0.095  0.194 -0.055  0.020  0.020 -0.204 -0.080  0.020  0.169 -0.179  0.045  0.219  0.095  0.194 -0.080 -0.105 
 0.257  0.381 -0.017  0.257  0.431  0.431  0.381  0.132  0.082  0.232  0.232  0.132  0.431 -0.017  0.182  0.381  0.107 -0.067 -0.142  0.456 -0.042  0.182 -0.042  0.431  0.007  0.107  0.306  0.331  0.456  0.207  0.232  0.232  0.032  0.057  0.431  0.456  0.406 -0.092 -0.042  0.306  0.107  0.356  0.082  0.580 -0.042  0.356  0.481  0.331  0.456  0.232  0.132 -0.017 -0.092 -0.167  0.082 -0.042  0.132 -0.042 -0.092  0.032 -0.017  0.157  0.007 -0.042 -0.067  0.007 -0.092 -0.042  0.157 -0.117 -0.117  0.007 -0.017  0.107  0.132  0.182  0.306  0.132 -0.042 -0.017 -0.092 -0.042  0.057 -0.042  0.057  0.132 -0.067 -0.092 -0.067 -0.142 -0.042 -0.042  0.232 -0.092  0.082  0.182  0.057  0.157 -0.042 -0.142 
 0.176  0.376 -0.023  0.251  0.450  0.450  0.376  0.127  0.027  0.201  0.151  0.151  0.426  0.002  0.102  0.351  0.077 -0.073 -0.123  0.426 -0.023  0.201 -0.023  0.426  0.002  0.102  0.326  0.351  0.301  0.226  0.251  0.201  0.002  0.052  0.376  0.450  0.426 -0.073 -0.023  0.301  0.127  0.376  0.102  0.500 -0.023  0.376  0.450  0.301  0.500  0.251  0.176 -0.023 -0.073 -0.147  0.077 -0.023  0.102 -0.023 -0.073  0.052 -0.048  0.176  0.027 -0.023 -0.073 -0.023 -0.098  0.002  0.102 -0.147 -0.123  0.002 -0.023  0.102  0.127  0.201  0.276  0.151 -0.023  0.002 -0.073 -0.073  0.052 -0.073  0.077  0.102 -0.023 -0.073 -0.098 -0.123 -0.023 -0.048  0.251 -0.073  0.077  0.102  0.027  0.127 -0.048 -0.123 
 0.147  0.321 -0.002  0.222  0.446  0.471  0.346  0.147  0.022  0.147  0.147  0.147  0.421  0.022  0.047  0.247  0.022 -0.052 -0.102  0.446 -0.002  0.222 -0.002  0.371 -0.002  0.122  0.346  0.371  0.272  0.222  0.272  0.172 -0.002  0.047  0.296  0.471  0.396 -0.102 -0.027  0.197  0.097  0.346  0.122  0.471 -0.052  0.346  0.421  0.247  0.471  0.197  0.172 -0.002 -0.052 -0.127  0.097 -0.002  0.122 -0.052 -0.052  0.072 -0.052  0.172  0.022 -0.002 -0.052 -0.002 -0.077  0.022  0.047 -0.127 -0.102  0.022 -0.027  0.122  0.097  0.222  0.272  0.147 -0.002  0.022 -0.052 -0.102  0.047 -0.052  0.097  0.097 -0.002 -0.077 -0.077 -0.102 -0.002 -0.027  0.247 -0.052  0.072  0.122  0.047  0.072 -0.052 -0.127 
 0.130  0.354  0.005  0.204  0.453  0.453  0.354  0.154  0.005  0.154  0.154  0.130  0.404  0.030  0.055  0.179  0.030 -0.045 -0.095  0.453  0.005  0.229  0.005  0.379  0.005  0.130  0.354  0.354  0.229  0.204  0.204  0.179  0.005  0.030  0.279  0.478  0.354 -0.095 -0.045  0.130  0.080  0.354  0.105  0.404 -0.045  0.304  0.404  0.254  0.503  0.179  0.154  0.005 -0.045 -0.120  0.005 -0.020  0.204 -0.095 -0.045  0.055 -0.045  0.179  0.030 -0.020 -0.070  0.030 -0.070  0.030  0.055 -0.120 -0.095  0.030 -0.020  0.154  0.080  0.204  0.279  0.130  0.030  0.005 -0.070 -0.095  0.055 -0.045  0.055  0.105 -0.020 -0.070 -0.070 -0.095 -0.020 -0.020  0.254 -0.045  0.080  0.154  0.055  0.080 -0.020 -0.120 
 0.143  0.317  0.018  0.193  0.467  0.392  0.317  0.143  0.018  0.168  0.093  0.143  0.367  0.018  0.043  0.143  0.018 -0.056 -0.106  0.442 -0.006  0.218 -0.006  0.367 -0.006  0.143  0.367  0.317  0.218  0.218  0.118  0.068  0.018 -0.031  0.268  0.492  0.268 -0.081 -0.056  0.068  0.018  0.367  0.118  0.342 -0.031  0.317  0.392  0.193  0.517  0.193  0.143  0.018 -0.031 -0.106 -0.006 -0.006  0.193 -0.106 -0.031  0.043 -0.056  0.168  0.018 -0.006 -0.056  0.018 -0.056  0.018  0.068 -0.106 -0.081  0.018 -0.056  0.168  0.068  0.193  0.243  0.093  0.043  0.018 -0.081 -0.081  0.043 -0.031 -0.006  0.093 -0.031 -0.056 -0.106 -0.106 -0.006 -0.031  0.243 -0.031  0.018  0.118  0.068  0.093 -0.006 -0.106 
 0.126  0.325  0.026  0.200  0.474  0.375  0.325  0.150  0.026  0.175  0.101  0.101  0.350  0.026  0.051  0.076  0.026 -0.049 -0.099  0.449  0.001  0.200  0.001  0.350  0.001  0.150  0.375  0.300  0.225  0.225  0.126  0.051  0.026 -0.024  0.250  0.474  0.275 -0.074 -0.049  0.051  0.026  0.375  0.126  0.300 -0.024  0.300  0.375  0.150  0.499  0.175  0.101  0.026 -0.024 -0.099  0.001 -0.024  0.175 -0.099 -0.024  0.051 -0.049  0.175  0.026  0.001 -0.049  0.001 -0.074  0.026  0.051 -0.099 -0.074  0.001 -0.049  0.150  0.051  0.200  0.200  0.076  0.051  0.001 -0.074 -0.074  0.051 -0.049 -0.024  0.101 -0.024 -0.074 -0.099 -0.099  0.001 -0.024  0.225 -0.024  0.026  0.101  0.076  0.101  0.001 -0.099 
 0.134  0.308  0.034  0.209  0.458  0.308  0.333  0.159 -0.015  0.184  0.109  0.109  0.358  0.009  0.059  0.034  0.034 -0.040 -0.090  0.458 -0.015  0.209  0.009  0.284 -0.015  0.159  0.358  0.308  0.209  0.259  0.134  0.059  0.034 -0.015  0.134  0.483  0.259 -0.090 -0.040  0.059 -0.040  0.383  0.134  0.284 -0.040  0.284  0.358  0.134  0.508  0.184  0.059  0.034 -0.015 -0.090 -0.015 -0.015  0.134 -0.065 -0.040  0.009 -0.040  0.159  0.009 -0.015 -0.040  0.009 -0.090  0.009  0.009 -0.090 -0.090  0.009 -0.040  0.109  0.059  0.209  0.109  0.034  0.059  0.009 -0.065 -0.090  0.059 -0.065 -0.015  0.084 -0.040 -0.065 -0.090 -0.090  0.009 -0.065  0.134 -0.015  0.034  0.109  0.084  0.084  0.009 -0.090 
 0.139  0.313  0.039  0.188  0.462  0.263  0.338  0.139 -0.011  0.188  0.114  0.114  0.363  0.014  0.064  0.039  0.039 -0.036 -0.086  0.413 -0.011  0.188  0.014  0.238 -0.036  0.163  0.363  0.313  0.213  0.263  0.139  0.064  0.039 -0.036  0.139  0.487  0.263 -0.086 -0.036  0.064 -0.036  0.388  0.139  0.288 -0.036  0.238  0.338  0.089  0.512  0.188  0.064  0.039 -0.011 -0.086 -0.036 -0.036  0.139 -0.061 -0.036  0.014 -0.061  0.139  0.014 -0.011 -0.036  0.014 -0.086 -0.036 -0.011 -0.086 -0.086  0.014 -0.036  0.089  0.064  0.188  0.089  0.039  0.064  0.014 -0.061 -0.086  0.064 -0.061 -0.011  0.089 -0.036 -0.061 -0.086 -0.086  0.014 -0.061  0.139 -0.011  0.039  0.064  0.039  0.089  0.014 -0.086 
 0.102  0.301  0.027  0.177  0.451  0.227  0.277  0.152 -0.022  0.177  0.052  0.127  0.277  0.002  0.077  0.027  0.027 -0.022 -0.072  0.326 -0.022  0.127  0.002  0.202 -0.022  0.177  0.376  0.301  0.177  0.252  0.152  0.077  0.027 -0.047  0.102  0.476  0.202 -0.072 -0.022  0.027 -0.047  0.401  0.127  0.252 -0.047  0.227  0.351  0.027  0.376  0.177  0.002 -0.022 -0.022 -0.072 -0.022 -0.022  0.052 -0.047 -0.022  0.002 -0.047  0.127 -0.022 -0.022 -0.022 -0.022 -0.072 -0.022  0.002 -0.072 -0.072  0.027 -0.022  0.077  0.077  0.077  0.077  0.002  0.052  0.027 -0.047 -0.072  0.027 -0.072  0.002  0.077  0.002 -0.047 -0.072 -0.072 -0.047 -0.047  0.052 -0.022  0.027  0.052  0.027  0.052  0.027 -0.072 
 0.090  0.239  0.015  0.189  0.339  0.189  0.214  0.164 -0.010  0.164 -0.010  0.040  0.239 -0.010  0.065  0.040  0.040 -0.010 -0.060  0.214 -0.010  0.090  0.015  0.090 -0.010  0.164  0.339  0.239  0.164  0.264  0.164  0.090  0.040 -0.035  0.090  0.588  0.189 -0.060 -0.035 -0.035 -0.035  0.339  0.140  0.239 -0.035  0.239  0.339  0.015  0.339  0.140  0.015 -0.060 -0.010 -0.060 -0.010 -0.060  0.015 -0.035 -0.010 -0.010 -0.035  0.065  0.015 -0.035 -0.010 -0.035 -0.060 -0.010 -0.010 -0.060 -0.060  0.015 -0.035  0.090  0.015  0.065  0.040  0.015  0.040  0.015 -0.035 -0.060  0.040 -0.060 -0.010  0.015  0.015 -0.035 -0.060 -0.060 -0.035 -0.035  0.015 -0.035  0.040  0.015  0.015  0.015  0.015 -0.035 
 0.082  0.107  0.007  0.132  0.281  0.132  0.206  0.181 -0.043  0.107  0.007  0.057  0.181 -0.018  0.057  0.032  0.032  0.007 -0.043  0.132  0.007  0.082  0.007  0.032  0.007  0.156  0.281  0.132  0.082  0.281  0.032  0.082  0.007 -0.043  0.082  0.605  0.107 -0.043 -0.018 -0.018 -0.018  0.206  0.107  0.206 -0.043  0.281  0.256  0.007  0.206  0.132  0.007 -0.043 -0.018 -0.043 -0.043 -0.043 -0.043 -0.018 -0.018 -0.018 -0.043  0.057  0.007 -0.018  0.032 -0.018 -0.043 -0.043 -0.018 -0.043 -0.043  0.032 -0.018  0.057  0.007  0.057  0.057  0.032  0.057 -0.018 -0.018 -0.043  0.032 -0.043  0.007 -0.018 -0.018 -0.018 -0.043 -0.043 -0.018 -0.043  0.007 -0.018  0.032 -0.018  0.007  0.032  0.007 -0.018 
 0.068  0.043 -0.031  0.143  0.193  0.118  0.193  0.143 -0.031  0.043  0.018 -0.006  0.168 -0.006  0.068  0.043  0.018  0.018 -0.031  0.068 -0.006  0.068 -0.006  0.043 -0.006  0.118  0.193  0.118  0.093  0.243  0.043  0.068  0.018 -0.031  0.068  0.567  0.093 -0.031 -0.031 -0.006 -0.006  0.118  0.093  0.093 -0.031  0.168  0.168  0.018  0.118  0.118 -0.006 -0.031 -0.006 -0.031 -0.031 -0.031 -0.031 -0.006 -0.006 -0.006 -0.031  0.018 -0.006 -0.031 -0.006 -0.006 -0.031 -0.031 -0.031 -0.031 -0.031  0.018 -0.031  0.018  0.018  0.068  0.068  0.043  0.043 -0.006 -0.031 -0.031  0.018 -0.031 -0.006 -0.006 -0.006 -0.006 -0.031 -0.031 -0.031 -0.031 -0.006 -0.006  0.018 -0.006  0.018  0.043 -0.006 -0.006 
 0.007  0.007 -0.017  0.107  0.057  0.082  0.107  0.107 -0.017  0.057  0.032 -0.017  0.107  0.007  0.007  0.007 -0.017  0.032 -0.017  0.007  0.007  0.032  0.007 -0.017  0.007  0.032  0.107  0.007  0.057  0.057 -0.017  0.032  0.007 -0.017  0.032  0.580  0.032 -0.017 -0.017 -0.017  0.007  0.007  0.057  0.057 -0.017  0.057  0.057  0.032  0.007  0.082 -0.017 -0.017  0.007 -0.017 -0.017 -0.017 -0.017  0.007 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017  0.007 -0.017  0.032 -0.017  0.082  0.057  0.032 -0.017 -0.017 -0.017 -0.017  0.007 -0.017 -0.017 -0.017  0.007  0.007 -0.017 -0.017 -0.017 -0.017 -0.017 -0.017  0.032  0.007  0.007  0.007 -0.017  0.007 
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 0.007  0.057  0.032 -0.018  0.007 -0.018  0.007 -0.018 -0.043  0.032  0.007 -0.043 -0.043 -0.043  0.007 -0.018 -0.018  0.007 -0.043 -0.043  0.057  0.032 -0.018 -0.018  0.007 -0.043  0.032  0.007  0.007 -0.018  0.057 -0.043 -0.018 -0.018  0.057 -0.018  0.132  0.057 -0.018  0.007  0.057 -0.018  0.007  0.007 -0.043  0.057 -0.043  0.082  0.007 -0.043  0.007 -0.043 -0.018 -0.018 -0.018  0.032 -0.043 -0.043  0.007 -0.018 -0.018  0.007 -0.018 -0.018 -0.018 -0.018  0.007 -0.018  0.032  0.032 -0.018  0.007  0.107 -0.043  0.007 -0.018 -0.043 -0.043 -0.018  0.007 -0.018 -0.018  0.032  0.007 -0.018  0.057 -0.043  0.007 -0.043 -0.043  0.007 -0.018  0.082 -0.018  0.007  0.007 -0.018  0.057 -0.018 -0.018 
 0.009  0.059  0.034 -0.016 -0.016 -0.016  0.009 -0.016 -0.041  0.034  0.009 -0.041 -0.041 -0.041  0.009 -0.016 -0.016  0.009 -0.041 -0.041  0.059  0.034 -0.016 -0.016  0.009 -0.041  0.009  0.009  0.009 -0.016  0.059 -0.041 -0.016 -0.016  0.059 -0.016  0.134  0.059 -0.041  0.009  0.034 -0.016  0.009  0.009 -0.041  0.059 -0.041  0.084  0.009 -0.041  0.009 -0.041 -0.016 -0.016 -0.016  0.034 -0.041 -0.041  0.009 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016  0.009 -0.016  0.034  0.034 -0.016  0.009  0.084 -0.041  0.009 -0.016 -0.041 -0.041 -0.041  0.009 -0.016 -0.016  0.034  0.009 -0.016  0.009 -0.041  0.009 -0.041 -0.041  0.009 -0.016  0.034 -0.016  0.009  0.009 -0.016  0.059 -0.016 -0.016 
 0.009  0.059  0.034 -0.016 -0.016 -0.016  0.009 -0.016 -0.041  0.034  0.009 -0.041 -0.041 -0.041  0.009 -0.016 -0.016  0.009 -0.041 -0.041  0.059  0.034 -0.016 -0.016  0.009 -0.041  0.009  0.009  0.009 -0.016  0.059 -0.041 -0.016 -0.016  0.059 -0.016  0.134  0.059 -0.041  0.009  0.034 -0.016  0.009  0.009 -0.041  0.059 -0.041  0.084  0.009 -0.041  0.009 -0.041 -0.016 -0.016 -0.016  0.034 -0.041 -0.041  0.009 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016  0.009 -0.016  0.034  0.034 -0.016  0.009  0.084 -0.041  0.009 -0.016 -0.041 -0.041 -0.041  0.009 -0.016 -0.016  0.034  0.009 -0.016  0.009 -0.041  0.009 -0.041 -0.041  0.009 -0.016  0.034 -0.016  0.009  0.009 -0.016  0.059 -0.016 -0.016 
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 0.017  0.067  0.017 -0.033 -0.008 -0.033  0.017 -0.033 -0.058  0.042  0.042 -0.058 -0.033 -0.058  0.067  0.017  0.042 -0.008 -0.058 -0.058  0.067  0.042 -0.033 -0.008  0.017 -0.058 -0.008 -0.008  0.017 -0.033  0.067 -0.008 -0.033 -0.033  0.092 -0.033  0.216  0.067 -0.058  0.017  0.017  0.017  0.042  0.042 -0.058  0.042 -0.058  0.117  0.042 -0.008  0.017 -0.058  0.017 -0.008 -0.008  0.042 -0.058 -0.033  0.017 -0.008 -0.033 -0.033 -0.008 -0.033 -0.033 -0.033  0.017 -0.033  0.042  0.017 -0.008 -0.008  0.142 -0.033  0.017 -0.033 -0.058 -0.033 -0.058  0.042 -0.033 -0.008  0.017  0.017 -0.033 -0.008 -0.058  0.017 -0.008 -0.033  0.042 -0.033  0.067  0.017  0.017 -0.008 -0.033  0.117 -0.033 -0.008 
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 0.041  0.191  0.091  0.066  0.141 -0.008  0.191  0.041 -0.058 -0.008  0.091 -0.058  0.091 -0.158 -0.058 -0.083  0.041 -0.133 -0.008 -0.058  0.041  0.664 -0.158 -0.058  0.066  0.016  0.266  0.116  0.266  0.066  0.141 -0.058 -0.108 -0.158  0.066  0.041  0.390  0.041  0.016  0.141  0.066  0.116  0.066 -0.033 -0.108  0.241  0.166  0.714  0.689  0.141  0.016 -0.083 -0.008 -0.208 -0.133 -0.008 -0.158 -0.033 -0.083 -0.058 -0.108 -0.058  0.066 -0.183 -0.008  0.141 -0.133 -0.133  0.016  0.116 -0.158  0.066  0.191 -0.058  0.016  0.116 -0.058 -0.083 -0.108 -0.083 -0.183 -0.133 -0.133  0.016  0.091  0.016  0.041 -0.083 -0.058 -0.133 -0.083 -0.083 -0.058 -0.058 -0.083 -0.008 -0.158  0.141  0.216 -0.183 
 0.045  0.144  0.120  0.070  0.144  0.045  0.219  0.045 -0.030  0.095  0.070 -0.055  0.144 -0.179 -0.080 -0.055  0.020 -0.154 -0.005 -0.055  0.070  0.618 -0.055 -0.080  0.095  0.120  0.269  0.095  0.319  0.070  0.269 -0.030 -0.105 -0.179  0.045  0.045  0.369  0.070  0.070  0.169  0.095  0.219  0.045 -0.030 -0.130  0.319  0.219  0.668  0.668  0.219 -0.005 -0.105 -0.005 -0.179 -0.154 -0.030 -0.179 -0.055 -0.080 -0.055 -0.105 -0.055  0.045 -0.179 -0.030  0.120 -0.154 -0.154 -0.005  0.169 -0.179  0.070  0.169 -0.080  0.095  0.095 -0.030 -0.055 -0.130 -0.055 -0.204 -0.154 -0.179 -0.005  0.120 -0.005 -0.005 -0.105 -0.080 -0.154 -0.055 -0.080 -0.080 -0.055 -0.080 -0.030 -0.154  0.120  0.219 -0.204 
 0.062  0.137  0.112  0.037  0.137  0.062  0.262  0.062 -0.037  0.162  0.062 -0.087  0.162 -0.187 -0.087 -0.062  0.012 -0.162  0.012 -0.037  0.087  0.585 -0.062 -0.037  0.087  0.137  0.262  0.087  0.361  0.062  0.237 -0.012 -0.087 -0.187  0.037  0.062  0.386  0.087  0.112  0.187  0.112  0.212  0.037 -0.012 -0.137  0.311  0.237  0.660  0.660  0.262 -0.012 -0.087  0.012 -0.187 -0.112 -0.012 -0.212 -0.037 -0.062 -0.062 -0.087 -0.037  0.037 -0.187 -0.037  0.137 -0.162 -0.162 -0.012  0.187 -0.187  0.037  0.187 -0.087  0.112  0.087 -0.037 -0.062 -0.137 -0.012 -0.237 -0.162 -0.187 -0.012  0.112 -0.012 -0.062 -0.112 -0.112 -0.162 -0.062 -0.087 -0.087 -0.087 -0.087 -0.037 -0.162  0.112  0.212 -0.187 
 0.105  0.154  0.154  0.030  0.154  0.130  0.254  0.055 -0.045  0.229  0.030 -0.070  0.179 -0.194 -0.045 -0.045  0.055 -0.169  0.005 -0.045  0.080  0.503 -0.070 -0.045  0.105  0.229  0.279  0.105  0.404  0.080  0.229  0.005 -0.020 -0.169  0.055  0.154  0.404  0.105  0.105  0.204  0.130  0.204  0.105 -0.020 -0.144  0.304  0.254  0.628  0.653  0.279 -0.045 -0.070  0.030 -0.194 -0.120 -0.020 -0.194 -0.045 -0.070 -0.070 -0.070 -0.070  0.030 -0.169 -0.045  0.130 -0.169 -0.169 -0.045  0.179 -0.194 -0.020  0.154 -0.120  0.130  0.055 -0.045 -0.070 -0.144  0.030 -0.244 -0.144 -0.169 -0.070  0.080  0.030 -0.070 -0.120 -0.120 -0.194 -0.070 -0.120 -0.045 -0.095 -0.095 -0.045 -0.169  0.105  0.204 -0.194 
 0.127  0.152  0.202  0.052  0.202  0.127  0.252  0.102 -0.047  0.252  0.127 -0.072  0.177 -0.197 -0.047  0.002  0.052 -0.197  0.002 -0.047  0.077  0.451 -0.072 -0.047  0.152  0.227  0.277  0.077  0.401  0.077  0.227  0.027 -0.022 -0.147  0.077  0.252  0.401  0.102  0.127  0.202  0.127  0.202  0.102 -0.022 -0.122  0.326  0.301  0.600  0.650  0.326 -0.072 -0.047  0.027 -0.197 -0.122 -0.022 -0.197 -0.047 -0.097 -0.097 -0.022 -0.072  0.027 -0.172 -0.072  0.127 -0.172 -0.172 -0.047  0.177 -0.197 -0.022  0.127 -0.097  0.127  0.102 -0.047 -0.072 -0.122  0.052 -0.247 -0.172 -0.147 -0.072  0.102  0.052 -0.072 -0.097 -0.122 -0.197 -0.072 -0.147 -0.047 -0.097 -0.097 -0.047 -0.172  0.102  0.202 -0.197 
 0.122  0.147  0.272  0.072  0.197  0.122  0.247  0.147 -0.052  0.296  0.122 -0.077  0.172 -0.227 -0.027  0.022  0.047 -0.177 -0.027 -0.052  0.072  0.371 -0.052 -0.027  0.122  0.222  0.321  0.097  0.421  0.072  0.247  0.022 -0.002 -0.127  0.097  0.247  0.371  0.122  0.122  0.222  0.122  0.197  0.097 -0.027 -0.127  0.346  0.371  0.521  0.645  0.421 -0.077 -0.052 -0.002 -0.227 -0.102 -0.002 -0.202 -0.052 -0.077 -0.102 -0.052 -0.052  0.047 -0.177 -0.102  0.072 -0.202 -0.177 -0.077  0.197 -0.177 -0.002  0.097 -0.077  0.122  0.097 -0.052 -0.027 -0.152  0.047 -0.252 -0.202 -0.152 -0.052  0.097  0.097 -0.102 -0.152 -0.127 -0.202 -0.077 -0.152 -0.002 -0.077 -0.077 -0.052 -0.177  0.097  0.197 -0.202 
 0.120  0.145  0.270  0.070  0.319  0.120  0.270  0.145 -0.029  0.319  0.120 -0.054  0.170 -0.204 -0.029  0.020  0.045 -0.179 -0.054  0.020  0.095  0.319 -0.054 -0.029  0.095  0.245  0.319  0.120  0.419  0.120  0.245  0.020 -0.004 -0.104  0.095  0.245  0.369  0.120  0.120  0.270  0.145  0.220  0.095 -0.029 -0.104  0.394  0.394  0.494  0.643  0.444 -0.104 -0.029 -0.004 -0.229 -0.104 -0.029 -0.179 -0.054 -0.079 -0.129 -0.029 -0.054  0.070 -0.179 -0.129  0.045 -0.179 -0.179 -0.079  0.195 -0.179  0.020  0.070 -0.054  0.095  0.095 -0.054 -0.029 -0.154  0.045 -0.229 -0.204 -0.179 -0.079  0.095  0.120 -0.104 -0.129 -0.154 -0.179 -0.079 -0.179  0.020 -0.054 -0.079 -0.054 -0.179  0.120  0.195 -0.204 
 0.115  0.164  0.364  0.090  0.364  0.140  0.289  0.164 -0.035  0.339  0.140 -0.035  0.164 -0.184 -0.010  0.040  0.040 -0.135 -0.085  0.040  0.090  0.289 -0.035  0.015  0.115  0.239  0.339  0.115  0.414  0.164  0.239  0.015  0.015 -0.060  0.115  0.214  0.364  0.115  0.115  0.264  0.140  0.264  0.115 -0.035 -0.135  0.389  0.438  0.463  0.638  0.488 -0.110 -0.060  0.015 -0.234 -0.085 -0.060 -0.184 -0.060 -0.085 -0.135 -0.035 -0.035  0.065 -0.184 -0.159  0.015 -0.159 -0.184 -0.085  0.164 -0.184  0.040  0.015 -0.085  0.090  0.115 -0.085 -0.035 -0.159  0.164 -0.234 -0.209 -0.184 -0.085  0.065  0.115 -0.135 -0.159 -0.159 -0.159 -0.085 -0.184  0.040 -0.035 -0.060 -0.035 -0.184  0.140  0.189 -0.234 
 0.110  0.185  0.359  0.135  0.384  0.160  0.260  0.185 -0.039  0.384  0.160 -0.014  0.185 -0.189 -0.014  0.035  0.010 -0.114 -0.089  0.085  0.035  0.284 -0.039  0.035  0.110  0.260  0.334  0.110  0.409  0.210  0.235 -0.014  0.035 -0.064  0.110  0.235  0.384  0.110  0.085  0.260  0.135  0.284  0.135  0.010 -0.164  0.359  0.534  0.434  0.633  0.509 -0.114 -0.064  0.010 -0.239 -0.089 -0.064 -0.164 -0.089 -0.089 -0.139 -0.039 -0.014  0.035 -0.189 -0.164  0.010 -0.164 -0.164 -0.089  0.160 -0.214  0.035 -0.014 -0.039  0.085  0.110 -0.089 -0.039 -0.139  0.185 -0.214 -0.189 -0.164 -0.089  0.085  0.085 -0.139 -0.164 -0.164 -0.164 -0.089 -0.189  0.035 -0.039 -0.039  0.060 -0.189  0.135  0.160 -0.239 
 0.126  0.176  0.350  0.176  0.400  0.201  0.251  0.201 -0.048  0.375  0.201  0.026  0.251 -0.198  0.001  0.101  0.001 -0.123 -0.098  0.201  0.026  0.276 -0.048  0.101  0.101  0.226  0.350  0.151  0.400  0.226  0.226 -0.023  0.051 -0.098  0.126  0.251  0.400  0.101  0.076  0.251  0.126  0.375  0.151  0.126 -0.148  0.350  0.550  0.350  0.624  0.500 -0.098 -0.073  0.026 -0.248 -0.098 -0.048 -0.173 -0.098 -0.098 -0.123 -0.023 -0.023  0.001 -0.148 -0.148 -0.023 -0.173 -0.173 -0.098  0.151 -0.223  0.026 -0.073 -0.023  0.076  0.076 -0.073 -0.048 -0.148  0.176 -0.223 -0.198 -0.148 -0.098  0.076  0.101 -0.173 -0.173 -0.173 -0.173 -0.123 -0.198  0.001 -0.073 -0.048  0.076 -0.173  0.201  0.101 -0.248 
 0.116  0.166  0.365  0.116  0.340  0.191  0.241  0.116 -0.083  0.241  0.166 -0.008  0.266 -0.108  0.041  0.141  0.041 -0.083 -0.033  0.116  0.016  0.241 -0.083  0.066  0.141  0.166  0.365  0.141  0.315  0.241  0.266  0.016  0.016 -0.058  0.066  0.290  0.465  0.066  0.066  0.191  0.041  0.340  0.166  0.066 -0.133  0.340  0.540  0.390  0.664  0.365 -0.033 -0.058  0.091 -0.158 -0.083 -0.058 -0.133 -0.058 -0.058 -0.083 -0.033 -0.033 -0.033 -0.108 -0.083 -0.083 -0.133 -0.108 -0.033  0.066 -0.158  0.016 -0.058 -0.008  0.066  0.141 -0.058  0.016 -0.083  0.091 -0.233 -0.183 -0.058 -0.083  0.066  0.066 -0.108 -0.183 -0.108 -0.158 -0.108 -0.133 -0.008 -0.058  0.016 -0.008 -0.083  0.216  0.066 -0.158 
 0.085  0.185  0.235  0.060  0.284  0.185  0.160  0.160 -0.089  0.185  0.135 -0.014  0.210 -0.089  0.110  0.060  0.060 -0.064 -0.014  0.035  0.060  0.260 -0.064  0.060  0.060  0.135  0.359  0.110  0.235  0.260  0.260  0.060  0.035 -0.089  0.135  0.334  0.409  0.060  0.010  0.085  0.060  0.359  0.110  0.060 -0.114  0.334  0.484  0.334  0.683  0.359  0.010 -0.039  0.060 -0.089 -0.064 -0.089 -0.114 -0.039 -0.089 -0.039 -0.064  0.035 -0.014 -0.089 -0.039 -0.039 -0.089 -0.064  0.060  0.060 -0.089  0.060  0.010  0.010  0.110  0.085 -0.064  0.085 -0.039  0.060 -0.139 -0.089 -0.039 -0.089  0.060  0.085 -0.089 -0.114 -0.064 -0.089 -0.039 -0.064  0.010  0.010  0.085  0.010 -0.089  0.185  0.035 -0.114 
 0.080  0.204  0.179  0.080  0.304  0.179  0.154  0.179 -0.070  0.154  0.080 -0.070  0.204 -0.070  0.130  0.055  0.080 -0.020 -0.020  0.030  0.055  0.254 -0.020  0.055  0.055  0.105  0.304  0.030  0.204  0.229  0.254  0.080  0.055 -0.095  0.154  0.354  0.379  0.030  0.005  0.080  0.080  0.279  0.130  0.030 -0.095  0.329  0.453  0.354  0.678  0.354  0.030 -0.020  0.080 -0.095 -0.045 -0.070 -0.095 -0.020 -0.070 -0.045 -0.045  0.055 -0.020 -0.095 -0.020 -0.045 -0.070 -0.045  0.055  0.080 -0.070  0.080 -0.020 -0.020  0.030  0.055 -0.045  0.105 -0.045  0.030 -0.120 -0.070 -0.045 -0.070  0.030  0.055 -0.070 -0.095 -0.045 -0.070 -0.045 -0.045  0.030  0.005  0.105  0.005 -0.070  0.204  0.055 -0.095 
 0.063  0.188  0.088  0.088  0.287  0.138  0.163  0.188 -0.086  0.063  0.013 -0.061  0.138 -0.036  0.063  0.013  0.038  0.013 -0.036 -0.036  0.038  0.263 -0.011  0.013  0.038  0.113  0.263  0.038  0.188  0.163  0.213  0.088  0.063 -0.061  0.188  0.362  0.387  0.038 -0.011  0.013  0.063  0.138  0.088  0.038 -0.086  0.238  0.387  0.312  0.736  0.312  0.038 -0.036 -0.011 -0.086 -0.061 -0.061 -0.061 -0.036 -0.061 -0.036 -0.011  0.063 -0.036 -0.061 -0.011 -0.011 -0.061 -0.011  0.038  0.038 -0.036  0.063 -0.011 -0.061  0.038  0.038 -0.011  0.138 -0.036 -0.061 -0.086 -0.086 -0.011 -0.036  0.063  0.038 -0.036 -0.086 -0.036 -0.086 -0.036 -0.061  0.038 -0.011  0.088  0.038 -0.036  0.163  0.013 -0.086 
 0.051  0.175  0.051  0.101  0.200  0.101  0.150  0.200 -0.074  0.076 -0.024 -0.049  0.101 -0.024  0.076  0.026  0.051  0.001 -0.049 -0.024  0.051  0.275 -0.024  0.001  0.051  0.076  0.200  0.051  0.200  0.150  0.200  0.051  0.076 -0.049  0.200  0.350  0.350  0.051 -0.024  0.026  0.076  0.076  0.101  0.026 -0.074  0.200  0.375  0.325  0.723  0.275  0.051 -0.049 -0.024 -0.074 -0.049 -0.049 -0.049 -0.024 -0.049 -0.024  0.001  0.026 -0.024 -0.049 -0.024  0.001 -0.074  0.001  0.051  0.026 -0.024  0.051 -0.024 -0.049  0.026  0.026  0.001  0.126 -0.049 -0.049 -0.074 -0.074  0.001 -0.024  0.026  0.026 -0.024 -0.074 -0.024 -0.074 -0.049 -0.049  0.001  0.001  0.076  0.026 -0.049  0.101  0.026 -0.074 
 0.070  0.145  0.020  0.070  0.170 -0.004  0.170  0.095 -0.054  0.020 -0.054 -0.029  0.070 -0.029  0.095 -0.029  0.045 -0.004 -0.029 -0.029  0.045  0.294 -0.029  0.020 -0.004  0.045  0.170  0.045  0.195  0.095  0.170  0.045 -0.004 -0.029  0.220  0.195  0.294  0.045 -0.004  0.045  0.095  0.070  0.070 -0.004 -0.054  0.145  0.319  0.294  0.718  0.195  0.045 -0.029 -0.004 -0.054 -0.029 -0.054 -0.029 -0.029 -0.029 -0.004 -0.004  0.020 -0.004 -0.029 -0.029  0.020 -0.054  0.020  0.070 -0.004 -0.004  0.045 -0.029 -0.029  0.045  0.020 -0.029  0.120 -0.029 -0.029 -0.054 -0.054  0.020 -0.029 -0.004 -0.004 -0.004 -0.054 -0.029 -0.054 -0.029 -0.029  0.020  0.020  0.045 -0.004 -0.029  0.120  0.020 -0.054 
 0.012  0.037  0.012  0.012  0.186 -0.038  0.112  0.062 -0.038  0.012 -0.038 -0.013  0.037 -0.013  0.037 -0.038  0.062  0.012 -0.013 -0.013  0.012  0.261 -0.013  0.037  0.012  0.062  0.137  0.062  0.112  0.087  0.087  0.037  0.012 -0.013  0.186  0.137  0.087 -0.013  0.012  0.062  0.037  0.062  0.037 -0.013 -0.038  0.112  0.137  0.186  0.809  0.112  0.037 -0.013  0.012 -0.038 -0.038 -0.038 -0.013 -0.013 -0.013  0.037  0.012  0.037 -0.013 -0.038 -0.038  0.012 -0.038  0.012  0.087 -0.013 -0.013  0.037 -0.013 -0.013  0.037  0.012 -0.038  0.087 -0.038 -0.013 -0.038 -0.038  0.012  0.012 -0.038 -0.013 -0.013 -0.038 -0.038 -0.038 -0.013  0.012  0.012  0.012  0.012  0.037 -0.013  0.087  0.012 -0.038 
 0.002  0.002  0.002  0.002  0.027 -0.023  0.077  0.002 -0.023  0.027 -0.023 -0.023  0.052  0.002  0.027 -0.023  0.052  0.002  0.027  0.002  0.002  0.151  0.002  0.027  0.002  0.002  0.052  0.077  0.052  0.027  0.002  0.002  0.002  0.002  0.077  0.027  0.002  0.002  0.027  0.002  0.002  0.002  0.052  0.002 -0.023  0.027  0.052  0.077  0.924 -0.023  0.027  0.002 -0.023 -0.023 -0.023 -0.023  0.002  0.002 -0.023  0.027  0.027  0.002  0.002 -0.023 -0.023  0.027 -0.023 -0.023  0.027  0.002 -0.023 -0.023 -0.023  0.002  0.027 -0.023 -0.023  0.002 -0.023 -0.023 -0.023 -0.023 -0.023  0.002 -0.023  0.002 -0.023 -0.023 -0.023 -0.023  0.002  0.002  0.002  0.002  0.002  0.052 -0.023  0.027  0.027 -0.023 
 0.003  0.003  0.003  0.003  0.028 -0.022  0.078  0.003 -0.022  0.028 -0.022 -0.022  0.053  0.003  0.028 -0.022  0.053  0.003  0.028  0.003  0.003  0.128  0.003  0.028  0.003  0.003  0.053  0.078  0.053  0.028  0.003  0.003  0.003 -0.022  0.053  0.028 -0.022  0.003  0.028  0.003 -0.022  0.003  0.053  0.003 -0.022  0.028  0.053  0.078  0.925 -0.022  0.028  0.003 -0.022 -0.022 -0.022 -0.022  0.003  0.003 -0.022  0.028  0.028  0.003  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.028  0.003 -0.022 -0.022 -0.022  0.003  0.028 -0.022 -0.022  0.003 -0.022 -0.022 -0.022 -0.022 -0.022  0.003 -0.022  0.003 -0.022 -0.022 -0.022 -0.022  0.003  0.003  0.003  0.003 -0.022  0.028 -0.022  0.028  0.028 -0.022 
 0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004  1.001 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004 -0.020 
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 0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004  1.001 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004 -0.020 
 0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004  1.001 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004 -0.020 
 0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004  1.001 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004 -0.020 
 0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004  1.001 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004 -0.020 
 0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004  1.001 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004 -0.020 
 0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004  1.001 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004 -0.020 
 0.004  0.004 -0.021 -0.021  0.004 -0.021  0.029  0.004 -0.021  0.029 -0.021 -0.021  0.054 -0.021  0.029 -0.021  0.054  0.004  0.004  0.004 -0.021  0.079  0.004  0.029 -0.021  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.021  0.054 -0.021 -0.021  0.004  0.004  0.004 -0.021  0.004  0.054  0.004 -0.021  0.029  0.029  0.004  1.000 -0.021  0.029  0.004 -0.021 -0.021 -0.021 -0.021  0.029  0.004 -0.021  0.004  0.004  0.004  0.004 -0.021 -0.021  0.004  0.004 -0.021  0.029  0.004 -0.021 -0.021 -0.021  0.004  0.029 -0.021 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.004 -0.021  0.029 -0.021 -0.021 -0.021 -0.021 -0.021  0.004  0.004  0.004 -0.021  0.029 -0.021  0.029  0.004 -0.021 
 0.023  0.023 -0.027 -0.027  0.023 -0.027  0.023 -0.002  0.023  0.048 -0.027 -0.027  0.073 -0.027  0.023 -0.002  0.073  0.023  0.023 -0.002 -0.027  0.222 -0.002  0.023 -0.027 -0.002  0.023  0.147  0.023  0.048 -0.002 -0.002  0.048 -0.027  0.172 -0.027 -0.027 -0.002  0.048 -0.002 -0.027 -0.002  0.073 -0.002 -0.027  0.023  0.123 -0.002  0.994 -0.002  0.023 -0.002 -0.027 -0.027 -0.027 -0.027  0.023 -0.002 -0.002  0.023 -0.002 -0.002 -0.002 -0.027 -0.027  0.023 -0.002 -0.027  0.023 -0.002 -0.027 -0.027 -0.027  0.023  0.023 -0.027 -0.027 -0.027 -0.002 -0.002 -0.027 -0.002 -0.002  0.023 -0.027  0.048 -0.002 -0.027 -0.027 -0.027 -0.027 -0.002 -0.002 -0.002 -0.027  0.023 -0.027  0.048  0.023 -0.027 
 0.028  0.053 -0.022 -0.022  0.053 -0.047  0.078  0.028  0.028  0.028 -0.047 -0.022  0.053 -0.047  0.053 -0.022  0.053  0.003  0.028 -0.022 -0.047  0.526 -0.022  0.028 -0.047  0.003  0.028  0.152  0.128  0.053 -0.022  0.003  0.053 -0.047  0.377 -0.022  0.003 -0.022  0.053  0.003 -0.022  0.003  0.103 -0.022  0.053  0.003  0.277  0.028  0.975  0.028  0.053 -0.022 -0.047 -0.047 -0.047 -0.022  0.028 -0.022  0.003  0.028  0.003  0.003  0.003 -0.047  0.003  0.028  0.003 -0.047  0.053  0.028 -0.047 -0.047  0.028  0.028  0.003 -0.047 -0.022 -0.047 -0.022 -0.022 -0.022  0.028  0.003  0.003 -0.047  0.028  0.003 -0.022 -0.047 -0.022 -0.047 -0.022 -0.022 -0.022 -0.022  0.003 -0.047  0.078  0.003 -0.047 
 0.082  0.156 -0.068  0.032  0.156 -0.043  0.082  0.032  0.082  0.107 -0.043  0.007  0.107 -0.043  0.007 -0.018  0.007  0.082  0.107 -0.043 -0.043  0.804 -0.068 -0.018 -0.093  0.007  0.082  0.181  0.430  0.156 -0.018  0.007  0.156 -0.043  0.729  0.007  0.032  0.007  0.032 -0.018 -0.018  0.007  0.107 -0.043  0.032  0.007  0.605  0.107  0.929  0.082  0.082 -0.018 -0.068 -0.093 -0.093 -0.018  0.007 -0.043  0.007  0.057 -0.018 -0.043  0.057 -0.043 -0.018  0.032 -0.018 -0.018  0.107 -0.018 -0.068 -0.093  0.057  0.132 -0.043 -0.043 -0.043 -0.068 -0.018 -0.043 -0.043  0.057  0.007 -0.018 -0.043  0.032 -0.043  0.007 -0.018 -0.068 -0.068 -0.018 -0.018 -0.043  0.007 -0.018 -0.093  0.107  0.057 -0.068 
 0.162  0.187  0.062  0.187  0.187  0.012  0.087  0.087  0.137  0.187 -0.087  0.037  0.137 -0.062 -0.012 -0.012  0.062  0.162  0.087 -0.037 -0.012  0.810 -0.062 -0.012 -0.037  0.037  0.187  0.336  0.585  0.262  0.012 -0.037  0.187 -0.012  0.785  0.087  0.037 -0.037  0.012 -0.012 -0.012  0.037  0.112 -0.037  0.062  0.012  0.710  0.137  0.884  0.112  0.037 -0.037 -0.062 -0.112 -0.087  0.012  0.012 -0.037  0.012  0.062 -0.037 -0.087  0.037 -0.087 -0.037  0.012 -0.062 -0.062  0.112 -0.037 -0.112 -0.137  0.037  0.212  0.012  0.037 -0.037 -0.012  0.012 -0.012 -0.037  0.062 -0.012  0.012 -0.062  0.037 -0.062  0.012 -0.062 -0.087 -0.062 -0.062 -0.012 -0.087 -0.012 -0.037 -0.087  0.137  0.137 -0.087 
 0.319  0.220  0.145  0.319  0.469  0.170  0.120  0.170  0.220  0.344 -0.029  0.070  0.195 -0.054 -0.004  0.045  0.070  0.170  0.070 -0.054 -0.054  0.818 -0.029  0.045 -0.054  0.070  0.245  0.494  0.793  0.344  0.170 -0.054  0.220 -0.029  0.818  0.195  0.020 -0.079 -0.029 -0.004  0.020  0.070  0.145 -0.004  0.070  0.145  0.818  0.220  0.818  0.195  0.070 -0.054 -0.079 -0.079 -0.079 -0.004  0.020 -0.054  0.020  0.020 -0.079 -0.054  0.070 -0.104 -0.104 -0.029 -0.079 -0.129  0.220 -0.104 -0.079 -0.204  0.045  0.344  0.095  0.120  0.070  0.045  0.095  0.020 -0.054  0.020 -0.004 -0.029 -0.029  0.070 -0.079  0.045 -0.054 -0.154 -0.104 -0.079  0.070 -0.079 -0.004 -0.054 -0.104  0.145  0.170 -0.104 
 0.360  0.211  0.136  0.410  0.535  0.186  0.236  0.211  0.186  0.335  0.036  0.036  0.211 -0.063  0.036  0.036  0.036  0.161  0.061 -0.038 -0.088  0.784 -0.063  0.186 -0.063  0.136  0.360  0.510  0.759  0.360  0.211 -0.038  0.261 -0.063  0.784  0.310  0.086 -0.063 -0.088  0.011  0.036  0.236  0.261  0.086  0.086  0.285  0.784  0.261  0.784  0.261  0.036 -0.088 -0.088 -0.113 -0.088 -0.038  0.086 -0.063  0.011 -0.013 -0.088 -0.038  0.111 -0.113 -0.088 -0.063 -0.088 -0.113  0.186 -0.088 -0.088 -0.188  0.036  0.410  0.086  0.111  0.111  0.036  0.061  0.061 -0.088 -0.013 -0.038 -0.013  0.011  0.036 -0.113  0.036 -0.063 -0.163 -0.138 -0.088  0.086 -0.113 -0.013 -0.063 -0.113  0.161  0.136 -0.113 
 0.444  0.245  0.120  0.494  0.668  0.294  0.294  0.319  0.145  0.394  0.045  0.070  0.294 -0.029 -0.004  0.120  0.020  0.145  0.020  0.020 -0.079  0.593 -0.029  0.245 -0.054  0.170  0.544  0.544  0.668  0.319  0.294  0.020  0.270 -0.054  0.718  0.419  0.095 -0.079 -0.129  0.095  0.120  0.369  0.245  0.170  0.070  0.444  0.743  0.369  0.743  0.270  0.095 -0.054 -0.129 -0.104 -0.104 -0.079  0.095 -0.079 -0.079 -0.029 -0.104 -0.079  0.145 -0.104 -0.079 -0.029 -0.079 -0.129  0.220 -0.129 -0.079 -0.104 -0.004  0.444  0.120  0.120  0.245  0.120  0.020  0.095 -0.104 -0.079 -0.054 -0.054  0.045  0.170 -0.029 -0.029 -0.079 -0.179 -0.104 -0.054  0.170 -0.079  0.020 -0.004 -0.054  0.220  0.170 -0.104 
 0.460  0.261  0.111  0.485  0.634  0.310  0.310  0.310  0.136  0.410  0.061  0.086  0.310 -0.063 -0.013  0.236 -0.013  0.136  0.011  0.186 -0.063  0.435 -0.013  0.385 -0.038  0.186  0.535  0.535  0.609  0.310  0.310  0.036  0.335 -0.013  0.709  0.460  0.136 -0.063 -0.038  0.161  0.186  0.410  0.236  0.186  0.086  0.460  0.709  0.410  0.734  0.261  0.111 -0.063 -0.138 -0.138 -0.113 -0.063  0.086 -0.088 -0.088 -0.038 -0.088 -0.063  0.136 -0.113 -0.088 -0.038 -0.088 -0.138  0.211 -0.138 -0.088 -0.113  0.011  0.410  0.136  0.111  0.335  0.111 -0.013  0.111 -0.138 -0.038 -0.063 -0.063  0.086  0.161 -0.038 -0.038 -0.088 -0.188 -0.063 -0.038  0.161 -0.088 -0.013  0.061 -0.063  0.236  0.186 -0.063 
 0.462  0.263  0.088  0.487  0.611  0.337  0.337  0.287  0.138  0.387  0.063  0.063  0.437 -0.036  0.013  0.362 -0.036  0.138 -0.036  0.312 -0.111  0.387  0.013  0.512 -0.011  0.238  0.512  0.537  0.586  0.337  0.337  0.063  0.412 -0.011  0.636  0.487  0.163 -0.111 -0.036  0.263  0.163  0.437  0.238  0.362  0.088  0.487  0.686  0.462  0.711  0.287  0.088 -0.086 -0.161 -0.161 -0.061 -0.086  0.063 -0.061 -0.086 -0.036 -0.086 -0.036  0.138 -0.136 -0.036 -0.061 -0.111 -0.136  0.163 -0.136 -0.186 -0.086  0.013  0.362  0.188  0.113  0.362  0.138 -0.036  0.063 -0.136 -0.061 -0.061 -0.111  0.063  0.163 -0.061 -0.061 -0.061 -0.211 -0.036 -0.011  0.188 -0.136 -0.061  0.138 -0.061  0.263  0.138 -0.036 
 0.455  0.281  0.081  0.480  0.579  0.330  0.380  0.281  0.131  0.380  0.081  0.056  0.455  0.031  0.006  0.430 -0.043  0.131 -0.018  0.380 -0.118  0.355  0.006  0.505 -0.018  0.231  0.480  0.480  0.555  0.330  0.330  0.056  0.430  0.031  0.629  0.480  0.181 -0.118 -0.018  0.231  0.206  0.455  0.256  0.480  0.031  0.455  0.679  0.455  0.704  0.281  0.056 -0.093 -0.143 -0.168 -0.043 -0.093  0.081 -0.043 -0.093 -0.043 -0.093  0.006  0.131 -0.143 -0.043 -0.093 -0.143 -0.143  0.181 -0.143 -0.193 -0.093  0.006  0.355  0.156  0.131  0.355  0.156 -0.043  0.031 -0.143 -0.068 -0.068 -0.143  0.056  0.156 -0.043 -0.068 -0.068 -0.218 -0.043 -0.018  0.181 -0.118 -0.068  0.156 -0.043  0.281  0.131 -0.043 
 0.450  0.326  0.102  0.450  0.550  0.326  0.376  0.226  0.127  0.351  0.127  0.052  0.475  0.027  0.002  0.450 -0.048  0.127 -0.023  0.450 -0.147  0.276  0.027  0.575 -0.048  0.226  0.475  0.475  0.550  0.326  0.326  0.052  0.475  0.027  0.575  0.475  0.251 -0.123  0.002  0.226  0.201  0.475  0.226  0.500  0.002  0.450  0.675  0.500  0.675  0.301  0.027 -0.123 -0.147 -0.147 -0.048 -0.123  0.077 -0.048 -0.098 -0.048 -0.073  0.002  0.102 -0.098 -0.023 -0.098 -0.172 -0.172  0.176 -0.123 -0.197 -0.098 -0.023  0.301  0.127  0.127  0.401  0.151 -0.023  0.002 -0.147 -0.073 -0.073 -0.147  0.052  0.201 -0.073 -0.073 -0.048 -0.222 -0.023 -0.023  0.176 -0.123 -0.048  0.151  0.027  0.276  0.077  0.002 
 0.401  0.326  0.102  0.451  0.551  0.326  0.376  0.227  0.127  0.326  0.127  0.077  0.526  0.027  0.027  0.451 -0.047  0.102 -0.047  0.476 -0.147  0.252  0.002  0.575 -0.047  0.177  0.501  0.451  0.551  0.351  0.326  0.052  0.476  0.027  0.575  0.476  0.277 -0.147  0.002  0.227  0.202  0.476  0.227  0.526 -0.022  0.451  0.675  0.501  0.675  0.301  0.002 -0.122 -0.172 -0.147 -0.047 -0.122  0.077 -0.022 -0.097 -0.022 -0.072  0.002  0.102 -0.097 -0.022 -0.072 -0.172 -0.172  0.177 -0.097 -0.197 -0.097 -0.022  0.301  0.102  0.127  0.401  0.152 -0.022  0.002 -0.147 -0.097 -0.072 -0.147  0.052  0.202 -0.097 -0.072 -0.047 -0.222 -0.022 -0.022  0.177 -0.122 -0.047  0.177  0.052  0.277  0.077  0.002 
 0.399  0.324  0.100  0.449  0.549  0.374  0.374  0.225  0.150  0.324  0.150  0.075  0.524  0.025  0.100  0.449 -0.024  0.050 -0.074  0.549 -0.099  0.250 -0.024  0.573 -0.049  0.150  0.499  0.399  0.549  0.324  0.324  0.075  0.449  0.025  0.573  0.499  0.299 -0.149  0.000  0.250  0.125  0.474  0.200  0.524 -0.074  0.449  0.623  0.499  0.673  0.324 -0.024 -0.149 -0.224 -0.149 -0.049 -0.074  0.075 -0.024 -0.099 -0.024 -0.049  0.025  0.075 -0.099 -0.024 -0.074 -0.199 -0.149  0.125 -0.074 -0.199 -0.099 -0.024  0.299  0.050  0.100  0.374  0.150 -0.024  0.000 -0.149 -0.099 -0.074 -0.149  0.050  0.200 -0.099 -0.074 -0.074 -0.224 -0.024  0.000  0.200 -0.149  0.000  0.200  0.075  0.275  0.025  0.000 
 0.398  0.323  0.099  0.423  0.523  0.398  0.348  0.224  0.124  0.323  0.149  0.074  0.523 -0.000  0.124  0.448 -0.025  0.049 -0.075  0.548 -0.100  0.249 -0.025  0.572 -0.050  0.149  0.523  0.398  0.548  0.298  0.298  0.074  0.448  0.074  0.572  0.523  0.348 -0.150 -0.000  0.249  0.099  0.473  0.199  0.548 -0.075  0.448  0.622  0.498  0.672  0.298 -0.050 -0.150 -0.225 -0.150 -0.050 -0.050  0.074 -0.025 -0.100 -0.025 -0.050  0.049  0.074 -0.100 -0.025 -0.050 -0.200 -0.075  0.124 -0.075 -0.175 -0.100 -0.025  0.298  0.049  0.124  0.373  0.149 -0.025 -0.025 -0.150 -0.075 -0.075 -0.150  0.074  0.224 -0.100 -0.075 -0.075 -0.225 -0.025 -0.000  0.174 -0.175 -0.000  0.224  0.049  0.274 -0.050  0.024 
 0.397  0.322  0.123  0.422  0.522  0.422  0.347  0.223  0.123  0.322  0.198  0.073  0.522 -0.001  0.148  0.447 -0.026 -0.001 -0.076  0.547 -0.076  0.223 -0.001  0.621 -0.051  0.148  0.522  0.397  0.547  0.297  0.273  0.073  0.422  0.098  0.596  0.571  0.347 -0.151 -0.001  0.248  0.098  0.472  0.198  0.571 -0.076  0.447  0.646  0.522  0.646  0.322 -0.051 -0.151 -0.226 -0.201 -0.051 -0.051  0.073 -0.026 -0.151 -0.026 -0.051  0.048  0.048 -0.101 -0.051 -0.051 -0.176 -0.076  0.148 -0.051 -0.176 -0.101 -0.026  0.297  0.048  0.098  0.347  0.148 -0.026 -0.026 -0.151 -0.076 -0.076 -0.151  0.073  0.223 -0.101 -0.051 -0.076 -0.226 -0.051 -0.001  0.173 -0.176 -0.001  0.223  0.048  0.273 -0.101 -0.001 
 0.374  0.324  0.125  0.399  0.523  0.424  0.349  0.224  0.100  0.324  0.199  0.050  0.523  0.000  0.149  0.448 -0.025 -0.025 -0.100  0.548 -0.075  0.224  0.000  0.623 -0.050  0.149  0.523  0.399  0.548  0.299  0.274  0.075  0.424  0.100  0.598  0.573  0.349 -0.149  0.000  0.249  0.075  0.473  0.199  0.573 -0.075  0.448  0.648  0.498  0.598  0.324 -0.050 -0.149 -0.199 -0.199 -0.050 -0.050  0.050 -0.025 -0.149 -0.025 -0.050  0.050  0.025 -0.100 -0.050 -0.050 -0.174 -0.075  0.149 -0.050 -0.174 -0.100 -0.025  0.249  0.050  0.100  0.349  0.149 -0.025  0.000 -0.149 -0.075 -0.075 -0.149  0.075  0.224 -0.149 -0.050 -0.075 -0.224 -0.050  0.025  0.174 -0.174  0.000  0.224  0.050  0.299 -0.100 -0.025 
 0.350  0.325  0.126  0.325  0.524  0.425  0.350  0.225  0.101  0.325  0.200  0.051  0.524 -0.024  0.150  0.449 -0.024 -0.024 -0.099  0.549 -0.074  0.225  0.051  0.624 -0.049  0.126  0.524  0.375  0.549  0.275  0.300  0.101  0.400  0.150  0.599  0.574  0.350 -0.148  0.026  0.250  0.076  0.474  0.175  0.574 -0.099  0.449  0.649  0.524  0.549  0.325 -0.024 -0.148 -0.198 -0.223 -0.049 -0.049  0.051 -0.024 -0.148 -0.024 -0.074  0.051 -0.024 -0.124 -0.049 -0.049 -0.173 -0.074  0.150 -0.049 -0.173 -0.074 -0.024  0.250  0.051  0.101  0.350  0.175 -0.049  0.001 -0.173 -0.074 -0.074 -0.148  0.051  0.225 -0.148 -0.049 -0.099 -0.223 -0.049  0.026  0.175 -0.173  0.001  0.225  0.051  0.300 -0.099 -0.024 
 0.347  0.347  0.123  0.322  0.522  0.422  0.347  0.223  0.098  0.322  0.223  0.048  0.522 -0.026  0.148  0.447 -0.026 -0.026 -0.126  0.547 -0.076  0.223  0.048  0.621 -0.051  0.123  0.522  0.347  0.547  0.273  0.297  0.073  0.397  0.173  0.596  0.571  0.347 -0.151 -0.001  0.248  0.073  0.472  0.173  0.571 -0.126  0.447  0.646  0.547  0.547  0.297 -0.001 -0.151 -0.201 -0.226 -0.051 -0.051  0.048 -0.026 -0.151 -0.026 -0.076  0.048 -0.026 -0.126 -0.051 -0.051 -0.176 -0.076  0.148 -0.051 -0.176 -0.101 -0.026  0.248  0.048  0.098  0.347  0.173 -0.051  0.023 -0.176 -0.076 -0.076 -0.151  0.048  0.248 -0.151 -0.051 -0.076 -0.226 -0.051  0.023  0.173 -0.176 -0.001  0.223  0.048  0.297 -0.101 -0.026 
 0.347  0.347  0.123  0.322  0.522  0.422  0.347  0.223  0.098  0.322  0.248  0.023  0.522 -0.026  0.148  0.447 -0.001 -0.026 -0.126  0.547 -0.076  0.223  0.048  0.621 -0.051  0.123  0.522  0.347  0.547  0.273  0.297  0.073  0.397  0.198  0.596  0.571  0.347 -0.151 -0.001  0.248  0.073  0.472  0.173  0.571 -0.126  0.447  0.646  0.547  0.571  0.297 -0.001 -0.151 -0.201 -0.226 -0.051 -0.051  0.048 -0.026 -0.151 -0.026 -0.076  0.048 -0.026 -0.126 -0.051 -0.051 -0.176 -0.076  0.148 -0.051 -0.176 -0.101 -0.026  0.223  0.048  0.098  0.347  0.173 -0.051  0.048 -0.176 -0.076 -0.076 -0.151  0.048  0.248 -0.151 -0.051 -0.076 -0.226 -0.051  0.023  0.173 -0.176 -0.001  0.223  0.048  0.297 -0.101 -0.026 
 0.376  0.351  0.077  0.277  0.476  0.426  0.376  0.252  0.152  0.301  0.102  0.027  0.526  0.002  0.077  0.401 -0.072  0.002 -0.072  0.526 -0.097  0.277  0.002  0.600 -0.022  0.202  0.476  0.426  0.551  0.177  0.152  0.102  0.351  0.177  0.551  0.501  0.326 -0.122  0.002  0.277  0.077  0.326  0.127  0.551 -0.122  0.476  0.551  0.476  0.476  0.277  0.077 -0.072 -0.147 -0.197 -0.097 -0.022  0.127 -0.047 -0.147 -0.047 -0.097  0.077  0.002 -0.122 -0.047 -0.047 -0.147 -0.072  0.102 -0.022 -0.197 -0.072 -0.097  0.227  0.027  0.102  0.277  0.152 -0.072 -0.022 -0.097 -0.097 -0.047 -0.097  0.052  0.227 -0.097 -0.022 -0.122 -0.172 -0.047 -0.047  0.202 -0.147  0.027  0.152  0.027  0.152 -0.022 -0.072 
 0.280  0.305  0.106  0.155  0.380  0.380  0.305  0.255  0.180  0.280  0.131  0.106  0.479  0.006  0.031  0.305 -0.044  0.056 -0.069  0.504 -0.069  0.280 -0.019  0.579  0.031  0.155  0.405  0.380  0.529  0.180  0.180  0.106  0.230  0.131  0.504  0.454  0.355 -0.119  0.006  0.230  0.081  0.355  0.131  0.429 -0.069  0.429  0.554  0.280  0.454  0.255  0.106 -0.044 -0.094 -0.168 -0.044  0.006  0.056 -0.094 -0.094 -0.019 -0.069  0.106  0.031 -0.069 -0.044  0.031 -0.094 -0.069  0.031 -0.069 -0.143 -0.019 -0.069  0.106  0.106  0.106  0.230  0.131 -0.019  0.006 -0.119 -0.069  0.006 -0.044  0.106  0.155 -0.094 -0.069 -0.094 -0.143  0.006 -0.044  0.131 -0.094  0.056  0.106  0.031  0.056 -0.019 -0.119 
 0.269  0.319  0.120  0.169  0.344  0.369  0.269  0.269  0.194  0.269  0.095  0.070  0.468 -0.030  0.020  0.194 -0.030  0.070 -0.055  0.493 -0.055  0.294 -0.005  0.543  0.045  0.169  0.394  0.394  0.468  0.169  0.169  0.095  0.244  0.045  0.468  0.468  0.319 -0.105 -0.005  0.194  0.045  0.319  0.144  0.394 -0.080  0.419  0.568  0.244  0.468  0.169  0.120 -0.055 -0.080 -0.154 -0.030 -0.005 -0.005 -0.130 -0.080 -0.005 -0.055  0.120  0.020 -0.055 -0.030  0.020 -0.105 -0.055  0.020 -0.055 -0.130 -0.030 -0.055  0.120  0.120  0.120  0.219  0.144 -0.005  0.020 -0.105 -0.055  0.020 -0.030  0.095  0.144 -0.080 -0.105 -0.105 -0.130 -0.005 -0.030  0.095 -0.080  0.045  0.095 -0.005  0.020 -0.005 -0.105 
 0.217  0.291  0.067  0.167  0.316  0.341  0.242  0.242  0.167  0.291  0.042  0.092  0.466 -0.032  0.017  0.117 -0.007  0.067 -0.032  0.541 -0.032  0.316  0.017  0.441  0.067  0.167  0.416  0.416  0.466  0.167  0.142  0.092  0.167 -0.057  0.416  0.466  0.316 -0.082 -0.032  0.167  0.017  0.341  0.167  0.267 -0.057  0.441  0.541  0.267  0.416  0.192  0.117 -0.032 -0.032 -0.082 -0.007 -0.032 -0.057 -0.107 -0.057  0.017 -0.032  0.117  0.017 -0.007 -0.007  0.017 -0.082 -0.057  0.067 -0.132 -0.107 -0.007 -0.057  0.092  0.117  0.117  0.192  0.117  0.017  0.042 -0.107 -0.107  0.017 -0.032  0.067  0.167 -0.082 -0.107 -0.107 -0.132 -0.032 -0.032  0.067 -0.082  0.067  0.117 -0.007  0.042 -0.032 -0.107 
 0.177  0.277  0.053  0.128  0.302  0.352  0.227  0.252  0.128  0.302  0.028  0.103  0.426 -0.022  0.028  0.053  0.003  0.028 -0.022  0.576 -0.022  0.327  0.028  0.377  0.078  0.177  0.402  0.426  0.352  0.177  0.152  0.078  0.152 -0.047  0.352  0.476  0.327 -0.097 -0.022  0.128  0.028  0.327  0.177  0.277 -0.047  0.451  0.551  0.252  0.426  0.202  0.078 -0.022 -0.022 -0.072  0.003 -0.022 -0.072 -0.097 -0.047  0.028 -0.047  0.103  0.028  0.003 -0.022  0.003 -0.122 -0.047  0.078 -0.122 -0.122  0.003 -0.072  0.078  0.128  0.128  0.202  0.128  0.028  0.053 -0.097 -0.097  0.028 -0.022  0.053  0.103 -0.072 -0.097 -0.097 -0.122 -0.022 -0.022  0.053 -0.072  0.053  0.103  0.003  0.053 -0.022 -0.122 
 0.194  0.194  0.069  0.119  0.293  0.343  0.219  0.219  0.069  0.318  0.044  0.094  0.293 -0.030  0.019  0.044 -0.005 -0.005 -0.055  0.592 -0.005  0.269  0.019  0.244  0.094  0.194  0.368  0.418  0.269  0.194  0.169  0.069  0.119 -0.080  0.293  0.493  0.244 -0.080 -0.055  0.069  0.019  0.293  0.169  0.244 -0.030  0.443  0.543  0.194  0.443  0.194  0.019 -0.030 -0.005 -0.080 -0.005 -0.030 -0.080 -0.080 -0.055 -0.030 -0.055  0.094  0.044  0.019 -0.030  0.019 -0.105 -0.030  0.044 -0.105 -0.105 -0.030 -0.080  0.094  0.069  0.119  0.219  0.094  0.044  0.044 -0.080 -0.105  0.044 -0.005  0.019  0.119 -0.055 -0.080 -0.080 -0.105 -0.005 -0.055 -0.030 -0.055  0.069  0.094 -0.005  0.044 -0.005 -0.105 
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 0.366 -0.057  0.042  0.416  0.242  0.092  0.341 -0.007 -0.032  0.017  0.142  0.092 -0.007 -0.107 -0.057  0.217  0.117 -0.007  0.067 -0.082 -0.082  0.267 -0.207 -0.132  0.242  0.017  0.017  0.142  0.441  0.790  0.167  0.067  0.017  0.117  0.117  0.142  0.167 -0.107  0.092  0.067  0.092  0.067  0.117 -0.107 -0.182  0.242  0.341  0.790  0.416  0.366  0.017  0.167  0.092 -0.182  0.067  0.067  0.142  0.067 -0.107 -0.082  0.790 -0.032 -0.057  0.167  0.017  0.092  0.017 -0.032  0.167 -0.057 -0.207  0.042  0.142 -0.007  0.242  0.042  0.242  0.017  0.466  0.017 -0.207 -0.107  0.167 -0.082  0.690  0.416 -0.032  0.092  0.067 -0.207 -0.082 -0.057  0.267 -0.107  0.067  0.192  0.242  0.092  0.017 -0.182 
 0.371 -0.028  0.097  0.445  0.246  0.146  0.346 -0.053 -0.003  0.047  0.122  0.221 -0.003 -0.128 -0.053  0.196  0.146 -0.053  0.072 -0.103 -0.053  0.246 -0.202 -0.128  0.246 -0.028  0.047  0.171  0.470  0.744  0.221  0.072  0.072  0.146  0.171  0.171  0.146 -0.078  0.047  0.097  0.047  0.047  0.171 -0.103 -0.202  0.221  0.321  0.769  0.520  0.346  0.047  0.146  0.122 -0.202  0.047  0.072  0.146  0.047 -0.103 -0.078  0.769 -0.053 -0.003  0.146  0.022  0.122 -0.028 -0.028  0.221 -0.078 -0.227  0.047  0.171  0.022  0.271  0.047  0.246  0.097  0.445  0.022 -0.227 -0.103  0.171 -0.103  0.695  0.421 -0.053  0.171  0.097 -0.227 -0.078 -0.078  0.321 -0.078  0.047  0.221  0.221  0.072  0.047 -0.128 
 0.339  0.115  0.115  0.489  0.414  0.190  0.339 -0.059 -0.034  0.065  0.140  0.314  0.090 -0.159 -0.009  0.140  0.140 -0.084  0.090 -0.084 -0.009  0.240 -0.184 -0.109  0.289  0.040  0.090  0.140  0.489  0.713  0.240  0.090  0.090  0.115  0.265  0.240  0.115 -0.109  0.040  0.190  0.015  0.115  0.240 -0.034 -0.259  0.265  0.464  0.738  0.539  0.364  0.015  0.115  0.165 -0.209  0.065  0.015  0.165  0.065 -0.134 -0.009  0.713  0.065  0.015  0.090 -0.009  0.215 -0.059 -0.034  0.240 -0.084 -0.259  0.015  0.190  0.115  0.364  0.065  0.215  0.090  0.414 -0.034 -0.259 -0.109  0.190 -0.084  0.638  0.489 -0.059  0.240  0.040 -0.209 -0.084 -0.109  0.314 -0.059  0.065  0.439  0.190  0.015  0.115 -0.159 
 0.328  0.179  0.104  0.478  0.453  0.229  0.328  0.004 -0.045  0.079  0.104  0.353  0.154 -0.170  0.029  0.154  0.154 -0.070  0.079 -0.045  0.029  0.204 -0.145 -0.120  0.303  0.054  0.179  0.129  0.453  0.652  0.254  0.104  0.079  0.104  0.403  0.254  0.104 -0.120  0.054  0.229  0.079  0.104  0.229  0.004 -0.220  0.303  0.478  0.727  0.528  0.353  0.004  0.104  0.254 -0.220  0.104 -0.020  0.154  0.054 -0.170 -0.020  0.702  0.079  0.054  0.079  0.029  0.229 -0.045 -0.045  0.303 -0.070 -0.270  0.029  0.154  0.179  0.378  0.079  0.254  0.104  0.353 -0.045 -0.270 -0.120  0.154 -0.095  0.602  0.503 -0.070  0.254  0.104 -0.220 -0.070 -0.070  0.328 -0.045  0.079  0.453  0.279  0.004  0.104 -0.170 
 0.315  0.266  0.041  0.490  0.440  0.266  0.290  0.016 -0.008  0.116  0.141  0.440  0.191 -0.183  0.016  0.166  0.216 -0.083  0.041  0.066  0.041  0.191 -0.133 -0.058  0.266  0.166  0.241  0.191  0.440  0.614  0.266  0.216  0.041  0.116  0.415  0.315  0.141 -0.108  0.066  0.365  0.016  0.166  0.216  0.141 -0.183  0.315  0.490  0.689  0.515  0.340  0.091  0.141  0.315 -0.258  0.216 -0.008  0.141  0.041 -0.158 -0.033  0.639  0.091  0.066  0.066  0.041  0.241 -0.058 -0.033  0.365 -0.058 -0.307  0.041  0.091  0.216  0.415  0.091  0.266  0.116  0.315 -0.008 -0.208 -0.133  0.116 -0.108  0.490  0.465 -0.083  0.266  0.066 -0.233 -0.083 -0.058  0.365 -0.058  0.041  0.490  0.290 -0.008  0.091 -0.158 
 0.311  0.311  0.037  0.460  0.460  0.261  0.286  0.037 -0.013  0.112  0.186  0.460  0.286 -0.187  0.062  0.161  0.236 -0.088  0.012  0.137  0.037  0.186 -0.113  0.012  0.261  0.161  0.236  0.186  0.435  0.585  0.261  0.236  0.037  0.137  0.411  0.361  0.112 -0.162  0.062  0.411  0.037  0.211  0.211  0.161 -0.162  0.336  0.485  0.660  0.510  0.361  0.112  0.137  0.286 -0.262  0.261 -0.063  0.137  0.037 -0.162 -0.013  0.635  0.087  0.037  0.037  0.037  0.236 -0.063 -0.063  0.386 -0.063 -0.312  0.062  0.087  0.261  0.411  0.087  0.261  0.112  0.261  0.062 -0.212 -0.138  0.112 -0.113  0.361  0.435 -0.038  0.261  0.062 -0.237 -0.113 -0.088  0.361 -0.063  0.037  0.485  0.336 -0.013  0.087 -0.162 
 0.352  0.327  0.028  0.452  0.477  0.302  0.278  0.078  0.003  0.078  0.203  0.452  0.302 -0.121  0.078  0.203  0.253 -0.146 -0.021  0.302  0.053  0.153 -0.121  0.128  0.228  0.253  0.302  0.178  0.452  0.552  0.253  0.327  0.003  0.128  0.452  0.427  0.203 -0.171  0.053  0.402  0.028  0.278  0.203  0.327 -0.196  0.377  0.477  0.626  0.527  0.377  0.153  0.128  0.253 -0.246  0.302 -0.071  0.153  0.003 -0.196 -0.021  0.601  0.053  0.078  0.003  0.028  0.253 -0.046 -0.096  0.377 -0.071 -0.295  0.103  0.078  0.278  0.352  0.078  0.203  0.103  0.153  0.053 -0.196 -0.121  0.103 -0.096  0.278  0.377  0.003  0.302  0.053 -0.246 -0.121 -0.146  0.377 -0.096  0.003  0.452  0.352 -0.021  0.053 -0.171 
 0.351  0.326  0.027  0.450  0.450  0.301  0.251  0.102  0.002  0.102  0.201  0.450  0.301 -0.098  0.052  0.201  0.276 -0.147 -0.023  0.326  0.077  0.176 -0.123  0.151  0.201  0.276  0.301  0.226  0.450  0.525  0.226  0.326  0.002  0.102  0.450  0.426  0.201 -0.147  0.027  0.401  0.002  0.301  0.226  0.401 -0.197  0.426  0.475  0.600  0.525  0.401  0.151  0.127  0.251 -0.247  0.301 -0.073  0.151  0.002 -0.197 -0.023  0.600  0.052  0.077  0.027  0.052  0.276 -0.048 -0.098  0.376 -0.048 -0.297  0.102  0.077  0.276  0.376  0.052  0.201  0.102  0.151  0.077 -0.197 -0.147  0.077 -0.098  0.251  0.351  0.002  0.301  0.052 -0.247 -0.123 -0.147  0.376 -0.098  0.002  0.450  0.351 -0.023  0.027 -0.197 
 0.368  0.293  0.044  0.418  0.442  0.318  0.268  0.069 -0.006  0.069  0.318  0.467  0.293 -0.106  0.044  0.168  0.268 -0.155 -0.031  0.418  0.069  0.168 -0.131  0.243  0.168  0.268  0.343  0.268  0.467  0.492  0.243  0.368 -0.006  0.069  0.442  0.418  0.318 -0.180  0.019  0.393  0.019  0.343  0.243  0.542 -0.180  0.418  0.442  0.542  0.542  0.467  0.143  0.069  0.218 -0.255  0.318 -0.056  0.143 -0.006 -0.205 -0.031  0.542  0.119  0.069  0.044  0.044  0.318 -0.031 -0.081  0.343 -0.006 -0.280  0.119  0.044  0.293  0.393  0.044  0.243  0.094  0.143  0.019 -0.180 -0.180  0.069 -0.106  0.193  0.368 -0.006  0.268  0.119 -0.255 -0.106 -0.155  0.393 -0.106  0.019  0.442  0.368 -0.006 -0.006 -0.205 
 0.415  0.290  0.041  0.365  0.464  0.315  0.265  0.066 -0.009  0.066  0.365  0.464  0.290 -0.134  0.066  0.165  0.265 -0.183 -0.034  0.415  0.066  0.165 -0.134  0.265  0.165  0.265  0.340  0.265  0.464  0.489  0.265  0.390 -0.034  0.066  0.439  0.415  0.315 -0.183  0.016  0.390  0.016  0.340  0.240  0.539 -0.158  0.415  0.439  0.539  0.539  0.464  0.141  0.066  0.190 -0.258  0.315 -0.059  0.141 -0.009 -0.208 -0.034  0.539  0.116  0.066  0.016  0.016  0.315 -0.034 -0.084  0.340 -0.009 -0.283  0.116  0.041  0.315  0.415  0.041  0.315  0.091  0.141  0.016 -0.183 -0.183  0.066 -0.109  0.165  0.365  0.016  0.265  0.116 -0.233 -0.109 -0.158  0.390 -0.109  0.041  0.415  0.390 -0.009 -0.009 -0.208 
 0.416  0.291  0.042  0.366  0.490  0.366  0.266  0.092  0.042  0.067  0.465  0.440  0.316 -0.133  0.092  0.166  0.266 -0.207 -0.033  0.440  0.092  0.142 -0.083  0.341  0.117  0.241  0.341  0.291  0.465  0.440  0.266  0.366 -0.058  0.017  0.440  0.416  0.316 -0.182 -0.008  0.416 -0.033  0.316  0.241  0.565 -0.182  0.440  0.391  0.540  0.515  0.416  0.142  0.042  0.191 -0.282  0.366 -0.058  0.142  0.017 -0.207 -0.033  0.515  0.142  0.067  0.017 -0.008  0.341 -0.058 -0.083  0.341 -0.058 -0.282  0.067  0.042  0.316  0.391  0.042  0.341  0.017  0.142 -0.033 -0.207 -0.207  0.067 -0.108  0.117  0.366  0.017  0.266  0.092 -0.232 -0.108 -0.157  0.391 -0.083  0.067  0.416  0.391 -0.033  0.017 -0.207 
 0.415  0.290  0.041  0.365  0.490  0.365  0.266  0.116  0.116  0.066  0.490  0.415  0.340 -0.133  0.116  0.166  0.266 -0.208 -0.033  0.440  0.091  0.141 -0.058  0.365  0.116  0.241  0.365  0.290  0.465  0.440  0.266  0.365 -0.033  0.016  0.440  0.415  0.290 -0.208 -0.008  0.415 -0.033  0.315  0.216  0.565 -0.183  0.440  0.390  0.540  0.540  0.415  0.141  0.041  0.166 -0.283  0.365 -0.058  0.141  0.016 -0.208 -0.033  0.515  0.141  0.066  0.016 -0.033  0.340 -0.033 -0.108  0.340 -0.058 -0.283  0.041  0.041  0.315  0.365  0.066  0.340 -0.008  0.141 -0.033 -0.208 -0.183  0.066 -0.108  0.116  0.390  0.016  0.266  0.091 -0.233 -0.108 -0.158  0.340 -0.083  0.066  0.415  0.390 -0.033  0.041 -0.183 
 0.416  0.316 -0.033  0.341  0.515  0.341  0.266  0.117  0.191  0.092  0.515  0.391  0.416 -0.133  0.117  0.166  0.266 -0.207 -0.033  0.515  0.092  0.142 -0.058  0.391  0.092  0.241  0.366  0.291  0.515  0.440  0.266  0.366 -0.058  0.017  0.465  0.416  0.316 -0.207  0.017  0.440 -0.008  0.291  0.191  0.565 -0.133  0.440  0.366  0.540  0.540  0.416  0.142  0.067  0.166 -0.282  0.366 -0.058  0.166  0.042 -0.207 -0.033  0.465  0.142  0.067  0.017 -0.058  0.341 -0.033 -0.108  0.341 -0.058 -0.282  0.042  0.042  0.316  0.366  0.117  0.341 -0.008  0.142 -0.033 -0.207 -0.182  0.042 -0.133  0.092  0.391  0.017  0.266  0.067 -0.232 -0.083 -0.157  0.341 -0.108  0.042  0.391  0.391 -0.083  0.092 -0.182 
 0.393  0.318 -0.106  0.343  0.517  0.343  0.268  0.119  0.193  0.069  0.542  0.343  0.418 -0.131  0.168  0.168  0.268 -0.230  0.019  0.517  0.094  0.143 -0.056  0.393  0.094  0.243  0.368  0.293  0.517  0.442  0.268  0.368 -0.081  0.019  0.442  0.418  0.318 -0.205  0.019  0.442 -0.006  0.293  0.168  0.592 -0.131  0.467  0.368  0.542  0.542  0.442  0.143  0.094  0.168 -0.280  0.368 -0.056  0.168  0.044 -0.205 -0.031  0.467  0.143  0.069  0.019 -0.056  0.368 -0.031 -0.106  0.343 -0.031 -0.280  0.044  0.044  0.318  0.343  0.119  0.343 -0.006  0.119 -0.031 -0.180 -0.180 -0.006 -0.131  0.069  0.393  0.019  0.268  0.044 -0.230 -0.081 -0.155  0.368 -0.106  0.069  0.393  0.393 -0.081  0.094 -0.180 
 0.393  0.343 -0.105  0.343  0.518  0.343  0.269  0.094  0.194  0.044  0.543  0.318  0.418 -0.130  0.194  0.194  0.269 -0.255  0.019  0.518  0.094  0.144 -0.055  0.418  0.094  0.244  0.418  0.293  0.493  0.393  0.269  0.368 -0.130  0.019  0.443  0.418  0.343 -0.205  0.019  0.443 -0.005  0.293  0.119  0.592 -0.155  0.493  0.368  0.543  0.543  0.443  0.169  0.119  0.144 -0.280  0.368 -0.055  0.169  0.044 -0.205 -0.030  0.418  0.144  0.069 -0.005 -0.080  0.368 -0.030 -0.080  0.343 -0.030 -0.280  0.044 -0.005  0.318  0.343  0.119  0.368 -0.005  0.119 -0.030 -0.180 -0.180 -0.005 -0.130  0.044  0.368  0.044  0.293  0.044 -0.205 -0.080 -0.155  0.393 -0.105  0.069  0.343  0.393 -0.080  0.094 -0.205 
 0.444  0.270 -0.054  0.345  0.444  0.370  0.295  0.096  0.096  0.071  0.469  0.295  0.345 -0.054  0.145  0.245  0.270 -0.178 -0.029  0.494  0.121  0.220 -0.054  0.295  0.096  0.270  0.370  0.295  0.494  0.270  0.220  0.395 -0.079 -0.004  0.370  0.370  0.345 -0.153  0.071  0.420  0.046  0.320  0.145  0.544 -0.129  0.420  0.245  0.519  0.519  0.469  0.195  0.071  0.145 -0.228  0.320 -0.004  0.170 -0.029 -0.178 -0.004  0.370  0.096  0.021 -0.004 -0.054  0.121 -0.054 -0.029  0.370 -0.054 -0.203 -0.004 -0.029  0.170  0.270  0.145  0.320  0.071  0.046 -0.029 -0.153 -0.203 -0.029 -0.079  0.021  0.295  0.071  0.270  0.071 -0.203 -0.054 -0.129  0.345 -0.104  0.071  0.370  0.295 -0.004 -0.004 -0.178 
 0.453  0.229 -0.020  0.353  0.328  0.428  0.328  0.054  0.079  0.079  0.328  0.303  0.279 -0.020  0.129  0.154  0.129 -0.120 -0.045  0.478  0.004  0.254 -0.070  0.254  0.029  0.254  0.353  0.279  0.428  0.279  0.229  0.229 -0.045 -0.020  0.279  0.303  0.353 -0.145  0.004  0.378  0.004  0.303  0.029  0.453 -0.120  0.378  0.229  0.528  0.428  0.378  0.154  0.079  0.029 -0.170  0.279  0.004  0.179  0.029 -0.095  0.054  0.154  0.104  0.054 -0.020 -0.020  0.054 -0.070  0.004  0.279 -0.020 -0.145  0.004 -0.045  0.129  0.179  0.179  0.303  0.129  0.054 -0.020 -0.095 -0.170  0.004 -0.045  0.054  0.204  0.054  0.154  0.029 -0.145  0.029 -0.070  0.353 -0.095  0.054  0.328  0.179  0.004 -0.020 -0.145 
 0.419  0.194 -0.005  0.344  0.319  0.419  0.344  0.045  0.045  0.045  0.294  0.269  0.319 -0.005  0.120  0.194  0.120 -0.105 -0.055  0.443 -0.005  0.244 -0.055  0.269  0.020  0.219  0.419  0.319  0.369  0.269  0.269  0.194 -0.080 -0.005  0.219  0.319  0.419 -0.130 -0.005  0.369  0.020  0.319  0.020  0.443 -0.130  0.369  0.194  0.493  0.419  0.344  0.120  0.070  0.020 -0.154  0.219  0.020  0.144  0.045 -0.080  0.070  0.045  0.120  0.045 -0.030  0.020  0.070 -0.055  0.020  0.294 -0.005 -0.130  0.020 -0.080  0.120  0.144  0.169  0.269  0.144 -0.005  0.020 -0.105 -0.154 -0.005 -0.055  0.120  0.194 -0.005  0.095 -0.005 -0.130 -0.005 -0.055  0.344 -0.080  0.070  0.219  0.120  0.020 -0.055 -0.154 
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 0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.104  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.054 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.004  0.029 -0.020 -0.020 -0.020 
 0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.104  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.029  0.029  0.054 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.004  0.029 -0.020 -0.020 -0.020 
 0.001 -0.023 -0.023 -0.023  0.001  0.026  0.001  0.026 -0.023 -0.023  0.001  0.001  0.001  0.001  0.026  0.001 -0.023  0.026 -0.023 -0.023 -0.023 -0.023 -0.023  0.001 -0.023  0.026  0.001 -0.023  0.076  0.001 -0.023  0.001  0.001  0.251  0.001  0.001  0.001  0.001 -0.023  0.001  0.001  0.001  0.051  0.026 -0.023  0.001 -0.023  0.001 -0.023  0.001 -0.023  0.051  0.026 -0.023 -0.023  0.001  0.001  0.001 -0.023  0.001  0.001 -0.023  0.001 -0.023  0.026  0.026  0.051 -0.023 -0.023  0.026 -0.023  0.001  0.001  0.001  0.001 -0.023  0.001  0.001 -0.023 -0.023  0.001  0.001  0.001  0.001 -0.023 -0.023  0.051  0.001  0.001  0.001  0.026 -0.023  0.001  0.026  0.051  0.001  0.026 -0.023 -0.023 -0.023 
 0.016  0.016 -0.033 -0.033 -0.008  0.016 -0.008  0.066 -0.008 -0.033  0.016 -0.008 -0.008  0.016  0.016 -0.008 -0.008  0.041 -0.008 -0.033 -0.033 -0.033 -0.033 -0.008 -0.033  0.016 -0.008 -0.033  0.091 -0.008 -0.033  0.016  0.016  0.714 -0.008 -0.008  0.016  0.016 -0.033 -0.008  0.066 -0.008  0.066  0.016 -0.033  0.016 -0.033 -0.008 -0.033 -0.008 -0.033  0.041  0.041 -0.033  0.016  0.016 -0.008 -0.008 -0.033 -0.008 -0.008 -0.033 -0.008 -0.033  0.016  0.041  0.041 -0.008 -0.033  0.016 -0.033 -0.008 -0.008  0.016 -0.008 -0.033 -0.008 -0.008 -0.033  0.016 -0.008  0.016 -0.008 -0.008 -0.033 -0.033  0.041 -0.008  0.016 -0.008  0.016 -0.033  0.016  0.016  0.091  0.016  0.016 -0.033 -0.033 -0.033 
 0.011  0.036 -0.038 -0.038 -0.013  0.036 -0.013  0.086 -0.013 -0.038  0.036 -0.013 -0.013  0.036  0.011 -0.013  0.011  0.036 -0.013 -0.038 -0.038 -0.038 -0.038  0.011 -0.013  0.036 -0.013 -0.038  0.086 -0.013 -0.038  0.011  0.011  0.858 -0.013 -0.013  0.036  0.011 -0.013 -0.013  0.061 -0.013  0.111  0.036 -0.038  0.061 -0.038 -0.013 -0.038 -0.013 -0.038  0.061  0.036 -0.038  0.011  0.011 -0.013 -0.013 -0.038 -0.013 -0.013 -0.013 -0.013 -0.038  0.036  0.036  0.061  0.011 -0.038  0.011 -0.038 -0.013 -0.013  0.011 -0.013  0.011 -0.013 -0.013 -0.038  0.036 -0.013  0.011  0.011 -0.013 -0.013 -0.038  0.061 -0.013  0.011 -0.013  0.036 -0.013  0.061  0.011  0.086  0.036  0.011 -0.038 -0.038 -0.038 
 0.054  0.029 -0.021 -0.021  0.004  0.029 -0.021  0.104  0.029 -0.046  0.029 -0.021 -0.021  0.029  0.004  0.004  0.004  0.029  0.004 -0.046 -0.046 -0.046 -0.021  0.004 -0.021  0.054 -0.021 -0.046  0.153  0.004 -0.021  0.004  0.004  0.976 -0.021 -0.021  0.029  0.004 -0.021 -0.021  0.054 -0.021  0.153  0.029 -0.021  0.104 -0.046 -0.021 -0.046 -0.021 -0.046  0.079  0.004 -0.046 -0.021  0.054 -0.021 -0.021 -0.046 -0.021 -0.021  0.004 -0.021 -0.046  0.029  0.029  0.054  0.029 -0.021  0.004 -0.046 -0.021 -0.021  0.004 -0.021  0.029  0.004 -0.021 -0.046  0.029  0.029  0.004  0.054 -0.021  0.004 -0.046  0.079 -0.021  0.004 -0.021  0.029 -0.021  0.079  0.004  0.054  0.029  0.029 -0.046 -0.046 -0.046 
 0.049  0.024 -0.026 -0.026 -0.001  0.024 -0.026  0.099  0.024 -0.051  0.024 -0.026 -0.026  0.024 -0.001 -0.001  0.024  0.049  0.024 -0.026 -0.026 -0.051 -0.026 -0.001 -0.026  0.049 -0.026 -0.051  0.173 -0.001 -0.026 -0.001 -0.001  0.971 -0.026 -0.026  0.049 -0.001 -0.026 -0.026  0.049 -0.026  0.223  0.049 -0.026  0.148 -0.051 -0.026 -0.051 -0.026 -0.051  0.074 -0.001 -0.051 -0.026  0.074 -0.026 -0.026 -0.051 -0.026 -0.026  0.049 -0.026 -0.051  0.049  0.024  0.049  0.049 -0.026 -0.001 -0.051 -0.026 -0.026 -0.001 -0.001  0.024 -0.001 -0.026 -0.051  0.024  0.049 -0.001  0.074 -0.001 -0.001 -0.051  0.074 -0.026 -0.001 -0.026  0.074 -0.001  0.074  0.024  0.074  0.049  0.024 -0.051 -0.051 -0.001 
 0.120  0.070 -0.004 -0.029  0.020  0.020 -0.029  0.145  0.020 -0.054  0.020 -0.029  0.020  0.020  0.070 -0.004 -0.004  0.070  0.045 -0.004 -0.054 -0.079 -0.029 -0.004  0.020  0.145 -0.029 -0.079  0.270  0.045  0.020  0.020 -0.004  0.942 -0.029 -0.029  0.195  0.020 -0.054 -0.054  0.120 -0.029  0.568  0.020 -0.054  0.270 -0.079 -0.029 -0.029 -0.029 -0.079  0.045  0.045 -0.079 -0.004  0.070 -0.054 -0.054 -0.079 -0.054 -0.029  0.020 -0.054 -0.079  0.095 -0.004  0.045  0.070 -0.054 -0.029 -0.079 -0.004 -0.004 -0.004  0.070 -0.004  0.070 -0.029  0.020  0.045  0.045 -0.029  0.070  0.020  0.020 -0.004  0.045 -0.029 -0.029 -0.004  0.045 -0.029  0.045  0.070  0.070  0.070 -0.004 -0.079 -0.079  0.045 
 0.209  0.059  0.034 -0.065  0.134  0.009 -0.040  0.109 -0.015 -0.015 -0.015 -0.040  0.034 -0.015  0.034 -0.065 -0.015  0.109  0.059  0.009 -0.015  0.009 -0.065 -0.015  0.059  0.209 -0.015 -0.040  0.259  0.109 -0.015  0.134  0.009  0.906 -0.065  0.034  0.308  0.034 -0.065 -0.090  0.134  0.034  0.707  0.059 -0.065  0.632 -0.090  0.009  0.034  0.009 -0.090  0.034  0.059 -0.065 -0.015  0.109 -0.065 -0.065 -0.090 -0.090 -0.015  0.009 -0.090 -0.040  0.259 -0.015  0.034  0.034 -0.015  0.034 -0.090  0.009  0.034 -0.015  0.084 -0.040  0.109 -0.040 -0.015  0.034  0.009 -0.040  0.034  0.009 -0.040 -0.015  0.034 -0.040 -0.065 -0.040  0.034 -0.065  0.034  0.034  0.059  0.034 -0.015 -0.065 -0.115  0.209 
 0.306  0.032  0.181 -0.043  0.107  0.132 -0.018  0.156  0.007 -0.018  0.007 -0.043  0.057 -0.068  0.156 -0.068 -0.043  0.107  0.057  0.107 -0.043  0.132 -0.018 -0.043  0.032  0.381  0.057 -0.068  0.381  0.156 -0.018  0.156  0.057  0.854 -0.118  0.206  0.455  0.007  0.007 -0.118  0.132  0.032  0.854  0.082 -0.093  0.804 -0.018  0.156 -0.018  0.156 -0.093  0.032  0.107 -0.118 -0.018  0.181 -0.093 -0.068 -0.118 -0.118 -0.043  0.007 -0.043 -0.043  0.381 -0.018 -0.018  0.032  0.032  0.032 -0.093  0.007  0.032 -0.043  0.082  0.132  0.057  0.007 -0.018 -0.018 -0.018 -0.093  0.032 -0.043 -0.043  0.007 -0.018 -0.068 -0.093 -0.093  0.032 -0.093 -0.018  0.007  0.082  0.057 -0.018 -0.068 -0.142  0.231 
 0.304  0.030  0.180 -0.044  0.155  0.155  0.005  0.230  0.080  0.005  0.005  0.030  0.130 -0.044  0.130 -0.044 -0.044  0.130  0.055  0.180 -0.044  0.255 -0.019 -0.019  0.030  0.379  0.055 -0.044  0.354  0.180  0.030  0.205  0.055  0.828 -0.119  0.354  0.578  0.005 -0.019 -0.144  0.130  0.080  0.828  0.055 -0.119  0.778  0.005  0.255 -0.044  0.155 -0.119  0.005  0.105 -0.144  0.055  0.155 -0.119 -0.069 -0.144 -0.119 -0.019  0.005 -0.069 -0.019  0.504 -0.044 -0.044  0.030  0.005  0.005 -0.119  0.005 -0.019 -0.019  0.080  0.130  0.055  0.005  0.005 -0.019 -0.019 -0.119  0.005 -0.069 -0.019 -0.019 -0.044 -0.044 -0.119 -0.119  0.055 -0.119 -0.019  0.030  0.105  0.080 -0.044 -0.069 -0.169  0.205 
 0.384  0.060  0.184 -0.015  0.159  0.209  0.035  0.184  0.060  0.110  0.060  0.085  0.159 -0.065  0.085  0.010 -0.040  0.135  0.060  0.334 -0.065  0.234 -0.015 -0.040  0.060  0.384  0.110 -0.040  0.483  0.309  0.060  0.209  0.060  0.782 -0.040  0.458  0.683 -0.065 -0.065 -0.189  0.085  0.110  0.782  0.135 -0.140  0.757  0.135  0.334 -0.090  0.359 -0.115 -0.015  0.135 -0.189  0.035  0.184 -0.140 -0.090 -0.140 -0.115 -0.040  0.035 -0.065  0.035  0.583 -0.090 -0.090  0.035 -0.015  0.010 -0.164  0.060 -0.065  0.035  0.135  0.135  0.110  0.035  0.010  0.010 -0.090 -0.140 -0.015 -0.140  0.060 -0.015 -0.040  0.010 -0.140 -0.189  0.010 -0.140 -0.065  0.010  0.085  0.110 -0.065 -0.065 -0.164  0.184 
 0.394  0.120  0.219  0.045  0.194  0.269  0.070  0.169  0.070  0.194  0.045  0.144  0.144 -0.030  0.045  0.120 -0.055  0.120  0.070  0.344 -0.080  0.244 -0.005 -0.055  0.095  0.369  0.120 -0.030  0.518  0.319  0.095  0.194  0.045  0.767 -0.005  0.443  0.668 -0.080 -0.130 -0.204  0.120  0.095  0.742  0.144 -0.154  0.717  0.219  0.468 -0.080  0.369 -0.154 -0.030  0.144 -0.229  0.020  0.169 -0.154 -0.130 -0.179 -0.130 -0.080  0.095 -0.055  0.120  0.618 -0.055 -0.105  0.020 -0.080 -0.005 -0.179  0.095 -0.055  0.045  0.169  0.144  0.144  0.095  0.070 -0.005 -0.105 -0.154 -0.030 -0.154  0.120  0.045 -0.005 -0.005 -0.154 -0.204  0.020 -0.154 -0.105 -0.005  0.070  0.120 -0.080 -0.005 -0.179  0.194 
 0.393  0.218  0.268  0.069  0.243  0.368  0.168  0.243  0.044  0.293  0.019  0.218  0.143 -0.031  0.044  0.119 -0.006  0.119  0.094  0.542 -0.081  0.218 -0.006 -0.006  0.094  0.343  0.343  0.044  0.542  0.368  0.119  0.143  0.044  0.692  0.119  0.542  0.642 -0.131 -0.131 -0.230  0.168  0.193  0.716  0.218 -0.155  0.667  0.243  0.467 -0.031  0.368 -0.180 -0.031  0.168 -0.255 -0.006  0.168 -0.180 -0.131 -0.205 -0.081 -0.081  0.143 -0.081  0.094  0.642 -0.056 -0.131 -0.006 -0.106  0.019 -0.205  0.069 -0.106  0.019  0.168  0.094  0.143  0.094  0.069 -0.006 -0.106 -0.230 -0.031 -0.180  0.143  0.193 -0.031 -0.006 -0.205 -0.230 -0.006 -0.131 -0.081 -0.056  0.069  0.143 -0.081 -0.006 -0.056  0.193 
 0.358  0.259  0.333  0.034  0.234  0.408  0.209  0.284  0.109  0.234  0.059  0.184  0.209  0.009  0.059  0.134  0.059  0.109  0.084  0.582 -0.065  0.209 -0.015  0.009  0.109  0.333  0.433  0.109  0.533  0.358  0.134  0.159  0.084  0.632  0.159  0.607  0.657 -0.140 -0.115 -0.215  0.159  0.234  0.707  0.308 -0.140  0.632  0.259  0.483  0.009  0.333 -0.140 -0.040  0.109 -0.240  0.034  0.184 -0.140 -0.115 -0.215 -0.115 -0.115  0.184 -0.065  0.109  0.632  0.034 -0.140 -0.040 -0.115 -0.015 -0.240  0.059 -0.090  0.034  0.184  0.084  0.134  0.084  0.059 -0.040 -0.115 -0.240 -0.015 -0.215  0.109  0.234 -0.015  0.009 -0.215 -0.240 -0.040 -0.165 -0.090 -0.090  0.059  0.159 -0.065 -0.015 -0.040  0.159 
 0.377  0.253  0.402  0.053  0.228  0.377  0.228  0.302  0.128  0.228  0.128  0.228  0.228  0.003  0.253  0.178  0.103  0.103  0.078  0.626 -0.096  0.178 -0.021  0.028  0.103  0.327  0.502  0.128  0.527  0.377  0.128  0.128  0.128  0.576  0.178  0.601  0.576 -0.121 -0.096 -0.221  0.178  0.278  0.651  0.302 -0.171  0.552  0.327  0.452  0.128  0.352 -0.146 -0.096  0.103 -0.271  0.053  0.128 -0.146 -0.121 -0.221 -0.146 -0.046  0.153 -0.096  0.103  0.527  0.028 -0.146 -0.046 -0.071  0.053 -0.246  0.053 -0.096  0.078  0.203  0.078  0.153  0.078  0.078 -0.021 -0.121 -0.221 -0.046 -0.196  0.103  0.253 -0.021  0.003 -0.221 -0.246 -0.071 -0.171 -0.096 -0.096  0.103  0.153 -0.071 -0.021 -0.071  0.103 
 0.397  0.248  0.447  0.048  0.223  0.372  0.223  0.297  0.123  0.173  0.123  0.223  0.248 -0.026  0.248  0.198  0.123  0.123  0.023  0.571 -0.076  0.223 -0.026  0.048  0.148  0.273  0.571  0.123  0.522  0.347  0.123  0.098  0.098  0.571  0.223  0.596  0.522 -0.101 -0.076 -0.226  0.148  0.273  0.646  0.297 -0.151  0.547  0.422  0.447  0.198  0.397 -0.126 -0.126  0.098 -0.276  0.048  0.123 -0.176 -0.076 -0.226 -0.126 -0.026  0.173 -0.076  0.098  0.472  0.048 -0.151 -0.101 -0.051  0.073 -0.251  0.048 -0.076  0.073  0.173  0.073  0.148  0.073  0.098 -0.001 -0.126 -0.226 -0.026 -0.201  0.098  0.248 -0.026 -0.001 -0.201 -0.251 -0.076 -0.176 -0.101 -0.126  0.073  0.123 -0.101 -0.026 -0.101  0.073 
 0.412  0.262  0.486  0.038  0.287  0.387  0.262  0.287  0.162  0.162  0.113  0.237  0.262 -0.037  0.287  0.138  0.113  0.113 -0.012  0.561 -0.062  0.212 -0.037  0.113  0.138  0.262  0.586  0.187  0.511  0.312  0.162  0.063  0.088  0.536  0.262  0.586  0.436 -0.112 -0.037 -0.161  0.113  0.312  0.636  0.287 -0.161  0.536  0.461  0.436  0.262  0.461 -0.062 -0.112  0.088 -0.286  0.013  0.113 -0.161 -0.062 -0.236 -0.161 -0.012  0.162 -0.037  0.063  0.387  0.038 -0.161 -0.112 -0.012  0.088 -0.261  0.038 -0.112  0.063  0.162  0.088  0.113  0.063  0.113  0.013 -0.112 -0.211 -0.037 -0.161  0.113  0.262 -0.037  0.038 -0.211 -0.236 -0.087 -0.186 -0.087 -0.137  0.063  0.113 -0.137 -0.037 -0.112  0.038 
 0.381  0.257  0.481  0.007  0.282  0.431  0.282  0.282  0.157  0.157  0.082  0.232  0.257 -0.042  0.282  0.132  0.132  0.107 -0.042  0.556 -0.042  0.207 -0.042  0.132  0.132  0.257  0.531  0.257  0.506  0.306  0.182  0.082  0.107  0.531  0.306  0.580  0.431 -0.117 -0.017 -0.092  0.132  0.381  0.630  0.356 -0.167  0.506  0.456  0.456  0.306  0.556 -0.017 -0.092  0.057 -0.291  0.007  0.082 -0.167 -0.042 -0.242 -0.167 -0.042  0.157 -0.042  0.082  0.356  0.032 -0.142 -0.117  0.057  0.082 -0.267  0.007 -0.117  0.057  0.182  0.082  0.132  0.032  0.107 -0.017 -0.167 -0.217 -0.017 -0.192  0.132  0.282 -0.042  0.032 -0.217 -0.242 -0.067 -0.192 -0.067 -0.142  0.057  0.107 -0.142  0.007 -0.092  0.007 
 0.371  0.246  0.470 -0.003  0.371  0.421  0.271  0.246  0.196  0.146  0.097  0.221  0.271 -0.053  0.221  0.171  0.122  0.146 -0.028  0.545 -0.078  0.196 -0.003  0.196  0.122  0.246  0.520  0.321  0.495  0.296  0.196  0.072  0.122  0.495  0.396  0.570  0.421 -0.128  0.072  0.022  0.196  0.421  0.595  0.396 -0.177  0.495  0.520  0.495  0.346  0.620 -0.028 -0.103  0.072 -0.302 -0.003  0.072 -0.177 -0.053 -0.252 -0.177 -0.053  0.171 -0.003  0.022  0.271  0.047 -0.152 -0.128  0.072  0.047 -0.277 -0.028 -0.103  0.072  0.171  0.072  0.196 -0.003  0.072 -0.003 -0.152 -0.227 -0.003 -0.202  0.122  0.346 -0.053  0.072 -0.227 -0.227 -0.053 -0.152 -0.028 -0.152  0.047  0.097 -0.053  0.072 -0.078 -0.028 
 0.346  0.246  0.421  0.022  0.371  0.421  0.246  0.246  0.196  0.171  0.097  0.196  0.296 -0.078  0.221  0.171  0.171  0.146 -0.003  0.545 -0.103  0.196 -0.003  0.296  0.097  0.246  0.520  0.321  0.495  0.321  0.196  0.047  0.122  0.495  0.421  0.570  0.421 -0.177  0.072  0.122  0.196  0.421  0.570  0.396 -0.177  0.520  0.545  0.495  0.421  0.620 -0.028 -0.078  0.072 -0.302 -0.003  0.072 -0.177 -0.053 -0.252 -0.177 -0.028  0.171 -0.028  0.022  0.221  0.047 -0.152 -0.128  0.072  0.047 -0.277 -0.003 -0.128  0.072  0.171  0.047  0.196 -0.003  0.072 -0.028 -0.152 -0.227 -0.003 -0.177  0.122  0.321 -0.053  0.072 -0.227 -0.252 -0.053 -0.152 -0.028 -0.152  0.047  0.097 -0.028  0.146 -0.078 -0.028 
 0.316  0.241  0.416  0.067  0.416  0.440  0.216  0.266  0.191  0.166  0.067  0.166  0.341 -0.083  0.166  0.191  0.191  0.166  0.042  0.540 -0.108  0.191  0.042  0.316  0.067  0.216  0.515  0.366  0.490  0.366  0.191  0.042  0.117  0.465  0.515  0.565  0.341 -0.207  0.067  0.166  0.241  0.465  0.565  0.391 -0.157  0.540  0.590  0.515  0.416  0.615 -0.033 -0.033  0.042 -0.282 -0.008  0.067 -0.182 -0.058 -0.257 -0.182 -0.033  0.166 -0.008 -0.008  0.117  0.042 -0.157 -0.133  0.142  0.042 -0.282  0.017 -0.133  0.067  0.216  0.067  0.166 -0.008  0.067 -0.008 -0.133 -0.207 -0.008 -0.182  0.092  0.316 -0.058  0.092 -0.207 -0.232 -0.058 -0.157 -0.033 -0.133  0.042  0.092 -0.008  0.142 -0.058 -0.008 
 0.316  0.266  0.341  0.092  0.440  0.490  0.266  0.216  0.166  0.142  0.042  0.042  0.341 -0.033  0.166  0.191  0.117  0.191  0.017  0.515 -0.083  0.241  0.017  0.316  0.067  0.216  0.515  0.391  0.465  0.341  0.241  0.067  0.117  0.366  0.490  0.490  0.316 -0.157 -0.008  0.117  0.191  0.416  0.565  0.341 -0.108  0.490  0.590  0.416  0.266  0.540 -0.033 -0.033  0.017 -0.207  0.042 -0.008 -0.133 -0.033 -0.182 -0.108 -0.008  0.117 -0.008  0.017  0.092  0.092 -0.133 -0.083  0.067 -0.008 -0.232  0.042 -0.083  0.092  0.191  0.017  0.191  0.042  0.042  0.042 -0.083 -0.207  0.017 -0.108  0.092  0.216 -0.008  0.067 -0.133 -0.157 -0.033 -0.083 -0.033 -0.108  0.042  0.117  0.017  0.092 -0.058 -0.058 
 0.239  0.239  0.214  0.089  0.388  0.463  0.189  0.239  0.114  0.114  0.064  0.089  0.313 -0.010  0.089  0.064  0.039  0.089 -0.035  0.438 -0.060  0.264 -0.035  0.264  0.089  0.214  0.463  0.413  0.463  0.264  0.313  0.089  0.089  0.264  0.338  0.438  0.313 -0.110 -0.035  0.014  0.089  0.438  0.388  0.214 -0.085  0.463  0.563  0.288  0.288  0.488 -0.010 -0.035 -0.035 -0.160  0.014 -0.060 -0.060 -0.060 -0.110 -0.035 -0.085  0.139 -0.035 -0.035 -0.010 -0.010 -0.085 -0.010  0.014 -0.010 -0.135  0.064 -0.085  0.039  0.139  0.089  0.164  0.064 -0.010  0.039 -0.110 -0.135 -0.010 -0.085  0.114  0.114 -0.010 -0.060 -0.085 -0.135 -0.010 -0.085  0.039 -0.010  0.089  0.089  0.039  0.089 -0.035 -0.135 
 0.160  0.260  0.185  0.110  0.334  0.459  0.185  0.260  0.010  0.135  0.035  0.085  0.284 -0.014  0.085  0.060  0.010  0.035 -0.039  0.409 -0.039  0.260  0.010  0.235  0.060  0.185  0.484  0.409  0.459  0.284  0.309  0.085  0.010  0.210  0.284  0.459  0.334 -0.089 -0.039 -0.039  0.035  0.459  0.384  0.210 -0.064  0.484  0.534  0.235  0.284  0.459 -0.014 -0.089 -0.039 -0.139  0.035 -0.039 -0.064 -0.039 -0.089 -0.014 -0.089  0.160 -0.014 -0.064  0.010 -0.014 -0.064  0.010  0.010 -0.064 -0.114  0.035 -0.064  0.010  0.085  0.110  0.135  0.060  0.010 -0.014 -0.114 -0.139  0.010 -0.064  0.110  0.110  0.010 -0.089 -0.089 -0.114  0.010 -0.089  0.010  0.010  0.110  0.085 -0.014  0.010 -0.039 -0.114 
 0.119  0.243  0.044  0.143  0.293  0.467  0.218  0.293  0.044  0.168  0.019  0.069  0.268 -0.031  0.069  0.044  0.019 -0.031 -0.081  0.293 -0.006  0.218  0.019  0.218  0.069  0.193  0.492  0.368  0.442  0.268  0.318  0.069 -0.006  0.143  0.193  0.467  0.343 -0.081 -0.056 -0.056  0.069  0.442  0.193  0.168 -0.081  0.492  0.418  0.218  0.293  0.368 -0.006 -0.106 -0.006 -0.106  0.044 -0.031 -0.056 -0.056 -0.056 -0.006 -0.106  0.168 -0.006 -0.031 -0.006  0.019 -0.106  0.019 -0.006 -0.081 -0.081 -0.006 -0.056 -0.031  0.069  0.143  0.119  0.044  0.019  0.019 -0.081 -0.106 -0.006 -0.056  0.094  0.094 -0.031 -0.081 -0.081 -0.106 -0.006 -0.056  0.044 -0.006  0.069  0.094 -0.031 -0.006 -0.031 -0.106 
 0.103  0.252  0.028  0.128  0.302  0.451  0.202  0.302  0.028  0.177  0.053  0.078  0.227 -0.022  0.078  0.028  0.003 -0.047 -0.097  0.202  0.003  0.227  0.003  0.152  0.078  0.202  0.476  0.352  0.377  0.277  0.327  0.078 -0.022  0.152  0.202  0.501  0.252 -0.072 -0.047 -0.047  0.103  0.377  0.177  0.177 -0.072  0.501  0.377  0.227  0.252  0.377  0.003 -0.097  0.003 -0.097  0.028 -0.022 -0.047 -0.047 -0.047  0.003 -0.097  0.177 -0.022 -0.022 -0.022  0.028 -0.097  0.003  0.003 -0.072 -0.072  0.003 -0.047  0.003  0.053  0.152  0.152  0.078  0.028  0.028 -0.072 -0.097  0.003 -0.047  0.053  0.128 -0.047 -0.072 -0.097 -0.097 -0.022 -0.047  0.053  0.003  0.078  0.078 -0.022  0.003 -0.022 -0.097 
 0.043  0.242  0.018  0.142  0.267  0.441  0.167  0.317  0.043  0.192  0.018  0.093  0.217 -0.007  0.093  0.068  0.018 -0.032 -0.082  0.167  0.018  0.242 -0.007  0.068  0.043  0.167  0.441  0.267  0.267  0.292  0.242  0.093 -0.007  0.142  0.217  0.516  0.242 -0.057 -0.032 -0.032  0.093  0.342  0.142  0.167 -0.057  0.491  0.367  0.242  0.167  0.267  0.018 -0.082  0.018 -0.082 -0.007 -0.032 -0.057 -0.032 -0.032  0.018 -0.082  0.167 -0.007 -0.032 -0.007  0.043 -0.082  0.018 -0.007 -0.082 -0.057 -0.007 -0.032 -0.007  0.043  0.167  0.142  0.093  0.018  0.043 -0.057 -0.082  0.043 -0.032  0.068  0.093 -0.032 -0.057 -0.082 -0.082 -0.007 -0.032  0.068 -0.007  0.093  0.093 -0.007  0.018 -0.007 -0.082 
 0.054  0.203  0.029  0.153  0.253  0.452  0.178  0.278 -0.021  0.153  0.004  0.104  0.228  0.004  0.054  0.029  0.029 -0.021 -0.071  0.153  0.029  0.253  0.004  0.004  0.029  0.178  0.452  0.203  0.203  0.278  0.178  0.104 -0.021  0.129  0.228  0.477  0.253 -0.046 -0.021 -0.021  0.104  0.203  0.079  0.178 -0.071  0.427  0.353  0.228  0.178  0.203  0.029 -0.071  0.029 -0.071 -0.021 -0.046 -0.046 -0.021 -0.021  0.004 -0.071  0.178 -0.021 -0.021  0.004  0.054 -0.071  0.004  0.004 -0.071 -0.071  0.004 -0.046  0.004  0.029  0.178  0.153  0.079  0.029 -0.021 -0.046 -0.071  0.054 -0.021  0.054  0.104 -0.021 -0.046 -0.071 -0.071 -0.021 -0.046  0.029 -0.021  0.079  0.104  0.004  0.029  0.004 -0.071 
 0.065  0.215  0.040  0.165  0.215  0.389  0.165  0.265 -0.034  0.165  0.015  0.115  0.240 -0.009  0.015  0.015  0.040 -0.009 -0.059  0.140  0.040  0.215  0.015 -0.009 -0.009  0.165  0.364  0.090  0.190  0.289  0.165  0.115 -0.009  0.065  0.190  0.489  0.240 -0.034 -0.009 -0.009  0.065  0.215  0.090  0.190 -0.059  0.339  0.314  0.190  0.115  0.165  0.015 -0.059  0.040 -0.059 -0.009 -0.059 -0.059 -0.034 -0.009  0.015 -0.059  0.115 -0.009 -0.034  0.015  0.040 -0.059  0.015 -0.009 -0.059 -0.059  0.015 -0.059  0.015  0.040  0.165  0.090  0.065  0.040 -0.009 -0.034 -0.059  0.040 -0.034  0.015  0.040 -0.009 -0.034 -0.059 -0.059 -0.009 -0.034  0.015 -0.009  0.090  0.115 -0.009  0.015  0.015 -0.059 
 0.027  0.102  0.027  0.176  0.226  0.351  0.151  0.251 -0.023  0.127 -0.023  0.077  0.176 -0.023  0.027  0.002  0.052  0.002 -0.048  0.102  0.052  0.201  0.027  0.002  0.002  0.151  0.326  0.002  0.127  0.201  0.127  0.102  0.002  0.002  0.201  0.475  0.127 -0.023  0.002  0.002  0.002  0.151  0.077  0.151 -0.048  0.276  0.276  0.201  0.077  0.176  0.002 -0.048  0.027 -0.048  0.002 -0.048 -0.048 -0.023  0.002  0.002 -0.048  0.052 -0.023 -0.048  0.002 -0.023 -0.048  0.027  0.002 -0.048 -0.048  0.027 -0.048 -0.023  0.052  0.151  0.077  0.077  0.052  0.002 -0.023 -0.048  0.052 -0.048  0.002  0.027  0.002 -0.023 -0.048 -0.048  0.002 -0.048  0.027 -0.023  0.052  0.052  0.002  0.027  0.002 -0.048 
 0.020  0.095  0.020  0.194  0.169  0.194  0.095  0.194 -0.005  0.095 -0.005 -0.005  0.095 -0.005  0.045  0.020  0.020  0.020 -0.030 -0.005  0.020  0.095  0.045 -0.030  0.020  0.144  0.120  0.020  0.095  0.144  0.070  0.120  0.020 -0.030  0.120  0.493  0.070 -0.030 -0.005 -0.005 -0.005  0.144  0.045  0.045 -0.030  0.219  0.194  0.120  0.070  0.120  0.020 -0.030  0.045 -0.030 -0.030 -0.030 -0.030 -0.005 -0.005 -0.005 -0.030 -0.005 -0.005 -0.030 -0.005 -0.005 -0.030 -0.005 -0.005 -0.030 -0.030  0.020 -0.030 -0.030  0.020  0.120  0.045  0.045  0.020 -0.005 -0.030 -0.030 -0.005 -0.030 -0.030  0.020  0.020 -0.005 -0.030 -0.030  0.020 -0.030 -0.005 -0.005  0.045  0.045 -0.005  0.020  0.020 -0.030 
 0.031  0.081  0.031  0.081  0.081  0.156  0.081  0.181  0.006  0.081 -0.018 -0.018  0.081  0.006  0.031  0.031  0.006  0.031 -0.018 -0.018  0.031  0.106  0.056 -0.018  0.031  0.056  0.031  0.006  0.081  0.106  0.056  0.056  0.031 -0.018  0.056  0.380  0.031 -0.018 -0.018  0.006  0.006  0.056  0.006 -0.018 -0.018  0.106  0.081  0.081  0.031  0.106  0.006 -0.018  0.031 -0.018 -0.018 -0.018 -0.018  0.006  0.006  0.006 -0.018 -0.018  0.006 -0.018  0.006 -0.018 -0.018  0.006 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018  0.006  0.081  0.006  0.031  0.006  0.006 -0.018 -0.018 -0.018 -0.018 -0.018  0.031 -0.018  0.006 -0.018 -0.018  0.031 -0.018 -0.018  0.006  0.031  0.056 -0.018  0.006  0.006 -0.018 
-0.004 -0.004 -0.004  0.020  0.045  0.070  0.020  0.095 -0.004  0.020 -0.004 -0.004  0.020  0.020 -0.004  0.020 -0.004  0.020 -0.004 -0.004 -0.004  0.020  0.020 -0.004 -0.004 -0.004 -0.004 -0.004  0.045 -0.004 -0.004  0.020  0.020 -0.004 -0.004  0.195 -0.004 -0.004 -0.004 -0.004 -0.004  0.020 -0.004 -0.004 -0.004 -0.004  0.020  0.020 -0.004  0.020 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004  0.020 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004  0.020  0.020 -0.004 -0.004 -0.004 -0.004 
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-0.009  0.215  0.415 -0.034  0.365  0.390  0.415  0.365  0.041  0.315  0.215  0.066  0.489  0.041  0.091  0.091  0.141 -0.134 -0.208 -0.009  0.290  0.116  0.265 -0.109  0.066  0.041  0.116  0.116  0.165  0.390  0.041  0.265  0.016 -0.084  0.215  0.763  0.639 -0.034  0.041  0.240  0.265 -0.034  0.215  0.091 -0.134  0.290  0.439  0.614  0.091  0.290 -0.059 -0.084  0.116 -0.134 -0.009  0.091 -0.109 -0.009 -0.109 -0.134 -0.084  0.066 -0.084 -0.109 -0.059 -0.009 -0.109  0.041 -0.084 -0.009 -0.134  0.041  0.066 -0.084  0.141  0.738 -0.084  0.265  0.091 -0.134 -0.158 -0.208 -0.158 -0.034  0.041 -0.009 -0.109 -0.059 -0.158 -0.134  0.165 -0.109 -0.059 -0.009  0.265  0.116 -0.183  0.215 -0.009  0.016 
 0.068  0.218  0.417 -0.031  0.442  0.392  0.517  0.367  0.043  0.317  0.168  0.043  0.467  0.018  0.118  0.143  0.093 -0.131 -0.206  0.118  0.292  0.193  0.268 -0.106  0.068  0.043  0.168  0.093  0.143  0.442  0.043  0.342  0.018 -0.056  0.292  0.716  0.666 -0.056  0.043  0.317  0.268 -0.056  0.218  0.143 -0.081  0.442  0.567  0.542  0.143  0.292 -0.056 -0.081  0.093 -0.156 -0.006  0.118 -0.081 -0.006 -0.131 -0.156 -0.156  0.068 -0.081 -0.106 -0.081 -0.056 -0.131  0.018 -0.081  0.018 -0.156  0.068  0.018 -0.056  0.218  0.666 -0.031  0.292  0.043 -0.156 -0.156 -0.181 -0.156 -0.106  0.018 -0.031 -0.131 -0.081 -0.156 -0.131  0.168 -0.131 -0.056  0.018  0.243  0.118 -0.206  0.218 -0.056 -0.006 
 0.043  0.268  0.417 -0.031  0.467  0.467  0.591  0.367  0.043  0.467  0.143  0.043  0.467  0.018  0.118  0.193  0.093 -0.156 -0.231  0.292  0.268  0.193  0.292  0.018  0.093  0.093  0.243  0.218  0.193  0.442  0.143  0.342 -0.006 -0.081  0.342  0.616  0.691 -0.081  0.018  0.317  0.218 -0.056  0.218  0.218 -0.106  0.467  0.641  0.467  0.268  0.367 -0.081 -0.031  0.018 -0.181  0.043  0.143 -0.056 -0.006 -0.181 -0.156 -0.181  0.093 -0.081 -0.081 -0.131 -0.056 -0.181 -0.031 -0.106  0.018 -0.181  0.043 -0.006 -0.081  0.268  0.616 -0.031  0.292 -0.031 -0.131 -0.181 -0.206 -0.131 -0.156  0.043 -0.031 -0.156 -0.131 -0.181 -0.131  0.093 -0.156 -0.031 -0.006  0.193  0.068 -0.206  0.268 -0.106 -0.031 
 0.059  0.258  0.408  0.034  0.507  0.457  0.582  0.358  0.084  0.507  0.134  0.084  0.457  0.059  0.084  0.258  0.084 -0.141 -0.215  0.408  0.258  0.208  0.308  0.084  0.084  0.109  0.258  0.283  0.183  0.457  0.158  0.283 -0.016 -0.091  0.358  0.557  0.682 -0.091 -0.016  0.333  0.158 -0.016  0.233  0.208 -0.091  0.482  0.632  0.432  0.283  0.432 -0.091 -0.066  0.009 -0.190  0.034  0.134 -0.066 -0.016 -0.190 -0.165 -0.190  0.084 -0.091 -0.091 -0.190 -0.066 -0.165 -0.066 -0.091  0.009 -0.190  0.034 -0.016 -0.091  0.308  0.607 -0.016  0.283 -0.091 -0.141 -0.165 -0.240 -0.141 -0.116  0.034  0.034 -0.165 -0.141 -0.190 -0.116  0.084 -0.165 -0.041 -0.016  0.183  0.109 -0.141  0.283 -0.116 -0.066 
 0.075  0.275  0.399  0.050  0.524  0.424  0.573  0.374  0.100  0.598  0.175  0.075  0.499  0.050  0.050  0.275  0.075 -0.149 -0.199  0.499  0.250  0.225  0.275  0.250  0.075  0.150  0.299  0.299  0.225  0.399  0.175  0.250  0.025 -0.024  0.399  0.424  0.648 -0.149  0.025  0.349  0.125  0.125  0.250  0.250 -0.049  0.524  0.623  0.374  0.374  0.474 -0.099 -0.074 -0.049 -0.174  0.050  0.125 -0.024 -0.049 -0.224 -0.199 -0.124  0.100 -0.124 -0.049 -0.174 -0.099 -0.124 -0.099 -0.074 -0.024 -0.199  0.025  0.050 -0.049  0.324  0.549  0.025  0.225 -0.099 -0.149 -0.174 -0.199 -0.149 -0.124  0.000  0.075 -0.174 -0.199 -0.199 -0.124  0.025 -0.199 -0.049  0.000  0.150  0.100 -0.099  0.324 -0.124 -0.074 
 0.074  0.248  0.398  0.124  0.572  0.423  0.547  0.373  0.074  0.597  0.173  0.099  0.497  0.024  0.049  0.348  0.049 -0.126 -0.175  0.572  0.248  0.223  0.273  0.273  0.074  0.124  0.298  0.298  0.223  0.398  0.173  0.248  0.024 -0.026  0.398  0.398  0.647 -0.150  0.024  0.348  0.124  0.148  0.248  0.248 -0.051  0.522  0.647  0.398  0.423  0.497 -0.101 -0.101 -0.101 -0.175  0.024  0.099 -0.001 -0.076 -0.225 -0.175 -0.126  0.099 -0.126 -0.026 -0.175 -0.076 -0.101 -0.101 -0.051 -0.051 -0.175  0.024  0.024 -0.026  0.298  0.547  0.049  0.223 -0.101 -0.150 -0.175 -0.175 -0.150 -0.126 -0.001  0.099 -0.175 -0.200 -0.200 -0.150 -0.026 -0.175 -0.051  0.024  0.124  0.099 -0.101  0.323 -0.101 -0.101 
 0.076  0.250  0.400  0.126  0.574  0.400  0.549  0.350  0.101  0.599  0.200  0.101  0.499  0.026  0.026  0.375  0.001 -0.099 -0.148  0.624  0.225  0.225  0.300  0.325  0.026  0.076  0.250  0.325  0.225  0.350  0.200  0.250  0.001  0.051  0.425  0.375  0.624 -0.148  0.051  0.375  0.126  0.175  0.225  0.250 -0.024  0.499  0.649  0.400  0.425  0.499 -0.074 -0.124 -0.148 -0.198  0.001  0.076 -0.024 -0.099 -0.248 -0.173 -0.124  0.101 -0.099 -0.024 -0.173 -0.099 -0.099 -0.099 -0.049 -0.049 -0.198  0.001  0.026 -0.024  0.300  0.524  0.076  0.225 -0.099 -0.148 -0.173 -0.148 -0.124 -0.124  0.026  0.101 -0.173 -0.198 -0.198 -0.173 -0.049 -0.198 -0.049  0.026  0.076  0.101 -0.099  0.325 -0.074 -0.124 
 0.101  0.251  0.400  0.126  0.550  0.400  0.550  0.325  0.101  0.599  0.201  0.076  0.475  0.001  0.051  0.400  0.026 -0.098 -0.148  0.649  0.201  0.226  0.325  0.325  0.001  0.051  0.276  0.325  0.251  0.375  0.201  0.201  0.001  0.076  0.400  0.375  0.624 -0.148  0.051  0.375  0.126  0.276  0.226  0.276 -0.048  0.500  0.649  0.400  0.425  0.525 -0.048 -0.098 -0.173 -0.198  0.026  0.051  0.001 -0.098 -0.248 -0.148 -0.123  0.101 -0.123 -0.023 -0.173 -0.073 -0.098 -0.098 -0.048 -0.048 -0.223  0.001  0.026  0.001  0.300  0.525  0.076  0.201 -0.098 -0.148 -0.198 -0.148 -0.123 -0.123  0.026  0.101 -0.173 -0.223 -0.198 -0.198 -0.073 -0.198 -0.048  0.026  0.076  0.126 -0.098  0.325 -0.098 -0.123 
 0.100  0.250  0.424  0.150  0.524  0.399  0.549  0.324  0.100  0.598  0.250  0.075  0.474 -0.024  0.050  0.399  0.025 -0.074 -0.149  0.648  0.200  0.200  0.324  0.299  0.000  0.050  0.299  0.324  0.275  0.374  0.225  0.175  0.000  0.100  0.399  0.324  0.623 -0.149  0.075  0.374  0.175  0.324  0.225  0.324 -0.099  0.499  0.648  0.399  0.424  0.524 -0.049 -0.099 -0.174 -0.199  0.050  0.000  0.000 -0.099 -0.249 -0.124 -0.124  0.125 -0.149 -0.024 -0.174 -0.074 -0.099 -0.099 -0.049 -0.049 -0.199  0.000  0.000  0.025  0.299  0.474  0.125  0.200 -0.099 -0.124 -0.199 -0.149 -0.124 -0.124  0.025  0.100 -0.149 -0.224 -0.199 -0.199 -0.124 -0.199 -0.024  0.000  0.075  0.125 -0.099  0.324 -0.099 -0.124 
 0.076  0.251  0.425  0.151  0.525  0.400  0.550  0.325  0.101  0.599  0.251  0.076  0.475 -0.023  0.076  0.400  0.026 -0.073 -0.148  0.649  0.201  0.201  0.325  0.300  0.001  0.051  0.276  0.325  0.276  0.375  0.226  0.176  0.001  0.101  0.400  0.325  0.624 -0.148  0.101  0.375  0.176  0.325  0.226  0.325 -0.098  0.500  0.649  0.400  0.425  0.500 -0.048 -0.098 -0.173 -0.198  0.051  0.026 -0.023 -0.098 -0.248 -0.123 -0.123  0.101 -0.148 -0.023 -0.198 -0.073 -0.098 -0.098 -0.048 -0.048 -0.198  0.001  0.001  0.026  0.300  0.475  0.126  0.201 -0.098 -0.123 -0.198 -0.148 -0.123 -0.123  0.001  0.126 -0.148 -0.223 -0.198 -0.198 -0.123 -0.198 -0.023  0.001  0.076  0.126 -0.098  0.300 -0.098 -0.123 
 0.076  0.276  0.400  0.176  0.525  0.400  0.550  0.350  0.101  0.599  0.276  0.076  0.475  0.001  0.076  0.400 -0.023 -0.073 -0.123  0.649  0.176  0.201  0.350  0.300  0.001  0.051  0.276  0.325  0.300  0.350  0.226  0.201  0.001  0.101  0.400  0.325  0.599 -0.148  0.126  0.375  0.201  0.325  0.226  0.350 -0.098  0.500  0.649  0.350  0.425  0.500 -0.023 -0.123 -0.173 -0.198  0.051  0.001 -0.023 -0.098 -0.248 -0.123 -0.098  0.101 -0.173 -0.048 -0.198 -0.098 -0.098 -0.098 -0.048 -0.048 -0.198  0.001  0.001  0.026  0.276  0.425  0.151  0.251 -0.123 -0.123 -0.198 -0.148 -0.098 -0.123  0.001  0.126 -0.148 -0.223 -0.173 -0.198 -0.123 -0.198 -0.023 -0.023  0.076  0.126 -0.098  0.300 -0.098 -0.123 
 0.122  0.271  0.396  0.171  0.520  0.421  0.545  0.321  0.097  0.570  0.271  0.072  0.470  0.022  0.146  0.445 -0.028 -0.078 -0.152  0.645  0.196  0.196  0.346  0.346 -0.003  0.047  0.271  0.321  0.271  0.346  0.221  0.196 -0.003  0.097  0.396  0.346  0.595 -0.152  0.122  0.371  0.196  0.346  0.221  0.396 -0.103  0.495  0.645  0.321  0.421  0.495 -0.028 -0.128 -0.177 -0.202  0.047 -0.028 -0.003 -0.078 -0.252 -0.128 -0.128  0.097 -0.177 -0.053 -0.202 -0.103 -0.128 -0.078 -0.053 -0.003 -0.227  0.022  0.047  0.072  0.271  0.371  0.296  0.296 -0.128 -0.128 -0.202 -0.152 -0.103 -0.128 -0.003  0.146 -0.152 -0.227 -0.152 -0.202 -0.128 -0.202  0.022 -0.028  0.097  0.122 -0.053  0.296 -0.128 -0.128 
 0.142  0.242  0.392  0.142  0.566  0.417  0.541  0.342  0.093  0.541  0.292  0.068  0.417  0.018  0.167  0.466 -0.057 -0.082 -0.156  0.641  0.192  0.192  0.367  0.367 -0.057  0.043  0.267  0.317  0.267  0.342  0.242  0.192 -0.007  0.068  0.392  0.367  0.591 -0.156  0.093  0.367  0.192  0.367  0.217  0.441 -0.107  0.516  0.616  0.342  0.417  0.491 -0.032 -0.156 -0.181 -0.206  0.043 -0.007 -0.007 -0.082 -0.256 -0.132 -0.132  0.068 -0.132 -0.057 -0.206 -0.107 -0.132 -0.057 -0.032  0.068 -0.231  0.018  0.068  0.142  0.267  0.267  0.342  0.317 -0.156 -0.132 -0.181 -0.132 -0.132 -0.132 -0.007  0.242 -0.156 -0.206 -0.132 -0.206 -0.132 -0.156  0.118 -0.057  0.093  0.142 -0.057  0.292 -0.132 -0.132 
 0.098  0.247  0.397  0.147  0.571  0.446  0.496  0.322  0.048  0.496  0.222  0.098  0.422  0.048  0.172  0.446 -0.027 -0.027 -0.176  0.471  0.147  0.123  0.172  0.272 -0.027  0.048  0.272  0.322  0.322  0.272  0.247  0.222  0.048 -0.027  0.322  0.397  0.471 -0.077  0.123  0.422  0.172  0.297  0.197  0.347 -0.077  0.496  0.671  0.347  0.471  0.521 -0.002 -0.102 -0.127 -0.176 -0.002 -0.002  0.073 -0.002 -0.176 -0.102 -0.052  0.048 -0.127 -0.052 -0.151 -0.052 -0.102 -0.027  0.023 -0.027 -0.201  0.048 -0.002  0.147  0.197  0.272  0.272  0.222 -0.077 -0.052 -0.151 -0.151 -0.077 -0.127  0.023  0.172 -0.151 -0.176 -0.127 -0.201 -0.102 -0.127  0.123 -0.102  0.123  0.098 -0.002  0.297 -0.077 -0.127 
 0.104  0.278  0.228  0.153  0.477  0.403  0.427  0.253  0.029  0.427  0.203  0.129  0.353  0.004  0.104  0.278  0.029  0.004 -0.145  0.452  0.104  0.153  0.029  0.253  0.029  0.129  0.303  0.303  0.228  0.228  0.253  0.203  0.104  0.004  0.353  0.378  0.378 -0.046  0.104  0.477  0.129  0.253  0.104  0.353 -0.096  0.477  0.702  0.328  0.502  0.403  0.029 -0.021 -0.046 -0.170  0.054 -0.021  0.054  0.029 -0.096 -0.046 -0.096  0.079 -0.071 -0.071 -0.096 -0.021 -0.170 -0.046  0.029 -0.046 -0.145  0.054  0.004  0.104  0.129  0.203  0.178  0.153 -0.046  0.004 -0.121 -0.121 -0.021 -0.121  0.004  0.079 -0.096 -0.121 -0.096 -0.145 -0.071 -0.096  0.029 -0.071  0.104  0.104  0.004  0.178 -0.046 -0.170 
 0.093  0.292  0.143  0.168  0.492  0.442  0.367  0.268  0.043  0.367  0.168  0.118  0.367 -0.006  0.068  0.243 -0.006  0.018 -0.131  0.417  0.093  0.168  0.018  0.243  0.043  0.143  0.317  0.292  0.218  0.243  0.218  0.193  0.118  0.018  0.342  0.367  0.342 -0.056  0.093  0.442  0.143  0.268  0.093  0.317 -0.081  0.467  0.716  0.317  0.542  0.392  0.043 -0.006 -0.031 -0.156  0.068 -0.031  0.018  0.018 -0.081 -0.056 -0.081  0.118 -0.056 -0.056 -0.081 -0.031 -0.156 -0.031  0.043 -0.031 -0.131  0.068 -0.006  0.068  0.093  0.218  0.193  0.168 -0.031  0.018 -0.106 -0.131 -0.006 -0.081  0.018  0.043 -0.081 -0.106 -0.081 -0.131 -0.056 -0.081  0.043 -0.056  0.118  0.143 -0.006  0.168 -0.031 -0.156 
 0.069  0.318  0.119  0.194  0.393  0.493  0.318  0.244  0.069  0.244  0.119  0.119  0.343 -0.005  0.094  0.094  0.019 -0.030 -0.105  0.293  0.019  0.219 -0.005  0.194  0.019  0.169  0.368  0.343  0.219  0.244  0.169  0.169  0.094  0.019  0.269  0.393  0.343 -0.080 -0.030  0.418  0.094  0.293  0.094  0.269 -0.105  0.393  0.667  0.318  0.568  0.368  0.044 -0.055 -0.030 -0.130  0.019 -0.055 -0.005  0.019 -0.055 -0.005 -0.080  0.144 -0.030 -0.055 -0.055 -0.005 -0.130 -0.005 -0.005 -0.055 -0.105  0.069 -0.030  0.044  0.069  0.194  0.169  0.169 -0.005 -0.005 -0.080 -0.130 -0.005 -0.030  0.019  0.069 -0.055 -0.080 -0.055 -0.130 -0.055 -0.080 -0.005 -0.030  0.119  0.169 -0.005  0.044 -0.005 -0.130 
 0.080  0.354  0.080  0.130  0.404  0.503  0.229  0.229  0.055  0.229  0.030  0.105  0.354 -0.020  0.105  0.080  0.055 -0.020 -0.120  0.279 -0.020  0.229  0.005  0.179  0.030  0.154  0.379  0.354  0.229  0.254  0.179  0.130  0.080  0.030  0.279  0.354  0.304 -0.070 -0.045  0.379  0.105  0.279  0.105  0.254 -0.095  0.379  0.653  0.304  0.578  0.329  0.055 -0.070 -0.020 -0.120  0.030 -0.045  0.005 -0.020 -0.045  0.005 -0.095  0.130 -0.020 -0.045 -0.045  0.005 -0.120  0.005  0.005 -0.045 -0.095  0.055 -0.045  0.030  0.055  0.179  0.154  0.154  0.005  0.005 -0.070 -0.120  0.005 -0.020  0.030  0.080 -0.045 -0.095 -0.070 -0.120 -0.045 -0.070  0.005 -0.020  0.130  0.130 -0.020  0.030  0.005 -0.120 
 0.070  0.344  0.045  0.095  0.344  0.494  0.245  0.195 -0.054  0.145 -0.004  0.095  0.394 -0.029  0.070 -0.004  0.020 -0.054 -0.104  0.220 -0.004  0.245  0.020  0.095  0.045  0.120  0.419  0.344  0.220  0.270  0.120  0.120  0.070 -0.004  0.245  0.344  0.270 -0.079 -0.029  0.369  0.045  0.245  0.070  0.245 -0.104  0.319  0.618  0.319  0.544  0.344  0.070 -0.079 -0.004 -0.104 -0.004 -0.054  0.020 -0.029 -0.029  0.020 -0.079  0.145 -0.029 -0.054 -0.004  0.020 -0.104  0.020  0.020 -0.054 -0.079  0.070 -0.054  0.045  0.045  0.170  0.145  0.120  0.020 -0.029 -0.054 -0.104  0.020 -0.004  0.020  0.070 -0.054 -0.104 -0.054 -0.104 -0.054 -0.054 -0.004 -0.004  0.145  0.145 -0.004 -0.004  0.020 -0.104 
 0.078  0.352  0.028  0.103  0.327  0.502  0.253  0.203 -0.046  0.153 -0.021  0.078  0.402 -0.071  0.078  0.003  0.028 -0.046 -0.096  0.203  0.003  0.253  0.028  0.103  0.028  0.128  0.427  0.327  0.178  0.278  0.128  0.103  0.078 -0.046  0.253  0.327  0.253 -0.071 -0.021  0.377  0.003  0.228  0.078  0.203 -0.096  0.278  0.626  0.253  0.502  0.352  0.078 -0.071  0.003 -0.096  0.003 -0.046  0.003 -0.021 -0.021  0.028 -0.071  0.128 -0.021 -0.071 -0.021  0.003 -0.096  0.003  0.028 -0.046 -0.071  0.053 -0.046  0.028  0.053  0.153  0.103  0.103  0.028 -0.021 -0.046 -0.096  0.028  0.003  0.028  0.053 -0.046 -0.096 -0.046 -0.096 -0.046 -0.046  0.003  0.003  0.128  0.128  0.003 -0.021  0.028 -0.096 
 0.067  0.267  0.042  0.092  0.341  0.491  0.242  0.167 -0.032  0.192 -0.007  0.092  0.341 -0.057  0.092 -0.007  0.017 -0.032 -0.082  0.142  0.017  0.267  0.042  0.017  0.042  0.117  0.416  0.341  0.167  0.291  0.067  0.092  0.067 -0.057  0.267  0.341  0.167 -0.057 -0.007  0.291 -0.007  0.192  0.117  0.192 -0.082  0.217  0.566  0.217  0.491  0.316  0.092 -0.057  0.017 -0.082 -0.032 -0.032 -0.032 -0.032 -0.032  0.017 -0.057  0.067 -0.007 -0.057 -0.057  0.017 -0.082 -0.007  0.017 -0.057 -0.057 -0.007 -0.007  0.042  0.042  0.067  0.042  0.067  0.042 -0.007 -0.032 -0.082  0.017 -0.007 -0.007  0.067 -0.032 -0.082 -0.057 -0.082 -0.032 -0.057  0.017  0.017  0.142  0.092 -0.032 -0.007  0.017 -0.082 
 0.048  0.248  0.048  0.098  0.297  0.497  0.248  0.173 -0.026  0.198 -0.026  0.098  0.297 -0.051  0.073 -0.001  0.023 -0.026 -0.076  0.148  0.023  0.273  0.048  0.023  0.048  0.098  0.372  0.372  0.148  0.273  0.073  0.073  0.073 -0.051  0.248  0.273  0.123 -0.051 -0.001  0.248 -0.001  0.198  0.123  0.198 -0.076  0.198  0.571  0.198  0.497  0.322  0.048 -0.051 -0.026 -0.076 -0.026 -0.026 -0.051 -0.026 -0.026  0.023 -0.051  0.073 -0.026 -0.051 -0.076 -0.001 -0.076 -0.001  0.023 -0.051 -0.051 -0.026 -0.001  0.023 -0.001 -0.001  0.023  0.023  0.023 -0.001 -0.026 -0.076  0.023 -0.001 -0.001  0.073 -0.026 -0.076 -0.051 -0.076 -0.051 -0.051  0.023  0.023  0.098  0.098 -0.026 -0.001  0.023 -0.076 
 0.038  0.187  0.063  0.113  0.212  0.486  0.237  0.187 -0.012  0.162 -0.012  0.113  0.237 -0.037  0.063  0.013 -0.012 -0.012 -0.062  0.088  0.038  0.262  0.038  0.013  0.038  0.113  0.287  0.337  0.138  0.237  0.063  0.038  0.038 -0.037  0.262  0.262  0.088 -0.012 -0.012  0.138  0.013  0.138  0.088  0.063 -0.062  0.138  0.611  0.162  0.486  0.287  0.038 -0.062 -0.012 -0.062 -0.037 -0.037 -0.037 -0.012 -0.037 -0.037 -0.037 -0.012 -0.012 -0.037 -0.062 -0.012 -0.062 -0.012 -0.012 -0.037 -0.037 -0.012 -0.062  0.013  0.013 -0.012  0.013  0.038  0.038 -0.012 -0.012 -0.062  0.038 -0.012 -0.037  0.063 -0.012 -0.062 -0.037 -0.062 -0.037 -0.062 -0.037  0.038  0.063  0.013 -0.012  0.013  0.013 -0.062 
 0.048  0.123  0.048  0.123  0.172  0.496  0.222  0.172 -0.002  0.123 -0.002  0.098  0.222 -0.027  0.048 -0.002 -0.002 -0.027 -0.052  0.048  0.048  0.222 -0.027  0.023  0.048  0.098  0.197  0.322  0.147  0.247  0.023  0.048  0.023 -0.027  0.272  0.222  0.098 -0.027 -0.002  0.098  0.023  0.098  0.098  0.048 -0.052  0.123  0.621  0.123  0.347  0.297  0.048 -0.052 -0.027 -0.052 -0.027 -0.027 -0.027 -0.002 -0.027 -0.027 -0.052 -0.002 -0.002 -0.027 -0.052  0.023 -0.052 -0.027 -0.027 -0.052 -0.027 -0.002 -0.052 -0.002 -0.002 -0.002  0.023  0.048  0.023 -0.002 -0.002 -0.052  0.023 -0.002 -0.052  0.023 -0.002 -0.052 -0.027 -0.027 -0.027 -0.052 -0.027  0.048  0.073  0.023 -0.027  0.023  0.023 -0.052 
 0.033  0.108  0.033  0.133  0.158  0.457  0.183  0.183  0.008  0.133 -0.016  0.108  0.158 -0.016  0.008  0.008  0.008 -0.016 -0.041  0.008  0.058  0.183 -0.016  0.008  0.058  0.008  0.133  0.233  0.158  0.208  0.033 -0.016  0.033 -0.016  0.258  0.208 -0.016 -0.016  0.008  0.033  0.033  0.058  0.033  0.058 -0.041  0.033  0.681  0.083  0.283  0.258  0.033 -0.041 -0.016 -0.041 -0.016 -0.016 -0.016 -0.016  0.008 -0.016 -0.041  0.008  0.008 -0.016 -0.041  0.033 -0.041 -0.041 -0.041 -0.041 -0.016 -0.016 -0.041  0.008  0.008  0.033 -0.016  0.058  0.058  0.008 -0.016 -0.016  0.033  0.008 -0.041  0.033  0.008 -0.041 -0.016 -0.016 -0.016 -0.041 -0.041  0.033  0.058  0.033 -0.016  0.033  0.033 -0.041 
 0.016  0.116  0.016  0.141  0.141  0.216  0.116  0.166 -0.008  0.091 -0.033  0.016  0.066  0.016  0.016  0.016  0.016 -0.008 -0.033  0.016  0.016  0.141 -0.008 -0.008  0.041  0.016  0.116  0.141  0.116  0.141  0.041 -0.008  0.016 -0.033  0.166  0.091 -0.008 -0.008  0.016  0.016  0.041  0.066  0.016  0.016 -0.033  0.041  0.789  0.066  0.241  0.216 -0.008 -0.033 -0.008 -0.033 -0.033 -0.008 -0.008  0.016  0.016 -0.008 -0.033 -0.008  0.016 -0.033 -0.033  0.016 -0.033 -0.033 -0.033 -0.033 -0.008 -0.008 -0.033 -0.008  0.016  0.016 -0.033  0.066  0.066  0.016 -0.008 -0.008  0.041 -0.008 -0.033  0.041  0.016 -0.033 -0.008 -0.008 -0.033 -0.033 -0.033 -0.008  0.066  0.041 -0.008  0.041  0.016 -0.033 
 0.003  0.053  0.053  0.078  0.053  0.028 -0.022  0.103  0.003  0.053 -0.022 -0.022  0.003  0.003  0.003  0.003  0.028  0.053 -0.022  0.003  0.003  0.028 -0.022 -0.022  0.028 -0.022  0.003 -0.022  0.028  0.053  0.003  0.003  0.053 -0.022  0.103  0.003 -0.022  0.003  0.028  0.028  0.003 -0.022 -0.022  0.003  0.003  0.028  0.999 -0.022  0.053  0.103 -0.022 -0.022  0.003 -0.022 -0.022 -0.022 -0.022  0.003  0.003 -0.022 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022 -0.022  0.003  0.003 -0.022 -0.022  0.028  0.003  0.003 -0.022  0.003  0.078  0.003  0.003  0.028  0.028  0.003 -0.022 -0.022  0.028 -0.022  0.003  0.003 -0.022 -0.022 -0.022  0.003  0.003 -0.022 -0.022  0.028  0.003 -0.022 
 0.003  0.053  0.053  0.053  0.053  0.003 -0.021  0.103  0.003  0.028 -0.021 -0.021 -0.021  0.003  0.003  0.003  0.028  0.053 -0.021  0.003 -0.021  0.028 -0.021 -0.021  0.028 -0.021  0.003 -0.021  0.028  0.053  0.003  0.003  0.053 -0.021  0.103  0.003 -0.021  0.003  0.028  0.028  0.003 -0.021 -0.021  0.003  0.003  0.028  1.000 -0.021  0.053  0.078 -0.021 -0.021  0.003 -0.021 -0.021 -0.021 -0.021  0.003  0.003 -0.021 -0.021 -0.021  0.003 -0.021 -0.021  0.003 -0.021 -0.021 -0.021  0.003  0.003 -0.021 -0.021  0.028  0.003  0.003 -0.021  0.003  0.078  0.003  0.003  0.028  0.028  0.003 -0.021 -0.021  0.028 -0.021  0.003  0.003 -0.021 -0.021 -0.021  0.003  0.003 -0.021 -0.021  0.028  0.003 -0.021 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004  0.079  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004  0.079  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004  0.079  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004  0.079  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004  0.079  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020 
 0.020  0.095  0.045  0.045  0.070 -0.029 -0.029  0.145 -0.004  0.020 -0.029 -0.029 -0.029 -0.004  0.020 -0.004  0.020  0.120 -0.004 -0.004 -0.004  0.070 -0.029 -0.029  0.020 -0.029  0.020 -0.004  0.020  0.070 -0.004 -0.004  0.070 -0.004  0.319 -0.004 -0.004 -0.004  0.120  0.070  0.045 -0.004 -0.029 -0.004  0.020  0.020  0.992 -0.029  0.120  0.070 -0.004 -0.029 -0.004 -0.029 -0.029 -0.004 -0.004 -0.004  0.020 -0.004 -0.004 -0.029  0.020 -0.029 -0.029  0.020 -0.029 -0.004 -0.029 -0.004 -0.004 -0.029 -0.029  0.045 -0.004 -0.004 -0.004  0.020  0.095  0.045 -0.004  0.020  0.020 -0.004 -0.029 -0.029  0.020 -0.029 -0.004 -0.004 -0.029 -0.004 -0.029 -0.004  0.020 -0.029 -0.029  0.095  0.020 -0.004 
-0.017  0.182  0.083  0.207  0.083 -0.017  0.008  0.232  0.033  0.033 -0.067 -0.017 -0.017  0.058 -0.017  0.058  0.008  0.382 -0.017 -0.017  0.008  0.232 -0.042 -0.067  0.058 -0.017  0.058  0.008  0.058  0.133  0.058  0.008  0.133 -0.017  0.681  0.058 -0.042 -0.017  0.157  0.083  0.282  0.058 -0.067 -0.017  0.058  0.008  0.955 -0.042  0.157  0.083 -0.017 -0.067 -0.042 -0.067 -0.017 -0.042 -0.042 -0.042  0.033  0.008 -0.042 -0.067  0.083 -0.042 -0.067 -0.017 -0.067 -0.042  0.008  0.008  0.008 -0.042 -0.067  0.033  0.033 -0.017  0.108  0.033  0.133  0.108 -0.017  0.033  0.033 -0.042  0.033  0.008  0.033 -0.017 -0.042 -0.017 -0.017  0.008 -0.042 -0.042 -0.017 -0.067 -0.042  0.157  0.033 -0.017 
 0.007  0.281  0.206  0.381  0.206  0.007  0.007  0.231  0.057  0.082 -0.068  0.007 -0.018  0.032 -0.018  0.032 -0.018  0.505 -0.043 -0.043 -0.018  0.306 -0.043 -0.043  0.032 -0.018  0.206 -0.018  0.181  0.132  0.132 -0.043  0.306  0.007  0.779  0.057 -0.043 -0.068  0.156  0.206  0.381  0.107 -0.068 -0.043  0.181  0.057  0.904  0.032  0.156  0.132  0.032 -0.118 -0.068 -0.093  0.057 -0.043 -0.043 -0.093 -0.018 -0.018 -0.093 -0.093  0.156 -0.043 -0.118 -0.068 -0.093 -0.043  0.007 -0.043  0.007 -0.093  0.007  0.082  0.082 -0.018  0.156  0.007  0.132  0.132 -0.043 -0.018 -0.018 -0.068  0.007  0.007  0.007 -0.018 -0.043 -0.068 -0.043 -0.018 -0.068 -0.068  0.007 -0.118 -0.018  0.107  0.007 -0.043 
-0.001  0.372  0.248  0.646  0.397  0.073  0.098  0.297  0.098  0.198 -0.051  0.098  0.098  0.123 -0.026  0.073 -0.076  0.696 -0.126 -0.101 -0.076  0.472  0.023 -0.076  0.023 -0.051  0.372  0.073  0.297  0.273  0.273  0.023  0.646  0.048  0.821  0.173 -0.001 -0.126  0.148  0.248  0.621  0.123  0.023 -0.051  0.248  0.098  0.821  0.048  0.248  0.273  0.023 -0.176 -0.051 -0.151  0.098 -0.001 -0.051 -0.126 -0.026 -0.051 -0.101 -0.126  0.273 -0.101 -0.126 -0.051 -0.176 -0.126 -0.001 -0.076 -0.051 -0.076  0.048  0.148  0.198  0.098  0.322  0.148  0.048  0.123 -0.126 -0.026 -0.051 -0.126 -0.001  0.023  0.023  0.023 -0.026 -0.151  0.023 -0.051 -0.051 -0.101  0.073 -0.076 -0.076  0.098  0.023 -0.051 
 0.036  0.434  0.260  0.609  0.459  0.136  0.136  0.385  0.136  0.185 -0.064  0.061  0.136  0.136 -0.039  0.086 -0.114  0.559 -0.114 -0.039  0.011  0.434  0.036  0.011  0.011 -0.014  0.559  0.235  0.260  0.235  0.310 -0.014  0.659  0.061  0.783  0.310  0.011 -0.139  0.111  0.335  0.609  0.136  0.061 -0.039  0.285  0.210  0.783  0.086  0.260  0.385  0.011 -0.163 -0.039 -0.188  0.160  0.111 -0.064 -0.139 -0.064 -0.039 -0.114 -0.139  0.235 -0.139 -0.139 -0.039 -0.188 -0.163  0.061 -0.114 -0.089 -0.089  0.061  0.210  0.210  0.061  0.434  0.160 -0.014  0.086 -0.163 -0.039 -0.064 -0.089 -0.014  0.011 -0.064  0.011 -0.089 -0.188  0.036 -0.139 -0.014 -0.139  0.061 -0.014 -0.064  0.036  0.011 -0.064 
 0.113  0.436  0.287  0.636  0.461  0.187  0.212  0.436  0.113  0.237 -0.012  0.088  0.312  0.138 -0.037  0.262 -0.161  0.436 -0.112  0.063  0.013  0.436  0.063  0.138 -0.012  0.038  0.611  0.312  0.312  0.237  0.387  0.038  0.636  0.063  0.661  0.387 -0.012 -0.186  0.162  0.387  0.611  0.312  0.237  0.088  0.287  0.412  0.735  0.187  0.412  0.461  0.013 -0.236 -0.062 -0.161  0.088  0.063 -0.037 -0.137 -0.112 -0.112 -0.087 -0.112  0.237 -0.137 -0.112 -0.087 -0.186 -0.211  0.088 -0.137 -0.112 -0.112  0.113  0.262  0.262  0.162  0.536  0.212 -0.087  0.138 -0.186 -0.112 -0.087 -0.137 -0.062 -0.012 -0.112 -0.012 -0.112 -0.236  0.013 -0.211  0.013 -0.161  0.063  0.013 -0.037  0.038 -0.087 -0.112 
 0.176  0.426  0.226  0.625  0.426  0.201  0.251  0.426  0.127  0.226  0.002  0.102  0.401  0.226 -0.073  0.351 -0.147  0.326 -0.123  0.251  0.002  0.426  0.027  0.201  0.002  0.102  0.625  0.326  0.326  0.176  0.376  0.102  0.625  0.052  0.650  0.401  0.052 -0.222  0.151  0.401  0.575  0.326  0.201  0.251  0.276  0.450  0.724  0.176  0.401  0.475  0.002 -0.197 -0.073 -0.172  0.127  0.077  0.002 -0.123 -0.123 -0.098 -0.073 -0.098  0.201 -0.123 -0.098 -0.098 -0.197 -0.222  0.077 -0.147 -0.147 -0.123  0.077  0.251  0.251  0.176  0.500  0.201 -0.098  0.127 -0.197 -0.098 -0.073 -0.123 -0.098  0.002 -0.098 -0.023 -0.098 -0.247 -0.023 -0.222  0.052 -0.172  0.052  0.027 -0.048  0.002 -0.123 -0.098 
 0.210  0.459  0.235  0.583  0.459  0.309  0.309  0.384  0.135  0.160  0.135  0.160  0.409  0.260 -0.039  0.459 -0.114  0.185 -0.164  0.359  0.010  0.334  0.010  0.359  0.010  0.135  0.583  0.384  0.384  0.160  0.359  0.110  0.608  0.110  0.633  0.409  0.185 -0.239  0.135  0.359  0.509  0.384  0.135  0.384  0.260  0.459  0.683  0.185  0.409  0.459 -0.039 -0.189 -0.089 -0.164  0.110  0.060 -0.014 -0.089 -0.114 -0.089 -0.014 -0.014  0.235 -0.139 -0.114 -0.089 -0.214 -0.189  0.060 -0.164 -0.164 -0.089  0.035  0.235  0.235  0.160  0.509  0.210 -0.114  0.110 -0.189 -0.089 -0.064 -0.139 -0.089  0.010 -0.139 -0.039 -0.114 -0.264 -0.014 -0.239  0.085 -0.164  0.010  0.135  0.035  0.010 -0.139 -0.089 
 0.235  0.459  0.235  0.559  0.509  0.309  0.309  0.334  0.135  0.160  0.135  0.160  0.459  0.260 -0.039  0.459 -0.114  0.185 -0.164  0.384 -0.014  0.309  0.010  0.384  0.010  0.135  0.583  0.384  0.384  0.160  0.359  0.085  0.608  0.110  0.608  0.384  0.210 -0.239  0.135  0.334  0.459  0.384  0.110  0.409  0.235  0.484  0.683  0.185  0.409  0.484 -0.039 -0.189 -0.089 -0.139  0.110  0.060  0.010 -0.089 -0.114 -0.064 -0.014  0.035  0.260 -0.089 -0.139 -0.089 -0.239 -0.189  0.035 -0.139 -0.164 -0.089  0.035  0.260  0.235  0.160  0.509  0.210 -0.114  0.110 -0.189 -0.089 -0.064 -0.114 -0.089  0.035 -0.139 -0.064 -0.114 -0.264  0.010 -0.214  0.110 -0.164 -0.014  0.135  0.060  0.060 -0.139 -0.089 
 0.255  0.454  0.230  0.504  0.504  0.354  0.304  0.304  0.155  0.155  0.105  0.205  0.504  0.205 -0.019  0.479 -0.094  0.180 -0.144  0.479 -0.044  0.255 -0.044  0.429  0.005  0.130  0.578  0.379  0.429  0.130  0.329  0.080  0.603  0.130  0.603  0.379  0.255 -0.244  0.130  0.329  0.354  0.379  0.080  0.404  0.205  0.504  0.678  0.205  0.404  0.479  0.005 -0.194 -0.069 -0.144  0.080  0.030  0.055 -0.044 -0.119 -0.069 -0.019  0.055  0.280 -0.069 -0.119 -0.069 -0.244 -0.144  0.055 -0.119 -0.169 -0.069 -0.019  0.255  0.230  0.180  0.479  0.205 -0.119  0.080 -0.219 -0.069 -0.069 -0.119 -0.044  0.080 -0.094 -0.069 -0.119 -0.244 -0.044 -0.194  0.155 -0.169  0.005  0.155  0.080  0.055 -0.144 -0.094 
 0.251  0.450  0.226  0.475  0.500  0.375  0.325  0.300  0.151  0.151  0.101  0.226  0.500  0.201  0.001  0.475 -0.098  0.176 -0.148  0.475 -0.048  0.251 -0.048  0.425  0.001  0.126  0.574  0.375  0.425  0.126  0.325  0.076  0.574  0.101  0.599  0.450  0.251 -0.223  0.126  0.325  0.350  0.375  0.076  0.525  0.201  0.500  0.674  0.201  0.425  0.475  0.001 -0.198 -0.073 -0.148  0.051  0.051  0.076 -0.048 -0.098 -0.073 -0.023  0.051  0.276 -0.073 -0.123 -0.048 -0.248 -0.148  0.051 -0.123 -0.173 -0.073  0.001  0.276  0.226  0.176  0.450  0.201 -0.098  0.076 -0.198 -0.073 -0.073 -0.123 -0.048  0.101 -0.098 -0.073 -0.123 -0.223 -0.048 -0.123  0.226 -0.198  0.026  0.151  0.076  0.051 -0.173 -0.023 
 0.273  0.398  0.223  0.472  0.497  0.398  0.323  0.273  0.173  0.148  0.124  0.223  0.497  0.173  0.074  0.472 -0.076  0.173 -0.150  0.472 -0.026  0.223 -0.001  0.522 -0.001  0.124  0.572  0.373  0.423  0.124  0.298  0.124  0.572  0.074  0.597  0.472  0.248 -0.225  0.148  0.373  0.298  0.373  0.049  0.547  0.198  0.497  0.672  0.198  0.447  0.497 -0.001 -0.175 -0.051 -0.175  0.049  0.049  0.074 -0.051 -0.101 -0.076 -0.026  0.049  0.273 -0.076 -0.126 -0.051 -0.250 -0.150  0.049 -0.101 -0.175 -0.076 -0.051  0.298  0.223  0.148  0.423  0.198 -0.101  0.074 -0.200 -0.026 -0.076 -0.126 -0.051  0.124 -0.101 -0.076 -0.126 -0.225 -0.051 -0.101  0.223 -0.200  0.049  0.148  0.099  0.074 -0.150 -0.026 
 0.298  0.373  0.223  0.472  0.497  0.398  0.323  0.273  0.198  0.148  0.124  0.223  0.497  0.173  0.099  0.472 -0.076  0.173 -0.126  0.497 -0.026  0.223 -0.001  0.547 -0.001  0.124  0.572  0.373  0.423  0.124  0.323  0.124  0.572  0.074  0.597  0.472  0.248 -0.225  0.148  0.398  0.273  0.373  0.049  0.547  0.198  0.497  0.672  0.198  0.423  0.497  0.024 -0.175 -0.051 -0.175  0.049  0.049  0.049 -0.051 -0.126 -0.076 -0.026  0.049  0.273 -0.076 -0.126 -0.051 -0.250 -0.150  0.049 -0.051 -0.200 -0.076 -0.051  0.323  0.223  0.124  0.447  0.198 -0.150  0.049 -0.200 -0.001 -0.076 -0.126 -0.051  0.124 -0.101 -0.076 -0.126 -0.225 -0.051 -0.101  0.198 -0.175  0.049  0.173  0.099  0.074 -0.150 -0.026 
 0.299  0.374  0.174  0.473  0.473  0.399  0.349  0.274  0.199  0.149  0.149  0.224  0.498  0.174  0.149  0.473 -0.050  0.174 -0.125  0.498 -0.025  0.224  0.000  0.548  0.000  0.125  0.573  0.399  0.424  0.100  0.324  0.125  0.573  0.075  0.573  0.523  0.274 -0.199  0.125  0.399  0.249  0.349  0.050  0.573  0.174  0.498  0.673  0.199  0.424  0.498  0.025 -0.174 -0.050 -0.174  0.050  0.050  0.050 -0.025 -0.125 -0.075 -0.050  0.050  0.274 -0.075 -0.125 -0.050 -0.249 -0.149  0.075 -0.050 -0.199 -0.075 -0.075  0.324  0.224  0.125  0.448  0.199 -0.149  0.050 -0.199  0.000 -0.075 -0.125 -0.050  0.174 -0.100 -0.075 -0.125 -0.224 -0.050 -0.100  0.199 -0.174  0.050  0.174  0.100  0.100 -0.149 -0.025 
 0.296  0.396  0.122  0.471  0.471  0.396  0.346  0.272  0.222  0.172  0.147  0.272  0.496  0.197  0.197  0.496 -0.027  0.172 -0.127  0.521 -0.027  0.222 -0.002  0.546 -0.002  0.122  0.570  0.396  0.471  0.097  0.321  0.122  0.570  0.072  0.570  0.521  0.272 -0.202  0.097  0.396  0.247  0.346  0.047  0.570  0.172  0.496  0.645  0.197  0.421  0.471  0.047 -0.177 -0.052 -0.177  0.072  0.047  0.047 -0.027 -0.127 -0.077 -0.052  0.047  0.272 -0.077 -0.127 -0.052 -0.252 -0.152  0.072 -0.077 -0.177 -0.077 -0.077  0.321  0.222  0.097  0.446  0.197 -0.152  0.072 -0.202 -0.002 -0.077 -0.127 -0.052  0.172 -0.102 -0.027 -0.102 -0.227 -0.052 -0.102  0.197 -0.177  0.047  0.197  0.097  0.097 -0.152 -0.027 
 0.297  0.397  0.098  0.471  0.446  0.397  0.347  0.272  0.247  0.172  0.147  0.272  0.496  0.197  0.222  0.496 -0.002  0.147 -0.127  0.521 -0.027  0.222 -0.002  0.571 -0.027  0.147  0.571  0.397  0.471  0.123  0.322  0.123  0.571  0.098  0.571  0.521  0.272 -0.201  0.073  0.397  0.222  0.347  0.048  0.571  0.172  0.496  0.646  0.197  0.446  0.446  0.048 -0.176 -0.052 -0.176  0.098  0.023  0.073 -0.027 -0.127 -0.077 -0.052  0.048  0.272 -0.077 -0.151 -0.052 -0.251 -0.127  0.073 -0.102 -0.176 -0.077 -0.077  0.322  0.172  0.098  0.446  0.197 -0.127  0.073 -0.201 -0.002 -0.077 -0.127 -0.052  0.222 -0.102 -0.027 -0.102 -0.226 -0.052 -0.102  0.222 -0.176  0.023  0.172  0.098  0.073 -0.151 -0.027 
 0.297  0.422  0.073  0.471  0.471  0.397  0.347  0.272  0.272  0.172  0.172  0.272  0.471  0.222  0.222  0.496 -0.002  0.147 -0.127  0.521 -0.027  0.222 -0.002  0.596 -0.002  0.147  0.571  0.397  0.446  0.098  0.322  0.123  0.571  0.123  0.571  0.546  0.272 -0.201  0.073  0.397  0.222  0.347  0.023  0.571  0.172  0.496  0.621  0.197  0.446  0.446  0.048 -0.176 -0.027 -0.176  0.098  0.023  0.073 -0.027 -0.151 -0.077 -0.052  0.048  0.272 -0.077 -0.151 -0.052 -0.251 -0.127  0.098 -0.102 -0.176 -0.077 -0.077  0.322  0.197  0.098  0.446  0.197 -0.127  0.073 -0.201 -0.052 -0.077 -0.127 -0.052  0.222 -0.102  0.023 -0.052 -0.226 -0.052 -0.102  0.222 -0.176  0.023  0.197  0.098  0.073 -0.151 -0.027 
 0.343  0.418  0.069  0.468  0.468  0.393  0.343  0.244  0.269  0.169  0.219  0.269  0.468  0.219  0.244  0.493  0.019  0.144 -0.130  0.518 -0.030  0.219  0.044  0.592 -0.005  0.194  0.568  0.393  0.468  0.094  0.293  0.119  0.592  0.194  0.568  0.568  0.269 -0.205  0.069  0.393  0.219  0.343  0.019  0.592  0.119  0.493  0.617  0.194  0.443  0.418  0.094 -0.180 -0.030 -0.205  0.094  0.019  0.069 -0.030 -0.155 -0.080 -0.080  0.044  0.269 -0.080 -0.155 -0.055 -0.255 -0.130  0.094 -0.130 -0.155 -0.105 -0.080  0.318  0.169  0.094  0.443  0.169 -0.130  0.094 -0.180 -0.055 -0.080 -0.130 -0.055  0.219 -0.055  0.019 -0.055 -0.230 -0.055 -0.105  0.219 -0.180  0.019  0.194  0.094  0.044 -0.155 -0.030 
 0.366  0.391  0.067  0.466  0.466  0.391  0.341  0.242  0.267  0.192  0.267  0.267  0.466  0.217  0.242  0.491  0.017  0.142 -0.132  0.516 -0.032  0.217  0.042  0.590 -0.007  0.242  0.566  0.391  0.466  0.092  0.291  0.142  0.566  0.192  0.566  0.566  0.291 -0.207  0.017  0.416  0.192  0.341  0.017  0.615  0.092  0.491  0.615  0.192  0.441  0.416  0.117 -0.157 -0.032 -0.207  0.092  0.017  0.067 -0.032 -0.157 -0.082 -0.082  0.042  0.242 -0.082 -0.157 -0.057 -0.257 -0.132  0.092 -0.132 -0.157 -0.107 -0.082  0.316  0.167  0.092  0.416  0.167 -0.132  0.092 -0.182 -0.057 -0.057 -0.132 -0.057  0.217 -0.057  0.017 -0.057 -0.232 -0.057 -0.107  0.217 -0.182  0.017  0.217  0.092  0.042 -0.157 -0.032 
 0.367  0.392  0.043  0.442  0.442  0.392  0.392  0.243  0.292  0.193  0.292  0.268  0.492  0.218  0.292  0.492  0.018  0.143 -0.131  0.492 -0.006  0.218  0.068  0.591 -0.031  0.243  0.567  0.392  0.467  0.093  0.292  0.168  0.542  0.218  0.567  0.567  0.292 -0.206  0.018  0.417  0.193  0.342  0.018  0.616  0.068  0.442  0.616  0.193  0.442  0.417  0.118 -0.156 -0.031 -0.206  0.093  0.018  0.068 -0.031 -0.156 -0.081 -0.106  0.043  0.243 -0.056 -0.156 -0.056 -0.256 -0.131  0.093 -0.106 -0.156 -0.106 -0.081  0.317  0.118  0.093  0.417  0.168 -0.131  0.043 -0.181 -0.056 -0.056 -0.131 -0.056  0.218 -0.056  0.018 -0.056 -0.231 -0.056 -0.106  0.218 -0.181  0.018  0.218  0.093  0.043 -0.156 -0.031 
 0.369  0.369  0.045  0.419  0.469  0.369  0.294  0.220  0.195  0.170  0.270  0.195  0.444  0.070  0.170  0.369 -0.054  0.145 -0.154  0.494 -0.029  0.220  0.045  0.519 -0.029  0.170  0.593  0.419  0.270  0.095  0.319  0.195  0.444  0.020  0.568  0.519  0.245 -0.229 -0.004  0.419  0.195  0.344  0.045  0.568  0.045  0.344  0.568  0.195  0.494  0.344  0.120 -0.104 -0.029 -0.179  0.120  0.045  0.095 -0.029 -0.104 -0.004 -0.104  0.045  0.245 -0.079 -0.154 -0.004 -0.204 -0.129  0.170 -0.129 -0.154 -0.054 -0.079  0.270  0.170  0.120  0.394  0.120 -0.104 -0.004 -0.154 -0.104  0.020 -0.079 -0.054  0.095 -0.029  0.070 -0.079 -0.204 -0.029 -0.129  0.145 -0.129  0.070  0.145  0.170 -0.004 -0.154 -0.054 
 0.210  0.334  0.035  0.359  0.484  0.359  0.334  0.235  0.160  0.210  0.185  0.135  0.359  0.010  0.010  0.260 -0.064  0.035 -0.114  0.484  0.010  0.210  0.010  0.434  0.035  0.160  0.509  0.409  0.260  0.185  0.334  0.160  0.260  0.035  0.534  0.434  0.260 -0.139  0.010  0.309  0.135  0.409  0.060  0.434 -0.039  0.309  0.583  0.160  0.384  0.260  0.110 -0.089 -0.114 -0.139  0.110 -0.014  0.110 -0.039 -0.089  0.035 -0.089  0.085  0.110 -0.014 -0.089  0.035 -0.114 -0.039  0.160 -0.164 -0.114 -0.014 -0.064  0.235  0.135  0.135  0.309  0.085 -0.039  0.035 -0.114 -0.089  0.035 -0.089  0.035  0.060 -0.064 -0.014 -0.089 -0.114 -0.064 -0.064  0.160 -0.114  0.085  0.110  0.085  0.060 -0.064 -0.139 
 0.177  0.351  0.052  0.376  0.476  0.376  0.326  0.202  0.102  0.177  0.177  0.152  0.301  0.002  0.002  0.252 -0.047  0.052 -0.122  0.451 -0.022  0.227  0.002  0.426  0.052  0.177  0.476  0.376  0.202  0.202  0.351  0.152  0.252  0.002  0.401  0.451  0.227 -0.122  0.027  0.301  0.127  0.426  0.027  0.376 -0.047  0.252  0.600  0.177  0.351  0.252  0.127 -0.072 -0.097 -0.147  0.077 -0.047  0.127 -0.072 -0.072  0.052 -0.072  0.102  0.077  0.002 -0.072  0.027 -0.097 -0.047  0.052 -0.147 -0.122  0.002 -0.047  0.252  0.102  0.127  0.326  0.077 -0.022  0.052 -0.097 -0.072  0.027 -0.072  0.052  0.077 -0.072 -0.047 -0.072 -0.097 -0.072 -0.072  0.152 -0.097  0.102  0.102  0.102  0.077 -0.047 -0.122 
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 0.069  0.019 -0.105 -0.080  0.094 -0.055 -0.105 -0.105 -0.030 -0.030 -0.030 -0.080 -0.080  0.069  0.019 -0.080  0.019 -0.030  0.094 -0.130 -0.155  0.119 -0.105 -0.105  0.044 -0.055 -0.030 -0.030  0.119 -0.005  0.044 -0.130 -0.155 -0.155  0.069  0.019 -0.055 -0.080 -0.080 -0.155 -0.005 -0.055 -0.055  0.019 -0.030 -0.055 -0.130 -0.005 -0.055 -0.030 -0.130 -0.005  0.094 -0.030 -0.055 -0.080 -0.005 -0.080 -0.105 -0.105 -0.080 -0.055 -0.080 -0.055 -0.105  0.044  0.019 -0.005 -0.105  0.019 -0.080 -0.030 -0.005  0.094 -0.080 -0.055 -0.080 -0.155 -0.005  0.194 -0.155  0.219  0.019  0.069 -0.105 -0.080 -0.005 -0.005  0.019 -0.105 -0.030 -0.055 -0.080  0.044 -0.055 -0.055  0.094 -0.130 -0.030  0.044 
 0.086  0.036 -0.113 -0.063  0.086 -0.038 -0.088 -0.113 -0.013 -0.038 -0.013 -0.063 -0.088  0.036 -0.013 -0.063 -0.013 -0.038  0.086 -0.113 -0.138  0.111 -0.113 -0.088  0.011 -0.038  0.011 -0.013  0.136  0.011  0.011 -0.113 -0.138 -0.138  0.061 -0.013 -0.038 -0.063 -0.088 -0.138 -0.063 -0.013 -0.038  0.036 -0.013 -0.063 -0.138  0.011 -0.063 -0.063 -0.113 -0.038  0.136 -0.013 -0.038 -0.063 -0.013 -0.063 -0.088 -0.113 -0.063 -0.013 -0.063 -0.038 -0.088  0.011  0.011  0.011 -0.088 -0.013 -0.063 -0.013  0.011  0.086 -0.063 -0.063 -0.063 -0.138  0.011  0.186 -0.138  0.236  0.011  0.061 -0.088 -0.088  0.011  0.011  0.036 -0.113 -0.013 -0.038 -0.088  0.036 -0.038 -0.038  0.061 -0.113 -0.038  0.011 
 0.087  0.062 -0.087 -0.062  0.087  0.012 -0.062 -0.087 -0.012 -0.037 -0.012 -0.037 -0.062  0.012 -0.062 -0.037 -0.037 -0.012  0.087 -0.087 -0.112  0.162 -0.112 -0.087  0.012 -0.012  0.062  0.062  0.087  0.062  0.012 -0.087 -0.112 -0.112  0.062 -0.012 -0.037 -0.112 -0.087 -0.112 -0.112 -0.012 -0.012 -0.037 -0.012 -0.062 -0.112  0.037 -0.012 -0.062 -0.087 -0.037  0.187 -0.012 -0.012 -0.037 -0.012 -0.062 -0.062 -0.087 -0.062 -0.012 -0.037 -0.037 -0.087  0.012  0.037  0.037 -0.062  0.012 -0.062 -0.012  0.037 -0.012 -0.062 -0.037 -0.037 -0.112 -0.087  0.137 -0.112  0.262  0.012  0.037 -0.112 -0.062  0.012  0.037  0.037 -0.087  0.012 -0.037 -0.062  0.037 -0.037 -0.062  0.037 -0.087 -0.012 -0.012 
 0.118  0.068 -0.081 -0.056  0.118  0.018 -0.056 -0.081 -0.006 -0.031 -0.006 -0.031 -0.031  0.018 -0.081 -0.056 -0.031 -0.031  0.093 -0.081 -0.106  0.168 -0.106 -0.081  0.018 -0.006  0.043  0.068  0.093  0.068 -0.031 -0.081 -0.106 -0.106  0.068 -0.006 -0.056 -0.106 -0.081 -0.106 -0.106 -0.031 -0.006 -0.031 -0.006 -0.056 -0.106  0.018 -0.006 -0.056 -0.081 -0.031  0.168 -0.056 -0.031 -0.031 -0.031 -0.056 -0.056 -0.081 -0.056 -0.006 -0.031 -0.056 -0.081 -0.006  0.043  0.043 -0.056 -0.031 -0.056  0.018  0.043 -0.006 -0.056 -0.031 -0.031 -0.081 -0.081  0.118 -0.106  0.268  0.018  0.043 -0.106 -0.056  0.018  0.018  0.018 -0.081 -0.031 -0.031 -0.056  0.018 -0.031 -0.056  0.043 -0.081 -0.006 -0.006 
 0.132  0.057 -0.067 -0.042  0.107  0.032 -0.042 -0.067 -0.017 -0.017 -0.017 -0.017 -0.017  0.007 -0.067 -0.042 -0.017 -0.042  0.057 -0.067 -0.092  0.157 -0.092 -0.067  0.032  0.007  0.057  0.082  0.032  0.057 -0.042 -0.067 -0.092 -0.092  0.032 -0.017 -0.067 -0.092 -0.067 -0.092 -0.092 -0.017  0.007 -0.017 -0.042 -0.042 -0.092  0.032  0.007 -0.042 -0.067 -0.042  0.157 -0.067 -0.017 -0.017 -0.067 -0.067 -0.042 -0.092 -0.042  0.007 -0.017 -0.067 -0.067  0.032  0.057  0.032 -0.042 -0.042 -0.042  0.032  0.057 -0.017 -0.067 -0.042 -0.017 -0.067 -0.067  0.107 -0.092  0.232  0.007  0.057 -0.092 -0.042  0.007  0.032  0.007 -0.067 -0.017 -0.042 -0.067  0.032 -0.017 -0.067  0.057 -0.067  0.007 -0.017 
 0.136  0.061 -0.064 -0.039  0.111  0.036 -0.039 -0.039 -0.064 -0.014 -0.014 -0.014 -0.014 -0.014 -0.064 -0.039 -0.014 -0.039  0.061 -0.064 -0.089  0.160 -0.089 -0.064  0.061  0.036  0.086  0.061  0.036  0.061 -0.039 -0.064 -0.089 -0.089  0.011 -0.014 -0.064 -0.089 -0.064 -0.089 -0.089 -0.014  0.011 -0.014 -0.039 -0.064 -0.089  0.036  0.011 -0.039 -0.064 -0.064  0.136 -0.064 -0.014 -0.039 -0.064 -0.064 -0.039 -0.089 -0.039 -0.014 -0.014 -0.039 -0.064  0.036  0.061  0.036 -0.039 -0.039 -0.039  0.036  0.061 -0.039 -0.064 -0.064 -0.014 -0.064 -0.064  0.061 -0.089  0.235  0.011  0.061 -0.089 -0.039  0.011  0.036 -0.014 -0.064 -0.014 -0.039 -0.064 -0.014 -0.014 -0.064  0.036 -0.039  0.011 -0.039 
 0.142  0.017 -0.057 -0.057  0.117  0.042 -0.032 -0.032 -0.082 -0.007 -0.057 -0.007  0.017 -0.032 -0.082 -0.032 -0.032 -0.032  0.067 -0.057 -0.082  0.192 -0.082 -0.057  0.042  0.017  0.042  0.042  0.042  0.042 -0.032 -0.057 -0.082 -0.082 -0.007 -0.007 -0.082 -0.082 -0.057 -0.082 -0.082 -0.007 -0.007 -0.007 -0.032 -0.057 -0.082  0.042 -0.007 -0.032 -0.057 -0.057  0.117 -0.057 -0.007 -0.032 -0.057 -0.057 -0.057 -0.082 -0.007 -0.032 -0.032 -0.032 -0.057  0.042  0.042  0.042 -0.032 -0.032 -0.032  0.042  0.067 -0.032 -0.057 -0.032 -0.007 -0.057 -0.057  0.067 -0.082  0.167  0.017  0.067 -0.057 -0.032 -0.032  0.067 -0.007 -0.057 -0.007 -0.032 -0.057 -0.007 -0.032 -0.057  0.042 -0.057  0.017 -0.032 
 0.148  0.024 -0.051 -0.051  0.124  0.049 -0.026 -0.026 -0.076 -0.026 -0.051 -0.001  0.024 -0.026 -0.076 -0.026 -0.026 -0.026  0.049 -0.076 -0.076  0.173 -0.076 -0.051  0.049  0.024  0.049  0.049  0.049  0.049 -0.051 -0.026 -0.076 -0.076 -0.001 -0.026 -0.076 -0.076 -0.051 -0.076 -0.076 -0.001 -0.051 -0.026 -0.051 -0.051 -0.076  0.024 -0.001 -0.026 -0.051 -0.051  0.024 -0.076 -0.026 -0.026 -0.051 -0.051 -0.051 -0.076 -0.001 -0.051 -0.026 -0.026 -0.051  0.049  0.024  0.049 -0.026 -0.026 -0.051  0.049  0.024 -0.051 -0.076 -0.026 -0.026 -0.051 -0.026  0.024 -0.076  0.074  0.024  0.074 -0.051 -0.026 -0.026  0.049 -0.001 -0.051 -0.001 -0.001 -0.051 -0.001 -0.026 -0.051  0.024 -0.051  0.024 -0.026 
 0.111  0.036 -0.064 -0.039  0.111  0.061  0.011 -0.039 -0.064  0.011 -0.064  0.011  0.036  0.011 -0.064 -0.039 -0.014 -0.014 -0.039 -0.064 -0.064  0.160 -0.064 -0.039  0.061  0.011  0.011  0.036  0.036  0.011 -0.039 -0.014 -0.064 -0.064 -0.014 -0.014 -0.039 -0.064 -0.064 -0.064 -0.064  0.011 -0.039 -0.014 -0.039 -0.039 -0.064  0.011  0.011 -0.039 -0.039 -0.064  0.011 -0.064 -0.014 -0.014 -0.039 -0.039 -0.064 -0.064  0.011 -0.039 -0.014 -0.014 -0.039  0.011 -0.014  0.061 -0.039 -0.039 -0.039  0.061  0.011 -0.039 -0.064 -0.014 -0.039 -0.039 -0.014  0.011 -0.064  0.086  0.011  0.036 -0.039 -0.014 -0.039 -0.014  0.011 -0.039 -0.014  0.011 -0.064  0.011 -0.014 -0.064  0.036 -0.064 -0.014 -0.014 
 0.095  0.045 -0.055 -0.030  0.095  0.020  0.020 -0.030 -0.055 -0.005 -0.055  0.020  0.045  0.020 -0.055 -0.030 -0.005 -0.005 -0.030 -0.055 -0.055  0.095 -0.055 -0.030  0.070  0.020  0.020  0.045  0.045 -0.005 -0.030 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.055 -0.055 -0.030 -0.055 -0.005 -0.055 -0.005 -0.030 -0.030 -0.055 -0.005  0.020 -0.030 -0.030 -0.055 -0.005 -0.055 -0.005 -0.005 -0.030 -0.030 -0.055 -0.055  0.020 -0.030 -0.030 -0.005 -0.030  0.020 -0.005  0.045 -0.055 -0.030 -0.030  0.070  0.020 -0.030 -0.055 -0.005 -0.030 -0.030 -0.005 -0.005 -0.055  0.070 -0.005  0.020 -0.030 -0.005 -0.030 -0.030  0.020 -0.030 -0.005  0.020 -0.030  0.020 -0.005 -0.055  0.045 -0.055 -0.030 -0.005 
 0.078  0.053 -0.047 -0.022  0.103  0.028  0.028 -0.022 -0.047  0.003 -0.022  0.028  0.053  0.003 -0.022 -0.022 -0.022  0.003 -0.047 -0.022 -0.047  0.103 -0.047 -0.022  0.078 -0.022  0.028  0.003  0.028 -0.022 -0.022  0.003 -0.047 -0.047  0.003 -0.022 -0.022 -0.047 -0.047 -0.022 -0.047  0.003 -0.047  0.003 -0.022 -0.022 -0.047  0.003  0.028 -0.022  0.003 -0.047  0.003 -0.047 -0.022 -0.022 -0.022 -0.022 -0.047 -0.047 -0.022 -0.022 -0.022  0.028 -0.022  0.003 -0.022  0.028 -0.047 -0.022 -0.022  0.028  0.028  0.003 -0.047 -0.022 -0.022 -0.022 -0.022 -0.022 -0.047  0.053 -0.022  0.028 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.028 -0.022  0.028  0.003 -0.047  0.003 -0.047 -0.022  0.003 
 0.081  0.056 -0.044 -0.019  0.081  0.031  0.031 -0.019 -0.044  0.006 -0.019  0.031  0.056  0.006 -0.019 -0.019 -0.019  0.006 -0.044 -0.019 -0.044  0.106 -0.044 -0.019  0.081 -0.019  0.031 -0.019  0.031 -0.019 -0.044  0.006 -0.044 -0.044  0.006 -0.019 -0.019 -0.044 -0.044 -0.019 -0.044  0.006 -0.044 -0.019 -0.019 -0.044 -0.044  0.006  0.031 -0.019  0.006 -0.044  0.006 -0.044 -0.019 -0.019 -0.019 -0.019 -0.044 -0.044 -0.019 -0.019 -0.019  0.031 -0.019  0.006 -0.019  0.031 -0.044 -0.019 -0.044  0.006  0.031  0.006 -0.044 -0.019 -0.019 -0.019 -0.019 -0.019 -0.044  0.056 -0.019  0.031 -0.019  0.006 -0.019 -0.019  0.006 -0.019 -0.019  0.031 -0.019  0.031  0.006 -0.044  0.006 -0.044 -0.044  0.006 
 0.059  0.059 -0.041 -0.016  0.084  0.009  0.034 -0.016 -0.041  0.009 -0.016  0.034  0.059  0.009 -0.016 -0.016 -0.016 -0.016 -0.041 -0.016 -0.041  0.109 -0.041 -0.016  0.059 -0.016  0.034 -0.016  0.034 -0.016 -0.041  0.034 -0.041 -0.041  0.009 -0.041 -0.016 -0.041 -0.041  0.009 -0.041  0.009 -0.041 -0.016 -0.016 -0.041 -0.041  0.009  0.034 -0.016  0.009 -0.041  0.009 -0.041 -0.016 -0.016 -0.016 -0.016 -0.041 -0.041 -0.016 -0.016 -0.016  0.009 -0.016  0.009 -0.016  0.034 -0.041 -0.016 -0.041  0.009  0.034  0.009 -0.041 -0.016 -0.016 -0.041 -0.016 -0.016 -0.041  0.059 -0.016  0.034 -0.016  0.009 -0.016 -0.016  0.009 -0.016 -0.016  0.034 -0.016  0.034  0.009 -0.041  0.009 -0.041 -0.041  0.009 
 0.059  0.059 -0.040 -0.015  0.084  0.009  0.034 -0.015 -0.040  0.009 -0.015  0.034  0.059  0.009 -0.015 -0.015 -0.015 -0.015 -0.040 -0.015 -0.040  0.109 -0.040 -0.015  0.059 -0.015  0.034 -0.015  0.034 -0.015 -0.040  0.034 -0.040 -0.040  0.009 -0.040 -0.015 -0.040 -0.040  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.040 -0.040  0.009  0.034 -0.015  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.015 -0.015 -0.040 -0.040 -0.015 -0.015 -0.015  0.009 -0.015  0.009 -0.015  0.034 -0.040 -0.015 -0.040 -0.015  0.034  0.009 -0.040 -0.015 -0.015 -0.040 -0.015 -0.015 -0.040  0.059 -0.015  0.034 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015  0.034 -0.015  0.034  0.009 -0.040  0.009 -0.040 -0.040  0.009 
 0.059  0.059 -0.040 -0.015  0.084  0.009  0.034 -0.015 -0.040  0.009 -0.015  0.034  0.059  0.009 -0.015 -0.015 -0.015 -0.015 -0.040 -0.015 -0.040  0.109 -0.040 -0.015  0.059 -0.015  0.034 -0.015  0.034 -0.015 -0.040  0.034 -0.040 -0.040  0.009 -0.040 -0.015 -0.040 -0.040  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.040 -0.040  0.009  0.034 -0.015  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.015 -0.015 -0.040 -0.040 -0.015 -0.015 -0.015  0.009 -0.015  0.009 -0.015  0.034 -0.040 -0.015 -0.040 -0.015  0.034  0.009 -0.040 -0.015 -0.015 -0.040 -0.015 -0.015 -0.040  0.059 -0.015  0.034 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015  0.034 -0.015  0.034  0.009 -0.040  0.009 -0.040 -0.040  0.009 
 0.059  0.059 -0.040 -0.015  0.084  0.009  0.034 -0.015 -0.040  0.009 -0.015  0.034  0.059  0.009 -0.015 -0.015 -0.015 -0.015 -0.040 -0.015 -0.040  0.109 -0.040 -0.015  0.059 -0.015  0.034 -0.015  0.034 -0.015 -0.040  0.034 -0.040 -0.040  0.009 -0.040 -0.015 -0.040 -0.040  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.040 -0.040  0.009  0.034 -0.015  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.015 -0.015 -0.040 -0.040 -0.015 -0.015 -0.015  0.009 -0.015  0.009 -0.015  0.034 -0.040 -0.015 -0.040 -0.015  0.034  0.009 -0.040 -0.015 -0.015 -0.040 -0.015 -0.015 -0.040  0.059 -0.015  0.034 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015  0.034 -0.015  0.034  0.009 -0.040  0.009 -0.040 -0.040  0.009 
 0.059  0.059 -0.040 -0.015  0.084  0.009  0.034 -0.015 -0.040  0.009 -0.015  0.034  0.059  0.009 -0.015 -0.015 -0.015 -0.015 -0.040 -0.015 -0.040  0.109 -0.040 -0.015  0.059 -0.015  0.034 -0.015  0.034 -0.015 -0.040  0.034 -0.040 -0.040  0.009 -0.040 -0.015 -0.040 -0.040  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.040 -0.040  0.009  0.034 -0.015  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.015 -0.015 -0.040 -0.040 -0.015 -0.015 -0.015  0.009 -0.015  0.009 -0.015  0.034 -0.040 -0.015 -0.040 -0.015  0.034  0.009 -0.040 -0.015 -0.015 -0.040 -0.015 -0.015 -0.040  0.059 -0.015  0.034 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015  0.034 -0.015  0.034  0.009 -0.040  0.009 -0.040 -0.040  0.009 
 0.059  0.059 -0.040 -0.015  0.084  0.009  0.034 -0.015 -0.040  0.009 -0.015  0.034  0.059  0.009 -0.015 -0.015 -0.015 -0.015 -0.040 -0.015 -0.040  0.109 -0.040 -0.015  0.059 -0.015  0.034 -0.015  0.034 -0.015 -0.040  0.034 -0.040 -0.040  0.009 -0.040 -0.015 -0.040 -0.040  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.040 -0.040  0.009  0.034 -0.015  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.015 -0.015 -0.040 -0.040 -0.015 -0.015 -0.015  0.009 -0.015  0.009 -0.015  0.034 -0.040 -0.015 -0.040 -0.015  0.034  0.009 -0.040 -0.015 -0.015 -0.040 -0.015 -0.015 -0.040  0.059 -0.015  0.034 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015  0.034 -0.015  0.034  0.009 -0.040  0.009 -0.040 -0.040  0.009 
 0.059  0.059 -0.040 -0.015  0.084  0.009  0.034 -0.015 -0.040  0.009 -0.015  0.034  0.059  0.009 -0.015 -0.015 -0.015 -0.015 -0.040 -0.015 -0.040  0.109 -0.040 -0.015  0.059 -0.015  0.034 -0.015  0.034 -0.015 -0.040  0.034 -0.040 -0.040  0.009 -0.040 -0.015 -0.040 -0.040  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.040 -0.040  0.009  0.034 -0.015  0.009 -0.040  0.009 -0.040 -0.015 -0.015 -0.015 -0.015 -0.040 -0.040 -0.015 -0.015 -0.015  0.009 -0.015  0.009 -0.015  0.034 -0.040 -0.015 -0.040 -0.015  0.034  0.009 -0.040 -0.015 -0.015 -0.040 -0.015 -0.015 -0.040  0.059 -0.015  0.034 -0.015  0.009 -0.015 -0.015  0.009 -0.015 -0.015  0.034 -0.015  0.034  0.009 -0.040  0.009 -0.040 -0.040  0.009 
 0.049  0.049 -0.075 -0.025  0.099  0.024  0.049 -0.025 -0.075 -0.025 -0.025  0.049  0.024 -0.025 -0.050 -0.050 -0.050  0.024 -0.050 -0.050 -0.075  0.174 -0.075 -0.025  0.024 -0.025 -0.000 -0.000  0.049 -0.025 -0.025  0.024 -0.075 -0.050 -0.025 -0.025 -0.025 -0.000 -0.025 -0.025 -0.075  0.024 -0.050 -0.025 -0.050 -0.050 -0.075  0.024 -0.000 -0.025 -0.025 -0.075  0.099 -0.075 -0.050 -0.050 -0.050 -0.025 -0.075 -0.075 -0.050  0.024 -0.000  0.024 -0.050  0.049  0.099 -0.000 -0.025 -0.000 -0.075 -0.000 -0.000 -0.000 -0.000 -0.025 -0.025 -0.050 -0.025  0.074 -0.075  0.124 -0.000  0.124 -0.000 -0.025 -0.025  0.024  0.024 -0.000 -0.025  0.049 -0.050  0.024 -0.025 -0.075 -0.025 -0.025 -0.025 -0.025 
 0.138  0.038 -0.136 -0.036  0.088 -0.011 -0.011 -0.061 -0.136 -0.036 -0.011  0.063  0.013  0.013 -0.086 -0.061  0.013  0.113 -0.011 -0.061 -0.111  0.238 -0.086 -0.036  0.013  0.013 -0.011 -0.011  0.063 -0.036 -0.061  0.038 -0.136 -0.111 -0.086 -0.011  0.063 -0.061 -0.086 -0.061 -0.061  0.013 -0.011 -0.011 -0.111 -0.036 -0.111  0.088 -0.061 -0.061 -0.061 -0.061  0.113 -0.061 -0.036 -0.061 -0.111 -0.061 -0.111 -0.136 -0.061  0.088  0.013 -0.036 -0.111  0.113  0.163 -0.036 -0.036  0.038  0.038  0.013 -0.036  0.038 -0.011 -0.086 -0.011 -0.061  0.013  0.088 -0.136  0.263  0.038  0.163 -0.036 -0.061  0.013 -0.036  0.013 -0.036 -0.061  0.013 -0.036 -0.036 -0.086 -0.111 -0.011 -0.036 -0.011 -0.086 
 0.143  0.043 -0.181 -0.081  0.118 -0.031 -0.056 -0.081 -0.131 -0.081 -0.006  0.018  0.018 -0.006 -0.156 -0.106 -0.006  0.093  0.043 -0.081 -0.156  0.218 -0.106 -0.081  0.043  0.018  0.068 -0.056  0.093 -0.031 -0.106 -0.031 -0.181 -0.131 -0.006 -0.056  0.118 -0.106 -0.106 -0.106 -0.006 -0.031 -0.056 -0.006 -0.131 -0.056 -0.106  0.118 -0.056 -0.106 -0.106 -0.031  0.068 -0.081 -0.081 -0.056 -0.031 -0.006 -0.131 -0.156 -0.056  0.068 -0.056 -0.081 -0.081  0.093  0.143 -0.031 -0.056  0.018  0.093  0.018 -0.006  0.068 -0.031 -0.081  0.018 -0.106 -0.006  0.068 -0.181  0.317  0.118  0.168 -0.081 -0.106 -0.031 -0.031  0.018 -0.081 -0.056  0.043 -0.081 -0.081 -0.081 -0.156  0.068  0.018 -0.006 -0.131 
 0.153 -0.021 -0.196 -0.121  0.153 -0.071 -0.071 -0.071 -0.121 -0.121 -0.046 -0.071  0.003  0.003 -0.121 -0.146  0.003  0.053  0.028 -0.146 -0.196  0.203 -0.096 -0.146  0.003 -0.021  0.053  0.028  0.103 -0.021 -0.096 -0.096 -0.221 -0.196  0.078 -0.046  0.053 -0.121 -0.096 -0.121 -0.021 -0.096 -0.121 -0.021 -0.121 -0.096 -0.171  0.103 -0.071 -0.071 -0.171  0.003  0.053 -0.046 -0.121 -0.071  0.053 -0.021 -0.196 -0.171 -0.096  0.053 -0.121 -0.096 -0.121  0.078  0.103  0.003 -0.046 -0.046  0.178  0.103 -0.021  0.128 -0.046 -0.071 -0.071 -0.146  0.003  0.203 -0.221  0.327  0.153  0.203 -0.096 -0.096 -0.071 -0.071  0.028 -0.146  0.028  0.028 -0.096 -0.071 -0.071 -0.121  0.078  0.028  0.078  0.003 
 0.132 -0.017 -0.217 -0.092  0.182 -0.092 -0.092 -0.017 -0.092 -0.142 -0.042 -0.092 -0.017 -0.017  0.032 -0.142 -0.042  0.007  0.032 -0.142 -0.217  0.232 -0.092 -0.167 -0.017 -0.042  0.057 -0.017  0.082 -0.017 -0.067 -0.167 -0.217 -0.217  0.107 -0.067  0.032 -0.117 -0.092 -0.092 -0.017 -0.117 -0.142  0.007 -0.142 -0.117 -0.117  0.032 -0.092 -0.067 -0.167  0.032  0.032 -0.017 -0.142 -0.092  0.057 -0.017 -0.192 -0.192 -0.092  0.007 -0.167 -0.092 -0.142  0.057  0.082  0.007 -0.042  0.007  0.182  0.132 -0.017  0.132 -0.042 -0.042 -0.092 -0.142  0.082  0.232 -0.242  0.406  0.132  0.232 -0.117 -0.117 -0.067 -0.092  0.032 -0.167  0.007  0.007 -0.067 -0.067 -0.092 -0.117  0.057  0.007  0.057  0.007 
 0.158 -0.066 -0.215 -0.141  0.183 -0.091 -0.091 -0.041 -0.091 -0.165  0.009 -0.091 -0.041  0.009  0.109 -0.141 -0.066 -0.066  0.034 -0.190 -0.215  0.258 -0.116 -0.190 -0.041 -0.091 -0.016 -0.041  0.059 -0.041 -0.041 -0.190 -0.240 -0.240  0.084 -0.041  0.009 -0.141 -0.116 -0.116 -0.016 -0.141 -0.141  0.084 -0.116 -0.116 -0.141  0.009 -0.116 -0.091 -0.165  0.034  0.009 -0.066 -0.165 -0.066  0.084  0.009 -0.215 -0.215 -0.066 -0.041 -0.190 -0.116 -0.091  0.034  0.059  0.009 -0.066  0.084  0.158  0.109  0.009  0.208  0.009 -0.066 -0.141 -0.116  0.059  0.283 -0.265  0.383  0.183  0.233 -0.141 -0.141 -0.091 -0.091  0.084 -0.190 -0.041 -0.016 -0.066 -0.091 -0.116 -0.141  0.034 -0.016 -0.016  0.084 
 0.174 -0.075 -0.224 -0.125  0.125 -0.075 -0.100 -0.050 -0.100 -0.149  0.025 -0.100 -0.100  0.000  0.100 -0.125 -0.075 -0.075  0.025 -0.224 -0.224  0.224 -0.125 -0.199 -0.050 -0.149 -0.025 -0.100  0.025 -0.050 -0.050 -0.199 -0.274 -0.249  0.075 -0.025 -0.050 -0.149 -0.125 -0.149 -0.025 -0.149 -0.149  0.100 -0.125 -0.125 -0.149  0.000 -0.125 -0.100 -0.125  0.025  0.025 -0.075 -0.174 -0.100  0.100  0.000 -0.199 -0.224 -0.075 -0.050 -0.174 -0.100 -0.100  0.025  0.050  0.050 -0.075  0.149  0.149  0.100  0.000  0.224  0.000 -0.075 -0.149 -0.100  0.100  0.299 -0.274  0.399  0.199  0.224 -0.125 -0.125 -0.100 -0.100  0.075 -0.199 -0.050 -0.025 -0.075 -0.100 -0.125 -0.174  0.075 -0.050 -0.050  0.125 
 0.187 -0.062 -0.236 -0.137  0.138 -0.087 -0.112 -0.062 -0.087 -0.161  0.038 -0.087 -0.137  0.038  0.138 -0.087 -0.087 -0.087  0.013 -0.236 -0.236  0.212 -0.161 -0.186 -0.037 -0.161 -0.037 -0.112  0.038 -0.037 -0.037 -0.236 -0.286 -0.236  0.113 -0.037 -0.062 -0.161 -0.137 -0.211 -0.037 -0.161 -0.161  0.113 -0.137 -0.087 -0.137  0.013 -0.137 -0.112 -0.137  0.013  0.038 -0.087 -0.186 -0.037  0.138 -0.012 -0.211 -0.236 -0.087 -0.037 -0.186 -0.112 -0.112  0.013  0.038  0.013 -0.062  0.187  0.138  0.113  0.013  0.237  0.013 -0.037 -0.137 -0.012  0.088  0.337 -0.286  0.412  0.212  0.187 -0.137 -0.137 -0.087 -0.087  0.063 -0.211 -0.062 -0.062 -0.062 -0.112 -0.137 -0.186  0.113 -0.062 -0.062  0.113 
 0.210 -0.039 -0.239 -0.139  0.160 -0.089 -0.139 -0.064 -0.089 -0.139  0.035 -0.089 -0.139  0.010  0.135 -0.064 -0.089 -0.114  0.010 -0.214 -0.239  0.210 -0.164 -0.189 -0.039 -0.164 -0.039 -0.114  0.035 -0.039 -0.039 -0.288 -0.288 -0.264  0.110 -0.039 -0.089 -0.164 -0.139 -0.214 -0.039 -0.164 -0.164  0.135 -0.139 -0.089 -0.139  0.010 -0.139 -0.114 -0.139  0.035  0.035 -0.089 -0.189 -0.014  0.110 -0.039 -0.214 -0.239 -0.114 -0.039 -0.164 -0.114 -0.114  0.035  0.010  0.010 -0.039  0.160  0.135  0.135 -0.014  0.235  0.010 -0.039 -0.139  0.010  0.085  0.334 -0.288  0.409  0.210  0.110 -0.139 -0.139 -0.089 -0.089  0.010 -0.214 -0.064 -0.064 -0.064 -0.114 -0.139 -0.189  0.110 -0.064 -0.064  0.110 
 0.208 -0.016 -0.241 -0.141  0.108 -0.091 -0.141 -0.066 -0.091 -0.141  0.058 -0.091 -0.141  0.008  0.133 -0.066 -0.116 -0.116  0.008 -0.216 -0.241  0.208 -0.166 -0.191  0.008 -0.141 -0.066 -0.116  0.033 -0.041 -0.066 -0.290 -0.290 -0.241  0.133 -0.041 -0.116 -0.116 -0.116 -0.191 -0.041 -0.191 -0.166  0.133 -0.141 -0.066 -0.141  0.008 -0.141 -0.116 -0.116  0.008  0.033 -0.091 -0.191 -0.016  0.083 -0.091 -0.216 -0.241 -0.141 -0.016 -0.166 -0.116 -0.141  0.008  0.008  0.008 -0.041  0.158  0.108  0.133 -0.041  0.208  0.008 -0.066 -0.116  0.008  0.083  0.332 -0.290  0.382  0.183  0.108 -0.141 -0.166 -0.116 -0.091 -0.041 -0.191 -0.066 -0.066 -0.066 -0.116 -0.166 -0.166  0.108 -0.066 -0.066  0.108 
 0.206 -0.018 -0.243 -0.143  0.106 -0.093 -0.118 -0.068 -0.093 -0.143  0.056 -0.093 -0.118  0.031  0.131 -0.068 -0.118 -0.118  0.006 -0.218 -0.243  0.206 -0.143 -0.168  0.006 -0.143 -0.068 -0.118  0.031 -0.043 -0.068 -0.292 -0.292 -0.243  0.131 -0.043 -0.093 -0.118 -0.118 -0.168 -0.043 -0.193 -0.168  0.156 -0.143 -0.068 -0.143  0.006 -0.143 -0.118 -0.118  0.006  0.031 -0.093 -0.193 -0.018  0.081 -0.093 -0.218 -0.243 -0.143 -0.018 -0.143 -0.118 -0.143  0.006  0.006  0.006 -0.043  0.156  0.106  0.131 -0.043  0.206  0.006 -0.068 -0.118  0.006  0.106  0.330 -0.292  0.380  0.181  0.081 -0.143 -0.143 -0.118 -0.093 -0.043 -0.193 -0.068 -0.068 -0.068 -0.118 -0.168 -0.168  0.106 -0.068 -0.068  0.106 
 0.203 -0.021 -0.220 -0.145  0.104 -0.096 -0.145 -0.071 -0.096 -0.145  0.054 -0.046 -0.121  0.054  0.129 -0.071 -0.121 -0.121  0.029 -0.220 -0.245  0.178 -0.145 -0.170  0.004 -0.170 -0.071 -0.121  0.029 -0.046 -0.071 -0.270 -0.295 -0.245  0.153 -0.046 -0.096 -0.121 -0.096 -0.170 -0.046 -0.195 -0.145  0.129 -0.145 -0.096 -0.145 -0.021 -0.145 -0.121 -0.121 -0.021  0.029 -0.071 -0.195 -0.021  0.104 -0.096 -0.220 -0.245 -0.170 -0.071 -0.121 -0.145 -0.145  0.004 -0.021  0.004 -0.021  0.153  0.104  0.104 -0.021  0.203 -0.021 -0.096 -0.145  0.029  0.129  0.328 -0.295  0.378  0.178  0.054 -0.195 -0.145 -0.121 -0.121 -0.046 -0.220 -0.071 -0.071 -0.071 -0.121 -0.145 -0.170  0.104 -0.046 -0.046  0.104 
 0.277 -0.022 -0.221 -0.122  0.103 -0.097 -0.171 -0.072 -0.097 -0.146  0.053 -0.022 -0.122  0.028  0.152 -0.072 -0.122 -0.122  0.028 -0.221 -0.246  0.177 -0.146 -0.171  0.028 -0.196 -0.072 -0.122  0.028 -0.047 -0.072 -0.271 -0.296 -0.246  0.152 -0.047 -0.122 -0.122 -0.097 -0.171 -0.047 -0.196 -0.171  0.103 -0.146 -0.072 -0.146 -0.022 -0.146 -0.122 -0.097 -0.022  0.028 -0.097 -0.196 -0.022  0.103 -0.122 -0.221 -0.246 -0.171 -0.072 -0.146 -0.146 -0.146  0.028 -0.022  0.003 -0.022  0.152  0.103  0.103 -0.022  0.202 -0.022 -0.097 -0.146  0.028  0.128  0.327 -0.296  0.377  0.177  0.053 -0.196 -0.146 -0.122 -0.122 -0.047 -0.221 -0.072 -0.072 -0.072 -0.122 -0.146 -0.146  0.103 -0.047 -0.072  0.103 
 0.301 -0.022 -0.222 -0.122  0.102 -0.097 -0.172 -0.072 -0.097 -0.147  0.052 -0.022 -0.122  0.027  0.152 -0.072 -0.072 -0.122  0.027 -0.222 -0.247  0.177 -0.147 -0.172  0.027 -0.197 -0.072 -0.122  0.027 -0.022 -0.047 -0.272 -0.296 -0.247  0.152 -0.047 -0.122 -0.122 -0.122 -0.172 -0.022 -0.197 -0.172  0.102 -0.147 -0.072 -0.147 -0.022 -0.147 -0.122 -0.097 -0.022  0.052 -0.097 -0.197 -0.022  0.102 -0.172 -0.222 -0.247 -0.172 -0.072 -0.147 -0.147 -0.147  0.027 -0.022 -0.022 -0.022  0.152  0.102  0.102 -0.022  0.227 -0.022 -0.097 -0.147  0.052  0.102  0.326 -0.296  0.376  0.177  0.052 -0.197 -0.172 -0.122 -0.122 -0.047 -0.222 -0.072 -0.072 -0.072 -0.097 -0.147 -0.147  0.102 -0.047 -0.097  0.077 
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 0.299 -0.025 -0.199 -0.125  0.100 -0.100 -0.174 -0.100 -0.100 -0.149  0.050 -0.025 -0.125  0.025  0.174 -0.075 -0.075 -0.125  0.025 -0.224 -0.249  0.174 -0.174 -0.174  0.025 -0.199 -0.075 -0.125  0.025 -0.050 -0.050 -0.274 -0.299 -0.249  0.149 -0.050 -0.125 -0.125 -0.125 -0.174 -0.025 -0.199 -0.149  0.100 -0.125 -0.075 -0.174 -0.025 -0.149 -0.125 -0.100 -0.025  0.075 -0.075 -0.199 -0.025  0.100 -0.149 -0.224 -0.249 -0.174 -0.050 -0.125 -0.149 -0.149  0.025 -0.025  0.000  0.000  0.149  0.050  0.025  0.025  0.174 -0.025 -0.100 -0.125  0.050  0.125  0.324 -0.299  0.374  0.174  0.050 -0.199 -0.149 -0.125 -0.125 -0.075 -0.224 -0.075 -0.075 -0.075 -0.100 -0.149 -0.125  0.100 -0.050 -0.075  0.100 
 0.297 -0.026 -0.201 -0.126  0.098 -0.101 -0.176 -0.101 -0.101 -0.151  0.048 -0.026 -0.126  0.023  0.173 -0.076 -0.076 -0.126  0.023 -0.226 -0.251  0.173 -0.176 -0.176  0.048 -0.201 -0.076 -0.101  0.023 -0.051 -0.051 -0.276 -0.300 -0.251  0.148 -0.051 -0.126 -0.126 -0.101 -0.176 -0.026 -0.201 -0.176  0.098 -0.076 -0.076 -0.176 -0.026 -0.151 -0.126 -0.076  0.023  0.098 -0.076 -0.201 -0.026  0.098 -0.151 -0.226 -0.251 -0.176 -0.051 -0.101 -0.151 -0.151  0.048 -0.026 -0.001 -0.001  0.148  0.048  0.023  0.048  0.173 -0.026 -0.101 -0.126  0.073  0.123  0.322 -0.300  0.372  0.148  0.048 -0.201 -0.151 -0.126 -0.126 -0.076 -0.226 -0.076 -0.076 -0.076 -0.101 -0.151 -0.126  0.098 -0.026 -0.076  0.098 
 0.322 -0.027 -0.201 -0.127  0.098 -0.102 -0.176 -0.102 -0.102 -0.151  0.048 -0.002 -0.127  0.023  0.172 -0.077 -0.077 -0.127  0.023 -0.226 -0.251  0.172 -0.176 -0.176  0.048 -0.201 -0.077 -0.102  0.023 -0.027 -0.052 -0.276 -0.301 -0.251  0.147 -0.052 -0.127 -0.127 -0.102 -0.176 -0.052 -0.201 -0.176  0.098 -0.077 -0.077 -0.176 -0.027 -0.151 -0.127 -0.077  0.023  0.123 -0.077 -0.201 -0.027  0.098 -0.176 -0.226 -0.251 -0.176 -0.052 -0.102 -0.151 -0.151  0.048 -0.027 -0.027 -0.002  0.147  0.048  0.023  0.048  0.172 -0.027 -0.102 -0.127  0.073  0.123  0.322 -0.301  0.372  0.147  0.048 -0.201 -0.151 -0.127 -0.127 -0.077 -0.226 -0.077 -0.077 -0.077 -0.102 -0.151 -0.127  0.098 -0.027 -0.077  0.073 
 0.321 -0.027 -0.202 -0.127  0.097 -0.102 -0.177 -0.102 -0.102 -0.152  0.047 -0.002 -0.127  0.022  0.172 -0.077 -0.077 -0.127  0.022 -0.227 -0.252  0.172 -0.177 -0.177  0.022 -0.202 -0.077 -0.102  0.022 -0.027 -0.052 -0.277 -0.301 -0.252  0.147 -0.052 -0.127 -0.127 -0.077 -0.202 -0.052 -0.202 -0.177  0.097 -0.077 -0.077 -0.177 -0.027 -0.152 -0.127 -0.077 -0.002  0.072 -0.077 -0.202 -0.052  0.072 -0.177 -0.227 -0.252 -0.177 -0.052 -0.127 -0.152 -0.152  0.047 -0.027 -0.052 -0.002  0.147  0.047  0.022  0.047  0.147 -0.027 -0.102 -0.127  0.047  0.122  0.321 -0.277  0.371  0.147  0.047 -0.202 -0.152 -0.127 -0.127 -0.077 -0.227 -0.077 -0.102 -0.077 -0.102 -0.152 -0.127  0.097 -0.027 -0.052  0.072 
 0.320 -0.028 -0.203 -0.128  0.096 -0.128 -0.178 -0.078 -0.103 -0.128  0.071 -0.003 -0.128  0.021  0.171 -0.078 -0.078 -0.128  0.021 -0.228 -0.253  0.171 -0.178 -0.203  0.021 -0.153 -0.078 -0.103  0.021 -0.053 -0.053 -0.278 -0.302 -0.253  0.146 -0.053 -0.128 -0.128 -0.078 -0.203 -0.028 -0.203 -0.178  0.096 -0.078 -0.078 -0.178 -0.028 -0.153 -0.128 -0.078 -0.003  0.071 -0.078 -0.203 -0.053  0.071 -0.178 -0.228 -0.253 -0.178 -0.053 -0.153 -0.153 -0.153  0.046 -0.028 -0.053 -0.003  0.146  0.046  0.021  0.046  0.146 -0.028 -0.103 -0.128  0.046  0.121  0.320 -0.253  0.370  0.121  0.046 -0.203 -0.153 -0.128 -0.128 -0.078 -0.228 -0.078 -0.103 -0.078 -0.103 -0.153 -0.128  0.096 -0.028 -0.053  0.071 
 0.275 -0.049 -0.173 -0.049  0.076 -0.074 -0.198 -0.074 -0.099 -0.074 -0.024  0.001 -0.124  0.076  0.126 -0.049 -0.024 -0.074  0.026 -0.173 -0.198  0.200 -0.148 -0.148  0.001 -0.124  0.001 -0.074 -0.024 -0.024  0.001 -0.198 -0.248 -0.198  0.076  0.001 -0.099 -0.099 -0.124 -0.124  0.001 -0.124 -0.099  0.101 -0.074 -0.124 -0.198 -0.049 -0.099 -0.074 -0.124  0.001  0.076 -0.049 -0.124 -0.099 -0.024 -0.124 -0.148 -0.198 -0.124  0.001 -0.099 -0.148 -0.099  0.026  0.026  0.001  0.026  0.126  0.051  0.026 -0.074  0.126 -0.024 -0.099 -0.124  0.076  0.051  0.200 -0.248  0.449  0.126  0.076 -0.124 -0.124 -0.074 -0.099 -0.024 -0.198 -0.049 -0.124 -0.049 -0.024 -0.099 -0.124  0.001 -0.049 -0.024  0.051 
 0.238 -0.011 -0.111 -0.036  0.063 -0.036 -0.111 -0.061 -0.011 -0.061 -0.011 -0.011 -0.111  0.088  0.063 -0.011 -0.036 -0.036  0.038 -0.111 -0.136  0.138 -0.161 -0.111  0.088 -0.061  0.038 -0.061  0.038 -0.036  0.013 -0.136 -0.161 -0.111  0.038  0.013 -0.061 -0.086 -0.086 -0.136 -0.011 -0.036 -0.086  0.063 -0.011 -0.086 -0.136  0.013 -0.061 -0.036 -0.136 -0.036  0.113 -0.061 -0.061 -0.061 -0.011 -0.086 -0.086 -0.136 -0.061 -0.011 -0.086 -0.061 -0.086  0.013 -0.061  0.013 -0.086  0.063 -0.061 -0.036 -0.061  0.138 -0.036 -0.036 -0.061  0.013  0.013  0.238 -0.161  0.412  0.088  0.013 -0.136 -0.111 -0.011 -0.011  0.013 -0.136 -0.036 -0.086 -0.061 -0.011 -0.061 -0.111  0.063 -0.111 -0.061  0.038 
 0.183  0.008 -0.091 -0.016  0.008 -0.016 -0.116 -0.091 -0.016 -0.066 -0.016 -0.041 -0.116  0.058  0.008 -0.016 -0.041  0.008  0.083 -0.091 -0.116  0.008 -0.141 -0.091  0.058 -0.041  0.008 -0.041  0.058 -0.016  0.008 -0.116 -0.141 -0.091  0.008  0.033 -0.041 -0.066 -0.091 -0.116  0.008 -0.016 -0.066  0.033 -0.116 -0.066 -0.116  0.033 -0.066 -0.016 -0.116 -0.016  0.108 -0.016 -0.041 -0.041 -0.041 -0.091 -0.066 -0.141 -0.066  0.008 -0.066 -0.041 -0.041  0.008 -0.041  0.033 -0.091  0.033 -0.016 -0.016 -0.041  0.083 -0.016 -0.041 -0.066  0.033 -0.041  0.208 -0.141  0.382  0.058 -0.066 -0.116 -0.091 -0.016  0.008  0.033 -0.116 -0.016 -0.091 -0.066  0.008 -0.016 -0.091  0.008 -0.116 -0.041  0.058 
 0.167  0.018 -0.082 -0.032  0.018 -0.007 -0.082 -0.082 -0.032 -0.057 -0.007 -0.057 -0.082 -0.032 -0.057 -0.057 -0.007  0.068  0.118 -0.082 -0.107  0.018 -0.107 -0.082  0.068 -0.007  0.018 -0.007  0.093  0.018 -0.032 -0.082 -0.107 -0.107  0.018  0.068 -0.032 -0.082 -0.057 -0.082  0.043 -0.032 -0.032  0.068 -0.082 -0.057 -0.107 -0.007 -0.082 -0.007 -0.107 -0.032  0.142 -0.032 -0.007 -0.032 -0.057 -0.107 -0.032 -0.107 -0.032 -0.007 -0.032 -0.032 -0.032 -0.057 -0.032  0.068 -0.107  0.018 -0.032  0.018 -0.007  0.043 -0.007 -0.007 -0.057 -0.032 -0.057  0.167 -0.107  0.342  0.043 -0.057 -0.107 -0.082  0.018  0.018  0.018 -0.082 -0.007 -0.057 -0.057  0.043 -0.007 -0.082  0.018 -0.082 -0.007  0.043 
 0.153  0.029 -0.071 -0.046  0.004  0.004 -0.071 -0.071 -0.046 -0.021 -0.021 -0.046 -0.071 -0.046 -0.096 -0.046 -0.021  0.029  0.104 -0.071 -0.096  0.004 -0.096 -0.071  0.054  0.004 -0.021  0.029  0.054  0.029 -0.021 -0.071 -0.096 -0.096  0.029  0.029 -0.071 -0.071 -0.046 -0.071  0.029 -0.021 -0.021  0.029 -0.071 -0.046 -0.096  0.004 -0.071  0.004 -0.096 -0.046  0.153 -0.071  0.004 -0.046 -0.046 -0.096 -0.021 -0.096 -0.046 -0.021 -0.021 -0.046 -0.046 -0.046  0.004  0.079 -0.096 -0.021  0.004  0.004  0.029 -0.046  0.004  0.004 -0.046 -0.046 -0.071  0.129 -0.096  0.328  0.004 -0.046 -0.096 -0.071  0.004  0.029  0.029 -0.071  0.004 -0.096 -0.071  0.054  0.004 -0.046  0.029 -0.046  0.004 -0.021 
 0.091  0.041 -0.084 -0.059 -0.009 -0.009 -0.059 -0.034 -0.059 -0.009 -0.009 -0.034 -0.059 -0.059 -0.084 -0.034 -0.034  0.041  0.091 -0.059 -0.084  0.041 -0.084 -0.059  0.066  0.016 -0.009  0.041  0.066 -0.009 -0.059 -0.059 -0.084 -0.084  0.041  0.016 -0.059 -0.059 -0.034 -0.059  0.016 -0.009 -0.009  0.016 -0.059 -0.059 -0.084 -0.059 -0.059  0.016 -0.084 -0.059  0.141 -0.059 -0.034 -0.034 -0.034 -0.084 -0.034 -0.084 -0.034 -0.009 -0.009 -0.009 -0.059 -0.034  0.041  0.091 -0.084 -0.009  0.016  0.016  0.041 -0.034  0.041 -0.034 -0.034 -0.034 -0.059  0.141 -0.084  0.240  0.016 -0.034 -0.084 -0.059  0.016 -0.009  0.041 -0.034 -0.009 -0.084 -0.059  0.066 -0.009 -0.059  0.016 -0.034  0.016 -0.009 
 0.098  0.023 -0.077 -0.052 -0.002 -0.002 -0.052 -0.027 -0.077 -0.002 -0.052 -0.027 -0.052 -0.052 -0.077 -0.027 -0.027  0.048  0.048 -0.052 -0.077  0.048 -0.052 -0.027  0.073 -0.027 -0.002  0.048  0.073 -0.027 -0.052 -0.052 -0.077 -0.077  0.048  0.023 -0.052 -0.052 -0.027 -0.052  0.023 -0.002  0.023 -0.002 -0.077 -0.052 -0.077 -0.052 -0.052 -0.002 -0.052 -0.077  0.098 -0.052 -0.027 -0.052 -0.052 -0.077 -0.027 -0.077 -0.027 -0.002 -0.002 -0.002 -0.052 -0.027  0.023  0.048 -0.052 -0.002  0.073 -0.002  0.048 -0.027  0.048 -0.027 -0.052 -0.027 -0.052  0.123 -0.077  0.197  0.048 -0.027 -0.077 -0.052 -0.027 -0.002  0.048 -0.027 -0.002 -0.077 -0.052  0.073 -0.002 -0.052  0.023 -0.027  0.023 -0.027 
 0.109  0.009 -0.066 -0.041 -0.016  0.034 -0.066 -0.016 -0.066  0.009 -0.041 -0.016 -0.066 -0.066 -0.066 -0.041 -0.016  0.059  0.059 -0.041 -0.066  0.034 -0.041 -0.041  0.034 -0.016  0.009  0.084  0.084 -0.016 -0.041 -0.041 -0.066 -0.066  0.059  0.034 -0.066 -0.041 -0.016 -0.016  0.034  0.009  0.009  0.009 -0.066 -0.041 -0.066 -0.041 -0.041  0.009 -0.041 -0.066  0.084 -0.066 -0.016 -0.041 -0.041 -0.066 -0.041 -0.066 -0.016 -0.041  0.009  0.009 -0.041  0.009  0.034  0.059 -0.041  0.009  0.084  0.009  0.034 -0.041  0.059 -0.016 -0.041  0.009 -0.041  0.109 -0.066  0.158  0.034 -0.016 -0.066 -0.041 -0.041  0.009  0.009 -0.041 -0.016 -0.066 -0.041  0.084 -0.016 -0.041  0.009 -0.016  0.034 -0.016 
 0.066  0.016 -0.059 -0.034 -0.009  0.041 -0.059 -0.009 -0.059  0.016 -0.059 -0.009 -0.059 -0.059 -0.059 -0.034 -0.034  0.066  0.016 -0.034 -0.059  0.041 -0.034 -0.034  0.041 -0.009 -0.009  0.066  0.066 -0.034 -0.034 -0.034 -0.059 -0.059  0.016 -0.009 -0.059 -0.034 -0.009 -0.009  0.041  0.016  0.016 -0.009 -0.059 -0.059 -0.059 -0.034 -0.034 -0.009 -0.034 -0.059  0.066 -0.059 -0.009 -0.034 -0.034 -0.059 -0.034 -0.059 -0.034 -0.034  0.016  0.016 -0.034 -0.009  0.016  0.041 -0.034  0.016  0.066 -0.009  0.041 -0.034  0.016 -0.034 -0.059 -0.009 -0.059  0.041 -0.059  0.091  0.016 -0.034 -0.059 -0.034 -0.034  0.016  0.016 -0.034 -0.034 -0.059 -0.059  0.066 -0.009 -0.034  0.016 -0.009  0.041 -0.034 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.052 -0.052 -0.052 -0.027  0.047 -0.002 -0.027 -0.052  0.072 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052  0.022 -0.002 -0.052 -0.027 -0.002 -0.002  0.022  0.022 -0.002  0.022 -0.052 -0.052 -0.027 -0.002 -0.027 -0.027 -0.027 -0.052  0.047 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.022  0.022 -0.027 -0.002  0.022  0.022 -0.027  0.022  0.047 -0.002  0.022 -0.027  0.022 -0.002 -0.052 -0.002 -0.027  0.047 -0.052  0.047  0.022 -0.027 -0.027 -0.027 -0.027  0.022 -0.002 -0.027 -0.027 -0.052 -0.052  0.072 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.052 -0.052 -0.027  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.052 -0.027 -0.002  0.022 -0.002  0.022 -0.027  0.022 -0.052 -0.052 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.022 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.022  0.022 -0.002 -0.002  0.022  0.022 -0.027  0.022  0.047  0.022  0.022 -0.002  0.022  0.022 -0.052 -0.002 -0.027  0.072 -0.052  0.047  0.022 -0.027 -0.027 -0.027 -0.027  0.022 -0.002 -0.027 -0.027 -0.052 -0.002  0.072 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 
 0.070  0.045 -0.054 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.004 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.020  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.004 -0.004  0.020  0.020 -0.004  0.020  0.045  0.020  0.020 -0.004  0.020  0.020 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.004  0.070 -0.029 -0.029 -0.029 -0.004  0.045 -0.029 
 0.070  0.045 -0.055 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020 -0.005  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.030 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.047  0.072 -0.053 -0.028 -0.053 -0.003 -0.053 -0.003 -0.078 -0.003 -0.053 -0.028 -0.003 -0.053 -0.053 -0.078 -0.053  0.022 -0.003 -0.028 -0.078  0.022 -0.053 -0.053  0.072 -0.028 -0.003  0.072  0.047 -0.053 -0.053 -0.003 -0.053 -0.078 -0.028 -0.003 -0.028 -0.028 -0.003 -0.003 -0.028  0.097 -0.003 -0.003 -0.028 -0.003 -0.053 -0.028 -0.053 -0.028 -0.003 -0.028  0.072 -0.053 -0.003 -0.053 -0.028 -0.078 -0.053 -0.078 -0.053 -0.053  0.072  0.022 -0.003 -0.028  0.022  0.022 -0.003 -0.003  0.122 -0.003 -0.003 -0.003 -0.003 -0.003 -0.078 -0.028 -0.028  0.047 -0.078  0.122  0.122 -0.053 -0.003 -0.053 -0.028 -0.003 -0.028 -0.053 -0.053 -0.053 -0.028  0.072 -0.028  0.022 -0.028  0.047  0.097 -0.053 
 0.143  0.093 -0.106 -0.031 -0.081 -0.031 -0.056 -0.006 -0.106 -0.056 -0.056 -0.056 -0.031 -0.106 -0.056 -0.106 -0.056  0.068  0.018 -0.081 -0.106  0.043 -0.081 -0.081  0.143 -0.056 -0.006  0.043  0.068  0.018 -0.106 -0.031 -0.106 -0.131 -0.056  0.018 -0.056 -0.031 -0.031 -0.031  0.043  0.043 -0.031 -0.006 -0.081 -0.031 -0.081 -0.056 -0.081 -0.056 -0.056 -0.056  0.093 -0.081 -0.056 -0.106 -0.031 -0.131 -0.081 -0.106 -0.056 -0.056  0.018 -0.006 -0.031 -0.031  0.068 -0.006  0.018 -0.031  0.118 -0.006  0.018  0.018 -0.031  0.043 -0.131 -0.081  0.093  0.118 -0.131  0.218  0.243 -0.081 -0.006 -0.106 -0.056 -0.031 -0.056 -0.081 -0.056 -0.031 -0.081  0.068 -0.081 -0.031  0.043  0.043  0.118 -0.106 
 0.143  0.043 -0.081 -0.056 -0.056 -0.056 -0.031 -0.031 -0.131 -0.106 -0.006 -0.081 -0.056 -0.081 -0.031 -0.131 -0.081  0.043  0.068 -0.131 -0.156  0.068 -0.106 -0.131  0.093 -0.056 -0.006  0.018  0.043 -0.031 -0.131 -0.081 -0.156 -0.181 -0.056  0.068 -0.081 -0.031 -0.031 -0.056 -0.006 -0.006 -0.056  0.018 -0.081 -0.006 -0.131  0.018 -0.106 -0.106 -0.081 -0.031  0.043 -0.031 -0.081 -0.106 -0.056 -0.131 -0.131 -0.106 -0.106 -0.031 -0.056 -0.031 -0.031 -0.006  0.143 -0.031  0.143 -0.056  0.168 -0.006 -0.006 -0.031 -0.006  0.018 -0.156 -0.081  0.093  0.068 -0.181  0.168  0.342 -0.056 -0.056 -0.131 -0.106 -0.031 -0.081 -0.131 -0.081 -0.056 -0.106  0.018 -0.131 -0.056  0.043  0.118  0.193 -0.131 
 0.179  0.004 -0.145 -0.120 -0.070 -0.095 -0.070 -0.020 -0.120 -0.145 -0.045 -0.095 -0.120 -0.045  0.029 -0.120 -0.095  0.004  0.054 -0.170 -0.170  0.054 -0.120 -0.120  0.054 -0.045 -0.020 -0.045  0.104 -0.095 -0.120 -0.145 -0.220 -0.245 -0.045  0.054 -0.120 -0.070 -0.095 -0.070  0.029 -0.070 -0.120  0.079 -0.120 -0.070 -0.170  0.054 -0.120 -0.095 -0.145 -0.020  0.029 -0.095 -0.095 -0.120 -0.045 -0.070 -0.195 -0.170 -0.095  0.004 -0.095 -0.070 -0.070 -0.045  0.079  0.029  0.179  0.004  0.229  0.004 -0.045  0.054  0.029  0.054 -0.145 -0.095  0.179  0.279 -0.220  0.279  0.328 -0.045 -0.095 -0.145 -0.045 -0.070 -0.095 -0.145 -0.095 -0.095 -0.120 -0.020 -0.095 -0.095  0.029  0.129  0.179 -0.120 
 0.165 -0.009 -0.159 -0.134 -0.059 -0.109 -0.059 -0.034 -0.109 -0.159 -0.059 -0.084 -0.109 -0.059 -0.009 -0.134 -0.059 -0.034  0.040 -0.184 -0.184  0.040 -0.159 -0.134  0.040 -0.084 -0.034 -0.059  0.115 -0.109 -0.059 -0.159 -0.234 -0.259 -0.034 -0.009 -0.134 -0.084 -0.109 -0.084  0.065 -0.109 -0.109  0.065 -0.109 -0.084 -0.184  0.015 -0.134 -0.109 -0.134  0.015  0.015 -0.109 -0.084 -0.084 -0.059 -0.059 -0.209 -0.184 -0.109  0.015 -0.134 -0.084 -0.084 -0.059  0.065  0.065  0.190 -0.009  0.215 -0.009 -0.034  0.040  0.015  0.065 -0.134 -0.084  0.140  0.339 -0.234  0.265  0.314 -0.034 -0.109 -0.134 -0.059 -0.084 -0.109 -0.109 -0.109 -0.109 -0.134 -0.059 -0.109 -0.084  0.015  0.115  0.165 -0.034 
 0.142 -0.032 -0.182 -0.132 -0.032 -0.157 -0.082 -0.057 -0.107 -0.182 -0.057 -0.082 -0.082 -0.032  0.017 -0.157 -0.057 -0.082  0.017 -0.207 -0.207  0.017 -0.182 -0.157  0.067 -0.107 -0.057 -0.107  0.117 -0.132 -0.032 -0.182 -0.257 -0.282 -0.057 -0.032 -0.157 -0.107 -0.132 -0.132  0.017 -0.157 -0.132  0.067 -0.107 -0.082 -0.207  0.017 -0.157 -0.082 -0.132 -0.007  0.017 -0.057 -0.057 -0.032  0.017 -0.082 -0.207 -0.207 -0.107  0.042 -0.157 -0.082 -0.107 -0.007  0.067  0.092  0.192  0.017  0.217 -0.057 -0.057  0.092 -0.007  0.042 -0.132 -0.107  0.192  0.441 -0.257  0.316  0.291 -0.057 -0.132 -0.082 -0.082 -0.107 -0.057 -0.132 -0.057 -0.132 -0.107 -0.057 -0.107 -0.107 -0.007  0.067  0.117  0.042 
 0.134 -0.040 -0.215 -0.140 -0.065 -0.165 -0.090 -0.065 -0.115 -0.165 -0.015 -0.090 -0.065  0.009  0.059 -0.165 -0.065 -0.090  0.009 -0.215 -0.215  0.009 -0.190 -0.165  0.059 -0.090 -0.065 -0.115  0.109 -0.140 -0.015 -0.165 -0.265 -0.289 -0.065 -0.040 -0.140 -0.115 -0.140 -0.140  0.034 -0.165 -0.140  0.059 -0.115 -0.090 -0.190  0.034 -0.165 -0.090 -0.115 -0.015  0.009 -0.040 -0.065  0.034  0.009 -0.090 -0.215 -0.215 -0.140  0.034 -0.165 -0.090 -0.090 -0.015  0.059  0.084  0.159  0.084  0.134 -0.090 -0.065  0.109 -0.015  0.009 -0.140 -0.015  0.209  0.508 -0.265  0.333  0.308 -0.065 -0.165 -0.065 -0.115 -0.140 -0.040 -0.140 -0.040 -0.140 -0.115 -0.040 -0.140 -0.140  0.009  0.034  0.109  0.059 
 0.169 -0.055 -0.229 -0.179 -0.030 -0.130 -0.105 -0.080 -0.105 -0.154 -0.030 -0.055 -0.055 -0.005  0.095 -0.130 -0.080 -0.105 -0.005 -0.204 -0.229  0.095 -0.204 -0.154  0.045 -0.105 -0.080 -0.105  0.095 -0.154 -0.030 -0.204 -0.279 -0.304 -0.030 -0.030 -0.130 -0.130 -0.179 -0.179  0.020 -0.154 -0.154  0.045 -0.105 -0.080 -0.130  0.020 -0.179 -0.105 -0.080 -0.030  0.020 -0.055 -0.080  0.045  0.020 -0.080 -0.204 -0.229 -0.154  0.045 -0.204 -0.080 -0.105 -0.005  0.070  0.070  0.144  0.095  0.120 -0.080 -0.055  0.169 -0.030 -0.005 -0.154  0.020  0.269  0.493 -0.279  0.344  0.294 -0.080 -0.130 -0.080 -0.130 -0.154 -0.055 -0.179 -0.055 -0.154 -0.080 -0.055 -0.154 -0.154  0.020  0.020  0.045  0.045 
 0.192 -0.032 -0.232 -0.182 -0.057 -0.132 -0.132 -0.082 -0.107 -0.157 -0.032 -0.007 -0.107  0.017  0.117 -0.132 -0.082 -0.107 -0.007 -0.207 -0.232  0.092 -0.207 -0.157  0.092 -0.082 -0.082 -0.107  0.092 -0.157 -0.007 -0.207 -0.282 -0.306  0.017 -0.032 -0.132 -0.107 -0.132 -0.182  0.067 -0.157 -0.157  0.042 -0.107 -0.082 -0.107  0.017 -0.182 -0.107 -0.082 -0.032  0.017 -0.057 -0.082  0.042 -0.007 -0.082 -0.232 -0.232 -0.157  0.042 -0.207 -0.082 -0.132 -0.032  0.067  0.067  0.142  0.067  0.117 -0.107 -0.082  0.142 -0.032 -0.007 -0.157 -0.032  0.291  0.441 -0.282  0.341  0.291 -0.082 -0.132 -0.057 -0.132 -0.132 -0.057 -0.182 -0.057 -0.157 -0.082 -0.057 -0.157 -0.157  0.017  0.017  0.042  0.017 
 0.209 -0.040 -0.265 -0.115 -0.065 -0.140 -0.165 -0.115 -0.115 -0.140 -0.015 -0.015 -0.115  0.009  0.109 -0.140 -0.090 -0.090  0.009 -0.215 -0.215  0.084 -0.215 -0.165  0.084 -0.090 -0.090 -0.115  0.084 -0.140 -0.015 -0.190 -0.265 -0.314  0.034 -0.015 -0.140 -0.115 -0.140 -0.190  0.059 -0.165 -0.165  0.034 -0.115 -0.090 -0.115  0.009 -0.190 -0.115 -0.090 -0.040  0.009 -0.065 -0.090  0.034 -0.015 -0.090 -0.240 -0.240 -0.165  0.059 -0.215 -0.115 -0.115 -0.040  0.059  0.059  0.159  0.109  0.084 -0.140 -0.065  0.159 -0.040  0.009 -0.165 -0.040  0.308  0.433 -0.289  0.358  0.284 -0.090 -0.140 -0.065 -0.140 -0.140 -0.090 -0.190 -0.065 -0.165 -0.090 -0.065 -0.165 -0.165  0.034  0.034  0.059  0.009 
 0.206 -0.043 -0.268 -0.118 -0.068 -0.143 -0.193 -0.118 -0.118 -0.118 -0.018 -0.018 -0.118  0.031  0.106 -0.143 -0.093 -0.093  0.006 -0.218 -0.218  0.106 -0.218 -0.168  0.081 -0.143 -0.093 -0.118  0.106 -0.118 -0.043 -0.193 -0.268 -0.317  0.031 -0.018 -0.143 -0.118 -0.143 -0.193  0.056 -0.168 -0.168  0.031 -0.118 -0.093 -0.093  0.006 -0.193 -0.118 -0.093 -0.043  0.006 -0.068 -0.093  0.031 -0.018 -0.118 -0.243 -0.243 -0.168  0.056 -0.218 -0.118 -0.118 -0.018  0.106  0.056  0.156  0.131  0.081 -0.143 -0.043  0.231 -0.043  0.006 -0.168  0.006  0.305  0.430 -0.292  0.355  0.281 -0.043 -0.143 -0.093 -0.143 -0.143 -0.093 -0.193 -0.068 -0.193 -0.093 -0.068 -0.168 -0.168  0.031  0.031  0.056  0.031 
 0.235 -0.039 -0.264 -0.089 -0.064 -0.139 -0.264 -0.114 -0.089 -0.114 -0.014 -0.014 -0.139  0.060  0.110 -0.139 -0.089 -0.089  0.010 -0.214 -0.239  0.135 -0.214 -0.164  0.060 -0.164 -0.114 -0.114  0.110 -0.114 -0.039 -0.189 -0.264 -0.313  0.085 -0.064 -0.164 -0.114 -0.164 -0.189  0.035 -0.164 -0.164  0.035 -0.089 -0.089 -0.089 -0.064 -0.189 -0.139 -0.064 -0.039  0.035 -0.089 -0.114  0.035 -0.014 -0.139 -0.214 -0.239 -0.164  0.060 -0.214 -0.139 -0.139 -0.014  0.110  0.010  0.135  0.135  0.085 -0.139 -0.039  0.235 -0.014  0.010 -0.164  0.010  0.309  0.434 -0.288  0.359  0.235 -0.014 -0.139 -0.089 -0.139 -0.139 -0.114 -0.214 -0.089 -0.189 -0.089 -0.089 -0.164 -0.164  0.010  0.035  0.085  0.035 
 0.257 -0.042 -0.267 -0.067 -0.067 -0.167 -0.267 -0.117 -0.092 -0.117 -0.017  0.007 -0.142  0.057  0.082 -0.117 -0.092 -0.092  0.007 -0.217 -0.242  0.132 -0.217 -0.167  0.057 -0.167 -0.117 -0.117  0.132 -0.092 -0.042 -0.192 -0.267 -0.291  0.107 -0.067 -0.142 -0.117 -0.167 -0.192  0.007 -0.167 -0.167  0.032 -0.092 -0.067 -0.092 -0.042 -0.192 -0.142 -0.067 -0.042  0.032 -0.092 -0.092  0.032 -0.017 -0.142 -0.217 -0.242 -0.192  0.057 -0.217 -0.142 -0.142 -0.017  0.107  0.032  0.132  0.132  0.082 -0.142 -0.042  0.232  0.007  0.032 -0.167  0.007  0.306  0.431 -0.291  0.406  0.232 -0.017 -0.142 -0.117 -0.142 -0.142 -0.117 -0.217 -0.092 -0.192 -0.092 -0.092 -0.142 -0.142  0.007  0.007  0.082  0.032 
 0.276 -0.048 -0.272 -0.073 -0.073 -0.172 -0.247 -0.123 -0.098 -0.123  0.027  0.002 -0.147  0.052  0.077 -0.123 -0.098 -0.098  0.002 -0.222 -0.247  0.127 -0.197 -0.197  0.052 -0.172 -0.123 -0.098  0.151 -0.098 -0.048 -0.197 -0.272 -0.272  0.102 -0.073 -0.147 -0.123 -0.098 -0.197  0.002 -0.172 -0.172  0.027 -0.123 -0.073 -0.098 -0.098 -0.197 -0.147 -0.048 -0.023  0.027 -0.098 -0.098  0.002 -0.023 -0.147 -0.222 -0.247 -0.197  0.052 -0.197 -0.147 -0.147  0.002  0.102  0.052  0.127  0.151  0.052 -0.147 -0.023  0.226 -0.023  0.027 -0.172  0.002  0.301  0.351 -0.297  0.401  0.226 -0.048 -0.147 -0.147 -0.147 -0.147 -0.123 -0.197 -0.098 -0.197 -0.098 -0.098 -0.147 -0.123  0.002  0.002  0.052  0.027 
 0.298 -0.050 -0.250 -0.075 -0.075 -0.175 -0.250 -0.125 -0.100 -0.125  0.049 -0.000 -0.175  0.049  0.074 -0.125 -0.100 -0.100 -0.000 -0.225 -0.250  0.124 -0.200 -0.200  0.024 -0.175 -0.125 -0.100  0.149 -0.100 -0.025 -0.200 -0.275 -0.275  0.099 -0.075 -0.150 -0.125 -0.100 -0.200 -0.000 -0.175 -0.150  0.049 -0.125 -0.075 -0.125 -0.100 -0.200 -0.150 -0.050 -0.025  0.024 -0.075 -0.100 -0.000 -0.025 -0.175 -0.225 -0.250 -0.200  0.049 -0.175 -0.150 -0.150 -0.000  0.099  0.024  0.099  0.149  0.049 -0.150 -0.000  0.224 -0.025  0.024 -0.150 -0.000  0.298  0.348 -0.299  0.398  0.199 -0.050 -0.175 -0.150 -0.125 -0.150 -0.125 -0.200 -0.100 -0.200 -0.100 -0.100 -0.150 -0.125  0.024 -0.000  0.049 -0.000 
 0.320 -0.053 -0.253 -0.078 -0.078 -0.178 -0.253 -0.128 -0.103 -0.128  0.046 -0.003 -0.203  0.046  0.071 -0.128 -0.078 -0.103 -0.003 -0.228 -0.253  0.121 -0.228 -0.203  0.021 -0.178 -0.128 -0.128  0.146 -0.103 -0.028 -0.178 -0.302 -0.253  0.096 -0.078 -0.178 -0.128 -0.103 -0.203 -0.003 -0.178 -0.153  0.046 -0.128 -0.078 -0.153 -0.153 -0.203 -0.153 -0.053 -0.028  0.021 -0.078 -0.078 -0.003 -0.028 -0.178 -0.228 -0.253 -0.203  0.046 -0.178 -0.153 -0.153  0.071  0.096  0.021  0.096  0.146  0.046 -0.153  0.021  0.246 -0.053  0.021 -0.178 -0.003  0.295  0.345 -0.302  0.420  0.171 -0.053 -0.178 -0.153 -0.128 -0.153 -0.128 -0.203 -0.103 -0.203 -0.103 -0.103 -0.153 -0.128  0.021 -0.028  0.021 -0.003 
 0.319 -0.055 -0.254 -0.080 -0.080 -0.179 -0.254 -0.130 -0.130 -0.130  0.045  0.020 -0.204  0.045  0.070 -0.130 -0.055 -0.105 -0.005 -0.229 -0.254  0.095 -0.229 -0.204  0.045 -0.179 -0.130 -0.154  0.144 -0.105 -0.030 -0.179 -0.304 -0.254  0.070 -0.080 -0.179 -0.154 -0.105 -0.229 -0.005 -0.179 -0.154  0.045 -0.130 -0.080 -0.130 -0.154 -0.204 -0.154 -0.055 -0.030 -0.005 -0.080 -0.105 -0.030 -0.055 -0.179 -0.229 -0.254 -0.204  0.045 -0.179 -0.154 -0.154  0.070  0.120 -0.005  0.095  0.144  0.045 -0.154  0.020  0.219 -0.055  0.020 -0.179 -0.005  0.294  0.344 -0.304  0.419  0.169 -0.055 -0.179 -0.154 -0.130 -0.154 -0.130 -0.204 -0.080 -0.229 -0.105 -0.105 -0.154 -0.130  0.020 -0.030  0.020 -0.005 
 0.322 -0.052 -0.251 -0.102 -0.052 -0.176 -0.251 -0.127 -0.127 -0.127  0.048  0.023 -0.251  0.048  0.073 -0.127 -0.052 -0.127 -0.002 -0.226 -0.251  0.098 -0.251 -0.251  0.048 -0.176 -0.102 -0.151  0.147 -0.077 -0.027 -0.226 -0.301 -0.251  0.048 -0.077 -0.176 -0.151 -0.102 -0.226 -0.002 -0.176 -0.151  0.048 -0.102 -0.077 -0.127 -0.151 -0.201 -0.151 -0.102 -0.002 -0.002 -0.077 -0.176 -0.027 -0.002 -0.176 -0.226 -0.251 -0.176  0.023 -0.176 -0.151 -0.151  0.073  0.098 -0.052  0.073  0.123  0.048 -0.151  0.048  0.222 -0.052  0.023 -0.151 -0.002  0.297  0.322 -0.301  0.397  0.172 -0.052 -0.176 -0.176 -0.127 -0.151 -0.127 -0.201 -0.077 -0.226 -0.077 -0.102 -0.151 -0.127  0.023 -0.002 -0.002 -0.002 
 0.326 -0.022 -0.247 -0.097 -0.047 -0.172 -0.247 -0.122 -0.122 -0.122  0.052  0.052 -0.247  0.052  0.077 -0.122 -0.047 -0.122  0.002 -0.222 -0.247  0.102 -0.247 -0.247  0.077 -0.172 -0.097 -0.147  0.127 -0.072 -0.047 -0.222 -0.296 -0.247  0.027 -0.072 -0.172 -0.172 -0.097 -0.222  0.052 -0.172 -0.147  0.077 -0.097 -0.072 -0.122 -0.147 -0.197 -0.147 -0.097  0.002  0.002 -0.072 -0.172 -0.022  0.002 -0.172 -0.222 -0.247 -0.147 -0.022 -0.147 -0.147 -0.147  0.077  0.077 -0.047  0.027  0.127  0.052 -0.147  0.052  0.227 -0.047 -0.022 -0.147 -0.022  0.301  0.326 -0.296  0.376  0.177 -0.047 -0.197 -0.197 -0.122 -0.147 -0.147 -0.197 -0.072 -0.222 -0.072 -0.097 -0.147 -0.122  0.027  0.002 -0.072  0.002 
 0.328 -0.020 -0.245 -0.095 -0.045 -0.170 -0.245 -0.120 -0.120 -0.120  0.054  0.029 -0.245  0.054  0.079 -0.120 -0.045 -0.120  0.004 -0.220 -0.245  0.104 -0.245 -0.245  0.104 -0.170 -0.120 -0.145  0.129 -0.095 -0.070 -0.220 -0.294 -0.245  0.029 -0.070 -0.170 -0.170 -0.095 -0.220  0.054 -0.195 -0.145  0.079 -0.070 -0.070 -0.145 -0.145 -0.195 -0.145 -0.095  0.004 -0.020 -0.070 -0.170 -0.020  0.004 -0.170 -0.220 -0.245 -0.145 -0.020 -0.145 -0.145 -0.145  0.054  0.054 -0.045 -0.045  0.154  0.054 -0.145  0.054  0.204 -0.045 -0.020 -0.145 -0.045  0.303  0.328 -0.270  0.378  0.154 -0.045 -0.195 -0.195 -0.120 -0.145 -0.170 -0.195 -0.095 -0.220 -0.070 -0.120 -0.145 -0.120  0.029  0.029 -0.070  0.004 
 0.247 -0.027 -0.177 -0.127 -0.077 -0.127 -0.202 -0.102 -0.102 -0.102 -0.052  0.047 -0.227  0.022  0.097 -0.077 -0.052 -0.102 -0.002 -0.177 -0.202  0.072 -0.202 -0.177  0.122 -0.127 -0.077 -0.077  0.097 -0.052 -0.027 -0.177 -0.227 -0.227  0.072 -0.002 -0.102 -0.127 -0.077 -0.177  0.022 -0.127 -0.127  0.097 -0.077 -0.052 -0.102 -0.077 -0.152 -0.077 -0.127 -0.002  0.047 -0.027 -0.127 -0.052 -0.052 -0.102 -0.152 -0.177 -0.127  0.047 -0.127 -0.102 -0.152  0.047 -0.002 -0.052 -0.027  0.097 -0.002 -0.127  0.047  0.172 -0.002 -0.027 -0.102 -0.052  0.296  0.247 -0.202  0.396  0.072 -0.052 -0.127 -0.177 -0.052 -0.102 -0.127 -0.152 -0.052 -0.177 -0.052 -0.077 -0.102 -0.077 -0.002 -0.027 -0.052 -0.002 
 0.215 -0.034 -0.109 -0.084 -0.034 -0.034 -0.134 -0.059 -0.084 -0.084 -0.034 -0.009 -0.134  0.015  0.065 -0.034 -0.009 -0.034  0.065 -0.109 -0.109  0.065 -0.134 -0.084  0.115 -0.034  0.015 -0.034  0.115 -0.034 -0.009 -0.134 -0.159 -0.159  0.015 -0.009 -0.109 -0.109 -0.034 -0.134 -0.009 -0.034 -0.084  0.040 -0.034 -0.084 -0.134 -0.034 -0.084  0.015 -0.134 -0.034  0.090 -0.009 -0.059 -0.059 -0.059 -0.084 -0.109 -0.084 -0.084 -0.034 -0.084 -0.059 -0.059 -0.034  0.015  0.015 -0.034  0.015 -0.009 -0.034 -0.034  0.140 -0.009 -0.034 -0.084 -0.034  0.140  0.289 -0.134  0.389  0.040 -0.034 -0.159 -0.109  0.015 -0.009 -0.009 -0.084 -0.009 -0.134 -0.034  0.015 -0.059 -0.059  0.065 -0.134 -0.009  0.015 
 0.184 -0.015 -0.090 -0.090 -0.015 -0.015 -0.140 -0.065 -0.065 -0.065 -0.015 -0.015 -0.140 -0.015  0.060 -0.040 -0.040  0.035  0.085 -0.090 -0.090  0.010 -0.115 -0.065  0.110 -0.040  0.010 -0.015  0.135 -0.015  0.010 -0.115 -0.140 -0.140  0.035  0.010 -0.090 -0.090  0.010 -0.140  0.060 -0.040 -0.065  0.060 -0.065 -0.065 -0.115 -0.040 -0.090  0.010 -0.115 -0.015  0.110 -0.065 -0.040 -0.040 -0.090 -0.090 -0.090 -0.090 -0.065 -0.040 -0.065 -0.040 -0.065 -0.040  0.010  0.035 -0.065 -0.015 -0.040 -0.015 -0.015  0.110 -0.015 -0.015 -0.065 -0.015  0.035  0.259 -0.115  0.359  0.010 -0.015 -0.140 -0.115  0.035  0.010  0.010 -0.090 -0.015 -0.090 -0.065  0.035 -0.065 -0.040  0.085 -0.140 -0.015  0.010 
 0.115  0.040 -0.059 -0.084  0.015 -0.009 -0.109 -0.034 -0.084 -0.034  0.015 -0.059 -0.109 -0.009 -0.034 -0.034 -0.034  0.065  0.090 -0.084 -0.109  0.015 -0.109 -0.084  0.065 -0.009  0.040  0.015  0.090 -0.009  0.015 -0.084 -0.109 -0.109  0.040 -0.009 -0.034 -0.059 -0.034 -0.109  0.040 -0.034 -0.034  0.040 -0.059 -0.034 -0.084 -0.084 -0.084  0.040 -0.109 -0.034  0.140 -0.059 -0.009 -0.059 -0.059 -0.059 -0.059 -0.059 -0.034 -0.034 -0.034 -0.009 -0.059 -0.034 -0.009  0.040 -0.084 -0.034 -0.059  0.015  0.040  0.065 -0.009 -0.034 -0.059 -0.059 -0.084  0.265 -0.109  0.339  0.040 -0.059 -0.084 -0.084  0.015  0.015  0.040 -0.059 -0.009 -0.084 -0.059  0.040 -0.059 -0.059  0.015 -0.109  0.015 -0.009 
 0.093  0.043 -0.057 -0.082  0.018 -0.007 -0.107 -0.057 -0.082 -0.032  0.043 -0.057 -0.107 -0.032 -0.007 -0.057 -0.032  0.068  0.118 -0.057 -0.107  0.018 -0.107 -0.082  0.068 -0.007  0.043  0.018  0.118 -0.007 -0.007 -0.082 -0.107 -0.107  0.043 -0.032 -0.057 -0.057 -0.057 -0.107  0.043 -0.032 -0.032  0.043 -0.057 -0.032 -0.082 -0.082 -0.082  0.018 -0.082 -0.057  0.118 -0.032 -0.007 -0.057 -0.057 -0.082 -0.057 -0.082 -0.032 -0.032 -0.032 -0.007 -0.057 -0.032 -0.007  0.068 -0.082 -0.007 -0.057  0.018  0.043  0.093 -0.007 -0.032 -0.057 -0.082 -0.082  0.292 -0.107  0.342  0.018 -0.057 -0.082 -0.082  0.018  0.018  0.043 -0.057 -0.007 -0.082 -0.057  0.043 -0.057 -0.057  0.018 -0.082 -0.007 -0.007 
 0.082  0.032 -0.042 -0.067  0.007  0.007 -0.092 -0.067 -0.067 -0.017  0.032 -0.042 -0.092 -0.017 -0.067 -0.042 -0.017  0.057  0.057 -0.042 -0.092  0.032 -0.092 -0.067  0.082  0.007 -0.017  0.032  0.132 -0.017 -0.042 -0.067 -0.092 -0.092  0.007 -0.017 -0.067 -0.067 -0.042 -0.067  0.007 -0.017 -0.017  0.007 -0.092 -0.067 -0.092 -0.067 -0.067  0.007 -0.067 -0.092  0.107 -0.067 -0.017 -0.067 -0.067 -0.092 -0.042 -0.067 -0.017  0.007 -0.017  0.007 -0.042 -0.042  0.032  0.057 -0.042  0.007  0.007  0.032  0.057  0.057  0.032 -0.042 -0.042 -0.042 -0.067  0.257 -0.092  0.306  0.032 -0.042 -0.092 -0.067  0.032  0.007  0.032 -0.017 -0.017 -0.092 -0.092  0.057 -0.042 -0.092  0.007 -0.067  0.007 -0.017 
 0.111  0.036 -0.063 -0.063  0.036  0.011 -0.088 -0.063 -0.088 -0.013  0.011 -0.038 -0.088 -0.038 -0.063 -0.038 -0.013  0.036  0.086 -0.038 -0.088  0.036 -0.088 -0.063  0.086  0.011 -0.013  0.036  0.111  0.011 -0.038 -0.063 -0.088 -0.088  0.011 -0.013 -0.063 -0.063 -0.038 -0.063  0.011 -0.013 -0.013  0.011 -0.088 -0.063 -0.088 -0.063 -0.063  0.011 -0.063 -0.063  0.111 -0.063 -0.013 -0.063 -0.063 -0.088 -0.038 -0.088 -0.013  0.011 -0.013  0.011 -0.038 -0.013  0.036  0.061 -0.038  0.011  0.036  0.036  0.036  0.036  0.036 -0.038 -0.038 -0.038 -0.063  0.261 -0.088  0.285  0.036 -0.038 -0.088 -0.063  0.036  0.036  0.011 -0.013 -0.013 -0.088 -0.063  0.061 -0.038 -0.038  0.011 -0.063  0.011 -0.038 
 0.122  0.047 -0.053 -0.053 -0.003  0.022 -0.078 -0.028 -0.078 -0.003 -0.003 -0.028 -0.053 -0.053 -0.078 -0.053 -0.028  0.047  0.072 -0.028 -0.078  0.047 -0.078 -0.078  0.097  0.022 -0.003  0.047  0.097 -0.003 -0.053 -0.053 -0.078 -0.078  0.022  0.022 -0.053 -0.053 -0.028 -0.053 -0.003 -0.003 -0.003  0.022 -0.078 -0.053 -0.078 -0.053 -0.053 -0.003 -0.053 -0.053  0.072 -0.078 -0.028 -0.053 -0.053 -0.078 -0.028 -0.078 -0.028 -0.053 -0.003 -0.003 -0.053 -0.003  0.047  0.047 -0.053 -0.003  0.072 -0.003  0.022  0.022  0.047 -0.028 -0.028 -0.028 -0.053  0.221 -0.078  0.271  0.047 -0.028 -0.078 -0.053  0.022  0.047 -0.003 -0.028 -0.003 -0.078 -0.053  0.047 -0.028 -0.028 -0.003 -0.028  0.022 -0.028 
 0.101  0.051 -0.048 -0.048 -0.023  0.001 -0.073 -0.023 -0.073  0.001  0.001 -0.023 -0.048 -0.048 -0.073 -0.048 -0.048  0.051  0.076 -0.023 -0.073  0.076 -0.073 -0.073  0.051  0.026  0.001  0.051  0.101 -0.023 -0.048 -0.048 -0.073 -0.073  0.026  0.026 -0.073 -0.048 -0.023 -0.048  0.001  0.001  0.001  0.026 -0.073 -0.048 -0.073 -0.023 -0.048  0.001 -0.048 -0.073  0.076 -0.073 -0.023 -0.048 -0.048 -0.073 -0.048 -0.073  0.001 -0.048  0.001  0.001 -0.048  0.001  0.051  0.026 -0.048  0.001  0.076  0.001  0.026  0.026  0.051  0.001 -0.023 -0.023 -0.073  0.226 -0.073  0.201  0.001 -0.023 -0.048 -0.048  0.001  0.051  0.001 -0.023 -0.023 -0.073 -0.048  0.051 -0.023 -0.048  0.001 -0.023  0.026 -0.023 
 0.089  0.014 -0.060 -0.035 -0.010  0.014 -0.060 -0.010 -0.060  0.014 -0.010 -0.010 -0.035 -0.060 -0.035 -0.060 -0.035  0.039  0.039 -0.010 -0.060  0.064 -0.060 -0.060  0.039 -0.010  0.014  0.089  0.089 -0.010 -0.035 -0.035 -0.060 -0.060  0.014 -0.010 -0.060 -0.035 -0.010 -0.010 -0.010  0.014 -0.010 -0.010 -0.060 -0.035 -0.060 -0.010 -0.035 -0.035 -0.035 -0.060  0.039 -0.060 -0.010 -0.035 -0.035 -0.060 -0.060 -0.060  0.014 -0.035  0.014  0.039 -0.035 -0.010  0.014  0.014 -0.035  0.014  0.039  0.014  0.014 -0.010  0.039  0.014 -0.060 -0.010 -0.035  0.114 -0.060  0.114  0.014 -0.010 -0.035 -0.035 -0.035  0.014  0.014 -0.035 -0.010 -0.060 -0.060  0.064 -0.010 -0.035  0.014 -0.010  0.039 -0.010 
 0.095  0.020 -0.055 -0.030 -0.005  0.020 -0.055 -0.005 -0.055  0.020 -0.005 -0.005 -0.030 -0.055 -0.030 -0.055 -0.030  0.045  0.020 -0.005 -0.055  0.070 -0.055 -0.055  0.045 -0.030  0.020  0.070  0.095 -0.030 -0.030 -0.030 -0.055 -0.055  0.020 -0.005 -0.055 -0.030 -0.005 -0.005 -0.005  0.020 -0.005 -0.005 -0.055 -0.055 -0.055 -0.005 -0.030 -0.030 -0.030 -0.055  0.045 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.030 -0.005  0.020  0.020 -0.030  0.020  0.045 -0.005  0.020 -0.005  0.045  0.020 -0.055 -0.005 -0.030  0.095 -0.055  0.045  0.020 -0.030 -0.030 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.055  0.070 -0.030 -0.030 -0.030 -0.005  0.045 -0.005 
 0.073  0.023 -0.051 -0.026 -0.026  0.023 -0.051 -0.001 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026 -0.001 -0.051 -0.026 -0.051 -0.026 -0.026 -0.026 -0.001 -0.051  0.023 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.023  0.048 -0.026 -0.001  0.023  0.023 -0.026  0.023  0.048 -0.001  0.023 -0.001  0.023 -0.001 -0.051 -0.001 -0.026  0.073 -0.051  0.048  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.073 -0.026 -0.026 -0.026 -0.001  0.048 -0.026 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028  0.021  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.028 -0.003  0.021  0.021 -0.003  0.021  0.046 -0.003  0.021 -0.003  0.021 -0.003 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.028  0.021 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.028  0.071 -0.028 -0.028 -0.028 -0.003  0.046 -0.028 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.021  0.021 -0.004  0.021 -0.029  0.021 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.004 -0.004  0.021  0.021 -0.004  0.021  0.046  0.021  0.021 -0.004  0.021  0.021 -0.054 -0.004 -0.029  0.071 -0.054  0.046  0.021 -0.029  0.021 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.004  0.071 -0.029 -0.029 -0.029 -0.004  0.046 -0.029 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.055 -0.030 -0.030 -0.030 -0.030 -0.030 -0.005 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.204  0.005 -0.070 -0.020 -0.020 -0.020 -0.070  0.005 -0.095 -0.045 -0.045 -0.020 -0.045 -0.045 -0.070 -0.070 -0.020  0.080  0.080 -0.045 -0.070  0.055 -0.070 -0.045  0.055 -0.070 -0.020  0.055  0.055  0.030 -0.045  0.005 -0.095 -0.095 -0.020  0.005 -0.020 -0.020 -0.020 -0.020  0.030  0.005 -0.020  0.005 -0.045 -0.070 -0.070 -0.070 -0.070 -0.020 -0.020 -0.045  0.080 -0.095 -0.045 -0.095 -0.070 -0.070 -0.045 -0.095 -0.045 -0.045  0.030  0.030 -0.020 -0.020 -0.020  0.030  0.005 -0.020  0.080  0.030  0.005 -0.020 -0.020 -0.020 -0.070 -0.045  0.130  0.105 -0.095  0.229  0.105 -0.045 -0.020 -0.070 -0.045  0.055 -0.045 -0.070  0.005 -0.045 -0.045  0.130 -0.045  0.005  0.005  0.005  0.080 -0.070 
 0.218 -0.006 -0.131 -0.056 -0.031 -0.031 -0.081 -0.031 -0.106 -0.081  0.019 -0.056 -0.081 -0.056 -0.106 -0.131 -0.056  0.094  0.044 -0.106 -0.106  0.119 -0.106 -0.081  0.044 -0.081 -0.031 -0.006  0.044  0.019 -0.031 -0.006 -0.155 -0.155 -0.031  0.044 -0.081 -0.056 -0.081 -0.056  0.094  0.019 -0.056  0.044 -0.081 -0.031 -0.106 -0.031 -0.106 -0.031 -0.031 -0.031  0.069 -0.056 -0.031 -0.106  0.019 -0.131 -0.106 -0.155 -0.081  0.044 -0.006  0.019 -0.056 -0.056  0.044  0.044  0.019 -0.056  0.193  0.044 -0.056 -0.006 -0.031 -0.006 -0.131 -0.031  0.143  0.143 -0.155  0.293  0.168 -0.106 -0.056 -0.081 -0.031  0.019 -0.081 -0.081  0.019  0.019 -0.081  0.094 -0.081 -0.031 -0.006  0.019  0.044 -0.106 
 0.175  0.000 -0.149 -0.074 -0.024 -0.049 -0.099  0.000 -0.049 -0.124  0.050 -0.049 -0.074 -0.074 -0.074 -0.124 -0.099  0.100  0.025 -0.149 -0.124  0.075 -0.149 -0.099  0.075 -0.074 -0.074 -0.049  0.000  0.000 -0.024 -0.024 -0.199 -0.199 -0.074  0.050 -0.099 -0.024 -0.074 -0.074  0.175  0.000 -0.074  0.050 -0.124 -0.049 -0.149 -0.049 -0.124 -0.074 -0.049 -0.049  0.050 -0.049 -0.049 -0.074  0.025 -0.149 -0.149 -0.199 -0.074  0.050 -0.049 -0.024 -0.074 -0.024  0.000  0.050  0.050  0.025  0.150  0.125 -0.074  0.025 -0.049  0.025 -0.124 -0.074  0.175  0.200 -0.199  0.299  0.150 -0.124 -0.074 -0.099 -0.024 -0.049 -0.074 -0.124 -0.024  0.100 -0.099  0.050 -0.124 -0.074  0.025  0.075  0.025 -0.149 
 0.192  0.018 -0.206 -0.107  0.018 -0.082 -0.156 -0.032 -0.057 -0.181  0.018 -0.007 -0.107 -0.057 -0.032 -0.156 -0.107  0.018  0.043 -0.181 -0.181  0.192 -0.156 -0.156  0.093 -0.132 -0.057 -0.057  0.043 -0.057 -0.032 -0.057 -0.231 -0.256 -0.007 -0.007 -0.107 -0.082 -0.057 -0.107  0.118 -0.082 -0.082  0.043 -0.181 -0.057 -0.206 -0.032 -0.132 -0.082 -0.132 -0.032  0.093 -0.007 -0.107 -0.057  0.018 -0.156 -0.181 -0.181 -0.082 -0.007 -0.107 -0.057 -0.107 -0.007  0.043  0.043  0.093  0.118  0.142  0.093 -0.057  0.068 -0.032  0.068 -0.132  0.018  0.317  0.242 -0.256  0.342  0.242 -0.082 -0.082 -0.107 -0.057 -0.082 -0.057 -0.156 -0.032  0.068 -0.132 -0.007 -0.107 -0.132 -0.007  0.068  0.043 -0.082 
 0.223 -0.001 -0.200 -0.126  0.074 -0.101 -0.175 -0.051 -0.051 -0.200 -0.026 -0.026 -0.076 -0.001  0.049 -0.150 -0.101 -0.001  0.024 -0.200 -0.200  0.198 -0.150 -0.175  0.074 -0.150 -0.051 -0.051  0.099 -0.051 -0.026 -0.076 -0.250 -0.275  0.024 -0.026 -0.076 -0.076 -0.076 -0.126  0.099 -0.076 -0.101  0.024 -0.126 -0.051 -0.175 -0.026 -0.101 -0.101 -0.150  0.024  0.074 -0.026 -0.126 -0.076 -0.001 -0.126 -0.200 -0.200 -0.101 -0.026 -0.126 -0.076 -0.126  0.024  0.074  0.024  0.099  0.099  0.173  0.074 -0.076  0.099 -0.026  0.049 -0.150  0.024  0.298  0.223 -0.275  0.398  0.223 -0.076 -0.101 -0.101 -0.076 -0.076 -0.051 -0.175 -0.051  0.049 -0.101 -0.001 -0.126 -0.126  0.049  0.049  0.074 -0.076 
 0.254 -0.020 -0.219 -0.095  0.080 -0.144 -0.169 -0.020 -0.045 -0.194 -0.020 -0.020 -0.095  0.030  0.105 -0.144 -0.095 -0.045  0.030 -0.194 -0.219  0.229 -0.169 -0.169  0.055 -0.169 -0.070 -0.120  0.105 -0.095 -0.070 -0.095 -0.294 -0.294  0.130  0.005 -0.070 -0.095 -0.095 -0.169  0.030 -0.120 -0.120  0.030 -0.120 -0.070 -0.144 -0.045 -0.120 -0.095 -0.144  0.005  0.080 -0.020 -0.144 -0.020  0.005 -0.120 -0.219 -0.219 -0.120 -0.020 -0.169 -0.070 -0.144  0.030  0.055  0.005  0.154  0.130  0.179  0.105 -0.070  0.105 -0.020  0.030 -0.169  0.030  0.304  0.304 -0.294  0.428  0.254 -0.020 -0.120 -0.120 -0.095 -0.095 -0.045 -0.194 -0.070  0.005 -0.095 -0.045 -0.095 -0.120  0.030  0.030  0.030 -0.045 
 0.272 -0.027 -0.226 -0.077  0.073 -0.127 -0.176 -0.027 -0.052 -0.127 -0.052 -0.002 -0.102  0.048  0.123 -0.151 -0.102 -0.052  0.023 -0.201 -0.226  0.222 -0.201 -0.176  0.023 -0.176 -0.077 -0.102  0.147 -0.077 -0.077 -0.102 -0.301 -0.301  0.123 -0.002 -0.077 -0.102 -0.102 -0.176  0.048 -0.127 -0.127  0.023 -0.127 -0.077 -0.151 -0.027 -0.127 -0.102 -0.077 -0.027  0.048 -0.027 -0.151 -0.027 -0.002 -0.102 -0.226 -0.226 -0.127 -0.027 -0.201 -0.077 -0.151 -0.002  0.098 -0.002  0.123  0.147  0.172  0.073 -0.077  0.123 -0.027  0.023 -0.176  0.023  0.347  0.297 -0.301  0.422  0.247 -0.027 -0.102 -0.127 -0.102 -0.102 -0.027 -0.201 -0.052 -0.002 -0.102 -0.052 -0.127 -0.151  0.048  0.023  0.023 -0.002 
 0.262 -0.037 -0.237 -0.087  0.037 -0.112 -0.187 -0.037 -0.087 -0.112 -0.062 -0.012 -0.112  0.087  0.112 -0.162 -0.137 -0.062  0.012 -0.212 -0.212  0.187 -0.212 -0.212  0.012 -0.187 -0.112 -0.137  0.137 -0.112 -0.112 -0.137 -0.286 -0.311  0.112 -0.037 -0.137 -0.112 -0.112 -0.187  0.037 -0.162 -0.137  0.012 -0.137 -0.087 -0.137 -0.087 -0.162 -0.112 -0.037 -0.062  0.037 -0.062 -0.187 -0.012 -0.012 -0.087 -0.237 -0.237 -0.137 -0.037 -0.212 -0.087 -0.137 -0.037  0.112  0.062  0.137  0.212  0.137  0.062 -0.037  0.187 -0.062  0.037 -0.187  0.012  0.336  0.311 -0.286  0.411  0.237 -0.012 -0.112 -0.137 -0.137 -0.112 -0.037 -0.212 -0.062 -0.012 -0.087 -0.112 -0.162 -0.162  0.062  0.037  0.037  0.012 
 0.281 -0.043 -0.267 -0.093  0.032 -0.118 -0.217 -0.043 -0.068 -0.118 -0.068 -0.018 -0.118  0.107  0.132 -0.142 -0.142 -0.068  0.032 -0.217 -0.217  0.181 -0.217 -0.217  0.007 -0.167 -0.118 -0.142  0.132 -0.093 -0.093 -0.142 -0.292 -0.317  0.132 -0.068 -0.142 -0.118 -0.118 -0.192  0.032 -0.167 -0.142  0.007 -0.142 -0.093 -0.093 -0.118 -0.167 -0.118 -0.043 -0.068  0.032 -0.093 -0.192  0.007 -0.018 -0.068 -0.242 -0.242 -0.167 -0.018 -0.217 -0.093 -0.142 -0.043  0.107  0.057  0.107  0.206  0.132  0.057 -0.043  0.206 -0.043  0.007 -0.167  0.007  0.331  0.331 -0.292  0.406  0.231 -0.018 -0.142 -0.142 -0.142 -0.142 -0.043 -0.217 -0.068 -0.018 -0.093 -0.118 -0.167 -0.192  0.057  0.032  0.057  0.007 
 0.304 -0.045 -0.269 -0.095  0.030 -0.120 -0.219 -0.045 -0.070 -0.120 -0.045 -0.020 -0.120  0.105  0.130 -0.120 -0.144 -0.070  0.005 -0.219 -0.219  0.179 -0.219 -0.219  0.005 -0.169 -0.120 -0.144  0.130 -0.095 -0.095 -0.144 -0.294 -0.319  0.130 -0.070 -0.144 -0.120 -0.120 -0.194  0.005 -0.169 -0.144  0.005 -0.144 -0.070 -0.095 -0.120 -0.169 -0.120 -0.045 -0.070  0.030 -0.095 -0.194  0.005 -0.020 -0.095 -0.244 -0.244 -0.194 -0.020 -0.219 -0.095 -0.144  0.005  0.105  0.055  0.105  0.204  0.130  0.055 -0.070  0.254 -0.045  0.005 -0.169  0.005  0.329  0.329 -0.294  0.404  0.229  0.005 -0.144 -0.144 -0.144 -0.144 -0.045 -0.219 -0.070 -0.020 -0.095 -0.120 -0.169 -0.169  0.080 -0.020  0.055  0.005 
 0.300 -0.048 -0.248 -0.098  0.026 -0.098 -0.223 -0.048 -0.073 -0.123 -0.048 -0.023 -0.123  0.101  0.101 -0.148 -0.148 -0.073  0.026 -0.223 -0.223  0.176 -0.223 -0.223  0.001 -0.173 -0.123 -0.148  0.126 -0.098 -0.098 -0.098 -0.297 -0.297  0.126 -0.073 -0.148 -0.123 -0.123 -0.198  0.001 -0.173 -0.148  0.001 -0.123 -0.073 -0.098 -0.123 -0.173 -0.123 -0.048 -0.073  0.026 -0.098 -0.173  0.001 -0.023 -0.123 -0.248 -0.248 -0.198  0.001 -0.223 -0.098 -0.148  0.026  0.101  0.026  0.151  0.226  0.126  0.051 -0.048  0.251 -0.048  0.001 -0.173  0.001  0.325  0.325 -0.297  0.425  0.226  0.026 -0.148 -0.148 -0.148 -0.148 -0.048 -0.223 -0.073 -0.023 -0.098 -0.123 -0.173 -0.148  0.076  0.001  0.051 -0.023 
 0.301 -0.047 -0.247 -0.097  0.027 -0.097 -0.222 -0.047 -0.072 -0.122 -0.047 -0.022 -0.122  0.102  0.102 -0.147 -0.147 -0.072  0.027 -0.222 -0.222  0.177 -0.222 -0.222  0.002 -0.197 -0.122 -0.147  0.102 -0.097 -0.097 -0.072 -0.296 -0.296  0.127 -0.072 -0.147 -0.122 -0.122 -0.197  0.002 -0.172 -0.147  0.002 -0.122 -0.072 -0.097 -0.147 -0.172 -0.122 -0.047 -0.072  0.027 -0.097 -0.172  0.002 -0.022 -0.147 -0.247 -0.247 -0.197  0.002 -0.222 -0.097 -0.147  0.077  0.102  0.027  0.177  0.227  0.102  0.027 -0.047  0.252 -0.047  0.002 -0.172 -0.022  0.326  0.326 -0.296  0.426  0.227  0.027 -0.147 -0.147 -0.147 -0.147 -0.072 -0.222 -0.097 -0.022 -0.097 -0.122 -0.172 -0.147  0.077  0.002  0.052 -0.022 
 0.300 -0.049 -0.248 -0.099  0.026 -0.099 -0.223 -0.049 -0.074 -0.124 -0.049 -0.024 -0.124  0.101  0.101 -0.148 -0.148 -0.074  0.001 -0.223 -0.223  0.175 -0.223 -0.223  0.001 -0.198 -0.124 -0.148  0.150 -0.099 -0.099 -0.074 -0.298 -0.298  0.126 -0.074 -0.148 -0.124 -0.124 -0.198  0.001 -0.173 -0.148  0.001 -0.124 -0.074 -0.099 -0.148 -0.173 -0.124 -0.049 -0.049  0.026 -0.099 -0.173  0.001 -0.024 -0.148 -0.248 -0.248 -0.198  0.001 -0.223 -0.099 -0.148  0.076  0.101  0.026  0.175  0.225  0.101  0.026 -0.074  0.250 -0.049  0.001 -0.173  0.001  0.325  0.325 -0.298  0.425  0.225  0.026 -0.148 -0.148 -0.148 -0.148 -0.074 -0.223 -0.099 -0.024 -0.099 -0.124 -0.173 -0.148  0.076 -0.024  0.051 -0.024 
 0.298 -0.050 -0.275 -0.100  0.024 -0.100 -0.225 -0.050 -0.100 -0.125 -0.050 -0.025 -0.125  0.099  0.124 -0.100 -0.150 -0.075 -0.025 -0.225 -0.225  0.149 -0.225 -0.225 -0.000 -0.200 -0.125 -0.150  0.149 -0.075 -0.075 -0.075 -0.299 -0.275  0.099 -0.075 -0.150 -0.125 -0.125 -0.200 -0.000 -0.175 -0.150 -0.000 -0.125 -0.075 -0.125 -0.150 -0.175 -0.125 -0.050 -0.025  0.024 -0.100 -0.175 -0.000 -0.000 -0.125 -0.250 -0.250 -0.200 -0.000 -0.225 -0.100 -0.150  0.074  0.099  0.049  0.149  0.224  0.074  0.024 -0.075  0.249 -0.050 -0.000 -0.175 -0.000  0.323  0.323 -0.299  0.423  0.224  0.024 -0.150 -0.150 -0.150 -0.150 -0.075 -0.225 -0.100 -0.025 -0.075 -0.125 -0.175 -0.175  0.074 -0.025  0.049 -0.000 
 0.271 -0.053 -0.278 -0.103  0.046 -0.103 -0.228 -0.053 -0.103 -0.128 -0.053 -0.028 -0.153  0.096  0.121 -0.103 -0.153 -0.078 -0.028 -0.228 -0.228  0.146 -0.228 -0.228 -0.003 -0.203 -0.103 -0.153  0.146 -0.078 -0.078 -0.078 -0.302 -0.278  0.071 -0.078 -0.153 -0.128 -0.128 -0.203 -0.003 -0.178 -0.153 -0.003 -0.128 -0.053 -0.153 -0.153 -0.178 -0.128 -0.053 -0.053  0.021 -0.103 -0.153 -0.003  0.021 -0.128 -0.253 -0.253 -0.178 -0.003 -0.228 -0.103 -0.153  0.096  0.096  0.071  0.146  0.221  0.071  0.021 -0.078  0.221 -0.053 -0.003 -0.153 -0.003  0.320  0.320 -0.302  0.420  0.221  0.021 -0.153 -0.153 -0.153 -0.153 -0.078 -0.228 -0.103 -0.028 -0.078 -0.128 -0.178 -0.178  0.071 -0.028  0.046 -0.003 
 0.271 -0.053 -0.277 -0.103  0.047 -0.103 -0.227 -0.053 -0.103 -0.128 -0.053 -0.028 -0.152  0.097  0.122 -0.103 -0.152 -0.078 -0.028 -0.227 -0.227  0.146 -0.227 -0.227 -0.003 -0.202 -0.103 -0.152  0.097 -0.053 -0.078 -0.078 -0.302 -0.277  0.072 -0.078 -0.152 -0.128 -0.128 -0.202 -0.003 -0.177 -0.152 -0.003 -0.128 -0.053 -0.152 -0.152 -0.177 -0.128 -0.053 -0.053  0.022 -0.103 -0.152 -0.003  0.022 -0.152 -0.227 -0.252 -0.177 -0.003 -0.227 -0.103 -0.152  0.097  0.097  0.047  0.146  0.221  0.072  0.022 -0.053  0.221 -0.028 -0.003 -0.152 -0.028  0.321  0.321 -0.302  0.421  0.221  0.022 -0.152 -0.152 -0.152 -0.152 -0.078 -0.227 -0.103 -0.028 -0.078 -0.128 -0.177 -0.177  0.072 -0.028  0.047 -0.028 
 0.273 -0.051 -0.251 -0.101  0.048 -0.126 -0.226 -0.051 -0.101 -0.126 -0.076 -0.026 -0.151  0.098  0.123 -0.101 -0.151 -0.076 -0.026 -0.226 -0.226  0.148 -0.226 -0.226 -0.001 -0.201 -0.101 -0.151  0.098 -0.076 -0.076 -0.076 -0.300 -0.276  0.048 -0.076 -0.151 -0.151 -0.126 -0.201 -0.001 -0.176 -0.151 -0.001 -0.126 -0.051 -0.151 -0.151 -0.176 -0.126 -0.051 -0.026  0.023 -0.101 -0.151 -0.001  0.023 -0.151 -0.226 -0.251 -0.176 -0.001 -0.226 -0.101 -0.151  0.098  0.073  0.048  0.173  0.223  0.073  0.023 -0.051  0.223 -0.051 -0.001 -0.151 -0.051  0.322  0.322 -0.300  0.397  0.198  0.023 -0.151 -0.176 -0.151 -0.151 -0.101 -0.226 -0.101 -0.026 -0.076 -0.126 -0.151 -0.126  0.073 -0.026  0.048 -0.026 
 0.272 -0.052 -0.251 -0.102  0.048 -0.127 -0.226 -0.027 -0.102 -0.102 -0.077 -0.027 -0.151  0.123  0.123 -0.102 -0.151 -0.077 -0.027 -0.226 -0.226  0.147 -0.226 -0.226  0.023 -0.201 -0.102 -0.151  0.098 -0.077 -0.077 -0.077 -0.301 -0.276  0.048 -0.077 -0.151 -0.151 -0.127 -0.201  0.023 -0.176 -0.151 -0.002 -0.102 -0.052 -0.151 -0.151 -0.176 -0.127 -0.052 -0.027  0.023 -0.102 -0.127 -0.002  0.023 -0.127 -0.226 -0.251 -0.176 -0.002 -0.226 -0.077 -0.151  0.073  0.073  0.098  0.172  0.222  0.073  0.023 -0.052  0.247 -0.052 -0.002 -0.151 -0.052  0.347  0.322 -0.301  0.397  0.197  0.023 -0.151 -0.176 -0.151 -0.151 -0.102 -0.226 -0.102 -0.027 -0.077 -0.127 -0.151 -0.127  0.073 -0.027  0.048 -0.002 
 0.298 -0.050 -0.250 -0.125  0.049 -0.100 -0.225 -0.025 -0.100 -0.100 -0.075 -0.025 -0.150  0.124  0.149 -0.100 -0.150 -0.100 -0.025 -0.225 -0.225  0.149 -0.225 -0.225  0.024 -0.200 -0.100 -0.150  0.099 -0.075 -0.075 -0.100 -0.299 -0.275  0.049 -0.075 -0.150 -0.150 -0.100 -0.200  0.024 -0.175 -0.150 -0.000 -0.100 -0.050 -0.150 -0.150 -0.175 -0.125 -0.050 -0.025  0.024 -0.100 -0.125 -0.000  0.024 -0.125 -0.225 -0.250 -0.175 -0.025 -0.225 -0.075 -0.150  0.074  0.024  0.099  0.149  0.224  0.074  0.024 -0.050  0.274 -0.050 -0.050 -0.150 -0.050  0.348  0.323 -0.299  0.373  0.224  0.024 -0.175 -0.175 -0.150 -0.150 -0.100 -0.225 -0.100 -0.025 -0.075 -0.125 -0.150 -0.125  0.074 -0.025 -0.025 -0.000 
 0.298 -0.051 -0.250 -0.126  0.049 -0.101 -0.225 -0.026 -0.101 -0.101 -0.076 -0.026 -0.175  0.124  0.148 -0.101 -0.126 -0.101 -0.026 -0.225 -0.225  0.148 -0.225 -0.225  0.024 -0.200 -0.101 -0.150  0.099 -0.076 -0.076 -0.101 -0.300 -0.275  0.049 -0.076 -0.150 -0.150 -0.101 -0.200  0.024 -0.175 -0.150 -0.001 -0.101 -0.051 -0.150 -0.150 -0.175 -0.126 -0.051 -0.026  0.024 -0.101 -0.126 -0.001  0.024 -0.150 -0.225 -0.250 -0.175 -0.026 -0.225 -0.076 -0.150  0.074  0.024  0.074  0.148  0.223  0.074  0.049 -0.051  0.273 -0.051 -0.051 -0.150 -0.051  0.348  0.323 -0.300  0.373  0.198  0.024 -0.175 -0.175 -0.150 -0.150 -0.101 -0.225 -0.101 -0.026 -0.076 -0.126 -0.150 -0.126  0.074 -0.026 -0.051 -0.026 
 0.278  0.003 -0.171 -0.146  0.053 -0.071 -0.171 -0.096 -0.146 -0.071 -0.071  0.028 -0.146  0.053  0.103 -0.096 -0.046 -0.071  0.003 -0.171 -0.171  0.103 -0.196 -0.196  0.028 -0.121 -0.096 -0.096  0.003 -0.021 -0.046 -0.071 -0.246 -0.246  0.028 -0.046 -0.121 -0.171 -0.046 -0.171  0.053 -0.146 -0.121  0.028 -0.071 -0.071 -0.171 -0.096 -0.121 -0.071 -0.021 -0.046  0.053 -0.071 -0.046  0.003 -0.021 -0.171 -0.146 -0.221 -0.096  0.028 -0.146 -0.021 -0.146  0.003 -0.046  0.103  0.078  0.178  0.053 -0.046 -0.096  0.253 -0.096 -0.121 -0.096 -0.021  0.278  0.253 -0.221  0.302  0.153  0.053 -0.146 -0.171 -0.071 -0.096 -0.096 -0.171 -0.096  0.003 -0.146 -0.071 -0.121 -0.121  0.103 -0.096  0.003 -0.046 
 0.146  0.021 -0.103 -0.128  0.021 -0.028 -0.103 -0.078 -0.128 -0.053 -0.028 -0.003 -0.128 -0.003  0.021 -0.078 -0.028  0.021  0.046 -0.128 -0.128  0.096 -0.128 -0.103  0.046 -0.028 -0.028 -0.028  0.046 -0.028 -0.028 -0.128 -0.153 -0.153 -0.028 -0.003 -0.053 -0.103 -0.053 -0.128  0.071 -0.053 -0.078  0.046 -0.078 -0.053 -0.153 -0.028 -0.053 -0.028 -0.078 -0.028  0.096 -0.078 -0.053 -0.028 -0.078 -0.103 -0.103 -0.128 -0.028 -0.003 -0.078 -0.053 -0.078 -0.003 -0.003  0.021 -0.028  0.021 -0.003 -0.028 -0.053  0.096 -0.103 -0.103 -0.053 -0.028  0.121  0.221 -0.128  0.271  0.071 -0.003 -0.078 -0.128  0.021 -0.003 -0.003 -0.103 -0.053 -0.078 -0.078  0.021 -0.053 -0.078  0.021 -0.078 -0.003 -0.053 
 0.142  0.018 -0.107 -0.107  0.018 -0.007 -0.107 -0.082 -0.107 -0.057 -0.007 -0.032 -0.107  0.018 -0.007 -0.057 -0.032  0.043  0.068 -0.107 -0.132  0.043 -0.107 -0.082  0.043 -0.032  0.018 -0.007  0.043 -0.032 -0.057 -0.107 -0.132 -0.132  0.018  0.018 -0.057 -0.082 -0.032 -0.107  0.043 -0.032 -0.057  0.068 -0.082 -0.057 -0.132 -0.082 -0.082 -0.032 -0.082 -0.032  0.118 -0.082 -0.032 -0.032 -0.057 -0.107 -0.082 -0.082 -0.007 -0.007 -0.057 -0.032 -0.082 -0.007 -0.007  0.043 -0.007  0.018  0.018 -0.007 -0.007  0.068 -0.057 -0.057 -0.082 -0.057  0.043  0.267 -0.132  0.292  0.093 -0.057 -0.057 -0.107  0.018  0.018  0.043 -0.107 -0.032 -0.082 -0.057  0.018 -0.032 -0.082 -0.007 -0.082 -0.032 -0.007 
 0.118  0.043 -0.081 -0.081 -0.006 -0.006 -0.081 -0.056 -0.056 -0.031 -0.031 -0.031 -0.081 -0.031 -0.056 -0.031 -0.031  0.043  0.093 -0.081 -0.106  0.018 -0.081 -0.081  0.068 -0.006 -0.006  0.018  0.068 -0.006 -0.031 -0.081 -0.106 -0.106  0.043 -0.006 -0.031 -0.056 -0.056 -0.056  0.018 -0.006 -0.031  0.043 -0.081 -0.031 -0.106 -0.056 -0.081 -0.006 -0.106 -0.056  0.143 -0.081 -0.006 -0.056 -0.031 -0.106 -0.056 -0.056 -0.056 -0.006 -0.031 -0.006 -0.056 -0.031  0.018  0.093 -0.006  0.018 -0.006 -0.006  0.043  0.043 -0.031 -0.031 -0.056 -0.081 -0.081  0.143 -0.106  0.292  0.018 -0.031 -0.081 -0.081  0.018  0.043  0.043 -0.081 -0.006 -0.106 -0.081  0.043 -0.031 -0.056  0.018 -0.081 -0.006  0.018 
 0.075  0.050 -0.074 -0.074  0.000  0.000 -0.074 -0.024 -0.049 -0.024 -0.024 -0.049 -0.074 -0.049 -0.074 -0.049 -0.024  0.050  0.100 -0.074 -0.099  0.050 -0.099 -0.074  0.075  0.000  0.000  0.025  0.075  0.000 -0.024 -0.074 -0.099 -0.099  0.050  0.000 -0.049 -0.049 -0.049 -0.049  0.000  0.000 -0.024  0.025 -0.074 -0.024 -0.099 -0.049 -0.074 -0.024 -0.099 -0.049  0.125 -0.099  0.000 -0.049 -0.049 -0.099 -0.049 -0.049 -0.049  0.000 -0.024  0.000 -0.049  0.000  0.025  0.100 -0.024 -0.024  0.000  0.000  0.050  0.050 -0.024 -0.024 -0.049 -0.074 -0.074  0.150 -0.099  0.275  0.025 -0.024 -0.074 -0.074  0.000  0.050  0.025 -0.074  0.000 -0.099 -0.074  0.025 -0.024 -0.049  0.025 -0.049  0.000  0.025 
 0.063  0.038 -0.062 -0.062 -0.012  0.013 -0.087 -0.037 -0.062 -0.012 -0.037 -0.037 -0.087 -0.037 -0.087 -0.037 -0.012  0.063  0.088 -0.062 -0.087  0.063 -0.087 -0.062  0.063  0.013 -0.012  0.038  0.063 -0.012 -0.037 -0.062 -0.087 -0.087  0.038  0.013 -0.037 -0.062 -0.037 -0.037  0.013 -0.012 -0.012  0.013 -0.062 -0.037 -0.087 -0.062 -0.062 -0.012 -0.087 -0.062  0.138 -0.087  0.013 -0.037 -0.037 -0.087 -0.037 -0.087 -0.037  0.038 -0.012 -0.012 -0.037 -0.012  0.038  0.088 -0.037 -0.012  0.013  0.013  0.038  0.013  0.013 -0.037 -0.037 -0.062 -0.062  0.162 -0.087  0.237  0.013 -0.037 -0.062 -0.062  0.013  0.013  0.013 -0.037  0.013 -0.087 -0.062  0.038 -0.012 -0.062  0.013 -0.037  0.013 -0.012 
 0.093  0.043 -0.082 -0.057 -0.007  0.043 -0.082 -0.032 -0.057 -0.007 -0.032 -0.032 -0.082 -0.082 -0.082 -0.057 -0.007  0.068  0.068 -0.057 -0.082  0.068 -0.082 -0.082  0.043  0.018 -0.007  0.068  0.068 -0.007 -0.032 -0.057 -0.082 -0.082  0.043  0.018 -0.057 -0.057 -0.032 -0.007  0.018 -0.007 -0.032 -0.007 -0.057 -0.032 -0.082 -0.057 -0.057  0.018 -0.082 -0.082  0.142 -0.082  0.018 -0.057 -0.032 -0.082 -0.057 -0.082 -0.032  0.043 -0.007 -0.007 -0.032 -0.007  0.043  0.093 -0.032 -0.007  0.043  0.018  0.018 -0.007  0.018 -0.032 -0.032 -0.032 -0.057  0.118 -0.082  0.217 -0.007 -0.032 -0.057 -0.057 -0.007  0.018  0.018 -0.032  0.018 -0.082 -0.057  0.093 -0.007 -0.057  0.018 -0.032  0.018 -0.007 
 0.106  0.056 -0.068 -0.043 -0.018  0.031 -0.068 -0.018 -0.043  0.006 -0.043 -0.018 -0.068 -0.068 -0.068 -0.043 -0.018  0.031  0.031 -0.043 -0.068  0.056 -0.068 -0.068  0.056  0.006 -0.018  0.081  0.081 -0.018 -0.043 -0.043 -0.068 -0.068  0.056  0.031 -0.068 -0.043 -0.018  0.006  0.006  0.006  0.006  0.006 -0.068 -0.043 -0.068 -0.043 -0.043 -0.018 -0.068 -0.068  0.106 -0.068 -0.018 -0.043 -0.018 -0.068 -0.043 -0.068 -0.018 -0.018  0.006  0.006 -0.043  0.006  0.056  0.081 -0.018  0.006  0.056  0.031  0.031 -0.043  0.031 -0.018 -0.043 -0.018 -0.043  0.081 -0.068  0.206  0.006 -0.018 -0.068 -0.043 -0.018  0.006  0.006 -0.043  0.006 -0.068 -0.043  0.081  0.006 -0.043  0.006 -0.018  0.031  0.006 
 0.061  0.036 -0.063 -0.038 -0.038 -0.013 -0.063 -0.013 -0.063  0.011 -0.063 -0.013 -0.063 -0.063 -0.038 -0.038 -0.013  0.036  0.036 -0.038 -0.063  0.061 -0.038 -0.038  0.036 -0.013 -0.013  0.061  0.061 -0.013 -0.038 -0.038 -0.063 -0.063  0.011  0.036 -0.038 -0.038 -0.013 -0.038 -0.013  0.011  0.011  0.011 -0.063 -0.013 -0.063 -0.038 -0.038 -0.038 -0.038 -0.063  0.111 -0.063 -0.013 -0.038 -0.038 -0.063 -0.063 -0.063 -0.038 -0.038  0.036  0.036 -0.038 -0.013  0.036  0.036 -0.013  0.036  0.061  0.011  0.011 -0.038  0.036 -0.013 -0.038 -0.038 -0.013  0.111 -0.063  0.186  0.036 -0.013 -0.038 -0.038 -0.038  0.011 -0.013 -0.038  0.011 -0.063 -0.063  0.036 -0.013 -0.038 -0.013 -0.013  0.036 -0.013 
 0.068  0.018 -0.057 -0.032 -0.032 -0.007 -0.057 -0.007 -0.057  0.018 -0.032 -0.007 -0.032 -0.057 -0.032 -0.032 -0.032  0.043  0.018 -0.007 -0.057  0.043 -0.032 -0.032  0.043 -0.007 -0.007  0.068  0.068 -0.007 -0.032 -0.032 -0.057 -0.057  0.018 -0.007 -0.032 -0.032 -0.007 -0.007 -0.007  0.018 -0.007 -0.007 -0.057 -0.007 -0.057 -0.032 -0.032 -0.032 -0.007 -0.057  0.068 -0.057 -0.007 -0.032 -0.032 -0.057 -0.057 -0.057 -0.032 -0.032  0.018  0.043 -0.032 -0.007  0.018  0.018 -0.032  0.043  0.043  0.018  0.018 -0.007  0.043 -0.007 -0.032 -0.032 -0.032  0.142 -0.057  0.118  0.018 -0.007 -0.032 -0.032 -0.032 -0.007 -0.007 -0.032 -0.007 -0.057 -0.032  0.043 -0.007 -0.032 -0.032 -0.007  0.043 -0.007 
 0.070  0.020 -0.055 -0.030 -0.030  0.020 -0.055 -0.005 -0.055  0.020 -0.030 -0.005 -0.030 -0.055 -0.030 -0.030 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.030 -0.030 -0.055 -0.055  0.020 -0.005 -0.030 -0.030 -0.005  0.020 -0.005  0.020 -0.005 -0.005 -0.055 -0.005 -0.055 -0.030 -0.030 -0.030 -0.005 -0.055  0.070 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.055 -0.030  0.020  0.045 -0.030 -0.005  0.020  0.020 -0.030  0.045  0.045 -0.005  0.020 -0.005  0.045 -0.005 -0.030 -0.005 -0.030  0.120 -0.055  0.070  0.020 -0.030 -0.030 -0.030 -0.030 -0.005 -0.005 -0.030 -0.030 -0.055 -0.030  0.070 -0.030 -0.030 -0.030 -0.005  0.045 -0.005 
 0.073  0.048 -0.051 -0.026 -0.026  0.023 -0.051  0.023 -0.051  0.023 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026  0.023 -0.051 -0.026 -0.026 -0.026 -0.026 -0.026 -0.001 -0.051  0.048 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.023  0.048 -0.026 -0.001  0.023  0.023 -0.026  0.023  0.048 -0.001  0.023 -0.001  0.023 -0.001 -0.051 -0.001 -0.026  0.073 -0.051  0.048  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.073 -0.026 -0.026 -0.026 -0.001  0.048 -0.026 
 0.073  0.048 -0.051 -0.026 -0.026  0.023 -0.051  0.023 -0.051  0.023 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026  0.023 -0.051 -0.026 -0.026 -0.026 -0.026 -0.026 -0.001 -0.051  0.048 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.023  0.048 -0.026 -0.001  0.023  0.023 -0.026  0.023  0.048 -0.001  0.023 -0.001  0.023 -0.001 -0.051 -0.001 -0.026  0.073 -0.051  0.048  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.073 -0.026 -0.026 -0.026 -0.001  0.048 -0.026 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.022 -0.002  0.022 -0.027  0.022 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.022 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.022  0.047 -0.027 -0.002  0.022  0.022 -0.027  0.022  0.047 -0.002  0.022 -0.002  0.022 -0.002 -0.052 -0.002 -0.027  0.072 -0.052  0.047  0.022 -0.027 -0.002 -0.027 -0.027  0.022 -0.002 -0.027 -0.027 -0.052 -0.027  0.072 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.003 -0.003  0.022  0.022 -0.028  0.022  0.047  0.022  0.022 -0.003  0.022  0.022 -0.053 -0.003 -0.028  0.072 -0.053  0.047  0.022 -0.028 -0.003 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.003  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.003 -0.003  0.021  0.021 -0.003  0.021  0.046  0.021  0.021 -0.003  0.021  0.021 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.028  0.021 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.003  0.071 -0.028 -0.028 -0.028 -0.003  0.046 -0.028 
 0.071  0.046 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.004 -0.004  0.021  0.021  0.021  0.021  0.046  0.021  0.021 -0.004  0.021  0.021 -0.054 -0.004 -0.029  0.071 -0.054  0.046  0.021 -0.029  0.021 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.004  0.071 -0.029 -0.004 -0.029 -0.004  0.046 -0.029 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.062  0.037 -0.062 -0.062 -0.062 -0.012 -0.087  0.037 -0.087 -0.012 -0.012 -0.012 -0.062 -0.037 -0.062 -0.087 -0.062  0.037  0.037 -0.037 -0.087  0.087 -0.037 -0.062  0.037 -0.062  0.012  0.037  0.062 -0.062 -0.062  0.012 -0.087 -0.087 -0.012  0.037 -0.062 -0.037 -0.012 -0.012 -0.037  0.012 -0.012 -0.012 -0.037 -0.037 -0.062 -0.037 -0.062 -0.062 -0.012 -0.087  0.112 -0.087 -0.012 -0.087 -0.062 -0.087 -0.087 -0.087 -0.037 -0.012  0.087  0.012 -0.012 -0.012  0.037  0.012  0.037 -0.012  0.062  0.012 -0.012  0.012  0.012  0.012 -0.087 -0.037 -0.062  0.112 -0.087  0.137  0.012 -0.037  0.012 -0.037 -0.062  0.012 -0.012 -0.062 -0.037 -0.087 -0.037  0.062 -0.062  0.012 -0.012  0.037  0.037 -0.037 
 0.079  0.029 -0.095 -0.095 -0.095 -0.070 -0.145  0.004 -0.095 -0.045 -0.045 -0.070 -0.095  0.004 -0.095 -0.095 -0.095  0.004  0.054 -0.095 -0.145  0.129 -0.095 -0.095  0.154 -0.070 -0.045  0.029  0.079 -0.045 -0.070 -0.045 -0.120 -0.145  0.004  0.054 -0.070 -0.070 -0.070 -0.045 -0.070 -0.020 -0.020  0.004 -0.070 -0.070 -0.120 -0.045 -0.045 -0.070 -0.070 -0.120  0.104 -0.095  0.029 -0.095  0.004 -0.120 -0.095 -0.145 -0.070  0.029  0.029 -0.045 -0.045 -0.045  0.054  0.029 -0.020 -0.020  0.129  0.004 -0.020  0.029  0.004  0.029 -0.120 -0.095 -0.020  0.328 -0.145  0.254  0.054 -0.020  0.004 -0.020 -0.045 -0.045 -0.045 -0.095  0.029 -0.120 -0.070  0.054 -0.020 -0.020  0.029  0.029  0.054 -0.020 
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 0.185  0.011 -0.089 -0.114 -0.039 -0.039 -0.114 -0.089 -0.089 -0.064 -0.064 -0.039 -0.114 -0.014 -0.039 -0.039 -0.039  0.011  0.061 -0.089 -0.114  0.086 -0.139 -0.114  0.086 -0.039  0.011 -0.014  0.061  0.011  0.036 -0.089 -0.139 -0.139  0.011 -0.014 -0.039 -0.089 -0.014 -0.139  0.036 -0.014 -0.064  0.036 -0.064 -0.064 -0.139 -0.014 -0.089 -0.014 -0.139  0.061  0.111 -0.039 -0.039 -0.064 -0.064 -0.114 -0.089 -0.089 -0.089 -0.014 -0.064 -0.039 -0.064 -0.039 -0.014  0.011 -0.064  0.036 -0.089 -0.039 -0.014  0.011 -0.039 -0.039 -0.089 -0.064  0.011  0.235 -0.139  0.335  0.061 -0.039 -0.089 -0.089  0.011  0.011  0.036 -0.114 -0.039 -0.114 -0.064  0.036 -0.064 -0.039  0.061 -0.139 -0.014 -0.039 
 0.110  0.035 -0.089 -0.089 -0.014 -0.039 -0.089 -0.089 -0.064 -0.039 -0.039 -0.039 -0.089 -0.014 -0.039 -0.039 -0.014  0.035  0.085 -0.089 -0.114  0.010 -0.114 -0.089  0.085 -0.014  0.035  0.010  0.060  0.010  0.010 -0.089 -0.114 -0.114  0.035 -0.014 -0.014 -0.089 -0.014 -0.114  0.035  0.010 -0.039  0.010 -0.089 -0.039 -0.114 -0.039 -0.089  0.010 -0.114  0.010  0.135 -0.039 -0.014 -0.039 -0.064 -0.114 -0.064 -0.089 -0.064 -0.014 -0.039 -0.014 -0.064 -0.039 -0.014  0.060 -0.089  0.010 -0.064 -0.014  0.010  0.010 -0.064 -0.039 -0.064 -0.064 -0.064  0.160 -0.114  0.334  0.010 -0.039 -0.089 -0.089 -0.014  0.010  0.060 -0.089 -0.014 -0.089 -0.089  0.060 -0.039 -0.039  0.010 -0.089  0.010 -0.014 
 0.119  0.019 -0.081 -0.081 -0.006 -0.031 -0.081 -0.081 -0.081 -0.031 -0.031 -0.031 -0.081 -0.006 -0.081 -0.031 -0.031  0.044  0.094 -0.081 -0.106  0.019 -0.106 -0.081  0.094 -0.006  0.044  0.019  0.069  0.019 -0.031 -0.081 -0.106 -0.106  0.044 -0.031 -0.031 -0.056 -0.031 -0.081  0.019  0.019 -0.031  0.044 -0.081 -0.031 -0.106 -0.056 -0.081 -0.006 -0.106 -0.031  0.143 -0.056 -0.006 -0.031 -0.056 -0.106 -0.056 -0.081 -0.056  0.019 -0.031  0.019 -0.056 -0.056  0.019  0.094 -0.081 -0.031 -0.056 -0.006  0.019  0.019 -0.006 -0.031 -0.056 -0.056 -0.081  0.143 -0.106  0.293  0.019 -0.056 -0.081 -0.081 -0.006  0.019  0.019 -0.056 -0.006 -0.106 -0.081  0.044 -0.031 -0.056  0.019 -0.081 -0.006 -0.006 
 0.106  0.031 -0.069 -0.069  0.006  0.006 -0.094 -0.044 -0.069 -0.019 -0.019 -0.044 -0.094 -0.044 -0.069 -0.019 -0.019  0.056  0.081 -0.069 -0.094  0.056 -0.094 -0.069  0.081  0.006  0.006  0.031  0.056  0.006 -0.044 -0.069 -0.094 -0.094  0.056 -0.019 -0.019 -0.044 -0.044 -0.044  0.006 -0.019 -0.019  0.031 -0.069 -0.019 -0.094 -0.069 -0.069  0.006 -0.094 -0.044  0.155 -0.069  0.006 -0.044 -0.044 -0.094 -0.044 -0.094 -0.044  0.031 -0.019  0.031 -0.044 -0.044  0.031  0.106 -0.044 -0.019  0.006  0.006  0.031 -0.019  0.006 -0.019 -0.044 -0.069 -0.069  0.131 -0.094  0.255  0.031 -0.044 -0.069 -0.069  0.006  0.031  0.031 -0.044  0.006 -0.094 -0.069  0.056 -0.019 -0.044  0.006 -0.044  0.006 -0.019 
 0.109  0.034 -0.090 -0.065  0.009  0.009 -0.090 -0.040 -0.065 -0.015 -0.015 -0.040 -0.090 -0.040 -0.090 -0.015 -0.040  0.059  0.084 -0.065 -0.090  0.059 -0.090 -0.065  0.084  0.009  0.009  0.034  0.059  0.009 -0.040 -0.065 -0.090 -0.090  0.059 -0.015 -0.015 -0.065 -0.040 -0.040  0.009 -0.015 -0.015  0.034 -0.065 -0.015 -0.090 -0.065 -0.065  0.009 -0.090 -0.040  0.159 -0.090  0.009 -0.040 -0.040 -0.090 -0.040 -0.090 -0.040  0.009 -0.015 -0.015 -0.065 -0.015  0.034  0.084 -0.040 -0.015  0.009  0.009  0.034 -0.015  0.009 -0.015 -0.040 -0.065 -0.065  0.134 -0.090  0.259  0.034 -0.040 -0.065 -0.065  0.009  0.034  0.009 -0.040  0.009 -0.090 -0.065  0.059 -0.015 -0.040  0.009 -0.040  0.009 -0.015 
 0.091  0.041 -0.083 -0.058 -0.008 -0.008 -0.083 -0.033 -0.058 -0.008 -0.033 -0.033 -0.083 -0.058 -0.083 -0.033 -0.033  0.066  0.091 -0.058 -0.083  0.066 -0.083 -0.058  0.066  0.016 -0.008  0.041  0.066 -0.008 -0.033 -0.058 -0.083 -0.083  0.041  0.016 -0.033 -0.058 -0.033 -0.033  0.016 -0.008 -0.008  0.041 -0.058 -0.033 -0.083 -0.058 -0.058  0.016 -0.083 -0.083  0.116 -0.083  0.016 -0.058 -0.033 -0.083 -0.033 -0.083 -0.033  0.016 -0.008 -0.008 -0.058 -0.008  0.041  0.091 -0.033 -0.008  0.016  0.016  0.041 -0.008  0.016 -0.033 -0.033 -0.058 -0.058  0.141 -0.083  0.241  0.016 -0.033 -0.058 -0.058  0.016 -0.008  0.016 -0.033  0.016 -0.083 -0.058  0.066 -0.008 -0.058  0.016 -0.033  0.016 -0.008 
 0.098  0.048 -0.076 -0.051 -0.051  0.048 -0.076 -0.026 -0.051 -0.001 -0.026 -0.026 -0.076 -0.051 -0.076 -0.051 -0.051  0.073  0.073 -0.051 -0.076  0.073 -0.076 -0.076  0.073 -0.001 -0.001  0.073  0.073 -0.001 -0.026 -0.051 -0.076 -0.076  0.048  0.023 -0.051 -0.051 -0.026 -0.001  0.023 -0.001 -0.001 -0.001 -0.051 -0.051 -0.076 -0.051 -0.051  0.023 -0.076 -0.076  0.123 -0.076  0.023 -0.051 -0.026 -0.076 -0.026 -0.076 -0.026  0.023 -0.001 -0.001 -0.051 -0.001  0.048  0.073 -0.026 -0.001  0.048  0.023  0.023 -0.026  0.023 -0.026 -0.051 -0.026 -0.076  0.098 -0.076  0.223 -0.026 -0.026 -0.076 -0.051 -0.001 -0.001  0.023 -0.026  0.023 -0.076 -0.051  0.098 -0.001 -0.051  0.023 -0.026  0.023 -0.001 
 0.083  0.033 -0.067 -0.042 -0.042  0.058 -0.067 -0.017 -0.042  0.008 -0.042 -0.017 -0.042 -0.067 -0.067 -0.042 -0.042  0.033  0.033 -0.042 -0.067  0.058 -0.042 -0.042  0.033 -0.017  0.008  0.083  0.083 -0.017 -0.042 -0.042 -0.067 -0.067  0.058  0.008 -0.067 -0.042 -0.017  0.008  0.008  0.008 -0.017 -0.017 -0.067 -0.042 -0.067 -0.042 -0.042 -0.042 -0.042 -0.067  0.058 -0.067 -0.017 -0.042 -0.017 -0.067 -0.067 -0.067 -0.017  0.008  0.008  0.008 -0.042  0.008  0.033  0.058 -0.042  0.033  0.033  0.008  0.008 -0.042  0.033 -0.017 -0.042 -0.017 -0.042  0.108 -0.067  0.133  0.008 -0.017 -0.067 -0.042 -0.042  0.008  0.033 -0.017 -0.017 -0.067 -0.042  0.083  0.008 -0.042  0.033 -0.017  0.033  0.008 
 0.061  0.036 -0.063 -0.038 -0.038  0.061 -0.063 -0.013 -0.038  0.011 -0.013 -0.013 -0.038 -0.063 -0.063 -0.038 -0.038  0.036  0.036 -0.013 -0.063  0.061 -0.038 -0.038  0.036 -0.038  0.011  0.086  0.061 -0.013 -0.063 -0.038 -0.063 -0.063  0.061  0.011 -0.063 -0.038 -0.013  0.036  0.011  0.011 -0.013 -0.013 -0.063 -0.038 -0.063 -0.013 -0.038 -0.038 -0.013 -0.063  0.036 -0.063 -0.013 -0.063 -0.013 -0.063 -0.063 -0.063  0.011 -0.013  0.011  0.011 -0.038  0.011  0.036  0.061 -0.038  0.036  0.036  0.011  0.011 -0.013  0.036  0.011 -0.063 -0.013 -0.038  0.111 -0.063  0.111  0.011 -0.038 -0.038 -0.038 -0.038  0.036  0.011 -0.038 -0.013 -0.063 -0.013  0.061  0.011 -0.038  0.011 -0.013  0.036  0.011 
 0.070  0.070 -0.054 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.029 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.029 -0.054 -0.054  0.020 -0.004 -0.054 -0.029 -0.004  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.054 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.045  0.045 -0.029 -0.004  0.020  0.020 -0.029  0.045  0.045 -0.004  0.020 -0.004  0.045  0.020 -0.054 -0.004 -0.029  0.095 -0.054  0.070  0.020 -0.029 -0.029 -0.029 -0.029  0.045 -0.004 -0.029 -0.029 -0.054 -0.029  0.070 -0.004 -0.029 -0.029 -0.004  0.045 -0.004 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053  0.022 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022  0.022 -0.003  0.022  0.047 -0.003  0.022 -0.003  0.047  0.022 -0.053 -0.003 -0.028  0.097 -0.053  0.047  0.022 -0.028  0.022 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.028  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.003 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.004 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.020  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.004 -0.004  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.004  0.020  0.020 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.004  0.070 -0.029 -0.004 -0.029 -0.004  0.045 -0.029 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
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 0.111 -0.038 -0.213 -0.038  0.236 -0.013 -0.163 -0.063  0.086 -0.088  0.261 -0.088 -0.138  0.011  0.036 -0.163  0.036 -0.063  0.061 -0.188 -0.088  0.385 -0.188 -0.163 -0.013 -0.063  0.036  0.011  0.111 -0.038 -0.063 -0.138 -0.263 -0.113  0.111 -0.113 -0.013 -0.138 -0.113 -0.088 -0.038 -0.038 -0.163  0.310 -0.088  0.111 -0.188 -0.038 -0.138 -0.063  0.011  0.236  0.061 -0.113 -0.138 -0.063  0.036  0.011 -0.188 -0.213 -0.038  0.036 -0.088 -0.213 -0.038  0.036  0.061 -0.113 -0.088 -0.038  0.036  0.161 -0.063  0.136 -0.038  0.061 -0.113 -0.038 -0.063  0.161 -0.287  0.460  0.036  0.011 -0.038 -0.138  0.011 -0.013  0.161 -0.188 -0.038 -0.013 -0.013 -0.113 -0.038 -0.088  0.011 -0.088 -0.038  0.136 
 0.150 -0.049 -0.223 -0.049  0.250 -0.049 -0.124 -0.074  0.076 -0.099  0.225 -0.049 -0.148  0.001  0.051 -0.173  0.051 -0.074  0.051 -0.173 -0.099  0.375 -0.148 -0.148  0.001 -0.074  0.026 -0.024  0.126 -0.024 -0.074 -0.148 -0.273 -0.124  0.101 -0.024 -0.024 -0.124 -0.124 -0.099 -0.049 -0.049 -0.173  0.300 -0.074  0.126 -0.198 -0.049 -0.148 -0.074  0.026  0.175  0.026 -0.074 -0.148 -0.049  0.051  0.001 -0.223 -0.223 -0.049  0.026 -0.099 -0.223 -0.049  0.051  0.051 -0.124 -0.074  0.026  0.026  0.150 -0.074  0.126 -0.049  0.051 -0.124  0.001 -0.074  0.175 -0.298  0.449  0.076  0.001 -0.049 -0.148  0.001 -0.024  0.150 -0.198 -0.024  0.026 -0.024 -0.124 -0.049 -0.074  0.001 -0.099 -0.049  0.150 
 0.149 -0.075 -0.225 -0.100  0.224 -0.050 -0.125 -0.075  0.074 -0.125  0.224 -0.050 -0.150 -0.000  0.099 -0.175  0.049 -0.100  0.049 -0.175 -0.150  0.373 -0.150 -0.150 -0.000 -0.075  0.024 -0.025  0.124 -0.050 -0.050 -0.200 -0.275 -0.125  0.074 -0.025 -0.025 -0.150 -0.125 -0.125 -0.050 -0.075 -0.175  0.274 -0.050  0.099 -0.200 -0.025 -0.150 -0.100  0.024  0.174  0.024 -0.025 -0.150 -0.050  0.074 -0.000 -0.200 -0.225 -0.050 -0.025 -0.125 -0.225 -0.050  0.049  0.024 -0.125 -0.050  0.049  0.074  0.124 -0.050  0.124 -0.075  0.049 -0.125  0.024 -0.050  0.199 -0.299  0.423  0.099 -0.025 -0.075 -0.125 -0.000 -0.025  0.174 -0.200 -0.025 -0.000 -0.000 -0.125 -0.100 -0.075 -0.025 -0.050 -0.075  0.174 
 0.149 -0.100 -0.224 -0.100  0.199 -0.050 -0.125 -0.075  0.075 -0.125  0.224 -0.050 -0.149  0.025  0.100 -0.174  0.075 -0.100  0.050 -0.174 -0.199  0.374 -0.174 -0.149  0.000 -0.075  0.025 -0.025  0.125 -0.050 -0.050 -0.224 -0.274 -0.125  0.075  0.000 -0.025 -0.149 -0.125 -0.125 -0.050 -0.075 -0.174  0.274 -0.050  0.100 -0.199 -0.025 -0.149 -0.100  0.025  0.199  0.025 -0.050 -0.149 -0.025  0.050  0.000 -0.199 -0.224 -0.050 -0.025 -0.125 -0.224 -0.050  0.050  0.025 -0.125 -0.050  0.050  0.075  0.125 -0.050  0.125 -0.050  0.050 -0.125  0.025 -0.050  0.199 -0.299  0.424  0.100  0.000 -0.075 -0.125  0.000 -0.025  0.174 -0.199 -0.025 -0.025  0.000 -0.125 -0.075 -0.075 -0.025 -0.050 -0.075  0.174 
 0.146 -0.103 -0.227 -0.128  0.171 -0.053 -0.128 -0.078  0.072 -0.128  0.196 -0.053 -0.152  0.047  0.146 -0.152  0.072 -0.103  0.047 -0.177 -0.202  0.371 -0.152 -0.152 -0.003 -0.103  0.022 -0.028  0.122 -0.053 -0.053 -0.252 -0.277 -0.128  0.072 -0.003 -0.028 -0.152 -0.128 -0.128 -0.053 -0.078 -0.177  0.271 -0.053  0.097 -0.177 -0.028 -0.152 -0.103  0.022  0.196  0.047 -0.053 -0.152 -0.028  0.047 -0.003 -0.177 -0.227 -0.053 -0.078 -0.128 -0.227 -0.053  0.047  0.022 -0.103 -0.028  0.097  0.072  0.122 -0.053  0.122 -0.053  0.022 -0.152  0.047 -0.028  0.221 -0.302  0.421  0.122 -0.003 -0.103 -0.128 -0.003 -0.028  0.171 -0.202 -0.028 -0.028 -0.003 -0.128 -0.078 -0.078 -0.003 -0.053 -0.103  0.196 
 0.142 -0.107 -0.231 -0.082  0.192 -0.057 -0.132 -0.082  0.093 -0.132  0.142 -0.057 -0.156  0.043  0.142 -0.156  0.068 -0.107  0.043 -0.181 -0.206  0.367 -0.156 -0.181 -0.007 -0.107  0.018 -0.032  0.093 -0.057 -0.057 -0.256 -0.281 -0.132  0.068 -0.007 -0.032 -0.156 -0.132 -0.132 -0.057 -0.107 -0.181  0.267 -0.057  0.118 -0.156 -0.032 -0.156 -0.107  0.018  0.192  0.043 -0.057 -0.156 -0.032  0.068 -0.007 -0.181 -0.231 -0.057 -0.082 -0.132 -0.231 -0.057  0.043  0.018 -0.107 -0.007  0.118  0.093  0.118 -0.057  0.118 -0.057  0.018 -0.156  0.043 -0.032  0.217 -0.306  0.417  0.142  0.018 -0.107 -0.132 -0.007 -0.032  0.167 -0.206 -0.032 -0.032 -0.007 -0.132 -0.082 -0.082  0.018 -0.057 -0.107  0.192 
 0.138 -0.112 -0.236 -0.087  0.187 -0.062 -0.137 -0.087  0.088 -0.137  0.138 -0.037 -0.161  0.063  0.187 -0.161  0.063 -0.112  0.038 -0.186 -0.211  0.362 -0.161 -0.186  0.013 -0.112  0.013 -0.037  0.088 -0.062 -0.062 -0.286 -0.286 -0.137  0.063 -0.012 -0.037 -0.137 -0.137 -0.137 -0.012 -0.112 -0.137  0.237 -0.062  0.113 -0.161 -0.037 -0.161 -0.087  0.013  0.187  0.038 -0.062 -0.161 -0.012  0.063 -0.012 -0.186 -0.236 -0.062 -0.112 -0.137 -0.161 -0.062  0.038 -0.012 -0.087  0.013  0.138  0.088  0.138 -0.062  0.138 -0.112  0.013 -0.137  0.038 -0.037  0.237 -0.311  0.412  0.187  0.038 -0.112 -0.137 -0.012 -0.062  0.138 -0.211 -0.037 -0.037 -0.012 -0.137 -0.112 -0.087  0.038 -0.062 -0.112  0.187 
 0.138 -0.111 -0.236 -0.086  0.188 -0.061 -0.136 -0.086  0.088 -0.136  0.138 -0.036 -0.161  0.063  0.188 -0.161  0.063 -0.111  0.038 -0.186 -0.211  0.362 -0.161 -0.186 -0.011 -0.111  0.013 -0.036  0.088 -0.061 -0.061 -0.285 -0.285 -0.136  0.063 -0.011 -0.036 -0.186 -0.136 -0.136 -0.011 -0.111 -0.136  0.238 -0.061  0.113 -0.161 -0.036 -0.161 -0.086  0.013  0.163  0.038 -0.061 -0.161  0.013  0.063 -0.011 -0.186 -0.236 -0.061 -0.111 -0.136 -0.161 -0.061  0.038 -0.011 -0.086  0.013  0.163  0.088  0.138 -0.036  0.113 -0.111 -0.011 -0.136  0.038 -0.036  0.287 -0.310  0.412  0.188  0.038 -0.111 -0.136 -0.036 -0.061  0.113 -0.211 -0.036 -0.011 -0.011 -0.136 -0.111 -0.086  0.063 -0.061 -0.111  0.188 
 0.137 -0.112 -0.237 -0.112  0.137 -0.037 -0.137 -0.087  0.087 -0.137  0.137  0.012 -0.137  0.062  0.212 -0.162  0.062 -0.112  0.037 -0.187 -0.262  0.361 -0.137 -0.187 -0.037 -0.137 -0.012 -0.037  0.087 -0.062 -0.062 -0.286 -0.286 -0.137  0.062 -0.012 -0.012 -0.187 -0.137 -0.137 -0.012 -0.112 -0.137  0.237 -0.062  0.112 -0.187 -0.012 -0.162 -0.087  0.012  0.162  0.037 -0.062 -0.162  0.037  0.062 -0.012 -0.187 -0.262 -0.062 -0.112 -0.137 -0.162 -0.087  0.062 -0.037 -0.087 -0.037  0.162  0.062  0.087 -0.037  0.112 -0.112 -0.012 -0.162  0.037 -0.037  0.286 -0.311  0.411  0.187  0.037 -0.112 -0.137 -0.037 -0.062  0.112 -0.212 -0.037 -0.012 -0.012 -0.137 -0.112 -0.087  0.087 -0.112 -0.137  0.187 
 0.153 -0.046 -0.170 -0.145  0.104 -0.071 -0.121 -0.121  0.079 -0.121  0.004  0.029 -0.121  0.104  0.129 -0.121  0.004 -0.071  0.104 -0.170 -0.245  0.303 -0.096 -0.121  0.029 -0.096 -0.046 -0.021  0.054 -0.021 -0.021 -0.220 -0.220 -0.170  0.104 -0.071  0.029 -0.170 -0.121 -0.096  0.029 -0.096 -0.071  0.178 -0.071  0.029 -0.170  0.029 -0.096 -0.046 -0.021  0.104  0.079 -0.046 -0.096  0.054  0.054 -0.021 -0.145 -0.195 -0.021 -0.071 -0.121 -0.145 -0.046  0.004 -0.021 -0.071 -0.046  0.104  0.054  0.054  0.029  0.178 -0.071 -0.046 -0.145  0.004 -0.021  0.228 -0.245  0.328  0.104  0.054 -0.071 -0.096 -0.046 -0.021  0.129 -0.195 -0.021 -0.021  0.054 -0.071 -0.071 -0.121  0.153 -0.071 -0.071  0.129 
 0.123  0.023 -0.102 -0.102  0.098 -0.052 -0.077 -0.102  0.023 -0.077 -0.002 -0.052 -0.077  0.048  0.073 -0.052 -0.027 -0.027  0.098 -0.102 -0.151  0.197 -0.102 -0.102  0.023 -0.052  0.048  0.023  0.073 -0.002  0.023 -0.127 -0.151 -0.127  0.147 -0.002 -0.077 -0.102 -0.027 -0.102 -0.052 -0.027 -0.027  0.123 -0.052 -0.027 -0.127  0.023 -0.002 -0.027 -0.077 -0.002  0.123  0.023 -0.052 -0.027 -0.027 -0.077 -0.102 -0.102  0.023  0.023 -0.077 -0.077 -0.052 -0.002  0.023 -0.002 -0.052 -0.002 -0.052 -0.002 -0.002  0.098 -0.052 -0.052 -0.052 -0.127 -0.052  0.172 -0.151  0.222 -0.002 -0.002 -0.127 -0.077 -0.002  0.048  0.048 -0.127 -0.027 -0.052 -0.002  0.023 -0.027 -0.102  0.073 -0.127  0.023  0.098 
 0.114  0.039 -0.110 -0.085  0.114 -0.010 -0.060 -0.085  0.039 -0.060  0.014 -0.060 -0.060  0.064  0.014 -0.060 -0.035 -0.010  0.089 -0.085 -0.135  0.189 -0.110 -0.085 -0.010 -0.035  0.064  0.014  0.089  0.014  0.039 -0.110 -0.135 -0.110  0.164 -0.060 -0.060 -0.085 -0.035 -0.085 -0.035 -0.010 -0.010  0.064 -0.035 -0.035 -0.110  0.039  0.014 -0.035 -0.060  0.014  0.139 -0.060 -0.035 -0.035 -0.010 -0.110 -0.085 -0.085  0.039 -0.010 -0.060 -0.060 -0.035  0.014  0.014  0.014 -0.060 -0.035 -0.035  0.014  0.014  0.064 -0.035 -0.035 -0.035 -0.110 -0.085  0.189 -0.135  0.264 -0.035 -0.035 -0.110 -0.060  0.014  0.064  0.039 -0.110 -0.010 -0.060  0.014  0.039 -0.010 -0.110  0.064 -0.110  0.039  0.039 
 0.120  0.045 -0.079 -0.054  0.070 -0.004 -0.029 -0.079 -0.029 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029 -0.029 -0.004  0.095 -0.079 -0.104  0.120 -0.104 -0.054 -0.004 -0.004  0.070  0.045  0.070  0.045 -0.004 -0.079 -0.104 -0.104  0.120 -0.029 -0.054 -0.054 -0.054 -0.079 -0.004  0.020 -0.054  0.045 -0.054 -0.054 -0.104  0.070 -0.004 -0.029 -0.079 -0.029  0.120 -0.054 -0.004 -0.004 -0.079 -0.104 -0.079 -0.104  0.020 -0.004 -0.029 -0.029 -0.054  0.020 -0.004  0.020 -0.079 -0.029 -0.029  0.020 -0.004  0.045 -0.029 -0.004 -0.029 -0.104 -0.079  0.145 -0.104  0.220 -0.004 -0.004 -0.079 -0.029 -0.004  0.070  0.020 -0.079 -0.004 -0.029 -0.029  0.045 -0.029 -0.079  0.070 -0.079 -0.004 -0.029 
 0.154  0.054 -0.070 -0.070  0.054  0.004 -0.070 -0.070 -0.020 -0.045  0.004 -0.020 -0.070 -0.045 -0.070 -0.020 -0.020 -0.020  0.079 -0.070 -0.095  0.154 -0.095 -0.070 -0.020  0.004  0.054  0.079  0.079  0.054  0.004 -0.070 -0.095 -0.095  0.104 -0.020 -0.045 -0.070 -0.070 -0.070 -0.020  0.004 -0.045  0.029 -0.070 -0.045 -0.095  0.079  0.004 -0.020 -0.070 -0.020  0.154 -0.045  0.004  0.004 -0.070 -0.095 -0.070 -0.095  0.029 -0.020 -0.020 -0.045 -0.045  0.029  0.029  0.029 -0.045 -0.020 -0.045  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.070 -0.070  0.104 -0.095  0.204  0.004 -0.020 -0.070 -0.020  0.004  0.054 -0.020 -0.070  0.004 -0.045 -0.045  0.004 -0.020 -0.070  0.054 -0.070  0.004 -0.020 
 0.140  0.040 -0.084 -0.059  0.040  0.040 -0.059 -0.034 -0.059 -0.034 -0.034 -0.034 -0.059 -0.059 -0.059 -0.009 -0.009  0.015  0.090 -0.059 -0.084  0.165 -0.084 -0.059  0.015 -0.009  0.065  0.090  0.065  0.040 -0.034 -0.059 -0.084 -0.084  0.090 -0.034 -0.034 -0.084 -0.084 -0.084 -0.034 -0.009 -0.034 -0.034 -0.059 -0.034 -0.084  0.065  0.015 -0.034 -0.084 -0.034  0.165 -0.059  0.015 -0.009 -0.059 -0.084 -0.059 -0.084 -0.009 -0.009 -0.009 -0.034 -0.059  0.040  0.015  0.065 -0.034  0.015 -0.034  0.015  0.015 -0.009 -0.034  0.015 -0.009 -0.059 -0.059  0.115 -0.084  0.140  0.040 -0.034 -0.059 -0.034 -0.034  0.065 -0.034 -0.059  0.015 -0.034 -0.059 -0.009 -0.009 -0.059  0.040 -0.034 -0.009 -0.034 
 0.120  0.045 -0.080 -0.055  0.045  0.045 -0.055 -0.030 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.005 -0.030  0.070 -0.055 -0.080  0.169 -0.080 -0.055  0.020 -0.005  0.070  0.095  0.070  0.070 -0.030 -0.055 -0.080 -0.080  0.095 -0.030 -0.055 -0.080 -0.080 -0.080 -0.030 -0.005 -0.030 -0.030 -0.055 -0.030 -0.080  0.070  0.020 -0.055 -0.080 -0.030  0.144 -0.055  0.020 -0.005 -0.055 -0.080 -0.055 -0.080 -0.005 -0.030 -0.005 -0.030 -0.055  0.045  0.020  0.045 -0.030 -0.005 -0.030  0.020  0.045 -0.055 -0.030  0.020 -0.005 -0.055 -0.055  0.095 -0.080  0.144  0.020 -0.030 -0.055 -0.030 -0.030  0.070 -0.030 -0.055  0.020 -0.030 -0.055 -0.005 -0.005 -0.055  0.045 -0.055 -0.005 -0.030 
 0.125  0.025 -0.074 -0.049  0.050  0.025 -0.049 -0.024 -0.049  0.000 -0.049 -0.024 -0.024 -0.049 -0.049 -0.024 -0.024 -0.024  0.050 -0.049 -0.074  0.150 -0.074 -0.049  0.025  0.000  0.050  0.100  0.050  0.075 -0.024 -0.049 -0.074 -0.074  0.075 -0.024 -0.074 -0.074 -0.049 -0.049 -0.024  0.000 -0.024 -0.024 -0.049 -0.049 -0.074  0.075  0.000 -0.049 -0.074 -0.024  0.175 -0.074  0.000  0.000 -0.049 -0.074 -0.049 -0.074  0.000 -0.024  0.000 -0.024 -0.049  0.025  0.025  0.025 -0.024 -0.024 -0.024  0.025  0.050 -0.049 -0.049 -0.024 -0.024 -0.049 -0.074  0.050 -0.074  0.150 -0.024  0.000 -0.049 -0.049 -0.024  0.050 -0.024 -0.049  0.000 -0.049 -0.024  0.000  0.000 -0.049  0.025 -0.049  0.025 -0.049 
 0.106  0.006 -0.069 -0.044  0.006  0.031 -0.069 -0.019 -0.069  0.006 -0.019 -0.019 -0.044 -0.044 -0.019 -0.019 -0.019  0.006  0.006 -0.019 -0.069  0.106 -0.069 -0.044  0.031  0.006  0.031  0.081  0.056  0.031 -0.019 -0.044 -0.069 -0.069  0.006 -0.019 -0.069 -0.069 -0.044 -0.019 -0.044  0.006 -0.019 -0.044 -0.044 -0.044 -0.069  0.056 -0.019 -0.044 -0.044 -0.069  0.180 -0.069  0.006 -0.019 -0.044 -0.069 -0.044 -0.069  0.006 -0.044 -0.019  0.006 -0.044  0.006  0.031  0.056  0.006  0.006  0.006  0.031  0.056 -0.019 -0.044 -0.019 -0.019 -0.044 -0.069  0.081 -0.069  0.155 -0.044  0.006 -0.044 -0.044 -0.019  0.031 -0.019 -0.069  0.006 -0.069 -0.044  0.006 -0.019 -0.069  0.006 -0.019  0.031 -0.044 
 0.066  0.016 -0.058 -0.033 -0.008  0.041 -0.058 -0.008 -0.058  0.016 -0.033 -0.033 -0.033 -0.033 -0.033 -0.033 -0.033  0.016 -0.033 -0.008 -0.058  0.116 -0.058 -0.058  0.041 -0.033 -0.008  0.066  0.091  0.016 -0.033 -0.033 -0.058 -0.058 -0.008 -0.008 -0.058 -0.058 -0.033 -0.008 -0.033  0.016 -0.033 -0.033 -0.058 -0.033 -0.058 -0.008 -0.033 -0.033 -0.033 -0.058  0.116 -0.058 -0.008 -0.058 -0.033 -0.058 -0.033 -0.058 -0.008 -0.058 -0.008  0.016 -0.033 -0.008  0.016  0.041 -0.008  0.016 -0.008  0.041  0.041 -0.008 -0.033 -0.008 -0.033 -0.033 -0.058  0.091 -0.058  0.141 -0.033 -0.008 -0.033 -0.033 -0.033  0.016 -0.008 -0.033  0.016 -0.058 -0.033  0.016 -0.008 -0.058 -0.033 -0.008  0.041 -0.033 
 0.070  0.020 -0.054 -0.029 -0.004  0.020 -0.054 -0.004 -0.054 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029 -0.054 -0.029 -0.004 -0.029 -0.029 -0.054  0.120 -0.054 -0.054  0.045 -0.029 -0.004  0.070  0.120  0.020 -0.029 -0.029 -0.054 -0.054 -0.004 -0.004 -0.054 -0.054 -0.029 -0.004 -0.029  0.020 -0.029 -0.029 -0.054 -0.029 -0.054 -0.004 -0.029 -0.029 -0.029 -0.054  0.045 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.004 -0.054 -0.004  0.020 -0.029 -0.004  0.020  0.020 -0.004 -0.029  0.020  0.045  0.020 -0.004 -0.054 -0.004 -0.029 -0.029 -0.054  0.095 -0.054  0.145 -0.029 -0.004 -0.029 -0.029 -0.029  0.020 -0.004 -0.029  0.020 -0.054 -0.029  0.020 -0.004 -0.054 -0.029  0.020  0.045 -0.029 
 0.097  0.022 -0.052 -0.027 -0.027  0.047 -0.052 -0.002 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027 -0.002 -0.052 -0.027 -0.027  0.097 -0.052 -0.052  0.047 -0.027 -0.002  0.072  0.122 -0.002 -0.027 -0.027 -0.052 -0.052 -0.002 -0.002 -0.052 -0.052 -0.052  0.022 -0.027  0.022 -0.052 -0.027 -0.052 -0.027 -0.052 -0.027 -0.027 -0.027 -0.027 -0.052 -0.002 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.052 -0.002  0.022 -0.027 -0.002  0.022  0.022 -0.002 -0.027  0.022  0.022  0.022 -0.002 -0.052 -0.027 -0.052 -0.002 -0.052  0.047 -0.052  0.072 -0.027 -0.052 -0.027 -0.027 -0.027  0.022 -0.002 -0.027 -0.002 -0.052 -0.027  0.047 -0.027 -0.027 -0.027  0.022  0.022 -0.027 
 0.098  0.023 -0.052 -0.027 -0.027  0.048 -0.052 -0.002 -0.052 -0.002 -0.027 -0.027 -0.027 -0.052 -0.027 -0.052 -0.027 -0.002 -0.052 -0.027 -0.027  0.098 -0.052 -0.052  0.048 -0.027 -0.002  0.073  0.123 -0.002 -0.027 -0.027 -0.052 -0.052 -0.002 -0.002 -0.052 -0.052 -0.052  0.023 -0.027  0.023 -0.052 -0.027 -0.052 -0.027 -0.052 -0.027 -0.027 -0.027 -0.027 -0.052 -0.002 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.052 -0.002  0.023 -0.027 -0.002  0.023  0.023 -0.002 -0.027  0.023  0.023  0.023 -0.002 -0.052 -0.027 -0.052 -0.002 -0.052  0.073 -0.052  0.073 -0.002 -0.052 -0.027 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.052 -0.027  0.048 -0.027 -0.027 -0.027  0.023  0.023 -0.027 
 0.098  0.048 -0.051 -0.026 -0.026  0.048 -0.051  0.023 -0.051 -0.001 -0.026 -0.026 -0.026 -0.026 -0.026 -0.051 -0.026 -0.001 -0.051 -0.026 -0.026  0.098 -0.051 -0.051  0.048 -0.026 -0.001  0.073  0.123 -0.001 -0.026 -0.026 -0.051 -0.051 -0.001 -0.001 -0.051 -0.051 -0.051  0.023 -0.026  0.023 -0.051 -0.001 -0.051 -0.026 -0.026 -0.026 -0.026 -0.026 -0.026 -0.051 -0.001 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.051 -0.001  0.023 -0.026 -0.001  0.023  0.023 -0.001 -0.026  0.023  0.023  0.023 -0.001 -0.051 -0.026 -0.051 -0.001 -0.051  0.073 -0.051  0.048 -0.001 -0.051 -0.026 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.048 -0.026 -0.051 -0.026  0.023  0.023 -0.026 
 0.099  0.049 -0.051 -0.026 -0.026  0.049 -0.051  0.024 -0.051 -0.001 -0.026 -0.026 -0.026 -0.001 -0.026 -0.051 -0.026 -0.001 -0.051 -0.026 -0.026  0.099 -0.051 -0.051  0.049 -0.026 -0.001  0.049  0.124 -0.001 -0.026 -0.001 -0.051 -0.051 -0.001 -0.001 -0.051 -0.051 -0.051  0.024 -0.026  0.024 -0.051 -0.001 -0.051 -0.026 -0.026 -0.026 -0.026 -0.026 -0.026 -0.051 -0.001 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.051 -0.001  0.024 -0.001 -0.001 -0.001  0.024 -0.001 -0.026  0.024  0.049  0.024 -0.001 -0.051 -0.001 -0.051 -0.001 -0.051  0.074 -0.051  0.049 -0.001 -0.051 -0.026 -0.026 -0.026  0.024 -0.001 -0.026 -0.026 -0.051 -0.001  0.049 -0.026 -0.051 -0.026  0.024  0.024 -0.026 
 0.098  0.048 -0.026 -0.026 -0.026  0.048 -0.051  0.023 -0.051 -0.001 -0.026 -0.026 -0.026 -0.001 -0.026 -0.051 -0.026 -0.001 -0.051 -0.026 -0.026  0.098 -0.051 -0.051  0.048 -0.026 -0.001  0.048  0.123 -0.026 -0.026 -0.001 -0.051 -0.051 -0.001 -0.001 -0.051 -0.051 -0.026  0.023 -0.026  0.023 -0.051 -0.001 -0.026 -0.026 -0.026 -0.026 -0.026 -0.026 -0.001 -0.051 -0.001 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.051 -0.001  0.023 -0.001 -0.001 -0.001  0.023  0.048 -0.026  0.023  0.023  0.023 -0.001 -0.051 -0.001 -0.051 -0.001 -0.051  0.073 -0.051  0.048 -0.001 -0.051 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.001  0.048 -0.026 -0.026 -0.026  0.023  0.023 -0.026 
 0.101  0.051 -0.024 -0.024 -0.024  0.051 -0.049  0.026 -0.049  0.001 -0.024 -0.024 -0.024 -0.024 -0.024 -0.049 -0.024  0.001 -0.049 -0.024 -0.024  0.076 -0.049 -0.049  0.051 -0.024  0.001  0.051  0.126 -0.024 -0.024  0.001 -0.049 -0.049  0.001  0.001 -0.049 -0.049 -0.024  0.001 -0.024  0.026 -0.049  0.001 -0.024 -0.024 -0.024 -0.024 -0.024 -0.024  0.001 -0.049  0.001 -0.049  0.001 -0.049 -0.024 -0.049 -0.049 -0.049 -0.024 -0.049  0.001  0.026  0.001 -0.024  0.001  0.026  0.026 -0.024  0.001  0.026  0.026  0.001 -0.049  0.001 -0.049  0.001 -0.049  0.076 -0.049  0.026  0.001 -0.049  0.001 -0.024 -0.024  0.026  0.001 -0.024 -0.024 -0.049  0.001  0.051 -0.024 -0.024 -0.024  0.026  0.026 -0.024 
 0.081  0.056 -0.019 -0.019 -0.019  0.031 -0.044  0.031 -0.044  0.006 -0.019 -0.019 -0.019 -0.019 -0.019 -0.044 -0.019  0.006 -0.044 -0.019 -0.044  0.056 -0.044 -0.044  0.056 -0.019  0.006  0.056  0.081 -0.019 -0.019  0.006 -0.044 -0.044  0.006 -0.019 -0.044 -0.044 -0.019  0.006 -0.019  0.031 -0.044  0.006 -0.019 -0.019 -0.019 -0.019 -0.019 -0.019  0.006 -0.044 -0.019 -0.044  0.006 -0.044 -0.019 -0.044 -0.044 -0.044 -0.019 -0.044  0.006  0.031  0.006 -0.019 -0.019  0.031  0.006 -0.019  0.006  0.006  0.031  0.006 -0.044  0.006 -0.044  0.006 -0.044  0.056 -0.044  0.031  0.006 -0.044  0.006 -0.019 -0.019  0.006  0.006 -0.044 -0.019 -0.044  0.006  0.056 -0.019 -0.019 -0.019  0.006  0.031 -0.019 
 0.082  0.057 -0.017 -0.017 -0.017  0.032 -0.042  0.032 -0.042  0.007 -0.017 -0.017 -0.017 -0.017 -0.017 -0.042 -0.017  0.007 -0.042 -0.017 -0.042  0.057 -0.042 -0.042  0.057 -0.017  0.007  0.057  0.082 -0.017 -0.042  0.007 -0.042 -0.042  0.007 -0.017 -0.042 -0.042 -0.017  0.007 -0.017  0.032 -0.042  0.007 -0.017 -0.042 -0.017 -0.017 -0.017 -0.017  0.007 -0.042 -0.017 -0.042  0.007 -0.042 -0.017 -0.042 -0.042 -0.042 -0.017 -0.042  0.007  0.032  0.007 -0.017 -0.017  0.032  0.007 -0.017  0.007  0.007  0.032  0.007 -0.042  0.007 -0.042  0.007 -0.042  0.057 -0.042  0.032  0.007 -0.042  0.007 -0.017 -0.017  0.007  0.007 -0.042 -0.017 -0.042  0.007  0.057 -0.017 -0.017 -0.017  0.007  0.032 -0.017 
 0.084  0.059 -0.016 -0.016 -0.016  0.009 -0.041  0.034 -0.041  0.009 -0.016 -0.016 -0.016 -0.016 -0.016 -0.041 -0.016  0.009 -0.041 -0.016 -0.041  0.059 -0.041 -0.041  0.059 -0.016  0.009  0.059  0.084 -0.016 -0.041  0.009 -0.041 -0.041  0.009 -0.041 -0.041 -0.041 -0.016  0.009 -0.016  0.034 -0.041  0.009 -0.016 -0.041 -0.016 -0.016 -0.016 -0.016  0.009 -0.041 -0.016 -0.041  0.009 -0.041 -0.016 -0.041 -0.041 -0.041 -0.016 -0.041  0.009  0.034  0.009 -0.016 -0.016  0.034  0.009 -0.016  0.009  0.009  0.034  0.009 -0.041  0.009 -0.041  0.009 -0.041  0.059 -0.041  0.034  0.009 -0.041  0.009 -0.016 -0.016  0.009  0.009 -0.041 -0.016 -0.041  0.009  0.059 -0.016 -0.016 -0.016  0.009  0.034 -0.016 
 0.100  0.050 -0.050 -0.025 -0.050  0.000 -0.075  0.000 -0.075 -0.025  0.000  0.000 -0.025 -0.050 -0.050 -0.050 -0.025  0.025  0.000 -0.050 -0.075  0.075 -0.050 -0.050  0.100 -0.025  0.025  0.050  0.075 -0.025 -0.050 -0.025 -0.075 -0.075 -0.025 -0.025 -0.050 -0.050 -0.025  0.000 -0.050  0.050  0.000  0.025 -0.050 -0.050 -0.050  0.000 -0.050  0.000  0.000 -0.075  0.100 -0.050 -0.025 -0.075 -0.050 -0.075 -0.025 -0.075 -0.050 -0.075  0.025  0.000 -0.025 -0.025  0.000  0.025  0.075  0.000  0.050  0.025  0.025 -0.025 -0.050 -0.025 -0.025 -0.025 -0.050  0.075 -0.075  0.125  0.050 -0.050  0.000 -0.050  0.000  0.025 -0.025 -0.075 -0.050 -0.075 -0.025  0.075  0.000  0.000 -0.050  0.075  0.075 -0.050 
 0.188  0.039 -0.111 -0.011 -0.086  0.014 -0.111 -0.036 -0.111 -0.036 -0.011  0.014 -0.061 -0.061 -0.111 -0.086 -0.036  0.014 -0.036 -0.061 -0.086  0.039 -0.086 -0.111  0.114 -0.011  0.014  0.014  0.139 -0.036 -0.061 -0.086 -0.111 -0.136 -0.011 -0.036 -0.061 -0.086 -0.061 -0.011 -0.061 -0.011 -0.036  0.014 -0.061 -0.036 -0.111 -0.036 -0.111 -0.036  0.014 -0.111  0.089 -0.061 -0.036 -0.086 -0.086 -0.136 -0.086 -0.111 -0.111 -0.036  0.039 -0.036 -0.036 -0.061  0.089  0.039  0.114 -0.011  0.064 -0.011 -0.011 -0.011 -0.061 -0.011 -0.061 -0.011 -0.036  0.139 -0.136  0.213  0.263 -0.086 -0.011 -0.111 -0.011 -0.036 -0.036 -0.086 -0.111 -0.111 -0.061  0.014 -0.061 -0.011 -0.061  0.014  0.139 -0.086 
 0.293  0.044 -0.155 -0.031 -0.081 -0.031 -0.081 -0.056 -0.155 -0.081 -0.006  0.044 -0.056 -0.056 -0.081 -0.106 -0.081  0.019 -0.031 -0.106 -0.131  0.044 -0.131 -0.155  0.094 -0.031 -0.006 -0.006  0.168 -0.056 -0.081 -0.131 -0.155 -0.180  0.019  0.094 -0.106 -0.081 -0.056 -0.031 -0.006 -0.031 -0.031  0.069 -0.106 -0.056 -0.155  0.019 -0.131 -0.056 -0.006 -0.131  0.044 -0.056 -0.081 -0.106 -0.056 -0.155 -0.131 -0.106 -0.131 -0.006  0.019 -0.056 -0.056 -0.056  0.119  0.019  0.218  0.044  0.069 -0.056 -0.031  0.019 -0.031 -0.031 -0.081 -0.006 -0.006  0.218 -0.180  0.268  0.368 -0.056 -0.031 -0.155 -0.056 -0.006 -0.081 -0.106 -0.056 -0.131 -0.106 -0.006 -0.081 -0.031 -0.056  0.044  0.094 -0.106 
 0.329  0.005 -0.169 -0.044 -0.119 -0.094 -0.144 -0.094 -0.119 -0.144  0.005  0.055 -0.094 -0.019  0.005 -0.094 -0.119  0.005  0.030 -0.169 -0.194  0.055 -0.194 -0.144  0.055 -0.094 -0.069 -0.044  0.130 -0.094 -0.119 -0.094 -0.169 -0.244  0.030  0.055 -0.144 -0.094 -0.094 -0.044 -0.044 -0.094 -0.094  0.055 -0.144 -0.069 -0.169  0.055 -0.169 -0.069 -0.044 -0.119  0.055 -0.044 -0.069 -0.044 -0.019 -0.119 -0.169 -0.169 -0.144  0.080 -0.044 -0.044 -0.094 -0.069  0.130  0.055  0.255 -0.019  0.105 -0.069 -0.044  0.055 -0.019 -0.019 -0.144 -0.044  0.030  0.404 -0.244  0.280  0.329 -0.069 -0.094 -0.144 -0.069 -0.069 -0.119 -0.169 -0.094 -0.119 -0.094 -0.044 -0.094 -0.094 -0.069  0.055  0.105 -0.069 
 0.336 -0.012 -0.187 -0.012 -0.137 -0.137 -0.137 -0.087 -0.112 -0.162  0.037  0.012 -0.087  0.012  0.087 -0.087 -0.112 -0.012  0.037 -0.162 -0.212  0.037 -0.187 -0.112  0.087 -0.087 -0.062 -0.087  0.137 -0.112 -0.112 -0.112 -0.187 -0.262  0.037  0.087 -0.137 -0.112 -0.137 -0.062 -0.012 -0.137 -0.112  0.037 -0.162 -0.062 -0.137  0.062 -0.137 -0.062 -0.087 -0.137  0.062 -0.037 -0.087 -0.012 -0.037 -0.087 -0.187 -0.187 -0.112  0.112 -0.087 -0.087 -0.112 -0.012  0.137  0.037  0.237  0.037  0.137 -0.087 -0.062  0.062  0.012  0.012 -0.137 -0.012  0.062  0.411 -0.262  0.336  0.311 -0.087 -0.112 -0.112 -0.087 -0.087 -0.087 -0.137 -0.087 -0.137 -0.087 -0.037 -0.087 -0.112 -0.037  0.037  0.062 -0.037 
 0.287 -0.037 -0.211 -0.012 -0.137 -0.161 -0.186 -0.087 -0.112 -0.186  0.038 -0.012 -0.137 -0.012  0.113 -0.112 -0.137 -0.062  0.038 -0.186 -0.236  0.038 -0.186 -0.112  0.088 -0.112 -0.087 -0.087  0.113 -0.112 -0.037 -0.087 -0.236 -0.286  0.063  0.063 -0.137 -0.112 -0.137 -0.087  0.013 -0.161 -0.137  0.038 -0.186 -0.087 -0.137  0.038 -0.161 -0.062 -0.087 -0.112  0.038 -0.037 -0.087  0.013  0.013 -0.137 -0.211 -0.211 -0.112  0.113 -0.087 -0.137 -0.137 -0.037  0.113 -0.012  0.212  0.088  0.138 -0.087 -0.037  0.088  0.013  0.013 -0.137 -0.037  0.138  0.387 -0.261  0.312  0.287 -0.112 -0.137 -0.112 -0.112 -0.087 -0.062 -0.161 -0.062 -0.161 -0.112 -0.037 -0.137 -0.112 -0.037  0.088  0.063 -0.062 
 0.329 -0.019 -0.194 -0.044 -0.119 -0.169 -0.194 -0.119 -0.119 -0.194  0.030  0.005 -0.144 -0.019  0.105 -0.119 -0.119 -0.069  0.030 -0.194 -0.244  0.055 -0.194 -0.119  0.105 -0.094 -0.094 -0.094  0.130 -0.144 -0.044 -0.094 -0.244 -0.269  0.105  0.080 -0.144 -0.119 -0.119 -0.119  0.005 -0.169 -0.094  0.030 -0.219 -0.094 -0.119  0.055 -0.169 -0.069 -0.094 -0.119  0.030  0.005 -0.094  0.005  0.005 -0.144 -0.219 -0.219 -0.119  0.105 -0.094 -0.144 -0.144 -0.019  0.105 -0.019  0.205  0.080  0.105 -0.119 -0.019  0.080 -0.019  0.030 -0.144 -0.044  0.180  0.354 -0.269  0.304  0.280 -0.119 -0.144 -0.094 -0.119 -0.094 -0.069 -0.144 -0.044 -0.169 -0.119 -0.044 -0.144 -0.094 -0.044  0.080  0.080 -0.069 
 0.317 -0.032 -0.206 -0.057 -0.107 -0.156 -0.206 -0.107 -0.082 -0.156  0.043  0.018 -0.156  0.043  0.093 -0.132 -0.132 -0.082  0.018 -0.206 -0.256  0.142 -0.206 -0.156  0.093 -0.156 -0.107 -0.057  0.142 -0.156 -0.057 -0.107 -0.256 -0.281  0.118  0.043 -0.132 -0.132 -0.057 -0.132 -0.007 -0.181 -0.107  0.043 -0.181 -0.082 -0.107  0.043 -0.181 -0.082 -0.082 -0.107  0.043 -0.007 -0.107 -0.007  0.018 -0.181 -0.206 -0.231 -0.132  0.093 -0.156 -0.132 -0.156 -0.032  0.093 -0.032  0.192  0.068  0.093 -0.132 -0.032  0.142 -0.007  0.043 -0.156 -0.032  0.242  0.342 -0.281  0.367  0.267 -0.107 -0.107 -0.107 -0.132 -0.107 -0.082 -0.156 -0.057 -0.181 -0.082 -0.057 -0.132 -0.082  0.018  0.043  0.118 -0.057 
 0.290 -0.034 -0.233 -0.059 -0.134 -0.134 -0.208 -0.109 -0.059 -0.158  0.016  0.016 -0.158  0.041  0.091 -0.109 -0.134 -0.084  0.041 -0.208 -0.258  0.165 -0.208 -0.158  0.066 -0.158 -0.109 -0.059  0.141 -0.158 -0.034 -0.158 -0.258 -0.233  0.141  0.041 -0.134 -0.134 -0.059 -0.158  0.041 -0.183 -0.109  0.016 -0.183 -0.084 -0.109  0.016 -0.183 -0.084 -0.084 -0.084  0.041 -0.009 -0.109 -0.009  0.016 -0.183 -0.208 -0.233 -0.134  0.091 -0.158 -0.134 -0.158 -0.009  0.116 -0.034  0.141  0.066  0.091 -0.134 -0.034  0.141 -0.009  0.066 -0.158 -0.034  0.240  0.340 -0.283  0.415  0.265 -0.109 -0.134 -0.134 -0.134 -0.109 -0.109 -0.183 -0.084 -0.183 -0.084 -0.059 -0.134 -0.109  0.016  0.041  0.116 -0.084 
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 0.300 -0.048 -0.248 -0.073 -0.123 -0.123 -0.248 -0.123 -0.073 -0.098  0.026  0.001 -0.198  0.051  0.076 -0.123 -0.123 -0.098  0.026 -0.223 -0.273  0.151 -0.223 -0.198  0.051 -0.148 -0.123 -0.123  0.151 -0.123 -0.048 -0.223 -0.297 -0.248  0.126 -0.098 -0.173 -0.198 -0.073 -0.223  0.001 -0.173 -0.123  0.001 -0.198 -0.098 -0.098 -0.148 -0.223 -0.123 -0.098 -0.048  0.051 -0.048 -0.198 -0.023 -0.048 -0.173 -0.223 -0.248 -0.198  0.051 -0.173 -0.148 -0.173  0.051  0.101 -0.048  0.001  0.126  0.051 -0.148  0.026  0.201 -0.073  0.026 -0.198 -0.023  0.300  0.350 -0.248  0.425  0.201 -0.023 -0.173 -0.148 -0.148 -0.148 -0.123 -0.198 -0.098 -0.223 -0.098 -0.098 -0.148 -0.123  0.076 -0.048  0.101 -0.023 
 0.274 -0.050 -0.249 -0.075 -0.100 -0.125 -0.249 -0.125 -0.075 -0.100  0.025  0.000 -0.174  0.050  0.075 -0.125 -0.125 -0.075  0.025 -0.224 -0.274  0.149 -0.224 -0.224  0.050 -0.149 -0.125 -0.125  0.149 -0.125 -0.050 -0.224 -0.299 -0.249  0.125 -0.100 -0.174 -0.199 -0.075 -0.224  0.000 -0.174 -0.125  0.000 -0.174 -0.100 -0.100 -0.149 -0.224 -0.125 -0.100 -0.050  0.050 -0.050 -0.199 -0.025 -0.050 -0.199 -0.224 -0.249 -0.199  0.075 -0.174 -0.149 -0.174  0.050  0.100 -0.050  0.025  0.125  0.050 -0.149  0.000  0.149 -0.075  0.025 -0.199 -0.025  0.274  0.349 -0.249  0.424  0.224 -0.025 -0.174 -0.149 -0.149 -0.149 -0.125 -0.199 -0.100 -0.224 -0.100 -0.100 -0.125 -0.125  0.100 -0.050  0.149 -0.025 
 0.274 -0.050 -0.250 -0.075 -0.100 -0.125 -0.250 -0.125 -0.075 -0.100  0.024 -0.000 -0.175  0.049  0.099 -0.100 -0.125 -0.075  0.024 -0.225 -0.275  0.149 -0.225 -0.225  0.049 -0.150 -0.125 -0.125  0.149 -0.125 -0.050 -0.200 -0.299 -0.250  0.124 -0.100 -0.175 -0.200 -0.075 -0.225 -0.000 -0.175 -0.125 -0.000 -0.175 -0.125 -0.100 -0.125 -0.225 -0.125 -0.100 -0.050  0.049 -0.050 -0.200 -0.025 -0.050 -0.200 -0.225 -0.250 -0.200  0.074 -0.175 -0.150 -0.175  0.049  0.099 -0.050  0.024  0.124  0.049 -0.150 -0.000  0.149 -0.075  0.024 -0.200 -0.025  0.274  0.348 -0.250  0.423  0.224 -0.025 -0.175 -0.150 -0.150 -0.150 -0.125 -0.200 -0.100 -0.225 -0.100 -0.100 -0.125 -0.125  0.099 -0.050  0.149 -0.025 
 0.275 -0.049 -0.249 -0.074 -0.099 -0.124 -0.249 -0.124 -0.074 -0.099  0.025  0.025 -0.174  0.050  0.100 -0.099 -0.124 -0.074  0.025 -0.224 -0.274  0.150 -0.224 -0.224  0.050 -0.149 -0.124 -0.124  0.125 -0.124 -0.074 -0.199 -0.298 -0.249  0.125 -0.099 -0.174 -0.199 -0.074 -0.224  0.000 -0.174 -0.124  0.000 -0.174 -0.124 -0.099 -0.149 -0.224 -0.124 -0.099 -0.049  0.050 -0.049 -0.199 -0.024 -0.049 -0.199 -0.224 -0.249 -0.199  0.050 -0.174 -0.149 -0.174  0.050  0.100 -0.049  0.025  0.100  0.050 -0.149  0.000  0.125 -0.074  0.025 -0.199 -0.099  0.275  0.349 -0.249  0.424  0.225 -0.024 -0.174 -0.149 -0.149 -0.149 -0.124 -0.199 -0.099 -0.224 -0.099 -0.124 -0.124 -0.124  0.100 -0.049  0.150 -0.024 
 0.274 -0.050 -0.250 -0.050 -0.100 -0.125 -0.250 -0.125 -0.075 -0.100  0.024  0.024 -0.175  0.049  0.099 -0.100 -0.050 -0.075  0.024 -0.225 -0.275  0.149 -0.225 -0.225  0.049 -0.150 -0.125 -0.125  0.124 -0.100 -0.075 -0.200 -0.299 -0.250  0.124 -0.100 -0.175 -0.200 -0.075 -0.225 -0.000 -0.175 -0.125 -0.000 -0.175 -0.125 -0.100 -0.150 -0.225 -0.125 -0.100 -0.050  0.049 -0.050 -0.200 -0.025 -0.050 -0.200 -0.225 -0.250 -0.200  0.024 -0.175 -0.150 -0.175  0.049  0.099 -0.050  0.024  0.099  0.049 -0.150 -0.000  0.124 -0.075 -0.000 -0.200 -0.100  0.274  0.348 -0.250  0.423  0.224 -0.025 -0.175 -0.150 -0.150 -0.150 -0.125 -0.200 -0.100 -0.225 -0.100 -0.125 -0.150 -0.125  0.099 -0.050  0.149 -0.025 
 0.318 -0.081 -0.180 -0.056 -0.106 -0.081 -0.230 -0.106 -0.081 -0.155 -0.031  0.044 -0.155  0.044  0.094 -0.056 -0.056 -0.081  0.069 -0.180 -0.205  0.094 -0.155 -0.155  0.069 -0.131 -0.081 -0.056  0.094 -0.081 -0.031 -0.155 -0.230 -0.180  0.069 -0.031 -0.106 -0.180 -0.081 -0.180 -0.056 -0.106 -0.131 -0.031 -0.131 -0.106 -0.081 -0.106 -0.155 -0.081 -0.106 -0.031  0.044 -0.056 -0.155 -0.056 -0.081 -0.155 -0.155 -0.180 -0.180  0.044 -0.106 -0.131 -0.155 -0.031  0.094 -0.031  0.044  0.094  0.094 -0.131  0.044  0.094 -0.081 -0.006 -0.155 -0.106  0.218  0.293 -0.180  0.442  0.168 -0.056 -0.131 -0.155 -0.106 -0.081 -0.106 -0.155 -0.056 -0.180 -0.056 -0.081 -0.081 -0.106  0.094 -0.081  0.019 -0.056 
 0.263 -0.036 -0.111 -0.061 -0.036 -0.011 -0.136 -0.111 -0.061 -0.111 -0.011 -0.011 -0.136  0.014  0.039  0.014 -0.061 -0.036  0.064 -0.111 -0.136 -0.011 -0.136 -0.086  0.114 -0.061  0.014 -0.036  0.139 -0.036  0.039 -0.136 -0.160 -0.086  0.064  0.039 -0.036 -0.136 -0.036 -0.111 -0.036 -0.036 -0.086 -0.011 -0.061 -0.086 -0.111 -0.061 -0.086 -0.011 -0.160 -0.036  0.089  0.014 -0.061 -0.061 -0.061 -0.111 -0.111 -0.086 -0.111  0.014 -0.086 -0.061 -0.086 -0.011  0.014 -0.011 -0.036  0.064  0.014 -0.061 -0.036  0.064 -0.086 -0.061 -0.111 -0.036  0.064  0.313 -0.160  0.313  0.114 -0.011 -0.136 -0.136 -0.036  0.014 -0.011 -0.061 -0.036 -0.111 -0.036  0.014 -0.061 -0.111  0.089 -0.111  0.014 -0.011 
 0.207  0.008 -0.092 -0.042 -0.042 -0.042 -0.142 -0.092 -0.042 -0.092 -0.017 -0.042 -0.142  0.033  0.033  0.008 -0.042 -0.017  0.083 -0.092 -0.117 -0.042 -0.117 -0.092  0.108 -0.042  0.008 -0.017  0.133 -0.017  0.033 -0.117 -0.142 -0.117  0.058  0.033 -0.067 -0.117 -0.017 -0.092 -0.067 -0.017 -0.067  0.008 -0.042 -0.092 -0.117 -0.042 -0.067  0.008 -0.142 -0.017  0.083  0.008 -0.042 -0.092 -0.067 -0.092 -0.092 -0.067 -0.092  0.008 -0.067 -0.042 -0.092 -0.017  0.008  0.008 -0.067  0.033  0.008 -0.042 -0.017  0.083 -0.067 -0.042 -0.092 -0.067  0.008  0.332 -0.142  0.257  0.083 -0.017 -0.142 -0.117 -0.017  0.033  0.008 -0.042 -0.017 -0.092 -0.017  0.008 -0.042 -0.092  0.083 -0.092 -0.017  0.008 
 0.156  0.032 -0.068 -0.068 -0.018 -0.018 -0.118 -0.068 -0.018 -0.043 -0.043 -0.043 -0.118  0.007 -0.018 -0.018 -0.043  0.032  0.082 -0.068 -0.093 -0.018 -0.093 -0.068  0.057 -0.018  0.032  0.007  0.107  0.007  0.007 -0.093 -0.118 -0.118  0.057 -0.018 -0.068 -0.093 -0.043 -0.093 -0.018  0.007 -0.043  0.007 -0.068 -0.068 -0.118 -0.043 -0.093  0.007 -0.118 -0.018  0.107  0.007 -0.018 -0.068 -0.043 -0.093 -0.068 -0.068 -0.068  0.007 -0.043 -0.018 -0.068 -0.043 -0.018  0.057 -0.118  0.007 -0.018 -0.018  0.007  0.007 -0.043 -0.043 -0.068 -0.043 -0.093  0.281 -0.118  0.256  0.057 -0.043 -0.118 -0.093 -0.018  0.032  0.032 -0.068 -0.018 -0.068 -0.043  0.032 -0.043 -0.093  0.032 -0.093  0.007 -0.018 
 0.117  0.017 -0.082 -0.057 -0.007 -0.007 -0.107 -0.057 -0.082 -0.032 -0.032 -0.057 -0.107 -0.007 -0.057 -0.032 -0.032  0.042  0.092 -0.082 -0.082 -0.007 -0.082 -0.057  0.067 -0.007  0.042 -0.007  0.117  0.042 -0.032 -0.082 -0.107 -0.107  0.067 -0.032 -0.057 -0.082 -0.057 -0.107 -0.007 -0.007 -0.032 -0.007 -0.057 -0.057 -0.107 -0.057 -0.082 -0.007 -0.107 -0.032  0.117 -0.032 -0.007 -0.057 -0.032 -0.082 -0.057 -0.057 -0.057 -0.007 -0.032 -0.007 -0.057 -0.007 -0.032  0.067 -0.107 -0.032 -0.007 -0.007  0.042 -0.007 -0.032 -0.032 -0.057 -0.057 -0.082  0.242 -0.107  0.267  0.042 -0.057 -0.107 -0.082 -0.007  0.042  0.017 -0.057 -0.007 -0.082 -0.057  0.042 -0.032 -0.082  0.042 -0.082 -0.007 -0.032 
 0.126  0.026 -0.074 -0.024  0.001  0.001 -0.099 -0.024 -0.074 -0.024 -0.049 -0.049 -0.099  0.001 -0.099 -0.024 -0.024  0.001  0.076 -0.074 -0.099  0.051 -0.099 -0.074  0.076  0.001  0.051  0.001  0.101  0.051 -0.049 -0.074 -0.099 -0.099  0.051 -0.024 -0.049 -0.099 -0.074 -0.099  0.001  0.001 -0.024  0.001 -0.074 -0.074 -0.099 -0.049 -0.074  0.001 -0.099 -0.024  0.126 -0.049  0.001 -0.049 -0.024 -0.074 -0.049 -0.049 -0.049 -0.024 -0.024 -0.024 -0.049  0.001 -0.024  0.076 -0.074 -0.049 -0.024  0.001  0.051 -0.024 -0.024 -0.049 -0.049 -0.049 -0.074  0.200 -0.099  0.250  0.076 -0.049 -0.099 -0.074  0.001  0.026  0.001 -0.049  0.001 -0.074 -0.074  0.051 -0.049 -0.074  0.051 -0.049  0.001 -0.024 
 0.084  0.034 -0.066 -0.016 -0.016  0.009 -0.091 -0.016 -0.066 -0.016 -0.041 -0.066 -0.091  0.009 -0.091 -0.041 -0.016 -0.016  0.009 -0.066 -0.091  0.059 -0.091 -0.066  0.084  0.009  0.009  0.009  0.109  0.059 -0.041 -0.066 -0.091 -0.091  0.059 -0.016 -0.066 -0.091 -0.066 -0.091 -0.016 -0.016 -0.016  0.009 -0.066 -0.066 -0.091 -0.041 -0.066 -0.041 -0.091 -0.016  0.109 -0.041 -0.016 -0.041 -0.016 -0.066 -0.041 -0.041 -0.041 -0.041 -0.016 -0.041 -0.041  0.009 -0.016  0.059 -0.066 -0.041 -0.016  0.009  0.059 -0.016 -0.016 -0.041 -0.041 -0.041 -0.066  0.208 -0.091  0.258  0.084 -0.041 -0.091 -0.066  0.009  0.009 -0.016 -0.041 -0.016 -0.091 -0.066  0.009 -0.041 -0.066  0.034 -0.041  0.009 -0.016 
 0.071  0.046 -0.079 -0.004 -0.029  0.021 -0.079 -0.029 -0.054 -0.004 -0.029 -0.054 -0.079 -0.029 -0.079 -0.029 -0.004 -0.029 -0.004 -0.054 -0.079  0.071 -0.079 -0.054  0.096  0.021  0.021  0.046  0.096  0.021 -0.054 -0.054 -0.079 -0.079  0.021 -0.004 -0.054 -0.079 -0.079 -0.054 -0.029 -0.004 -0.029 -0.004 -0.079 -0.054 -0.079 -0.029 -0.054 -0.054 -0.079 -0.054  0.021 -0.029 -0.029 -0.054 -0.029 -0.054 -0.029 -0.079 -0.029 -0.054 -0.004 -0.029 -0.054 -0.029  0.021  0.046 -0.029 -0.029 -0.004  0.021  0.046 -0.004 -0.004 -0.029 -0.029 -0.029 -0.054  0.170 -0.079  0.245  0.096 -0.054 -0.079 -0.054  0.021 -0.004 -0.004 -0.029 -0.004 -0.079 -0.079 -0.004 -0.029 -0.079  0.021 -0.029 -0.004 -0.004 
 0.074  0.049 -0.075 -0.000 -0.025  0.024 -0.075 -0.025 -0.050 -0.000 -0.000 -0.050 -0.050 -0.050 -0.050 -0.025 -0.025 -0.025 -0.000 -0.025 -0.075  0.099 -0.075 -0.050  0.099  0.024  0.024  0.049  0.099  0.024 -0.050 -0.050 -0.075 -0.075  0.024 -0.000 -0.050 -0.075 -0.075 -0.050 -0.025 -0.000 -0.025 -0.000 -0.075 -0.050 -0.075 -0.000 -0.050 -0.050 -0.050 -0.050  0.024 -0.025 -0.025 -0.050 -0.025 -0.075 -0.025 -0.075 -0.000 -0.075 -0.000 -0.000 -0.050 -0.025  0.024  0.049 -0.025 -0.025 -0.025  0.024  0.049 -0.000 -0.025 -0.000 -0.025 -0.050 -0.050  0.149 -0.075  0.199  0.099 -0.050 -0.050 -0.050  0.024 -0.000 -0.000 -0.050 -0.000 -0.075 -0.075 -0.000 -0.025 -0.075  0.024 -0.025 -0.000 -0.000 
 0.083  0.058 -0.067  0.008 -0.017  0.033 -0.067 -0.017 -0.067  0.008 -0.017 -0.042 -0.042 -0.042 -0.042 -0.042 -0.017 -0.017 -0.042 -0.017 -0.067  0.108 -0.067 -0.067  0.058  0.008  0.008  0.058  0.108  0.033 -0.042 -0.042 -0.067 -0.067  0.008  0.008 -0.067 -0.067 -0.067 -0.067 -0.042  0.008 -0.042 -0.017 -0.067 -0.042 -0.067  0.008 -0.042 -0.042 -0.042 -0.042  0.033 -0.042 -0.017 -0.042 -0.042 -0.067 -0.042 -0.067  0.008 -0.067  0.008  0.008 -0.042 -0.017  0.033  0.058 -0.042 -0.017 -0.042  0.033  0.033  0.008 -0.017 -0.017 -0.042 -0.042 -0.042  0.133 -0.067  0.182  0.108 -0.042 -0.042 -0.042 -0.017  0.008  0.008 -0.042  0.008 -0.067 -0.067  0.008 -0.017 -0.067  0.033 -0.017  0.008 -0.017 
 0.067  0.042 -0.057 -0.032 -0.007  0.017 -0.057 -0.007 -0.057  0.017 -0.007 -0.032 -0.032 -0.032 -0.032 -0.032 -0.007 -0.007 -0.032 -0.032 -0.057  0.117 -0.057 -0.057  0.042  0.017 -0.007  0.042  0.092  0.042 -0.032 -0.032 -0.057 -0.057  0.017  0.017 -0.057 -0.057 -0.057 -0.032 -0.032  0.017 -0.032 -0.007 -0.057 -0.032 -0.057  0.017 -0.032 -0.032 -0.032 -0.057  0.017 -0.032 -0.007 -0.032 -0.032 -0.057 -0.032 -0.057 -0.007 -0.057 -0.007  0.017 -0.032 -0.007  0.017  0.042 -0.032 -0.007 -0.032  0.042  0.042  0.017 -0.032 -0.007 -0.057 -0.032 -0.032  0.117 -0.057  0.142  0.042 -0.057 -0.032 -0.032 -0.007  0.017 -0.007 -0.032  0.017 -0.057 -0.032  0.017 -0.007 -0.057 -0.007 -0.007  0.017 -0.007 
 0.074  0.024 -0.050 -0.025 -0.000  0.024 -0.050 -0.000 -0.050 -0.000 -0.025 -0.025 -0.025 -0.025 -0.025 -0.050 -0.000 -0.000 -0.050 -0.025 -0.050  0.124 -0.050 -0.050  0.049 -0.025 -0.000  0.024  0.099 -0.000 -0.025 -0.025 -0.050 -0.050 -0.000 -0.000 -0.050 -0.050 -0.050 -0.025 -0.025  0.024 -0.025 -0.025 -0.050 -0.025 -0.050 -0.000 -0.025 -0.025 -0.025 -0.050 -0.000 -0.050 -0.000 -0.050 -0.025 -0.050 -0.025 -0.050 -0.025 -0.050 -0.000  0.024 -0.025 -0.000 -0.000  0.049 -0.025 -0.025 -0.000 -0.000  0.049  0.024 -0.050 -0.025 -0.050 -0.025 -0.025  0.074 -0.050  0.074  0.049 -0.050 -0.025 -0.025 -0.025  0.024 -0.000 -0.025 -0.000 -0.050 -0.025  0.024 -0.000 -0.050 -0.025 -0.000  0.024 -0.025 
 0.077  0.027 -0.048 -0.023 -0.023  0.052 -0.048  0.002 -0.048  0.002 -0.023 -0.023 -0.023 -0.023 -0.023 -0.048  0.002  0.002 -0.048 -0.023 -0.048  0.127 -0.048 -0.048  0.052 -0.023  0.002  0.052  0.102  0.002 -0.023 -0.023 -0.048 -0.048  0.002  0.002 -0.048 -0.048 -0.048  0.002 -0.023  0.027 -0.023 -0.023 -0.048 -0.023 -0.048  0.002 -0.023 -0.023 -0.023 -0.048  0.002 -0.048  0.002 -0.048 -0.023 -0.048 -0.048 -0.048 -0.023 -0.048  0.002  0.027 -0.023 -0.023  0.002  0.052 -0.023 -0.023  0.002  0.002  0.027  0.002 -0.048 -0.023 -0.048  0.002 -0.023  0.077 -0.048  0.077  0.027 -0.048 -0.023 -0.023 -0.023  0.027  0.002 -0.023 -0.023 -0.048 -0.023  0.052  0.002 -0.048 -0.023  0.002  0.027 -0.023 
 0.080  0.055 -0.045 -0.020 -0.020  0.030 -0.045  0.030 -0.045  0.005 -0.020 -0.020 -0.020 -0.045 -0.020 -0.045 -0.020  0.005 -0.045 -0.020 -0.045  0.105 -0.045 -0.045  0.055 -0.020  0.005  0.055  0.130  0.005 -0.020 -0.020 -0.045 -0.045  0.005 -0.020 -0.045 -0.045 -0.045  0.005 -0.020  0.030 -0.045  0.005 -0.045 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.045  0.005 -0.045  0.005 -0.045 -0.020 -0.045 -0.045 -0.045 -0.020 -0.045  0.005  0.030 -0.020 -0.020 -0.020  0.030 -0.020 -0.020  0.005  0.005  0.030  0.005 -0.045 -0.020 -0.045  0.005 -0.045  0.080 -0.045  0.030  0.005 -0.045 -0.020 -0.020 -0.020  0.030  0.005 -0.020 -0.020 -0.045 -0.020  0.055 -0.020 -0.045 -0.020  0.030  0.030 -0.020 
 0.082  0.057 -0.043 -0.018 -0.018  0.032 -0.043  0.032 -0.043  0.007 -0.018 -0.018 -0.018 -0.043 -0.018 -0.043 -0.018  0.007 -0.043 -0.018 -0.043  0.082 -0.043 -0.043  0.057 -0.018  0.007  0.057  0.107  0.007 -0.018 -0.018 -0.043 -0.043  0.007 -0.018 -0.043 -0.043 -0.043  0.007 -0.018  0.032 -0.043  0.007 -0.043 -0.018 -0.018 -0.018 -0.018 -0.018 -0.018 -0.043 -0.018 -0.043  0.007 -0.043 -0.018 -0.043 -0.043 -0.043 -0.018 -0.043  0.007  0.032 -0.018 -0.018 -0.018  0.032 -0.043 -0.018  0.007  0.007  0.032  0.007 -0.043 -0.018 -0.043  0.007 -0.043  0.082 -0.043  0.032  0.007 -0.043 -0.018 -0.018 -0.018  0.032  0.007 -0.018 -0.018 -0.043 -0.018  0.057 -0.018 -0.043 -0.018  0.007  0.032 -0.018 
 0.083  0.058 -0.016 -0.016 -0.016  0.008 -0.041  0.033 -0.041  0.008 -0.016 -0.016 -0.016 -0.016 -0.016 -0.041 -0.016  0.008 -0.041 -0.016 -0.041  0.058 -0.041 -0.041  0.058 -0.016  0.008  0.058  0.083 -0.016 -0.041  0.008 -0.041 -0.041  0.008 -0.041 -0.041 -0.041 -0.016  0.008 -0.016  0.033 -0.041  0.008 -0.041 -0.041 -0.016 -0.016 -0.016 -0.016 -0.016 -0.041 -0.016 -0.041  0.008 -0.041 -0.016 -0.041 -0.041 -0.041 -0.016 -0.041  0.008  0.033  0.008 -0.016 -0.016  0.033  0.008 -0.016  0.008  0.008  0.033  0.008 -0.041  0.008 -0.041  0.008 -0.041  0.058 -0.041  0.033  0.008 -0.041  0.008 -0.016 -0.016  0.008  0.008 -0.041 -0.016 -0.041  0.008  0.058 -0.016 -0.016 -0.016  0.008  0.033 -0.016 
 0.084  0.059 -0.015 -0.015 -0.015  0.009 -0.040  0.034 -0.040  0.009 -0.015 -0.015 -0.015 -0.015 -0.015 -0.040 -0.015  0.009 -0.040 -0.015 -0.040  0.059 -0.040 -0.040  0.059 -0.015  0.009  0.059  0.084 -0.015 -0.040  0.009 -0.040 -0.040  0.009 -0.040 -0.040 -0.040 -0.015  0.009 -0.015  0.034 -0.040  0.009 -0.040 -0.040 -0.015 -0.015 -0.015 -0.015 -0.015 -0.040 -0.015 -0.040  0.009 -0.040 -0.015 -0.040 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009 -0.015 -0.015  0.034  0.009 -0.015  0.009  0.009  0.034  0.009 -0.040  0.009 -0.040  0.009 -0.040  0.059 -0.040  0.034  0.009 -0.040  0.009 -0.015 -0.015  0.009  0.009 -0.040 -0.015 -0.040  0.009  0.059 -0.015 -0.015 -0.015  0.009  0.034 -0.015 
 0.084  0.059 -0.016 -0.016 -0.016  0.009 -0.041  0.034 -0.041  0.009 -0.016 -0.016 -0.016 -0.016 -0.016 -0.041 -0.016  0.009 -0.041 -0.016 -0.041  0.059 -0.041 -0.041  0.059 -0.016  0.009  0.059  0.084 -0.016 -0.041  0.009 -0.041 -0.041  0.009 -0.041 -0.041 -0.041 -0.016  0.009 -0.016  0.034 -0.041  0.009 -0.016 -0.041 -0.016 -0.016 -0.016 -0.016  0.009 -0.041 -0.016 -0.041  0.009 -0.041 -0.016 -0.041 -0.041 -0.041 -0.016 -0.041  0.009  0.034  0.009 -0.016 -0.016  0.034  0.009 -0.016  0.009  0.009  0.034  0.009 -0.041  0.009 -0.041  0.009 -0.041  0.059 -0.041  0.034  0.009 -0.041  0.009 -0.016 -0.016  0.009  0.009 -0.041 -0.016 -0.041  0.009  0.059 -0.016 -0.016 -0.016  0.009  0.034 -0.016 
 0.084  0.059 -0.016 -0.016 -0.016  0.009 -0.041  0.034 -0.041  0.009 -0.016 -0.016 -0.016 -0.016 -0.016 -0.041 -0.016  0.009 -0.041 -0.016 -0.041  0.059 -0.041 -0.041  0.059 -0.016  0.009  0.059  0.084 -0.016 -0.041  0.009 -0.041 -0.041  0.009 -0.041 -0.041 -0.041 -0.016  0.009 -0.016  0.034 -0.041  0.009 -0.016 -0.041 -0.016 -0.016 -0.016 -0.016  0.009 -0.041 -0.016 -0.041  0.009 -0.041 -0.016 -0.041 -0.041 -0.041 -0.016 -0.041  0.009  0.034  0.009 -0.016 -0.016  0.034  0.009 -0.016  0.009  0.009  0.034  0.009 -0.041  0.009 -0.041  0.009 -0.041  0.059 -0.041  0.034  0.009 -0.041  0.009 -0.016 -0.016  0.009  0.009 -0.041 -0.016 -0.041  0.009  0.059 -0.016 -0.016 -0.016  0.009  0.034 -0.016 
 0.084  0.059 -0.016 -0.016 -0.016  0.009 -0.041  0.034 -0.041  0.009 -0.016 -0.016 -0.016 -0.016 -0.016 -0.041 -0.016  0.009 -0.041 -0.016 -0.041  0.059 -0.041 -0.041  0.059 -0.016  0.009  0.059  0.084 -0.016 -0.041  0.009 -0.041 -0.041  0.009 -0.041 -0.041 -0.041 -0.016  0.009 -0.016  0.034 -0.041  0.009 -0.016 -0.041 -0.016 -0.016 -0.016 -0.016  0.009 -0.041 -0.016 -0.041  0.009 -0.041 -0.016 -0.041 -0.041 -0.041 -0.016 -0.041  0.009  0.034  0.009 -0.016 -0.016  0.034  0.009 -0.016  0.009  0.009  0.034  0.009 -0.041  0.009 -0.041  0.009 -0.041  0.059 -0.041  0.034  0.009 -0.041  0.009 -0.016 -0.016  0.009  0.009 -0.041 -0.016 -0.041  0.009  0.059 -0.016 -0.016 -0.016  0.009  0.034 -0.016 
 0.115  0.040 -0.034 -0.009 -0.034 -0.009 -0.059  0.040 -0.059  0.015 -0.034 -0.009  0.015 -0.034 -0.034 -0.059 -0.009  0.065 -0.034 -0.009 -0.059  0.065 -0.059 -0.059  0.090 -0.034 -0.009  0.090  0.090 -0.034 -0.059  0.015 -0.034 -0.059 -0.009 -0.034 -0.059 -0.059 -0.009 -0.009  0.015  0.015 -0.034 -0.009 -0.034 -0.009 -0.034 -0.009 -0.034 -0.009 -0.009 -0.059 -0.009 -0.059 -0.009 -0.034 -0.034 -0.059 -0.059 -0.059 -0.034 -0.034  0.015  0.040 -0.009 -0.009  0.040  0.040 -0.009 -0.034  0.040 -0.009  0.015  0.015 -0.009 -0.009 -0.059  0.015 -0.034  0.065 -0.059  0.140  0.040 -0.059  0.015 -0.034 -0.034  0.015 -0.009 -0.034 -0.034 -0.059 -0.009  0.115 -0.009  0.015 -0.009  0.015  0.090 -0.034 
 0.152  0.052 -0.072 -0.047 -0.022 -0.022 -0.097  0.002 -0.097 -0.047 -0.022  0.027  0.002 -0.047 -0.097 -0.122 -0.047  0.052  0.077 -0.072 -0.072  0.052 -0.047 -0.072  0.027 -0.022  0.002  0.052  0.102 -0.047 -0.072 -0.047 -0.097 -0.122 -0.022  0.002 -0.097 -0.097 -0.047 -0.022  0.002  0.027 -0.047  0.027 -0.072 -0.047 -0.097  0.027 -0.097 -0.047 -0.047 -0.072  0.102 -0.047 -0.047 -0.072 -0.072 -0.122 -0.097 -0.097 -0.022 -0.047  0.027 -0.022  0.027 -0.022  0.027  0.077  0.027 -0.072  0.102  0.102 -0.022  0.002 -0.022 -0.047 -0.047  0.002 -0.022  0.202 -0.122  0.227  0.127 -0.097 -0.022 -0.097 -0.022 -0.047 -0.047 -0.072 -0.047 -0.122 -0.047  0.127 -0.022 -0.022  0.027  0.002  0.102 -0.072 
 0.275  0.051 -0.099 -0.074  0.001 -0.049 -0.148  0.026 -0.148 -0.099 -0.024  0.026 -0.049 -0.049 -0.074 -0.148 -0.049  0.026  0.076 -0.124 -0.124  0.026 -0.099 -0.099  0.026 -0.049  0.001  0.001  0.175 -0.049 -0.049 -0.049 -0.148 -0.173 -0.024  0.026 -0.124 -0.099 -0.099 -0.074  0.001 -0.024 -0.074  0.026 -0.124 -0.049 -0.148  0.051 -0.099 -0.099 -0.074 -0.024  0.101 -0.074 -0.074 -0.074 -0.074 -0.173 -0.148 -0.124 -0.049  0.051  0.026 -0.049 -0.024 -0.024  0.051  0.076  0.001 -0.024  0.200  0.126 -0.049  0.026  0.001 -0.024 -0.074  0.051 -0.024  0.275 -0.173  0.300  0.200 -0.124 -0.074 -0.099 -0.049 -0.024 -0.024 -0.099 -0.024 -0.148 -0.049  0.126 -0.024 -0.049  0.001 -0.024  0.051 -0.099 
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 0.142  0.017 -0.057 -0.032  0.017 -0.007 -0.057 -0.082 -0.007 -0.032 -0.007 -0.057 -0.082 -0.007 -0.057 -0.032 -0.032  0.042  0.042 -0.082 -0.107  0.017 -0.107 -0.082  0.042 -0.007 -0.032 -0.007  0.117  0.042  0.017 -0.082 -0.107 -0.107  0.092 -0.032 -0.057 -0.082 -0.082 -0.082  0.067 -0.057 -0.032  0.067 -0.082 -0.082 -0.107 -0.032 -0.082 -0.007 -0.107 -0.032 -0.007 -0.007 -0.007 -0.057  0.017 -0.082 -0.057 -0.082 -0.007  0.017 -0.032 -0.032 -0.057 -0.032 -0.032  0.042 -0.107 -0.007 -0.032  0.017  0.017  0.042 -0.007 -0.057 -0.057 -0.032 -0.082  0.316 -0.107  0.316  0.117 -0.082 -0.107 -0.107  0.017  0.017 -0.007 -0.057  0.017 -0.082 -0.032  0.067 -0.007 -0.082  0.017 -0.082 -0.032  0.042 
 0.146  0.021 -0.053 -0.028  0.021 -0.003 -0.053 -0.078 -0.003 -0.028 -0.003 -0.053 -0.078 -0.003 -0.053 -0.053 -0.028  0.046  0.046 -0.078 -0.103 -0.003 -0.103 -0.078  0.046 -0.003 -0.028 -0.003  0.096  0.046  0.021 -0.078 -0.103 -0.103  0.096 -0.028 -0.078 -0.078 -0.078 -0.078  0.071 -0.053 -0.028  0.071 -0.078 -0.078 -0.103 -0.028 -0.078 -0.003 -0.103 -0.053 -0.003 -0.003 -0.003 -0.078  0.021 -0.078 -0.053 -0.103 -0.003  0.021 -0.028 -0.028 -0.053 -0.028 -0.028  0.046 -0.103 -0.003 -0.028  0.021 -0.003  0.046 -0.003 -0.053 -0.053 -0.028 -0.078  0.320 -0.103  0.320  0.096 -0.078 -0.103 -0.103  0.021  0.021 -0.003 -0.053  0.021 -0.078 -0.028  0.071 -0.003 -0.078  0.021 -0.078 -0.028  0.046 
 0.109  0.034 -0.066 -0.016  0.034  0.009 -0.091 -0.066  0.009 -0.016 -0.016 -0.091 -0.091  0.009 -0.066 -0.041 -0.041  0.034  0.059 -0.066 -0.091  0.009 -0.091 -0.066  0.084  0.009 -0.016  0.009  0.109  0.034 -0.041 -0.066 -0.091 -0.091  0.059 -0.016 -0.066 -0.066 -0.066 -0.066  0.059 -0.041 -0.016  0.034 -0.066 -0.066 -0.091 -0.041 -0.066  0.009 -0.091 -0.041 -0.016 -0.016 -0.016 -0.066  0.009 -0.066 -0.041 -0.091 -0.016 -0.016 -0.016 -0.016 -0.066 -0.016 -0.016  0.084 -0.091 -0.016 -0.016  0.034  0.009  0.034  0.009 -0.041 -0.041 -0.041 -0.066  0.258 -0.091  0.283  0.084 -0.066 -0.091 -0.091  0.034  0.034  0.009 -0.041 -0.016 -0.066 -0.066  0.059  0.009 -0.066  0.034 -0.041 -0.016  0.034 
 0.116  0.041 -0.058 -0.033  0.016  0.016 -0.083 -0.033 -0.008 -0.008 -0.033 -0.083 -0.083 -0.008 -0.083 -0.033 -0.033  0.041  0.041 -0.058 -0.083  0.041 -0.083 -0.058  0.066 -0.008 -0.008  0.016  0.116  0.041 -0.033 -0.058 -0.083 -0.083  0.066 -0.008 -0.058 -0.058 -0.058 -0.058  0.041 -0.033 -0.033  0.041 -0.083 -0.058 -0.083 -0.033 -0.058 -0.008 -0.083 -0.033 -0.033 -0.033 -0.008 -0.058 -0.008 -0.058 -0.033 -0.083 -0.033 -0.033 -0.008 -0.008 -0.058 -0.033 -0.008  0.091 -0.083 -0.033 -0.033  0.016  0.016 -0.008  0.016 -0.033 -0.058 -0.033 -0.058  0.166 -0.083  0.266  0.041 -0.058 -0.083 -0.083 -0.008  0.041 -0.008 -0.033 -0.008 -0.058 -0.058  0.066 -0.033 -0.058  0.041 -0.008 -0.008  0.041 
 0.122  0.047 -0.052 -0.027  0.022  0.022 -0.077 -0.027 -0.052 -0.002 -0.027 -0.077 -0.077 -0.027 -0.077 -0.052 -0.027  0.022  0.022 -0.052 -0.077  0.047 -0.077 -0.077  0.072 -0.002 -0.002  0.022  0.097  0.047 -0.052 -0.052 -0.077 -0.077  0.022 -0.002 -0.052 -0.052 -0.052 -0.077 -0.002 -0.027 -0.027  0.022 -0.077 -0.052 -0.077 -0.027 -0.052 -0.002 -0.077 -0.052 -0.027 -0.052 -0.027 -0.052 -0.027 -0.077 -0.027 -0.077 -0.027 -0.052 -0.002 -0.002 -0.052 -0.002 -0.002  0.072 -0.077 -0.027 -0.027  0.022 -0.002 -0.027  0.022 -0.027 -0.052 -0.027 -0.052  0.147 -0.077  0.272  0.022 -0.052 -0.077 -0.077 -0.002  0.047 -0.002 -0.027 -0.002 -0.077 -0.052  0.072 -0.027 -0.052  0.047 -0.027 -0.002 -0.002 
 0.125  0.050 -0.050 -0.025  0.025  0.025 -0.075 -0.025 -0.050  0.000 -0.025 -0.050 -0.075 -0.025 -0.075 -0.050 -0.025  0.025 -0.025 -0.050 -0.075  0.050 -0.075 -0.075  0.075  0.000  0.025  0.025  0.100  0.025 -0.025 -0.050 -0.075 -0.075  0.025  0.000 -0.050 -0.050 -0.050 -0.075  0.000  0.000 -0.025  0.000 -0.075 -0.050 -0.075 -0.050 -0.050  0.000 -0.075 -0.050  0.000 -0.050  0.000 -0.050 -0.050 -0.075 -0.025 -0.075 -0.025 -0.025  0.000  0.000 -0.050  0.000  0.000  0.075 -0.075 -0.025 -0.025  0.025  0.025 -0.025  0.025 -0.025 -0.050 -0.025 -0.050  0.149 -0.075  0.224  0.025 -0.050 -0.075 -0.050  0.000  0.025  0.025 -0.025  0.000 -0.075 -0.050  0.075 -0.025 -0.050  0.025 -0.025  0.000  0.000 
 0.129  0.054 -0.071 -0.046  0.004  0.029 -0.071 -0.021 -0.071  0.004  0.004 -0.021 -0.071 -0.046 -0.071 -0.046 -0.021  0.004 -0.021 -0.021 -0.071  0.079 -0.071 -0.071  0.054  0.004  0.004  0.054  0.129  0.029 -0.021 -0.046 -0.071 -0.071  0.004  0.004 -0.071 -0.046 -0.046 -0.046 -0.021  0.004 -0.046  0.004 -0.071 -0.046 -0.071 -0.046 -0.046 -0.021 -0.046 -0.046  0.029 -0.046  0.004 -0.046 -0.046 -0.071 -0.046 -0.071 -0.021 -0.021  0.004 -0.021 -0.046 -0.021  0.029  0.054 -0.021 -0.021  0.004  0.029  0.029  0.004  0.029 -0.021 -0.046 -0.021 -0.046  0.178 -0.071  0.203  0.004 -0.046 -0.071 -0.046 -0.021  0.029  0.029 -0.046  0.004 -0.071 -0.071  0.079 -0.021 -0.046  0.029  0.004  0.004 -0.021 
 0.107  0.057 -0.067 -0.042 -0.017  0.032 -0.067 -0.017 -0.067  0.007  0.007 -0.017 -0.042 -0.042 -0.042 -0.042 -0.017  0.007 -0.017 -0.017 -0.067  0.082 -0.067 -0.067  0.032  0.007  0.007  0.057  0.132  0.007 -0.042 -0.042 -0.067 -0.067  0.007  0.007 -0.067 -0.042 -0.042 -0.042 -0.017  0.007 -0.042  0.007 -0.067 -0.042 -0.067 -0.042 -0.042 -0.017 -0.042 -0.067  0.032 -0.042 -0.017 -0.042 -0.042 -0.067 -0.067 -0.067 -0.017 -0.067  0.007  0.007 -0.042 -0.017  0.032  0.057 -0.017 -0.017 -0.017  0.032  0.007 -0.017  0.007 -0.017 -0.042 -0.042 -0.042  0.182 -0.067  0.207  0.007 -0.042 -0.067 -0.042 -0.017  0.007  0.007 -0.042  0.007 -0.067 -0.067  0.057 -0.017 -0.067  0.007  0.007  0.007 -0.017 
 0.084  0.009 -0.066 -0.041 -0.016  0.059 -0.066 -0.016 -0.066  0.009 -0.016 -0.016 -0.041 -0.041 -0.041 -0.041 -0.041  0.034  0.009 -0.016 -0.066  0.109 -0.066 -0.066  0.034 -0.016  0.009  0.084  0.134  0.009 -0.041 -0.041 -0.066 -0.066 -0.016  0.009 -0.066 -0.041 -0.016  0.009 -0.016  0.009 -0.041  0.009 -0.066 -0.041 -0.066 -0.016 -0.041 -0.041 -0.041 -0.066  0.084 -0.066 -0.016 -0.041 -0.041 -0.066 -0.066 -0.066  0.009 -0.041 -0.016  0.034 -0.041 -0.016  0.034  0.034 -0.016  0.009  0.034  0.034  0.009 -0.016  0.009 -0.016 -0.041 -0.016 -0.066  0.134 -0.066  0.183 -0.016 -0.016 -0.041 -0.041 -0.041  0.009  0.009 -0.016  0.009 -0.066 -0.041  0.059 -0.016 -0.041  0.009  0.009  0.034 -0.041 
 0.111  0.011 -0.063 -0.038 -0.038  0.036 -0.063 -0.013 -0.063 -0.013 -0.038 -0.013 -0.038 -0.038 -0.038 -0.038 -0.038  0.036  0.011 -0.013 -0.038  0.111 -0.063 -0.063  0.036 -0.038 -0.013  0.086  0.136  0.011 -0.038 -0.038 -0.063 -0.063 -0.013  0.011 -0.063 -0.038 -0.013  0.011 -0.013  0.011 -0.038 -0.013 -0.063 -0.038 -0.063 -0.013 -0.038 -0.038 -0.038 -0.063  0.061 -0.063 -0.013 -0.063 -0.038 -0.063 -0.063 -0.063 -0.013 -0.038 -0.013  0.036 -0.038 -0.013  0.036  0.011 -0.013  0.011  0.036  0.036  0.011 -0.013  0.011 -0.013 -0.038 -0.013 -0.063  0.136 -0.063  0.161 -0.013 -0.013 -0.038 -0.038 -0.038  0.036 -0.013 -0.013  0.011 -0.063 -0.038  0.061 -0.013 -0.013 -0.038  0.011  0.036 -0.038 
 0.088  0.013 -0.061 -0.036 -0.036  0.038 -0.061 -0.011 -0.061 -0.011 -0.036 -0.011 -0.036 -0.036 -0.036 -0.061 -0.036  0.038 -0.011 -0.011 -0.036  0.088 -0.061 -0.061  0.038 -0.036 -0.011  0.063  0.113 -0.011 -0.036 -0.036 -0.061 -0.061 -0.011  0.013 -0.036 -0.036 -0.011  0.013 -0.011  0.013 -0.061 -0.011 -0.061 -0.011 -0.061 -0.036 -0.036 -0.036 -0.036 -0.061  0.038 -0.061 -0.011 -0.061 -0.036 -0.061 -0.061 -0.061 -0.036 -0.036 -0.011  0.038 -0.036 -0.011  0.038  0.013 -0.011 -0.011  0.038  0.013  0.013 -0.011  0.013 -0.011 -0.061 -0.011 -0.061  0.088 -0.061  0.088 -0.011 -0.036 -0.011 -0.036 -0.036  0.038 -0.011 -0.011 -0.011 -0.061 -0.036  0.063 -0.011 -0.011 -0.036  0.013  0.038 -0.036 
 0.086  0.011 -0.063 -0.038 -0.038  0.036 -0.063 -0.013 -0.063 -0.013 -0.038 -0.013 -0.038 -0.038 -0.038 -0.063 -0.038  0.036 -0.013 -0.013 -0.038  0.086 -0.038 -0.038  0.036 -0.038 -0.013  0.061  0.111 -0.013 -0.013 -0.038 -0.063 -0.063 -0.013  0.011 -0.038 -0.038 -0.013  0.011 -0.013  0.011 -0.063 -0.013 -0.063 -0.013 -0.063 -0.038 -0.038 -0.038 -0.013 -0.063  0.036 -0.063  0.011 -0.063 -0.038 -0.063 -0.063 -0.063 -0.038 -0.013  0.011  0.036 -0.038 -0.013  0.036  0.011 -0.013 -0.013  0.036  0.011  0.011 -0.013  0.011  0.011 -0.063 -0.013 -0.063  0.086 -0.063  0.086 -0.013 -0.038  0.011 -0.038 -0.038  0.036 -0.013 -0.013 -0.013 -0.063 -0.038  0.061 -0.013 -0.013 -0.038  0.011  0.061 -0.038 
 0.084  0.009 -0.066 -0.041 -0.041  0.034 -0.066 -0.016 -0.066 -0.016 -0.041 -0.016 -0.041 -0.041 -0.041 -0.066 -0.016  0.034 -0.016  0.009 -0.041  0.084 -0.041 -0.041  0.034 -0.041  0.009  0.059  0.109 -0.016 -0.016 -0.041 -0.066 -0.066 -0.016  0.009 -0.041 -0.041 -0.016  0.009 -0.016  0.009 -0.066 -0.016 -0.066 -0.016 -0.066 -0.041 -0.041 -0.041 -0.016 -0.066  0.034 -0.066  0.009 -0.066 -0.041 -0.066 -0.066 -0.066 -0.041  0.009  0.009  0.034 -0.041 -0.016  0.034  0.009  0.034  0.034  0.034  0.009  0.009 -0.016  0.009  0.009 -0.066 -0.016 -0.041  0.059 -0.066  0.059 -0.041 -0.016  0.059 -0.041 -0.041  0.034 -0.016 -0.016  0.009 -0.066 -0.041  0.059 -0.041 -0.016 -0.041  0.034  0.059 -0.041 
 0.083  0.008 -0.066 -0.041 -0.041  0.033 -0.066 -0.016 -0.066 -0.016 -0.041 -0.016 -0.041 -0.041 -0.041 -0.066 -0.016  0.033 -0.016  0.008 -0.041  0.083 -0.041 -0.041  0.033 -0.041  0.008  0.058  0.108 -0.016 -0.016 -0.041 -0.066 -0.066 -0.016  0.008 -0.041 -0.041 -0.016  0.008 -0.016  0.008 -0.041 -0.016 -0.066 -0.016 -0.066 -0.041 -0.041 -0.041 -0.016 -0.066  0.033 -0.066  0.008 -0.066 -0.041 -0.066 -0.066 -0.066 -0.041  0.008  0.008  0.033 -0.041 -0.016  0.033  0.008  0.008  0.033  0.033  0.008  0.008 -0.016  0.008  0.008 -0.066 -0.016 -0.041  0.058 -0.066  0.058 -0.016 -0.016  0.033 -0.041 -0.041  0.033 -0.016 -0.016  0.008 -0.066 -0.041  0.058 -0.041 -0.016 -0.041  0.033  0.058 -0.041 
 0.083  0.008 -0.066 -0.041 -0.041  0.033 -0.066 -0.016 -0.066 -0.016 -0.041 -0.016 -0.041 -0.041 -0.041 -0.066 -0.016  0.033 -0.016  0.008 -0.041  0.083 -0.041 -0.041  0.033 -0.041  0.008  0.058  0.108 -0.016 -0.016 -0.041 -0.066 -0.066 -0.016  0.008 -0.041 -0.041 -0.016  0.008 -0.016  0.008 -0.041 -0.016 -0.066 -0.016 -0.066 -0.041 -0.041 -0.041 -0.016 -0.066  0.033 -0.066  0.008 -0.066 -0.041 -0.066 -0.066 -0.066 -0.041  0.008  0.008  0.033 -0.041 -0.016  0.033  0.008  0.008  0.033  0.033  0.008 -0.016 -0.016  0.008  0.008 -0.066 -0.016 -0.041  0.083 -0.066  0.058  0.008 -0.016  0.033 -0.041 -0.041  0.033 -0.016 -0.016  0.008 -0.066 -0.041  0.058 -0.041 -0.016 -0.041  0.033  0.058 -0.041 
 0.083  0.008 -0.066 -0.041 -0.041  0.033 -0.066 -0.016 -0.066 -0.016 -0.041 -0.016 -0.041 -0.041 -0.041 -0.066 -0.016  0.033 -0.016  0.008 -0.041  0.083 -0.041 -0.041  0.033 -0.041  0.008  0.058  0.108 -0.016 -0.016 -0.041 -0.066 -0.066 -0.016  0.008 -0.041 -0.041 -0.016  0.008 -0.016  0.008 -0.041 -0.016 -0.066 -0.016 -0.066 -0.041 -0.041 -0.041 -0.016 -0.066  0.033 -0.066  0.008 -0.066 -0.041 -0.066 -0.066 -0.066 -0.041  0.008  0.008  0.033 -0.041 -0.016  0.033  0.008  0.008  0.033  0.033  0.008 -0.016 -0.016  0.008  0.008 -0.066 -0.016 -0.041  0.083 -0.066  0.058  0.008 -0.016  0.033 -0.041 -0.041  0.033 -0.016 -0.016  0.008 -0.066 -0.041  0.058 -0.041 -0.016 -0.041  0.033  0.058 -0.041 
 0.084  0.009 -0.066 -0.041 -0.041  0.034 -0.066 -0.016 -0.066 -0.016 -0.041 -0.016 -0.041 -0.041 -0.041 -0.066 -0.016  0.034 -0.016  0.009 -0.041  0.084 -0.041 -0.041  0.034 -0.041  0.009  0.059  0.109 -0.016 -0.016 -0.041 -0.066 -0.066 -0.016  0.009 -0.041 -0.041 -0.016  0.009 -0.016  0.009 -0.041 -0.016 -0.066 -0.016 -0.066 -0.041 -0.041 -0.041 -0.016 -0.066  0.034 -0.066  0.009 -0.066 -0.041 -0.066 -0.066 -0.066 -0.041  0.034  0.009  0.034 -0.041 -0.016  0.034  0.009  0.009  0.034  0.034  0.009 -0.016 -0.016  0.009  0.009 -0.041 -0.016 -0.041  0.059 -0.066  0.059 -0.016 -0.016  0.034 -0.041 -0.041  0.034 -0.016 -0.016  0.009 -0.066 -0.041  0.059 -0.041 -0.016 -0.041  0.034  0.059 -0.041 
 0.057  0.007 -0.093 -0.043 -0.068  0.032 -0.093 -0.018 -0.093 -0.043 -0.018 -0.043 -0.068 -0.018 -0.068 -0.093 -0.043  0.057  0.007 -0.018 -0.068  0.107 -0.043 -0.043  0.082 -0.068  0.032  0.032  0.107 -0.018 -0.018 -0.018 -0.093 -0.093 -0.043  0.032 -0.043 -0.068 -0.018 -0.018  0.007 -0.018 -0.018  0.007 -0.068  0.032 -0.043 -0.043 -0.068 -0.018 -0.018 -0.093  0.057 -0.093  0.007 -0.093 -0.043 -0.093 -0.068 -0.093 -0.068  0.032  0.007  0.032 -0.043 -0.043  0.057 -0.018  0.007  0.007  0.132  0.032 -0.043 -0.043 -0.018  0.032 -0.068 -0.043 -0.043  0.082 -0.093  0.107 -0.018 -0.018  0.057 -0.043 -0.018  0.032 -0.043 -0.043  0.032 -0.093 -0.018  0.107 -0.018  0.007 -0.018  0.032  0.057 -0.068 
 0.128  0.028 -0.097 -0.072 -0.097 -0.022 -0.146  0.003 -0.122 -0.072 -0.047 -0.022 -0.097 -0.022 -0.122 -0.072 -0.072  0.103  0.053 -0.072 -0.097  0.177 -0.047 -0.047  0.053 -0.047  0.053  0.028  0.128  0.003 -0.047 -0.047 -0.122 -0.146 -0.097  0.003 -0.072 -0.097 -0.047 -0.072  0.003 -0.072 -0.022  0.003 -0.097  0.003 -0.097 -0.047 -0.122 -0.047 -0.072 -0.072  0.152 -0.097 -0.022 -0.097 -0.022 -0.146 -0.122 -0.097 -0.072  0.028 -0.022 -0.022 -0.047 -0.072  0.103  0.003  0.003  0.003  0.152  0.003  0.053  0.028 -0.047  0.003 -0.072 -0.072 -0.022  0.252 -0.146  0.302  0.078 -0.072  0.028 -0.072  0.003  0.003 -0.072 -0.097  0.128 -0.097 -0.047  0.103 -0.022  0.003 -0.047  0.103  0.053 -0.122 
 0.158 -0.016 -0.066 -0.091 -0.141 -0.041 -0.166  0.008 -0.116 -0.066  0.008 -0.016 -0.116  0.008 -0.066 -0.091 -0.066  0.108  0.033 -0.116 -0.141  0.183 -0.041 -0.091  0.033 -0.066  0.033  0.008  0.083 -0.016 -0.041 -0.091 -0.166 -0.191 -0.066 -0.066 -0.091 -0.116 -0.091 -0.116  0.008 -0.091 -0.041  0.058 -0.091  0.008 -0.091  0.008 -0.141 -0.041 -0.091 -0.091  0.108 -0.091 -0.016 -0.091 -0.041 -0.091 -0.166 -0.141 -0.116  0.058 -0.066 -0.066 -0.066 -0.066  0.108  0.008 -0.016  0.008  0.133 -0.016  0.033  0.033 -0.041  0.033 -0.116 -0.066 -0.016  0.332 -0.191  0.407  0.183 -0.116 -0.016 -0.091 -0.041 -0.066 -0.016 -0.141  0.158 -0.116 -0.016  0.033 -0.066 -0.016 -0.041  0.083  0.083 -0.116 
 0.127 -0.022 -0.097 -0.122 -0.097 -0.122 -0.172  0.152 -0.097 -0.097 -0.047 -0.072 -0.097  0.027 -0.047 -0.122 -0.097  0.077  0.002 -0.147 -0.197  0.127 -0.072 -0.147  0.102 -0.022 -0.022 -0.072  0.077 -0.072 -0.047 -0.147 -0.222 -0.247 -0.072 -0.122 -0.097 -0.147 -0.147 -0.197  0.077 -0.097 -0.072  0.002 -0.072  0.002 -0.147  0.027 -0.197 -0.097 -0.072 -0.022  0.052 -0.072 -0.047 -0.022 -0.072 -0.072 -0.197 -0.172 -0.147  0.052 -0.122 -0.072 -0.097 -0.047  0.152  0.002  0.077  0.052  0.152  0.002  0.002  0.027 -0.072  0.102 -0.147 -0.122  0.027  0.376 -0.222  0.451  0.202 -0.122 -0.072 -0.097 -0.072 -0.072 -0.022 -0.172  0.077 -0.147 -0.022 -0.022 -0.122 -0.072 -0.072  0.077  0.027 -0.072 
 0.135  0.010 -0.115 -0.140 -0.115 -0.140 -0.189  0.159 -0.115 -0.140 -0.065 -0.065 -0.115  0.010  0.010 -0.140 -0.040  0.060 -0.015 -0.164 -0.214  0.184 -0.065 -0.164  0.135 -0.015 -0.040 -0.090  0.035 -0.115 -0.015 -0.189 -0.239 -0.264 -0.040 -0.140 -0.115 -0.164 -0.140 -0.214  0.110 -0.090 -0.090  0.035 -0.090 -0.015 -0.140  0.010 -0.214 -0.115 -0.090 -0.015  0.060 -0.090 -0.065 -0.015 -0.090 -0.065 -0.214 -0.189 -0.164  0.035 -0.140 -0.090 -0.115 -0.015  0.135  0.010  0.085  0.035  0.159  0.010 -0.015  0.010 -0.065  0.110 -0.140 -0.115  0.035  0.384 -0.239  0.458  0.209 -0.090 -0.065 -0.065 -0.090 -0.065 -0.015 -0.189  0.060 -0.164 -0.040 -0.040 -0.140 -0.090 -0.065  0.060  0.010 -0.015 
 0.135  0.010 -0.140 -0.115 -0.140 -0.140 -0.189  0.110 -0.115 -0.115 -0.065 -0.015 -0.140  0.010  0.060 -0.140 -0.090 -0.015 -0.015 -0.214 -0.239  0.135 -0.115 -0.140  0.110 -0.040 -0.090 -0.115  0.035 -0.140 -0.040 -0.189 -0.264 -0.289 -0.040 -0.115 -0.140 -0.140 -0.164 -0.239  0.085 -0.140 -0.090  0.010 -0.065 -0.065 -0.164 -0.040 -0.214 -0.115 -0.090  0.035  0.010 -0.090 -0.065 -0.015 -0.090 -0.090 -0.214 -0.214 -0.214  0.035 -0.115 -0.115 -0.140  0.010  0.110 -0.015  0.110  0.060  0.159 -0.015 -0.040 -0.015 -0.065  0.060 -0.140 -0.090  0.085  0.334 -0.264  0.433  0.184 -0.090 -0.115 -0.090 -0.115 -0.090 -0.015 -0.189 -0.015 -0.189 -0.065 -0.065 -0.164 -0.115 -0.040  0.085 -0.015  0.010 
 0.099 -0.000 -0.200 -0.125 -0.125 -0.150 -0.175  0.099 -0.125 -0.100 -0.050 -0.025 -0.150  0.049  0.049 -0.175 -0.100 -0.050 -0.025 -0.250 -0.225  0.124 -0.125 -0.150  0.099 -0.050 -0.100 -0.125  0.024 -0.125 -0.025 -0.200 -0.250 -0.299 -0.050 -0.125 -0.150 -0.150 -0.175 -0.250  0.074 -0.150 -0.100  0.024 -0.075 -0.075 -0.175 -0.050 -0.225 -0.125 -0.075  0.049 -0.000 -0.100 -0.050 -0.000 -0.100 -0.100 -0.225 -0.225 -0.225 -0.000 -0.125 -0.100 -0.125 -0.000  0.099 -0.000  0.074  0.074  0.124 -0.025 -0.050  0.024 -0.075  0.049 -0.150 -0.075  0.099  0.348 -0.275  0.423  0.199 -0.050 -0.125 -0.075 -0.125 -0.100 -0.025 -0.200 -0.025 -0.175 -0.075 -0.075 -0.175 -0.150  0.024  0.074 -0.000  0.074 
 0.089 -0.010 -0.210 -0.110 -0.085 -0.160 -0.185  0.089 -0.135 -0.085 -0.035 -0.035 -0.160  0.039  0.064 -0.185 -0.085 -0.060 -0.035 -0.235 -0.235  0.114 -0.135 -0.160  0.039 -0.060 -0.085 -0.135  0.014 -0.135 -0.035 -0.235 -0.260 -0.309 -0.035 -0.110 -0.160 -0.160 -0.185 -0.210  0.064 -0.160 -0.110  0.039 -0.035 -0.110 -0.210 -0.085 -0.210 -0.135 -0.060  0.039 -0.035 -0.110 -0.060 -0.035 -0.035 -0.110 -0.235 -0.235 -0.235 -0.035 -0.160 -0.085 -0.110  0.039  0.039 -0.010  0.064  0.089  0.039 -0.060 -0.060  0.064 -0.060  0.039 -0.160 -0.110  0.114  0.338 -0.260  0.413  0.189 -0.060 -0.135 -0.110 -0.135 -0.110 -0.035 -0.210 -0.035 -0.185 -0.085 -0.085 -0.185 -0.160  0.039  0.114  0.014  0.089 
 0.089 -0.010 -0.210 -0.110 -0.085 -0.160 -0.160  0.089 -0.135 -0.110 -0.110 -0.035 -0.110  0.039  0.064 -0.185 -0.085 -0.060 -0.035 -0.260 -0.210  0.114 -0.160 -0.185  0.039 -0.060 -0.110 -0.135  0.014 -0.135 -0.035 -0.235 -0.260 -0.309 -0.035 -0.110 -0.160 -0.160 -0.185 -0.210  0.064 -0.160 -0.110  0.014 -0.035 -0.135 -0.210 -0.085 -0.210 -0.135 -0.085  0.039 -0.035 -0.110 -0.060 -0.035 -0.035 -0.135 -0.235 -0.235 -0.235 -0.010 -0.210 -0.060 -0.110  0.039  0.039  0.064  0.064  0.089  0.039 -0.085 -0.060  0.039 -0.060  0.039 -0.160 -0.110  0.114  0.338 -0.260  0.413  0.189 -0.060 -0.135 -0.110 -0.135 -0.110 -0.035 -0.185 -0.035 -0.185 -0.085 -0.060 -0.185 -0.160  0.039  0.114  0.014  0.089 
 0.080 -0.019 -0.219 -0.119 -0.094 -0.169 -0.169  0.080 -0.144 -0.119 -0.144 -0.044 -0.119  0.055  0.080 -0.169 -0.044 -0.069  0.005 -0.269 -0.219  0.105 -0.169 -0.194  0.005 -0.044 -0.119 -0.144  0.005 -0.144 -0.044 -0.244 -0.269 -0.318 -0.019 -0.119 -0.169 -0.169 -0.194 -0.194  0.055 -0.169 -0.119  0.005  0.005 -0.144 -0.194 -0.119 -0.219 -0.144 -0.094  0.030 -0.019 -0.119 -0.069  0.005 -0.019 -0.144 -0.244 -0.244 -0.244 -0.019 -0.219 -0.069 -0.094  0.030  0.005  0.105  0.055  0.105  0.030 -0.094 -0.019  0.055 -0.069  0.030 -0.169 -0.119  0.105  0.354 -0.269  0.404  0.205 -0.044 -0.144 -0.119 -0.144 -0.119 -0.044 -0.194 -0.019 -0.169 -0.094 -0.069 -0.169 -0.169  0.030  0.130  0.005  0.080 
 0.079 -0.020 -0.220 -0.120 -0.095 -0.170 -0.195  0.079 -0.145 -0.120 -0.170 -0.045 -0.120  0.054  0.079 -0.170 -0.020 -0.070  0.004 -0.270 -0.220  0.079 -0.170 -0.195  0.029 -0.045 -0.120 -0.145  0.004 -0.145 -0.045 -0.245 -0.270 -0.319 -0.020 -0.120 -0.170 -0.170 -0.195 -0.195  0.054 -0.170 -0.120  0.004  0.004 -0.145 -0.170 -0.120 -0.220 -0.145 -0.095  0.029 -0.020 -0.120 -0.070  0.004 -0.020 -0.145 -0.245 -0.245 -0.245 -0.020 -0.220 -0.070 -0.095  0.029  0.004  0.104  0.054  0.104  0.029 -0.095 -0.020  0.054 -0.070  0.029 -0.170 -0.120  0.129  0.353 -0.270  0.378  0.204 -0.020 -0.145 -0.170 -0.145 -0.120 -0.070 -0.195 -0.020 -0.170 -0.095 -0.070 -0.170 -0.170  0.029  0.129  0.004  0.079 
 0.075 -0.025 -0.224 -0.125 -0.100 -0.174 -0.199  0.075 -0.149 -0.100 -0.174 -0.050 -0.174  0.025  0.075 -0.174 -0.025 -0.075  0.000 -0.274 -0.224  0.075 -0.174 -0.199  0.050 -0.075 -0.125 -0.149  0.050 -0.149 -0.075 -0.224 -0.274 -0.324  0.000 -0.125 -0.174 -0.174 -0.199 -0.199  0.050 -0.174 -0.125  0.000  0.000 -0.149 -0.174 -0.100 -0.224 -0.149 -0.100  0.025 -0.050 -0.125 -0.050 -0.025 -0.025 -0.149 -0.249 -0.249 -0.249 -0.025 -0.224 -0.075 -0.100  0.050  0.000  0.125  0.025  0.075  0.025 -0.125  0.000  0.050 -0.075  0.025 -0.199 -0.125  0.174  0.299 -0.274  0.374  0.174  0.000 -0.149 -0.199 -0.149 -0.125 -0.100 -0.199 -0.025 -0.149 -0.100 -0.075 -0.174 -0.174  0.025  0.125  0.000  0.050 
 0.073 -0.026 -0.226 -0.126 -0.101 -0.176 -0.176  0.023 -0.151 -0.101 -0.176 -0.026 -0.176  0.023  0.073 -0.176 -0.026 -0.076 -0.001 -0.276 -0.226  0.073 -0.176 -0.201  0.073 -0.076 -0.126 -0.151  0.048 -0.151 -0.076 -0.226 -0.276 -0.325 -0.001 -0.126 -0.176 -0.176 -0.176 -0.201  0.048 -0.176 -0.126 -0.001 -0.001 -0.151 -0.176 -0.101 -0.226 -0.151 -0.101  0.023 -0.051 -0.126 -0.051 -0.051 -0.026 -0.151 -0.251 -0.251 -0.251 -0.026 -0.226 -0.076 -0.101  0.023 -0.001  0.123  0.048  0.073 -0.001 -0.126 -0.001  0.048 -0.076  0.023 -0.176 -0.126  0.198  0.297 -0.276  0.372  0.173 -0.001 -0.151 -0.201 -0.151 -0.126 -0.126 -0.201 -0.026 -0.151 -0.101 -0.076 -0.176 -0.176  0.023  0.148 -0.001  0.048 
 0.074 -0.025 -0.225 -0.125 -0.100 -0.175 -0.175 -0.000 -0.150 -0.100 -0.175 -0.025 -0.175  0.024  0.074 -0.175 -0.025 -0.075 -0.025 -0.275 -0.225  0.074 -0.150 -0.200  0.074 -0.075 -0.150 -0.150  0.074 -0.150 -0.075 -0.225 -0.275 -0.324 -0.000 -0.125 -0.175 -0.175 -0.175 -0.200  0.049 -0.175 -0.125 -0.000 -0.025 -0.150 -0.175 -0.100 -0.225 -0.150 -0.125  0.024 -0.050 -0.125 -0.075 -0.050 -0.025 -0.150 -0.250 -0.250 -0.250 -0.025 -0.225 -0.075 -0.125  0.024 -0.000  0.099  0.049  0.074  0.024 -0.125 -0.000  0.049 -0.075  0.024 -0.175 -0.125  0.199  0.298 -0.275  0.373  0.174 -0.000 -0.150 -0.200 -0.150 -0.125 -0.125 -0.200 -0.025 -0.150 -0.100 -0.075 -0.200 -0.175  0.024  0.149 -0.000  0.049 
 0.075 -0.025 -0.224 -0.125 -0.100 -0.174 -0.199 -0.025 -0.149 -0.125 -0.149 -0.025 -0.174  0.025  0.050 -0.199 -0.025 -0.075 -0.025 -0.274 -0.224  0.100 -0.199 -0.224  0.075 -0.075 -0.125 -0.149  0.075 -0.149 -0.075 -0.224 -0.274 -0.324  0.025 -0.125 -0.174 -0.149 -0.174 -0.224  0.050 -0.174 -0.125  0.000 -0.025 -0.149 -0.174 -0.100 -0.224 -0.149 -0.149  0.025 -0.025 -0.125 -0.075 -0.075 -0.050 -0.149 -0.224 -0.249 -0.249 -0.025 -0.224 -0.075 -0.125  0.025  0.000  0.075  0.050  0.075  0.025 -0.125  0.000  0.025 -0.075  0.025 -0.174 -0.125  0.199  0.299 -0.274  0.374  0.174  0.000 -0.149 -0.174 -0.149 -0.125 -0.125 -0.199 -0.025 -0.174 -0.100 -0.075 -0.199 -0.174  0.025  0.149  0.000  0.050 
 0.074 -0.026 -0.225 -0.150 -0.101 -0.175 -0.200 -0.051 -0.126 -0.150 -0.126 -0.026 -0.175  0.024  0.049 -0.200  0.024 -0.101 -0.001 -0.275 -0.225  0.099 -0.200 -0.225  0.074 -0.076 -0.126 -0.150  0.049 -0.126 -0.076 -0.225 -0.275 -0.325 -0.001 -0.126 -0.175 -0.150 -0.175 -0.225  0.049 -0.175 -0.126 -0.001 -0.026 -0.126 -0.175 -0.101 -0.225 -0.150 -0.150  0.024 -0.026 -0.126 -0.101 -0.076 -0.051 -0.150 -0.225 -0.250 -0.250 -0.026 -0.225 -0.076 -0.126  0.049  0.049  0.074  0.049  0.074  0.024 -0.126 -0.001  0.024 -0.076  0.024 -0.175 -0.101  0.223  0.298 -0.275  0.348  0.173 -0.001 -0.150 -0.175 -0.150 -0.126 -0.126 -0.200 -0.001 -0.175 -0.101 -0.076 -0.175 -0.175  0.024  0.148 -0.026  0.024 
 0.075 -0.024 -0.199 -0.149 -0.099 -0.174 -0.199 -0.049 -0.124 -0.124 -0.124 -0.024 -0.199  0.025  0.050 -0.199  0.025 -0.099  0.000 -0.274 -0.249  0.100 -0.199 -0.224  0.075 -0.074 -0.124 -0.174  0.050 -0.124 -0.074 -0.224 -0.298 -0.323  0.000 -0.124 -0.174 -0.149 -0.174 -0.224  0.050 -0.174 -0.124  0.000 -0.024 -0.124 -0.174 -0.099 -0.224 -0.149 -0.149  0.025 -0.024 -0.124 -0.099 -0.074 -0.049 -0.149 -0.224 -0.249 -0.249 -0.024 -0.224 -0.099 -0.099  0.050  0.050  0.050  0.050  0.075  0.025 -0.124  0.000  0.025 -0.074 -0.024 -0.174 -0.099  0.225  0.299 -0.274  0.324  0.175 -0.024 -0.174 -0.174 -0.149 -0.124 -0.124 -0.224  0.000 -0.199 -0.099 -0.099 -0.174 -0.174  0.025  0.150 -0.074  0.025 
 0.076 -0.024 -0.198 -0.148 -0.099 -0.173 -0.198 -0.049 -0.148 -0.099 -0.124 -0.024 -0.198  0.026  0.051 -0.198  0.001 -0.099  0.001 -0.273 -0.248  0.101 -0.198 -0.223  0.076 -0.074 -0.124 -0.173  0.101 -0.124 -0.074 -0.223 -0.298 -0.323  0.026 -0.124 -0.198 -0.173 -0.173 -0.248  0.051 -0.173 -0.124  0.001 -0.024 -0.124 -0.173 -0.099 -0.223 -0.148 -0.148  0.001 -0.024 -0.124 -0.124 -0.074 -0.074 -0.148 -0.223 -0.248 -0.248 -0.024 -0.223 -0.099 -0.099  0.051  0.076  0.001  0.051  0.101  0.026 -0.124  0.001  0.026 -0.074 -0.024 -0.173 -0.099  0.225  0.300 -0.273  0.300  0.175 -0.024 -0.173 -0.173 -0.148 -0.124 -0.124 -0.223  0.026 -0.198 -0.099 -0.099 -0.173 -0.173  0.026  0.150 -0.074  0.001 
 0.076  0.001 -0.173 -0.148 -0.123 -0.173 -0.198 -0.048 -0.148 -0.098 -0.123 -0.023 -0.198  0.051  0.051 -0.198  0.026 -0.098  0.001 -0.273 -0.248  0.101 -0.198 -0.223  0.076 -0.073 -0.123 -0.173  0.101 -0.123 -0.073 -0.223 -0.297 -0.322  0.051 -0.123 -0.198 -0.173 -0.173 -0.248  0.051 -0.198 -0.123  0.026 -0.023 -0.123 -0.173 -0.098 -0.223 -0.148 -0.148 -0.023 -0.023 -0.123 -0.123 -0.073 -0.073 -0.148 -0.223 -0.248 -0.248 -0.023 -0.198 -0.123 -0.098  0.051  0.076  0.001  0.076  0.101  0.026 -0.123  0.001  0.026 -0.073 -0.023 -0.173 -0.098  0.226  0.300 -0.273  0.300  0.176 -0.023 -0.173 -0.173 -0.148 -0.123 -0.123 -0.223  0.026 -0.198 -0.098 -0.098 -0.173 -0.148  0.026  0.126 -0.073  0.001 
 0.075  0.000 -0.199 -0.149 -0.124 -0.174 -0.199 -0.049 -0.149 -0.099 -0.099 -0.024 -0.199  0.025  0.050 -0.199  0.050 -0.099  0.000 -0.274 -0.249  0.100 -0.199 -0.224  0.075 -0.074 -0.149 -0.174  0.100 -0.124 -0.074 -0.224 -0.298 -0.323  0.050 -0.124 -0.199 -0.174 -0.174 -0.249  0.050 -0.199 -0.124  0.025 -0.024 -0.124 -0.174 -0.099 -0.224 -0.149 -0.149 -0.024 -0.024 -0.124 -0.124 -0.074 -0.074 -0.174 -0.224 -0.249 -0.249 -0.024 -0.199 -0.124 -0.099  0.075  0.075 -0.024  0.100  0.100  0.025 -0.124  0.000  0.050 -0.074 -0.024 -0.174 -0.099  0.225  0.299 -0.274  0.299  0.175  0.000 -0.174 -0.149 -0.149 -0.124 -0.124 -0.224  0.025 -0.174 -0.099 -0.099 -0.174 -0.149  0.025  0.125 -0.099 -0.024 
 0.058  0.033 -0.191 -0.066 -0.116 -0.091 -0.216 -0.016 -0.141 -0.141 -0.091 -0.016 -0.191  0.008  0.058 -0.141  0.008 -0.066  0.008 -0.191 -0.216  0.058 -0.166 -0.141  0.058 -0.041 -0.091 -0.116  0.083 -0.091  0.008 -0.141 -0.216 -0.241  0.083 -0.066 -0.141 -0.166 -0.091 -0.216  0.033 -0.166 -0.091  0.083 -0.116 -0.141 -0.091 -0.016 -0.166 -0.091 -0.141 -0.016  0.033 -0.091 -0.066 -0.066 -0.016 -0.116 -0.166 -0.166 -0.191  0.033 -0.166 -0.116 -0.116 -0.016  0.008 -0.016 -0.041  0.158  0.033 -0.066 -0.066 -0.016 -0.016 -0.041 -0.116 -0.141  0.158  0.233 -0.241  0.307  0.133 -0.041 -0.116 -0.116 -0.091 -0.091 -0.066 -0.141  0.033 -0.141 -0.091 -0.016 -0.116 -0.166  0.058  0.033 -0.066 -0.016 
 0.066  0.016 -0.108 -0.083 -0.083 -0.058 -0.158  0.016 -0.058 -0.083 -0.033 -0.083 -0.158  0.016  0.016 -0.058  0.016 -0.008  0.066 -0.108 -0.133  0.041 -0.133 -0.108  0.066 -0.033 -0.008 -0.033  0.091 -0.033  0.041 -0.133 -0.158 -0.158  0.066  0.016 -0.058 -0.108 -0.083 -0.133 -0.008 -0.083 -0.058  0.041 -0.083 -0.058 -0.083 -0.008 -0.133 -0.008 -0.133 -0.033  0.066 -0.033 -0.033 -0.058 -0.008 -0.083 -0.108 -0.083 -0.108 -0.033 -0.108 -0.058 -0.083 -0.008  0.066  0.016 -0.033  0.141 -0.008 -0.033 -0.008 -0.008 -0.058 -0.008 -0.083 -0.133  0.091  0.241 -0.158  0.340  0.016  0.016 -0.083 -0.133 -0.008 -0.033 -0.033 -0.108  0.041 -0.083 -0.058  0.041 -0.058 -0.083  0.041 -0.008 -0.033 -0.008 
 0.058  0.008 -0.091 -0.066 -0.066 -0.041 -0.141  0.033 -0.066 -0.066 -0.016 -0.091 -0.141  0.008 -0.016 -0.041  0.008 -0.016  0.058 -0.091 -0.116  0.033 -0.116 -0.091  0.058 -0.041  0.008 -0.016  0.083 -0.016  0.058 -0.116 -0.141 -0.141  0.058  0.008 -0.041 -0.091 -0.066 -0.116 -0.041 -0.041 -0.066  0.033 -0.066 -0.066 -0.116 -0.016 -0.116 -0.016 -0.116 -0.041  0.083 -0.016 -0.041 -0.066  0.008 -0.066 -0.091 -0.066 -0.091 -0.016 -0.066 -0.041 -0.066 -0.016  0.033  0.033 -0.016  0.158 -0.016 -0.016 -0.016  0.033 -0.041  0.008 -0.091 -0.116  0.033  0.208 -0.141  0.382  0.033  0.033 -0.066 -0.116  0.008 -0.016 -0.016 -0.091  0.058 -0.091 -0.016  0.058 -0.041 -0.066  0.058 -0.016 -0.016 -0.016 
 0.056  0.031 -0.069 -0.069 -0.044 -0.019 -0.119  0.006 -0.044 -0.044 -0.019 -0.069 -0.119  0.031 -0.069 -0.019  0.006  0.006  0.081 -0.069 -0.094  0.056 -0.119 -0.094  0.081 -0.019  0.056  0.006  0.081  0.006  0.056 -0.094 -0.119 -0.119  0.031  0.006 -0.044 -0.069 -0.019 -0.094 -0.019 -0.019 -0.044  0.006 -0.044 -0.044 -0.094 -0.019 -0.094  0.006 -0.119 -0.094  0.081 -0.069 -0.019 -0.094  0.031 -0.044 -0.069 -0.044 -0.069 -0.019 -0.044 -0.019 -0.044  0.006  0.031  0.056  0.006  0.081 -0.044  0.006  0.006  0.031 -0.019 -0.019 -0.069 -0.094 -0.019  0.180 -0.119  0.355  0.006  0.006 -0.044 -0.094  0.031  0.006  0.006 -0.069  0.081 -0.119 -0.044  0.081 -0.044 -0.094  0.031  0.006  0.006 -0.019 
 0.041  0.041 -0.059 -0.059 -0.059 -0.009 -0.109 -0.009 -0.034 -0.034 -0.009 -0.059 -0.109 -0.009 -0.059 -0.009 -0.009  0.016  0.091 -0.059 -0.084  0.066 -0.109 -0.084  0.091 -0.009  0.066  0.016  0.091 -0.034  0.041 -0.084 -0.109 -0.109  0.041  0.016 -0.034 -0.059 -0.009 -0.084 -0.034 -0.009 -0.034  0.016 -0.034 -0.034 -0.084 -0.059 -0.084 -0.009 -0.109 -0.084  0.091 -0.059 -0.009 -0.084  0.041 -0.084 -0.059 -0.034 -0.059 -0.009 -0.034 -0.034 -0.034 -0.034  0.041  0.041 -0.009  0.016 -0.009  0.016  0.016  0.041  0.016 -0.009 -0.059 -0.084 -0.084  0.165 -0.109  0.340  0.016 -0.034 -0.059 -0.084  0.041 -0.034 -0.009 -0.034  0.066 -0.109 -0.059  0.016 -0.034 -0.084 -0.009 -0.009  0.041 -0.009 
 0.054  0.054 -0.045 -0.045 -0.045  0.004 -0.095  0.004 -0.070 -0.020 -0.020 -0.045 -0.095 -0.045 -0.070 -0.020 -0.020  0.029  0.054 -0.070 -0.070  0.054 -0.095 -0.070  0.079  0.004  0.029  0.029  0.104 -0.020 -0.020 -0.070 -0.095 -0.095  0.004  0.004 -0.045 -0.070  0.004 -0.070 -0.045  0.004 -0.020  0.029 -0.045 -0.045 -0.070 -0.070 -0.070 -0.020 -0.095 -0.095  0.079 -0.070  0.004 -0.070 -0.020 -0.070 -0.045 -0.020 -0.045  0.004 -0.020 -0.020 -0.020 -0.045  0.054  0.054  0.004 -0.020  0.004  0.029  0.029  0.029  0.029 -0.020 -0.045 -0.070 -0.070  0.179 -0.095  0.279  0.029 -0.045 -0.045 -0.070  0.029 -0.020 -0.020  0.004  0.054 -0.095 -0.070  0.054 -0.045 -0.070  0.004  0.004  0.029 -0.020 
 0.061  0.061 -0.064 -0.064 -0.064  0.011 -0.089  0.011 -0.064 -0.014 -0.039 -0.039 -0.089 -0.039 -0.064 -0.039 -0.014  0.036  0.036 -0.064 -0.064  0.061 -0.089 -0.064  0.086  0.011 -0.014  0.036  0.111 -0.014 -0.014 -0.064 -0.089 -0.089  0.011  0.011 -0.039 -0.064  0.011 -0.064 -0.039 -0.014  0.011  0.011 -0.064 -0.039 -0.064 -0.064 -0.064 -0.014 -0.089 -0.089  0.086 -0.089 -0.014 -0.064 -0.014 -0.064 -0.039 -0.039 -0.039 -0.014 -0.014  0.011 -0.039 -0.064  0.036  0.061 -0.039  0.011  0.036  0.011  0.036  0.011  0.036 -0.039 -0.039 -0.064 -0.039  0.160 -0.089  0.260  0.061 -0.039 -0.064 -0.064  0.011 -0.014 -0.014  0.011  0.011 -0.089 -0.089  0.061 -0.039 -0.064  0.011 -0.039  0.036 -0.014 
 0.044  0.044 -0.055 -0.055 -0.055  0.019 -0.080  0.019 -0.055 -0.005 -0.055 -0.030 -0.080 -0.030 -0.055 -0.030 -0.030  0.019 -0.005 -0.055 -0.055  0.069 -0.080 -0.055  0.069 -0.005 -0.005  0.044  0.094 -0.005 -0.030 -0.055 -0.080 -0.080  0.019  0.019 -0.030 -0.055 -0.030 -0.055 -0.030 -0.005 -0.005 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.080 -0.080  0.069 -0.080 -0.005 -0.055 -0.030 -0.055 -0.055 -0.030 -0.055 -0.005 -0.005  0.019 -0.030 -0.030  0.019  0.044 -0.030  0.019  0.019  0.019  0.044 -0.005  0.044 -0.030 -0.030 -0.055 -0.055  0.169 -0.080  0.244  0.044 -0.030 -0.055 -0.055 -0.005 -0.005 -0.030  0.019 -0.005 -0.080 -0.080  0.044 -0.030 -0.055 -0.030 -0.030  0.044 -0.005 
 0.050  0.050 -0.050 -0.050 -0.050  0.025 -0.075  0.025 -0.050  0.000 -0.050 -0.025 -0.075 -0.050 -0.050 -0.050 -0.025  0.025  0.000 -0.050 -0.050  0.025 -0.050 -0.025  0.075  0.000  0.000  0.050  0.100 -0.025 -0.050 -0.050 -0.075 -0.075  0.025  0.000 -0.025 -0.050 -0.025 -0.050 -0.025  0.000  0.000 -0.025 -0.050 -0.025 -0.050 -0.050 -0.050 -0.025 -0.050 -0.075  0.050 -0.075 -0.025 -0.050 -0.025 -0.050 -0.050 -0.025 -0.050 -0.025  0.025  0.025 -0.025 -0.025  0.025  0.050 -0.050  0.000  0.025  0.025  0.050  0.000  0.050 -0.025 -0.025 -0.050 -0.050  0.174 -0.075  0.224  0.025 -0.050 -0.050 -0.050  0.000  0.000 -0.025  0.000  0.000 -0.075 -0.075  0.050 -0.025 -0.050 -0.025 -0.025  0.050  0.000 
 0.056  0.056 -0.043 -0.043 -0.043 -0.018 -0.068  0.031 -0.068  0.006 -0.018 -0.018 -0.043 -0.043 -0.018 -0.043 -0.018  0.031 -0.018 -0.018 -0.043  0.031 -0.043 -0.018  0.056 -0.018  0.006  0.031  0.106 -0.043 -0.043 -0.043 -0.068 -0.068  0.006  0.006 -0.043 -0.043 -0.018 -0.043 -0.018  0.006 -0.018 -0.018 -0.043 -0.018 -0.043 -0.043 -0.043 -0.018 -0.018 -0.068  0.031 -0.068 -0.018 -0.068 -0.018 -0.043 -0.068 -0.018 -0.068 -0.018  0.031  0.056 -0.018 -0.018  0.031  0.031 -0.043  0.006  0.031  0.006  0.056  0.031  0.031 -0.043 -0.043 -0.043 -0.043  0.131 -0.068  0.131  0.031 -0.043 -0.043 -0.043 -0.018 -0.018 -0.018  0.006 -0.043 -0.068 -0.068  0.056 -0.018 -0.043 -0.043 -0.018  0.056 -0.043 
 0.065  0.040 -0.060 -0.035 -0.035 -0.010 -0.060 -0.010 -0.060  0.015 -0.035 -0.010 -0.035 -0.060 -0.035 -0.060 -0.010  0.040 -0.010 -0.010 -0.035  0.040 -0.035 -0.035  0.040 -0.010 -0.010  0.040  0.090 -0.035 -0.035 -0.035 -0.060 -0.060 -0.010  0.015 -0.035 -0.035 -0.010 -0.010 -0.010  0.015 -0.010 -0.010 -0.060 -0.010 -0.060 -0.035 -0.035 -0.035 -0.010 -0.060  0.040 -0.060 -0.010 -0.060 -0.035 -0.060 -0.060 -0.035 -0.060 -0.010  0.040  0.065 -0.010 -0.010  0.040  0.040 -0.035  0.015  0.040 -0.010  0.040  0.015  0.015 -0.035 -0.035 -0.035 -0.035  0.090 -0.060  0.115  0.015 -0.035 -0.035 -0.035 -0.010 -0.010 -0.010 -0.010 -0.035 -0.060 -0.035  0.065 -0.010 -0.035 -0.035 -0.010  0.040 -0.035 
 0.072  0.022 -0.052 -0.027 -0.027 -0.002 -0.052 -0.002 -0.052  0.022 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.002  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.047  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002 -0.002 -0.002  0.022 -0.027 -0.002 -0.052 -0.027 -0.052 -0.027 -0.027 -0.027 -0.002 -0.052  0.047 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.002  0.022  0.047 -0.027 -0.002  0.022  0.022 -0.027  0.022  0.047 -0.002  0.022 -0.002  0.022 -0.002 -0.052 -0.027 -0.027  0.072 -0.052  0.072  0.022 -0.027 -0.002 -0.027 -0.027  0.022 -0.002 -0.027 -0.027 -0.052 -0.027  0.047 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 
 0.073  0.048 -0.052 -0.027 -0.027 -0.002 -0.052  0.023 -0.052  0.023 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.002  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.048  0.073 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002 -0.002 -0.002  0.023 -0.027  0.023 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.048 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.002  0.023  0.048 -0.027 -0.002  0.023  0.023 -0.027  0.023  0.048 -0.002  0.023 -0.002  0.023 -0.002 -0.052 -0.027 -0.027  0.048 -0.052  0.048 -0.002 -0.027 -0.002 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.052 -0.027  0.048 -0.027 -0.027 -0.027 -0.002  0.048 -0.027 
 0.074  0.049 -0.050 -0.025 -0.025  0.024 -0.050  0.024 -0.050 -0.000 -0.025 -0.000 -0.025 -0.050 -0.025 -0.050 -0.025  0.049 -0.000 -0.000 -0.050  0.049 -0.025 -0.025  0.049 -0.025 -0.000  0.074  0.074 -0.025 -0.050 -0.025 -0.050 -0.050 -0.000 -0.000 -0.025 -0.025 -0.000  0.024 -0.000  0.024 -0.025  0.024 -0.050 -0.025 -0.025 -0.025 -0.025 -0.025 -0.000 -0.050  0.024 -0.050 -0.000 -0.050 -0.025 -0.050 -0.050 -0.050 -0.025 -0.025  0.024  0.049 -0.025 -0.000  0.024  0.024 -0.025  0.024  0.049 -0.000 -0.000 -0.000  0.024 -0.000 -0.050 -0.000 -0.025  0.049 -0.050  0.049 -0.000 -0.025 -0.000 -0.025 -0.025  0.024 -0.000 -0.025 -0.025 -0.050 -0.025  0.074 -0.025 -0.025 -0.025 -0.000  0.049 -0.025 
 0.074  0.024 -0.051 -0.026 -0.026  0.024 -0.051 -0.001 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.049 -0.001 -0.001 -0.051  0.049 -0.026 -0.026  0.049 -0.026 -0.001  0.074  0.074 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.024 -0.001  0.024 -0.026 -0.001 -0.051 -0.026 -0.051 -0.026 -0.026 -0.026 -0.001 -0.051  0.024 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.024  0.049 -0.026 -0.001  0.024  0.024 -0.026  0.024  0.049 -0.001 -0.001 -0.001  0.024 -0.001 -0.051 -0.001 -0.026  0.074 -0.051  0.049  0.024 -0.026 -0.001 -0.026 -0.026  0.024 -0.001 -0.026 -0.026 -0.051 -0.026  0.074 -0.026 -0.026 -0.026 -0.001  0.049 -0.026 
 0.073  0.023 -0.051 -0.026 -0.026  0.023 -0.051 -0.001 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026 -0.001 -0.051 -0.026 -0.051 -0.026 -0.026 -0.026 -0.001 -0.051  0.023 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.023  0.048 -0.026 -0.001  0.023  0.023 -0.026  0.023  0.048 -0.001  0.023 -0.001  0.023 -0.001 -0.051 -0.001 -0.026  0.073 -0.051  0.048  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.073 -0.026 -0.026 -0.026 -0.001  0.048 -0.026 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.022 -0.002  0.022 -0.027  0.022 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.022 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.022  0.047 -0.002 -0.002  0.022  0.022 -0.027  0.022  0.047  0.022  0.022 -0.002  0.022  0.022 -0.052 -0.002 -0.027  0.072 -0.052  0.047  0.022 -0.027 -0.002 -0.027 -0.027  0.022 -0.002 -0.027 -0.027 -0.052 -0.002  0.072 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 
 0.070  0.045 -0.054 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.004 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.020  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.004 -0.004  0.020  0.020 -0.004  0.020  0.045  0.020  0.020 -0.004  0.020  0.020 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.004  0.070 -0.029 -0.029 -0.029 -0.004  0.045 -0.029 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.055 -0.030 -0.030 -0.030 -0.030 -0.030 -0.005 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.144  0.044 -0.055 -0.055 -0.055 -0.005 -0.055  0.044 -0.080 -0.005 -0.005 -0.005  0.019 -0.030 -0.055 -0.080 -0.055  0.044  0.044 -0.030 -0.055  0.019 -0.055 -0.055  0.069 -0.005 -0.005  0.094  0.069  0.019 -0.080 -0.030 -0.055 -0.080  0.019  0.019 -0.055 -0.030 -0.005 -0.005 -0.030  0.019 -0.030  0.044 -0.055 -0.055 -0.055 -0.005 -0.055 -0.030 -0.005 -0.080  0.069 -0.055 -0.030 -0.030 -0.055 -0.080 -0.080 -0.080 -0.030 -0.055  0.019  0.019 -0.030 -0.005  0.019 -0.005 -0.005 -0.005  0.094  0.069 -0.005  0.044  0.019  0.019 -0.080 -0.005 -0.005  0.219 -0.080  0.144  0.094 -0.005 -0.005 -0.030 -0.030 -0.005 -0.030 -0.030 -0.030 -0.080 -0.005  0.044 -0.030 -0.030 -0.005 -0.005  0.069 -0.030 
 0.190  0.015 -0.084 -0.059 -0.084 -0.034 -0.059 -0.009 -0.134 -0.059 -0.034 -0.059 -0.009 -0.034 -0.034 -0.109 -0.034  0.065  0.065 -0.084 -0.084  0.040 -0.084 -0.009  0.115 -0.034 -0.034  0.040  0.140 -0.009 -0.109 -0.059 -0.109 -0.134  0.015  0.040 -0.084 -0.059 -0.059 -0.059 -0.009  0.040 -0.059  0.115 -0.084 -0.034 -0.109 -0.034 -0.109 -0.059 -0.059  0.015  0.140 -0.059 -0.059 -0.084 -0.059 -0.109 -0.084 -0.109 -0.059 -0.084  0.040 -0.034 -0.059 -0.009  0.040 -0.009 -0.009 -0.034  0.190  0.015 -0.009  0.015  0.040  0.065 -0.084  0.015 -0.009  0.439 -0.134  0.240  0.240 -0.059 -0.009 -0.084 -0.009 -0.009 -0.059 -0.059 -0.084 -0.034 -0.009  0.040 -0.034 -0.009 -0.009  0.040  0.165 -0.084 
 0.218  0.019 -0.131 -0.106 -0.081 -0.006 -0.106 -0.031 -0.106 -0.106 -0.081 -0.081 -0.031 -0.031 -0.031 -0.131 -0.056  0.044  0.119 -0.131 -0.131  0.094 -0.131 -0.031  0.119 -0.056 -0.006 -0.006  0.168 -0.006 -0.081 -0.131 -0.155 -0.180  0.044  0.019 -0.131 -0.081 -0.106 -0.056 -0.031 -0.031 -0.056  0.069 -0.106 -0.081 -0.155 -0.006 -0.106 -0.081 -0.106 -0.056  0.069 -0.081 -0.081 -0.081 -0.081 -0.106 -0.131 -0.106 -0.081 -0.031 -0.031 -0.056 -0.006 -0.006  0.019  0.019  0.019 -0.006  0.193 -0.006  0.019  0.019  0.094  0.069 -0.106 -0.031 -0.006  0.542 -0.180  0.293  0.268 -0.081 -0.006 -0.131  0.019 -0.056 -0.081 -0.106 -0.056 -0.056 -0.056 -0.031 -0.031 -0.031 -0.031  0.019  0.143 -0.056 
 0.181 -0.043 -0.192 -0.142 -0.068 -0.093 -0.068 -0.093 -0.118 -0.118 -0.018 -0.118  0.007 -0.068 -0.043 -0.167 -0.043 -0.018  0.057 -0.192 -0.192  0.082 -0.118 -0.068  0.132 -0.118 -0.018 -0.093  0.181 -0.018 -0.118 -0.192 -0.217 -0.242  0.007 -0.018 -0.118 -0.118 -0.118 -0.068  0.007 -0.068 -0.093  0.156 -0.118 -0.043 -0.192  0.032 -0.142 -0.118 -0.142 -0.068  0.057 -0.043 -0.068  0.007 -0.018 -0.118 -0.167 -0.167 -0.118 -0.043 -0.093 -0.093 -0.068  0.007  0.057  0.082  0.107  0.007  0.231  0.007 -0.043  0.032  0.032  0.007 -0.142 -0.068  0.057  0.630 -0.242  0.256  0.331 -0.043 -0.068 -0.068 -0.043 -0.068 -0.043 -0.167 -0.093 -0.068 -0.093 -0.043 -0.068 -0.068  0.007 -0.018  0.107 -0.018 
 0.189 -0.060 -0.185 -0.135 -0.060 -0.110 -0.085 -0.085 -0.110 -0.160 -0.035 -0.035  0.014 -0.035 -0.060 -0.185 -0.060 -0.010  0.039 -0.185 -0.185  0.089 -0.110 -0.085  0.089 -0.085 -0.035 -0.110  0.139 -0.085 -0.085 -0.210 -0.235 -0.260 -0.010 -0.035 -0.135 -0.085 -0.110 -0.085  0.014 -0.135 -0.110  0.114 -0.135 -0.060 -0.210  0.014 -0.160 -0.135 -0.135 -0.110  0.039 -0.060 -0.085  0.014 -0.010 -0.110 -0.185 -0.210 -0.110 -0.035 -0.160 -0.085 -0.085  0.014  0.014  0.089  0.114  0.064  0.214  0.014 -0.035  0.064  0.014  0.014 -0.160 -0.060  0.064  0.587 -0.260  0.264  0.313 -0.060 -0.110 -0.085 -0.060 -0.085 -0.060 -0.135 -0.085 -0.085 -0.085 -0.035 -0.060 -0.085 -0.010 -0.010  0.114  0.014 
 0.237 -0.037 -0.162 -0.087 -0.037 -0.162 -0.112 -0.062 -0.087 -0.187 -0.012 -0.037  0.012 -0.037  0.037 -0.162 -0.062 -0.062  0.012 -0.187 -0.212  0.087 -0.112 -0.137  0.062 -0.087 -0.062 -0.112  0.087 -0.112 -0.037 -0.262 -0.262 -0.286 -0.012 -0.012 -0.162 -0.087 -0.137 -0.087 -0.012 -0.162 -0.137  0.062 -0.137 -0.062 -0.212  0.037 -0.162 -0.112 -0.137 -0.112  0.062 -0.062 -0.087  0.037  0.012 -0.087 -0.212 -0.212 -0.137 -0.012 -0.187 -0.112 -0.087  0.012  0.012  0.062  0.137  0.137  0.212  0.012 -0.062  0.087 -0.012  0.012 -0.162 -0.037  0.112  0.511 -0.262  0.311  0.311 -0.062 -0.137 -0.087 -0.087 -0.112 -0.037 -0.162 -0.037 -0.112 -0.112 -0.037 -0.112 -0.112 -0.037  0.012  0.087  0.087 
 0.254 -0.045 -0.169 -0.070  0.005 -0.169 -0.120 -0.045 -0.095 -0.194 -0.020 -0.020 -0.020  0.005  0.080 -0.120 -0.070 -0.045  0.005 -0.194 -0.219  0.105 -0.144 -0.144  0.055 -0.095 -0.070 -0.120  0.080 -0.120 -0.045 -0.269 -0.269 -0.294  0.055 -0.020 -0.144 -0.095 -0.169 -0.120 -0.020 -0.169 -0.095  0.055 -0.120 -0.070 -0.194  0.030 -0.169 -0.120 -0.120 -0.120  0.055 -0.045 -0.095  0.030  0.005 -0.070 -0.194 -0.219 -0.144 -0.045 -0.169 -0.095 -0.095  0.005  0.030  0.055  0.130  0.154  0.179  0.030 -0.070  0.105 -0.020  0.005 -0.169 -0.045  0.080  0.478 -0.269  0.279  0.304 -0.070 -0.120 -0.095 -0.095 -0.120 -0.020 -0.169 -0.045 -0.120 -0.120 -0.045 -0.095 -0.120 -0.020  0.005  0.105  0.080 
 0.268 -0.056 -0.180 -0.106  0.019 -0.180 -0.155 -0.056 -0.131 -0.180 -0.031  0.019 -0.031  0.069  0.094 -0.131 -0.081 -0.081  0.019 -0.205 -0.255  0.094 -0.180 -0.155  0.069 -0.131 -0.081 -0.106  0.069 -0.131 -0.031 -0.230 -0.255 -0.305  0.044 -0.056 -0.131 -0.106 -0.155 -0.155 -0.031 -0.180 -0.081  0.019 -0.106 -0.106 -0.230  0.019 -0.180 -0.106 -0.056 -0.131  0.044 -0.006 -0.106  0.019 -0.006 -0.081 -0.205 -0.230 -0.180 -0.031 -0.180 -0.081 -0.106 -0.006  0.044  0.019  0.094  0.143  0.143  0.044 -0.056  0.119 -0.031 -0.006 -0.180 -0.031  0.119  0.467 -0.280  0.268  0.268 -0.056 -0.131 -0.081 -0.106 -0.131 -0.031 -0.205 -0.056 -0.131 -0.081 -0.056 -0.106 -0.131  0.019  0.019  0.094  0.094 
 0.261 -0.063 -0.187 -0.113 -0.013 -0.162 -0.162 -0.063 -0.138 -0.138 -0.038  0.037 -0.038  0.087  0.087 -0.138 -0.088 -0.088  0.012 -0.212 -0.262  0.137 -0.187 -0.162  0.062 -0.162 -0.088 -0.088  0.087 -0.138 -0.038 -0.237 -0.262 -0.312  0.062 -0.063 -0.138 -0.113 -0.138 -0.162 -0.038 -0.187 -0.088  0.012 -0.113 -0.113 -0.212  0.012 -0.162 -0.138 -0.063 -0.138  0.037  0.012 -0.113  0.012 -0.013 -0.138 -0.212 -0.237 -0.187 -0.063 -0.187 -0.113 -0.113 -0.013  0.087  0.012  0.087  0.137  0.112  0.062 -0.063  0.137 -0.038 -0.038 -0.187 -0.038  0.137  0.460 -0.287  0.311  0.261 -0.013 -0.138 -0.088 -0.138 -0.138 -0.038 -0.212 -0.063 -0.088 -0.088 -0.063 -0.138 -0.138  0.012  0.012  0.087  0.087 
 0.280 -0.069 -0.194 -0.094  0.005 -0.144 -0.169 -0.094 -0.144 -0.119  0.005  0.030 -0.044  0.080  0.080 -0.119 -0.094 -0.094  0.005 -0.219 -0.244  0.130 -0.194 -0.169  0.080 -0.169 -0.119 -0.094  0.080 -0.144 -0.019 -0.244 -0.269 -0.269  0.055 -0.069 -0.144 -0.094 -0.069 -0.194 -0.019 -0.194 -0.119  0.005 -0.144 -0.144 -0.219  0.005 -0.169 -0.144 -0.094 -0.119  0.030  0.005 -0.119  0.005  0.005 -0.144 -0.219 -0.244 -0.194 -0.069 -0.194 -0.144 -0.094 -0.044  0.080  0.005  0.080  0.130  0.105  0.055 -0.019  0.180 -0.019 -0.044 -0.194  0.005  0.155  0.454 -0.293  0.354  0.255  0.005 -0.144 -0.069 -0.144 -0.144 -0.044 -0.194 -0.069 -0.094 -0.094 -0.069 -0.144 -0.119  0.030  0.005  0.130  0.080 
 0.281 -0.068 -0.193 -0.093  0.006 -0.143 -0.193 -0.093 -0.118 -0.118  0.006  0.056 -0.043  0.081  0.106 -0.093 -0.093 -0.093  0.006 -0.218 -0.243  0.156 -0.193 -0.193  0.081 -0.168 -0.118 -0.068  0.081 -0.143 -0.018 -0.268 -0.268 -0.268  0.106 -0.093 -0.143 -0.093 -0.068 -0.193 -0.018 -0.193 -0.093  0.006 -0.143 -0.143 -0.218  0.006 -0.168 -0.143 -0.093 -0.118  0.056 -0.043 -0.118  0.006 -0.018 -0.143 -0.218 -0.243 -0.193 -0.068 -0.193 -0.143 -0.093 -0.043  0.081  0.006  0.056  0.106  0.106  0.056 -0.043  0.156 -0.018 -0.068 -0.193 -0.043  0.131  0.455 -0.268  0.355  0.256  0.006 -0.168 -0.068 -0.143 -0.118 -0.018 -0.193 -0.068 -0.093 -0.093 -0.068 -0.143 -0.118  0.031  0.006  0.131  0.081 
 0.303 -0.071 -0.195 -0.096  0.029 -0.145 -0.195 -0.096 -0.096 -0.145  0.029  0.054 -0.071  0.079  0.104 -0.096 -0.096 -0.096  0.029 -0.220 -0.245  0.178 -0.195 -0.195  0.054 -0.145 -0.121 -0.071  0.054 -0.145 -0.021 -0.270 -0.270 -0.270  0.129 -0.096 -0.121 -0.096 -0.071 -0.195 -0.021 -0.195 -0.121  0.004 -0.145 -0.145 -0.220  0.004 -0.170 -0.145 -0.096 -0.096  0.054 -0.096 -0.121  0.004 -0.021 -0.121 -0.220 -0.245 -0.195 -0.021 -0.170 -0.145 -0.121 -0.046  0.054  0.029  0.029  0.104  0.104  0.104 -0.046  0.153 -0.021 -0.046 -0.170 -0.021  0.129  0.452 -0.270  0.353  0.253  0.029 -0.170 -0.071 -0.145 -0.096 -0.021 -0.195 -0.071 -0.071 -0.096 -0.071 -0.145 -0.121  0.104 -0.021  0.129  0.079 
 0.278 -0.071 -0.171 -0.096  0.028 -0.146 -0.171 -0.096 -0.096 -0.121  0.053  0.028 -0.071  0.078  0.103 -0.096 -0.096 -0.071  0.028 -0.221 -0.246  0.178 -0.196 -0.196  0.078 -0.121 -0.121 -0.071  0.053 -0.146 -0.021 -0.271 -0.271 -0.271  0.128 -0.096 -0.121 -0.121 -0.071 -0.196 -0.021 -0.196 -0.121  0.003 -0.146 -0.146 -0.221  0.028 -0.171 -0.146 -0.096 -0.096  0.053 -0.096 -0.146  0.003 -0.021 -0.121 -0.221 -0.246 -0.196 -0.021 -0.171 -0.146 -0.121 -0.046  0.028  0.028  0.003  0.103  0.103  0.103 -0.071  0.153 -0.021 -0.046 -0.171 -0.021  0.128  0.452 -0.221  0.352  0.253  0.028 -0.171 -0.071 -0.146 -0.096 -0.021 -0.196 -0.071 -0.071 -0.096 -0.071 -0.146 -0.146  0.128 -0.021  0.128  0.078 
 0.275 -0.074 -0.174 -0.074  0.025 -0.124 -0.149 -0.099 -0.099 -0.099  0.050  0.025 -0.099  0.075  0.100 -0.099 -0.099 -0.074  0.025 -0.224 -0.249  0.175 -0.199 -0.199  0.075 -0.124 -0.124 -0.099  0.075 -0.149 -0.024 -0.274 -0.298 -0.249  0.125 -0.099 -0.124 -0.174 -0.074 -0.224  0.000 -0.199 -0.099  0.000 -0.099 -0.149 -0.224  0.025 -0.199 -0.149 -0.099 -0.099  0.025 -0.074 -0.199 -0.024 -0.049 -0.099 -0.224 -0.249 -0.199 -0.024 -0.174 -0.149 -0.124  0.000  0.050 -0.024  0.000  0.100  0.100  0.100 -0.074  0.100 -0.049  0.000 -0.174 -0.049  0.125  0.399 -0.224  0.399  0.250  0.050 -0.149 -0.149 -0.149 -0.099 -0.024 -0.199 -0.074 -0.099 -0.099 -0.074 -0.149 -0.149  0.125  0.000  0.100  0.075 
 0.247 -0.077 -0.176 -0.077  0.023 -0.127 -0.151 -0.127 -0.102 -0.102  0.048  0.048 -0.127  0.073  0.098 -0.102 -0.052 -0.077  0.023 -0.226 -0.251  0.172 -0.201 -0.201  0.073 -0.127 -0.127 -0.127  0.098 -0.151 -0.027 -0.276 -0.301 -0.226  0.123 -0.102 -0.127 -0.176 -0.077 -0.226 -0.002 -0.201 -0.102 -0.002 -0.102 -0.151 -0.226 -0.002 -0.201 -0.151 -0.077 -0.077  0.023 -0.077 -0.201 -0.027 -0.052 -0.102 -0.226 -0.251 -0.201 -0.027 -0.176 -0.151 -0.151  0.023  0.048 -0.027 -0.002  0.098  0.073  0.048 -0.077  0.098 -0.052 -0.002 -0.176 -0.077  0.123  0.372 -0.226  0.422  0.222  0.048 -0.151 -0.127 -0.151 -0.102 -0.027 -0.201 -0.077 -0.127 -0.102 -0.077 -0.151 -0.151  0.147 -0.002  0.098  0.048 
 0.248 -0.076 -0.176 -0.076  0.023 -0.126 -0.151 -0.126 -0.101 -0.101  0.048  0.048 -0.126  0.073  0.098 -0.101 -0.026 -0.076  0.023 -0.226 -0.251  0.198 -0.201 -0.201  0.073 -0.126 -0.126 -0.126  0.098 -0.151 -0.026 -0.276 -0.300 -0.226  0.123 -0.101 -0.126 -0.176 -0.076 -0.226 -0.001 -0.201 -0.101 -0.026 -0.101 -0.151 -0.226  0.023 -0.201 -0.126 -0.076 -0.076  0.023 -0.076 -0.201 -0.026 -0.051 -0.126 -0.226 -0.251 -0.176 -0.026 -0.176 -0.151 -0.151  0.023  0.048 -0.026 -0.051  0.098  0.048  0.023 -0.076  0.098 -0.051  0.023 -0.176 -0.076  0.123  0.322 -0.226  0.422  0.198  0.048 -0.126 -0.126 -0.151 -0.076 -0.026 -0.201 -0.076 -0.126 -0.101 -0.076 -0.151 -0.151  0.148 -0.001  0.073  0.048 
 0.246 -0.078 -0.177 -0.053  0.022 -0.128 -0.152 -0.128 -0.103 -0.103  0.047  0.047 -0.128  0.072  0.097 -0.103 -0.028 -0.078  0.022 -0.227 -0.252  0.196 -0.202 -0.202  0.072 -0.128 -0.128 -0.128  0.097 -0.152 -0.028 -0.277 -0.302 -0.227  0.122 -0.103 -0.128 -0.177 -0.078 -0.227 -0.003 -0.202 -0.103 -0.028 -0.103 -0.152 -0.227  0.022 -0.202 -0.128 -0.078 -0.078  0.047 -0.078 -0.202 -0.028 -0.053 -0.128 -0.227 -0.252 -0.177 -0.003 -0.177 -0.152 -0.152  0.022  0.047 -0.028 -0.053  0.097  0.047  0.022 -0.078  0.097 -0.053  0.022 -0.177 -0.078  0.122  0.321 -0.227  0.421  0.196  0.047 -0.128 -0.128 -0.152 -0.078 -0.028 -0.202 -0.078 -0.128 -0.103 -0.078 -0.152 -0.152  0.146 -0.003  0.072  0.047 
 0.248 -0.051 -0.176 -0.051  0.023 -0.126 -0.151 -0.126 -0.101 -0.101 -0.001  0.073 -0.126  0.073  0.098 -0.101  0.023 -0.076  0.023 -0.251 -0.251  0.173 -0.226 -0.201  0.048 -0.126 -0.126 -0.126  0.098 -0.126 -0.026 -0.276 -0.300 -0.226  0.123 -0.101 -0.126 -0.176 -0.076 -0.226 -0.001 -0.201 -0.076 -0.026 -0.101 -0.151 -0.226 -0.026 -0.201 -0.126 -0.101 -0.051  0.048 -0.076 -0.201 -0.026 -0.051 -0.151 -0.226 -0.251 -0.201 -0.001 -0.151 -0.151 -0.151  0.023  0.073 -0.051 -0.076  0.098  0.048 -0.026 -0.076  0.073 -0.051 -0.001 -0.201 -0.076  0.123  0.297 -0.226  0.422  0.198  0.048 -0.151 -0.126 -0.151 -0.101 -0.026 -0.201 -0.051 -0.126 -0.101 -0.076 -0.151 -0.151  0.148 -0.026  0.073 -0.001 
 0.273 -0.051 -0.175 -0.051  0.024 -0.126 -0.175 -0.126 -0.076 -0.101 -0.001  0.074 -0.126  0.099  0.099 -0.101  0.049 -0.076  0.024 -0.250 -0.250  0.173 -0.250 -0.225  0.049 -0.126 -0.126 -0.126  0.099 -0.126 -0.051 -0.275 -0.300 -0.225  0.124 -0.101 -0.126 -0.175 -0.076 -0.225 -0.001 -0.200 -0.076 -0.026 -0.101 -0.150 -0.225 -0.026 -0.200 -0.126 -0.126 -0.026  0.049 -0.076 -0.200 -0.026 -0.051 -0.150 -0.225 -0.250 -0.200 -0.001 -0.150 -0.150 -0.150  0.049  0.074 -0.051 -0.076  0.099  0.049 -0.026 -0.051  0.074 -0.051 -0.001 -0.200 -0.101  0.124  0.298 -0.225  0.423  0.198  0.024 -0.175 -0.126 -0.150 -0.101 -0.026 -0.200 -0.051 -0.126 -0.101 -0.101 -0.150 -0.126  0.148 -0.026  0.074 -0.001 
 0.275 -0.049 -0.174 -0.049  0.025 -0.124 -0.174 -0.124 -0.074 -0.099  0.000  0.075 -0.149  0.100  0.125 -0.099  0.075 -0.074  0.025 -0.249 -0.249  0.175 -0.249 -0.224  0.075 -0.124 -0.124 -0.124  0.100 -0.124 -0.049 -0.274 -0.298 -0.224  0.125 -0.099 -0.124 -0.174 -0.074 -0.224  0.000 -0.199 -0.074 -0.024 -0.099 -0.149 -0.199 -0.024 -0.199 -0.124 -0.124 -0.024  0.075 -0.074 -0.199 -0.049 -0.049 -0.149 -0.224 -0.249 -0.224  0.000 -0.149 -0.149 -0.149  0.050  0.050 -0.049 -0.074  0.100  0.050 -0.049 -0.049  0.075 -0.049  0.000 -0.199 -0.099  0.125  0.299 -0.224  0.424  0.200  0.025 -0.174 -0.124 -0.149 -0.099 -0.024 -0.199 -0.074 -0.124 -0.099 -0.099 -0.149 -0.124  0.150 -0.024  0.075  0.000 
 0.290 -0.034 -0.134 -0.034 -0.034 -0.084 -0.134 -0.109 -0.059 -0.084 -0.059  0.041 -0.158  0.141  0.041 -0.059 -0.084 -0.084  0.041 -0.208 -0.208  0.141 -0.183 -0.183  0.091 -0.084 -0.059 -0.084  0.091 -0.109  0.016 -0.233 -0.233 -0.208  0.141 -0.034 -0.084 -0.134 -0.109 -0.233 -0.059 -0.134 -0.034  0.016 -0.109 -0.084 -0.158 -0.034 -0.158 -0.059 -0.134  0.016  0.091 -0.009 -0.134 -0.059 -0.009 -0.158 -0.208 -0.183 -0.158 -0.009 -0.084 -0.134 -0.183  0.016  0.041 -0.084 -0.034  0.066 -0.034 -0.084 -0.034  0.066 -0.059 -0.009 -0.183 -0.034  0.066  0.340 -0.183  0.415  0.190  0.016 -0.134 -0.134 -0.084 -0.059 -0.059 -0.183 -0.034 -0.158 -0.084 -0.059 -0.134 -0.109  0.165 -0.084  0.091 -0.009 
 0.212  0.013 -0.087 -0.062 -0.037 -0.037 -0.112 -0.087 -0.087 -0.062 -0.087  0.038 -0.137  0.013  0.013  0.013 -0.037 -0.037  0.063 -0.112 -0.137  0.113 -0.137 -0.112  0.088 -0.062  0.013 -0.037  0.138 -0.037  0.063 -0.137 -0.137 -0.137  0.038 -0.012 -0.062 -0.137 -0.062 -0.161 -0.037 -0.037 -0.037 -0.012 -0.112 -0.062 -0.137 -0.012 -0.087 -0.012 -0.137 -0.012  0.113 -0.012 -0.062 -0.062 -0.012 -0.087 -0.112 -0.087 -0.112  0.013 -0.062 -0.062 -0.087 -0.012  0.038 -0.012 -0.087 -0.012 -0.087 -0.062 -0.012  0.038 -0.062 -0.012 -0.087 -0.012 -0.012  0.287 -0.161  0.312  0.113  0.063 -0.112 -0.112 -0.012  0.013 -0.012 -0.087 -0.012 -0.112 -0.087  0.013 -0.062 -0.087  0.063 -0.087  0.013 -0.012 
 0.165 -0.009 -0.059 -0.059 -0.034 -0.034 -0.109 -0.059 -0.084 -0.059 -0.059 -0.059 -0.109 -0.009 -0.009 -0.009 -0.009 -0.034  0.090 -0.084 -0.109  0.115 -0.109 -0.109  0.065 -0.034  0.040 -0.009  0.115 -0.009  0.040 -0.109 -0.134 -0.134  0.015 -0.034 -0.059 -0.109 -0.059 -0.134 -0.034 -0.009 -0.009 -0.009 -0.084 -0.084 -0.109  0.015 -0.059  0.015 -0.134 -0.034  0.090  0.015 -0.034 -0.059 -0.059 -0.059 -0.084 -0.059 -0.084  0.015 -0.034 -0.034 -0.059 -0.009  0.040  0.015 -0.059 -0.009 -0.084 -0.034  0.015  0.065 -0.059 -0.034 -0.084 -0.059 -0.034  0.289 -0.134  0.339  0.090 -0.009 -0.134 -0.084  0.015  0.040  0.015 -0.084 -0.009 -0.109 -0.059  0.015 -0.059 -0.084  0.040 -0.109  0.040 -0.009 
 0.139  0.014 -0.061 -0.061 -0.011 -0.011 -0.086 -0.061 -0.061 -0.036 -0.036 -0.061 -0.086 -0.011 -0.061 -0.011 -0.011 -0.036  0.114 -0.061 -0.111  0.064 -0.086 -0.086  0.089 -0.011  0.064  0.014  0.139  0.014 -0.011 -0.086 -0.111 -0.111  0.039 -0.011 -0.036 -0.086 -0.061 -0.111 -0.061  0.014 -0.011 -0.011 -0.061 -0.061 -0.111  0.014 -0.086 -0.036 -0.111 -0.036  0.114 -0.011 -0.011 -0.036 -0.061 -0.086 -0.061 -0.061 -0.061  0.014 -0.036 -0.011 -0.061 -0.011  0.039  0.039 -0.061 -0.036 -0.061 -0.011  0.039  0.014 -0.061 -0.036 -0.061 -0.086 -0.086  0.213 -0.111  0.313  0.064 -0.036 -0.111 -0.086 -0.011  0.039  0.014 -0.061 -0.011 -0.086 -0.061  0.039 -0.036 -0.061  0.039 -0.111 -0.011 -0.036 
 0.076  0.026 -0.074 -0.049 -0.024  0.001 -0.074 -0.049 -0.049 -0.024 -0.049 -0.074 -0.074 -0.024 -0.049 -0.049  0.001 -0.024  0.126 -0.074 -0.099  0.051 -0.099 -0.074  0.101  0.001  0.026  0.001  0.126  0.001  0.001 -0.074 -0.099 -0.099  0.051 -0.024 -0.074 -0.074 -0.049 -0.099 -0.049  0.001 -0.024  0.001 -0.049 -0.074 -0.099 -0.024 -0.074 -0.024 -0.099 -0.049  0.126 -0.049  0.001 -0.024 -0.049 -0.074 -0.049 -0.049 -0.049  0.001 -0.024  0.001 -0.074 -0.024 -0.024  0.051 -0.074 -0.024 -0.049  0.001  0.051  0.001 -0.049 -0.049 -0.049 -0.074 -0.074  0.225 -0.099  0.325  0.076 -0.049 -0.099 -0.074  0.001  0.001  0.026 -0.049  0.001 -0.074 -0.074  0.051 -0.024 -0.074  0.026 -0.099  0.001 -0.024 
 0.068  0.043 -0.057 -0.032 -0.032  0.018 -0.082 -0.057 -0.057 -0.007 -0.007 -0.057 -0.082 -0.032 -0.082 -0.032 -0.007 -0.032  0.068 -0.032 -0.082  0.043 -0.082 -0.057  0.093  0.018  0.043  0.018  0.093 -0.007 -0.007 -0.057 -0.082 -0.082  0.068 -0.007 -0.057 -0.082 -0.057 -0.082 -0.032 -0.007 -0.032  0.018 -0.057 -0.057 -0.082 -0.057 -0.057 -0.032 -0.057 -0.082  0.118 -0.057 -0.007 -0.057 -0.057 -0.082 -0.032 -0.082 -0.032  0.018 -0.007 -0.032 -0.057 -0.032 -0.007  0.068 -0.057 -0.032 -0.057  0.018  0.043  0.018 -0.032 -0.032 -0.032 -0.057 -0.057  0.217 -0.082  0.317  0.043 -0.032 -0.082 -0.057  0.018  0.018  0.018 -0.032 -0.007 -0.082 -0.057  0.043 -0.007 -0.082  0.018 -0.057  0.018 -0.007 
 0.075  0.050 -0.075 -0.050 -0.025  0.025 -0.075 -0.050 -0.050  0.000  0.000 -0.050 -0.075 -0.050 -0.075 -0.025  0.000 -0.025  0.050 -0.025 -0.075  0.050 -0.075 -0.050  0.075  0.025  0.025  0.025  0.100  0.000 -0.025 -0.050 -0.075 -0.075  0.025  0.000 -0.050 -0.075 -0.050 -0.050 -0.050  0.000  0.000 -0.025 -0.075 -0.050 -0.075 -0.050 -0.050 -0.025 -0.050 -0.075  0.100 -0.075  0.000 -0.050 -0.050 -0.075 -0.025 -0.075 -0.025  0.000  0.000 -0.025 -0.050 -0.025  0.000  0.050 -0.025 -0.025  0.000  0.025  0.050  0.000 -0.025 -0.025 -0.025 -0.050 -0.050  0.199 -0.075  0.274  0.050 -0.025 -0.075 -0.050  0.025  0.000  0.025 -0.025  0.000 -0.075 -0.075  0.050 -0.025 -0.075  0.025 -0.050  0.025  0.000 
 0.081  0.031 -0.069 -0.044 -0.019  0.031 -0.069 -0.019 -0.069  0.006 -0.019 -0.019 -0.044 -0.044 -0.044 -0.044 -0.019  0.031  0.006 -0.019 -0.069  0.081 -0.069 -0.069  0.056 -0.019  0.006  0.056  0.106  0.006 -0.019 -0.044 -0.069 -0.069 -0.019  0.006 -0.044 -0.044 -0.019 -0.019 -0.019  0.006  0.006  0.006 -0.069 -0.044 -0.069 -0.044 -0.044 -0.044 -0.044 -0.069  0.106 -0.069  0.006 -0.044 -0.044 -0.069 -0.019 -0.069 -0.019 -0.044  0.006  0.006 -0.044 -0.019  0.006  0.056 -0.019  0.006  0.031  0.031  0.031  0.006 -0.019 -0.044 -0.044 -0.044 -0.044  0.131 -0.069  0.230  0.006 -0.019 -0.069 -0.044 -0.019 -0.019  0.006 -0.044  0.006 -0.069 -0.044  0.031 -0.019 -0.069  0.006 -0.019  0.031 -0.044 
 0.085  0.035 -0.064 -0.039 -0.014  0.035 -0.064 -0.014 -0.064  0.010 -0.039 -0.014 -0.039 -0.039 -0.039 -0.064 -0.039  0.035 -0.039 -0.014 -0.064  0.085 -0.064 -0.064  0.060 -0.014 -0.014  0.060  0.110  0.010 -0.039 -0.039 -0.064 -0.064 -0.014  0.010 -0.039 -0.039 -0.014 -0.014 -0.014  0.010 -0.014  0.010 -0.064 -0.039 -0.064 -0.039 -0.039 -0.039 -0.039 -0.064  0.085 -0.064 -0.014 -0.039 -0.039 -0.064 -0.039 -0.064 -0.039 -0.039  0.010  0.035 -0.039 -0.014  0.035  0.035 -0.014 -0.014  0.035  0.035  0.010  0.010  0.010 -0.039 -0.039 -0.039 -0.064  0.135 -0.064  0.235 -0.014 -0.014 -0.064 -0.039 -0.014 -0.014 -0.014 -0.014  0.010 -0.064 -0.039  0.035 -0.014 -0.064 -0.039 -0.014  0.035 -0.039 
 0.064  0.014 -0.061 -0.036 -0.036  0.039 -0.061 -0.011 -0.061 -0.011 -0.036 -0.011 -0.036 -0.061 -0.036 -0.061 -0.036  0.039 -0.011 -0.011 -0.061  0.114 -0.061 -0.061  0.039 -0.011 -0.011  0.064  0.114 -0.011 -0.036 -0.036 -0.061 -0.061 -0.011  0.014 -0.061 -0.036 -0.011  0.014 -0.011  0.014 -0.036 -0.011 -0.061 -0.036 -0.061 -0.011 -0.036 -0.036 -0.036 -0.061  0.039 -0.061 -0.011 -0.036 -0.036 -0.061 -0.061 -0.061 -0.036 -0.036  0.014  0.039 -0.036 -0.011  0.039  0.014 -0.011 -0.011  0.039  0.014  0.014 -0.011  0.014 -0.011 -0.061 -0.011 -0.061  0.089 -0.061  0.114 -0.011 -0.036 -0.036 -0.036 -0.036  0.039 -0.011 -0.011 -0.011 -0.061 -0.036  0.064 -0.011 -0.036 -0.036  0.014  0.039 -0.036 
 0.067  0.017 -0.058 -0.033 -0.033  0.042 -0.058 -0.008 -0.058 -0.008 -0.033 -0.008 -0.033 -0.058 -0.033 -0.058 -0.033  0.042 -0.008 -0.008 -0.058  0.092 -0.058 -0.058  0.042 -0.033 -0.008  0.067  0.117 -0.033 -0.033 -0.033 -0.058 -0.058 -0.008  0.017 -0.058 -0.033 -0.008  0.017 -0.008  0.017 -0.008 -0.008 -0.058 -0.033 -0.058 -0.008 -0.033 -0.033 -0.033 -0.058  0.017 -0.058 -0.008 -0.058 -0.033 -0.058 -0.058 -0.058 -0.033 -0.033  0.017  0.042 -0.033 -0.008  0.042  0.017 -0.033 -0.008  0.042  0.017  0.017 -0.008  0.017 -0.008 -0.058 -0.008 -0.058  0.067 -0.058  0.067 -0.008 -0.033 -0.033 -0.033 -0.033  0.042 -0.008 -0.008 -0.008 -0.058 -0.033  0.067 -0.033 -0.033 -0.033  0.017  0.042 -0.033 
 0.067  0.017 -0.058 -0.033 -0.033  0.042 -0.058 -0.008 -0.058 -0.008 -0.033 -0.008 -0.033 -0.058 -0.033 -0.058 -0.033  0.042 -0.008 -0.008 -0.058  0.067 -0.033 -0.033  0.042 -0.033 -0.008  0.067  0.092 -0.033 -0.033 -0.033 -0.058 -0.058 -0.008  0.017 -0.033 -0.033 -0.008  0.017 -0.008  0.017 -0.033 -0.008 -0.058 -0.008 -0.058 -0.033 -0.033 -0.033 -0.008 -0.058  0.017 -0.058 -0.008 -0.058 -0.033 -0.058 -0.058 -0.058 -0.033 -0.033  0.017  0.042 -0.033 -0.008  0.042  0.017 -0.033  0.017  0.042  0.017  0.017 -0.008  0.017 -0.008 -0.058 -0.008 -0.033  0.042 -0.058  0.067 -0.008 -0.033 -0.008 -0.033 -0.033  0.042 -0.008 -0.033 -0.033 -0.058 -0.033  0.067 -0.033 -0.033 -0.033  0.017  0.042 -0.033 
 0.068  0.018 -0.056 -0.031 -0.031  0.043 -0.056 -0.006 -0.056 -0.006 -0.031 -0.006 -0.031 -0.056 -0.031 -0.056 -0.031  0.043 -0.006 -0.006 -0.056  0.043 -0.031 -0.031  0.043 -0.031 -0.006  0.068  0.093 -0.031 -0.031 -0.031 -0.056 -0.056 -0.006  0.018 -0.031 -0.031 -0.006  0.018 -0.006  0.018 -0.031 -0.006 -0.056 -0.006 -0.056 -0.031 -0.031 -0.031 -0.006 -0.056  0.018 -0.056 -0.006 -0.056 -0.031 -0.056 -0.056 -0.056 -0.031 -0.031  0.018  0.043 -0.031 -0.006  0.043  0.018 -0.031  0.018  0.043 -0.006  0.018 -0.006  0.018 -0.006 -0.056 -0.006 -0.031  0.043 -0.056  0.043 -0.006 -0.031 -0.006 -0.031 -0.031  0.043 -0.006 -0.031 -0.031 -0.056 -0.031  0.068 -0.031 -0.031 -0.031  0.018  0.043 -0.031 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022  0.022 -0.028  0.022  0.047 -0.003  0.022 -0.003  0.022 -0.003 -0.053 -0.003 -0.028  0.072 -0.053  0.047  0.022 -0.028 -0.003 -0.028 -0.028  0.047 -0.003 -0.028 -0.028 -0.053 -0.028  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022  0.022 -0.028  0.022  0.047 -0.003  0.022 -0.003  0.022 -0.003 -0.053 -0.003 -0.028  0.072 -0.053  0.047  0.022 -0.028 -0.003 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.028  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022  0.022 -0.003  0.022  0.047 -0.003  0.022 -0.003  0.022 -0.003 -0.053 -0.003 -0.028  0.072 -0.053  0.047  0.022 -0.028  0.022 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.028  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.020  0.020 -0.004  0.020 -0.029  0.020 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.029 -0.004  0.020  0.020  0.020  0.020  0.045 -0.004  0.020 -0.004  0.020 -0.004 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.029  0.070 -0.029 -0.004 -0.029 -0.004  0.045 -0.029 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.064  0.064 -0.061 -0.036 -0.036 -0.011 -0.061  0.039 -0.086 -0.011 -0.011 -0.036 -0.061 -0.061 -0.061 -0.061 -0.061  0.089 -0.011 -0.036 -0.086  0.089 -0.036 -0.061  0.039 -0.011 -0.011  0.064  0.089 -0.061 -0.061 -0.036 -0.086 -0.086  0.014  0.014 -0.061 -0.036 -0.011 -0.011 -0.011  0.039 -0.011  0.064 -0.061  0.014 -0.061  0.014 -0.036 -0.061 -0.011 -0.061  0.039 -0.036 -0.011 -0.061 -0.061 -0.061 -0.061 -0.061 -0.036 -0.061  0.039  0.014 -0.011 -0.011  0.039 -0.011 -0.011  0.014  0.089  0.014  0.039  0.014  0.039  0.039 -0.086 -0.036 -0.011  0.139 -0.086  0.188  0.064 -0.036 -0.011 -0.011 -0.036 -0.011 -0.011 -0.061 -0.061 -0.086 -0.036  0.039 -0.036 -0.011 -0.011 -0.036  0.064 -0.036 
 0.145  0.021 -0.104 -0.054 -0.054 -0.004 -0.054 -0.029 -0.104 -0.079 -0.029 -0.029 -0.054 -0.054 -0.079 -0.104 -0.029  0.071  0.021 -0.104 -0.104  0.145 -0.104 -0.079  0.046 -0.054 -0.004  0.046  0.121 -0.004 -0.129 -0.054 -0.129 -0.153 -0.004  0.046 -0.079 -0.079 -0.054 -0.054 -0.004 -0.004 -0.029  0.071 -0.104 -0.029 -0.104  0.021 -0.079 -0.054 -0.054 -0.054  0.121 -0.104 -0.079 -0.104 -0.054 -0.079 -0.104 -0.129 -0.079 -0.079 -0.004 -0.054 -0.029 -0.004  0.046  0.021 -0.029 -0.029  0.145 -0.004 -0.004 -0.004  0.021  0.046 -0.129 -0.079  0.021  0.245 -0.153  0.320  0.170 -0.104 -0.029 -0.029 -0.054 -0.029 -0.054 -0.079 -0.079 -0.079 -0.054  0.021 -0.079 -0.004 -0.029 -0.004  0.096 -0.054 
 0.233  0.008 -0.141 -0.091 -0.066 -0.041 -0.116 -0.041 -0.116 -0.116 -0.016 -0.016 -0.091 -0.016 -0.116 -0.141 -0.066  0.058  0.033 -0.141 -0.141  0.158 -0.141 -0.116  0.083 -0.066 -0.041  0.008  0.083 -0.041 -0.091 -0.091 -0.166 -0.191 -0.016  0.033 -0.116 -0.091 -0.116 -0.091 -0.041 -0.041 -0.066  0.058 -0.141 -0.016 -0.141  0.058 -0.116 -0.066 -0.091 -0.016  0.133 -0.141 -0.041 -0.091 -0.066 -0.091 -0.116 -0.141 -0.116  0.033 -0.016 -0.066 -0.066 -0.016  0.083  0.033  0.008 -0.041  0.233 -0.016 -0.041  0.008  0.008  0.108 -0.116  0.033  0.008  0.307 -0.191  0.432  0.283 -0.116 -0.066 -0.066 -0.016 -0.041 -0.041 -0.091 -0.066 -0.066 -0.091  0.008 -0.041 -0.041 -0.091  0.008  0.058 -0.091 
 0.245 -0.004 -0.178 -0.104  0.021 -0.104 -0.178 -0.079 -0.104 -0.178  0.021 -0.029 -0.129 -0.004 -0.004 -0.153 -0.104 -0.004  0.046 -0.203 -0.203  0.145 -0.178 -0.129  0.121 -0.104 -0.054 -0.029  0.121 -0.104 -0.054 -0.153 -0.228 -0.253 -0.029  0.046 -0.129 -0.104 -0.153 -0.104 -0.029 -0.104 -0.129  0.071 -0.129 -0.079 -0.178  0.071 -0.104 -0.029 -0.153 -0.004  0.096 -0.079 -0.104 -0.104 -0.054 -0.079 -0.178 -0.178 -0.129  0.046 -0.079 -0.104 -0.104 -0.054  0.046 -0.004  0.096 -0.029  0.245 -0.029 -0.029  0.046  0.021  0.096 -0.129  0.021  0.071  0.370 -0.253  0.444  0.295 -0.104 -0.104 -0.029 -0.054 -0.079 -0.029 -0.153 -0.029 -0.079 -0.153  0.046 -0.054 -0.079 -0.054  0.071  0.021 -0.079 
 0.228 -0.021 -0.195 -0.071  0.104 -0.096 -0.220 -0.096 -0.121 -0.195 -0.021 -0.021 -0.096  0.004  0.079 -0.145 -0.121 -0.021  0.029 -0.220 -0.220  0.153 -0.195 -0.121  0.104 -0.121 -0.046 -0.021  0.104 -0.071 -0.046 -0.145 -0.245 -0.270  0.129  0.029 -0.145 -0.145 -0.170 -0.121 -0.071 -0.121 -0.145  0.054 -0.145 -0.096 -0.145  0.079 -0.096 -0.046 -0.145 -0.021  0.129 -0.021 -0.121 -0.096 -0.021 -0.071 -0.195 -0.195 -0.170  0.029 -0.121 -0.121 -0.121 -0.046  0.029  0.004  0.079  0.004  0.203  0.004 -0.046  0.029  0.029  0.079 -0.145  0.104  0.104  0.378 -0.270  0.427  0.303 -0.071 -0.121 -0.021 -0.071 -0.096 -0.021 -0.170 -0.021 -0.121 -0.145  0.029 -0.096 -0.096 -0.046  0.029  0.004 -0.021 
 0.234 -0.040 -0.190 -0.065  0.134 -0.140 -0.165 -0.065 -0.065 -0.165  0.009 -0.040 -0.115  0.034  0.059 -0.165 -0.090 -0.065  0.034 -0.215 -0.215  0.209 -0.215 -0.115  0.084 -0.140 -0.040 -0.065  0.084 -0.090 -0.040 -0.165 -0.265 -0.289  0.134  0.009 -0.115 -0.165 -0.165 -0.165 -0.040 -0.140 -0.140  0.059 -0.165 -0.115 -0.165  0.059 -0.115 -0.065 -0.140 -0.040  0.109 -0.040 -0.140 -0.115 -0.015 -0.065 -0.215 -0.215 -0.165  0.034 -0.140 -0.115 -0.115 -0.040  0.009 -0.015  0.084  0.034  0.209  0.009 -0.065  0.009  0.009  0.059 -0.140  0.059  0.134  0.383 -0.289  0.433  0.284 -0.065 -0.115 -0.015 -0.090 -0.115 -0.015 -0.165 -0.040 -0.140 -0.115  0.009 -0.115 -0.115 -0.015  0.009 -0.015  0.059 
 0.228 -0.071 -0.220 -0.071  0.129 -0.145 -0.170 -0.096 -0.071 -0.145  0.004 -0.021 -0.121  0.004  0.079 -0.145 -0.096 -0.071  0.029 -0.220 -0.220  0.228 -0.220 -0.121  0.079 -0.170 -0.046 -0.071  0.079 -0.096 -0.046 -0.170 -0.270 -0.295  0.129  0.004 -0.121 -0.170 -0.145 -0.195 -0.046 -0.145 -0.145  0.029 -0.145 -0.121 -0.195  0.054 -0.121 -0.096 -0.121 -0.021  0.079 -0.046 -0.145 -0.096  0.004 -0.096 -0.220 -0.220 -0.170  0.029 -0.145 -0.121 -0.121 -0.046  0.004 -0.021  0.054  0.054  0.203 -0.021 -0.071  0.029 -0.021  0.054 -0.145  0.029  0.153  0.403 -0.295  0.427  0.278 -0.071 -0.096 -0.021 -0.096 -0.121 -0.021 -0.170 -0.046 -0.170 -0.121  0.029 -0.121 -0.145  0.029 -0.021 -0.021  0.079 
 0.243 -0.081 -0.230 -0.081  0.119 -0.131 -0.180 -0.081 -0.056 -0.131 -0.006 -0.031 -0.131  0.044  0.119 -0.131 -0.106 -0.081  0.019 -0.205 -0.205  0.218 -0.230 -0.131  0.069 -0.180 -0.056 -0.056  0.094 -0.106 -0.056 -0.205 -0.280 -0.305  0.143 -0.056 -0.131 -0.180 -0.131 -0.205 -0.056 -0.180 -0.155  0.019 -0.155 -0.106 -0.205  0.044 -0.131 -0.106 -0.081 -0.006  0.069 -0.056 -0.155 -0.031 -0.006 -0.106 -0.230 -0.230 -0.155  0.044 -0.131 -0.081 -0.131 -0.056  0.019 -0.006  0.019  0.094  0.168 -0.006 -0.081  0.069 -0.031  0.069 -0.155  0.044  0.193  0.393 -0.305  0.418  0.293 -0.081 -0.131 -0.031 -0.106 -0.106 -0.031 -0.180 -0.056 -0.180 -0.131  0.019 -0.131 -0.155  0.069 -0.031 -0.006  0.069 
 0.239 -0.060 -0.234 -0.085  0.115 -0.135 -0.159 -0.110 -0.060 -0.135 -0.010 -0.010 -0.135  0.040  0.140 -0.110 -0.110 -0.085  0.015 -0.209 -0.209  0.214 -0.234 -0.135  0.090 -0.135 -0.060 -0.060  0.090 -0.110 -0.035 -0.234 -0.259 -0.309  0.164 -0.060 -0.135 -0.135 -0.110 -0.209 -0.035 -0.184 -0.159  0.015 -0.159 -0.110 -0.209  0.040 -0.135 -0.110 -0.085 -0.035  0.065 -0.060 -0.159 -0.035  0.015 -0.110 -0.234 -0.234 -0.159  0.015 -0.135 -0.085 -0.135 -0.060 -0.010 -0.010 -0.010  0.090  0.140 -0.060 -0.085  0.065 -0.010  0.065 -0.184  0.040  0.239  0.389 -0.309  0.414  0.289 -0.085 -0.135 -0.010 -0.110 -0.110 -0.060 -0.184 -0.060 -0.159 -0.135  0.015 -0.135 -0.159  0.065 -0.060 -0.010  0.065 
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 0.188 -0.086 -0.036  0.038  0.013 -0.011 -0.086 -0.161 -0.136 -0.036  0.287  0.013 -0.136 -0.086  0.113 -0.011  0.462 -0.086  0.013 -0.111 -0.011 -0.086 -0.186 -0.036  0.138  0.013 -0.061  0.088 -0.086  0.013  0.038 -0.136 -0.136 -0.111  0.088 -0.036  0.013 -0.061  0.088  0.088  0.063 -0.086 -0.011  0.138 -0.111 -0.061 -0.136  0.113 -0.011  0.013 -0.036 -0.011  0.013 -0.111 -0.086  0.088 -0.086 -0.036 -0.011 -0.061  0.088 -0.061 -0.036  0.013 -0.061 -0.036 -0.161  0.138 -0.086 -0.136 -0.036  0.013  0.013  0.238  0.063 -0.061 -0.011  0.013  0.088  0.362 -0.061  0.337  0.013 -0.161 -0.086  0.263 -0.036 -0.011  0.013 -0.036 -0.036 -0.136 -0.061  0.312 -0.011 -0.061 -0.036 -0.011 -0.036 -0.011 
 0.246 -0.103 -0.128  0.046 -0.003 -0.028 -0.078 -0.203 -0.128 -0.028  0.320  0.021 -0.178 -0.053  0.121 -0.028  0.520 -0.053  0.046 -0.178 -0.003 -0.103 -0.228 -0.028  0.121 -0.003 -0.078  0.096 -0.028  0.071  0.046 -0.153 -0.153 -0.128  0.071 -0.028  0.021 -0.103  0.021  0.046  0.046 -0.053 -0.053  0.171 -0.153 -0.103 -0.178  0.146 -0.053 -0.028 -0.078 -0.028 -0.003 -0.128 -0.103  0.071 -0.103 -0.003 -0.053 -0.078  0.046 -0.078 -0.028 -0.053 -0.053 -0.053 -0.178  0.121 -0.153 -0.053 -0.003 -0.053  0.021  0.271  0.046 -0.078 -0.078  0.046  0.146  0.370 -0.078  0.345  0.071 -0.153 -0.103  0.246 -0.078  0.021  0.021 -0.078 -0.028 -0.128 -0.103  0.345 -0.028 -0.103  0.071 -0.078  0.046  0.046 
 0.254 -0.145 -0.145  0.079 -0.020 -0.020 -0.095 -0.220 -0.120  0.029  0.254  0.079 -0.195  0.004  0.104 -0.045  0.478 -0.020  0.004 -0.195 -0.020 -0.045 -0.245 -0.070  0.104 -0.020 -0.070  0.104 -0.020  0.129  0.054 -0.170 -0.195 -0.145  0.054 -0.020 -0.020 -0.120  0.004  0.029  0.054 -0.070 -0.070  0.129 -0.145 -0.120 -0.170  0.129 -0.070 -0.020 -0.120  0.004  0.029 -0.120 -0.070  0.029 -0.095 -0.020 -0.120 -0.120  0.054 -0.070 -0.045 -0.120 -0.045 -0.095 -0.170  0.079 -0.170  0.079  0.004 -0.070  0.004  0.328  0.054 -0.095 -0.145  0.054  0.179  0.328 -0.095  0.378  0.129 -0.170 -0.120  0.254 -0.120  0.004  0.004 -0.120 -0.070 -0.095 -0.095  0.353 -0.020 -0.145  0.054 -0.120  0.029  0.054 
 0.287 -0.112 -0.161  0.063 -0.062 -0.087 -0.112 -0.186 -0.137  0.013  0.262  0.063 -0.186  0.013  0.113 -0.062  0.511 -0.012  0.013 -0.211 -0.062 -0.037 -0.261 -0.087  0.162 -0.012 -0.087  0.138 -0.037  0.088  0.038 -0.211 -0.211 -0.186  0.038  0.013 -0.037 -0.112 -0.012 -0.012  0.038 -0.062 -0.062  0.138 -0.137 -0.137 -0.186  0.113 -0.087 -0.062 -0.137  0.013  0.013 -0.161 -0.137 -0.012 -0.087  0.013 -0.137 -0.112 -0.012 -0.112 -0.037 -0.112 -0.087 -0.087 -0.087  0.063 -0.211  0.088  0.013 -0.037  0.013  0.362  0.063 -0.112 -0.186  0.063  0.162  0.337 -0.137  0.362  0.212 -0.112 -0.137  0.187 -0.137 -0.012 -0.012 -0.161 -0.087 -0.112 -0.112  0.337 -0.037 -0.161  0.063 -0.186  0.013  0.088 
 0.282 -0.117 -0.167  0.032 -0.067 -0.092 -0.117 -0.192 -0.142  0.007  0.182  0.132 -0.192 -0.017  0.132 -0.067  0.531  0.007  0.007 -0.217 -0.067 -0.042 -0.267 -0.092  0.157 -0.017 -0.092  0.132 -0.042  0.107  0.032 -0.217 -0.217 -0.192  0.007  0.007 -0.042 -0.117 -0.017 -0.017  0.032 -0.067 -0.067  0.132 -0.142 -0.142 -0.192  0.132 -0.092 -0.067 -0.142 -0.017 -0.017 -0.117 -0.142 -0.017 -0.092  0.007 -0.142 -0.117 -0.042 -0.117 -0.042 -0.117 -0.092 -0.092 -0.092  0.057 -0.217  0.082  0.007 -0.042  0.007  0.381  0.057 -0.117 -0.217  0.057  0.182  0.356 -0.142  0.356  0.207 -0.117 -0.142  0.182 -0.142  0.007 -0.017 -0.167 -0.092 -0.117 -0.117  0.331 -0.067 -0.167  0.057 -0.192  0.007  0.107 
 0.300 -0.124 -0.173  0.001 -0.049 -0.124 -0.148 -0.198 -0.148  0.001  0.175  0.126 -0.173 -0.049  0.175 -0.049  0.499 -0.024  0.001 -0.173 -0.099 -0.074 -0.273 -0.099  0.200 -0.024 -0.099  0.126 -0.024  0.101  0.001 -0.248 -0.223 -0.223  0.001  0.001 -0.024 -0.099 -0.049 -0.049  0.026 -0.099 -0.099  0.126 -0.148 -0.099 -0.198  0.150 -0.099 -0.124 -0.148 -0.024 -0.024 -0.124 -0.148 -0.024 -0.024 -0.074 -0.148 -0.124 -0.099 -0.099 -0.049 -0.074 -0.124 -0.074 -0.024  0.051 -0.173  0.101  0.001 -0.099 -0.024  0.375  0.101 -0.099 -0.223  0.051  0.225  0.400 -0.148  0.300  0.200 -0.099 -0.124  0.126 -0.148  0.001 -0.074 -0.148 -0.099 -0.148 -0.124  0.300 -0.148 -0.148  0.101 -0.198 -0.024  0.101 
 0.300 -0.124 -0.173  0.001 -0.049 -0.124 -0.148 -0.173 -0.124  0.001  0.175  0.126 -0.198  0.001  0.175 -0.049  0.499 -0.024  0.001 -0.173 -0.099 -0.099 -0.273 -0.099  0.225 -0.049 -0.099  0.101  0.001  0.101  0.051 -0.248 -0.223 -0.223  0.001  0.026 -0.024 -0.099 -0.099 -0.049  0.001 -0.099 -0.099  0.126 -0.148 -0.099 -0.198  0.126 -0.099 -0.099 -0.148 -0.024 -0.024 -0.124 -0.148 -0.049 -0.024 -0.074 -0.173 -0.124 -0.124 -0.099 -0.074 -0.074 -0.124 -0.074 -0.024  0.051 -0.173  0.101  0.001 -0.099 -0.024  0.350  0.101 -0.124 -0.223  0.051  0.250  0.400 -0.173  0.300  0.200 -0.074 -0.148  0.126 -0.148 -0.024 -0.074 -0.124 -0.099 -0.148 -0.124  0.275 -0.148 -0.124  0.101 -0.198 -0.024  0.101 
 0.297 -0.127 -0.201 -0.052 -0.052 -0.176 -0.176 -0.176 -0.102 -0.002  0.172  0.098 -0.226 -0.002  0.222 -0.002  0.496 -0.002 -0.002 -0.201 -0.127 -0.077 -0.276 -0.102  0.222 -0.052 -0.102  0.048 -0.002  0.073  0.073 -0.226 -0.226 -0.226 -0.002  0.023 -0.027 -0.102 -0.077 -0.077 -0.002 -0.102 -0.102  0.098 -0.151 -0.102 -0.201  0.123 -0.102 -0.102 -0.151 -0.027 -0.002 -0.127 -0.151 -0.052 -0.052 -0.077 -0.176 -0.102 -0.127 -0.102 -0.077 -0.077 -0.127 -0.077 -0.002  0.048 -0.176  0.098  0.023 -0.102 -0.027  0.347  0.098 -0.151 -0.226  0.023  0.222  0.372 -0.176  0.297  0.197 -0.077 -0.176  0.073 -0.151 -0.052 -0.052 -0.127 -0.052 -0.151 -0.151  0.222 -0.151 -0.127  0.098 -0.176 -0.027  0.098 
 0.320 -0.129 -0.178 -0.054 -0.054 -0.178 -0.203 -0.178 -0.104 -0.029  0.170  0.121 -0.228 -0.004  0.220 -0.004  0.494 -0.004 -0.004 -0.203 -0.129 -0.054 -0.278 -0.104  0.220 -0.004 -0.104  0.046 -0.004  0.071  0.071 -0.228 -0.228 -0.228 -0.004  0.021 -0.054 -0.104 -0.079 -0.079 -0.004 -0.104 -0.079  0.096 -0.153 -0.104 -0.203  0.121 -0.104 -0.104 -0.153 -0.054  0.021 -0.104 -0.153 -0.054 -0.054 -0.079 -0.178 -0.104 -0.129 -0.079 -0.054 -0.079 -0.153 -0.079 -0.004  0.046 -0.153  0.096  0.021 -0.104 -0.029  0.345  0.071 -0.153 -0.228 -0.004  0.220  0.370 -0.178  0.245  0.195 -0.104 -0.203  0.021 -0.153 -0.054 -0.079 -0.129 -0.054 -0.153 -0.153  0.220 -0.153 -0.129  0.096 -0.178 -0.004  0.096 
 0.314 -0.110 -0.184 -0.060 -0.060 -0.184 -0.159 -0.184 -0.110 -0.035  0.164  0.164 -0.234 -0.010  0.214 -0.010  0.438 -0.060 -0.010 -0.209 -0.159 -0.035 -0.284 -0.110  0.214 -0.010 -0.085  0.040 -0.010  0.090  0.065 -0.259 -0.234 -0.234  0.015 -0.010 -0.135 -0.110 -0.110 -0.135 -0.035 -0.135 -0.085  0.065 -0.159 -0.135 -0.184  0.065 -0.110 -0.110 -0.135 -0.060  0.040 -0.110 -0.135 -0.060 -0.035 -0.085 -0.234 -0.135 -0.159 -0.085 -0.060 -0.085 -0.184 -0.110 -0.010  0.065 -0.159  0.090  0.015 -0.110 -0.035  0.314  0.040 -0.135 -0.234 -0.010  0.214  0.364 -0.209  0.239  0.189 -0.110 -0.209 -0.010 -0.159 -0.060 -0.085 -0.135 -0.060 -0.135 -0.184  0.065 -0.135 -0.085  0.090 -0.184 -0.035  0.090 
 0.311 -0.113 -0.187 -0.063 -0.063 -0.187 -0.138 -0.187 -0.113 -0.038  0.161  0.161 -0.212 -0.013  0.211 -0.038  0.386 -0.063 -0.013 -0.187 -0.187 -0.013 -0.287 -0.138  0.211 -0.013 -0.088  0.012 -0.013  0.087  0.062 -0.262 -0.237 -0.237  0.012 -0.013 -0.138 -0.113 -0.088 -0.138 -0.038 -0.138 -0.088  0.062 -0.138 -0.138 -0.187  0.062 -0.138 -0.113 -0.138 -0.063  0.037 -0.113 -0.138 -0.113 -0.038 -0.088 -0.237 -0.187 -0.162 -0.088 -0.063 -0.088 -0.187 -0.113 -0.013  0.062 -0.162  0.087  0.012 -0.113 -0.038  0.311  0.037 -0.113 -0.237 -0.013  0.211  0.361 -0.187  0.211  0.186 -0.063 -0.212 -0.038 -0.162 -0.063 -0.088 -0.138 -0.088 -0.138 -0.187  0.062 -0.138 -0.088  0.062 -0.162 -0.038  0.087 
 0.309 -0.064 -0.164 -0.064 -0.064 -0.189 -0.139 -0.164 -0.114 -0.064  0.160  0.210 -0.214 -0.014  0.210 -0.039  0.359 -0.064 -0.014 -0.189 -0.189  0.010 -0.288 -0.139  0.185  0.010 -0.089  0.010 -0.014  0.085  0.035 -0.264 -0.239 -0.239  0.010 -0.014 -0.189 -0.114 -0.089 -0.139 -0.014 -0.164 -0.089  0.060 -0.139 -0.164 -0.189  0.060 -0.139 -0.114 -0.139 -0.039  0.035 -0.114 -0.114 -0.139 -0.039 -0.139 -0.239 -0.214 -0.189 -0.089 -0.039 -0.089 -0.164 -0.039 -0.014  0.060 -0.164  0.085 -0.014 -0.114 -0.064  0.284  0.035 -0.114 -0.214 -0.014  0.185  0.334 -0.214  0.210  0.210 -0.064 -0.214 -0.089 -0.164 -0.064 -0.089 -0.139 -0.064 -0.139 -0.189  0.060 -0.139 -0.089  0.060 -0.139 -0.039  0.085 
 0.309 -0.065 -0.164 -0.065 -0.065 -0.140 -0.164 -0.164 -0.115 -0.065  0.135  0.209 -0.189 -0.015  0.209 -0.065  0.359 -0.065 -0.015 -0.189 -0.189  0.035 -0.289 -0.140  0.159  0.010 -0.090  0.010 -0.015  0.060  0.010 -0.264 -0.239 -0.239  0.035 -0.040 -0.189 -0.090 -0.115 -0.140  0.010 -0.164 -0.090  0.060 -0.140 -0.164 -0.189  0.035 -0.140 -0.115 -0.140 -0.065  0.035 -0.115 -0.090 -0.140 -0.040 -0.140 -0.239 -0.214 -0.189 -0.065 -0.040 -0.090 -0.164 -0.040 -0.015  0.060 -0.164  0.085 -0.015 -0.115 -0.065  0.284  0.035 -0.115 -0.214 -0.015  0.184  0.334 -0.214  0.209  0.234 -0.065 -0.214 -0.090 -0.164 -0.065 -0.090 -0.140 -0.065 -0.140 -0.189  0.035 -0.140 -0.115  0.060 -0.140 -0.040  0.085 
 0.307 -0.067 -0.166 -0.067 -0.067 -0.142 -0.166 -0.166 -0.117 -0.092  0.133  0.182 -0.191  0.008  0.182 -0.067  0.357 -0.067 -0.017 -0.191 -0.191  0.058 -0.291 -0.142  0.157  0.008 -0.117 -0.017 -0.017  0.033  0.008 -0.266 -0.241 -0.241  0.033 -0.042 -0.166 -0.067 -0.117 -0.142  0.008 -0.166 -0.092  0.033 -0.142 -0.166 -0.191  0.033 -0.166 -0.117 -0.117 -0.042  0.033 -0.117 -0.092 -0.166 -0.042 -0.142 -0.241 -0.241 -0.216 -0.042 -0.042 -0.092 -0.166 -0.042  0.008  0.058 -0.191  0.083 -0.017 -0.117 -0.092  0.282  0.033 -0.117 -0.191  0.008  0.182  0.307 -0.216  0.207  0.232 -0.042 -0.216 -0.092 -0.166 -0.092 -0.092 -0.142 -0.042 -0.142 -0.191  0.033 -0.142 -0.117  0.058 -0.142 -0.042  0.108 
 0.261 -0.013 -0.138 -0.063 -0.038 -0.113 -0.113 -0.138 -0.113 -0.063  0.062  0.012 -0.162 -0.013  0.137 -0.013  0.261 -0.013 -0.013 -0.162 -0.138  0.012 -0.212 -0.113  0.186 -0.063 -0.113  0.037  0.037  0.062  0.037 -0.187 -0.187 -0.162 -0.013 -0.013 -0.162 -0.038 -0.113 -0.162 -0.013 -0.113 -0.088  0.012 -0.138 -0.162 -0.162  0.037 -0.162 -0.063 -0.212 -0.088  0.012 -0.063 -0.088 -0.138 -0.038 -0.113 -0.162 -0.162 -0.138 -0.013 -0.063 -0.063 -0.162 -0.013  0.012 -0.038 -0.138  0.087 -0.013 -0.088 -0.063  0.186  0.012 -0.038 -0.138  0.037  0.211  0.211 -0.187  0.286  0.261 -0.038 -0.187 -0.113 -0.088 -0.038 -0.063 -0.138 -0.013 -0.113 -0.162  0.062 -0.088 -0.088  0.012 -0.187 -0.038  0.112 
 0.178  0.004 -0.096 -0.021 -0.021 -0.046 -0.121 -0.096 -0.096 -0.046  0.004  0.004 -0.121  0.054  0.029 -0.046  0.079  0.004  0.054 -0.096 -0.096  0.004 -0.121 -0.071  0.153 -0.046 -0.071 -0.021  0.079  0.029 -0.021 -0.121 -0.121 -0.121  0.004  0.004 -0.121 -0.046 -0.046 -0.121  0.004 -0.071 -0.071  0.029 -0.096 -0.071 -0.121 -0.021 -0.121 -0.021 -0.145 -0.046  0.029 -0.046 -0.046 -0.071 -0.071 -0.046 -0.096 -0.121 -0.096 -0.021 -0.046 -0.046 -0.071  0.004  0.004  0.004 -0.071  0.054  0.004 -0.046 -0.021  0.104  0.004 -0.046 -0.096  0.004  0.079  0.203 -0.121  0.353  0.104 -0.021 -0.096 -0.121 -0.046  0.029 -0.046 -0.096 -0.021 -0.121 -0.096  0.029 -0.046 -0.096  0.054 -0.121 -0.021 -0.021 
 0.142  0.018 -0.082 -0.007 -0.032 -0.032 -0.132 -0.082 -0.082 -0.032 -0.032 -0.007 -0.132  0.068 -0.007 -0.057  0.043  0.018  0.068 -0.082 -0.107  0.018 -0.107 -0.082  0.118 -0.032 -0.057 -0.007  0.093  0.018 -0.032 -0.107 -0.107 -0.132  0.018 -0.007 -0.107 -0.057 -0.057 -0.107  0.043 -0.082 -0.057  0.018 -0.107 -0.082 -0.107 -0.007 -0.107 -0.007 -0.132 -0.032  0.043 -0.057 -0.032 -0.057 -0.082 -0.057 -0.082 -0.107 -0.082 -0.007 -0.057 -0.057 -0.082  0.018 -0.007  0.018 -0.032  0.068 -0.032 -0.032 -0.007  0.068 -0.007 -0.032 -0.082  0.018  0.093  0.217 -0.107  0.367  0.043 -0.007 -0.082 -0.107 -0.032  0.018 -0.032 -0.107 -0.007 -0.107 -0.082  0.043 -0.032 -0.082  0.043 -0.107 -0.007 -0.007 
 0.120  0.020 -0.080 -0.080 -0.005 -0.005 -0.105 -0.055 -0.080 -0.030 -0.030 -0.030 -0.105  0.020 -0.030 -0.030  0.020  0.020  0.070 -0.055 -0.105  0.020 -0.080 -0.080  0.095 -0.005 -0.030  0.020  0.045  0.020 -0.005 -0.080 -0.105 -0.105  0.020 -0.005 -0.080 -0.080 -0.030 -0.080  0.070 -0.030 -0.030  0.020 -0.080 -0.080 -0.080 -0.080 -0.080  0.020 -0.105 -0.030  0.070 -0.055 -0.005 -0.055 -0.080 -0.030 -0.055 -0.105 -0.055  0.045 -0.030 -0.005 -0.055  0.020  0.020  0.045 -0.055  0.020 -0.005 -0.005  0.020 -0.055  0.045 -0.055 -0.055 -0.005 -0.005  0.120 -0.105  0.294  0.045 -0.030 -0.080 -0.080 -0.005  0.020  0.020 -0.055 -0.005 -0.105 -0.080  0.070 -0.030 -0.055  0.020 -0.055 -0.005 -0.005 
 0.128  0.028 -0.071 -0.071  0.003  0.003 -0.096 -0.021 -0.071 -0.021 -0.046 -0.046 -0.096  0.003 -0.046 -0.021  0.028  0.028  0.078 -0.046 -0.096  0.053 -0.071 -0.071  0.078  0.003 -0.021  0.028  0.078  0.003 -0.021 -0.071 -0.096 -0.096  0.028  0.003 -0.071 -0.071 -0.046 -0.071  0.028 -0.021 -0.021  0.003 -0.071 -0.071 -0.071 -0.071 -0.071  0.003 -0.096 -0.071  0.078 -0.046  0.003 -0.071 -0.071 -0.021 -0.046 -0.096 -0.046  0.053 -0.021  0.003 -0.071  0.028  0.028  0.053 -0.046  0.028  0.028  0.003  0.028 -0.046  0.053 -0.046 -0.046 -0.046 -0.021  0.153 -0.096  0.278  0.028 -0.046 -0.096 -0.071  0.003  0.028  0.028 -0.021  0.003 -0.096 -0.071  0.078 -0.021 -0.046  0.003 -0.046  0.003  0.003 
 0.066  0.041 -0.058 -0.058 -0.033  0.016 -0.083 -0.033 -0.083 -0.008 -0.033 -0.033 -0.083 -0.008 -0.083 -0.033 -0.033  0.041  0.066 -0.058 -0.083  0.066 -0.083 -0.058  0.041 -0.008 -0.008  0.041  0.091 -0.008 -0.008 -0.058 -0.083 -0.083  0.016  0.016 -0.083 -0.058 -0.033 -0.058  0.016 -0.008 -0.033 -0.008 -0.083 -0.058 -0.083 -0.058 -0.058 -0.033 -0.083 -0.083  0.091 -0.058  0.016 -0.058 -0.058 -0.083 -0.058 -0.083 -0.033  0.016 -0.008  0.016 -0.058 -0.033  0.041  0.066 -0.033  0.016  0.041  0.016  0.041 -0.033  0.041 -0.033 -0.058 -0.033 -0.058  0.141 -0.083  0.241 -0.008 -0.033 -0.083 -0.058 -0.033  0.016  0.016 -0.008  0.016 -0.083 -0.083  0.041 -0.008 -0.058  0.016 -0.033  0.016 -0.033 
 0.070  0.020 -0.055 -0.055 -0.030  0.020 -0.080 -0.030 -0.080 -0.005 -0.055 -0.030 -0.080 -0.030 -0.080 -0.030 -0.030  0.045  0.070 -0.055 -0.080  0.070 -0.080 -0.055  0.045 -0.030 -0.005  0.045  0.070 -0.005 -0.030 -0.055 -0.080 -0.080  0.020  0.020 -0.080 -0.055 -0.030 -0.055  0.020 -0.005 -0.030 -0.005 -0.080 -0.055 -0.080 -0.055 -0.055 -0.030 -0.080 -0.080  0.095 -0.080  0.020 -0.055 -0.055 -0.080 -0.055 -0.080 -0.030 -0.005 -0.005 -0.005 -0.055 -0.030  0.020  0.045 -0.030 -0.005  0.070  0.020  0.045 -0.030  0.045 -0.030 -0.055 -0.030 -0.055  0.120 -0.080  0.244 -0.005 -0.030 -0.080 -0.055 -0.055 -0.005 -0.005 -0.030  0.020 -0.080 -0.080  0.020 -0.005 -0.055 -0.005 -0.030  0.020 -0.030 
 0.081  0.031 -0.069 -0.044 -0.044  0.031 -0.069 -0.019 -0.069  0.006 -0.044 -0.019 -0.044 -0.044 -0.069 -0.044 -0.044  0.056  0.056 -0.044 -0.069  0.081 -0.069 -0.069  0.031 -0.019  0.006  0.056  0.081  0.006 -0.019 -0.044 -0.069 -0.069  0.006  0.031 -0.069 -0.044 -0.019 -0.044  0.006  0.006 -0.019  0.006 -0.069 -0.044 -0.069 -0.044 -0.044 -0.019 -0.069 -0.069  0.106 -0.069  0.006 -0.044 -0.044 -0.069 -0.044 -0.069 -0.019 -0.019  0.006  0.006 -0.044 -0.019  0.031  0.031 -0.019  0.006  0.081  0.031  0.031 -0.044  0.056 -0.019 -0.044 -0.019 -0.069  0.081 -0.069  0.180 -0.044 -0.019 -0.069 -0.044 -0.044  0.006  0.006 -0.019  0.006 -0.069 -0.069  0.031 -0.019 -0.044  0.006 -0.019  0.031 -0.019 
 0.083  0.033 -0.067 -0.042 -0.042  0.033 -0.067 -0.017 -0.067  0.008 -0.067 -0.017 -0.042 -0.042 -0.042 -0.042 -0.042  0.058  0.033 -0.042 -0.067  0.108 -0.067 -0.067  0.033 -0.017 -0.017  0.058  0.083  0.008 -0.042 -0.042 -0.067 -0.067  0.008  0.033 -0.067 -0.042 -0.017 -0.042  0.008  0.008 -0.017  0.008 -0.067 -0.042 -0.067 -0.017 -0.042 -0.017 -0.067 -0.067  0.108 -0.067 -0.017 -0.042 -0.042 -0.067 -0.067 -0.067  0.008 -0.042  0.033  0.033 -0.042 -0.017  0.033  0.033 -0.017  0.008  0.083  0.033  0.008 -0.042  0.058  0.008 -0.042 -0.017 -0.067  0.083 -0.067  0.182 -0.042 -0.042 -0.042 -0.042 -0.042  0.033  0.008 -0.042  0.008 -0.067 -0.067  0.033 -0.017 -0.042  0.008 -0.017  0.033 -0.017 
 0.087  0.012 -0.062 -0.037 -0.037  0.012 -0.062 -0.012 -0.062  0.012 -0.062 -0.012 -0.037 -0.037 -0.037 -0.037 -0.037  0.037 -0.012 -0.037 -0.062  0.112 -0.062 -0.062  0.037 -0.012 -0.012  0.037  0.112 -0.037 -0.037 -0.037 -0.062 -0.062 -0.012  0.012 -0.037 -0.037 -0.012 -0.012 -0.012  0.012 -0.037 -0.012 -0.062 -0.012 -0.062 -0.012 -0.037 -0.037 -0.062 -0.062  0.087 -0.062 -0.012 -0.037 -0.037 -0.062 -0.062 -0.062 -0.012 -0.037  0.012  0.037 -0.037 -0.012  0.037  0.012 -0.012  0.037  0.037  0.012  0.012 -0.037  0.012 -0.012 -0.037 -0.037 -0.037  0.062 -0.062  0.112 -0.037 -0.037 -0.012 -0.037 -0.037  0.037  0.012 -0.012 -0.012 -0.062 -0.037  0.037 -0.012 -0.037 -0.012 -0.012  0.037 -0.037 
 0.089  0.014 -0.060 -0.035 -0.035  0.014 -0.060 -0.010 -0.060 -0.010 -0.035 -0.010 -0.035 -0.060 -0.035 -0.060 -0.035  0.039 -0.010 -0.010 -0.060  0.114 -0.035 -0.035  0.039 -0.035 -0.010  0.039  0.089 -0.035 -0.035 -0.035 -0.060 -0.060 -0.010  0.014 -0.035 -0.035 -0.010 -0.010 -0.010  0.014 -0.035 -0.010 -0.060 -0.010 -0.060 -0.010 -0.035 -0.035 -0.010 -0.060  0.064 -0.060 -0.010 -0.060 -0.035 -0.060 -0.060 -0.060 -0.010 -0.035  0.014  0.039 -0.035 -0.010  0.039  0.014 -0.010  0.014  0.039  0.014  0.014 -0.010  0.014 -0.010 -0.035 -0.035 -0.035  0.064 -0.060  0.089 -0.035 -0.035 -0.010 -0.035 -0.035  0.039  0.014 -0.035 -0.010 -0.060 -0.035  0.039 -0.035 -0.035 -0.010 -0.010  0.039 -0.035 
 0.071  0.021 -0.054 -0.029 -0.029  0.021 -0.054 -0.004 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.071 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029 -0.004 -0.054 -0.004 -0.054 -0.029 -0.029 -0.029 -0.004 -0.054  0.046 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.029 -0.004  0.021  0.021 -0.004  0.021  0.046 -0.004  0.021 -0.004  0.021 -0.004 -0.054 -0.004 -0.029  0.046 -0.054  0.046 -0.004 -0.029 -0.004 -0.029 -0.029  0.046 -0.004 -0.029 -0.029 -0.054 -0.029  0.071 -0.029 -0.029 -0.029 -0.004  0.046 -0.029 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.072 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.047 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022  0.022 -0.003  0.022  0.047 -0.003  0.022 -0.003  0.022 -0.003 -0.053 -0.003 -0.028  0.047 -0.053  0.047 -0.003 -0.028 -0.003 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.028  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.022 -0.002  0.022 -0.027  0.022 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.022 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.022  0.047 -0.027 -0.002  0.022  0.022 -0.027  0.022  0.047 -0.002  0.022 -0.002  0.022 -0.002 -0.052 -0.002 -0.027  0.072 -0.052  0.047  0.022 -0.027 -0.002 -0.027 -0.027  0.022 -0.002 -0.027 -0.027 -0.052 -0.027  0.072 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.003 -0.003  0.022  0.022 -0.028  0.022  0.047  0.022  0.022 -0.003  0.022  0.022 -0.053 -0.003 -0.028  0.072 -0.053  0.047  0.022 -0.028 -0.003 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.003  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.070  0.045 -0.054 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.020  0.020 -0.004  0.020 -0.029  0.020 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.004 -0.004  0.020  0.020 -0.004  0.020  0.045  0.020  0.020 -0.004  0.020  0.020 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.004  0.070 -0.029 -0.029 -0.029 -0.004  0.045 -0.029 
 0.070  0.045 -0.055 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020 -0.005  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.030 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.141  0.041 -0.058 -0.033 -0.058  0.016 -0.058  0.016 -0.083 -0.008  0.016  0.016 -0.033 -0.008 -0.058 -0.083 -0.033  0.041  0.016 -0.033 -0.058  0.066 -0.058 -0.058  0.066 -0.033 -0.008  0.066  0.091 -0.008 -0.058 -0.008 -0.083 -0.083 -0.008 -0.008 -0.058 -0.033 -0.008  0.016 -0.008 -0.008 -0.033 -0.008 -0.058 -0.008 -0.058 -0.008 -0.033 -0.008 -0.008 -0.058  0.016 -0.083 -0.008 -0.083 -0.058 -0.083 -0.083 -0.083 -0.058  0.041 -0.008  0.041 -0.033 -0.033  0.091 -0.008  0.041  0.016  0.041 -0.008 -0.008  0.016 -0.008 -0.008 -0.083 -0.008 -0.008  0.116 -0.083  0.041  0.066 -0.008  0.016 -0.008 -0.033  0.041 -0.033 -0.058  0.066 -0.083 -0.033  0.091 -0.058  0.016  0.016  0.016  0.066 -0.058 
 0.254  0.005 -0.120 -0.095 -0.070 -0.020 -0.095 -0.020 -0.144 -0.070 -0.020  0.005 -0.045 -0.070 -0.045 -0.070 -0.020  0.030  0.080 -0.095 -0.095  0.105 -0.095 -0.070  0.055 -0.045 -0.020  0.055  0.154  0.005 -0.070 -0.020 -0.120 -0.144 -0.070  0.030 -0.120 -0.070 -0.070 -0.020  0.005 -0.070 -0.070 -0.020 -0.095 -0.045 -0.120 -0.070 -0.095 -0.070 -0.070 -0.020  0.105 -0.095 -0.020 -0.120 -0.045 -0.144 -0.120 -0.095 -0.095  0.130 -0.020  0.030 -0.020 -0.070  0.105 -0.020  0.005  0.030  0.105 -0.020  0.005 -0.020 -0.070  0.005 -0.045 -0.070  0.105  0.279 -0.144  0.204  0.229 -0.045  0.005 -0.045 -0.070  0.005 -0.095 -0.095  0.130 -0.070 -0.095  0.130 -0.070  0.005 -0.020  0.055  0.130 -0.120 
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 0.239 -0.035 -0.259 -0.060 -0.085 -0.135 -0.209 -0.085 -0.060 -0.085 -0.010 -0.010 -0.159  0.115  0.140 -0.159 -0.135 -0.085 -0.010 -0.209 -0.259  0.140 -0.209 -0.209  0.065 -0.184 -0.085 -0.110  0.140 -0.135 -0.060 -0.135 -0.234 -0.309  0.115 -0.010 -0.159 -0.110 -0.110 -0.159  0.065 -0.159 -0.159  0.040 -0.159 -0.085 -0.085 -0.060 -0.184 -0.135 -0.035 -0.060  0.040 -0.060 -0.085  0.090 -0.010 -0.110 -0.234 -0.234 -0.110  0.040 -0.209 -0.135 -0.110 -0.035  0.115 -0.010  0.140  0.140  0.140 -0.110 -0.060  0.214 -0.060  0.090 -0.159  0.015  0.314  0.414 -0.284  0.389  0.264 -0.110 -0.110 -0.110 -0.110 -0.110 -0.010 -0.184 -0.035 -0.184 -0.060 -0.060 -0.135 -0.184  0.015  0.065  0.115 -0.060 
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 0.238 -0.036 -0.261 -0.061 -0.111 -0.136 -0.236 -0.086 -0.061 -0.086 -0.011 -0.011 -0.161  0.113  0.138 -0.161 -0.136 -0.086  0.013 -0.211 -0.261  0.138 -0.211 -0.211  0.063 -0.186 -0.111 -0.111  0.138 -0.136 -0.061 -0.186 -0.236 -0.310  0.113 -0.036 -0.161 -0.111 -0.111 -0.161  0.063 -0.161 -0.161  0.013 -0.161 -0.086 -0.086 -0.061 -0.186 -0.136 -0.011 -0.036  0.038 -0.086 -0.161  0.088 -0.036 -0.111 -0.236 -0.236 -0.111  0.063 -0.211 -0.136 -0.111 -0.011  0.113  0.013  0.088  0.163  0.113 -0.136 -0.036  0.263 -0.061  0.088 -0.186  0.013  0.312  0.387 -0.285  0.387  0.263 -0.086 -0.111 -0.136 -0.136 -0.111 -0.011 -0.186 -0.036 -0.186 -0.061 -0.086 -0.161 -0.186  0.038  0.013  0.113 -0.086 
 0.236 -0.038 -0.262 -0.038 -0.113 -0.138 -0.237 -0.113 -0.038 -0.088 -0.013 -0.013 -0.162  0.112  0.137 -0.162 -0.138 -0.088  0.037 -0.212 -0.262  0.161 -0.212 -0.187  0.062 -0.162 -0.113 -0.113  0.137 -0.138 -0.063 -0.187 -0.237 -0.312  0.137 -0.038 -0.162 -0.113 -0.113 -0.162  0.062 -0.162 -0.162  0.012 -0.162 -0.088 -0.088 -0.088 -0.187 -0.138 -0.013 -0.038  0.037 -0.088 -0.162  0.087 -0.038 -0.138 -0.237 -0.237 -0.138  0.087 -0.212 -0.138 -0.138 -0.013  0.112  0.012  0.087  0.161  0.087 -0.162 -0.038  0.236 -0.063  0.087 -0.187  0.012  0.311  0.361 -0.287  0.386  0.236 -0.088 -0.113 -0.138 -0.138 -0.113 -0.088 -0.187 -0.063 -0.187 -0.063 -0.088 -0.162 -0.187  0.037  0.012  0.087 -0.063 
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 0.235 -0.039 -0.264 -0.039 -0.114 -0.139 -0.239 -0.114 -0.039 -0.089  0.010 -0.014 -0.164  0.085  0.110 -0.139 -0.114 -0.089  0.035 -0.214 -0.264  0.135 -0.214 -0.189  0.060 -0.189 -0.114 -0.114  0.135 -0.114 -0.064 -0.214 -0.239 -0.313  0.135 -0.039 -0.164 -0.114 -0.114 -0.189  0.060 -0.164 -0.164  0.010 -0.164 -0.064 -0.114 -0.139 -0.189 -0.139 -0.039 -0.039  0.035 -0.089 -0.139  0.060  0.010 -0.164 -0.239 -0.239 -0.164  0.060 -0.189 -0.139 -0.164  0.035  0.110  0.010  0.085  0.210  0.085 -0.164 -0.039  0.210 -0.039  0.035 -0.189  0.010  0.309  0.384 -0.288  0.409  0.235 -0.089 -0.164 -0.114 -0.139 -0.139 -0.089 -0.214 -0.089 -0.189 -0.039 -0.089 -0.164 -0.164  0.035  0.010  0.085 -0.039 
 0.233 -0.041 -0.266 -0.016 -0.091 -0.141 -0.241 -0.116 -0.066 -0.091  0.033 -0.016 -0.141  0.083  0.108 -0.141 -0.116 -0.091  0.008 -0.191 -0.241  0.108 -0.216 -0.191  0.033 -0.191 -0.116 -0.116  0.133 -0.091 -0.041 -0.216 -0.241 -0.315  0.083 -0.041 -0.166 -0.141 -0.116 -0.191  0.058 -0.166 -0.166  0.008 -0.166 -0.066 -0.091 -0.141 -0.191 -0.141 -0.041 -0.041  0.033 -0.091 -0.141  0.033  0.008 -0.166 -0.241 -0.241 -0.166  0.058 -0.191 -0.141 -0.141  0.033  0.108  0.008  0.083  0.208  0.083 -0.166 -0.041  0.233 -0.041  0.033 -0.191  0.008  0.307  0.357 -0.290  0.407  0.233 -0.091 -0.166 -0.141 -0.141 -0.141 -0.091 -0.216 -0.091 -0.191 -0.041 -0.091 -0.166 -0.166  0.033  0.008  0.083 -0.041 
 0.256 -0.043 -0.267 -0.018 -0.093 -0.142 -0.217 -0.093 -0.068 -0.093  0.032 -0.018 -0.142  0.082  0.107 -0.142 -0.118 -0.068  0.007 -0.192 -0.242  0.107 -0.217 -0.192  0.032 -0.192 -0.118 -0.118  0.132 -0.093 -0.068 -0.217 -0.242 -0.317  0.107 -0.043 -0.167 -0.093 -0.118 -0.192  0.057 -0.167 -0.142  0.007 -0.167 -0.068 -0.093 -0.142 -0.192 -0.142 -0.043 -0.043  0.032 -0.093 -0.142  0.032  0.007 -0.167 -0.242 -0.242 -0.167  0.057 -0.192 -0.118 -0.142  0.007  0.107  0.007  0.057  0.231  0.082 -0.167 -0.043  0.231 -0.043  0.032 -0.192  0.007  0.306  0.331 -0.292  0.406  0.231 -0.093 -0.167 -0.167 -0.142 -0.142 -0.093 -0.217 -0.093 -0.167 -0.043 -0.093 -0.167 -0.167  0.032  0.007  0.082 -0.043 
 0.280 -0.044 -0.269 -0.019 -0.119 -0.144 -0.219 -0.094 -0.069 -0.094  0.030 -0.019 -0.144  0.080  0.105 -0.144 -0.119 -0.069 -0.019 -0.194 -0.269  0.105 -0.219 -0.194  0.030 -0.194 -0.119 -0.119  0.155 -0.094 -0.069 -0.194 -0.244 -0.318  0.105 -0.044 -0.169 -0.094 -0.119 -0.194  0.030 -0.169 -0.144  0.005 -0.169 -0.069 -0.094 -0.144 -0.194 -0.144 -0.044 -0.044  0.030 -0.094 -0.144  0.005  0.005 -0.169 -0.244 -0.244 -0.194  0.055 -0.194 -0.119 -0.169  0.030  0.105  0.005  0.055  0.230  0.080 -0.144 -0.069  0.255 -0.044  0.030 -0.194  0.005  0.304  0.329 -0.293  0.404  0.230 -0.094 -0.169 -0.169 -0.144 -0.144 -0.119 -0.219 -0.094 -0.169 -0.044 -0.094 -0.169 -0.169  0.030 -0.044  0.080 -0.044 
 0.280 -0.044 -0.269 -0.019 -0.119 -0.144 -0.244 -0.094 -0.069 -0.094  0.030 -0.019 -0.144  0.080  0.105 -0.144 -0.119 -0.069 -0.019 -0.194 -0.269  0.105 -0.219 -0.194  0.030 -0.194 -0.119 -0.119  0.155 -0.094 -0.044 -0.194 -0.244 -0.318  0.105 -0.044 -0.169 -0.119 -0.119 -0.194  0.030 -0.169 -0.144  0.005 -0.169 -0.069 -0.094 -0.144 -0.194 -0.144 -0.044 -0.044  0.030 -0.094 -0.144  0.030  0.005 -0.169 -0.244 -0.244 -0.194  0.055 -0.194 -0.119 -0.169  0.005  0.105  0.005  0.055  0.230  0.080 -0.144 -0.069  0.255 -0.044  0.030 -0.194  0.005  0.304  0.329 -0.293  0.404  0.230 -0.094 -0.169 -0.169 -0.144 -0.144 -0.094 -0.219 -0.094 -0.194 -0.044 -0.094 -0.169 -0.169  0.030 -0.044  0.080 -0.044 
 0.279 -0.045 -0.269 -0.020 -0.120 -0.169 -0.244 -0.095 -0.070 -0.095  0.030 -0.020 -0.144  0.080  0.105 -0.144 -0.095 -0.070 -0.020 -0.194 -0.269  0.105 -0.219 -0.194  0.055 -0.194 -0.120 -0.120  0.154 -0.095 -0.045 -0.194 -0.244 -0.319  0.105 -0.045 -0.169 -0.120 -0.120 -0.194  0.030 -0.169 -0.144  0.005 -0.169 -0.070 -0.070 -0.120 -0.194 -0.144 -0.045 -0.045  0.030 -0.095 -0.144  0.030  0.005 -0.169 -0.244 -0.244 -0.194  0.055 -0.194 -0.120 -0.169  0.005  0.105  0.005  0.030  0.229  0.080 -0.144 -0.070  0.254 -0.045  0.030 -0.194  0.005  0.304  0.329 -0.294  0.404  0.204 -0.095 -0.169 -0.169 -0.144 -0.144 -0.095 -0.219 -0.095 -0.194 -0.045 -0.095 -0.169 -0.169  0.030 -0.070  0.080 -0.045 
 0.277 -0.047 -0.196 -0.047 -0.047 -0.122 -0.171 -0.122 -0.047 -0.047  0.028 -0.047 -0.097  0.103  0.103 -0.097 -0.072 -0.097  0.003 -0.146 -0.221  0.078 -0.171 -0.196  0.078 -0.122 -0.097 -0.097  0.177 -0.097 -0.047 -0.221 -0.196 -0.246  0.103  0.028 -0.097 -0.097 -0.072 -0.171 -0.072 -0.122 -0.146 -0.022 -0.097 -0.047 -0.072 -0.072 -0.122 -0.122 -0.146  0.003  0.053 -0.072 -0.122 -0.072 -0.047 -0.171 -0.171 -0.171 -0.122  0.053 -0.146 -0.097 -0.146 -0.022  0.078  0.003 -0.022  0.152  0.078 -0.097 -0.022  0.177 -0.022 -0.022 -0.171 -0.072  0.302  0.377 -0.246  0.377  0.202 -0.047 -0.146 -0.146 -0.072 -0.072 -0.072 -0.171 -0.072 -0.146 -0.047 -0.072 -0.122 -0.122  0.103 -0.072  0.003  0.003 
 0.171 -0.028 -0.103 -0.078 -0.028 -0.028 -0.128 -0.078 -0.028 -0.078 -0.028 -0.028 -0.128  0.021  0.046 -0.028 -0.053 -0.028  0.096 -0.103 -0.153  0.021 -0.128 -0.103  0.071 -0.028 -0.003 -0.028  0.146 -0.028 -0.003 -0.128 -0.153 -0.153  0.071 -0.003 -0.053 -0.103 -0.053 -0.103 -0.053 -0.053 -0.078  0.046 -0.078 -0.028 -0.128 -0.028 -0.103 -0.053 -0.153 -0.028  0.071 -0.003 -0.053 -0.028 -0.028 -0.128 -0.103 -0.078 -0.053  0.021 -0.078 -0.053 -0.053 -0.053  0.046  0.021 -0.028  0.146  0.021 -0.028 -0.028  0.121 -0.003 -0.053 -0.103 -0.053  0.096  0.345 -0.153  0.345  0.096 -0.053 -0.103 -0.103 -0.003 -0.003 -0.028 -0.103 -0.003 -0.078 -0.078 -0.003 -0.028 -0.053  0.046 -0.078 -0.028 -0.003 
 0.185 -0.014 -0.114 -0.064 -0.014 -0.014 -0.139 -0.089 -0.064 -0.064 -0.014 -0.014 -0.139  0.011 -0.039 -0.039 -0.039  0.011  0.111 -0.089 -0.139  0.011 -0.114 -0.089  0.061 -0.039  0.011 -0.014  0.160 -0.014 -0.064 -0.114 -0.139 -0.139  0.036 -0.014 -0.039 -0.089 -0.014 -0.089 -0.039 -0.039 -0.064  0.061 -0.064 -0.014 -0.139 -0.039 -0.114 -0.064 -0.139 -0.014  0.111 -0.064 -0.039 -0.014 -0.014 -0.114 -0.089 -0.089 -0.039  0.036 -0.064 -0.014 -0.039 -0.039  0.061  0.036 -0.014  0.086  0.036 -0.014 -0.014  0.036  0.036 -0.064 -0.089 -0.039  0.036  0.285 -0.139  0.335  0.111 -0.064 -0.089 -0.089  0.011  0.011  0.011 -0.064 -0.014 -0.064 -0.089  0.011 -0.014 -0.064  0.061 -0.089 -0.014 -0.014 
 0.136  0.011 -0.089 -0.064 -0.014 -0.014 -0.114 -0.089 -0.064 -0.039 -0.039 -0.039 -0.114  0.011 -0.064 -0.064 -0.039  0.061  0.160 -0.089 -0.114 -0.014 -0.114 -0.064  0.061 -0.014  0.011  0.011  0.111  0.011 -0.039 -0.089 -0.114 -0.114  0.036  0.011 -0.064 -0.064 -0.064 -0.064  0.011 -0.039 -0.014  0.061 -0.089 -0.039 -0.114 -0.064 -0.089 -0.014 -0.114 -0.014  0.086 -0.064 -0.014 -0.064 -0.014 -0.089 -0.064 -0.089 -0.064  0.011 -0.039  0.011 -0.014 -0.039  0.011  0.086 -0.089  0.061  0.036 -0.014  0.036  0.011  0.011 -0.039 -0.064 -0.064 -0.039  0.210 -0.114  0.335  0.061 -0.064 -0.089 -0.089 -0.014  0.011  0.036 -0.039  0.011 -0.089 -0.089  0.036  0.011 -0.064  0.061 -0.089  0.011 -0.014 
 0.143  0.018 -0.081 -0.081 -0.006 -0.006 -0.106 -0.081 -0.056 -0.031 -0.056 -0.031 -0.106 -0.006 -0.081 -0.056 -0.031  0.068  0.118 -0.081 -0.106 -0.006 -0.106 -0.056  0.068 -0.006 -0.006  0.018  0.093  0.018 -0.056 -0.081 -0.106 -0.106  0.018  0.018 -0.056 -0.081 -0.056 -0.056  0.018 -0.031 -0.006  0.068 -0.081 -0.031 -0.106 -0.056 -0.081 -0.006 -0.106 -0.031  0.068 -0.056 -0.006 -0.056 -0.006 -0.081 -0.056 -0.081 -0.056  0.018 -0.031 -0.006 -0.056 -0.031  0.018  0.093 -0.081  0.043  0.043 -0.006  0.043 -0.006  0.018 -0.031 -0.056 -0.056 -0.031  0.193 -0.106  0.268  0.043 -0.056 -0.081 -0.081 -0.006  0.018  0.043 -0.031 -0.006 -0.081 -0.081  0.043 -0.031 -0.056  0.043 -0.081 -0.006 -0.006 
 0.108  0.033 -0.066 -0.066  0.008  0.008 -0.091 -0.066 -0.066 -0.016 -0.041 -0.041 -0.091 -0.066 -0.091 -0.041 -0.016  0.083  0.058 -0.066 -0.091  0.008 -0.091 -0.066  0.058  0.008 -0.016  0.033  0.083  0.033 -0.041 -0.066 -0.091 -0.091  0.033  0.008 -0.041 -0.066 -0.041 -0.041  0.033 -0.016  0.008  0.008 -0.066 -0.041 -0.091 -0.066 -0.066  0.008 -0.091 -0.066  0.083 -0.091  0.008 -0.066 -0.041 -0.091 -0.041 -0.091 -0.041  0.033 -0.016  0.008 -0.041 -0.016  0.033  0.108 -0.066  0.008  0.033  0.008  0.033 -0.016  0.033 -0.041 -0.041 -0.041 -0.041  0.158 -0.091  0.258  0.033 -0.041 -0.066 -0.066  0.008  0.033  0.033 -0.016  0.008 -0.066 -0.066  0.058 -0.016 -0.041  0.008 -0.066  0.008 -0.016 
 0.087  0.037 -0.062 -0.062 -0.012  0.012 -0.087 -0.037 -0.062 -0.012 -0.037 -0.037 -0.087 -0.062 -0.087 -0.062 -0.012  0.062  0.062 -0.062 -0.087  0.062 -0.087 -0.087  0.062  0.012 -0.012  0.037  0.087  0.012 -0.037 -0.062 -0.087 -0.087  0.037  0.012 -0.037 -0.062 -0.037 -0.037  0.012 -0.012  0.012  0.012 -0.087 -0.037 -0.087 -0.062 -0.062  0.012 -0.087 -0.087  0.087 -0.087 -0.012 -0.062 -0.037 -0.087 -0.037 -0.087 -0.037  0.037 -0.012 -0.012 -0.037 -0.012  0.037  0.062 -0.037  0.012  0.037  0.012  0.012 -0.012  0.037 -0.037 -0.037 -0.037 -0.037  0.162 -0.087  0.262  0.037 -0.037 -0.062 -0.062  0.012  0.012  0.012 -0.012 -0.012 -0.087 -0.062  0.062 -0.012 -0.062  0.012 -0.037  0.012 -0.012 
 0.095  0.045 -0.079 -0.054 -0.029  0.020 -0.079 -0.029 -0.054 -0.004 -0.029 -0.029 -0.079 -0.054 -0.079 -0.054 -0.029  0.045  0.020 -0.054 -0.079  0.070 -0.054 -0.054  0.070  0.020 -0.004  0.045  0.095 -0.029 -0.029 -0.054 -0.079 -0.079  0.045  0.020 -0.029 -0.054 -0.029 -0.029  0.020 -0.004 -0.004 -0.004 -0.079 -0.029 -0.079 -0.054 -0.054 -0.004 -0.054 -0.079  0.070 -0.079 -0.004 -0.054 -0.029 -0.079 -0.029 -0.079 -0.029  0.045  0.020 -0.004 -0.054 -0.004  0.045  0.070 -0.004  0.020  0.020  0.020  0.020 -0.054  0.020 -0.029 -0.029 -0.054 -0.029  0.170 -0.079  0.245  0.020 -0.029 -0.054 -0.054  0.020  0.020  0.020 -0.029 -0.004 -0.079 -0.054  0.070 -0.004 -0.054  0.020 -0.029  0.020 -0.004 
 0.103  0.028 -0.072 -0.047 -0.047  0.028 -0.072 -0.022 -0.072  0.003 -0.072 -0.022 -0.072 -0.047 -0.072 -0.047 -0.022  0.028  0.003 -0.047 -0.072  0.078 -0.047 -0.047  0.053 -0.022 -0.022  0.053  0.128 -0.022 -0.022 -0.047 -0.072 -0.072  0.028  0.003 -0.047 -0.047 -0.022 -0.047  0.003  0.003 -0.022 -0.022 -0.072 -0.022 -0.072 -0.047 -0.047 -0.022 -0.047 -0.072  0.078 -0.072  0.003 -0.047 -0.047 -0.072 -0.047 -0.072 -0.022  0.028  0.028  0.003 -0.047 -0.022  0.028  0.053 -0.022  0.028  0.028  0.028  0.028 -0.047  0.028 -0.022 -0.047 -0.047 -0.022  0.152 -0.072  0.177  0.028 -0.022 -0.047 -0.047 -0.047  0.028  0.028 -0.022  0.003 -0.072 -0.072  0.078  0.003 -0.047  0.028  0.003  0.028 -0.022 
 0.061  0.036 -0.063 -0.038 -0.038  0.011 -0.063 -0.013 -0.063  0.011 -0.038 -0.013 -0.038 -0.038 -0.038 -0.038 -0.038  0.036 -0.013 -0.013 -0.063  0.086 -0.038 -0.038  0.036 -0.038 -0.013  0.036  0.111 -0.038 -0.013 -0.038 -0.063 -0.063 -0.013  0.011 -0.038 -0.038 -0.013 -0.038 -0.013  0.011 -0.013 -0.013 -0.063 -0.013 -0.063 -0.038 -0.038 -0.038 -0.013 -0.063  0.061 -0.063  0.011 -0.063 -0.038 -0.063 -0.063 -0.063 -0.038 -0.013  0.036  0.036 -0.038 -0.013  0.036  0.011 -0.013  0.036  0.036  0.011  0.011 -0.013  0.011 -0.038 -0.063 -0.038 -0.038  0.086 -0.063  0.086  0.011 -0.038 -0.038 -0.038 -0.038  0.011  0.011 -0.013 -0.013 -0.063 -0.063  0.036 -0.038 -0.038  0.011  0.011  0.036 -0.038 
 0.065  0.015 -0.060 -0.035 -0.035  0.015 -0.060 -0.010 -0.060 -0.010 -0.035 -0.010 -0.035 -0.060 -0.035 -0.035 -0.035  0.040 -0.010 -0.010 -0.060  0.090 -0.035 -0.035  0.040 -0.035 -0.010  0.040  0.115 -0.035 -0.010 -0.035 -0.060 -0.060 -0.010  0.015 -0.035 -0.035 -0.010 -0.035 -0.010  0.015 -0.010 -0.010 -0.060 -0.010 -0.060 -0.035 -0.035 -0.035 -0.010 -0.060  0.040 -0.060  0.015 -0.060 -0.035 -0.060 -0.060 -0.060 -0.035 -0.010  0.015  0.040 -0.035 -0.010  0.040  0.015 -0.010  0.040  0.040  0.015  0.015 -0.010  0.015 -0.035 -0.060 -0.035 -0.035  0.090 -0.060  0.065  0.015 -0.035 -0.035 -0.035 -0.035  0.015  0.015 -0.010 -0.010 -0.060 -0.060  0.040 -0.035 -0.035  0.015  0.015  0.040 -0.035 
 0.068  0.018 -0.057 -0.032 -0.032  0.018 -0.057 -0.007 -0.057 -0.007 -0.032 -0.007 -0.032 -0.057 -0.032 -0.057 -0.032  0.043 -0.007 -0.007 -0.057  0.043 -0.032 -0.032  0.043 -0.032 -0.007  0.068  0.118 -0.032 -0.032 -0.032 -0.057 -0.057 -0.007  0.018 -0.032 -0.032 -0.007  0.018 -0.007  0.018 -0.032 -0.007 -0.057 -0.007 -0.057 -0.032 -0.032 -0.032 -0.007 -0.057  0.018 -0.057 -0.007 -0.057 -0.032 -0.057 -0.057 -0.057 -0.032 -0.032  0.018  0.043 -0.032 -0.007  0.043  0.018 -0.032  0.018  0.043  0.018  0.018 -0.007  0.018 -0.007 -0.057 -0.007 -0.032  0.093 -0.057  0.043  0.018 -0.032 -0.007 -0.032 -0.032  0.043 -0.007 -0.007 -0.032 -0.057 -0.032  0.068 -0.032 -0.032 -0.032  0.018  0.043 -0.032 
 0.069  0.044 -0.055 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.055 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.094 -0.030 -0.030 -0.030 -0.055 -0.055 -0.005  0.019 -0.030 -0.030 -0.005  0.019 -0.005  0.019 -0.030  0.019 -0.055 -0.005 -0.030 -0.030 -0.030 -0.030 -0.005 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.030 -0.005  0.044  0.019 -0.030  0.019  0.044  0.019  0.019 -0.005  0.019 -0.005 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030 -0.005 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.030  0.069 -0.030 -0.030 -0.030  0.019  0.044 -0.030 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.003 -0.003  0.022  0.022 -0.028  0.022  0.047  0.022  0.022 -0.003  0.022  0.022 -0.053 -0.003 -0.028  0.072 -0.053  0.047  0.022 -0.028 -0.003 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.003  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.003 -0.003  0.021  0.021 -0.003  0.021  0.046  0.021  0.021 -0.003  0.021  0.021 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.028  0.021 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.003  0.071 -0.028 -0.028 -0.028 -0.003  0.046 -0.028 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.055 -0.030 -0.030 -0.030 -0.030 -0.030 -0.005 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.055 -0.030 -0.030 -0.030 -0.030 -0.030 -0.005 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
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 0.091  0.041 -0.058 -0.058 -0.058 -0.008 -0.033  0.016 -0.083 -0.008 -0.008 -0.008 -0.033 -0.058 -0.058 -0.083 -0.058  0.066  0.016 -0.033 -0.083  0.041 -0.058 -0.058  0.041 -0.033 -0.008  0.066  0.166  0.016 -0.058 -0.008 -0.083 -0.083  0.041 -0.008 -0.058 -0.058 -0.008 -0.008  0.016  0.041 -0.058  0.041 -0.058 -0.058 -0.058 -0.008 -0.033 -0.033  0.016 -0.058  0.066 -0.058  0.016 -0.058 -0.058 -0.083 -0.083 -0.058 -0.058 -0.033  0.016  0.016 -0.008 -0.033  0.066 -0.008 -0.008 -0.008  0.041 -0.008 -0.008 -0.008  0.016  0.016 -0.058 -0.008 -0.058  0.241 -0.083  0.116  0.066 -0.058  0.041  0.016 -0.033  0.016 -0.033 -0.033 -0.058 -0.058 -0.033  0.066 -0.058 -0.008  0.041  0.041  0.066 -0.033 
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 0.355 -0.019 -0.143 -0.119 -0.069 -0.143 -0.193 -0.119 -0.069 -0.119  0.006  0.056 -0.119 -0.069  0.131 -0.143 -0.119 -0.069  0.031 -0.193 -0.243  0.180 -0.193 -0.168  0.131 -0.168 -0.044  0.006  0.255 -0.044 -0.094 -0.119 -0.218 -0.218  0.155  0.031 -0.143 -0.143 -0.168 -0.193 -0.019 -0.168 -0.069  0.056 -0.168 -0.069 -0.044  0.006 -0.168 -0.143 -0.119 -0.069  0.081  0.106 -0.069 -0.094 -0.019 -0.094 -0.218 -0.193 -0.143  0.081 -0.094 -0.143 -0.119 -0.019  0.106 -0.019  0.255  0.081  0.131 -0.094 -0.044 -0.019  0.006  0.006 -0.143  0.056  0.255  0.629 -0.293  0.330  0.330 -0.143 -0.094 -0.044 -0.094 -0.119 -0.044 -0.168 -0.094 -0.168 -0.069 -0.019 -0.143 -0.143 -0.069  0.056  0.081 -0.019 
 0.349 -0.025 -0.149 -0.050 -0.075 -0.125 -0.199 -0.125 -0.025 -0.125  0.000  0.075 -0.125 -0.050  0.125 -0.149 -0.125 -0.075  0.025 -0.199 -0.249  0.149 -0.199 -0.199  0.149 -0.149 -0.050  0.000  0.224 -0.050 -0.100 -0.125 -0.224 -0.249  0.174  0.025 -0.149 -0.100 -0.125 -0.199 -0.025 -0.174 -0.075  0.050 -0.174 -0.075 -0.050 -0.025 -0.149 -0.149 -0.125 -0.075  0.100  0.100 -0.075 -0.100  0.000 -0.100 -0.224 -0.199 -0.174  0.100 -0.125 -0.149 -0.125 -0.025  0.075 -0.025  0.249  0.100  0.125 -0.100 -0.050  0.000  0.000 -0.025 -0.149  0.050  0.299  0.598 -0.299  0.324  0.324 -0.149 -0.125 -0.050 -0.100 -0.125 -0.075 -0.174 -0.100 -0.174 -0.075 -0.050 -0.125 -0.125 -0.050  0.050  0.075  0.025 
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 0.364 -0.060 -0.159 -0.035 -0.110 -0.159 -0.209 -0.135 -0.035 -0.135 -0.010  0.065 -0.159  0.015  0.140 -0.135 -0.159 -0.085  0.040 -0.209 -0.259  0.140 -0.234 -0.184  0.115 -0.159 -0.085 -0.035  0.214 -0.035 -0.035 -0.110 -0.209 -0.234  0.189  0.015 -0.184 -0.110 -0.135 -0.234 -0.010 -0.159 -0.085  0.040 -0.184 -0.110 -0.060 -0.035 -0.159 -0.110 -0.135 -0.035  0.090  0.065 -0.060 -0.060 -0.010 -0.135 -0.234 -0.209 -0.159  0.090 -0.135 -0.159 -0.135 -0.060  0.040 -0.035  0.264  0.115  0.115 -0.110 -0.035  0.040 -0.010 -0.035 -0.159  0.015  0.314  0.563 -0.284  0.364  0.314 -0.159 -0.135 -0.110 -0.110 -0.135 -0.110 -0.159 -0.085 -0.184 -0.110 -0.060 -0.110 -0.110 -0.060  0.090  0.115  0.090 
 0.340 -0.058 -0.158 -0.008 -0.108 -0.158 -0.183 -0.133 -0.033 -0.133  0.041  0.066 -0.158  0.041  0.141 -0.108 -0.158 -0.083  0.041 -0.208 -0.258  0.141 -0.233 -0.208  0.116 -0.158 -0.083 -0.033  0.216 -0.008 -0.033 -0.133 -0.233 -0.208  0.191  0.016 -0.183 -0.108 -0.083 -0.233 -0.033 -0.158 -0.083  0.041 -0.183 -0.108 -0.083 -0.058 -0.158 -0.108 -0.133 -0.033  0.091  0.066 -0.058 -0.083 -0.008 -0.133 -0.233 -0.208 -0.208  0.066 -0.133 -0.158 -0.158 -0.058  0.041 -0.033  0.266  0.141  0.116 -0.158 -0.033  0.041 -0.033 -0.083 -0.158 -0.008  0.315  0.540 -0.283  0.365  0.315 -0.133 -0.133 -0.108 -0.108 -0.133 -0.108 -0.133 -0.083 -0.208 -0.133 -0.083 -0.108 -0.083 -0.058  0.041  0.116  0.116 
 0.316 -0.057 -0.157 -0.007 -0.132 -0.157 -0.182 -0.132 -0.032 -0.132  0.067  0.067 -0.157  0.042  0.142 -0.132 -0.132 -0.082  0.042 -0.207 -0.257  0.142 -0.232 -0.207  0.117 -0.157 -0.082 -0.032  0.217  0.017 -0.032 -0.157 -0.232 -0.207  0.192  0.017 -0.182 -0.107 -0.082 -0.232 -0.032 -0.157 -0.082  0.042 -0.182 -0.107 -0.082 -0.057 -0.157 -0.107 -0.132 -0.032  0.092  0.067 -0.032 -0.107 -0.007 -0.157 -0.232 -0.207 -0.207  0.017 -0.132 -0.157 -0.157 -0.032  0.042 -0.007  0.267  0.142  0.092 -0.157 -0.032  0.092 -0.032 -0.082 -0.157 -0.007  0.316  0.541 -0.257  0.366  0.316 -0.107 -0.132 -0.107 -0.132 -0.132 -0.107 -0.157 -0.082 -0.207 -0.157 -0.082 -0.132 -0.082 -0.057  0.042  0.117  0.117 
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 0.302 -0.072 -0.171 -0.022 -0.146 -0.122 -0.171 -0.171 -0.047 -0.047  0.103  0.078 -0.246  0.053  0.177 -0.097 -0.047 -0.097  0.028 -0.221 -0.271  0.152 -0.246 -0.221  0.053 -0.146 -0.097 -0.047  0.177  0.003 -0.047 -0.196 -0.296 -0.246  0.152 -0.022 -0.146 -0.122 -0.072 -0.246 -0.047 -0.171 -0.122  0.003 -0.146 -0.146 -0.122 -0.072 -0.171 -0.122 -0.072 -0.047  0.128 -0.022 -0.072 -0.122  0.003 -0.171 -0.246 -0.246 -0.221  0.028 -0.146 -0.146 -0.196 -0.047  0.078 -0.047  0.202  0.152  0.078 -0.196  0.003  0.177 -0.022 -0.122 -0.196  0.028  0.252  0.426 -0.246  0.352  0.277  0.003 -0.171 -0.097 -0.146 -0.146 -0.122 -0.196 -0.097 -0.221 -0.196 -0.097 -0.146 -0.097  0.078  0.003  0.078  0.103 
 0.275 -0.074 -0.173  0.001 -0.148 -0.124 -0.173 -0.173 -0.049 -0.074  0.101  0.076 -0.223  0.051  0.175 -0.099 -0.024 -0.099  0.026 -0.223 -0.273  0.150 -0.298 -0.248  0.051 -0.148 -0.099 -0.049  0.150  0.001 -0.049 -0.198 -0.298 -0.248  0.150 -0.024 -0.148 -0.124 -0.074 -0.248 -0.049 -0.173 -0.124  0.001 -0.148 -0.148 -0.148 -0.049 -0.173 -0.124 -0.099 -0.074  0.101  0.001 -0.049 -0.124  0.001 -0.173 -0.248 -0.248 -0.223  0.001 -0.173 -0.148 -0.198 -0.049  0.101 -0.024  0.200  0.150  0.076 -0.198 -0.024  0.175 -0.024 -0.124 -0.223  0.001  0.275  0.375 -0.248  0.350  0.275  0.026 -0.173 -0.099 -0.148 -0.148 -0.124 -0.198 -0.074 -0.223 -0.198 -0.099 -0.148 -0.099  0.076 -0.024  0.051  0.101 
 0.275 -0.074 -0.174 -0.024 -0.149 -0.099 -0.224 -0.174 -0.074 -0.074  0.100  0.075 -0.224  0.050  0.175 -0.099 -0.024 -0.099  0.025 -0.224 -0.274  0.150 -0.298 -0.249  0.050 -0.149 -0.099 -0.049  0.150  0.000 -0.049 -0.199 -0.298 -0.224  0.150 -0.074 -0.149 -0.124 -0.074 -0.224 -0.049 -0.174 -0.124  0.000 -0.149 -0.149 -0.149 -0.049 -0.174 -0.124 -0.099 -0.074  0.100 -0.024 -0.074 -0.099 -0.024 -0.174 -0.249 -0.249 -0.224  0.000 -0.174 -0.149 -0.199 -0.024  0.100  0.000  0.150  0.125  0.075 -0.199 -0.024  0.175 -0.024 -0.124 -0.224  0.000  0.275  0.374 -0.249  0.374  0.250  0.025 -0.199 -0.099 -0.149 -0.149 -0.124 -0.199 -0.074 -0.224 -0.174 -0.099 -0.149 -0.099  0.075 -0.049  0.050  0.100 
 0.300 -0.073 -0.198 -0.023 -0.148 -0.098 -0.223 -0.173 -0.073 -0.073  0.101  0.076 -0.248  0.051  0.176 -0.098 -0.023 -0.098  0.026 -0.223 -0.273  0.151 -0.297 -0.248  0.051 -0.148 -0.098 -0.048  0.151  0.001 -0.048 -0.223 -0.297 -0.223  0.151 -0.073 -0.148 -0.123 -0.073 -0.223 -0.048 -0.173 -0.123  0.001 -0.148 -0.148 -0.148 -0.048 -0.173 -0.123 -0.098 -0.073  0.101 -0.048 -0.123 -0.098 -0.023 -0.173 -0.248 -0.248 -0.223  0.001 -0.173 -0.148 -0.198 -0.023  0.126 -0.023  0.101  0.126  0.076 -0.198 -0.023  0.201 -0.023 -0.123 -0.223  0.001  0.276  0.350 -0.248  0.400  0.251  0.026 -0.198 -0.098 -0.148 -0.148 -0.123 -0.198 -0.073 -0.223 -0.173 -0.098 -0.148 -0.098  0.101 -0.048  0.051  0.101 
 0.302 -0.072 -0.196 -0.022 -0.146 -0.097 -0.221 -0.171 -0.097 -0.072  0.103  0.103 -0.246  0.053  0.177 -0.097  0.003 -0.097  0.028 -0.221 -0.271  0.152 -0.296 -0.246  0.028 -0.146 -0.097 -0.047  0.152  0.003 -0.047 -0.221 -0.296 -0.221  0.152 -0.072 -0.146 -0.122 -0.072 -0.221 -0.022 -0.171 -0.097  0.003 -0.171 -0.171 -0.171 -0.072 -0.171 -0.122 -0.122 -0.072  0.103 -0.047 -0.122 -0.097 -0.047 -0.171 -0.246 -0.246 -0.221  0.003 -0.171 -0.146 -0.196 -0.022  0.128 -0.022  0.053  0.128  0.028 -0.196 -0.022  0.202 -0.022 -0.122 -0.221  0.003  0.227  0.352 -0.246  0.402  0.252  0.028 -0.196 -0.097 -0.146 -0.146 -0.122 -0.196 -0.072 -0.246 -0.171 -0.097 -0.146 -0.097  0.103 -0.097  0.053  0.103 
 0.281 -0.068 -0.142 -0.142 -0.093 -0.043 -0.142 -0.093 -0.142 -0.018  0.057  0.082 -0.167  0.082  0.156 -0.093 -0.043 -0.043  0.057 -0.167 -0.217  0.132 -0.217 -0.192  0.057 -0.093 -0.093 -0.068  0.132 -0.018  0.007 -0.192 -0.217 -0.142  0.032 -0.043 -0.167 -0.142 -0.043 -0.217  0.007 -0.093 -0.142  0.007 -0.118 -0.142 -0.118 -0.043 -0.142 -0.043 -0.118 -0.093  0.082 -0.068 -0.093 -0.093 -0.093 -0.142 -0.192 -0.192 -0.192 -0.018 -0.142 -0.068 -0.118  0.032  0.082 -0.068 -0.068  0.107  0.082 -0.142 -0.068  0.132 -0.018 -0.068 -0.167 -0.068  0.132  0.331 -0.167  0.381  0.156  0.007 -0.192 -0.068 -0.118 -0.068 -0.068 -0.118 -0.093 -0.167 -0.142 -0.043 -0.068 -0.043  0.132 -0.192  0.032  0.007 
 0.244 -0.030 -0.105 -0.105 -0.055 -0.030 -0.130 -0.080 -0.105 -0.080 -0.030  0.019 -0.130  0.019  0.094 -0.030 -0.055  0.019  0.094 -0.105 -0.130  0.044 -0.130 -0.105  0.044 -0.030 -0.005 -0.030  0.144 -0.030 -0.030 -0.130 -0.155 -0.155 -0.005  0.044 -0.080 -0.105 -0.080 -0.130  0.044 -0.030 -0.055  0.019 -0.105 -0.080 -0.130 -0.030 -0.080 -0.005 -0.130 -0.055  0.119  0.019 -0.055 -0.055 -0.080 -0.105 -0.105 -0.105 -0.105  0.044 -0.055 -0.030 -0.080 -0.055  0.069 -0.005 -0.055  0.069  0.019 -0.055 -0.005  0.094 -0.005 -0.080 -0.105 -0.030 -0.005  0.343 -0.130  0.318  0.144 -0.030 -0.130 -0.130 -0.055  0.019 -0.005 -0.055 -0.030 -0.080 -0.080  0.019 -0.030 -0.080  0.069 -0.155 -0.005 -0.005 
 0.212 -0.012 -0.087 -0.087 -0.037 -0.037 -0.112 -0.087 -0.112 -0.062 -0.037  0.013 -0.112 -0.012  0.063 -0.037 -0.062  0.038  0.113 -0.087 -0.137  0.038 -0.112 -0.087  0.038 -0.012  0.013 -0.012  0.162 -0.012 -0.062 -0.112 -0.137 -0.137  0.013  0.038 -0.062 -0.087 -0.087 -0.112  0.038 -0.012 -0.062  0.038 -0.087 -0.062 -0.137 -0.037 -0.112 -0.012 -0.137 -0.062  0.113  0.038 -0.062 -0.037 -0.062 -0.112 -0.087 -0.087 -0.087  0.063 -0.037 -0.012 -0.062 -0.037  0.038  0.013 -0.037 -0.012  0.013 -0.037 -0.012  0.038 -0.012 -0.062 -0.087 -0.037 -0.062  0.362 -0.137  0.287  0.063 -0.037 -0.112 -0.112 -0.037  0.038 -0.012 -0.062 -0.062 -0.087 -0.062  0.013 -0.037 -0.062  0.063 -0.137  0.013  0.013 
 0.190  0.016 -0.084 -0.084 -0.009 -0.009 -0.084 -0.084 -0.059 -0.034 -0.034 -0.009 -0.084 -0.009 -0.009 -0.034 -0.034  0.041  0.116 -0.059 -0.109  0.016 -0.084 -0.084  0.066 -0.009  0.016  0.016  0.116  0.016 -0.084 -0.084 -0.109 -0.109  0.041  0.016 -0.084 -0.059 -0.059 -0.059  0.016 -0.009 -0.034  0.066 -0.084 -0.084 -0.109 -0.009 -0.084 -0.009 -0.109 -0.034  0.141 -0.009 -0.059 -0.059 -0.034 -0.084 -0.059 -0.084 -0.059  0.016 -0.034  0.016 -0.059 -0.009  0.041  0.091 -0.034 -0.009  0.016 -0.009  0.016 -0.009  0.016 -0.059 -0.059 -0.034 -0.059  0.315 -0.109  0.265  0.041 -0.009 -0.109 -0.084 -0.009  0.041  0.016 -0.034 -0.034 -0.059 -0.059  0.041 -0.034 -0.059  0.016 -0.084 -0.009  0.016 
 0.149  0.025 -0.075 -0.075  0.000  0.000 -0.075 -0.075 -0.050 -0.025 -0.025  0.000 -0.075  0.000  0.000 -0.050 -0.050  0.050  0.125 -0.075 -0.100  0.025 -0.075 -0.075  0.075  0.000  0.000  0.025  0.125  0.000 -0.075 -0.075 -0.100 -0.100  0.025  0.000 -0.075 -0.050 -0.050 -0.050  0.025  0.000 -0.025  0.025 -0.075 -0.075 -0.100 -0.050 -0.075  0.000 -0.100 -0.050  0.149  0.000 -0.050 -0.050 -0.050 -0.100 -0.050 -0.075 -0.050 -0.025 -0.025  0.025 -0.050 -0.025  0.025  0.100 -0.050  0.000  0.025  0.000  0.050  0.000  0.025 -0.050 -0.050 -0.025 -0.075  0.299 -0.100  0.274  0.050 -0.025 -0.100 -0.075  0.000  0.025  0.025 -0.025 -0.025 -0.050 -0.050  0.050 -0.025 -0.050  0.000 -0.075  0.000  0.025 
 0.111  0.036 -0.064 -0.064  0.011  0.011 -0.089 -0.039 -0.039 -0.014 -0.039 -0.039 -0.089 -0.039 -0.089 -0.039 -0.039  0.036  0.111 -0.064 -0.089  0.061 -0.089 -0.064  0.061  0.011 -0.014  0.036  0.086  0.011 -0.064 -0.064 -0.089 -0.089  0.036  0.011 -0.064 -0.064 -0.039 -0.039  0.011 -0.014 -0.014  0.011 -0.064 -0.064 -0.089 -0.064 -0.064  0.011 -0.089 -0.039  0.136 -0.064 -0.039 -0.039 -0.039 -0.089 -0.039 -0.089 -0.039 -0.014 -0.014  0.011 -0.039 -0.014  0.036  0.111 -0.039 -0.014  0.036 -0.014  0.036 -0.039  0.036 -0.039 -0.039 -0.039 -0.064  0.160 -0.089  0.260  0.011 -0.039 -0.089 -0.064  0.011  0.036  0.036 -0.039 -0.014 -0.089 -0.064  0.061 -0.014 -0.039  0.011 -0.039  0.011  0.011 
 0.117  0.042 -0.058 -0.058  0.017 -0.008 -0.083 -0.033 -0.058 -0.008 -0.033 -0.033 -0.083 -0.033 -0.083 -0.058 -0.033  0.042  0.092 -0.058 -0.083  0.067 -0.083 -0.083  0.067  0.017 -0.008  0.042  0.067 -0.008 -0.058 -0.058 -0.083 -0.083  0.042  0.017 -0.058 -0.058 -0.033 -0.033  0.017 -0.008 -0.008  0.017 -0.058 -0.058 -0.083 -0.058 -0.058 -0.008 -0.083 -0.033  0.117 -0.083 -0.033 -0.033 -0.033 -0.083 -0.033 -0.083 -0.033 -0.008 -0.008 -0.008 -0.058 -0.008  0.042  0.092 -0.033 -0.008  0.067 -0.008  0.017 -0.033  0.042 -0.033 -0.033 -0.033 -0.058  0.142 -0.083  0.266  0.017 -0.033 -0.083 -0.058  0.017  0.042  0.042 -0.033 -0.008 -0.083 -0.058  0.067 -0.008 -0.033  0.017 -0.033  0.017 -0.008 
 0.101  0.051 -0.073 -0.048 -0.023  0.001 -0.073 -0.023 -0.048  0.001 -0.023 -0.023 -0.073 -0.073 -0.073 -0.048 -0.023  0.051  0.026 -0.048 -0.073  0.051 -0.073 -0.073  0.076  0.001  0.001  0.051  0.076 -0.023 -0.048 -0.048 -0.073 -0.073  0.051  0.001 -0.048 -0.048 -0.023 -0.023  0.026  0.001  0.001  0.001 -0.073 -0.048 -0.073 -0.048 -0.048  0.001 -0.073 -0.073  0.051 -0.073 -0.023 -0.048 -0.023 -0.073 -0.023 -0.073 -0.023  0.001  0.026  0.001 -0.048  0.001  0.026  0.076 -0.048  0.026  0.051  0.001  0.026 -0.048  0.051 -0.023 -0.048 -0.023 -0.023  0.101 -0.073  0.276  0.051 -0.023 -0.073 -0.048  0.001  0.001  0.026 -0.023 -0.023 -0.073 -0.048  0.076  0.001 -0.048  0.026 -0.023  0.026  0.001 
 0.108  0.058 -0.066 -0.041 -0.016  0.033 -0.066 -0.016 -0.041  0.008 -0.016 -0.016 -0.066 -0.066 -0.066 -0.041 -0.016  0.033  0.033 -0.041 -0.066  0.058 -0.066 -0.066  0.083  0.008  0.008  0.083  0.083 -0.016 -0.041 -0.041 -0.066 -0.066  0.033  0.008 -0.041 -0.041 -0.016  0.008  0.008  0.008  0.008  0.008 -0.066 -0.066 -0.066 -0.041 -0.041 -0.016 -0.066 -0.066  0.058 -0.066 -0.016 -0.041 -0.016 -0.066 -0.016 -0.066 -0.016 -0.041  0.033  0.008 -0.041 -0.016  0.033  0.083 -0.041  0.033  0.033  0.008  0.033 -0.041  0.033 -0.016 -0.041 -0.016 -0.016  0.108 -0.066  0.183  0.058 -0.016 -0.066 -0.041  0.008  0.008  0.008 -0.041 -0.016 -0.066 -0.066  0.083 -0.016 -0.041  0.008 -0.016  0.033  0.008 
 0.066  0.041 -0.059 -0.034 -0.034  0.041 -0.059 -0.009 -0.059  0.016 -0.034 -0.009 -0.059 -0.059 -0.034 -0.034 -0.009  0.041  0.016 -0.009 -0.059  0.041 -0.034 -0.034  0.041 -0.009 -0.009  0.091  0.066 -0.009 -0.034 -0.034 -0.059 -0.059  0.041  0.016 -0.059 -0.034 -0.009 -0.009  0.016  0.016 -0.009  0.016 -0.059 -0.059 -0.059 -0.034 -0.034 -0.034 -0.009 -0.059  0.041 -0.059 -0.009 -0.034 -0.034 -0.059 -0.034 -0.059 -0.034 -0.034  0.041  0.041 -0.034 -0.009  0.016  0.066 -0.034  0.041  0.041  0.016  0.041 -0.009  0.041 -0.009 -0.059 -0.009 -0.009  0.116 -0.059  0.116  0.041 -0.009 -0.059 -0.034 -0.034 -0.009 -0.009 -0.034 -0.009 -0.059 -0.059  0.066 -0.009 -0.034 -0.009 -0.009  0.041 -0.009 
 0.071  0.021 -0.053 -0.028 -0.028  0.046 -0.053 -0.003 -0.053  0.021 -0.028 -0.003 -0.053 -0.053 -0.028 -0.028 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.003 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053  0.021 -0.003 -0.053 -0.028 -0.003  0.021 -0.003  0.021 -0.003 -0.003 -0.053 -0.053 -0.053 -0.028 -0.028 -0.028 -0.003 -0.053  0.046 -0.053 -0.003 -0.028 -0.028 -0.053 -0.053 -0.053 -0.053 -0.028  0.021  0.046 -0.028 -0.003  0.021  0.046 -0.028  0.046  0.046 -0.003  0.021 -0.003  0.046 -0.003 -0.053 -0.003 -0.028  0.096 -0.053  0.046  0.021 -0.028 -0.053 -0.028 -0.028 -0.003 -0.003 -0.028 -0.028 -0.053 -0.028  0.071 -0.028 -0.028 -0.003 -0.003  0.046 -0.003 
 0.073  0.048 -0.052 -0.027 -0.027  0.023 -0.052  0.023 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.023 -0.002  0.023 -0.027  0.023 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.023 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.023  0.048 -0.027 -0.002  0.023  0.023 -0.027  0.023  0.048 -0.002  0.023 -0.002  0.023 -0.002 -0.052 -0.002 -0.027  0.073 -0.052  0.048  0.023 -0.027 -0.002 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.052 -0.027  0.073 -0.027 -0.027 -0.027 -0.002  0.048 -0.027 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.003 -0.003  0.022  0.022 -0.028  0.022  0.047  0.022  0.022 -0.003  0.022  0.022 -0.053 -0.003 -0.028  0.072 -0.053  0.047  0.022 -0.028 -0.003 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.003  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.004 -0.004  0.021  0.021 -0.004  0.021  0.046  0.021  0.021 -0.004  0.021  0.021 -0.054 -0.004 -0.029  0.071 -0.054  0.046  0.021 -0.029  0.021 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.004  0.071 -0.029 -0.029 -0.029 -0.004  0.046 -0.029 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.020 -0.004  0.020 -0.029  0.020 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.004 -0.004  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.004  0.020  0.020 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.004  0.070 -0.029 -0.004 -0.029 -0.004  0.045 -0.029 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.110  0.035 -0.064 -0.039 -0.064 -0.014 -0.014  0.035 -0.089 -0.039 -0.014  0.010 -0.014 -0.039 -0.064 -0.089 -0.064  0.060  0.010 -0.039 -0.089  0.085 -0.039 -0.039  0.035 -0.014 -0.039  0.060  0.135 -0.064 -0.064 -0.014 -0.089 -0.089  0.010 -0.039 -0.064 -0.014 -0.014 -0.014  0.035  0.060 -0.014 -0.014 -0.039 -0.064 -0.039 -0.014 -0.039 -0.039 -0.014 -0.064  0.035 -0.064 -0.039 -0.039 -0.039 -0.089 -0.089 -0.089 -0.039 -0.039  0.010  0.010  0.010 -0.014  0.035  0.010  0.010  0.010  0.185  0.010 -0.014  0.010 -0.014 -0.014 -0.089 -0.014 -0.014  0.135 -0.089  0.110  0.110 -0.064  0.010 -0.014 -0.039 -0.014 -0.039 -0.039 -0.064 -0.014 -0.014  0.085 -0.064 -0.039 -0.014  0.060  0.085 -0.064 
 0.225  0.000 -0.124 -0.074 -0.024 -0.049 -0.049 -0.024 -0.149 -0.049 -0.024 -0.024 -0.049 -0.024 -0.099 -0.149 -0.074  0.075  0.100 -0.099 -0.124  0.075 -0.099 -0.099  0.125 -0.049 -0.049  0.050  0.250  0.000 -0.124 -0.049 -0.124 -0.149  0.025  0.025 -0.124 -0.049 -0.049 -0.074  0.000  0.025 -0.074  0.000 -0.099 -0.049 -0.074  0.050 -0.074 -0.074 -0.074 -0.074  0.100 -0.124 -0.074 -0.049 -0.099 -0.099 -0.124 -0.149  0.000 -0.024  0.000 -0.049 -0.049 -0.024  0.100  0.000  0.000  0.000  0.225  0.025 -0.049  0.025  0.000  0.000 -0.124  0.000  0.000  0.275 -0.149  0.250  0.200 -0.024  0.000 -0.024 -0.074  0.000 -0.049 -0.099 -0.049 -0.024 -0.074  0.050 -0.049  0.000  0.025  0.100  0.150 -0.099 
 0.250 -0.049 -0.124 -0.099 -0.049 -0.074 -0.149 -0.049 -0.174 -0.099 -0.024 -0.024 -0.099 -0.024  0.025 -0.174 -0.099  0.075  0.075 -0.149 -0.174  0.075 -0.149 -0.099  0.150 -0.099 -0.024 -0.024  0.200 -0.024 -0.074 -0.074 -0.174 -0.199  0.025  0.000 -0.124 -0.074 -0.099 -0.099  0.050 -0.024 -0.074  0.000 -0.099 -0.049 -0.074  0.075 -0.099 -0.024 -0.124  0.000  0.100 -0.074 -0.049 -0.099 -0.049 -0.099 -0.149 -0.174 -0.049 -0.024 -0.024 -0.049 -0.074 -0.074  0.100  0.000  0.050  0.000  0.175  0.025 -0.024  0.100  0.000 -0.024 -0.149  0.000 -0.024  0.299 -0.174  0.349  0.250 -0.049 -0.049 -0.049 -0.099 -0.024 -0.074 -0.124 -0.049 -0.049 -0.074  0.000 -0.074 -0.049  0.025  0.075  0.200 -0.099 
 0.270 -0.054 -0.178 -0.079 -0.079 -0.104 -0.178 -0.079 -0.129 -0.153 -0.004 -0.029 -0.153 -0.029  0.071 -0.153 -0.104  0.021  0.046 -0.203 -0.203  0.096 -0.203 -0.129  0.121 -0.129 -0.054 -0.054  0.145 -0.079 -0.104 -0.129 -0.228 -0.253 -0.004 -0.029 -0.104 -0.129 -0.129 -0.104  0.046 -0.129 -0.104  0.071 -0.153 -0.079 -0.129  0.096 -0.129 -0.054 -0.079 -0.029  0.096 -0.054 -0.079 -0.079 -0.004 -0.079 -0.178 -0.203 -0.079  0.046 -0.104 -0.079 -0.104 -0.079  0.096  0.021  0.096  0.021  0.195 -0.004 -0.079  0.145  0.021  0.021 -0.153  0.071  0.096  0.370 -0.228  0.320  0.295 -0.104 -0.104 -0.079 -0.104 -0.079 -0.054 -0.129 -0.029 -0.079 -0.129 -0.004 -0.079 -0.104  0.046  0.046  0.170 -0.054 
 0.275 -0.049 -0.174 -0.074 -0.099 -0.124 -0.224 -0.074 -0.099 -0.174  0.025  0.000 -0.174 -0.024  0.125 -0.124 -0.099 -0.024  0.025 -0.199 -0.224  0.100 -0.224 -0.124  0.150 -0.149 -0.049  0.025  0.125 -0.049 -0.074 -0.099 -0.249 -0.249  0.050 -0.024 -0.124 -0.149 -0.049 -0.099  0.000 -0.149 -0.099  0.050 -0.149 -0.099 -0.124  0.075 -0.124 -0.049 -0.099 -0.049  0.100 -0.024 -0.099 -0.099  0.000 -0.099 -0.199 -0.199 -0.124  0.025 -0.099 -0.099 -0.124 -0.024  0.075  0.025  0.150  0.025  0.175 -0.024 -0.099  0.175  0.025  0.000 -0.149  0.075  0.175  0.399 -0.249  0.324  0.275 -0.124 -0.124 -0.074 -0.099 -0.074 -0.024 -0.124 -0.024 -0.124 -0.149  0.000 -0.124 -0.124  0.075  0.000  0.175 -0.024 
 0.283 -0.066 -0.165 -0.091 -0.116 -0.165 -0.165 -0.066 -0.091 -0.165  0.059 -0.016 -0.141  0.009  0.109 -0.116 -0.116 -0.066  0.009 -0.190 -0.240  0.084 -0.190 -0.141  0.158 -0.165 -0.066 -0.016  0.109 -0.066 -0.041 -0.165 -0.240 -0.265  0.084  0.059 -0.141 -0.141 -0.041 -0.141  0.009 -0.165 -0.116  0.059 -0.190 -0.091 -0.091  0.059 -0.141 -0.066 -0.141 -0.041  0.084 -0.016 -0.116 -0.066  0.034 -0.141 -0.215 -0.215 -0.141  0.059 -0.116 -0.116 -0.141 -0.016  0.084 -0.016  0.134  0.084  0.158 -0.041 -0.066  0.158  0.009  0.009 -0.141  0.059  0.233  0.408 -0.265  0.333  0.283 -0.116 -0.116 -0.091 -0.116 -0.091 -0.041 -0.141 -0.041 -0.141 -0.091 -0.041 -0.141 -0.116  0.034 -0.016  0.134  0.034 
 0.299 -0.050 -0.174 -0.100 -0.100 -0.149 -0.174 -0.100 -0.100 -0.149  0.050  0.000 -0.149  0.000  0.149 -0.125 -0.125 -0.075  0.000 -0.199 -0.199  0.075 -0.199 -0.149  0.149 -0.149 -0.075 -0.025  0.149 -0.075 -0.050 -0.125 -0.249 -0.274  0.100  0.050 -0.125 -0.149 -0.050 -0.149  0.000 -0.174 -0.125  0.050 -0.199 -0.100 -0.100  0.025 -0.149 -0.075 -0.149 -0.050  0.075 -0.025 -0.100 -0.075  0.050 -0.174 -0.224 -0.224 -0.174  0.075 -0.125 -0.125 -0.125 -0.025  0.100 -0.025  0.149  0.075  0.100 -0.100 -0.050  0.174  0.025 -0.025 -0.149  0.050  0.224  0.399 -0.274  0.324  0.274 -0.100 -0.125 -0.100 -0.125 -0.125 -0.075 -0.149 -0.050 -0.125 -0.100 -0.050 -0.149 -0.100  0.050 -0.025  0.125  0.025 
 0.286 -0.063 -0.187 -0.063 -0.113 -0.162 -0.162 -0.113 -0.113 -0.162  0.062  0.012 -0.162  0.062  0.161 -0.088 -0.113 -0.088 -0.013 -0.212 -0.212  0.087 -0.212 -0.138  0.161 -0.162 -0.088 -0.038  0.137 -0.063 -0.013 -0.113 -0.262 -0.262  0.137  0.037 -0.138 -0.088 -0.063 -0.187  0.012 -0.187 -0.138  0.037 -0.212 -0.113 -0.088  0.012 -0.162 -0.113 -0.088 -0.063  0.062 -0.038 -0.113 -0.013  0.012 -0.187 -0.237 -0.237 -0.187  0.062 -0.113 -0.138 -0.138 -0.038  0.087 -0.038  0.137  0.137  0.087 -0.162 -0.038  0.211  0.012 -0.038 -0.187  0.037  0.211  0.411 -0.287  0.336  0.286 -0.113 -0.138 -0.113 -0.138 -0.138 -0.088 -0.187 -0.063 -0.138 -0.113 -0.063 -0.138 -0.088  0.012 -0.038  0.137  0.012 
 0.309 -0.089 -0.189 -0.089 -0.114 -0.189 -0.164 -0.139 -0.089 -0.164  0.060  0.010 -0.164  0.035  0.135 -0.089 -0.139 -0.089  0.010 -0.214 -0.214  0.085 -0.214 -0.139  0.160 -0.164 -0.089 -0.039  0.135 -0.064 -0.014 -0.139 -0.264 -0.264  0.135  0.035 -0.139 -0.089 -0.064 -0.189  0.010 -0.189 -0.139  0.010 -0.214 -0.089 -0.114  0.010 -0.164 -0.139 -0.089 -0.039  0.060 -0.039 -0.114 -0.014  0.035 -0.189 -0.239 -0.239 -0.189  0.060 -0.114 -0.139 -0.139 -0.039  0.085 -0.039  0.085  0.135  0.085 -0.164 -0.014  0.235  0.010 -0.039 -0.189  0.060  0.235  0.409 -0.288  0.334  0.284 -0.089 -0.164 -0.114 -0.139 -0.139 -0.089 -0.189 -0.064 -0.139 -0.114 -0.064 -0.139 -0.089  0.010 -0.039  0.135  0.010 
 0.305 -0.069 -0.193 -0.094 -0.119 -0.168 -0.143 -0.143 -0.069 -0.143  0.056  0.006 -0.168  0.081  0.106 -0.119 -0.143 -0.094  0.031 -0.218 -0.243  0.155 -0.218 -0.143  0.106 -0.168 -0.094 -0.069  0.131 -0.069 -0.019 -0.193 -0.268 -0.268  0.155 -0.019 -0.143 -0.094 -0.069 -0.193  0.006 -0.168 -0.143  0.006 -0.193 -0.094 -0.143 -0.019 -0.168 -0.143 -0.094 -0.019  0.056 -0.044 -0.119 -0.019  0.031 -0.193 -0.218 -0.243 -0.193  0.056 -0.119 -0.143 -0.143 -0.044  0.106 -0.019  0.031  0.131  0.056 -0.168  0.006  0.230  0.006 -0.019 -0.193  0.056  0.280  0.380 -0.293  0.355  0.230 -0.044 -0.168 -0.143 -0.143 -0.143 -0.094 -0.193 -0.069 -0.168 -0.094 -0.094 -0.143 -0.119  0.006 -0.044  0.131  0.031 
 0.302 -0.071 -0.196 -0.096 -0.121 -0.171 -0.146 -0.146 -0.071 -0.121  0.053  0.003 -0.171  0.078  0.103 -0.121 -0.146 -0.096  0.028 -0.221 -0.246  0.153 -0.221 -0.146  0.103 -0.171 -0.096 -0.046  0.128 -0.071 -0.021 -0.221 -0.271 -0.271  0.153 -0.046 -0.146 -0.096 -0.071 -0.196  0.003 -0.171 -0.146  0.003 -0.196 -0.096 -0.146  0.003 -0.171 -0.146 -0.096 -0.021  0.053 -0.046 -0.146 -0.021  0.028 -0.196 -0.221 -0.246 -0.196  0.053 -0.121 -0.146 -0.146 -0.046  0.128 -0.021  0.003  0.128  0.053 -0.171  0.003  0.203  0.003  0.028 -0.196  0.053  0.278  0.377 -0.295  0.402  0.253 -0.046 -0.171 -0.146 -0.146 -0.146 -0.096 -0.196 -0.046 -0.171 -0.096 -0.096 -0.146 -0.121  0.028 -0.046  0.128  0.028 
 0.303 -0.071 -0.195 -0.096 -0.096 -0.145 -0.195 -0.145 -0.071 -0.121  0.029  0.004 -0.170  0.054  0.079 -0.121 -0.145 -0.096  0.029 -0.220 -0.245  0.153 -0.220 -0.145  0.079 -0.170 -0.121 -0.071  0.129 -0.121 -0.021 -0.220 -0.270 -0.245  0.129 -0.096 -0.145 -0.096 -0.071 -0.220 -0.021 -0.170 -0.145  0.004 -0.195 -0.071 -0.170  0.004 -0.195 -0.145 -0.096  0.004  0.054 -0.071 -0.145 -0.046 -0.046 -0.195 -0.220 -0.245 -0.195  0.054 -0.121 -0.145 -0.145 -0.021  0.129 -0.046  0.004  0.129  0.054 -0.170  0.004  0.153  0.004  0.029 -0.195  0.029  0.278  0.378 -0.295  0.427  0.253 -0.046 -0.170 -0.145 -0.145 -0.145 -0.096 -0.195 -0.046 -0.195 -0.096 -0.096 -0.145 -0.121  0.029 -0.046  0.129  0.029 
 0.280 -0.069 -0.218 -0.094 -0.094 -0.143 -0.218 -0.143 -0.069 -0.119  0.031  0.031 -0.168  0.056  0.081 -0.119 -0.143 -0.094  0.031 -0.218 -0.243  0.155 -0.218 -0.143  0.081 -0.168 -0.119 -0.094  0.131 -0.143 -0.019 -0.218 -0.268 -0.243  0.131 -0.069 -0.143 -0.094 -0.069 -0.218 -0.019 -0.168 -0.143  0.006 -0.193 -0.069 -0.193 -0.019 -0.193 -0.143 -0.094  0.006  0.056 -0.069 -0.143 -0.044 -0.044 -0.193 -0.218 -0.243 -0.193  0.056 -0.119 -0.143 -0.143  0.006  0.106 -0.044  0.006  0.131  0.056 -0.168  0.006  0.155 -0.019  0.031 -0.193  0.031  0.280  0.380 -0.293  0.429  0.230 -0.044 -0.168 -0.143 -0.143 -0.143 -0.094 -0.193 -0.069 -0.193 -0.094 -0.094 -0.143 -0.119  0.031 -0.044  0.131  0.006 
 0.279 -0.070 -0.220 -0.070 -0.070 -0.145 -0.220 -0.145 -0.095 -0.120  0.004  0.029 -0.145  0.054  0.079 -0.120 -0.095 -0.095  0.004 -0.220 -0.245  0.129 -0.245 -0.195  0.054 -0.170 -0.120 -0.095  0.129 -0.145 -0.020 -0.220 -0.270 -0.245  0.104 -0.070 -0.145 -0.120 -0.070 -0.220  0.004 -0.170 -0.145 -0.020 -0.170 -0.070 -0.195 -0.070 -0.195 -0.145 -0.120  0.004  0.054 -0.070 -0.170 -0.020 -0.045 -0.195 -0.220 -0.245 -0.195  0.054 -0.145 -0.145 -0.145  0.054  0.104 -0.045 -0.020  0.129  0.054 -0.170  0.004  0.154 -0.020  0.029 -0.195  0.029  0.279  0.378 -0.245  0.428  0.204 -0.045 -0.170 -0.145 -0.145 -0.145 -0.120 -0.195 -0.095 -0.195 -0.095 -0.095 -0.145 -0.120  0.029 -0.045  0.129 -0.020 
 0.276 -0.073 -0.223 -0.073 -0.073 -0.123 -0.223 -0.148 -0.098 -0.123  0.026  0.026 -0.148  0.051  0.076 -0.123 -0.098 -0.098  0.001 -0.223 -0.248  0.126 -0.248 -0.198  0.026 -0.173 -0.123 -0.098  0.076 -0.148 -0.023 -0.223 -0.273 -0.248  0.101 -0.073 -0.148 -0.123 -0.073 -0.223  0.001 -0.173 -0.148  0.001 -0.123 -0.073 -0.223 -0.073 -0.198 -0.148 -0.123  0.001  0.026 -0.073 -0.173 -0.023 -0.048 -0.173 -0.223 -0.248 -0.198  0.051 -0.173 -0.148 -0.148  0.051  0.126 -0.048  0.001  0.126  0.051 -0.173  0.026  0.176 -0.023  0.026 -0.173 -0.023  0.276  0.375 -0.248  0.425  0.226 -0.048 -0.173 -0.123 -0.123 -0.148 -0.123 -0.198 -0.073 -0.198 -0.098 -0.098 -0.148 -0.123  0.051 -0.023  0.126 -0.023 
 0.276 -0.073 -0.197 -0.073 -0.073 -0.123 -0.197 -0.147 -0.098 -0.098  0.052  0.027 -0.147  0.052  0.077 -0.123 -0.098 -0.098  0.002 -0.222 -0.247  0.127 -0.247 -0.222  0.027 -0.147 -0.123 -0.098  0.077 -0.147 -0.023 -0.247 -0.272 -0.247  0.102 -0.098 -0.172 -0.123 -0.073 -0.222  0.002 -0.172 -0.123  0.002 -0.098 -0.073 -0.222 -0.098 -0.197 -0.147 -0.123  0.002  0.027 -0.073 -0.172 -0.023 -0.048 -0.172 -0.222 -0.247 -0.197  0.027 -0.172 -0.147 -0.147  0.052  0.077 -0.048 -0.023  0.127  0.052 -0.172  0.027  0.176 -0.048  0.027 -0.172 -0.023  0.276  0.376 -0.222  0.426  0.226 -0.023 -0.172 -0.123 -0.123 -0.123 -0.073 -0.197 -0.048 -0.197 -0.098 -0.098 -0.147 -0.123  0.077  0.002  0.102 -0.023 
 0.275 -0.074 -0.199 -0.049 -0.074 -0.124 -0.199 -0.149 -0.124 -0.099  0.075  0.000 -0.149  0.050  0.100 -0.099 -0.099 -0.099  0.000 -0.224 -0.249  0.100 -0.249 -0.224  0.025 -0.124 -0.124 -0.124  0.075 -0.149 -0.024 -0.224 -0.274 -0.249  0.075 -0.099 -0.174 -0.124 -0.074 -0.224  0.000 -0.174 -0.149  0.025 -0.074 -0.074 -0.224 -0.124 -0.199 -0.149 -0.099  0.000  0.000 -0.074 -0.174 -0.024 -0.049 -0.149 -0.224 -0.249 -0.199  0.075 -0.174 -0.149 -0.149  0.075  0.075 -0.049  0.000  0.125  0.050 -0.174  0.025  0.175 -0.049  0.025 -0.174 -0.024  0.275  0.349 -0.224  0.424  0.225 -0.024 -0.174 -0.124 -0.124 -0.149 -0.099 -0.199 -0.074 -0.199 -0.099 -0.099 -0.149 -0.124  0.075  0.000  0.075  0.000 
 0.275 -0.074 -0.174 -0.049 -0.099 -0.124 -0.174 -0.149 -0.124 -0.099  0.075  0.000 -0.174  0.050  0.100 -0.099 -0.074 -0.099  0.000 -0.224 -0.249  0.100 -0.249 -0.224  0.050 -0.124 -0.124 -0.149  0.075 -0.149 -0.024 -0.224 -0.298 -0.249  0.075 -0.099 -0.174 -0.149 -0.074 -0.224  0.000 -0.174 -0.124  0.000 -0.049 -0.099 -0.224 -0.149 -0.224 -0.149 -0.099  0.000  0.000 -0.049 -0.199 -0.024 -0.049 -0.149 -0.224 -0.249 -0.199  0.075 -0.174 -0.149 -0.149  0.075  0.075 -0.049 -0.049  0.125  0.050 -0.174  0.025  0.150 -0.074  0.025 -0.174 -0.024  0.275  0.324 -0.224  0.424  0.200  0.000 -0.174 -0.149 -0.124 -0.149 -0.124 -0.199 -0.099 -0.199 -0.099 -0.099 -0.149 -0.124  0.075  0.000  0.050  0.025 
 0.272 -0.077 -0.176 -0.052 -0.102 -0.127 -0.176 -0.151 -0.127 -0.102  0.073  0.023 -0.176  0.048  0.073 -0.127 -0.002 -0.102 -0.002 -0.226 -0.251  0.098 -0.251 -0.226  0.048 -0.127 -0.127 -0.151  0.073 -0.127 -0.027 -0.226 -0.301 -0.251  0.073 -0.102 -0.176 -0.151 -0.077 -0.226 -0.002 -0.176 -0.151  0.023 -0.052 -0.102 -0.226 -0.151 -0.226 -0.127 -0.102 -0.027 -0.002 -0.052 -0.201 -0.027 -0.052 -0.127 -0.226 -0.251 -0.201  0.073 -0.176 -0.151 -0.151  0.073  0.098 -0.027 -0.027  0.123  0.048 -0.176  0.023  0.147 -0.077  0.023 -0.176 -0.027  0.272  0.322 -0.226  0.422  0.172 -0.002 -0.176 -0.127 -0.127 -0.151 -0.127 -0.201 -0.077 -0.201 -0.102 -0.102 -0.151 -0.127  0.073 -0.002  0.048  0.048 
 0.273 -0.076 -0.176 -0.051 -0.076 -0.126 -0.176 -0.151 -0.151 -0.101  0.073  0.048 -0.151  0.048  0.073 -0.126 -0.001 -0.101 -0.001 -0.226 -0.251  0.098 -0.226 -0.251  0.023 -0.126 -0.126 -0.151  0.073 -0.126 -0.026 -0.226 -0.300 -0.251  0.073 -0.101 -0.176 -0.151 -0.076 -0.201 -0.001 -0.176 -0.126  0.023 -0.051 -0.126 -0.226 -0.151 -0.226 -0.126 -0.101 -0.026 -0.001 -0.051 -0.201 -0.026 -0.051 -0.126 -0.226 -0.251 -0.201  0.048 -0.176 -0.151 -0.151  0.073  0.098 -0.026 -0.026  0.123  0.048 -0.176  0.023  0.148 -0.076  0.023 -0.176 -0.026  0.248  0.322 -0.226  0.422  0.173 -0.001 -0.176 -0.126 -0.126 -0.126 -0.101 -0.201 -0.076 -0.201 -0.101 -0.101 -0.151 -0.126  0.073 -0.001  0.048  0.048 
 0.231  0.006 -0.143 -0.043 -0.093 -0.068 -0.168 -0.143 -0.093 -0.068  0.031  0.031 -0.168  0.056  0.056 -0.068 -0.018 -0.068  0.056 -0.168 -0.193  0.031 -0.168 -0.168  0.056 -0.093 -0.068 -0.068  0.081 -0.068  0.056 -0.193 -0.243 -0.168  0.006 -0.018 -0.118 -0.168 -0.068 -0.168 -0.093 -0.093 -0.068  0.006 -0.068 -0.168 -0.218 -0.068 -0.168 -0.068 -0.168  0.006  0.056 -0.018 -0.143 -0.093 -0.093 -0.118 -0.168 -0.168 -0.193 -0.068 -0.118 -0.118 -0.093  0.081  0.031  0.006  0.006  0.106 -0.043 -0.118 -0.018  0.056 -0.093  0.056 -0.143  0.006  0.231  0.256 -0.193  0.430  0.131  0.006 -0.193 -0.118 -0.093 -0.043 -0.043 -0.143 -0.068 -0.193 -0.143 -0.018 -0.093 -0.143  0.031 -0.018  0.031 -0.018 
 0.220 -0.004 -0.104 -0.054 -0.054 -0.004 -0.129 -0.104 -0.079 -0.079 -0.029 -0.029 -0.129 -0.004  0.045 -0.004 -0.029 -0.054  0.095 -0.104 -0.129  0.045 -0.129 -0.079  0.095 -0.054  0.020 -0.029  0.120 -0.054  0.020 -0.129 -0.154 -0.104 -0.004 -0.004 -0.054 -0.129 -0.054 -0.154 -0.004 -0.029 -0.079 -0.004 -0.054 -0.104 -0.154 -0.029 -0.079 -0.004 -0.154 -0.004  0.095 -0.004 -0.054 -0.054 -0.054 -0.104 -0.104 -0.079 -0.104 -0.029 -0.079 -0.054 -0.029  0.020 -0.004  0.020 -0.079 -0.004 -0.054 -0.054 -0.029  0.070 -0.104 -0.054 -0.104 -0.004  0.070  0.294 -0.154  0.319  0.095 -0.029 -0.129 -0.104 -0.029  0.020 -0.004 -0.054 -0.029 -0.104 -0.079  0.020 -0.029 -0.104  0.070 -0.054 -0.004  0.020 
 0.192 -0.007 -0.082 -0.057 -0.032 -0.007 -0.107 -0.082 -0.032 -0.057 -0.057 -0.007 -0.107  0.017 -0.057 -0.007 -0.032 -0.032  0.092 -0.082 -0.132 -0.007 -0.107 -0.107  0.067 -0.032  0.017 -0.007  0.117 -0.032  0.042 -0.107 -0.132 -0.132  0.017  0.042 -0.082 -0.107 -0.082 -0.107 -0.007 -0.007 -0.057  0.017 -0.082 -0.082 -0.132 -0.057 -0.082  0.017 -0.132 -0.032  0.067  0.017 -0.032 -0.032 -0.032 -0.082 -0.082 -0.057 -0.082 -0.007 -0.057 -0.032 -0.057 -0.032 -0.007  0.067 -0.132 -0.007 -0.057 -0.032 -0.007  0.067 -0.057 -0.057 -0.082 -0.007 -0.007  0.267 -0.132  0.291  0.117 -0.082 -0.107 -0.107 -0.032  0.017  0.017 -0.082 -0.007 -0.082 -0.057  0.017 -0.057 -0.082  0.067 -0.032  0.017 -0.007 
 0.140  0.015 -0.084 -0.034 -0.009 -0.034 -0.109 -0.084 -0.034 -0.034 -0.034 -0.009 -0.109 -0.009 -0.059 -0.034 -0.034 -0.009  0.065 -0.084 -0.109 -0.009 -0.084 -0.084  0.065 -0.009  0.040  0.015  0.065  0.015 -0.009 -0.084 -0.109 -0.109  0.040  0.015 -0.084 -0.084 -0.084 -0.084 -0.009 -0.009 -0.034  0.015 -0.059 -0.059 -0.109 -0.034 -0.084 -0.009 -0.109 -0.034  0.090 -0.009 -0.009 -0.034 -0.009 -0.084 -0.059 -0.059 -0.059 -0.009 -0.034 -0.009 -0.059 -0.034  0.015  0.090 -0.109 -0.059 -0.034 -0.009  0.015  0.040 -0.034 -0.034 -0.059 -0.034 -0.084  0.215 -0.109  0.289  0.090 -0.059 -0.109 -0.084 -0.009  0.015  0.015 -0.084  0.015 -0.084 -0.034  0.040 -0.034 -0.084  0.040 -0.034 -0.009  0.015 
 0.099  0.024 -0.075 -0.025 -0.000 -0.025 -0.100 -0.075 -0.025 -0.025 -0.025 -0.075 -0.100 -0.000 -0.075 -0.025 -0.025 -0.000  0.024 -0.075 -0.100 -0.000 -0.075 -0.075  0.074 -0.000  0.024  0.024  0.049  0.024 -0.025 -0.075 -0.100 -0.100  0.049 -0.000 -0.075 -0.100 -0.075 -0.075 -0.025 -0.000 -0.025 -0.025 -0.050 -0.050 -0.100 -0.025 -0.075 -0.000 -0.100 -0.025  0.099 -0.000 -0.000 -0.025 -0.025 -0.075 -0.050 -0.075 -0.050 -0.000 -0.025 -0.050 -0.075 -0.025  0.024  0.074 -0.100 -0.050 -0.025 -0.000 -0.000  0.024 -0.025 -0.025 -0.050 -0.050 -0.075  0.199 -0.100  0.298  0.074 -0.050 -0.075 -0.075 -0.000  0.024  0.024 -0.075  0.024 -0.075 -0.050  0.049 -0.025 -0.075  0.049 -0.000 -0.000  0.024 
 0.115  0.040 -0.060 -0.010 -0.010 -0.010 -0.085 -0.060 -0.035 -0.010 -0.035 -0.060 -0.085 -0.060 -0.085 -0.035 -0.035 -0.010  0.040 -0.060 -0.085  0.015 -0.085 -0.060  0.090  0.015  0.015  0.040  0.065  0.040 -0.035 -0.060 -0.085 -0.085  0.040 -0.010 -0.060 -0.085 -0.060 -0.035 -0.010 -0.010 -0.010 -0.010 -0.085 -0.060 -0.085 -0.035 -0.060  0.015 -0.085 -0.010  0.065 -0.035 -0.010 -0.035 -0.010 -0.060 -0.035 -0.085 -0.035 -0.010 -0.010 -0.035 -0.060 -0.010  0.015  0.065 -0.060 -0.035  0.015  0.015  0.040 -0.035 -0.010 -0.035 -0.035 -0.035 -0.060  0.140 -0.085  0.264  0.090 -0.035 -0.060 -0.060  0.015  0.040  0.015 -0.060 -0.010 -0.085 -0.060  0.065 -0.010 -0.060  0.040 -0.035  0.015  0.015 
 0.068  0.043 -0.056 -0.006 -0.031  0.018 -0.081 -0.031 -0.031 -0.006 -0.031 -0.031 -0.081 -0.056 -0.081 -0.031 -0.031  0.018 -0.031 -0.056 -0.081  0.043 -0.081 -0.056  0.093  0.018  0.018  0.043  0.068  0.018 -0.031 -0.056 -0.081 -0.081  0.043 -0.006 -0.056 -0.081 -0.031 -0.031  0.018 -0.006 -0.031 -0.031 -0.081 -0.056 -0.081 -0.031 -0.056 -0.006 -0.081 -0.056  0.018 -0.031 -0.006 -0.056 -0.006 -0.056 -0.031 -0.081 -0.031 -0.031 -0.006 -0.031 -0.056 -0.006  0.018  0.068 -0.056 -0.031 -0.006  0.018  0.043 -0.031 -0.006 -0.031 -0.031 -0.031 -0.056  0.143 -0.081  0.243  0.093 -0.031 -0.056 -0.056  0.018 -0.031 -0.006 -0.081 -0.006 -0.081 -0.056  0.018 -0.006 -0.081  0.018 -0.006  0.018  0.018 
 0.077  0.027 -0.073  0.002 -0.023  0.027 -0.073 -0.023 -0.048  0.002 -0.048 -0.023 -0.073 -0.048 -0.073 -0.048 -0.023  0.052 -0.023 -0.048 -0.073  0.052 -0.073 -0.073  0.027 -0.023  0.027  0.052  0.077  0.002 -0.048 -0.048 -0.073 -0.073  0.052  0.002 -0.073 -0.048 -0.023 -0.048  0.027  0.002 -0.048  0.002 -0.073 -0.048 -0.073 -0.023 -0.048  0.002 -0.073 -0.048  0.052 -0.023 -0.023 -0.048 -0.023 -0.073 -0.048 -0.073 -0.023 -0.073  0.002 -0.023 -0.048  0.002  0.002  0.052 -0.048  0.002  0.002  0.027  0.027 -0.023  0.027 -0.023 -0.048 -0.023 -0.048  0.102 -0.073  0.176  0.077 -0.023 -0.073 -0.048 -0.048 -0.023  0.002 -0.073  0.002 -0.073 -0.048  0.002 -0.023 -0.073  0.027 -0.023  0.027  0.002 
 0.080  0.030 -0.070  0.005 -0.020  0.005 -0.070 -0.020 -0.045  0.005 -0.045 -0.020 -0.045 -0.070 -0.070 -0.045 -0.020  0.055 -0.020 -0.045 -0.070  0.080 -0.070 -0.070  0.030 -0.020  0.030  0.055  0.080  0.005 -0.045 -0.045 -0.070 -0.070  0.030  0.005 -0.070 -0.045 -0.020 -0.045  0.030  0.005 -0.045  0.005 -0.070 -0.045 -0.070  0.005 -0.045 -0.020 -0.070 -0.045  0.055 -0.045 -0.020 -0.045 -0.020 -0.070 -0.045 -0.070  0.005 -0.070  0.005 -0.020 -0.045 -0.020  0.005  0.055 -0.045  0.005  0.030  0.030  0.030 -0.020  0.030  0.005 -0.045 -0.020 -0.045  0.105 -0.070  0.179  0.080 -0.020 -0.045 -0.045 -0.045  0.005  0.005 -0.070  0.005 -0.070 -0.070  0.030 -0.020 -0.070  0.030 -0.020  0.030  0.005 
 0.064  0.039 -0.061 -0.036 -0.011  0.014 -0.061 -0.011 -0.061  0.014 -0.011 -0.011 -0.036 -0.061 -0.036 -0.036 -0.011  0.039 -0.036 -0.011 -0.061  0.089 -0.061 -0.061  0.039 -0.011  0.014  0.064  0.064 -0.036 -0.036 -0.036 -0.061 -0.061 -0.011 -0.011 -0.061 -0.036 -0.011 -0.011 -0.011  0.014 -0.036  0.014 -0.061 -0.036 -0.061 -0.011 -0.036 -0.036 -0.036 -0.061  0.039 -0.036 -0.011 -0.036 -0.036 -0.061 -0.036 -0.061 -0.011 -0.036  0.014  0.039 -0.036 -0.011  0.014  0.039 -0.036  0.014  0.064 -0.011  0.039  0.014  0.039 -0.011 -0.061  0.014 -0.036  0.064 -0.061  0.114  0.039 -0.011 -0.036 -0.036 -0.036  0.014  0.014 -0.036 -0.036 -0.061 -0.061  0.064 -0.011 -0.061  0.014 -0.011  0.039 -0.036 
 0.070  0.045 -0.054 -0.029 -0.004 -0.004 -0.054 -0.004 -0.054  0.020 -0.004 -0.004 -0.029 -0.054 -0.029 -0.054 -0.004  0.045 -0.029 -0.004 -0.054  0.095 -0.054 -0.054  0.045 -0.004  0.020  0.045  0.070 -0.029 -0.029 -0.029 -0.054 -0.054 -0.004 -0.004 -0.054 -0.029 -0.004 -0.029 -0.004  0.020 -0.029  0.020 -0.054 -0.054 -0.054 -0.004 -0.029 -0.029 -0.029 -0.054  0.045 -0.054 -0.004 -0.029 -0.029 -0.054 -0.029 -0.054 -0.004 -0.029  0.020  0.045 -0.029 -0.004  0.020  0.045 -0.029 -0.004  0.045 -0.004  0.045 -0.004  0.020 -0.004 -0.054 -0.029 -0.029  0.045 -0.054  0.120  0.020 -0.029 -0.029 -0.029 -0.029 -0.004  0.020 -0.029 -0.029 -0.054 -0.054  0.045 -0.004 -0.054  0.020 -0.004  0.045 -0.029 
 0.077  0.027 -0.048 -0.023 -0.023  0.002 -0.048  0.002 -0.048  0.002 -0.023  0.002 -0.023 -0.048 -0.023 -0.048 -0.023  0.052 -0.048  0.002 -0.048  0.052 -0.023 -0.023  0.052  0.002  0.002  0.052  0.077 -0.023 -0.023 -0.023 -0.048 -0.048  0.002  0.027 -0.048 -0.023  0.002  0.002  0.002  0.027 -0.048  0.027 -0.048 -0.048 -0.048 -0.023 -0.023 -0.023  0.002 -0.048  0.027 -0.048  0.002 -0.023 -0.023 -0.048 -0.048 -0.048 -0.023 -0.023  0.027  0.052 -0.023  0.002  0.027  0.027 -0.023  0.002  0.052  0.002  0.002  0.002  0.027  0.002 -0.048 -0.023 -0.048  0.052 -0.048  0.077 -0.023 -0.023 -0.023 -0.023 -0.023  0.002  0.002 -0.023 -0.023 -0.048 -0.023  0.052 -0.023 -0.048  0.002  0.002  0.052 -0.023 
 0.075  0.025 -0.049 -0.024 -0.024  0.025 -0.049  0.000 -0.049  0.000 -0.024  0.000 -0.024 -0.049 -0.024 -0.049 -0.024  0.050  0.000  0.000 -0.049  0.050 -0.024 -0.024  0.050 -0.024  0.000  0.075  0.075 -0.024 -0.049 -0.024 -0.049 -0.049  0.000  0.025 -0.024 -0.024  0.000  0.025  0.000  0.025 -0.049  0.025 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.000 -0.049  0.025 -0.049  0.000 -0.049 -0.024 -0.049 -0.049 -0.049 -0.024 -0.024  0.025  0.050 -0.024  0.000  0.025  0.025 -0.024  0.025  0.050  0.000  0.000  0.000  0.025  0.000 -0.049  0.000 -0.024  0.050 -0.049  0.075 -0.024 -0.024  0.000 -0.024 -0.024  0.025  0.000 -0.024 -0.024 -0.049 -0.024  0.075 -0.024 -0.024 -0.024  0.000  0.050 -0.024 
 0.075  0.025 -0.049 -0.024 -0.024  0.025 -0.049  0.000 -0.049  0.000 -0.024  0.000 -0.024 -0.049 -0.024 -0.049 -0.024  0.050  0.000  0.000 -0.049  0.050 -0.024 -0.024  0.050 -0.024  0.000  0.075  0.075 -0.024 -0.049 -0.024 -0.049 -0.049  0.000  0.000 -0.024 -0.024  0.000  0.025  0.000  0.025 -0.024  0.000 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.000 -0.049  0.025 -0.049  0.000 -0.049 -0.024 -0.049 -0.049 -0.049 -0.024 -0.024  0.025  0.050 -0.024  0.000  0.025  0.025 -0.024  0.025  0.050  0.000  0.000  0.000  0.025  0.000 -0.049  0.000 -0.024  0.050 -0.049  0.050  0.000 -0.024  0.000 -0.024 -0.024  0.025  0.000 -0.024 -0.024 -0.049 -0.024  0.075 -0.024 -0.024 -0.024  0.000  0.050 -0.024 
 0.075  0.025 -0.049 -0.024 -0.024  0.025 -0.049  0.000 -0.049  0.000 -0.024  0.000 -0.024 -0.049 -0.024 -0.049 -0.024  0.050  0.000  0.000 -0.049  0.050 -0.024 -0.024  0.050 -0.024  0.000  0.075  0.075 -0.024 -0.049 -0.024 -0.049 -0.049  0.000  0.000 -0.024 -0.024  0.000  0.025  0.000  0.025 -0.024  0.000 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.000 -0.049  0.025 -0.049  0.000 -0.049 -0.024 -0.049 -0.049 -0.049 -0.024 -0.024  0.025  0.050 -0.024  0.000  0.025  0.025 -0.024  0.025  0.050  0.000  0.000  0.000  0.025  0.000 -0.049  0.000 -0.024  0.050 -0.049  0.050  0.000 -0.024  0.000 -0.024 -0.024  0.025  0.000 -0.024 -0.024 -0.049 -0.024  0.075 -0.024 -0.024 -0.024  0.000  0.050 -0.024 
 0.076  0.026 -0.049 -0.024 -0.024  0.026 -0.049  0.001 -0.049  0.001 -0.024  0.001 -0.024 -0.049 -0.024 -0.049 -0.024  0.051  0.001  0.001 -0.049  0.051 -0.024 -0.024  0.051 -0.024  0.001  0.076  0.076 -0.024 -0.049 -0.024 -0.049 -0.049  0.001  0.001 -0.024 -0.024  0.001  0.026  0.001  0.026 -0.024  0.001 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.001 -0.049  0.026 -0.049  0.001 -0.049 -0.024 -0.049 -0.049 -0.049 -0.024 -0.024  0.026  0.051 -0.024  0.001  0.026  0.026 -0.024  0.026  0.051  0.001  0.001  0.001  0.026  0.001 -0.049  0.001 -0.024  0.051 -0.049  0.051  0.001 -0.024  0.001 -0.024 -0.024  0.026  0.001 -0.024 -0.024 -0.049 -0.024  0.076 -0.024 -0.024 -0.024  0.001  0.051 -0.024 
 0.076  0.026 -0.049 -0.024 -0.024  0.026 -0.049  0.001 -0.049  0.001 -0.024  0.001 -0.024 -0.049 -0.024 -0.049 -0.024  0.051  0.001  0.001 -0.049  0.051 -0.024 -0.024  0.051 -0.024  0.001  0.076  0.076 -0.024 -0.049 -0.024 -0.049 -0.049  0.001  0.001 -0.024 -0.024  0.001  0.026  0.001  0.026 -0.024  0.001 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.001 -0.049  0.026 -0.049  0.001 -0.049 -0.024 -0.049 -0.049 -0.049 -0.024 -0.024  0.026  0.051 -0.024  0.001  0.026  0.026 -0.024  0.026  0.051  0.001  0.001  0.001  0.026  0.001 -0.049  0.001 -0.024  0.051 -0.049  0.051  0.001 -0.024  0.001 -0.024 -0.024  0.026  0.001 -0.024 -0.024 -0.049 -0.024  0.076 -0.024 -0.024 -0.024  0.001  0.051 -0.024 
 0.076  0.026 -0.049 -0.024 -0.024  0.026 -0.049  0.001 -0.049  0.001 -0.024  0.001 -0.024 -0.049 -0.024 -0.049 -0.024  0.051  0.001  0.001 -0.049  0.051 -0.024 -0.024  0.051 -0.024  0.001  0.076  0.076 -0.024 -0.049 -0.024 -0.049 -0.049  0.001  0.001 -0.024 -0.024  0.001  0.026  0.001  0.026 -0.024  0.001 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.001 -0.049  0.026 -0.049  0.001 -0.049 -0.024 -0.049 -0.049 -0.049 -0.024 -0.024  0.026  0.051 -0.024  0.001  0.026  0.026 -0.024  0.026  0.051  0.001  0.001  0.001  0.026  0.001 -0.049  0.001 -0.024  0.051 -0.049  0.051  0.001 -0.024  0.001 -0.024 -0.024  0.026  0.001 -0.024 -0.024 -0.049 -0.024  0.076 -0.024 -0.024 -0.024  0.001  0.051 -0.024 
 0.075  0.025 -0.049 -0.024 -0.024  0.025 -0.049  0.000 -0.049  0.000 -0.024  0.000 -0.024 -0.049 -0.024 -0.049 -0.024  0.050  0.000  0.000 -0.049  0.050 -0.024 -0.024  0.050 -0.024  0.000  0.075  0.075 -0.024 -0.049 -0.024 -0.049 -0.049  0.000  0.000 -0.024 -0.024  0.000  0.025  0.000  0.025 -0.024  0.000 -0.049 -0.024 -0.049 -0.024 -0.024 -0.024  0.000 -0.049  0.025 -0.049  0.000 -0.049 -0.024 -0.049 -0.049 -0.049 -0.024 -0.024  0.025  0.050 -0.024  0.000  0.025  0.025 -0.024  0.025  0.050  0.000  0.000  0.000  0.025  0.000 -0.049  0.000 -0.024  0.050 -0.049  0.050  0.000 -0.024  0.000 -0.024 -0.024  0.025  0.000 -0.024 -0.024 -0.049 -0.024  0.075 -0.024 -0.024 -0.024  0.000  0.050 -0.024 
 0.074  0.024 -0.050 -0.025 -0.025  0.024 -0.050 -0.000 -0.050 -0.000 -0.025 -0.000 -0.025 -0.050 -0.025 -0.050 -0.025  0.049 -0.000 -0.000 -0.050  0.049 -0.025 -0.025  0.049 -0.025 -0.000  0.074  0.074 -0.025 -0.050 -0.025 -0.050 -0.050 -0.000 -0.000 -0.025 -0.025 -0.000  0.024 -0.000  0.024 -0.025 -0.000 -0.050 -0.025 -0.050 -0.025 -0.025 -0.025 -0.000 -0.050  0.024 -0.050 -0.000 -0.050 -0.025 -0.050 -0.050 -0.050 -0.025 -0.025  0.024  0.049 -0.025 -0.000  0.024  0.024 -0.025  0.024  0.049 -0.000 -0.000 -0.000  0.024 -0.000 -0.050 -0.000 -0.025  0.074 -0.050  0.049  0.024 -0.025 -0.000 -0.025 -0.025  0.024 -0.000 -0.025 -0.025 -0.050 -0.025  0.074 -0.025 -0.025 -0.025 -0.000  0.049 -0.025 
 0.121  0.021 -0.053 -0.028 -0.053 -0.003 -0.078 -0.003 -0.078 -0.003 -0.028 -0.003  0.021 -0.078 -0.053 -0.078 -0.003  0.071 -0.003 -0.028 -0.078  0.021 -0.028 -0.053  0.071 -0.053  0.021  0.146  0.046 -0.053 -0.053 -0.003 -0.053 -0.078  0.046  0.021 -0.053 -0.028  0.021 -0.003  0.021 -0.003 -0.053  0.021 -0.028 -0.028 -0.053 -0.053 -0.053 -0.003 -0.003 -0.053  0.046 -0.078 -0.003 -0.078 -0.053 -0.078 -0.053 -0.078 -0.053 -0.003  0.021  0.046 -0.028 -0.003  0.046  0.046 -0.003 -0.003  0.071  0.021 -0.028 -0.003  0.021  0.021 -0.078 -0.028  0.046  0.071 -0.053  0.121  0.071 -0.053  0.021 -0.053 -0.053  0.021 -0.028 -0.053 -0.053 -0.078 -0.003  0.121 -0.028 -0.003 -0.028 -0.003  0.096 -0.028 
 0.103  0.028 -0.097 -0.072 -0.097 -0.047 -0.122 -0.047 -0.097 -0.072 -0.022 -0.072 -0.047 -0.097 -0.122 -0.072 -0.047  0.053  0.053 -0.097 -0.146  0.028 -0.072 -0.047  0.103 -0.047 -0.022  0.103  0.078 -0.047 -0.072 -0.047 -0.122 -0.146 -0.022  0.028 -0.047 -0.072 -0.022  0.028  0.028 -0.022 -0.047  0.003 -0.072 -0.022 -0.097 -0.122 -0.122 -0.022 -0.047  0.078  0.078 -0.146 -0.072 -0.097 -0.097 -0.072 -0.072 -0.122 -0.097 -0.047  0.053  0.003 -0.022  0.003  0.078  0.028 -0.072  0.003  0.103  0.028  0.053 -0.022 -0.047  0.103 -0.122 -0.047  0.053  0.177 -0.122  0.302  0.128 -0.072 -0.022 -0.122 -0.047  0.028 -0.047 -0.097 -0.047 -0.072 -0.072  0.128 -0.047 -0.022 -0.072 -0.022  0.128  0.003 
 0.137  0.037 -0.113 -0.038 -0.113 -0.063 -0.187 -0.063 -0.038 -0.063  0.012 -0.038 -0.063 -0.113 -0.113 -0.088 -0.063  0.037  0.087 -0.138 -0.162  0.062 -0.138 -0.088  0.087 -0.088  0.012  0.087  0.112 -0.063 -0.063 -0.088 -0.162 -0.187  0.037  0.012 -0.063 -0.113 -0.038  0.012  0.012 -0.063 -0.063  0.037 -0.088 -0.038 -0.038 -0.138 -0.162 -0.063 -0.088  0.112  0.137 -0.187 -0.088 -0.113 -0.088 -0.113 -0.113 -0.138 -0.113 -0.013  0.012 -0.013 -0.038  0.037  0.186 -0.038  0.012  0.012  0.062  0.012  0.037 -0.038 -0.063  0.112 -0.138  0.012  0.112  0.211 -0.162  0.336  0.137 -0.088 -0.063 -0.138 -0.063  0.037 -0.038 -0.138 -0.038 -0.113 -0.063  0.087 -0.088 -0.063 -0.063  0.012  0.137 -0.013 
 0.246  0.022 -0.177 -0.028 -0.028 -0.103 -0.202 -0.103 -0.078 -0.128 -0.003 -0.078 -0.053 -0.053 -0.053 -0.152 -0.103 -0.028  0.047 -0.202 -0.202  0.122 -0.152 -0.152  0.097 -0.103 -0.028 -0.003  0.097 -0.078 -0.053 -0.128 -0.202 -0.252  0.122  0.022 -0.128 -0.152 -0.152 -0.078 -0.028 -0.128 -0.103  0.022 -0.078 -0.053 -0.053 -0.103 -0.152 -0.103 -0.128  0.122  0.097 -0.103 -0.103 -0.152 -0.003 -0.103 -0.177 -0.177 -0.152  0.047 -0.078 -0.103 -0.078 -0.003  0.146 -0.003  0.122 -0.003  0.171 -0.028 -0.003 -0.078 -0.078  0.072 -0.152  0.022  0.171  0.296 -0.252  0.371  0.196 -0.103 -0.103 -0.078 -0.078 -0.053 -0.028 -0.152 -0.053 -0.152 -0.078  0.022 -0.078 -0.128 -0.053  0.097  0.072 -0.053 
 0.250  0.000 -0.174  0.000 -0.024 -0.149 -0.199 -0.099 -0.074 -0.124 -0.024 -0.074 -0.074 -0.024  0.025 -0.174 -0.099 -0.074  0.025 -0.224 -0.224  0.100 -0.149 -0.174  0.100 -0.124 -0.049 -0.024  0.100 -0.099 -0.074 -0.149 -0.174 -0.274  0.100  0.000 -0.124 -0.149 -0.174 -0.099 -0.024 -0.149 -0.124  0.000 -0.074 -0.074 -0.099 -0.099 -0.174 -0.074 -0.124  0.125  0.075 -0.049 -0.099 -0.124 -0.024 -0.074 -0.174 -0.199 -0.199  0.050 -0.124 -0.099 -0.099 -0.024  0.125  0.000  0.150  0.025  0.200 -0.049  0.025 -0.074 -0.099  0.025 -0.149  0.000  0.175  0.349 -0.274  0.374  0.175 -0.099 -0.149 -0.099 -0.099 -0.099 -0.024 -0.174 -0.074 -0.174 -0.049  0.000 -0.099 -0.149 -0.074  0.125  0.050 -0.024 
 0.257 -0.042 -0.216 -0.017  0.033 -0.166 -0.216 -0.092 -0.067 -0.117 -0.042 -0.092 -0.117  0.008  0.058 -0.166 -0.117 -0.092  0.008 -0.266 -0.191  0.083 -0.191 -0.191  0.083 -0.117 -0.092 -0.067  0.133 -0.142 -0.042 -0.092 -0.166 -0.266  0.058 -0.017 -0.142 -0.166 -0.166 -0.117 -0.017 -0.166 -0.142  0.033 -0.092 -0.092 -0.092 -0.117 -0.216 -0.067 -0.166  0.108  0.058 -0.067 -0.092 -0.117  0.008 -0.042 -0.191 -0.191 -0.241  0.058 -0.142 -0.092 -0.117 -0.017  0.108  0.008  0.133  0.083  0.207 -0.067 -0.017 -0.067 -0.067  0.033 -0.142  0.108  0.182  0.307 -0.291  0.407  0.207 -0.142 -0.142 -0.117 -0.117 -0.117 -0.042 -0.166 -0.067 -0.142 -0.067 -0.017 -0.117 -0.166 -0.042  0.108  0.033  0.008 
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 0.222 -0.027 -0.226 -0.002  0.023 -0.176 -0.226 -0.077 -0.077 -0.102 -0.027 -0.052 -0.127 -0.002  0.098 -0.151 -0.102 -0.102  0.023 -0.226 -0.226  0.098 -0.201 -0.176  0.048 -0.077 -0.077 -0.102  0.123 -0.127 -0.002 -0.151 -0.176 -0.301  0.073 -0.052 -0.151 -0.176 -0.176 -0.201 -0.027 -0.201 -0.151  0.048 -0.102 -0.102 -0.102 -0.151 -0.226 -0.102 -0.102  0.048  0.073 -0.077 -0.102 -0.102 -0.002 -0.052 -0.201 -0.226 -0.251  0.048 -0.151 -0.102 -0.127 -0.027  0.098 -0.027  0.123  0.123  0.197 -0.102  0.023 -0.052 -0.077  0.023 -0.151  0.048  0.172  0.297 -0.301  0.397  0.197 -0.151 -0.151 -0.102 -0.127 -0.127 -0.052 -0.176 -0.077 -0.201 -0.052 -0.077 -0.127 -0.151 -0.052  0.098  0.048  0.048 
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 0.279 -0.045 -0.219  0.030 -0.045 -0.144 -0.244 -0.144 -0.045 -0.095  0.154  0.005 -0.194  0.005  0.130 -0.120 -0.095 -0.095  0.030 -0.219 -0.244  0.154 -0.244 -0.244  0.055 -0.095 -0.120 -0.144  0.154 -0.120 -0.020 -0.219 -0.269 -0.219  0.130 -0.045 -0.169 -0.169 -0.144 -0.219  0.005 -0.169 -0.144  0.055 -0.095 -0.095 -0.144 -0.144 -0.219 -0.120 -0.120  0.030  0.105 -0.045 -0.194 -0.095  0.030 -0.144 -0.219 -0.244 -0.194  0.030 -0.120 -0.144 -0.144  0.055  0.105 -0.045  0.080  0.130  0.105 -0.169  0.030  0.130 -0.070  0.005 -0.169  0.055  0.279  0.304 -0.244  0.428  0.179 -0.095 -0.169 -0.169 -0.095 -0.144 -0.120 -0.194 -0.095 -0.219 -0.045 -0.095 -0.144 -0.144  0.030  0.055  0.030  0.080 
 0.277 -0.047 -0.221  0.028 -0.072 -0.146 -0.196 -0.146 -0.047 -0.097  0.152  0.003 -0.171  0.003  0.128 -0.122 -0.097 -0.097  0.028 -0.221 -0.246  0.152 -0.246 -0.246  0.053 -0.097 -0.122 -0.146  0.152 -0.122 -0.022 -0.221 -0.271 -0.221  0.128 -0.047 -0.171 -0.146 -0.122 -0.221 -0.022 -0.171 -0.122  0.053 -0.097 -0.097 -0.171 -0.146 -0.221 -0.122 -0.122  0.028  0.128 -0.022 -0.196 -0.097  0.003 -0.146 -0.221 -0.246 -0.221  0.028 -0.122 -0.146 -0.146  0.028  0.078 -0.047  0.003  0.128  0.053 -0.171  0.028  0.128 -0.072 -0.022 -0.171  0.028  0.277  0.302 -0.221  0.426  0.177 -0.072 -0.196 -0.171 -0.122 -0.146 -0.122 -0.196 -0.097 -0.196 -0.047 -0.097 -0.171 -0.146  0.028  0.028 -0.022  0.078 
 0.277 -0.047 -0.222  0.002 -0.072 -0.147 -0.197 -0.147 -0.072 -0.097  0.202  0.027 -0.222  0.002  0.127 -0.122 -0.097 -0.097  0.027 -0.222 -0.247  0.152 -0.247 -0.247  0.052 -0.097 -0.122 -0.147  0.152 -0.122 -0.022 -0.222 -0.272 -0.222  0.127 -0.047 -0.172 -0.147 -0.122 -0.222 -0.022 -0.172 -0.122  0.052 -0.097 -0.097 -0.172 -0.147 -0.222 -0.122 -0.122  0.027  0.127 -0.047 -0.197 -0.097  0.027 -0.147 -0.222 -0.247 -0.222  0.027 -0.122 -0.147 -0.147  0.027  0.077 -0.047 -0.022  0.102  0.052 -0.172  0.052  0.127 -0.072 -0.022 -0.172  0.052  0.277  0.301 -0.222  0.426  0.127 -0.072 -0.197 -0.172 -0.122 -0.122 -0.097 -0.172 -0.097 -0.197 -0.047 -0.097 -0.172 -0.147  0.027  0.027 -0.047  0.077 
 0.271 -0.053 -0.203 -0.003 -0.078 -0.103 -0.178 -0.153 -0.078 -0.103  0.221  0.021 -0.228 -0.003  0.146 -0.103 -0.103 -0.103  0.021 -0.228 -0.253  0.146 -0.253 -0.253  0.071 -0.103 -0.128 -0.128  0.171 -0.128 -0.028 -0.228 -0.302 -0.203  0.121 -0.078 -0.178 -0.153 -0.103 -0.228 -0.028 -0.178 -0.128  0.046 -0.103 -0.103 -0.178 -0.153 -0.228 -0.128 -0.103  0.021  0.121 -0.078 -0.203 -0.103  0.021 -0.178 -0.228 -0.253 -0.228  0.021 -0.128 -0.153 -0.153  0.046  0.071 -0.053 -0.053  0.096  0.046 -0.178  0.046  0.121 -0.078 -0.028 -0.178  0.046  0.271  0.295 -0.228  0.420  0.146 -0.028 -0.203 -0.153 -0.128 -0.128 -0.078 -0.178 -0.103 -0.203 -0.078 -0.103 -0.153 -0.128  0.096 -0.003 -0.053  0.046 
 0.245 -0.054 -0.203 -0.004 -0.079 -0.129 -0.153 -0.153 -0.079 -0.104  0.195  0.021 -0.228 -0.029  0.145 -0.104 -0.104 -0.104  0.021 -0.228 -0.253  0.145 -0.253 -0.253  0.071 -0.104 -0.129 -0.129  0.170 -0.129 -0.029 -0.228 -0.303 -0.203  0.121 -0.054 -0.178 -0.153 -0.104 -0.228 -0.004 -0.178 -0.129  0.046 -0.104 -0.104 -0.178 -0.153 -0.228 -0.129 -0.104  0.021  0.121 -0.054 -0.203 -0.079  0.046 -0.178 -0.228 -0.253 -0.228  0.021 -0.129 -0.153 -0.153  0.046  0.046 -0.054 -0.054  0.096  0.046 -0.178  0.046  0.121 -0.079 -0.029 -0.178  0.046  0.270  0.295 -0.228  0.420  0.096 -0.029 -0.203 -0.153 -0.129 -0.129 -0.079 -0.178 -0.104 -0.203 -0.079 -0.104 -0.153 -0.129  0.096 -0.004 -0.054  0.046 
 0.248 -0.051 -0.200 -0.001 -0.076 -0.126 -0.150 -0.150 -0.076 -0.101  0.198  0.024 -0.250 -0.026  0.148 -0.101 -0.101 -0.101  0.024 -0.225 -0.250  0.148 -0.250 -0.250  0.074 -0.101 -0.126 -0.126  0.173 -0.126 -0.026 -0.250 -0.300 -0.200  0.099 -0.026 -0.175 -0.150 -0.101 -0.225 -0.001 -0.175 -0.126  0.049 -0.101 -0.076 -0.200 -0.150 -0.225 -0.126 -0.101  0.024  0.124 -0.026 -0.200 -0.076 -0.001 -0.175 -0.225 -0.250 -0.225 -0.001 -0.126 -0.150 -0.150  0.024  0.024 -0.051 -0.051  0.099  0.049 -0.175  0.049  0.124 -0.076 -0.026 -0.175  0.024  0.273  0.298 -0.225  0.423  0.074 -0.026 -0.200 -0.150 -0.126 -0.126 -0.076 -0.175 -0.101 -0.200 -0.076 -0.101 -0.150 -0.126  0.099 -0.001 -0.051  0.049 
 0.270 -0.079 -0.154 -0.054 -0.004 -0.079 -0.104 -0.104 -0.054 -0.104  0.095  0.045 -0.179 -0.029  0.070 -0.054 -0.054 -0.079  0.070 -0.179 -0.179  0.195 -0.204 -0.179  0.095 -0.029 -0.079 -0.079  0.095 -0.129 -0.004 -0.204 -0.229 -0.154  0.095  0.020 -0.179 -0.079 -0.104 -0.254 -0.029 -0.129 -0.154 -0.004 -0.129 -0.129 -0.179 -0.104 -0.154 -0.054 -0.104 -0.004  0.145 -0.054 -0.129 -0.054 -0.004 -0.104 -0.179 -0.179 -0.154  0.020 -0.154 -0.079 -0.079  0.020  0.045 -0.054 -0.079 -0.004 -0.004 -0.104 -0.079  0.020 -0.029 -0.004 -0.154  0.020  0.145  0.245 -0.204  0.394  0.120  0.020 -0.179 -0.129 -0.079 -0.079 -0.054 -0.104 -0.054 -0.154 -0.129 -0.054 -0.129 -0.154  0.045 -0.079 -0.054  0.070 
 0.161 -0.038 -0.113 -0.063 -0.038 -0.013 -0.138 -0.088 -0.063 -0.088 -0.038  0.037 -0.138 -0.013  0.087  0.012 -0.013 -0.038  0.062 -0.113 -0.138  0.062 -0.138 -0.113  0.137 -0.038  0.012 -0.038  0.087 -0.038  0.062 -0.138 -0.162 -0.088  0.037  0.012 -0.113 -0.113 -0.063 -0.162 -0.013 -0.063 -0.088 -0.013 -0.088 -0.088 -0.138 -0.038 -0.088  0.012 -0.138 -0.038  0.112  0.012 -0.038 -0.063 -0.013 -0.088 -0.113 -0.088 -0.113 -0.038 -0.113 -0.063 -0.113 -0.013  0.012 -0.013 -0.063  0.012 -0.038 -0.063 -0.038  0.012 -0.013 -0.038 -0.113  0.012  0.012  0.286 -0.162  0.361  0.062  0.037 -0.138 -0.113 -0.013  0.012 -0.013 -0.088 -0.013 -0.113 -0.088  0.037 -0.063 -0.088  0.037 -0.088 -0.038  0.012 
 0.158 -0.041 -0.091 -0.066 -0.041 -0.041 -0.116 -0.066 -0.041 -0.066 -0.041  0.008 -0.116 -0.016  0.083 -0.016 -0.016 -0.016  0.083 -0.116 -0.116  0.058 -0.116 -0.116  0.083 -0.016  0.008 -0.016  0.108 -0.016  0.058 -0.116 -0.141 -0.141  0.033 -0.016 -0.091 -0.091 -0.066 -0.116 -0.016 -0.041 -0.066  0.008 -0.066 -0.066 -0.116 -0.016 -0.091  0.033 -0.116 -0.016  0.108  0.033 -0.041 -0.066  0.008 -0.066 -0.091 -0.066 -0.091 -0.041 -0.091 -0.041 -0.091 -0.016  0.033  0.033 -0.066  0.033 -0.066 -0.041 -0.016  0.008 -0.016 -0.066 -0.091 -0.041  0.008  0.307 -0.141  0.332  0.058 -0.016 -0.141 -0.116 -0.016  0.033  0.008 -0.091  0.008 -0.116 -0.066  0.058 -0.066 -0.066  0.008 -0.091 -0.016  0.058 
 0.134  0.009 -0.065 -0.065 -0.015 -0.015 -0.090 -0.040 -0.040 -0.040 -0.015 -0.015 -0.090 -0.040 -0.015 -0.015 -0.015  0.034  0.109 -0.090 -0.115  0.009 -0.115 -0.090  0.084 -0.015  0.034  0.009  0.109  0.009 -0.015 -0.090 -0.115 -0.115  0.034 -0.015 -0.065 -0.065 -0.040 -0.065 -0.015  0.009 -0.040  0.034 -0.040 -0.065 -0.090 -0.015 -0.090  0.009 -0.115 -0.015  0.134  0.009 -0.015 -0.040 -0.040 -0.065 -0.065 -0.040 -0.065 -0.015 -0.040 -0.015 -0.065 -0.040  0.009  0.059 -0.065  0.009 -0.015 -0.015  0.009  0.009  0.009 -0.040 -0.065 -0.040 -0.090  0.259 -0.115  0.333  0.059 -0.065 -0.115 -0.090 -0.015  0.009 -0.015 -0.065  0.009 -0.090 -0.065  0.034 -0.040 -0.065  0.034 -0.090 -0.015 -0.015 
 0.096  0.021 -0.054 -0.054 -0.004 -0.004 -0.079 -0.029 -0.029 -0.029 -0.004 -0.054 -0.079 -0.054 -0.029 -0.004 -0.029  0.046  0.096 -0.079 -0.104 -0.004 -0.104 -0.079  0.096 -0.004  0.021  0.021  0.071  0.021 -0.004 -0.079 -0.104 -0.104  0.046 -0.029 -0.054 -0.054 -0.054 -0.054 -0.004 -0.004 -0.029  0.021 -0.029 -0.054 -0.079 -0.054 -0.079  0.021 -0.104 -0.054  0.096 -0.029 -0.004 -0.079 -0.029 -0.054 -0.054 -0.029 -0.054 -0.004 -0.029 -0.029 -0.054 -0.029  0.021  0.046 -0.079 -0.029 -0.004 -0.004  0.021 -0.004  0.021 -0.029 -0.054 -0.054 -0.079  0.195 -0.104  0.345  0.046 -0.054 -0.104 -0.079 -0.004  0.021 -0.004 -0.079  0.021 -0.104 -0.054  0.046 -0.029 -0.054  0.046 -0.079 -0.004 -0.004 
 0.088  0.038 -0.061 -0.036 -0.036 -0.011 -0.086 -0.061 -0.061 -0.011 -0.036 -0.036 -0.086 -0.036 -0.086 -0.036 -0.011  0.088  0.063 -0.061 -0.086  0.013 -0.086 -0.061  0.088  0.013  0.013  0.038  0.088 -0.036 -0.036 -0.061 -0.086 -0.086  0.063 -0.011 -0.061 -0.061 -0.036 -0.061  0.038 -0.011 -0.011  0.038 -0.061 -0.061 -0.086 -0.061 -0.061  0.013 -0.086 -0.086  0.063 -0.036 -0.011 -0.061 -0.036 -0.086 -0.036 -0.061 -0.036  0.038 -0.011 -0.011 -0.036 -0.036  0.038  0.038 -0.061 -0.011  0.013  0.013  0.063  0.013  0.038 -0.036 -0.036 -0.036 -0.061  0.163 -0.086  0.287  0.038 -0.036 -0.086 -0.061  0.013 -0.011  0.013 -0.036 -0.011 -0.061 -0.061  0.063 -0.011 -0.061  0.013 -0.061  0.013 -0.011 
 0.071  0.046 -0.079 -0.054 -0.029  0.021 -0.079 -0.029 -0.054 -0.004 -0.029 -0.029 -0.079 -0.079 -0.079 -0.029 -0.029  0.046  0.071 -0.054 -0.079  0.046 -0.079 -0.054  0.096  0.021 -0.004  0.046  0.096 -0.029 -0.029 -0.054 -0.079 -0.079  0.071  0.021 -0.054 -0.054 -0.029 -0.054  0.021 -0.004 -0.004  0.021 -0.054 -0.054 -0.079 -0.054 -0.054 -0.004 -0.079 -0.079  0.071 -0.054 -0.004 -0.054 -0.054 -0.079 -0.029 -0.054 -0.029 -0.004 -0.004 -0.004 -0.029 -0.004  0.046  0.046 -0.054 -0.004  0.021  0.021  0.071 -0.029  0.046 -0.029 -0.029 -0.029 -0.054  0.145 -0.079  0.245  0.046 -0.029 -0.079 -0.054  0.021 -0.004 -0.004 -0.029 -0.004 -0.079 -0.054  0.021 -0.004 -0.054 -0.004 -0.029  0.021 -0.004 
 0.081  0.056 -0.069 -0.044 -0.019  0.031 -0.069 -0.019 -0.044  0.006 -0.019 -0.019 -0.069 -0.069 -0.069 -0.044 -0.019  0.031  0.056 -0.044 -0.069  0.056 -0.069 -0.069  0.081  0.006  0.006  0.056  0.081 -0.019 -0.044 -0.044 -0.069 -0.069  0.031  0.031 -0.044 -0.044 -0.019 -0.044  0.006  0.006  0.031  0.006 -0.069 -0.044 -0.069 -0.044 -0.044 -0.044 -0.069 -0.069  0.081 -0.069 -0.019 -0.044 -0.044 -0.069 -0.019 -0.069 -0.019 -0.044  0.006  0.006 -0.044 -0.019  0.056  0.056 -0.044  0.006  0.056  0.006  0.031 -0.019  0.056 -0.019 -0.044 -0.019 -0.044  0.106 -0.069  0.230  0.081 -0.019 -0.069 -0.044  0.006  0.006  0.006 -0.044 -0.019 -0.069 -0.069  0.031 -0.019 -0.044  0.006 -0.019  0.031  0.006 
 0.085  0.035 -0.065 -0.040 -0.015  0.010 -0.065 -0.015 -0.065  0.010 -0.015 -0.015 -0.065 -0.065 -0.065 -0.040 -0.015  0.035  0.035 -0.015 -0.065  0.035 -0.040 -0.040  0.060 -0.015  0.010  0.060  0.085 -0.015 -0.040 -0.040 -0.065 -0.065  0.035  0.035 -0.015 -0.040 -0.015 -0.040  0.010  0.010  0.010  0.010 -0.065 -0.040 -0.065 -0.040 -0.040 -0.040 -0.015 -0.065  0.060 -0.065 -0.015 -0.040 -0.040 -0.065 -0.015 -0.065 -0.015 -0.040  0.035  0.010 -0.040 -0.015  0.035  0.035 -0.040  0.035  0.035  0.010  0.035  0.010  0.060 -0.015 -0.040 -0.015 -0.015  0.135 -0.065  0.234  0.060 -0.015 -0.040 -0.040 -0.015 -0.015  0.010 -0.040 -0.015 -0.065 -0.065  0.035 -0.015 -0.040  0.010 -0.015  0.035 -0.015 
 0.070  0.020 -0.054 -0.029 -0.029 -0.004 -0.054 -0.004 -0.054  0.020 -0.029 -0.004 -0.029 -0.054 -0.029 -0.029 -0.029  0.045 -0.004 -0.004 -0.054  0.070 -0.029 -0.029  0.045 -0.004 -0.004  0.045  0.070 -0.029 -0.054 -0.029 -0.054 -0.054  0.020 -0.004 -0.029 -0.029 -0.004 -0.029 -0.004  0.020 -0.004 -0.004 -0.054 -0.029 -0.054 -0.004 -0.029 -0.029 -0.004 -0.054  0.045 -0.054 -0.004 -0.029 -0.029 -0.054 -0.054 -0.054 -0.004 -0.029  0.020  0.045 -0.029 -0.004  0.020  0.020 -0.029  0.045  0.045 -0.004  0.020 -0.004  0.045  0.020 -0.054 -0.029 -0.029  0.095 -0.054  0.070  0.020 -0.029 -0.004 -0.029 -0.029  0.020  0.020 -0.029 -0.029 -0.054 -0.054  0.045 -0.029 -0.029  0.020 -0.004  0.045 -0.004 
 0.072  0.022 -0.053 -0.028 -0.028 -0.003 -0.053 -0.003 -0.053  0.022 -0.028 -0.003 -0.028 -0.053 -0.028 -0.028 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.003 -0.003  0.047  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003 -0.003 -0.003  0.022 -0.028 -0.003 -0.053 -0.028 -0.053 -0.028 -0.028 -0.028 -0.003 -0.053  0.047 -0.053 -0.003 -0.028 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022  0.022 -0.028  0.047  0.047 -0.003  0.022 -0.003  0.022 -0.003 -0.053 -0.028 -0.028  0.072 -0.053  0.072  0.022 -0.028 -0.003 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.028  0.047 -0.028 -0.028 -0.003 -0.003  0.047 -0.028 
 0.073  0.023 -0.051 -0.026 -0.026  0.023 -0.051 -0.001 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026 -0.001 -0.051 -0.026 -0.051 -0.026 -0.026 -0.026 -0.001 -0.051  0.023 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.023  0.048 -0.026 -0.001  0.023  0.023 -0.026  0.023  0.048 -0.001  0.023 -0.001  0.023 -0.001 -0.051 -0.001 -0.026  0.073 -0.051  0.048  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.073 -0.026 -0.026 -0.026 -0.001  0.048 -0.026 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.022 -0.002  0.022 -0.027  0.022 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.022 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.022  0.047 -0.027 -0.002  0.022  0.022 -0.027  0.022  0.047 -0.002  0.022 -0.002  0.022 -0.002 -0.052 -0.002 -0.027  0.072 -0.052  0.047  0.022 -0.027 -0.002 -0.027 -0.027  0.022 -0.002 -0.027 -0.027 -0.052 -0.027  0.072 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028  0.021  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.028 -0.003  0.021  0.021 -0.003  0.021  0.046 -0.003  0.021 -0.003  0.021 -0.003 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.028  0.021 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.028  0.071 -0.028 -0.028 -0.028 -0.003  0.046 -0.028 
 0.070  0.045 -0.054 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.004 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.020  0.020 -0.004  0.020 -0.029  0.020 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.029 -0.004  0.020  0.020 -0.004  0.020  0.045 -0.004  0.020 -0.004  0.020 -0.004 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.029  0.070 -0.029 -0.029 -0.029 -0.004  0.045 -0.029 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.045  0.070 -0.055 -0.030 -0.055 -0.005 -0.055 -0.005 -0.080 -0.030 -0.030 -0.030 -0.055 -0.005 -0.055 -0.055 -0.055  0.045  0.020 -0.030 -0.055  0.070 -0.030 -0.055  0.070 -0.030 -0.030  0.070  0.120 -0.030 -0.055 -0.030 -0.080 -0.080 -0.030 -0.005 -0.055 -0.030 -0.005  0.020 -0.005  0.020 -0.055  0.045 -0.055 -0.055 -0.055 -0.055 -0.055 -0.030 -0.005 -0.055  0.045 -0.080 -0.030 -0.055 -0.055 -0.080 -0.080 -0.055 -0.030 -0.030  0.045  0.045 -0.030 -0.030  0.070 -0.005  0.020 -0.005  0.045  0.045 -0.005  0.020 -0.005 -0.005 -0.080 -0.030 -0.055  0.219 -0.080  0.070  0.045 -0.030 -0.005 -0.030 -0.030  0.020 -0.030 -0.030  0.045 -0.080 -0.030  0.070 -0.055 -0.030 -0.055  0.045  0.020 -0.055 
 0.087  0.037 -0.088 -0.038 -0.113 -0.038 -0.088  0.012 -0.138 -0.063 -0.038 -0.063 -0.063  0.012 -0.063 -0.113 -0.063  0.012  0.012 -0.088 -0.113  0.112 -0.063 -0.088  0.161 -0.038 -0.013  0.037  0.112 -0.063 -0.063 -0.038 -0.113 -0.138 -0.088 -0.013 -0.088 -0.038 -0.038 -0.013 -0.038  0.037 -0.038 -0.013 -0.088 -0.038 -0.113 -0.088 -0.113 -0.063 -0.063 -0.088  0.112 -0.113 -0.038 -0.063 -0.038 -0.138 -0.088 -0.063 -0.088 -0.013  0.012  0.012 -0.063 -0.038  0.137  0.012  0.037 -0.013  0.137  0.037  0.012  0.037 -0.063 -0.038 -0.088 -0.063  0.012  0.435 -0.138  0.286  0.261 -0.038  0.012 -0.038 -0.038 -0.013 -0.088 -0.088  0.137 -0.038 -0.063  0.137 -0.063 -0.013 -0.063  0.161  0.137 -0.113 
 0.065  0.040 -0.134 -0.084 -0.109 -0.084 -0.109  0.015 -0.134 -0.084 -0.009 -0.084 -0.084 -0.034 -0.059 -0.059 -0.109 -0.009 -0.009 -0.134 -0.134  0.165 -0.109 -0.084  0.140 -0.034  0.040 -0.009  0.165 -0.109 -0.059 -0.059 -0.159 -0.184 -0.059 -0.059 -0.109 -0.059 -0.084 -0.084 -0.034 -0.034 -0.059 -0.059 -0.084 -0.059 -0.134 -0.034 -0.134 -0.034 -0.084 -0.109  0.065 -0.009  0.040 -0.134 -0.059 -0.134 -0.134 -0.109 -0.084  0.040 -0.059  0.040 -0.084 -0.059  0.140  0.040  0.065 -0.009  0.190  0.065 -0.009  0.115 -0.059 -0.059 -0.109 -0.084 -0.034  0.514 -0.184  0.339  0.289 -0.084 -0.034 -0.084 -0.034 -0.034 -0.084 -0.084  0.140 -0.109 -0.034  0.115 -0.034 -0.059 -0.084  0.115  0.115 -0.109 
 0.152  0.003 -0.146 -0.072 -0.072 -0.097 -0.122  0.028 -0.122 -0.146 -0.047 -0.072 -0.097 -0.047 -0.072 -0.097 -0.122 -0.022  0.028 -0.146 -0.171  0.128 -0.146 -0.122  0.103 -0.047  0.003 -0.072  0.128 -0.122 -0.047 -0.146 -0.221 -0.246 -0.022 -0.047 -0.146 -0.072 -0.122 -0.146  0.078 -0.072 -0.072 -0.022 -0.146 -0.097 -0.196  0.003 -0.171 -0.072 -0.146 -0.122  0.053  0.003  0.003 -0.122 -0.047 -0.146 -0.196 -0.171 -0.122  0.053 -0.122  0.003 -0.122 -0.072  0.103  0.103  0.152  0.053  0.227  0.103  0.028  0.053 -0.022 -0.022 -0.146 -0.047  0.003  0.526 -0.246  0.327  0.302 -0.097 -0.097 -0.122 -0.072 -0.097 -0.097 -0.122  0.078 -0.122 -0.097  0.003 -0.097 -0.122 -0.097  0.177  0.152 -0.097 
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 0.146 -0.003 -0.028 -0.078 -0.003  0.122  0.097 -0.152 -0.028  0.022  0.296 -0.028  0.122 -0.078  0.221  0.122  0.122 -0.103 -0.053  0.072 -0.078  0.072 -0.128 -0.078  0.072  0.022 -0.003  0.246  0.072  0.719  0.271 -0.078 -0.078 -0.053  0.196  0.146  0.670  0.047  0.047 -0.003  0.047 -0.003  0.097  0.769 -0.227  0.221 -0.053  0.396  0.047  0.122 -0.003  0.595  0.171  0.146 -0.152 -0.078 -0.028 -0.152  0.022  0.047  0.072 -0.078 -0.128 -0.053  0.047 -0.053 -0.028 -0.103 -0.152 -0.103 -0.103 -0.078 -0.103  0.072 -0.003 -0.028 -0.078 -0.152 -0.103  0.171  0.196  0.171 -0.202 -0.028  0.171  0.022  0.047  0.072 -0.028 -0.053 -0.152 -0.128  0.122  0.146 -0.053  0.396  0.097 -0.053  0.047  0.047 
 0.099 -0.000 -0.025 -0.100  0.074  0.224  0.124 -0.150 -0.025 -0.000  0.448  0.024  0.124 -0.125  0.249  0.149  0.124 -0.125 -0.100  0.099 -0.050  0.074 -0.150 -0.075  0.049  0.024 -0.000  0.249  0.074  0.697  0.274 -0.025 -0.100 -0.075  0.199  0.224  0.572  0.024  0.074 -0.000  0.049  0.049  0.099  0.722 -0.250  0.249 -0.075  0.448  0.024  0.149 -0.025  0.597  0.149  0.274 -0.175 -0.075 -0.025 -0.125  0.024 -0.025  0.049 -0.125 -0.150 -0.075 -0.000 -0.025 -0.025 -0.125 -0.175 -0.075 -0.100 -0.075 -0.150  0.074  0.024 -0.050 -0.100 -0.175 -0.100  0.249  0.174  0.174 -0.200 -0.000  0.124  0.049 -0.000  0.049 -0.025 -0.075 -0.175 -0.150  0.074  0.149 -0.075  0.373  0.124 -0.075  0.024  0.024 
 0.087 -0.012 -0.012 -0.062  0.062  0.262  0.137 -0.162 -0.037  0.037  0.561  0.037  0.112 -0.137  0.262  0.112  0.162 -0.087 -0.087  0.162 -0.037  0.062 -0.162 -0.062  0.062  0.062  0.037  0.237  0.112  0.660  0.237 -0.012 -0.112 -0.087  0.212  0.286  0.561 -0.012  0.087 -0.012  0.062  0.062  0.087  0.710 -0.262  0.237 -0.037  0.436  0.012  0.137 -0.012  0.585  0.137  0.286 -0.187 -0.087 -0.037 -0.137  0.012 -0.062  0.037 -0.137 -0.137 -0.062 -0.012 -0.037 -0.037 -0.137 -0.162 -0.087 -0.062 -0.062 -0.162  0.062  0.062 -0.062 -0.087 -0.162 -0.112  0.237  0.162  0.162 -0.212 -0.012  0.112  0.037 -0.012  0.062 -0.037 -0.112 -0.187 -0.037  0.037  0.162 -0.087  0.336  0.112 -0.087  0.012  0.012 
 0.126  0.051 -0.048 -0.048  0.076  0.325  0.201 -0.148 -0.048  0.051  0.574  0.126  0.151 -0.123  0.325  0.051  0.201 -0.073 -0.098  0.201 -0.023  0.101 -0.173 -0.023  0.051  0.076  0.051  0.300  0.101  0.599  0.226  0.001 -0.098 -0.098  0.251  0.375  0.525 -0.023  0.076 -0.048  0.076  0.076  0.101  0.674 -0.297  0.276 -0.048  0.475  0.101  0.126 -0.023  0.550  0.101  0.350 -0.198 -0.073 -0.048 -0.073 -0.023 -0.123  0.001 -0.123 -0.123 -0.073 -0.023 -0.023 -0.048 -0.148 -0.173 -0.098 -0.048 -0.073 -0.198  0.076  0.101 -0.048 -0.098 -0.198 -0.098  0.226  0.151  0.176 -0.198 -0.023  0.076  0.026 -0.023  0.051 -0.048 -0.098 -0.198 -0.048  0.001  0.126 -0.098  0.276  0.151 -0.123  0.001 -0.023 
 0.118  0.093 -0.031 -0.006  0.093  0.392  0.193 -0.181 -0.081  0.068  0.567  0.118  0.193 -0.131  0.367  0.043  0.268 -0.081 -0.106  0.218  0.043  0.118 -0.181 -0.006  0.068  0.068  0.093  0.367  0.143  0.542  0.268  0.043 -0.106 -0.106  0.243  0.417  0.492 -0.056  0.093 -0.056  0.093  0.093  0.143  0.641 -0.305  0.268 -0.081  0.542  0.243  0.093  0.018  0.542  0.043  0.317 -0.206 -0.081 -0.056 -0.056 -0.006 -0.156 -0.031 -0.106 -0.081 -0.056 -0.006 -0.031 -0.056 -0.106 -0.181 -0.106 -0.056 -0.081 -0.181  0.043  0.093 -0.056 -0.131 -0.206 -0.081  0.243  0.118  0.168 -0.131 -0.031  0.093  0.068 -0.006  0.018 -0.006 -0.106 -0.181  0.018 -0.031  0.143 -0.081  0.243  0.118 -0.131  0.018 -0.031 
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 0.030  0.030 -0.020  0.005  0.055  0.055  0.055 -0.045 -0.045  0.005  0.179  0.055  0.130 -0.020  0.030  0.055  0.080 -0.020  0.030  0.204 -0.045 -0.045 -0.045  0.105  0.105  0.105  0.030  0.055  0.005  0.080  0.005 -0.020 -0.045  0.055  0.005  0.030  0.603  0.005  0.005  0.005  0.055  0.105  0.105  0.703 -0.045  0.080 -0.045  0.055  0.005 -0.020  0.005  0.105  0.005  0.005 -0.045  0.055  0.005 -0.020  0.030 -0.020  0.080  0.005 -0.020 -0.020  0.030  0.005 -0.020 -0.045 -0.020 -0.020  0.105  0.055 -0.020  0.005  0.030  0.005  0.005 -0.045  0.080  0.055  0.030  0.154 -0.020 -0.045  0.055 -0.020  0.105  0.030  0.005  0.030  0.005 -0.020  0.005  0.030  0.005  0.005 -0.045  0.005  0.005  0.005 
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 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 0.056  0.131  0.156  0.056  0.081 -0.018  0.156 -0.093  0.131 -0.018 -0.018 -0.093  0.006 -0.068 -0.093  0.006  0.031  0.206 -0.018 -0.093  0.006  0.330  0.056  0.206  0.006 -0.018  0.006  0.056  0.181 -0.118  0.853 -0.168  0.056 -0.093  0.579  0.106  0.181 -0.093  0.006 -0.018  0.181  0.330  0.031  0.206  0.305  0.031  0.206  0.305 -0.043  0.555 -0.118  0.256  0.156  0.131 -0.018 -0.043  0.006  0.131  0.505  0.081 -0.068 -0.143  0.056 -0.043 -0.093 -0.068  0.056 -0.043 -0.143 -0.043 -0.043 -0.068  0.106  0.006  0.106  0.031  0.031  0.006  0.056 -0.043  0.056  0.031 -0.143 -0.118  0.081  0.006  0.231 -0.043  0.056 -0.068  0.006  0.031  0.031  0.430 -0.068 -0.018 -0.118  0.081 -0.018 -0.068 
 0.054  0.228  0.153  0.054  0.178  0.079  0.129 -0.096  0.129  0.029  0.004 -0.145 -0.021 -0.071 -0.121  0.004 -0.021  0.278 -0.021 -0.121 -0.021  0.328  0.029  0.228  0.054 -0.046  0.079  0.054  0.228 -0.071  0.801 -0.220  0.079 -0.121  0.652  0.228  0.153 -0.096  0.029 -0.046  0.203  0.353  0.029  0.278  0.278  0.104  0.178  0.427 -0.071  0.627 -0.145  0.452  0.153  0.104 -0.021 -0.096  0.079  0.129  0.702  0.104 -0.071 -0.096  0.054 -0.096 -0.121 -0.046  0.029 -0.046 -0.145 -0.071 -0.021 -0.121  0.079 -0.021  0.153  0.004  0.054  0.004  0.004  0.029  0.079  0.054 -0.121 -0.121  0.153 -0.046  0.278 -0.021  0.104 -0.121 -0.046  0.004  0.004  0.477 -0.071  0.004 -0.046  0.079 -0.046 -0.096 
 0.035  0.284  0.085  0.110  0.209  0.184  0.110 -0.090  0.135  0.035  0.035 -0.164 -0.040 -0.015 -0.115 -0.015 -0.015  0.259 -0.040 -0.140 -0.065  0.334  0.010  0.209  0.085 -0.065  0.060  0.085  0.309 -0.090  0.757 -0.189  0.135 -0.090  0.683  0.284  0.135 -0.115  0.010 -0.040  0.184  0.334  0.010  0.259  0.284  0.110  0.159  0.433 -0.065  0.608 -0.164  0.558  0.234  0.110 -0.090 -0.140  0.060  0.159  0.683  0.085 -0.090 -0.115  0.060 -0.090 -0.140 -0.015  0.010 -0.040 -0.140 -0.090 -0.040 -0.140  0.060 -0.040  0.159  0.010  0.060  0.010 -0.015  0.085  0.085  0.135 -0.090 -0.115  0.135 -0.065  0.359 -0.015  0.110 -0.115 -0.065 -0.015 -0.015  0.533 -0.065  0.010 -0.065  0.060 -0.065 -0.090 
 0.067  0.266  0.042  0.216  0.241  0.266  0.092 -0.058  0.142  0.067  0.067 -0.207 -0.058 -0.008 -0.108  0.017 -0.008  0.291 -0.033 -0.157 -0.083  0.416 -0.008  0.191  0.092 -0.058  0.067  0.092  0.341 -0.083  0.739 -0.182  0.142 -0.108  0.690  0.291  0.117 -0.083 -0.008 -0.058  0.191  0.341  0.017  0.266  0.291  0.241  0.191  0.465 -0.033  0.590 -0.157  0.565  0.266  0.092 -0.108 -0.157  0.017  0.166  0.640  0.042 -0.083 -0.083  0.017 -0.133 -0.157 -0.033 -0.008 -0.033 -0.133 -0.108 -0.058 -0.157  0.017 -0.058  0.166  0.017  0.042  0.017 -0.033  0.092  0.067  0.166 -0.108 -0.108  0.092 -0.058  0.341 -0.008  0.117 -0.157 -0.108 -0.008  0.017  0.490 -0.083  0.067 -0.083  0.042 -0.058 -0.108 
 0.054  0.278  0.004  0.228  0.278  0.253  0.079 -0.021  0.153  0.054  0.054 -0.220 -0.071 -0.021 -0.096  0.029 -0.021  0.378 -0.046 -0.170 -0.096  0.477  0.004  0.178  0.104 -0.071  0.054  0.079  0.378 -0.046  0.726 -0.170  0.153 -0.121  0.677  0.353  0.104 -0.096 -0.021 -0.046  0.178  0.353 -0.021  0.228  0.278  0.278  0.278  0.452 -0.046  0.577 -0.195  0.552  0.303  0.054 -0.121 -0.145  0.029  0.203  0.627  0.004 -0.096 -0.096  0.004 -0.145 -0.170 -0.021 -0.021 -0.071 -0.096 -0.071 -0.046 -0.170  0.029 -0.071  0.153  0.004  0.029  0.004 -0.021  0.153  0.079  0.153 -0.121 -0.121  0.104 -0.071  0.328 -0.021  0.153 -0.170 -0.121 -0.021  0.029  0.452 -0.071  0.079 -0.096  0.029 -0.071 -0.121 
 0.068  0.267 -0.032  0.417  0.317  0.192  0.018  0.018  0.192  0.093  0.068 -0.231 -0.057 -0.032 -0.107  0.068 -0.007  0.417 -0.032 -0.206 -0.132  0.516  0.043  0.167  0.068 -0.057  0.093  0.093  0.441 -0.007  0.715 -0.156  0.242 -0.132  0.666  0.392  0.093 -0.107 -0.082 -0.082  0.142  0.317 -0.082  0.192  0.267  0.267  0.392  0.417 -0.057  0.516 -0.206  0.516  0.292  0.018 -0.107 -0.132 -0.007  0.192  0.591 -0.007 -0.082 -0.082 -0.007 -0.156 -0.156 -0.057 -0.032 -0.057 -0.132 -0.082 -0.032 -0.156  0.018 -0.107  0.142 -0.007  0.018 -0.007 -0.057  0.142  0.043  0.167 -0.132 -0.156  0.093 -0.057  0.292 -0.032  0.167 -0.231 -0.132  0.018  0.018  0.317 -0.057  0.167 -0.107  0.043 -0.107 -0.107 
 0.087  0.261 -0.038  0.535  0.386  0.137  0.012  0.062  0.161  0.112  0.087 -0.212  0.012 -0.038 -0.113  0.062 -0.013  0.411 -0.038 -0.212 -0.138  0.535  0.062  0.137  0.062 -0.063  0.112  0.137  0.435  0.037  0.710 -0.138  0.236 -0.113  0.660  0.411  0.137 -0.113 -0.063 -0.138  0.137  0.261 -0.088  0.137  0.261  0.286  0.411  0.435 -0.038  0.386 -0.187  0.510  0.261  0.012 -0.138 -0.113 -0.013  0.211  0.585 -0.038 -0.038 -0.088 -0.013 -0.162 -0.162 -0.038 -0.013 -0.038 -0.113 -0.113 -0.038 -0.113  0.037 -0.088  0.137 -0.013  0.012  0.037 -0.063  0.137  0.062  0.161 -0.138 -0.138  0.087 -0.063  0.311 -0.013  0.161 -0.237 -0.138  0.062  0.012  0.311 -0.063  0.161 -0.113  0.062 -0.113 -0.088 
 0.107  0.306 -0.042  0.556  0.456  0.082  0.007  0.107  0.232  0.107  0.107 -0.217  0.057 -0.017 -0.092  0.082  0.032  0.406 -0.067 -0.217 -0.167  0.556  0.082  0.107  0.107 -0.017  0.157  0.057  0.431  0.032  0.705 -0.117  0.257 -0.117  0.630  0.481  0.132 -0.142 -0.092 -0.142  0.132  0.232 -0.092  0.157  0.257  0.331  0.506  0.406  0.007  0.331 -0.192  0.506  0.232 -0.017 -0.142 -0.117  0.007  0.232  0.556 -0.042  0.007 -0.167 -0.042 -0.167 -0.142  0.007 -0.017 -0.042 -0.117 -0.117 -0.017 -0.067  0.032 -0.067  0.157  0.007  0.032  0.032 -0.067  0.107  0.082  0.157 -0.142 -0.142  0.082 -0.092  0.331  0.007  0.132 -0.242 -0.142  0.107  0.007  0.282 -0.067  0.157 -0.117  0.082 -0.117 -0.092 
 0.080  0.279 -0.045  0.603  0.453  0.030  0.055  0.130  0.279  0.130  0.130 -0.194  0.080 -0.045 -0.120  0.055  0.030  0.404 -0.070 -0.219 -0.144  0.578  0.080  0.130  0.105  0.005  0.154  0.055  0.428  0.055  0.678 -0.120  0.254 -0.120  0.578  0.503  0.154 -0.144 -0.095 -0.120  0.130  0.254 -0.070  0.154  0.229  0.354  0.528  0.379  0.005  0.304 -0.194  0.503  0.204 -0.045 -0.144 -0.120  0.005  0.229  0.553 -0.070  0.005 -0.144 -0.045 -0.144 -0.169  0.005 -0.020 -0.045 -0.120 -0.120 -0.020 -0.070  0.055 -0.070  0.154 -0.020  0.005  0.030 -0.070  0.080  0.080  0.130 -0.144 -0.144  0.080 -0.070  0.329  0.030  0.080 -0.244 -0.169  0.130 -0.020  0.254 -0.070  0.179 -0.120  0.080 -0.120 -0.095 
 0.105  0.254 -0.045  0.603  0.478  0.030  0.055  0.154  0.304  0.154  0.130 -0.194  0.105 -0.045 -0.120  0.055  0.030  0.404 -0.070 -0.244 -0.144  0.578  0.080  0.105  0.130  0.030  0.154  0.055  0.453  0.080  0.678 -0.120  0.279 -0.095  0.553  0.503  0.154 -0.144 -0.095 -0.120  0.130  0.204 -0.045  0.154  0.229  0.404  0.528  0.379  0.055  0.304 -0.194  0.478  0.179 -0.045 -0.144 -0.120  0.005  0.204  0.528 -0.070  0.005 -0.144 -0.095 -0.120 -0.169  0.005 -0.020 -0.045 -0.120 -0.120 -0.020 -0.045  0.055 -0.070  0.130 -0.020 -0.020  0.030 -0.070  0.030  0.080  0.105 -0.144 -0.144  0.080 -0.095  0.329  0.030  0.080 -0.244 -0.169  0.154 -0.020  0.179 -0.095  0.179 -0.120  0.055 -0.120 -0.095 
 0.102  0.276 -0.048  0.600  0.475  0.027  0.052  0.151  0.326  0.151  0.102 -0.197  0.127 -0.048 -0.123  0.027  0.002  0.401 -0.073 -0.247 -0.147  0.550  0.077  0.102  0.127  0.027  0.176  0.052  0.475  0.077  0.675 -0.123  0.276 -0.098  0.550  0.525  0.151 -0.147 -0.098 -0.098  0.127  0.201 -0.023  0.176  0.226  0.401  0.550  0.351  0.102  0.276 -0.172  0.475  0.151 -0.048 -0.147 -0.123  0.027  0.226  0.525 -0.073  0.027 -0.147 -0.123 -0.123 -0.172  0.002 -0.048 -0.048 -0.147 -0.123 -0.048 -0.073  0.052 -0.048  0.151  0.002 -0.023  0.027 -0.073  0.027  0.052  0.102 -0.147 -0.147  0.077 -0.123  0.326  0.027  0.077 -0.247 -0.197  0.151 -0.023  0.176 -0.098  0.226 -0.123 -0.023 -0.123 -0.098 
 0.097  0.272 -0.027  0.595  0.521  0.047  0.072  0.172  0.321  0.172  0.072 -0.177  0.147 -0.027 -0.127  0.022 -0.002  0.421 -0.077 -0.252 -0.152  0.521  0.097  0.097  0.197  0.097  0.247  0.072  0.521  0.072  0.670 -0.127  0.247 -0.102  0.570  0.496  0.147 -0.152 -0.102 -0.102  0.122  0.222 -0.027  0.172  0.272  0.421  0.546  0.321  0.122  0.272 -0.177  0.446  0.147 -0.052 -0.152 -0.127  0.022  0.222  0.471 -0.077  0.022 -0.152 -0.127 -0.102 -0.177 -0.002 -0.052 -0.052 -0.152 -0.077 -0.052 -0.052  0.022 -0.027  0.147 -0.027 -0.027  0.047  0.022  0.022  0.072  0.097 -0.152 -0.152  0.097 -0.127  0.296  0.022  0.072 -0.277 -0.202  0.172 -0.027  0.147 -0.102  0.272 -0.127 -0.027 -0.127 -0.102 
 0.131  0.281 -0.018  0.530  0.480  0.056  0.031  0.106  0.330  0.106  0.056 -0.143  0.031 -0.018 -0.068  0.031  0.006  0.380 -0.043 -0.193 -0.118  0.380  0.056 -0.043  0.131  0.081  0.231  0.031  0.505  0.081  0.654 -0.093  0.206 -0.118  0.555  0.430  0.031 -0.168 -0.093 -0.043  0.131  0.231 -0.018  0.156  0.206  0.405  0.604  0.231  0.081  0.256 -0.093  0.355  0.181 -0.043 -0.068 -0.093  0.006  0.131  0.330 -0.093  0.031 -0.093 -0.068 -0.093 -0.093 -0.018 -0.118 -0.068 -0.118 -0.068 -0.043 -0.043 -0.118 -0.043  0.181  0.006 -0.043  0.006  0.031 -0.018 -0.018  0.106 -0.093 -0.168 -0.018 -0.118  0.131 -0.018  0.081 -0.193 -0.118  0.106 -0.018  0.031 -0.068  0.256 -0.093 -0.068 -0.143 -0.068 
 0.088  0.212  0.038  0.436  0.436  0.038 -0.012  0.138  0.212  0.138  0.038 -0.087  0.013 -0.012 -0.037  0.038  0.038  0.287 -0.062 -0.112 -0.062  0.312 -0.012 -0.062  0.138  0.063  0.138  0.038  0.412  0.113  0.486 -0.037  0.187 -0.037  0.486  0.436  0.038 -0.112 -0.037 -0.012  0.187  0.187 -0.037  0.138  0.113  0.461  0.636  0.212  0.088  0.262 -0.037  0.362  0.138 -0.037 -0.012 -0.062  0.038  0.113  0.113 -0.087  0.013 -0.087 -0.062 -0.012 -0.012  0.063 -0.087 -0.037 -0.087 -0.062 -0.012 -0.037 -0.087 -0.062  0.113  0.013 -0.037  0.038  0.038  0.013 -0.012  0.063 -0.087 -0.137  0.013 -0.087  0.088  0.038  0.038 -0.112 -0.062  0.088  0.038  0.063 -0.087  0.187 -0.037 -0.037 -0.087 -0.037 
 0.081  0.206  0.006  0.355  0.380  0.056 -0.018  0.131  0.231  0.156  0.056 -0.068  0.006 -0.043 -0.018  0.056  0.006  0.206 -0.068 -0.093 -0.043  0.305 -0.018 -0.043  0.131  0.081  0.131  0.056  0.405  0.106  0.405 -0.018  0.181 -0.018  0.455  0.455  0.056 -0.093  0.006  0.006  0.181  0.156 -0.018  0.131  0.056  0.455  0.629  0.206  0.081  0.281 -0.018  0.305  0.131 -0.018 -0.018 -0.043  0.031  0.131  0.106 -0.068  0.006 -0.093 -0.043 -0.018  0.006  0.081 -0.068 -0.068 -0.093 -0.043  0.006 -0.043 -0.093 -0.068  0.106  0.031  0.006  0.056  0.031  0.006 -0.018  0.081 -0.093 -0.118  0.031 -0.068  0.056  0.056  0.031 -0.093 -0.068  0.081  0.056  0.056 -0.068  0.181 -0.043 -0.043 -0.068 -0.018 
 0.113  0.162  0.013  0.262  0.262  0.063  0.013  0.162  0.162  0.162 -0.012 -0.037  0.013 -0.037  0.013  0.038  0.038  0.212 -0.037 -0.062 -0.012  0.312 -0.012 -0.037  0.088  0.013  0.088  0.038  0.387  0.138  0.262  0.013  0.162 -0.012  0.486  0.387  0.088 -0.062  0.038 -0.012  0.212  0.138 -0.012  0.162 -0.012  0.436  0.636  0.162  0.088  0.262  0.013  0.187  0.088  0.013 -0.012 -0.062 -0.037  0.138  0.063 -0.037 -0.012 -0.062 -0.037  0.013  0.013  0.038 -0.037 -0.062 -0.062 -0.037  0.038 -0.037 -0.062 -0.062  0.113  0.013 -0.037 -0.012  0.013 -0.012 -0.037  0.063 -0.087 -0.087  0.063 -0.062  0.013  0.088  0.038 -0.062 -0.037  0.038  0.063  0.038 -0.062  0.138 -0.012 -0.037 -0.037 -0.012 
 0.127  0.177  0.002  0.227  0.227  0.052  0.027  0.152  0.102  0.177 -0.022 -0.022  0.002 -0.047  0.027  0.052  0.002  0.202 -0.022 -0.047  0.002  0.326  0.002 -0.047  0.052 -0.022  0.052  0.052  0.401  0.102  0.127  0.027  0.152  0.002  0.501  0.376  0.077 -0.047  0.027 -0.022  0.202  0.052  0.002  0.127 -0.047  0.326  0.650  0.102  0.077  0.227  0.027  0.102  0.002  0.002  0.002 -0.072 -0.022  0.152  0.052 -0.022  0.002 -0.047 -0.022  0.002  0.002  0.052 -0.022 -0.047 -0.047 -0.022  0.002 -0.022 -0.047 -0.047  0.102  0.002 -0.072 -0.047 -0.022  0.002 -0.022  0.052 -0.072 -0.072  0.077 -0.047  0.002  0.102  0.027 -0.047 -0.022  0.052  0.052  0.027 -0.047  0.127 -0.072 -0.022 -0.047  0.002 
 0.098  0.172  0.023  0.147  0.147  0.023 -0.002  0.172  0.073  0.172 -0.027 -0.002 -0.002 -0.027  0.048  0.023  0.023  0.197 -0.002 -0.052  0.023  0.197 -0.002 -0.027  0.048 -0.052  0.023  0.048  0.347  0.023  0.073 -0.002  0.172 -0.027  0.496  0.322  0.048 -0.027  0.048 -0.002  0.172 -0.002 -0.027  0.073 -0.027  0.172  0.745  0.023  0.098  0.222 -0.002  0.023 -0.002 -0.002 -0.052 -0.052 -0.052  0.098  0.048 -0.002 -0.002 -0.052 -0.052  0.023 -0.002  0.048 -0.002 -0.052 -0.027 -0.027 -0.002 -0.027 -0.052 -0.052  0.098 -0.027 -0.052 -0.052 -0.027 -0.002 -0.002 -0.027 -0.052 -0.052  0.023 -0.027 -0.027  0.048  0.023 -0.027 -0.002  0.048  0.048 -0.027 -0.052  0.048 -0.052 -0.027 -0.027 -0.002 
 0.104  0.129  0.079  0.129  0.104  0.029 -0.021  0.153  0.029  0.153 -0.021 -0.021  0.004  0.004  0.029  0.029  0.004  0.203  0.004 -0.021  0.029  0.129  0.004 -0.021  0.054 -0.046  0.029  0.029  0.253  0.054 -0.021  0.004  0.178 -0.021  0.502  0.328 -0.021  0.004  0.054  0.029  0.129 -0.021 -0.046  0.079  0.004  0.104  0.926  0.004  0.079  0.203 -0.021  0.004  0.004 -0.021 -0.046 -0.021 -0.046  0.054  0.029  0.004  0.029 -0.046 -0.046  0.004  0.029  0.029  0.004 -0.046 -0.021 -0.021  0.004 -0.021 -0.046 -0.046  0.104  0.004 -0.021 -0.046 -0.021  0.004  0.004 -0.021 -0.021 -0.046 -0.046 -0.046 -0.021  0.054  0.029 -0.046 -0.021  0.029  0.079  0.004 -0.046  0.029 -0.046 -0.021 -0.021  0.004 
 0.043  0.118  0.093  0.093  0.093  0.043 -0.007  0.142 -0.007  0.068 -0.032 -0.032 -0.007  0.018  0.018  0.018  0.018  0.167 -0.007 -0.007  0.018  0.043 -0.007 -0.032  0.068 -0.032  0.043 -0.007  0.192  0.043 -0.007 -0.007  0.142 -0.007  0.367  0.167 -0.007 -0.007  0.043  0.043  0.093 -0.032 -0.032  0.018  0.018 -0.007  0.965 -0.007  0.068  0.118 -0.007 -0.007 -0.007 -0.032 -0.032 -0.007 -0.032  0.043  0.018  0.018  0.043 -0.032 -0.032 -0.007  0.018  0.018 -0.007 -0.032 -0.007 -0.032 -0.007 -0.007 -0.032 -0.032  0.043 -0.007 -0.007 -0.032 -0.032 -0.007  0.043 -0.007 -0.007 -0.032 -0.032 -0.032 -0.032  0.043  0.018 -0.032 -0.007  0.043  0.043 -0.007 -0.032 -0.007 -0.032 -0.007 -0.007 -0.007 
 0.021  0.071  0.071  0.096  0.096  0.046 -0.003  0.121 -0.003  0.071 -0.028 -0.028 -0.003  0.021 -0.003  0.021  0.021  0.171 -0.003 -0.003 -0.003  0.021 -0.003 -0.028  0.046 -0.028 -0.003 -0.028  0.146  0.046 -0.003 -0.003  0.121 -0.028  0.246  0.121 -0.003 -0.003  0.046  0.046  0.096 -0.028 -0.028  0.021 -0.003 -0.003  0.993 -0.003  0.021  0.071 -0.003 -0.003 -0.003 -0.028 -0.028 -0.003 -0.028  0.021 -0.003 -0.003  0.046 -0.028 -0.028 -0.003  0.021  0.021 -0.003 -0.028 -0.003 -0.028 -0.003 -0.003 -0.028 -0.003  0.046 -0.003 -0.003 -0.028 -0.028 -0.003  0.046 -0.003 -0.003 -0.028 -0.028 -0.028 -0.028  0.046  0.021 -0.028 -0.003  0.046  0.046 -0.003 -0.028 -0.003 -0.028 -0.003 -0.003 -0.028 
 0.004  0.054  0.054  0.054  0.054 -0.021 -0.021  0.079  0.004  0.004 -0.021 -0.021 -0.021  0.004  0.004  0.004  0.029  0.054 -0.021  0.004 -0.021  0.004 -0.021 -0.021  0.029 -0.021  0.004 -0.021  0.029  0.054  0.004  0.004  0.054 -0.021  0.129  0.004 -0.021  0.004  0.054  0.029  0.004 -0.021 -0.021  0.004  0.004  0.004  1.000 -0.021  0.029  0.054  0.004 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.029 -0.021 -0.021  0.054 -0.021 -0.021 -0.021  0.029  0.004  0.004 -0.021  0.004 -0.021  0.004  0.004 -0.021  0.004  0.004  0.004  0.004 -0.021 -0.021  0.004  0.029  0.004  0.004 -0.021 -0.021 -0.021 -0.021  0.054 -0.021 -0.021 -0.021  0.029  0.029  0.004 -0.021 -0.021 -0.021  0.004  0.004 -0.021 
 0.004  0.054  0.054  0.054  0.054 -0.021 -0.021  0.079  0.004  0.004 -0.021 -0.021 -0.021  0.004  0.004  0.004  0.029  0.054 -0.021  0.004 -0.021  0.004 -0.021 -0.021  0.029 -0.021  0.004 -0.021  0.029  0.054  0.004  0.004  0.054 -0.021  0.129  0.004 -0.021  0.004  0.054  0.029  0.004 -0.021 -0.021  0.004  0.004  0.004  1.000 -0.021  0.029  0.054  0.004 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.029 -0.021 -0.021  0.054 -0.021 -0.021 -0.021  0.029  0.004  0.004 -0.021  0.004 -0.021  0.004  0.004 -0.021  0.004  0.004  0.004  0.004 -0.021 -0.021  0.004  0.029  0.004  0.004 -0.021 -0.021 -0.021 -0.021  0.054 -0.021 -0.021 -0.021  0.029  0.029  0.004 -0.021 -0.021 -0.021  0.004  0.004 -0.021 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.004  0.054  0.054  0.054  0.054 -0.020 -0.020  0.079  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004  0.004  0.054 -0.020  0.104  0.004 -0.020  0.004  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004  1.001 -0.020  0.029  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.018  0.068  0.068  0.068  0.043 -0.032 -0.032  0.142 -0.007  0.018 -0.032 -0.032 -0.032  0.018  0.018 -0.007  0.018  0.093 -0.032 -0.007 -0.007  0.068 -0.032 -0.032  0.068 -0.032  0.043 -0.007  0.068  0.093 -0.007 -0.007  0.093 -0.032  0.441  0.018 -0.032 -0.007  0.068  0.018 -0.007 -0.007 -0.032 -0.007  0.018  0.018  0.990 -0.032  0.118  0.068 -0.007 -0.032 -0.007 -0.032 -0.032 -0.007 -0.007  0.018  0.018 -0.007  0.043 -0.032 -0.032 -0.032  0.018 -0.007 -0.007 -0.007 -0.007 -0.032 -0.007  0.018 -0.032 -0.007 -0.007 -0.007 -0.007 -0.032 -0.032 -0.007  0.043 -0.007 -0.007 -0.032 -0.032 -0.032 -0.032  0.043 -0.032 -0.032 -0.032  0.043  0.018 -0.007 -0.032 -0.007  0.018  0.018 -0.007 -0.032 
 0.033  0.157  0.182  0.157  0.108 -0.042  0.008  0.257  0.083  0.033 -0.067 -0.067  0.008  0.033  0.008  0.058  0.008  0.332  0.008 -0.017  0.008  0.232 -0.042 -0.067  0.033 -0.067  0.157  0.033  0.157  0.157  0.033 -0.017  0.157 -0.042  0.730  0.108  0.008 -0.042  0.133  0.058  0.108  0.033 -0.042 -0.042  0.008  0.008  0.955 -0.017  0.282  0.083 -0.017 -0.042  0.033 -0.067 -0.042 -0.017 -0.042  0.033  0.058 -0.017  0.108 -0.017 -0.042  0.033 -0.017 -0.017 -0.017  0.008 -0.042 -0.017 -0.017  0.008 -0.067 -0.017  0.083  0.008 -0.017 -0.042 -0.067 -0.017  0.058  0.008 -0.042 -0.042 -0.067 -0.067 -0.067  0.008 -0.017 -0.042 -0.042  0.083  0.008  0.008 -0.067  0.008 -0.017  0.008 -0.042 -0.042 
 0.052  0.301  0.252  0.426  0.127 -0.072  0.077  0.401  0.127  0.077 -0.022 -0.072  0.002  0.002  0.002  0.052  0.002  0.476 -0.022 -0.047  0.002  0.277 -0.072 -0.097  0.002 -0.047  0.227  0.127  0.277  0.301  0.077  0.002  0.202 -0.047  0.800  0.227  0.002 -0.047  0.127  0.027  0.227  0.077  0.027 -0.047  0.127 -0.022  0.899 -0.022  0.526  0.177 -0.022 -0.047  0.077 -0.072  0.002 -0.047 -0.097  0.027  0.127 -0.022  0.102 -0.047 -0.047  0.102 -0.047  0.052 -0.047  0.002 -0.097 -0.047  0.002 -0.022 -0.097  0.002  0.127  0.002 -0.022 -0.072 -0.072  0.027  0.027 -0.022 -0.097 -0.122  0.027 -0.072 -0.072  0.002 -0.072 -0.097 -0.022  0.152 -0.022  0.027 -0.072  0.052 -0.022  0.077 -0.022 -0.097 
 0.125  0.399  0.374  0.598  0.299  0.075  0.100  0.524  0.175  0.175 -0.049  0.000  0.100  0.000  0.025  0.050 -0.049  0.623 -0.074 -0.074 -0.074  0.374  0.000 -0.099  0.000  0.025  0.449  0.200  0.598  0.349  0.125 -0.024  0.449  0.025  0.823  0.399 -0.024 -0.099  0.100  0.050  0.449  0.100  0.150 -0.049  0.100  0.075  0.823  0.025  0.798  0.275  0.000 -0.024  0.025 -0.074 -0.074 -0.099 -0.149  0.050  0.200 -0.049  0.100 -0.024 -0.074  0.100 -0.099  0.050 -0.099 -0.074 -0.174 -0.024 -0.049 -0.049 -0.099 -0.049  0.100 -0.024 -0.024 -0.024 -0.099  0.025  0.075 -0.049 -0.149 -0.199  0.075 -0.124 -0.024  0.050 -0.049 -0.149 -0.099  0.150  0.000  0.075 -0.099  0.250 -0.074  0.125 -0.024 -0.124 
 0.170  0.420  0.395  0.569  0.370  0.170  0.096  0.519  0.145  0.245 -0.054  0.021  0.195  0.021 -0.004  0.046 -0.054  0.519 -0.079 -0.029 -0.104  0.395  0.046 -0.104 -0.029  0.071  0.544  0.345  0.644  0.320  0.121 -0.054  0.519 -0.004  0.768  0.494 -0.004 -0.153  0.121  0.071  0.544  0.220  0.145 -0.004  0.096  0.220  0.793  0.071  0.768  0.345 -0.004  0.046  0.046 -0.054 -0.104 -0.079 -0.178  0.046  0.220 -0.029  0.096 -0.029 -0.079  0.145 -0.129  0.046 -0.104 -0.079 -0.153 -0.029 -0.029  0.021 -0.079 -0.029  0.071 -0.054 -0.004 -0.029 -0.104  0.046  0.096 -0.079 -0.178 -0.203  0.046 -0.129 -0.054  0.021 -0.029 -0.129 -0.153  0.145  0.046  0.145 -0.129  0.345 -0.104  0.145 -0.079 -0.153 
 0.243  0.442  0.392  0.616  0.467  0.268  0.118  0.492  0.143  0.317 -0.006  0.093  0.243  0.018 -0.056  0.043 -0.106  0.392 -0.131  0.018 -0.131  0.392  0.093  0.018 -0.006  0.093  0.616  0.467  0.691  0.367  0.218 -0.006  0.567 -0.031  0.716  0.517  0.018 -0.181  0.093  0.118  0.542  0.292  0.292  0.043  0.093  0.367  0.741  0.143  0.716  0.492 -0.056  0.043  0.043 -0.031 -0.131 -0.106 -0.181  0.018  0.243 -0.056  0.093  0.018 -0.106  0.193 -0.131  0.018 -0.056 -0.106 -0.106 -0.081 -0.006 -0.006 -0.081 -0.056  0.018 -0.031  0.018  0.018 -0.081  0.018  0.118 -0.131 -0.231 -0.256  0.018 -0.131 -0.031  0.043 -0.031 -0.081 -0.156  0.093  0.068  0.243 -0.181  0.392 -0.106  0.143 -0.156 -0.181 
 0.240  0.415  0.390  0.614  0.514  0.340  0.190  0.464  0.165  0.340  0.016  0.091  0.290 -0.034 -0.034  0.041 -0.109  0.290 -0.084  0.091 -0.109  0.340  0.066  0.091 -0.034  0.091  0.589  0.464  0.689  0.290  0.215 -0.009  0.564 -0.034  0.689  0.539  0.016 -0.183  0.116  0.091  0.514  0.340  0.290  0.041  0.041  0.415  0.738  0.165  0.689  0.489 -0.084 -0.009  0.016 -0.009 -0.109 -0.109 -0.158  0.041  0.215 -0.059  0.116  0.041 -0.109  0.215 -0.134  0.041 -0.059 -0.109 -0.084 -0.084  0.016 -0.034 -0.034 -0.059 -0.009 -0.034  0.016  0.016 -0.059  0.016  0.141 -0.134 -0.233 -0.283  0.016 -0.183 -0.009  0.016  0.016 -0.084 -0.158  0.091  0.091  0.240 -0.183  0.415 -0.134  0.141 -0.158 -0.183 
 0.255  0.380  0.355  0.579  0.579  0.405  0.280  0.454  0.180  0.330  0.031  0.106  0.380 -0.019 -0.019  0.031 -0.094  0.205 -0.094  0.155 -0.069  0.305  0.031  0.180 -0.019  0.081  0.579  0.454  0.654  0.255  0.255  0.031  0.579  0.006  0.654  0.529  0.056 -0.168  0.106  0.155  0.454  0.405  0.280  0.081  0.006  0.429  0.728  0.180  0.654  0.504 -0.094 -0.019 -0.019  0.056 -0.119 -0.119 -0.168  0.031  0.180 -0.069  0.180  0.031 -0.069  0.180 -0.143  0.056 -0.019 -0.119 -0.069 -0.094  0.006 -0.044 -0.044 -0.019 -0.069 -0.044  0.081  0.031 -0.044  0.006  0.131 -0.168 -0.218 -0.293 -0.019 -0.218  0.006  0.006  0.006 -0.143 -0.143  0.056  0.081  0.230 -0.119  0.405 -0.143  0.131 -0.193 -0.193 
 0.255  0.380  0.355  0.529  0.579  0.454  0.280  0.454  0.180  0.305  0.056  0.106  0.405 -0.019  0.006  0.031 -0.094  0.205 -0.094  0.205 -0.069  0.280  0.031  0.255 -0.019  0.106  0.554  0.429  0.554  0.230  0.230  0.056  0.579  0.031  0.629  0.529  0.056 -0.168  0.106  0.155  0.454  0.429  0.280  0.106  0.006  0.429  0.728  0.180  0.654  0.529 -0.094 -0.044 -0.019  0.081 -0.143 -0.143 -0.193  0.031  0.180 -0.069  0.205  0.031 -0.019  0.180 -0.143  0.056 -0.044 -0.119 -0.069 -0.094  0.056 -0.044 -0.019  0.006 -0.094 -0.044  0.056  0.006 -0.044 -0.019  0.155 -0.168 -0.243 -0.293 -0.019 -0.193  0.006  0.031  0.031 -0.143 -0.193  0.056  0.081  0.230 -0.094  0.429 -0.143  0.131 -0.193 -0.243 
 0.214  0.388  0.363  0.513  0.612  0.488  0.313  0.388  0.189  0.288  0.089  0.114  0.438 -0.010  0.014  0.064 -0.085  0.189 -0.110  0.438 -0.010  0.239  0.064  0.463 -0.010  0.114  0.538  0.413  0.513  0.189  0.239  0.064  0.563  0.064  0.612  0.513  0.164 -0.210  0.114  0.189  0.388  0.463  0.288  0.189 -0.010  0.463  0.712  0.164  0.637  0.513 -0.110 -0.060 -0.010  0.114 -0.160 -0.135 -0.210  0.039  0.189 -0.060  0.214  0.014  0.039  0.164 -0.135  0.039 -0.060 -0.135 -0.060 -0.110  0.139 -0.060  0.014  0.014 -0.085 -0.060  0.064 -0.010 -0.035 -0.010  0.189 -0.160 -0.235 -0.309 -0.010 -0.210 -0.035  0.014  0.064 -0.135 -0.185  0.039  0.114  0.164 -0.110  0.488 -0.160  0.139 -0.185 -0.260 
 0.213  0.362  0.362  0.512  0.611  0.462  0.337  0.312  0.213  0.287  0.088  0.088  0.437 -0.011  0.013  0.088 -0.086  0.163 -0.086  0.487 -0.011  0.238  0.063  0.487 -0.011  0.113  0.562  0.412  0.512  0.188  0.238  0.063  0.562  0.063  0.611  0.512  0.213 -0.236  0.138  0.188  0.362  0.462  0.263  0.238 -0.011  0.462  0.711  0.163  0.586  0.487 -0.111 -0.061  0.013  0.088 -0.161 -0.111 -0.211  0.038  0.188 -0.036  0.213  0.013  0.038  0.113 -0.111  0.038 -0.061 -0.136 -0.086 -0.111  0.138 -0.086  0.063 -0.036 -0.111 -0.086  0.038  0.013 -0.036  0.013  0.188 -0.161 -0.236 -0.285 -0.011 -0.211 -0.061  0.013  0.088 -0.111 -0.186  0.038  0.113  0.163 -0.111  0.512 -0.136  0.138 -0.186 -0.285 
 0.257  0.357  0.382  0.481  0.631  0.456  0.357  0.282  0.207  0.232  0.108  0.083  0.481 -0.017  0.033  0.207 -0.092  0.133 -0.092  0.556 -0.017  0.232  0.058  0.506 -0.017  0.083  0.556  0.407  0.481  0.182  0.232  0.058  0.531  0.058  0.606  0.506  0.257 -0.241  0.133  0.207  0.332  0.481  0.282  0.382 -0.067  0.481  0.706  0.207  0.506  0.506 -0.142 -0.042  0.008  0.108 -0.166 -0.117 -0.191  0.033  0.207 -0.017  0.207  0.058  0.033  0.083 -0.117  0.033 -0.067 -0.142 -0.042 -0.117  0.133 -0.042  0.008 -0.042 -0.117 -0.092  0.033  0.008 -0.042  0.008  0.207 -0.166 -0.216 -0.241 -0.017 -0.216 -0.092  0.033  0.083 -0.117 -0.191  0.058  0.133  0.157 -0.117  0.531 -0.092  0.133 -0.191 -0.266 
 0.256  0.355  0.380  0.480  0.629  0.455  0.355  0.281  0.206  0.231  0.106  0.081  0.505  0.006  0.031  0.256 -0.093  0.131 -0.093  0.555 -0.018  0.206  0.106  0.530 -0.018  0.081  0.555  0.405  0.455  0.181  0.256  0.056  0.530  0.106  0.604  0.530  0.256 -0.243  0.131  0.206  0.305  0.480  0.256  0.380 -0.068  0.480  0.679  0.181  0.480  0.505 -0.118 -0.043  0.006  0.106 -0.168 -0.118 -0.168  0.006  0.206 -0.018  0.181  0.056  0.081  0.081 -0.118  0.031 -0.093 -0.143 -0.018 -0.118  0.131 -0.043  0.006 -0.043 -0.118 -0.093  0.031  0.006 -0.043  0.006  0.206 -0.168 -0.218 -0.243 -0.043 -0.218 -0.068  0.031  0.081 -0.068 -0.193  0.081  0.131  0.156 -0.118  0.530 -0.093  0.056 -0.193 -0.268 
 0.252  0.351  0.376  0.476  0.600  0.451  0.351  0.252  0.202  0.227  0.152  0.077  0.501  0.027  0.052  0.426 -0.047  0.127 -0.097  0.551 -0.022  0.202  0.127  0.526  0.002  0.077  0.526  0.401  0.451  0.202  0.277  0.077  0.476  0.102  0.575  0.551  0.252 -0.247  0.102  0.227  0.277  0.476  0.252  0.476 -0.097  0.476  0.650  0.252  0.476  0.501 -0.097 -0.022  0.002  0.127 -0.172 -0.147 -0.172  0.002  0.177  0.027  0.152  0.052  0.077  0.052 -0.147 -0.022 -0.097 -0.122  0.002 -0.147  0.127  0.002  0.002 -0.022 -0.122 -0.097  0.052  0.002 -0.022  0.002  0.202 -0.147 -0.222 -0.247 -0.047 -0.222 -0.047  0.052  0.077 -0.072 -0.197  0.102  0.102  0.127 -0.122  0.526 -0.097  0.077 -0.197 -0.272 
 0.250  0.350  0.375  0.474  0.599  0.449  0.350  0.250  0.200  0.225  0.150  0.076  0.524  0.026  0.076  0.425 -0.049  0.126 -0.099  0.549 -0.024  0.200  0.126  0.599  0.001  0.076  0.499  0.400  0.425  0.250  0.275  0.076  0.474  0.175  0.574  0.549  0.250 -0.248  0.101  0.250  0.275  0.474  0.250  0.499 -0.099  0.474  0.649  0.275  0.474  0.449 -0.099 -0.024  0.001  0.101 -0.173 -0.148 -0.173  0.001  0.175 -0.024  0.150  0.001  0.076  0.051 -0.173 -0.024 -0.099 -0.148  0.026 -0.148  0.126  0.001 -0.024 -0.074 -0.074 -0.099  0.076  0.001  0.001  0.001  0.175 -0.148 -0.198 -0.248 -0.049 -0.198 -0.049  0.051  0.126 -0.074 -0.198  0.101  0.051  0.101 -0.099  0.524 -0.099  0.076 -0.198 -0.248 
 0.246  0.346  0.396  0.470  0.570  0.396  0.346  0.271  0.171  0.246  0.171  0.072  0.520 -0.003  0.097  0.421 -0.053  0.122 -0.103  0.545 -0.028  0.221  0.146  0.645 -0.003  0.072  0.495  0.396  0.396  0.246  0.271  0.072  0.470  0.171  0.570  0.545  0.246 -0.252  0.097  0.246  0.271  0.470  0.271  0.520 -0.128  0.470  0.645  0.296  0.470  0.421 -0.103 -0.028 -0.003  0.097 -0.202 -0.152 -0.177 -0.028  0.171 -0.078  0.171 -0.028  0.072  0.047 -0.177 -0.028 -0.103 -0.152  0.022 -0.152  0.122  0.047 -0.003 -0.078 -0.053 -0.103  0.072  0.022 -0.003 -0.003  0.146 -0.152 -0.227 -0.252 -0.053 -0.202 -0.053  0.047  0.122 -0.078 -0.227  0.097  0.047  0.097 -0.128  0.520 -0.103  0.072 -0.202 -0.227 
 0.297  0.347  0.397  0.472  0.571  0.397  0.347  0.273  0.148  0.248  0.148  0.073  0.522 -0.001  0.123  0.422 -0.051  0.123 -0.101  0.547 -0.026  0.223  0.148  0.646 -0.026  0.073  0.497  0.397  0.397  0.223  0.273  0.073  0.447  0.173  0.522  0.547  0.248 -0.226  0.098  0.248  0.273  0.472  0.273  0.547 -0.126  0.472  0.646  0.297  0.472  0.422 -0.101 -0.026 -0.001  0.098 -0.201 -0.151 -0.176 -0.026  0.148 -0.101  0.173 -0.026  0.073  0.048 -0.176 -0.026 -0.101 -0.176  0.023 -0.151  0.123  0.073 -0.001 -0.076 -0.001 -0.101  0.073  0.048 -0.001 -0.026  0.123 -0.151 -0.201 -0.251 -0.076 -0.201 -0.051  0.048  0.123 -0.076 -0.226  0.123  0.048  0.098 -0.126  0.522 -0.101  0.048 -0.201 -0.226 
 0.322  0.347  0.397  0.497  0.596  0.397  0.347  0.273  0.148  0.248  0.148  0.073  0.497 -0.001  0.123  0.422 -0.051  0.123 -0.101  0.547 -0.026  0.223  0.148  0.621 -0.026  0.073  0.522  0.372  0.397  0.198  0.273  0.073  0.422  0.173  0.522  0.571  0.248 -0.226  0.098  0.223  0.273  0.472  0.273  0.547 -0.126  0.472  0.646  0.273  0.472  0.422 -0.076 -0.026 -0.001  0.098 -0.201 -0.151 -0.176 -0.026  0.148 -0.101  0.173 -0.026  0.073  0.048 -0.151 -0.026 -0.101 -0.176  0.023 -0.151  0.098  0.098 -0.026 -0.101 -0.001 -0.101  0.073  0.048 -0.001 -0.026  0.123 -0.151 -0.201 -0.251 -0.076 -0.226 -0.051  0.023  0.123 -0.101 -0.226  0.123  0.048  0.098 -0.151  0.522 -0.101  0.048 -0.201 -0.226 
 0.320  0.345  0.395  0.494  0.594  0.395  0.345  0.270  0.170  0.245  0.145  0.071  0.494 -0.004  0.121  0.420 -0.054  0.121 -0.104  0.544 -0.004  0.220  0.145  0.644 -0.029  0.071  0.494  0.370  0.420  0.195  0.270  0.071  0.420  0.170  0.519  0.569  0.245 -0.228  0.096  0.270  0.270  0.469  0.270  0.544 -0.104  0.469  0.644  0.295  0.469  0.420 -0.079 -0.029 -0.004  0.096 -0.203 -0.153 -0.178 -0.029  0.145 -0.079  0.170 -0.029  0.071  0.046 -0.178 -0.029 -0.104 -0.178  0.021 -0.153  0.121  0.145 -0.004 -0.104 -0.004 -0.104  0.071  0.071 -0.004 -0.029  0.121 -0.153 -0.178 -0.253 -0.079 -0.228 -0.054  0.046  0.121 -0.104 -0.228  0.121  0.071  0.096 -0.129  0.519 -0.104  0.046 -0.203 -0.228 
 0.319  0.344  0.394  0.494  0.593  0.394  0.344  0.270  0.195  0.245  0.145  0.070  0.494 -0.004  0.120  0.419 -0.054  0.120 -0.104  0.544 -0.004  0.220  0.120  0.643 -0.004  0.070  0.494  0.369  0.419  0.195  0.270  0.070  0.444  0.170  0.519  0.568  0.245 -0.229  0.095  0.270  0.220  0.469  0.220  0.544 -0.104  0.469  0.643  0.294  0.469  0.419 -0.054 -0.029 -0.004  0.095 -0.204 -0.154 -0.179 -0.029  0.145 -0.079  0.170 -0.029  0.070  0.045 -0.179 -0.054 -0.129 -0.179  0.020 -0.154  0.120  0.145 -0.004 -0.104 -0.004 -0.104  0.045  0.070 -0.004 -0.029  0.120 -0.154 -0.179 -0.254 -0.079 -0.254 -0.054  0.045  0.120 -0.079 -0.229  0.120  0.070  0.095 -0.129  0.519 -0.129  0.045 -0.204 -0.229 
 0.270  0.295  0.220  0.469  0.594  0.295  0.320  0.195  0.220  0.320  0.170  0.046  0.395  0.046 -0.054  0.320 -0.079  0.121 -0.079  0.544 -0.029  0.245  0.121  0.644  0.021  0.096  0.420  0.370  0.395  0.170  0.345  0.046  0.395  0.046  0.469  0.494  0.245 -0.178  0.021  0.295  0.245  0.494  0.195  0.494 -0.029  0.420  0.569  0.270  0.494  0.395 -0.004  0.046  0.071  0.046 -0.129 -0.178 -0.153  0.021  0.145 -0.004  0.170 -0.004  0.071  0.071 -0.129 -0.054 -0.104 -0.153  0.021 -0.153  0.170  0.071  0.046 -0.054 -0.054 -0.054 -0.029  0.046 -0.004 -0.054  0.170 -0.153 -0.153 -0.203 -0.079 -0.203 -0.054  0.096  0.046 -0.029 -0.153  0.096 -0.004  0.096 -0.079  0.519 -0.104 -0.029 -0.153 -0.203 
 0.208  0.283  0.208  0.307  0.557  0.332  0.332  0.233  0.133  0.258  0.133  0.108  0.382  0.008 -0.016  0.258 -0.041  0.058 -0.091  0.482 -0.066  0.283  0.058  0.557  0.033  0.133  0.357  0.382  0.357  0.208  0.283  0.058  0.183 -0.016  0.382  0.457  0.158 -0.141 -0.041  0.233  0.108  0.432  0.208  0.407  0.008  0.407  0.557  0.208  0.457  0.332 -0.041  0.033  0.108  0.033 -0.066 -0.116 -0.066  0.008  0.158 -0.041  0.183 -0.016  0.058  0.033 -0.066 -0.016 -0.041 -0.091 -0.066 -0.066  0.208 -0.041  0.058 -0.066 -0.041  0.033 -0.016 -0.091  0.008 -0.066  0.108 -0.066 -0.166 -0.166 -0.066 -0.116 -0.016  0.133 -0.041 -0.041 -0.116  0.058 -0.016 -0.016 -0.041  0.482 -0.116 -0.041 -0.066 -0.116 
 0.201  0.251  0.176  0.276  0.550  0.350  0.300  0.176  0.101  0.251  0.101  0.126  0.375 -0.023  0.001  0.176 -0.023  0.076 -0.098  0.450 -0.048  0.276  0.051  0.550  0.026  0.151  0.350  0.400  0.375  0.226  0.276  0.051  0.176 -0.048  0.300  0.475  0.126 -0.123 -0.048  0.201  0.051  0.375  0.176  0.325  0.001  0.425  0.550  0.226  0.475  0.300 -0.023  0.051  0.101 -0.048 -0.048 -0.098 -0.048  0.026  0.201 -0.023  0.151  0.001  0.026 -0.023 -0.048  0.001 -0.048 -0.123 -0.073 -0.073  0.201 -0.023  0.076 -0.098 -0.023  0.051 -0.048 -0.073  0.001 -0.073  0.076 -0.048 -0.148 -0.148 -0.048 -0.098 -0.048  0.126 -0.048 -0.023 -0.098  0.076  0.001  0.026 -0.048  0.425 -0.098 -0.048 -0.073 -0.123 
 0.224  0.224  0.099  0.249  0.498  0.298  0.249  0.174  0.049  0.224  0.049  0.124  0.298 -0.000  0.024  0.149 -0.000  0.024 -0.075  0.398 -0.025  0.274  0.024  0.523  0.049  0.149  0.348  0.348  0.298  0.199  0.249  0.049  0.124 -0.050  0.298  0.448  0.149 -0.100 -0.075  0.099 -0.000  0.323  0.149  0.274 -0.000  0.423  0.548  0.224  0.498  0.249 -0.025  0.024  0.049 -0.075 -0.025 -0.075 -0.050  0.024  0.224 -0.000  0.099  0.024 -0.050 -0.000 -0.025  0.024 -0.075 -0.100 -0.050 -0.050  0.199 -0.000  0.099 -0.100 -0.025  0.074 -0.050 -0.075  0.024 -0.075  0.049 -0.025 -0.125 -0.125 -0.075 -0.075 -0.050  0.124 -0.050 -0.000 -0.100  0.099 -0.000  0.024 -0.050  0.373 -0.075 -0.050 -0.075 -0.100 
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 0.010 -0.039  0.035 -0.039 -0.014 -0.039 -0.039 -0.014  0.010 -0.039  0.010 -0.039 -0.014 -0.039 -0.014  0.010  0.010 -0.039  0.060 -0.039 -0.014  0.060 -0.014 -0.014 -0.014  0.010 -0.014 -0.014 -0.014  0.010 -0.014 -0.039  0.010 -0.014  0.010 -0.014  0.010 -0.039  0.010  0.035 -0.014  0.010 -0.014  0.085  0.035  0.060  0.010  0.010 -0.014  0.010 -0.014  0.060  0.010  0.085 -0.014  0.035 -0.014  0.035  0.035  0.010  0.633 -0.014  0.035  0.035  0.010 -0.039  0.010 -0.039  0.035 -0.014  0.035  0.334 -0.039  0.010 -0.039  0.035  0.010  0.035 -0.039 -0.014  0.085 -0.014  0.035  0.010  0.060  0.035  0.060  0.035  0.135 -0.039 -0.014 -0.014 -0.014  0.035  0.110  0.010  0.010 -0.014 -0.014 -0.039 
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-0.000 -0.100 -0.025  0.024  0.274 -0.050 -0.025 -0.000  0.049 -0.225 -0.150 -0.050  0.199 -0.175 -0.000 -0.025 -0.000 -0.125  0.323 -0.050 -0.125  0.224 -0.075  0.049 -0.025  0.224  0.024 -0.075  0.149 -0.050 -0.025 -0.125 -0.125  0.174  0.124 -0.200  0.174 -0.100 -0.075  0.323  0.149  0.049  0.174  0.373 -0.100  0.149 -0.000  0.373  0.074  0.224  0.224  0.249 -0.000  0.498 -0.225  0.274  0.049  0.473  0.174 -0.025  0.772 -0.100 -0.050 -0.025  0.049  0.074 -0.025 -0.200 -0.125 -0.000  0.348  0.697 -0.025 -0.000  0.249  0.099 -0.025  0.024 -0.025  0.099  0.199  0.298  0.024 -0.050  0.099  0.174  0.099  0.697  0.772 -0.100  0.099  0.174  0.124  0.124  0.747 -0.050  0.049  0.149 -0.025 -0.025 
-0.014 -0.114 -0.014  0.011  0.235 -0.014 -0.014 -0.014  0.036 -0.213 -0.139 -0.014  0.210 -0.114 -0.014 -0.039 -0.039 -0.139  0.285 -0.064 -0.114  0.235 -0.089  0.111 -0.039  0.260 -0.014 -0.089  0.185 -0.064 -0.014 -0.139 -0.139  0.185  0.111 -0.188  0.235 -0.114 -0.089  0.335  0.136  0.061  0.185  0.509 -0.089  0.136 -0.014  0.410  0.086  0.285  0.260  0.260  0.011  0.609 -0.238  0.310  0.036  0.459  0.185 -0.064  0.758 -0.139 -0.064 -0.039  0.111  0.136 -0.014 -0.213 -0.139 -0.014  0.335  0.659 -0.039 -0.014  0.235  0.111  0.011 -0.014 -0.014  0.086  0.185  0.385  0.011 -0.064  0.086  0.160  0.086  0.684  0.758 -0.114  0.086  0.160  0.111  0.111  0.733 -0.064  0.061  0.160 -0.039 -0.039 
 0.023 -0.052 -0.002  0.023  0.222 -0.002 -0.027 -0.027  0.048 -0.226 -0.102 -0.002  0.197 -0.127 -0.027 -0.052 -0.052 -0.151  0.272 -0.052 -0.127  0.247 -0.102  0.123 -0.052  0.297 -0.002 -0.077  0.222 -0.077  0.023 -0.127 -0.151  0.172  0.147 -0.201  0.222 -0.077 -0.077  0.347  0.123  0.073  0.197  0.546 -0.077  0.123 -0.027  0.397  0.098  0.297  0.322  0.322  0.023  0.621 -0.251  0.347  0.023  0.446  0.272 -0.077  0.745 -0.102 -0.027 -0.027  0.098  0.147 -0.002 -0.226 -0.127 -0.052  0.322  0.646 -0.027  0.023  0.272  0.147  0.048 -0.002 -0.002  0.147  0.197  0.422 -0.027 -0.077  0.073  0.147  0.098  0.671  0.745 -0.127  0.073  0.172  0.098  0.123  0.720 -0.077  0.048  0.147 -0.052 -0.052 
 0.017 -0.057 -0.007  0.042  0.217  0.042  0.017 -0.007  0.042 -0.232 -0.082  0.017  0.217 -0.132 -0.032 -0.057 -0.057 -0.157  0.267 -0.057 -0.107  0.242 -0.107  0.142 -0.057  0.291  0.017 -0.057  0.267 -0.007  0.017 -0.132 -0.157  0.167  0.167 -0.157  0.217 -0.082 -0.082  0.341  0.142  0.067  0.217  0.566 -0.057  0.142 -0.032  0.416  0.092  0.291  0.341  0.341  0.017  0.640 -0.257  0.391  0.042  0.441  0.291 -0.082  0.740 -0.107  0.017 -0.007  0.117  0.142 -0.032 -0.232 -0.132 -0.057  0.316  0.590 -0.032  0.042  0.291  0.142  0.067 -0.007 -0.007  0.142  0.217  0.416  0.017 -0.082  0.067  0.142  0.142  0.640  0.740 -0.132  0.067  0.192  0.117  0.117  0.715 -0.082  0.067  0.142 -0.032 -0.057 
 0.087 -0.037 -0.012  0.062  0.187  0.037 -0.037 -0.012  0.037 -0.237 -0.062  0.012  0.212 -0.137 -0.037 -0.062 -0.062 -0.162  0.262 -0.062 -0.112  0.237 -0.112  0.137 -0.062  0.262  0.012 -0.037  0.262  0.012  0.012 -0.137 -0.162  0.162  0.162 -0.137  0.212 -0.087 -0.087  0.336  0.137  0.062  0.212  0.610 -0.062  0.162 -0.037  0.436  0.112  0.311  0.361  0.361  0.012  0.635 -0.262  0.386  0.037  0.436  0.311 -0.037  0.735 -0.087  0.012 -0.012  0.137  0.162 -0.012 -0.237 -0.162 -0.087  0.311  0.585 -0.037  0.037  0.311  0.137  0.087 -0.012 -0.012  0.137  0.262  0.411  0.037 -0.112  0.037  0.137  0.137  0.635  0.735 -0.137  0.062  0.212  0.137  0.112  0.710 -0.087  0.062  0.137 -0.037 -0.037 
 0.086  0.011 -0.013  0.061  0.186  0.061 -0.038 -0.013  0.036 -0.238 -0.063  0.036  0.211 -0.138 -0.038 -0.038 -0.063 -0.163  0.261 -0.063 -0.113  0.236 -0.138  0.111 -0.088  0.285  0.011 -0.063  0.261  0.011  0.011 -0.138 -0.163  0.111  0.186 -0.138  0.211 -0.088 -0.088  0.335  0.136  0.086  0.211  0.634 -0.063  0.186 -0.038  0.435  0.111  0.310  0.360  0.335  0.036  0.634 -0.263  0.385  0.061  0.460  0.310 -0.038  0.734 -0.088  0.011 -0.013  0.136  0.186 -0.013 -0.238 -0.163 -0.088  0.335  0.560 -0.038  0.036  0.310  0.136  0.111 -0.013 -0.013  0.136  0.261  0.410  0.011 -0.113  0.036  0.136  0.136  0.634  0.709 -0.113  0.061  0.211  0.136  0.111  0.684 -0.088  0.061  0.136 -0.038 -0.063 
 0.181  0.031 -0.018  0.081  0.206  0.081  0.006 -0.043  0.031 -0.243  0.006  0.081  0.231 -0.143 -0.018 -0.043 -0.068 -0.168  0.256 -0.068 -0.118  0.231 -0.143  0.106 -0.068  0.281  0.006 -0.043  0.281  0.006  0.031 -0.068 -0.168  0.106  0.181 -0.043  0.256 -0.093 -0.093  0.355  0.131  0.106  0.206  0.654 -0.093  0.181 -0.043  0.430  0.131  0.305  0.430  0.330  0.031  0.604 -0.268  0.380  0.056  0.455  0.330 -0.043  0.729 -0.068 -0.018 -0.018  0.156  0.181  0.006 -0.243 -0.143 -0.093  0.330  0.505 -0.043  0.006  0.305  0.131  0.106 -0.018  0.006  0.131  0.256  0.380 -0.018 -0.143  0.031  0.131  0.131  0.604  0.704 -0.093  0.056  0.206  0.131  0.106  0.679 -0.093  0.031  0.131 -0.068 -0.068 
 0.208  0.059 -0.016  0.084  0.183  0.084  0.034 -0.066  0.034 -0.240  0.009  0.084  0.233 -0.141  0.009 -0.041 -0.066 -0.165  0.258 -0.066 -0.116  0.233 -0.141  0.109 -0.066  0.283  0.009 -0.041  0.283 -0.016  0.034 -0.066 -0.165  0.109  0.183 -0.066  0.258 -0.091 -0.091  0.383  0.134  0.109  0.208  0.657 -0.116  0.183 -0.041  0.408  0.134  0.333  0.457  0.333  0.059  0.607 -0.265  0.383  0.034  0.457  0.358 -0.066  0.682 -0.066 -0.016 -0.016  0.158  0.183 -0.016 -0.240 -0.141 -0.066  0.333  0.482 -0.066  0.009  0.308  0.134  0.084 -0.016  0.009  0.158  0.283  0.383  0.009 -0.165  0.034  0.134  0.109  0.607  0.682 -0.091  0.059  0.208  0.134  0.109  0.682 -0.091  0.034  0.134 -0.016 -0.066 
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 0.004  0.004 -0.020  0.004  0.079 -0.020  0.029 -0.020  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.029  0.029 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.054  0.029  0.029 -0.020  0.004  0.029  0.004  0.079 -0.020  0.029 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.129  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.054 -0.020  0.029  0.029  0.004  0.029 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.004  0.004 -0.020  0.004  0.079 -0.020  0.029 -0.020  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.029  0.029  0.029 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.054  0.029  0.029 -0.020  0.004  0.029  0.004  0.079 -0.020  0.029 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.129  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.054 -0.020  0.029  0.029  0.004  0.029 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.019  0.019 -0.030 -0.005  0.069 -0.030  0.019 -0.030  0.019 -0.030  0.044 -0.030 -0.005 -0.030  0.069  0.019  0.019 -0.005  0.044 -0.030 -0.005 -0.005 -0.030 -0.005 -0.030 -0.030 -0.005 -0.005 -0.005 -0.005 -0.030 -0.030 -0.030 -0.005  0.019 -0.030  0.069  0.044  0.119 -0.005  0.069  0.069  0.019  0.094 -0.030  0.019 -0.030  0.019 -0.005 -0.005 -0.005 -0.005  0.019 -0.030 -0.030 -0.005  0.044 -0.030 -0.005 -0.005  0.269 -0.005 -0.005  0.019 -0.005  0.019 -0.030 -0.005 -0.030  0.019  0.094  0.069  0.019  0.069  0.019  0.044  0.044 -0.030 -0.030  0.019 -0.005  0.019 -0.005 -0.005  0.094 -0.005  0.044 -0.005 -0.005 -0.030  0.019  0.019 -0.030  0.019  0.019 -0.030 -0.030 -0.030  0.044 -0.005 
 0.009  0.059 -0.066 -0.041  0.084 -0.066  0.034 -0.066  0.009 -0.016  0.059 -0.066 -0.041 -0.016  0.034  0.009 -0.016  0.034  0.084 -0.041 -0.041  0.034 -0.041 -0.041  0.034 -0.066 -0.041  0.009  0.009 -0.041  0.009 -0.066 -0.041  0.009  0.084 -0.016  0.109  0.034  0.109 -0.041  0.333  0.059  0.009  0.208 -0.066  0.059 -0.066 -0.016  0.034  0.009  0.009 -0.016  0.059  0.009 -0.066 -0.041  0.034  0.009  0.009 -0.016  0.507 -0.041 -0.041 -0.016  0.009  0.009 -0.066 -0.016 -0.066  0.009  0.134  0.059 -0.016  0.109  0.059  0.134  0.009 -0.066 -0.066  0.034 -0.016  0.059 -0.016 -0.016  0.158  0.009  0.084  0.009  0.034 -0.016  0.034  0.084 -0.066  0.059  0.109 -0.041 -0.066 -0.041  0.034 -0.016 
 0.033  0.108 -0.016 -0.066  0.108 -0.091  0.033 -0.116 -0.041 -0.041  0.158 -0.066 -0.041 -0.066  0.158  0.058 -0.066  0.033  0.083 -0.016 -0.091  0.058 -0.091 -0.066  0.058 -0.091 -0.066  0.058  0.033 -0.066  0.083 -0.116 -0.041  0.058  0.133  0.008  0.083  0.058  0.133  0.008  0.407  0.058  0.008  0.357 -0.091  0.133 -0.041  0.033 -0.016  0.033  0.058  0.033  0.058  0.008 -0.116 -0.041  0.008  0.108  0.058 -0.041  0.631 -0.066 -0.066 -0.016  0.058  0.008 -0.091 -0.041 -0.066  0.033  0.133  0.083 -0.066  0.108  0.058  0.183 -0.016  0.008 -0.066  0.183 -0.066  0.258 -0.016 -0.066  0.183  0.083  0.083 -0.016  0.033 -0.041  0.008  0.083 -0.066  0.058  0.108 -0.066 -0.091 -0.066  0.033  0.008 
 0.136  0.160 -0.089 -0.064  0.111 -0.089 -0.039 -0.114 -0.064 -0.039  0.310 -0.089 -0.039 -0.064  0.185  0.086 -0.089 -0.039  0.061 -0.064 -0.139  0.111 -0.163  0.011  0.260 -0.014 -0.039  0.136 -0.014 -0.089  0.160 -0.139 -0.064 -0.014  0.136 -0.014  0.185 -0.014  0.160  0.061  0.559  0.136 -0.039  0.584 -0.163  0.160  0.011 -0.014 -0.039 -0.014  0.061  0.260  0.061 -0.039 -0.188  0.086  0.011  0.210  0.036 -0.064  0.808 -0.039 -0.064 -0.014  0.036 -0.014 -0.139 -0.039 -0.114  0.011  0.086  0.061 -0.064  0.136  0.111  0.160 -0.014 -0.014 -0.089  0.335 -0.089  0.434 -0.014 -0.139  0.111  0.185  0.061  0.061  0.185 -0.089 -0.014  0.036 -0.089  0.160  0.235 -0.089 -0.089 -0.114 -0.014 -0.014 
 0.175  0.200 -0.099 -0.074  0.076 -0.074 -0.049 -0.124 -0.099 -0.074  0.325 -0.049 -0.024 -0.074  0.200  0.076 -0.124 -0.099  0.051 -0.074 -0.148  0.150 -0.198  0.001  0.300  0.051 -0.024  0.126  0.026 -0.099  0.200 -0.124 -0.074 -0.049  0.126 -0.024  0.200 -0.049  0.126  0.026  0.549  0.126 -0.074  0.674 -0.148  0.250  0.026  0.026 -0.049 -0.049  0.051  0.250  0.051 -0.024 -0.198  0.200 -0.024  0.275  0.001 -0.074  0.798 -0.074 -0.074 -0.049  0.051 -0.049 -0.173 -0.024 -0.148  0.001  0.051  0.026 -0.074  0.126  0.126  0.126 -0.024  0.001 -0.049  0.474 -0.074  0.474  0.026 -0.148  0.101  0.275  0.076  0.076  0.225 -0.099 -0.024  0.001 -0.124  0.175  0.200 -0.049 -0.049 -0.148 -0.049 -0.024 
 0.217  0.192 -0.132 -0.107  0.118 -0.007 -0.057 -0.132 -0.082 -0.082  0.342  0.043 -0.007 -0.032  0.167  0.043 -0.057 -0.107  0.093 -0.057 -0.181  0.192 -0.231 -0.032  0.342  0.068  0.043  0.142  0.118 -0.107  0.217 -0.132 -0.107 -0.057  0.118 -0.032  0.217 -0.132  0.093 -0.007  0.541  0.192 -0.082  0.715 -0.156  0.242  0.018  0.093 -0.032 -0.007  0.018  0.317  0.093 -0.032 -0.181  0.242 -0.007  0.242  0.018 -0.107  0.765 -0.032 -0.082 -0.132  0.018 -0.107 -0.181 -0.032 -0.181 -0.032  0.043  0.043 -0.057  0.167  0.093  0.068 -0.057  0.018 -0.007  0.516 -0.057  0.516  0.043 -0.181  0.043  0.267  0.068  0.118  0.267 -0.107 -0.032 -0.007 -0.132  0.217  0.167 -0.057 -0.057 -0.156 -0.107 -0.057 
 0.257  0.182 -0.117 -0.067  0.133 -0.042 -0.092 -0.142 -0.092 -0.092  0.357  0.008  0.008 -0.017  0.182  0.008 -0.042 -0.117  0.083 -0.042 -0.166  0.157 -0.216 -0.017  0.332  0.083  0.058  0.133  0.133 -0.092  0.207 -0.166 -0.117 -0.042  0.108 -0.017  0.207 -0.142  0.083  0.008  0.531  0.182 -0.092  0.706 -0.142  0.232  0.008  0.108 -0.017 -0.017  0.008  0.357  0.108  0.008 -0.166  0.232 -0.017  0.232  0.008 -0.117  0.755 -0.042 -0.092 -0.142  0.008 -0.117 -0.191 -0.092 -0.166  0.008  0.033  0.033 -0.092  0.157  0.133  0.058 -0.067  0.033 -0.017  0.531 -0.067  0.481  0.058 -0.166  0.033  0.257  0.058  0.083  0.257 -0.092 -0.042  0.008 -0.142  0.182  0.157 -0.092 -0.067 -0.166 -0.117 -0.067 
 0.270  0.170 -0.178 -0.079  0.121 -0.004 -0.104 -0.153 -0.079 -0.079  0.370  0.046  0.046 -0.029  0.195 -0.004 -0.004 -0.129  0.046 -0.054 -0.178  0.170 -0.253 -0.029  0.320  0.071  0.071  0.145  0.145 -0.079  0.220 -0.178 -0.129 -0.054  0.096 -0.004  0.195 -0.153  0.046 -0.004  0.420  0.245 -0.104  0.669 -0.153  0.195 -0.029  0.096 -0.029 -0.004  0.021  0.345  0.121 -0.004 -0.153  0.220 -0.054  0.220 -0.004 -0.104  0.619 -0.054 -0.054 -0.178 -0.004 -0.104 -0.203 -0.079 -0.178 -0.004  0.021  0.021 -0.054  0.145  0.121  0.021 -0.079  0.021 -0.004  0.569 -0.104  0.494  0.121 -0.178  0.021  0.245  0.021  0.071  0.245 -0.079 -0.054  0.021 -0.153  0.170  0.121 -0.104 -0.079 -0.153 -0.104 -0.054 
 0.269  0.144 -0.180 -0.080  0.144 -0.005 -0.105 -0.130 -0.105 -0.080  0.368  0.069  0.094 -0.030  0.219 -0.030  0.019 -0.130  0.044 -0.055 -0.180  0.144 -0.230 -0.030  0.318  0.069  0.044  0.144  0.119 -0.055  0.269 -0.205 -0.155 -0.055  0.069 -0.005  0.194 -0.130  0.044 -0.005  0.393  0.219 -0.105  0.642 -0.155  0.219 -0.055  0.069 -0.055 -0.005  0.019  0.343  0.144  0.044 -0.130  0.194 -0.080  0.194 -0.030 -0.105  0.393 -0.030 -0.080 -0.180 -0.005 -0.080 -0.180 -0.080 -0.155  0.044 -0.005  0.019 -0.080  0.169  0.094  0.044 -0.080  0.019 -0.005  0.568 -0.130  0.493  0.144 -0.205  0.019  0.219  0.019  0.019  0.219 -0.080 -0.055  0.019 -0.105  0.169  0.094 -0.130 -0.080 -0.155 -0.055 -0.055 
 0.256  0.106 -0.168 -0.093  0.156 -0.018 -0.093 -0.168 -0.068 -0.093  0.405  0.056  0.131 -0.018  0.256 -0.043  0.056 -0.143  0.006 -0.043 -0.168  0.106 -0.193 -0.043  0.305  0.056  0.006  0.106  0.106 -0.043  0.281 -0.218 -0.168 -0.068  0.031 -0.018  0.206 -0.143  0.006 -0.018  0.256  0.181 -0.068  0.629 -0.168  0.181 -0.118  0.106 -0.068 -0.018 -0.018  0.355  0.181  0.081 -0.118  0.106 -0.068  0.206 -0.043 -0.168  0.181 -0.043 -0.068 -0.193 -0.018 -0.093 -0.168 -0.118 -0.143  0.081 -0.018  0.056 -0.093  0.206  0.081  0.031 -0.093  0.031  0.031  0.555 -0.143  0.455  0.206 -0.168 -0.043  0.156  0.006  0.006  0.206 -0.093 -0.068 -0.043 -0.068  0.181  0.056 -0.143 -0.068 -0.143 -0.068 -0.068 
 0.255  0.106 -0.168 -0.069  0.155 -0.019 -0.094 -0.168 -0.069 -0.094  0.405  0.056  0.155 -0.019  0.255 -0.044  0.031 -0.143  0.006 -0.044 -0.168  0.081 -0.193 -0.044  0.305  0.056 -0.069  0.081  0.131  0.006  0.280 -0.218 -0.193 -0.044  0.006 -0.019  0.205 -0.143 -0.019 -0.044  0.180  0.180 -0.069  0.629 -0.168  0.155 -0.119  0.106 -0.069 -0.019 -0.069  0.330  0.180  0.081 -0.119  0.106 -0.069  0.205 -0.069 -0.143  0.081 -0.044 -0.069 -0.193  0.006 -0.094 -0.168 -0.119 -0.143  0.081 -0.019  0.031 -0.094  0.205  0.081  0.006 -0.119  0.031  0.031  0.604 -0.168  0.429  0.230 -0.168 -0.019  0.155  0.006  0.006  0.180 -0.094 -0.094 -0.044 -0.069  0.180  0.056 -0.143 -0.019 -0.168 -0.044 -0.019 
 0.248  0.098 -0.151 -0.076  0.148 -0.026 -0.076 -0.151 -0.051 -0.126  0.397  0.073  0.148  0.048  0.273 -0.076  0.023 -0.101 -0.001 -0.051 -0.176  0.073 -0.176 -0.026  0.273  0.048 -0.076  0.073  0.123 -0.001  0.248 -0.251 -0.201 -0.051 -0.001  0.023  0.148 -0.151 -0.001 -0.101  0.148  0.148 -0.051  0.596 -0.176  0.148 -0.126  0.098 -0.101 -0.026 -0.051  0.322  0.173  0.123 -0.126  0.073 -0.051  0.148 -0.076 -0.201  0.048 -0.076 -0.051 -0.226 -0.026 -0.076 -0.126 -0.101 -0.151  0.048 -0.026 -0.001 -0.101  0.223  0.073 -0.001 -0.126  0.023  0.048  0.596 -0.126  0.397  0.223 -0.101 -0.051  0.098 -0.001  0.023  0.173 -0.101 -0.126 -0.051 -0.101  0.123  0.023 -0.151 -0.026 -0.226 -0.001 -0.026 
 0.245  0.070 -0.154 -0.029  0.145 -0.004 -0.079 -0.154 -0.029 -0.129  0.394  0.045  0.145  0.045  0.270 -0.079  0.020 -0.104 -0.004 -0.054 -0.179  0.070 -0.204 -0.029  0.270  0.045 -0.079  0.070  0.120 -0.029  0.195 -0.254 -0.204 -0.054  0.020  0.020  0.145 -0.154 -0.004 -0.129  0.070  0.145 -0.054  0.568 -0.179  0.145 -0.129  0.095 -0.104 -0.054 -0.104  0.319  0.170  0.120 -0.104  0.045 -0.029  0.120 -0.079 -0.204  0.020 -0.054 -0.029 -0.229 -0.029 -0.054 -0.129 -0.104 -0.154  0.045 -0.029 -0.004 -0.104  0.220  0.070 -0.004 -0.129  0.045 -0.004  0.593 -0.129  0.394  0.220 -0.079 -0.079  0.095 -0.004  0.020  0.170 -0.104 -0.129 -0.054 -0.104  0.070  0.045 -0.129 -0.029 -0.229 -0.004 -0.029 
 0.217  0.068 -0.156 -0.032  0.192  0.018 -0.082 -0.181 -0.007 -0.132  0.392  0.043  0.093  0.043  0.292 -0.107  0.018 -0.082 -0.007 -0.057 -0.206  0.093 -0.206 -0.032  0.242  0.043 -0.107  0.093  0.118 -0.057  0.192 -0.256 -0.206 -0.057 -0.007  0.018  0.118 -0.132 -0.007 -0.156  0.068  0.118 -0.057  0.541 -0.206  0.118 -0.132  0.093 -0.132 -0.032 -0.132  0.317  0.217  0.167 -0.107  0.068 -0.032  0.068 -0.107 -0.256 -0.007 -0.057 -0.032 -0.181 -0.057 -0.057 -0.132 -0.057 -0.132  0.043 -0.032 -0.082 -0.082  0.242  0.068  0.018 -0.132  0.068 -0.032  0.616 -0.107  0.367  0.242 -0.082 -0.107  0.043 -0.032  0.018  0.142 -0.107 -0.181 -0.107 -0.107  0.043  0.018 -0.181 -0.032 -0.231 -0.007 -0.032 
 0.242  0.067 -0.157 -0.057  0.192  0.042 -0.082 -0.182 -0.007 -0.132  0.391  0.042  0.092  0.067  0.316 -0.107  0.017 -0.082 -0.007 -0.057 -0.257  0.092 -0.207 -0.032  0.242  0.042 -0.107  0.092  0.117 -0.057  0.192 -0.232 -0.207 -0.057 -0.007  0.017  0.117 -0.132 -0.007 -0.157  0.067  0.117 -0.057  0.541 -0.207  0.142 -0.132  0.092 -0.132 -0.032 -0.132  0.316  0.242  0.142 -0.082  0.067 -0.007  0.042 -0.107 -0.257 -0.007 -0.057 -0.007 -0.182 -0.057 -0.057 -0.107 -0.057 -0.132  0.042 -0.032 -0.057 -0.082  0.192  0.067  0.017 -0.132  0.092 -0.057  0.615 -0.107  0.366  0.242 -0.107 -0.107  0.042 -0.032  0.017  0.142 -0.107 -0.182 -0.082 -0.107  0.042  0.042 -0.182 -0.032 -0.232 -0.007 -0.032 
 0.217  0.042 -0.182 -0.082  0.192  0.042 -0.082 -0.182 -0.032 -0.107  0.341  0.042  0.042  0.067  0.316 -0.107  0.017 -0.082 -0.007 -0.107 -0.257  0.117 -0.207 -0.032  0.217  0.017 -0.082  0.142  0.142 -0.057  0.192 -0.257 -0.207 -0.057 -0.032  0.017  0.117 -0.157  0.017 -0.157  0.042  0.117 -0.057  0.541 -0.207  0.117 -0.157  0.117 -0.132 -0.057 -0.132  0.316  0.242  0.092 -0.032  0.067  0.017  0.042 -0.107 -0.257 -0.007 -0.082 -0.007 -0.182 -0.107 -0.057 -0.057 -0.057 -0.107  0.042 -0.057 -0.057 -0.057  0.142  0.092  0.017 -0.132  0.067 -0.057  0.590 -0.157  0.366  0.267 -0.107 -0.132  0.042 -0.057  0.017  0.117 -0.107 -0.157 -0.082 -0.107  0.017  0.042 -0.157 -0.032 -0.232 -0.007 -0.032 
 0.191  0.016 -0.183 -0.083  0.191  0.041 -0.083 -0.208 -0.033 -0.108  0.340  0.041  0.041  0.066  0.266 -0.108  0.016 -0.083 -0.008 -0.108 -0.258  0.141 -0.208 -0.033  0.216  0.016 -0.058  0.116  0.141 -0.058  0.191 -0.258 -0.208 -0.058 -0.033 -0.008  0.116 -0.158  0.016 -0.158  0.041  0.116 -0.058  0.540 -0.208  0.091 -0.183  0.091 -0.133 -0.083 -0.133  0.340  0.241  0.091 -0.008  0.066  0.016 -0.033 -0.108 -0.258 -0.058 -0.083 -0.008 -0.183 -0.108 -0.058 -0.058 -0.058 -0.108  0.041 -0.058 -0.083 -0.058  0.141  0.066  0.041 -0.133  0.041 -0.058  0.589 -0.158  0.340  0.216 -0.083 -0.133  0.041 -0.033  0.016  0.091 -0.133 -0.158 -0.108 -0.108  0.016  0.041 -0.158 -0.008 -0.233 -0.008 -0.033 
 0.166 -0.008 -0.182 -0.083  0.166  0.042 -0.108 -0.232 -0.033 -0.108  0.341  0.042  0.042  0.067  0.291 -0.108  0.017 -0.083 -0.008 -0.157 -0.257  0.142 -0.207 -0.058  0.166 -0.008 -0.058  0.117  0.142 -0.058  0.166 -0.257 -0.232 -0.083 -0.033 -0.008  0.117 -0.182  0.017 -0.182  0.042  0.067 -0.058  0.465 -0.207  0.067 -0.232  0.092 -0.157 -0.108 -0.133  0.341  0.241  0.067 -0.008  0.042 -0.008 -0.083 -0.133 -0.257 -0.083 -0.083 -0.008 -0.182 -0.108 -0.058 -0.058 -0.083 -0.108  0.042 -0.058 -0.083 -0.058  0.067  0.042  0.042 -0.133  0.042 -0.033  0.565 -0.157  0.341  0.191 -0.083 -0.133  0.067 -0.033  0.017  0.092 -0.133 -0.157 -0.133 -0.108  0.042  0.017 -0.157 -0.008 -0.232  0.017 -0.033 
 0.166 -0.008 -0.158 -0.083  0.166  0.041 -0.083 -0.233 -0.033 -0.108  0.340  0.041  0.041  0.041  0.290 -0.108  0.016 -0.083 -0.008 -0.158 -0.258  0.141 -0.208 -0.058  0.166 -0.008 -0.058  0.166  0.116 -0.058  0.166 -0.258 -0.233 -0.083 -0.008 -0.008  0.116 -0.183 -0.008 -0.183 -0.008  0.066 -0.083  0.465 -0.208  0.066 -0.233  0.116 -0.158 -0.108 -0.133  0.365  0.241  0.041 -0.008  0.041  0.041 -0.108 -0.133 -0.258 -0.108 -0.058 -0.008 -0.183 -0.108 -0.058 -0.058 -0.083 -0.083  0.016 -0.058 -0.083 -0.058  0.016  0.016  0.041 -0.133  0.016 -0.008  0.540 -0.158  0.315  0.216 -0.108 -0.133  0.066 -0.033  0.016  0.066 -0.158 -0.183 -0.133 -0.108  0.016 -0.008 -0.158 -0.033 -0.233  0.016 -0.008 
 0.163 -0.011 -0.160 -0.086  0.163  0.039 -0.111 -0.235 -0.036 -0.111  0.288  0.089  0.064  0.039  0.238 -0.111  0.014 -0.086 -0.011 -0.160 -0.285  0.139 -0.210 -0.061  0.163 -0.011 -0.011  0.163  0.089 -0.061  0.188 -0.260 -0.235 -0.086 -0.011  0.014  0.114 -0.185 -0.036 -0.185 -0.011  0.064 -0.086  0.462 -0.210  0.064 -0.235  0.114 -0.160 -0.111 -0.136  0.363  0.238  0.039 -0.011  0.039  0.039 -0.136 -0.136 -0.260 -0.111 -0.061 -0.011 -0.185 -0.086 -0.061 -0.061 -0.086 -0.086  0.014 -0.061 -0.086 -0.061  0.014  0.014  0.039 -0.160  0.014 -0.011  0.562 -0.185  0.313  0.213 -0.111 -0.136  0.064 -0.036  0.014  0.039 -0.160 -0.185 -0.136 -0.111  0.014 -0.011 -0.185 -0.036 -0.210  0.014  0.014 
 0.187 -0.037 -0.137 -0.087  0.087  0.037 -0.062 -0.187 -0.037 -0.112  0.112  0.062  0.062 -0.012  0.162 -0.062 -0.037 -0.012  0.037 -0.112 -0.237  0.012 -0.162 -0.062  0.162  0.037  0.012  0.162  0.137  0.012  0.137 -0.212 -0.212 -0.062  0.012  0.062  0.062 -0.187 -0.037 -0.112  0.062  0.062 -0.137  0.436 -0.212 -0.012 -0.187  0.062 -0.137 -0.037 -0.112  0.311  0.162  0.012 -0.062  0.087  0.012 -0.087 -0.087 -0.212 -0.037 -0.012 -0.062 -0.137 -0.037 -0.037 -0.087 -0.037 -0.162  0.037 -0.062 -0.062 -0.037  0.037  0.037  0.087 -0.112  0.012  0.037  0.511 -0.162  0.262  0.162 -0.087 -0.087  0.062 -0.062  0.012  0.087 -0.112 -0.112 -0.162 -0.087  0.037  0.037 -0.137  0.012 -0.162  0.012  0.037 
 0.239 -0.035 -0.135 -0.085  0.065  0.040 -0.110 -0.110 -0.060 -0.035  0.090  0.040  0.040 -0.035  0.140 -0.010  0.015 -0.010  0.090 -0.060 -0.159  0.040 -0.085 -0.060  0.065  0.015  0.015  0.065  0.164  0.015  0.015 -0.135 -0.159 -0.035  0.090  0.090  0.065 -0.135 -0.110 -0.060  0.115  0.040 -0.060  0.289 -0.135 -0.010 -0.135 -0.010 -0.060  0.015 -0.085  0.115  0.115  0.040 -0.085  0.015 -0.060 -0.135 -0.060 -0.135 -0.010  0.015 -0.110 -0.085 -0.010  0.040 -0.035  0.015 -0.110  0.040 -0.010 -0.035 -0.010  0.040  0.040 -0.035 -0.035 -0.010 -0.060  0.438 -0.135  0.239  0.140 -0.060 -0.085 -0.035  0.015  0.040  0.040 -0.035 -0.110 -0.110 -0.035  0.015  0.040 -0.110  0.015 -0.135 -0.010 -0.010 
 0.204 -0.020 -0.120 -0.095  0.105  0.030 -0.095 -0.120 -0.045 -0.070  0.055 -0.070 -0.020 -0.070  0.080  0.005  0.030  0.005  0.130 -0.045 -0.144  0.080 -0.120 -0.045  0.055  0.005  0.005  0.055  0.154  0.005 -0.020 -0.120 -0.144 -0.020  0.105  0.080  0.080 -0.120 -0.095 -0.070  0.105  0.005 -0.045  0.279 -0.120  0.030 -0.120  0.005 -0.020  0.005 -0.070  0.080  0.130  0.005 -0.070  0.005 -0.070 -0.144 -0.045 -0.144  0.005  0.030 -0.095 -0.070  0.005  0.055 -0.020  0.030 -0.095  0.005 -0.020 -0.020 -0.045  0.005  0.030 -0.045 -0.020 -0.020 -0.045  0.354 -0.144  0.204  0.055 -0.045 -0.070 -0.095  0.030  0.030  0.030 -0.020 -0.095 -0.045 -0.020  0.005  0.030 -0.095  0.030 -0.120 -0.045  0.005 
 0.204  0.004 -0.095 -0.095  0.129  0.004 -0.095 -0.095 -0.020 -0.070  0.029 -0.045 -0.045 -0.045  0.029  0.029  0.004  0.029  0.154 -0.070 -0.120  0.079 -0.095 -0.020  0.004 -0.020  0.029  0.054  0.104  0.029 -0.045 -0.095 -0.120 -0.070  0.129  0.004  0.054 -0.095 -0.070 -0.045  0.104  0.004 -0.070  0.254 -0.095  0.029 -0.095  0.029  0.004  0.004 -0.070  0.054  0.104 -0.045 -0.045  0.004 -0.045 -0.120 -0.070 -0.120  0.054  0.029 -0.070 -0.045 -0.020  0.054  0.004  0.054 -0.095  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.045 -0.045  0.303 -0.120  0.154  0.054 -0.070 -0.045 -0.095  0.004  0.029  0.029 -0.045 -0.070 -0.020 -0.020  0.029  0.029 -0.095  0.054 -0.095 -0.045  0.029 
 0.194 -0.005 -0.080 -0.080  0.144 -0.005 -0.080 -0.080 -0.030 -0.055  0.044 -0.055 -0.080 -0.055 -0.030 -0.005 -0.005  0.044  0.169 -0.055 -0.105  0.069 -0.105 -0.030  0.019 -0.005  0.019  0.044  0.069  0.019 -0.030 -0.080 -0.105 -0.080  0.119  0.019 -0.005 -0.080 -0.030 -0.030  0.094 -0.005 -0.055  0.169 -0.080 -0.030 -0.080  0.019 -0.030 -0.005 -0.080  0.019  0.144 -0.055 -0.030 -0.030 -0.030 -0.105 -0.080 -0.105  0.069  0.044 -0.055 -0.030 -0.030  0.019 -0.005  0.069 -0.080  0.019 -0.005 -0.005 -0.030 -0.030  0.019 -0.005 -0.030 -0.055 -0.030  0.244 -0.105  0.169 -0.005 -0.030 -0.055 -0.080 -0.005  0.069 -0.030 -0.030 -0.055 -0.030 -0.055  0.044  0.019 -0.080  0.069 -0.105 -0.005  0.019 
 0.212  0.012 -0.062 -0.062  0.112 -0.012 -0.062 -0.062 -0.037 -0.037  0.012 -0.062 -0.062 -0.037 -0.062  0.012 -0.012  0.062  0.112 -0.037 -0.087  0.062 -0.087 -0.037  0.012 -0.012  0.037  0.037  0.062  0.012 -0.037 -0.062 -0.087 -0.087  0.137  0.012 -0.012 -0.062 -0.037 -0.062  0.112  0.012 -0.037  0.112 -0.062 -0.062 -0.062 -0.037 -0.037  0.012 -0.087  0.037  0.187 -0.037 -0.037 -0.012 -0.012 -0.087 -0.062 -0.087  0.087  0.037 -0.037 -0.012 -0.012 -0.012 -0.012  0.087 -0.087  0.037  0.012  0.012 -0.012 -0.012  0.012 -0.012 -0.037 -0.037 -0.037  0.087 -0.087  0.162 -0.012 -0.037 -0.062 -0.087 -0.012  0.062 -0.012 -0.062 -0.037 -0.037 -0.062  0.062  0.012 -0.062  0.012 -0.087  0.012 -0.012 
 0.170  0.020 -0.079 -0.054  0.120 -0.004 -0.054 -0.054 -0.029 -0.029  0.020 -0.054 -0.054 -0.054 -0.079 -0.004 -0.004  0.070  0.120 -0.054 -0.079  0.045 -0.079 -0.029  0.020 -0.004  0.045  0.045  0.045  0.020 -0.054 -0.054 -0.079 -0.079  0.145  0.020 -0.029 -0.054 -0.029 -0.054  0.095  0.020 -0.029  0.120 -0.054 -0.079 -0.054 -0.029 -0.029  0.020 -0.079  0.045  0.145 -0.054 -0.029 -0.004 -0.004 -0.079 -0.054 -0.079  0.095 -0.004 -0.029 -0.004 -0.004 -0.029 -0.004  0.095 -0.079  0.020  0.020 -0.004  0.020 -0.004  0.020 -0.004 -0.029 -0.029 -0.029  0.070 -0.079  0.145 -0.004 -0.029 -0.054 -0.079 -0.004  0.070  0.020 -0.054 -0.029 -0.029 -0.054  0.045  0.020 -0.054  0.020 -0.079  0.020 -0.004 
 0.152  0.027 -0.072 -0.047  0.077  0.002 -0.047 -0.047 -0.022 -0.022  0.052 -0.022 -0.047 -0.072 -0.072 -0.022  0.002  0.077  0.102 -0.022 -0.072  0.052 -0.072 -0.047  0.052  0.002  0.027  0.052  0.052  0.027 -0.047 -0.047 -0.072 -0.072  0.102 -0.022 -0.022 -0.047 -0.022 -0.047  0.102  0.027 -0.022  0.077 -0.047 -0.072 -0.072 -0.022 -0.022  0.027 -0.047  0.002  0.127 -0.047 -0.022  0.002 -0.022 -0.072 -0.047 -0.072  0.077  0.002 -0.022 -0.022 -0.022  0.002 -0.022  0.077 -0.072  0.027  0.027  0.002  0.027  0.027  0.027  0.002 -0.047 -0.022 -0.047  0.102 -0.072  0.127  0.002 -0.022 -0.047 -0.047  0.002  0.052  0.027 -0.072 -0.022 -0.047 -0.047  0.052  0.027 -0.047  0.027 -0.072  0.027  0.002 
 0.130  0.030 -0.070 -0.045  0.080  0.005 -0.045 -0.045 -0.020 -0.020  0.030 -0.045 -0.020 -0.070 -0.045 -0.020  0.005  0.080  0.055 -0.020 -0.070  0.055 -0.070 -0.045  0.055  0.005  0.005  0.055  0.055  0.005 -0.045 -0.045 -0.070 -0.070  0.105 -0.020 -0.020 -0.045 -0.045 -0.045  0.105  0.030 -0.020  0.080 -0.045 -0.070 -0.070 -0.020 -0.045  0.005 -0.045  0.005  0.105 -0.045 -0.020  0.005 -0.020 -0.070 -0.045 -0.070  0.080  0.005 -0.020  0.005 -0.020  0.005 -0.020  0.080 -0.070  0.005  0.030  0.005  0.030  0.030  0.030  0.005 -0.045 -0.020 -0.045  0.130 -0.070  0.130  0.005 -0.045 -0.045 -0.045  0.005  0.055  0.030 -0.070 -0.020 -0.045 -0.045  0.080  0.030 -0.045  0.030 -0.070  0.005  0.005 
 0.136  0.011 -0.063 -0.038  0.061  0.011 -0.038 -0.038 -0.038 -0.013  0.011 -0.038 -0.013 -0.063 -0.038 -0.038 -0.013  0.086  0.036 -0.013 -0.063  0.036 -0.063 -0.038  0.061 -0.013  0.011  0.036  0.061  0.011 -0.038 -0.038 -0.063 -0.063  0.086 -0.013 -0.063 -0.038 -0.038 -0.013  0.086 -0.013 -0.013  0.061 -0.038 -0.063 -0.063 -0.013 -0.038  0.011 -0.038 -0.013  0.086 -0.063 -0.013  0.011 -0.013 -0.063 -0.038 -0.063  0.086  0.011 -0.038  0.011 -0.038 -0.013 -0.038  0.086 -0.063  0.011  0.036  0.011  0.036  0.036  0.036  0.011 -0.038 -0.013 -0.038  0.136 -0.063  0.086 -0.013 -0.038 -0.038 -0.038 -0.013  0.036  0.011 -0.063 -0.013 -0.038 -0.013  0.086  0.011 -0.038  0.036 -0.063 -0.013  0.011 
 0.140  0.015 -0.060 -0.035  0.065  0.015 -0.060 -0.035 -0.035 -0.010  0.015 -0.035 -0.035 -0.060 -0.035 -0.035 -0.035  0.040  0.040 -0.010 -0.060  0.040 -0.060 -0.060  0.065 -0.010  0.015  0.040  0.065  0.015 -0.060 -0.035 -0.060 -0.060  0.090 -0.010 -0.060 -0.035 -0.035 -0.010  0.065 -0.010 -0.010  0.065 -0.035 -0.060 -0.060 -0.010 -0.035  0.015 -0.035 -0.010  0.065 -0.060 -0.010  0.015 -0.010 -0.060 -0.035 -0.060  0.090  0.015 -0.035  0.015 -0.035 -0.010 -0.035  0.090 -0.060 -0.010  0.015  0.015  0.040  0.040  0.040  0.015 -0.035 -0.010 -0.060  0.140 -0.060  0.090 -0.035 -0.035 -0.035 -0.035 -0.010  0.015  0.015 -0.060 -0.010 -0.060 -0.010  0.090  0.015 -0.035  0.040 -0.035 -0.010  0.015 
 0.099  0.024 -0.051 -0.026  0.049  0.024 -0.051 -0.026 -0.026 -0.001 -0.001 -0.026 -0.026 -0.051 -0.026 -0.026 -0.026  0.049 -0.026 -0.001 -0.051  0.049 -0.051 -0.051  0.074 -0.001 -0.001  0.049  0.049 -0.001 -0.051 -0.026 -0.051 -0.051  0.074 -0.026 -0.051 -0.026 -0.026 -0.001  0.074 -0.001 -0.026  0.024 -0.051 -0.051 -0.051 -0.001 -0.026  0.024 -0.026 -0.051 -0.001 -0.051 -0.001 -0.026 -0.001 -0.051 -0.026 -0.051  0.049 -0.026 -0.026  0.024 -0.026 -0.026 -0.026  0.074 -0.051 -0.001 -0.001  0.024  0.049  0.024  0.049  0.024 -0.051 -0.001 -0.051  0.124 -0.051  0.049 -0.026 -0.026 -0.026 -0.026 -0.001 -0.001  0.024 -0.051 -0.001 -0.051 -0.026  0.099 -0.001 -0.051  0.049 -0.026 -0.001  0.024 
 0.107  0.032 -0.043 -0.018 -0.018  0.032 -0.043 -0.018 -0.018  0.007 -0.018 -0.018 -0.018 -0.043 -0.018 -0.018 -0.018  0.032 -0.018  0.007 -0.043  0.057 -0.043 -0.043  0.082 -0.018  0.007  0.032  0.057  0.007 -0.043 -0.018 -0.043 -0.043  0.082 -0.018 -0.043 -0.018 -0.018  0.007  0.057  0.007 -0.018  0.032 -0.043 -0.043 -0.043  0.007 -0.018  0.007 -0.018 -0.043  0.007 -0.043 -0.018 -0.043  0.007 -0.043 -0.043 -0.043  0.007 -0.043 -0.018  0.032 -0.018 -0.018 -0.018  0.057 -0.043  0.007 -0.018  0.007  0.007  0.007  0.032  0.032 -0.043 -0.018 -0.043  0.132 -0.043  0.032 -0.018 -0.043 -0.018 -0.018 -0.018  0.007 -0.018 -0.043  0.007 -0.043 -0.018  0.082 -0.018 -0.043  0.007 -0.043 -0.018  0.032 
 0.064  0.039 -0.036 -0.011 -0.011  0.014 -0.036 -0.011 -0.036  0.014 -0.011 -0.011 -0.011 -0.036 -0.011 -0.036 -0.011  0.014 -0.036  0.014 -0.036  0.064 -0.036 -0.036  0.089 -0.011  0.014  0.014  0.064 -0.011 -0.036 -0.011 -0.036 -0.036  0.064 -0.011 -0.036 -0.011 -0.036 -0.011 -0.011  0.014 -0.011  0.014 -0.036 -0.036 -0.036  0.014 -0.011 -0.011 -0.011 -0.036  0.014 -0.036 -0.011 -0.036 -0.011 -0.036 -0.036 -0.036 -0.011 -0.036 -0.011  0.039 -0.011 -0.011 -0.011  0.014 -0.036 -0.011 -0.011 -0.011  0.014  0.014  0.039  0.039 -0.036 -0.036 -0.036  0.064 -0.036  0.014 -0.011 -0.036 -0.011 -0.011 -0.011  0.014 -0.011 -0.036 -0.011 -0.036 -0.011  0.039 -0.011 -0.036  0.014 -0.036 -0.011  0.014 
 0.045  0.045 -0.030 -0.005 -0.005  0.020 -0.030 -0.005 -0.030 -0.005 -0.005 -0.005 -0.005 -0.030 -0.005 -0.030 -0.005 -0.005 -0.030  0.020 -0.030  0.070 -0.030 -0.030  0.070 -0.005  0.020  0.020  0.070 -0.030 -0.030 -0.005 -0.030 -0.030  0.045 -0.005 -0.030 -0.030 -0.030 -0.005 -0.030  0.020 -0.005 -0.005 -0.030 -0.030 -0.030  0.020 -0.005 -0.005 -0.005 -0.030 -0.005 -0.030 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.005 -0.030 -0.005  0.045 -0.005 -0.005 -0.005  0.020 -0.030 -0.005 -0.005 -0.005  0.020  0.020  0.020  0.020 -0.030 -0.030 -0.030  0.045 -0.030  0.020 -0.030 -0.030 -0.005 -0.005 -0.005  0.020 -0.005 -0.030 -0.005 -0.030 -0.005  0.045 -0.005 -0.030 -0.005 -0.030 -0.030  0.020 
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 0.029  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054 -0.020 -0.020  0.054 -0.020  0.029  0.004  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 
 0.029  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054 -0.020 -0.020  0.054 -0.020  0.029  0.004  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.004 
 0.021  0.046 -0.029 -0.004 -0.029 -0.004 -0.004 -0.004 -0.029 -0.004 -0.004 -0.004  0.021 -0.029 -0.004 -0.029  0.021  0.046 -0.004 -0.004 -0.029  0.046 -0.004 -0.004  0.046 -0.029  0.021  0.021  0.046 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.029 -0.029 -0.029 -0.029 -0.004 -0.029  0.071 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.004 -0.004  0.021 -0.029  0.021 -0.004 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004  0.021  0.021  0.046 -0.029  0.021 -0.004 -0.004  0.021  0.046 -0.029 -0.004 -0.029 -0.029 -0.004 -0.004 -0.029  0.021 -0.004 -0.029 -0.004 -0.004 -0.004 -0.004 -0.004 -0.029 -0.004 -0.029  0.021  0.046 -0.004 -0.004 -0.004 -0.029 -0.029 -0.004 
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 0.047 -0.002 -0.152 -0.052 -0.077 -0.052 -0.077 -0.027 -0.052 -0.077  0.022 -0.102 -0.027  0.022 -0.052 -0.077 -0.077  0.197  0.097 -0.102 -0.102  0.172  0.022 -0.052  0.122 -0.052 -0.002 -0.052  0.022 -0.027 -0.027 -0.102 -0.152 -0.127 -0.002  0.122 -0.052 -0.052 -0.102 -0.077 -0.052 -0.052 -0.002 -0.052 -0.152  0.022 -0.177 -0.002 -0.102 -0.002 -0.127 -0.027  0.097  0.072 -0.002 -0.077 -0.052 -0.077 -0.102 -0.102 -0.102  0.022  0.022 -0.002 -0.077 -0.027  0.147 -0.052  0.122  0.097  0.047 -0.052 -0.027  0.047 -0.002  0.022 -0.052 -0.077  0.022  0.247 -0.177  0.247  0.222  0.047  0.047 -0.077  0.022 -0.077 -0.027 -0.127  0.022 -0.027 -0.027 -0.002 -0.077 -0.077 -0.002 -0.027  0.147 -0.102 
 0.036 -0.013 -0.163 -0.063 -0.013 -0.113 -0.113 -0.013 -0.013 -0.088  0.036 -0.113 -0.063  0.086 -0.038 -0.088 -0.063  0.186  0.086 -0.163 -0.163  0.211 -0.013 -0.138  0.061 -0.063 -0.038 -0.063  0.111 -0.038 -0.013 -0.163 -0.213 -0.213  0.011  0.086 -0.063 -0.113 -0.163 -0.163 -0.038 -0.113 -0.038 -0.063 -0.138 -0.013 -0.163  0.061 -0.138 -0.038 -0.188 -0.038  0.061  0.086 -0.038 -0.113 -0.063 -0.063 -0.188 -0.163 -0.163 -0.013 -0.013 -0.038 -0.088 -0.013  0.186 -0.063  0.136  0.161  0.136 -0.088 -0.063 -0.013 -0.038  0.011 -0.138 -0.088  0.086  0.310 -0.238  0.310  0.211  0.061  0.036 -0.138 -0.013 -0.088  0.011 -0.163  0.036 -0.088 -0.038 -0.038 -0.063 -0.113  0.036 -0.013  0.161 -0.138 
 0.063 -0.036 -0.136 -0.111 -0.036 -0.136 -0.086 -0.036 -0.011 -0.086  0.013 -0.061 -0.086  0.063  0.038 -0.111 -0.061  0.113  0.088 -0.186 -0.186  0.213 -0.036 -0.161  0.063 -0.086 -0.036 -0.011  0.163 -0.061 -0.036 -0.186 -0.236 -0.236  0.088  0.063 -0.061 -0.136 -0.186 -0.186 -0.061 -0.136 -0.061 -0.061 -0.136 -0.011 -0.136  0.088 -0.111 -0.086 -0.211 -0.061  0.113  0.063 -0.111 -0.086 -0.061 -0.061 -0.186 -0.186 -0.186 -0.036 -0.036 -0.061 -0.111  0.013  0.163 -0.061  0.163  0.163  0.163 -0.111 -0.036 -0.011 -0.036 -0.011 -0.136 -0.061  0.088  0.387 -0.261  0.287  0.287  0.113  0.013 -0.161 -0.036 -0.086  0.013 -0.161  0.013 -0.086 -0.061 -0.061 -0.086 -0.136  0.013 -0.036  0.163 -0.011 
 0.111 -0.088 -0.163 -0.088 -0.013 -0.163 -0.138 -0.063 -0.013 -0.063 -0.013 -0.063 -0.088  0.086  0.061 -0.163 -0.088  0.061  0.061 -0.213 -0.213  0.211 -0.088 -0.163  0.061 -0.113 -0.038 -0.038  0.136 -0.088 -0.038 -0.213 -0.238 -0.263  0.136  0.011 -0.113 -0.088 -0.163 -0.213 -0.038 -0.163 -0.063 -0.038 -0.138 -0.063 -0.163  0.036 -0.138 -0.113 -0.213 -0.038  0.111 -0.013 -0.113 -0.113 -0.063 -0.038 -0.213 -0.213 -0.238 -0.063 -0.063 -0.113 -0.088  0.011  0.136 -0.038  0.136  0.211  0.136 -0.113 -0.063 -0.013 -0.038  0.011 -0.188  0.036  0.111  0.410 -0.287  0.385  0.261  0.111 -0.063 -0.113 -0.088 -0.138  0.011 -0.188 -0.013 -0.113 -0.038 -0.063 -0.113 -0.138  0.036 -0.013  0.161  0.086 
 0.107 -0.093 -0.142 -0.093 -0.018 -0.142 -0.118 -0.068 -0.018 -0.068 -0.018 -0.043 -0.068  0.107  0.107 -0.167 -0.093  0.032  0.032 -0.217 -0.217  0.206 -0.142 -0.192  0.057 -0.093 -0.043 -0.043  0.132 -0.093 -0.043 -0.217 -0.242 -0.267  0.156 -0.018 -0.118 -0.068 -0.167 -0.217 -0.043 -0.167 -0.093 -0.018 -0.142 -0.068 -0.167  0.057 -0.118 -0.118 -0.217 -0.043  0.107 -0.043 -0.118 -0.118 -0.043 -0.043 -0.217 -0.217 -0.242 -0.068 -0.093 -0.118 -0.068 -0.018  0.132 -0.018  0.057  0.231  0.132 -0.118 -0.068  0.032 -0.018 -0.018 -0.192  0.032  0.107  0.406 -0.292  0.356  0.256  0.206 -0.093 -0.093 -0.093 -0.142  0.032 -0.192 -0.043 -0.093 -0.043 -0.068 -0.118 -0.142  0.082 -0.043  0.156  0.082 
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 0.162 -0.087 -0.162 -0.062  0.062 -0.137 -0.112 -0.087 -0.037 -0.062 -0.112 -0.037 -0.112  0.087  0.087 -0.187 -0.087 -0.012  0.012 -0.262 -0.237  0.187 -0.212 -0.187  0.037 -0.112 -0.062 -0.062  0.112 -0.112 -0.062 -0.187 -0.237 -0.286  0.162 -0.062 -0.137 -0.087 -0.162 -0.237 -0.037 -0.187 -0.112 -0.012 -0.137 -0.087 -0.212  0.012 -0.137 -0.112 -0.187 -0.037  0.087 -0.037 -0.137 -0.112  0.012 -0.062 -0.212 -0.237 -0.262 -0.087 -0.137 -0.087 -0.112 -0.037  0.112 -0.037  0.012  0.237  0.112 -0.112 -0.062  0.087 -0.012 -0.037 -0.212  0.087  0.137  0.361 -0.286  0.386  0.262  0.212 -0.137 -0.087 -0.137 -0.162  0.012 -0.212 -0.062 -0.112 -0.062 -0.062 -0.137 -0.162  0.112 -0.062  0.137  0.037 
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 0.235 -0.064 -0.164 -0.039  0.010 -0.089 -0.114 -0.114 -0.014 -0.089 -0.114  0.010 -0.189  0.110  0.185 -0.114 -0.039 -0.039  0.010 -0.239 -0.239  0.185 -0.239 -0.189  0.035 -0.164 -0.089 -0.114  0.110 -0.114 -0.064 -0.214 -0.288 -0.288  0.160 -0.064 -0.164 -0.139 -0.114 -0.214 -0.014 -0.189 -0.064 -0.014 -0.139 -0.114 -0.189 -0.064 -0.164 -0.114 -0.164  0.010  0.110 -0.014 -0.189 -0.089  0.010 -0.114 -0.214 -0.239 -0.264 -0.089 -0.139 -0.089 -0.114 -0.014  0.085 -0.039  0.010  0.235  0.060 -0.189 -0.064  0.060 -0.039 -0.014 -0.214  0.085  0.210  0.284 -0.288  0.409  0.235  0.135 -0.139 -0.114 -0.164 -0.114 -0.039 -0.214 -0.064 -0.114 -0.089 -0.089 -0.164 -0.164  0.110 -0.064  0.135  0.035 
 0.257 -0.067 -0.167 -0.042  0.007 -0.092 -0.117 -0.117 -0.017 -0.117 -0.117  0.032 -0.192  0.107  0.182 -0.092 -0.042 -0.042  0.057 -0.242 -0.242  0.182 -0.242 -0.192  0.032 -0.167 -0.092 -0.092  0.107 -0.117 -0.042 -0.217 -0.291 -0.267  0.157 -0.067 -0.167 -0.142 -0.092 -0.217 -0.017 -0.192 -0.067 -0.017 -0.142 -0.117 -0.192 -0.092 -0.167 -0.117 -0.167  0.007  0.107 -0.017 -0.192 -0.092  0.007 -0.117 -0.217 -0.242 -0.267 -0.117 -0.142 -0.117 -0.142  0.007  0.057 -0.042  0.007  0.232  0.057 -0.192 -0.042  0.057 -0.067 -0.017 -0.217  0.082  0.207  0.282 -0.267  0.406  0.232  0.132 -0.142 -0.117 -0.167 -0.117 -0.042 -0.242 -0.067 -0.117 -0.092 -0.092 -0.142 -0.142  0.107 -0.042  0.132  0.032 
 0.254 -0.070 -0.170 -0.070  0.004 -0.095 -0.120 -0.120 -0.045 -0.120 -0.095  0.054 -0.195  0.104  0.154 -0.095 -0.020 -0.045  0.054 -0.245 -0.245  0.179 -0.245 -0.195  0.029 -0.170 -0.095 -0.095  0.104 -0.120 -0.045 -0.220 -0.294 -0.270  0.154 -0.070 -0.170 -0.145 -0.095 -0.220 -0.020 -0.195 -0.070 -0.020 -0.145 -0.120 -0.195 -0.095 -0.170 -0.120 -0.170  0.004  0.079  0.004 -0.195 -0.095 -0.020 -0.145 -0.220 -0.245 -0.270 -0.095 -0.120 -0.120 -0.145  0.029  0.079 -0.045 -0.020  0.179  0.054 -0.195 -0.070  0.029 -0.070  0.004 -0.220  0.029  0.204  0.279 -0.245  0.428  0.204  0.129 -0.145 -0.120 -0.170 -0.120 -0.045 -0.245 -0.045 -0.120 -0.095 -0.070 -0.145 -0.145  0.104 -0.045  0.129  0.029 
 0.254 -0.070 -0.170 -0.070  0.004 -0.095 -0.145 -0.120 -0.070 -0.120 -0.070  0.079 -0.195  0.104  0.154 -0.095  0.004 -0.045  0.054 -0.245 -0.245  0.179 -0.245 -0.195  0.004 -0.170 -0.095 -0.095  0.104 -0.120 -0.020 -0.220 -0.294 -0.270  0.154 -0.070 -0.170 -0.145 -0.095 -0.220 -0.020 -0.195 -0.045 -0.020 -0.145 -0.170 -0.195 -0.120 -0.170 -0.120 -0.170  0.004  0.079 -0.020 -0.195 -0.070 -0.020 -0.145 -0.220 -0.245 -0.270 -0.095 -0.120 -0.120 -0.145  0.029  0.054 -0.045 -0.020  0.204  0.054 -0.195 -0.045  0.079 -0.070  0.004 -0.220  0.054  0.179  0.279 -0.245  0.428  0.204  0.129 -0.170 -0.120 -0.170 -0.120 -0.070 -0.245 -0.095 -0.120 -0.095 -0.070 -0.145 -0.170  0.104 -0.045  0.129  0.029 
 0.254 -0.070 -0.170 -0.070  0.004 -0.095 -0.145 -0.120 -0.070 -0.120 -0.045  0.104 -0.195  0.104  0.129 -0.095  0.029 -0.020  0.029 -0.245 -0.245  0.179 -0.245 -0.220  0.029 -0.170 -0.120 -0.120  0.104 -0.145 -0.020 -0.220 -0.294 -0.245  0.129 -0.070 -0.170 -0.145 -0.070 -0.220 -0.020 -0.195 -0.020 -0.045 -0.120 -0.170 -0.195 -0.145 -0.195 -0.120 -0.170  0.004  0.079 -0.020 -0.195 -0.070 -0.020 -0.170 -0.220 -0.245 -0.270 -0.095 -0.120 -0.120 -0.145  0.029  0.029 -0.070 -0.070  0.204  0.054 -0.195 -0.020  0.079 -0.095  0.004 -0.220  0.054  0.179  0.279 -0.245  0.428  0.204  0.129 -0.170 -0.120 -0.170 -0.120 -0.070 -0.220 -0.095 -0.120 -0.095 -0.070 -0.145 -0.170  0.104 -0.020  0.104  0.004 
 0.250 -0.074 -0.173 -0.074 -0.024 -0.099 -0.148 -0.124 -0.074 -0.124 -0.049  0.101 -0.198  0.076  0.150 -0.099  0.026 -0.024  0.026 -0.248 -0.248  0.175 -0.248 -0.223  0.076 -0.173 -0.124 -0.124  0.101 -0.148 -0.024 -0.223 -0.298 -0.248  0.126 -0.049 -0.173 -0.148 -0.074 -0.223 -0.024 -0.198 -0.024 -0.049 -0.074 -0.148 -0.198 -0.148 -0.198 -0.124 -0.173  0.026  0.101 -0.024 -0.198 -0.074 -0.024 -0.198 -0.223 -0.248 -0.273 -0.099 -0.124 -0.124 -0.148  0.026  0.026 -0.074 -0.074  0.200  0.051 -0.198  0.001  0.076 -0.099  0.001 -0.223  0.051  0.175  0.275 -0.248  0.425  0.200  0.126 -0.173 -0.124 -0.173 -0.124 -0.099 -0.223 -0.099 -0.124 -0.099 -0.074 -0.148 -0.148  0.101  0.001  0.101  0.001 
 0.244 -0.080 -0.180 -0.080 -0.030 -0.105 -0.155 -0.130 -0.080 -0.130 -0.055  0.094 -0.205  0.069  0.144 -0.105  0.019 -0.030  0.044 -0.255 -0.255  0.169 -0.255 -0.230  0.069 -0.180 -0.130 -0.130  0.094 -0.155 -0.030 -0.230 -0.304 -0.255  0.119 -0.055 -0.180 -0.155 -0.080 -0.230 -0.030 -0.205 -0.030 -0.055 -0.080 -0.130 -0.205 -0.155 -0.205 -0.130 -0.155  0.019  0.119 -0.030 -0.180 -0.080 -0.005 -0.205 -0.230 -0.255 -0.280 -0.080 -0.130 -0.130 -0.155  0.019  0.019 -0.030 -0.080  0.194  0.044 -0.205 -0.005  0.069 -0.105 -0.005 -0.205  0.069  0.169  0.269 -0.255  0.418  0.194  0.094 -0.180 -0.130 -0.180 -0.130 -0.105 -0.230 -0.105 -0.130 -0.105 -0.080 -0.155 -0.155  0.094 -0.005  0.094 -0.005 
 0.148 -0.001 -0.151 -0.076 -0.051 -0.051 -0.126 -0.176 -0.076 -0.076 -0.051  0.048 -0.226  0.023  0.048 -0.126 -0.001 -0.126  0.048 -0.201 -0.201  0.148 -0.226 -0.151  0.098 -0.126 -0.076 -0.076  0.173 -0.101  0.023 -0.201 -0.251 -0.176  0.048 -0.026 -0.101 -0.151 -0.076 -0.201 -0.101 -0.151 -0.026 -0.076 -0.076 -0.126 -0.151 -0.126 -0.151 -0.101 -0.126  0.023  0.073 -0.001 -0.101 -0.051 -0.001 -0.126 -0.201 -0.176 -0.201 -0.076 -0.051 -0.101 -0.126  0.023  0.023 -0.001 -0.051  0.098 -0.001 -0.151  0.023  0.048 -0.076 -0.026 -0.151  0.048  0.098  0.223 -0.226  0.397  0.123  0.073 -0.126 -0.126 -0.101 -0.051 -0.076 -0.151 -0.051 -0.151 -0.126 -0.001 -0.151 -0.101  0.123 -0.026 -0.051 -0.001 
 0.111 -0.013 -0.088 -0.038 -0.038 -0.038 -0.138 -0.113 -0.038 -0.063 -0.063 -0.038 -0.138  0.061  0.036 -0.038 -0.013 -0.038  0.061 -0.138 -0.138  0.136 -0.138 -0.113  0.061 -0.063 -0.013 -0.038  0.086 -0.063  0.061 -0.138 -0.163 -0.113  0.036  0.011 -0.038 -0.113 -0.063 -0.163 -0.038 -0.063 -0.038 -0.013 -0.063 -0.088 -0.163 -0.038 -0.113 -0.038 -0.163  0.011  0.086  0.036 -0.038 -0.088  0.036 -0.113 -0.113 -0.088 -0.113 -0.063 -0.063 -0.063 -0.088  0.011  0.036 -0.013 -0.063 -0.013 -0.038 -0.063 -0.013  0.036 -0.088 -0.013 -0.113 -0.038  0.011  0.261 -0.163  0.335  0.061  0.011 -0.063 -0.113 -0.013  0.011 -0.013 -0.088 -0.013 -0.088 -0.063  0.036 -0.063 -0.063  0.086 -0.088 -0.013  0.011 
 0.132  0.007 -0.068 -0.068 -0.043 -0.018 -0.118 -0.093 -0.018 -0.043 -0.068 -0.043 -0.118  0.007 -0.043 -0.043 -0.043 -0.043  0.107 -0.118 -0.118  0.057 -0.118 -0.118  0.082 -0.043  0.007 -0.018  0.132 -0.043  0.057 -0.118 -0.142 -0.142  0.032  0.007 -0.043 -0.093 -0.043 -0.142 -0.068 -0.043 -0.018 -0.018 -0.093 -0.068 -0.142 -0.018 -0.093 -0.018 -0.142 -0.043  0.082  0.007 -0.043 -0.068  0.057 -0.118 -0.093 -0.068 -0.093 -0.043 -0.043 -0.043 -0.093 -0.043  0.057  0.007 -0.068 -0.018 -0.043 -0.043  0.007  0.057 -0.068 -0.018 -0.093 -0.093 -0.018  0.256 -0.142  0.306  0.057  0.032 -0.093 -0.118  0.007  0.032 -0.018 -0.093  0.007 -0.118 -0.068  0.057 -0.068 -0.043  0.057 -0.093  0.007  0.007 
 0.084  0.009 -0.066 -0.066 -0.041 -0.016 -0.091 -0.066  0.009 -0.041 -0.041 -0.041 -0.091 -0.041 -0.066 -0.016 -0.016 -0.041  0.109 -0.091 -0.091  0.059 -0.091 -0.091  0.084 -0.016  0.059  0.009  0.134 -0.016  0.034 -0.091 -0.116 -0.116  0.034 -0.016 -0.016 -0.091 -0.091 -0.091 -0.066  0.009 -0.016 -0.016 -0.066 -0.041 -0.116 -0.016 -0.091 -0.041 -0.116 -0.066  0.109 -0.016 -0.016 -0.041  0.059 -0.091 -0.066 -0.041 -0.066 -0.016 -0.041 -0.016 -0.066 -0.066  0.034  0.084 -0.091 -0.041 -0.066 -0.016  0.034  0.009 -0.066 -0.041 -0.066 -0.091 -0.091  0.208 -0.116  0.258  0.034 -0.066 -0.091 -0.091  0.009 -0.016  0.009 -0.066  0.034 -0.091 -0.041  0.059 -0.041 -0.091  0.034 -0.041 -0.016  0.009 
 0.090  0.015 -0.059 -0.059 -0.034 -0.009 -0.084 -0.084  0.015 -0.034 -0.059 -0.034 -0.084 -0.034 -0.109 -0.009 -0.009 -0.034  0.115 -0.084 -0.084  0.040 -0.084 -0.084  0.065 -0.009  0.040  0.015  0.140 -0.034  0.015 -0.084 -0.109 -0.109  0.040 -0.009 -0.009 -0.109 -0.084 -0.059 -0.059  0.015 -0.009 -0.009 -0.059 -0.034 -0.109 -0.009 -0.084 -0.034 -0.109 -0.059  0.090 -0.034 -0.009 -0.034  0.015 -0.084 -0.059 -0.059 -0.059  0.015 -0.034 -0.009 -0.059 -0.059  0.065  0.090 -0.084 -0.034 -0.034 -0.009  0.065 -0.009 -0.034 -0.034 -0.059 -0.084 -0.084  0.190 -0.109  0.265  0.040 -0.059 -0.059 -0.084  0.015 -0.009 -0.009 -0.034  0.015 -0.109 -0.084  0.040 -0.034 -0.084  0.040 -0.009 -0.009 -0.009 
 0.053  0.028 -0.072 -0.022 -0.022 -0.022 -0.097 -0.072  0.003 -0.022 -0.047 -0.047 -0.097 -0.047 -0.097 -0.022  0.003  0.028  0.103 -0.072 -0.097  0.028 -0.097 -0.072  0.078  0.003  0.028  0.028  0.103 -0.022 -0.022 -0.072 -0.097 -0.097  0.003  0.003 -0.047 -0.072 -0.047 -0.047 -0.047  0.003  0.003  0.028 -0.047 -0.047 -0.097 -0.022 -0.072 -0.047 -0.097 -0.072  0.103 -0.047  0.003 -0.072  0.028 -0.072 -0.047 -0.047 -0.047  0.003 -0.022 -0.022 -0.047 -0.072  0.078  0.078 -0.072 -0.022  0.003  0.003  0.078  0.003  0.003 -0.047 -0.047 -0.072 -0.072  0.177 -0.097  0.277  0.078 -0.047 -0.047 -0.072  0.003  0.003  0.003 -0.022  0.028 -0.097 -0.097  0.028 -0.047 -0.072  0.053  0.003  0.003  0.003 
 0.065  0.040 -0.060 -0.010 -0.010  0.015 -0.085 -0.060  0.015 -0.010 -0.035 -0.035 -0.085 -0.060 -0.085 -0.010 -0.010  0.015  0.090 -0.060 -0.085  0.015 -0.085 -0.060  0.065  0.015  0.015  0.040  0.090 -0.010 -0.060 -0.060 -0.085 -0.085 -0.010  0.015 -0.085 -0.060 -0.035 -0.035 -0.035  0.015 -0.010  0.015 -0.060 -0.060 -0.085 -0.035 -0.060 -0.035 -0.085 -0.060  0.090 -0.035 -0.035 -0.060  0.015 -0.060 -0.060 -0.060 -0.035 -0.035 -0.010 -0.010 -0.060 -0.060  0.065  0.065 -0.060 -0.010  0.015  0.015  0.040 -0.010  0.015 -0.035 -0.035 -0.060 -0.060  0.164 -0.085  0.214  0.115 -0.035 -0.085 -0.060 -0.010 -0.010 -0.010 -0.010  0.015 -0.085 -0.085  0.015 -0.035 -0.060  0.040 -0.010  0.015  0.015 
 0.070  0.045 -0.079 -0.004 -0.029  0.020 -0.079 -0.029 -0.004 -0.004 -0.004 -0.029 -0.079 -0.079 -0.079 -0.004 -0.004  0.045  0.045 -0.054 -0.079  0.045 -0.079 -0.054  0.020  0.020  0.020  0.045  0.070 -0.004 -0.054 -0.054 -0.079 -0.079 -0.004  0.020 -0.079 -0.054 -0.029 -0.054 -0.004 -0.004 -0.004 -0.004 -0.054 -0.054 -0.079 -0.029 -0.054 -0.054 -0.079 -0.054  0.070 -0.029 -0.029 -0.054 -0.004 -0.054 -0.054 -0.054 -0.029 -0.029 -0.004 -0.004 -0.054 -0.029  0.095  0.045 -0.054 -0.004  0.070  0.020  0.045 -0.029  0.045 -0.029 -0.029 -0.004 -0.054  0.120 -0.079  0.220  0.095 -0.029 -0.079 -0.054 -0.004 -0.004 -0.004 -0.029  0.020 -0.054 -0.079  0.020 -0.029 -0.054  0.020  0.020  0.020 -0.004 
 0.051  0.026 -0.073  0.001 -0.023  0.001 -0.073 -0.023  0.001  0.001  0.026 -0.023 -0.073 -0.073 -0.048 -0.023  0.001  0.051  0.026 -0.023 -0.073  0.051 -0.073 -0.073  0.026  0.026  0.026  0.051  0.051  0.001 -0.048 -0.048 -0.073 -0.073  0.001  0.026 -0.073 -0.048 -0.023 -0.048  0.001  0.001 -0.023  0.001 -0.048 -0.048 -0.073 -0.023 -0.048 -0.048 -0.048 -0.048  0.026 -0.023 -0.023 -0.048  0.001 -0.048 -0.048 -0.048 -0.023 -0.023 -0.023  0.026 -0.048 -0.023  0.101  0.026 -0.048  0.001  0.051  0.001  0.026  0.001  0.051 -0.023 -0.048  0.001 -0.048  0.126 -0.073  0.151  0.101 -0.023 -0.073 -0.048  0.001 -0.023  0.001 -0.048  0.001 -0.048 -0.073  0.026 -0.023 -0.048  0.026  0.026  0.026  0.001 
 0.056  0.006 -0.069  0.006 -0.019 -0.019 -0.044 -0.019  0.006  0.006 -0.019 -0.019 -0.044 -0.069 -0.044 -0.044 -0.019  0.056 -0.044 -0.019 -0.069  0.031 -0.069 -0.069  0.031 -0.019  0.006  0.031  0.056 -0.019 -0.044 -0.044 -0.069 -0.069  0.006  0.056 -0.069 -0.044 -0.019 -0.044  0.006  0.006 -0.019  0.006 -0.044 -0.044 -0.069 -0.019 -0.044 -0.044 -0.044 -0.044  0.031  0.006 -0.019 -0.044  0.031 -0.044 -0.044 -0.044 -0.069 -0.044  0.006  0.031 -0.044 -0.019  0.081  0.031 -0.044  0.006  0.056 -0.019  0.031  0.006  0.031 -0.044 -0.069  0.006 -0.019  0.056 -0.069  0.081  0.106 -0.019 -0.069 -0.044 -0.044 -0.044 -0.019 -0.044 -0.019 -0.044 -0.069  0.031 -0.019 -0.044  0.006  0.031  0.031 -0.019 
 0.056  0.031 -0.069  0.006 -0.019  0.006 -0.044 -0.019  0.006  0.006 -0.044 -0.019 -0.044 -0.069 -0.044 -0.044 -0.019  0.056 -0.019 -0.044 -0.069  0.006 -0.044 -0.044  0.031 -0.019  0.006  0.056  0.056 -0.019 -0.044 -0.044 -0.069 -0.069  0.006  0.031 -0.044 -0.044 -0.019  0.006  0.006  0.006 -0.044  0.006 -0.044 -0.069 -0.069 -0.044 -0.044 -0.044 -0.044 -0.044  0.031  0.031 -0.019 -0.044  0.031 -0.044 -0.044 -0.044 -0.069 -0.044  0.006  0.031 -0.044 -0.019  0.056  0.031 -0.044  0.006  0.056 -0.019  0.031 -0.019  0.031 -0.044 -0.069  0.031 -0.019  0.031 -0.069  0.081  0.106 -0.019 -0.069 -0.044 -0.044 -0.019 -0.019 -0.044 -0.019 -0.044 -0.044  0.056 -0.019 -0.044  0.006  0.031  0.031 -0.019 
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 0.055  0.055 -0.069  0.005 -0.019  0.005 -0.044  0.005  0.005 -0.019 -0.019 -0.019 -0.044 -0.069 -0.044 -0.044 -0.019  0.055 -0.019 -0.019 -0.069  0.030 -0.044 -0.044  0.030 -0.019  0.005  0.055  0.055 -0.019 -0.044 -0.044 -0.069 -0.069  0.005  0.030 -0.044 -0.044 -0.019  0.005  0.005  0.005 -0.044  0.030 -0.044 -0.069 -0.044 -0.019 -0.044 -0.044 -0.019 -0.044  0.005  0.030 -0.019 -0.044  0.030 -0.044 -0.044 -0.044 -0.044 -0.044  0.005  0.030 -0.019 -0.019  0.055  0.030 -0.044  0.005  0.055  0.005  0.030  0.005  0.030  0.005 -0.069  0.030 -0.019  0.055 -0.069  0.055  0.105 -0.019 -0.044 -0.044 -0.044  0.005 -0.019 -0.044 -0.019 -0.044 -0.019  0.055 -0.044 -0.044 -0.019  0.030  0.030 -0.019 
 0.055  0.055 -0.069  0.005 -0.019  0.005 -0.044  0.005  0.005 -0.019 -0.019 -0.019 -0.044 -0.069 -0.044 -0.044 -0.019  0.055 -0.019 -0.019 -0.069  0.030 -0.044 -0.044  0.030 -0.019  0.005  0.055  0.055 -0.019 -0.044 -0.044 -0.069 -0.069  0.005  0.030 -0.044 -0.044 -0.019  0.005  0.005  0.005 -0.044  0.030 -0.044 -0.069 -0.044 -0.019 -0.044 -0.044 -0.019 -0.044  0.005  0.030 -0.019 -0.044  0.030 -0.044 -0.044 -0.044 -0.044 -0.044  0.005  0.030 -0.019 -0.019  0.055  0.030 -0.044  0.005  0.055  0.005  0.030  0.005  0.030  0.005 -0.069  0.030 -0.019  0.055 -0.069  0.055  0.105 -0.019 -0.044 -0.044 -0.044  0.005 -0.019 -0.044 -0.019 -0.044 -0.019  0.055 -0.044 -0.044 -0.019  0.030  0.030 -0.019 
 0.055  0.055 -0.069  0.005 -0.019  0.005 -0.044  0.005  0.005 -0.019 -0.019 -0.019 -0.044 -0.069 -0.044 -0.044 -0.019  0.055 -0.019 -0.019 -0.069  0.030 -0.044 -0.044  0.030 -0.019  0.005  0.055  0.055 -0.019 -0.044 -0.044 -0.069 -0.069  0.005  0.030 -0.044 -0.044 -0.019  0.005  0.005  0.005 -0.044  0.030 -0.044 -0.069 -0.044 -0.019 -0.044 -0.044 -0.019 -0.044  0.005  0.030 -0.019 -0.044  0.030 -0.044 -0.044 -0.044 -0.044 -0.044  0.005  0.030 -0.019 -0.019  0.055  0.030 -0.044  0.005  0.055  0.005  0.030  0.005  0.030  0.005 -0.069  0.030 -0.019  0.055 -0.069  0.055  0.105 -0.019 -0.044 -0.044 -0.044  0.005 -0.019 -0.044 -0.019 -0.044 -0.019  0.055 -0.044 -0.044 -0.019  0.030  0.030 -0.019 
 0.056  0.056 -0.069  0.006 -0.019  0.006 -0.044  0.006  0.006 -0.019 -0.019 -0.019 -0.044 -0.069 -0.044 -0.044 -0.019  0.056 -0.019 -0.019 -0.069  0.031 -0.044 -0.044  0.031 -0.019  0.006  0.056  0.056 -0.019 -0.044 -0.044 -0.069 -0.069  0.006  0.031 -0.044 -0.044 -0.019  0.006  0.006  0.006 -0.044  0.031 -0.044 -0.069 -0.044 -0.019 -0.044 -0.044 -0.019 -0.044  0.006  0.031 -0.019 -0.044  0.031 -0.044 -0.044 -0.044 -0.044 -0.044  0.006  0.031 -0.044 -0.019  0.056  0.031 -0.044  0.006  0.056 -0.019  0.031  0.006  0.031 -0.019 -0.069  0.031 -0.019  0.056 -0.069  0.056  0.106 -0.019 -0.044 -0.044 -0.044  0.006 -0.019 -0.044 -0.019 -0.044 -0.044  0.056 -0.044 -0.044 -0.019  0.031  0.031 -0.019 
 0.046  0.071 -0.078 -0.003 -0.053 -0.028 -0.053 -0.003 -0.003 -0.028 -0.003 -0.028 -0.078 -0.103 -0.053 -0.028 -0.028  0.121  0.071 -0.053 -0.103  0.071 -0.078 -0.053  0.021 -0.003 -0.003  0.046  0.046 -0.028 -0.078 -0.078 -0.078 -0.103  0.021  0.046 -0.053 -0.078 -0.028 -0.028  0.071  0.021 -0.028  0.021 -0.028 -0.103 -0.078 -0.003 -0.078 -0.003 -0.028 -0.003  0.121  0.071 -0.053 -0.078 -0.003 -0.078 -0.078 -0.078 -0.053 -0.053  0.021 -0.003 -0.053 -0.053  0.096  0.021 -0.003 -0.003  0.046 -0.003  0.021  0.021  0.046  0.071 -0.028 -0.003  0.021  0.221 -0.103  0.121  0.096 -0.053 -0.053 -0.078 -0.028 -0.028 -0.053 -0.078 -0.028 -0.078 -0.053  0.046 -0.078 -0.028 -0.053  0.071  0.021 -0.003 
 0.022  0.047 -0.102 -0.077 -0.127 -0.052 -0.077 -0.052 -0.077 -0.102 -0.052 -0.077 -0.077 -0.027 -0.052 -0.077 -0.052  0.047  0.022 -0.127 -0.177  0.047 -0.102 -0.102  0.047 -0.002 -0.027  0.022  0.022 -0.077 -0.052 -0.102 -0.127 -0.177  0.022 -0.027 -0.077 -0.102 -0.052 -0.102  0.097 -0.002 -0.052 -0.002 -0.102 -0.027 -0.152  0.097 -0.127 -0.052 -0.102 -0.077  0.072  0.072 -0.102 -0.127  0.047 -0.077 -0.127 -0.127 -0.102 -0.102 -0.027 -0.077 -0.102 -0.002  0.122 -0.027  0.022 -0.027  0.197  0.022 -0.002  0.047 -0.002  0.072 -0.077 -0.027  0.072  0.346 -0.177  0.247  0.247 -0.102 -0.052 -0.127 -0.077 -0.027 -0.077 -0.127 -0.077 -0.077 -0.077  0.047 -0.077 -0.077 -0.077  0.097  0.047 -0.027 
 0.056  0.056 -0.093 -0.143 -0.118 -0.093 -0.118 -0.043 -0.093 -0.143 -0.018 -0.118 -0.093 -0.068  0.081 -0.118 -0.093 -0.018  0.056 -0.168 -0.218  0.081 -0.143 -0.118  0.081 -0.068 -0.018 -0.018  0.031 -0.093 -0.018 -0.118 -0.168 -0.218  0.031  0.006 -0.093 -0.093 -0.118 -0.068  0.106 -0.093 -0.043  0.081 -0.118 -0.043 -0.168  0.081 -0.143 -0.068 -0.118 -0.093  0.056  0.056 -0.118 -0.118  0.056 -0.093 -0.168 -0.168 -0.093 -0.068 -0.043 -0.093 -0.068 -0.018  0.081 -0.018  0.081 -0.018  0.206  0.031 -0.043  0.056  0.056  0.031 -0.118 -0.068  0.106  0.330 -0.218  0.231  0.256 -0.093 -0.068 -0.118 -0.093 -0.043 -0.068 -0.118 -0.068 -0.093 -0.118  0.031 -0.093 -0.118 -0.043  0.106  0.031 -0.043 
 0.135  0.035 -0.115 -0.140 -0.115 -0.115 -0.115 -0.040 -0.115 -0.189 -0.065 -0.115 -0.115 -0.090  0.035 -0.140 -0.115 -0.065  0.060 -0.214 -0.214  0.010 -0.164 -0.090  0.060 -0.065 -0.040 -0.065  0.110 -0.115 -0.040 -0.140 -0.214 -0.239 -0.015 -0.040 -0.140 -0.090 -0.164 -0.065  0.060 -0.140 -0.065  0.060 -0.164 -0.065 -0.164  0.060 -0.189 -0.115 -0.164 -0.090  0.035  0.060 -0.115 -0.090  0.035 -0.090 -0.214 -0.189 -0.090 -0.065 -0.090 -0.115 -0.115 -0.015  0.085  0.035  0.110 -0.040  0.209  0.010 -0.065  0.060  0.010  0.035 -0.140  0.035  0.135  0.384 -0.239  0.234  0.309 -0.115 -0.115 -0.164 -0.090 -0.065 -0.065 -0.115 -0.065 -0.115 -0.065  0.010 -0.140 -0.090 -0.065  0.060  0.010 -0.040 
 0.121 -0.003 -0.103 -0.153 -0.078 -0.153 -0.078 -0.053 -0.103 -0.203 -0.078 -0.103 -0.128 -0.078  0.046 -0.153 -0.053 -0.078  0.071 -0.203 -0.228 -0.003 -0.178 -0.103  0.096 -0.078 -0.053 -0.103  0.096 -0.128 -0.053 -0.178 -0.228 -0.253 -0.003 -0.028 -0.103 -0.103 -0.153 -0.103  0.071 -0.153 -0.053  0.046 -0.153 -0.078 -0.153  0.071 -0.203 -0.128 -0.178 -0.078  0.046  0.071 -0.128 -0.053  0.021 -0.078 -0.228 -0.203 -0.103 -0.053 -0.053 -0.128 -0.128 -0.003  0.071  0.021  0.171  0.046  0.221 -0.028 -0.053  0.096 -0.003 -0.003 -0.153  0.021  0.171  0.370 -0.253  0.271  0.320 -0.103 -0.128 -0.078 -0.078 -0.103 -0.053 -0.128 -0.053 -0.128 -0.078 -0.028 -0.103 -0.103 -0.053  0.071  0.046 -0.053 
 0.153 -0.021 -0.096 -0.170 -0.096 -0.170 -0.071 -0.071 -0.121 -0.145 -0.071 -0.096 -0.145 -0.046  0.054 -0.145 -0.071 -0.121  0.054 -0.220 -0.245  0.029 -0.170 -0.121  0.104 -0.071 -0.071 -0.096  0.079 -0.145 -0.021 -0.170 -0.245 -0.270  0.029 -0.021 -0.121 -0.096 -0.145 -0.121  0.054 -0.145 -0.071  0.054 -0.195 -0.096 -0.145  0.029 -0.195 -0.096 -0.245 -0.071  0.079  0.079 -0.071 -0.021  0.029 -0.096 -0.220 -0.220 -0.121  0.004 -0.096 -0.145 -0.145 -0.021  0.079  0.004  0.203  0.104  0.228 -0.046 -0.046  0.054 -0.021  0.004 -0.170  0.004  0.228  0.353 -0.270  0.253  0.353 -0.071 -0.121 -0.096 -0.096 -0.121 -0.071 -0.145 -0.046 -0.145 -0.071 -0.046 -0.121 -0.121 -0.071  0.079  0.054  0.004 
 0.220 -0.054 -0.104 -0.104 -0.104 -0.154 -0.079 -0.079 -0.104 -0.154 -0.079 -0.104 -0.154 -0.054  0.045 -0.154 -0.079 -0.129  0.045 -0.229 -0.254  0.045 -0.179 -0.129  0.095 -0.079 -0.079 -0.104  0.070 -0.154 -0.029 -0.179 -0.229 -0.303  0.045 -0.004 -0.129 -0.104 -0.154 -0.154  0.020 -0.129 -0.104  0.045 -0.179 -0.079 -0.104  0.020 -0.204 -0.104 -0.229 -0.029  0.070  0.020 -0.079 -0.004  0.045 -0.104 -0.229 -0.229 -0.129  0.045 -0.104 -0.154 -0.154 -0.029  0.070 -0.004  0.195  0.095  0.220 -0.054 -0.054  0.070 -0.004  0.020 -0.154 -0.004  0.270  0.394 -0.279  0.270  0.319 -0.079 -0.104 -0.104 -0.104 -0.129 -0.079 -0.179 -0.054 -0.154 -0.079 -0.054 -0.129 -0.129 -0.054  0.070  0.045 -0.004 
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 0.296 -0.053 -0.227 -0.078 -0.128 -0.128 -0.252 -0.128 -0.078 -0.103  0.072  0.047 -0.177  0.072  0.072 -0.128  0.072 -0.103 -0.003 -0.227 -0.277  0.122 -0.227 -0.227  0.047 -0.152 -0.128 -0.128  0.122 -0.053 -0.028 -0.227 -0.302 -0.252  0.097 -0.103 -0.177 -0.152 -0.078 -0.202 -0.003 -0.177 -0.103  0.047 -0.128 -0.078 -0.103 -0.152 -0.202 -0.152 -0.078 -0.028  0.022 -0.053 -0.202 -0.003 -0.003 -0.177 -0.227 -0.252 -0.202 -0.028 -0.177 -0.152 -0.177  0.072  0.072 -0.028 -0.028  0.122  0.047 -0.152  0.022  0.246 -0.028 -0.003 -0.177 -0.003  0.296  0.321 -0.252  0.421  0.196 -0.028 -0.177 -0.128 -0.128 -0.152 -0.128 -0.202 -0.078 -0.202 -0.078 -0.103 -0.152 -0.128  0.047 -0.053  0.047 -0.003 
 0.291 -0.058 -0.232 -0.058 -0.083 -0.133 -0.257 -0.133 -0.108 -0.108  0.067  0.067 -0.182  0.067  0.092 -0.108  0.092 -0.108 -0.008 -0.232 -0.282  0.092 -0.257 -0.257  0.042 -0.157 -0.108 -0.157  0.117 -0.058 -0.058 -0.232 -0.307 -0.257  0.067 -0.108 -0.182 -0.157 -0.083 -0.232 -0.008 -0.182 -0.108  0.042 -0.083 -0.083 -0.108 -0.157 -0.207 -0.157 -0.108 -0.008  0.017 -0.033 -0.207 -0.033 -0.008 -0.182 -0.232 -0.257 -0.182 -0.008 -0.182 -0.157 -0.182  0.067  0.067 -0.058 -0.033  0.117  0.042 -0.157  0.042  0.216 -0.033 -0.008 -0.157 -0.033  0.291  0.316 -0.257  0.416  0.191 -0.008 -0.182 -0.133 -0.133 -0.157 -0.133 -0.207 -0.083 -0.232 -0.083 -0.108 -0.157 -0.133  0.067 -0.033  0.042 -0.008 
 0.292 -0.057 -0.231 -0.057 -0.107 -0.132 -0.256 -0.132 -0.107 -0.107  0.093  0.068 -0.156  0.068  0.068 -0.132  0.093 -0.107 -0.007 -0.231 -0.281  0.093 -0.231 -0.256  0.043 -0.156 -0.107 -0.156  0.118 -0.057 -0.057 -0.231 -0.306 -0.256  0.068 -0.107 -0.181 -0.181 -0.082 -0.206 -0.007 -0.181 -0.107  0.043 -0.082 -0.082 -0.132 -0.132 -0.231 -0.156 -0.107 -0.007  0.018 -0.032 -0.206 -0.032 -0.007 -0.181 -0.231 -0.256 -0.181 -0.007 -0.181 -0.156 -0.181  0.068  0.043 -0.057 -0.032  0.118  0.043 -0.156  0.043  0.192 -0.057 -0.007 -0.156 -0.032  0.292  0.317 -0.256  0.417  0.192 -0.007 -0.181 -0.132 -0.132 -0.156 -0.132 -0.206 -0.107 -0.231 -0.082 -0.107 -0.156 -0.132  0.068 -0.032  0.043 -0.007 
 0.267 -0.032 -0.231 -0.057 -0.107 -0.132 -0.256 -0.132 -0.107 -0.107  0.093  0.043 -0.156  0.068  0.068 -0.132  0.118 -0.107 -0.007 -0.231 -0.281  0.093 -0.231 -0.256  0.043 -0.156 -0.107 -0.156  0.118 -0.107 -0.082 -0.231 -0.306 -0.256  0.068 -0.107 -0.181 -0.181 -0.082 -0.206 -0.007 -0.181 -0.107  0.068 -0.082 -0.082 -0.156 -0.132 -0.231 -0.132 -0.107 -0.007  0.018 -0.032 -0.206 -0.032 -0.007 -0.181 -0.231 -0.256 -0.181 -0.007 -0.156 -0.156 -0.181  0.068  0.043 -0.057 -0.007  0.118  0.043 -0.156  0.043  0.142 -0.082 -0.007 -0.156 -0.057  0.292  0.317 -0.256  0.417  0.192 -0.007 -0.181 -0.132 -0.132 -0.156 -0.132 -0.206 -0.107 -0.231 -0.082 -0.132 -0.156 -0.132  0.068 -0.032  0.043 -0.007 
 0.267 -0.032 -0.232 -0.057 -0.082 -0.132 -0.257 -0.132 -0.107 -0.107  0.092  0.067 -0.157  0.067  0.067 -0.132  0.117 -0.107 -0.007 -0.232 -0.257  0.092 -0.232 -0.257  0.042 -0.157 -0.107 -0.157  0.117 -0.107 -0.082 -0.232 -0.306 -0.257  0.067 -0.107 -0.182 -0.182 -0.082 -0.207 -0.007 -0.182 -0.107  0.067 -0.082 -0.107 -0.157 -0.132 -0.232 -0.132 -0.107 -0.007  0.017 -0.032 -0.207 -0.032 -0.007 -0.182 -0.232 -0.257 -0.182 -0.007 -0.157 -0.157 -0.157  0.067  0.042 -0.057 -0.007  0.117  0.042 -0.157  0.042  0.142 -0.082 -0.007 -0.157 -0.057  0.291  0.316 -0.257  0.416  0.192 -0.007 -0.182 -0.132 -0.132 -0.157 -0.132 -0.207 -0.107 -0.232 -0.082 -0.132 -0.157 -0.132  0.067 -0.032  0.042 -0.007 
 0.267 -0.032 -0.231 -0.057 -0.057 -0.132 -0.256 -0.132 -0.107 -0.107  0.093  0.068 -0.156  0.068  0.043 -0.132  0.093 -0.107 -0.007 -0.231 -0.256  0.093 -0.231 -0.256  0.043 -0.156 -0.107 -0.156  0.118 -0.107 -0.082 -0.231 -0.306 -0.256  0.068 -0.107 -0.181 -0.181 -0.082 -0.206 -0.007 -0.181 -0.107  0.068 -0.082 -0.107 -0.156 -0.132 -0.231 -0.132 -0.107 -0.007  0.018 -0.032 -0.206 -0.032 -0.007 -0.181 -0.231 -0.256 -0.181 -0.032 -0.156 -0.206 -0.156  0.068  0.043 -0.057  0.018  0.118  0.043 -0.156  0.043  0.142 -0.107 -0.032 -0.156 -0.057  0.292  0.317 -0.231  0.417  0.217 -0.007 -0.206 -0.132 -0.132 -0.156 -0.132 -0.231 -0.107 -0.231 -0.082 -0.132 -0.156 -0.107  0.093 -0.032  0.018 -0.007 
 0.218 -0.106 -0.156 -0.081 -0.006 -0.056 -0.206 -0.181 -0.106 -0.131 -0.006  0.068 -0.156  0.118  0.093 -0.081  0.068 -0.106  0.018 -0.156 -0.231  0.093 -0.206 -0.181  0.118 -0.106 -0.106 -0.131  0.118 -0.056 -0.031 -0.181 -0.256 -0.181  0.068 -0.031 -0.106 -0.181 -0.081 -0.181 -0.031 -0.181 -0.081  0.018 -0.106 -0.081 -0.156 -0.106 -0.156 -0.131 -0.081 -0.006  0.018 -0.106 -0.156  0.018 -0.056 -0.181 -0.181 -0.181 -0.106  0.018 -0.156 -0.131 -0.131  0.043 -0.006 -0.056 -0.006  0.143 -0.081 -0.081 -0.031  0.143 -0.131 -0.081 -0.131 -0.081  0.143  0.367 -0.181  0.367  0.168  0.018 -0.181 -0.106 -0.081 -0.081 -0.081 -0.156 -0.081 -0.181 -0.081 -0.081 -0.131 -0.106  0.168 -0.106 -0.006 -0.006 
 0.239 -0.060 -0.110 -0.085 -0.035 -0.010 -0.135 -0.110 -0.035 -0.110  0.015  0.065 -0.135  0.065  0.065 -0.010 -0.060 -0.060 -0.010 -0.110 -0.135  0.065 -0.135 -0.085  0.140 -0.060 -0.060 -0.060  0.115 -0.035  0.015 -0.135 -0.159 -0.085  0.015  0.040 -0.035 -0.135 -0.010 -0.135 -0.060 -0.085 -0.085  0.015 -0.085 -0.060 -0.159 -0.035 -0.085 -0.060 -0.110 -0.010  0.090 -0.085 -0.060 -0.035 -0.085 -0.135 -0.085 -0.110 -0.085 -0.010 -0.110 -0.060 -0.085 -0.035 -0.035 -0.010 -0.060  0.115 -0.060 -0.035 -0.035  0.115 -0.085 -0.010 -0.110 -0.010  0.040  0.314 -0.159  0.364  0.115  0.015 -0.110 -0.110  0.015  0.015 -0.035 -0.060 -0.035 -0.135 -0.060 -0.010 -0.035 -0.110  0.090 -0.135  0.015  0.015 
 0.186 -0.038 -0.088 -0.088 -0.013 -0.013 -0.113 -0.088 -0.038 -0.088  0.011  0.011 -0.113  0.086  0.036  0.011 -0.063 -0.038  0.011 -0.088 -0.113  0.061 -0.113 -0.063  0.111 -0.038 -0.063 -0.038  0.111 -0.013  0.036 -0.113 -0.138 -0.088  0.011  0.011 -0.038 -0.113 -0.038 -0.113 -0.038 -0.063 -0.063 -0.013 -0.063 -0.038 -0.138 -0.038 -0.063 -0.063 -0.088 -0.013  0.111 -0.063 -0.038 -0.013 -0.063 -0.113 -0.063 -0.088 -0.063 -0.013 -0.088 -0.038 -0.063 -0.038 -0.013  0.011 -0.038  0.061 -0.063 -0.013 -0.013  0.061 -0.088 -0.013 -0.088  0.011 -0.088  0.236 -0.138  0.360  0.086 -0.013 -0.088 -0.113  0.036  0.036 -0.013 -0.088 -0.013 -0.113 -0.063  0.011 -0.038 -0.088  0.111 -0.113  0.011  0.011 
 0.169  0.019 -0.055 -0.080  0.019 -0.005 -0.080 -0.055 -0.030 -0.030 -0.030 -0.030 -0.080 -0.055 -0.030  0.019 -0.030 -0.005  0.019 -0.055 -0.105  0.019 -0.080 -0.080  0.069 -0.005 -0.055 -0.005  0.094  0.019  0.019 -0.080 -0.105 -0.080  0.019 -0.030 -0.005 -0.080 -0.030 -0.080 -0.055  0.019 -0.030  0.019 -0.080 -0.030 -0.105 -0.005 -0.055 -0.055 -0.105 -0.055  0.144 -0.030 -0.005 -0.030 -0.005 -0.105 -0.055 -0.055 -0.005  0.044 -0.030 -0.005 -0.055 -0.005 -0.005  0.094 -0.030 -0.005 -0.055  0.019  0.019  0.044 -0.055 -0.005 -0.055 -0.055 -0.080  0.194 -0.105  0.368  0.019 -0.030 -0.080 -0.080  0.044  0.044  0.044 -0.080 -0.005 -0.105 -0.055  0.044 -0.030 -0.080  0.044 -0.080 -0.005  0.044 
 0.178  0.028 -0.071 -0.071  0.028 -0.021 -0.071 -0.071 -0.046 -0.021 -0.046 -0.021 -0.071 -0.071 -0.071  0.003 -0.021  0.003  0.028 -0.046 -0.096  0.028 -0.096 -0.071  0.078  0.003 -0.046  0.028  0.078  0.003 -0.021 -0.071 -0.096 -0.096  0.028 -0.021 -0.021 -0.071 -0.046 -0.046 -0.046  0.028 -0.021  0.028 -0.071 -0.046 -0.096 -0.046 -0.071 -0.046 -0.096 -0.046  0.153 -0.071  0.003 -0.021 -0.021 -0.096 -0.046 -0.096  0.003  0.053 -0.021  0.003 -0.071 -0.021  0.003  0.103 -0.021 -0.021 -0.021  0.028  0.003  0.028 -0.046  0.003 -0.046 -0.046 -0.071  0.178 -0.096  0.352  0.053 -0.046 -0.096 -0.071  0.053  0.028  0.053 -0.071  0.003 -0.096 -0.071  0.053 -0.021 -0.071  0.028 -0.071  0.003  0.053 
 0.091  0.041 -0.058 -0.058  0.016 -0.008 -0.083 -0.058 -0.033 -0.008 -0.033 -0.033 -0.083 -0.083 -0.083 -0.033 -0.033  0.041  0.041 -0.058 -0.083  0.041 -0.083 -0.058  0.091  0.016 -0.033  0.041  0.066 -0.008 -0.008 -0.058 -0.083 -0.083  0.041 -0.008 -0.058 -0.058 -0.033 -0.033 -0.008 -0.008 -0.008  0.066 -0.058 -0.033 -0.083 -0.058 -0.058 -0.033 -0.083 -0.083  0.141 -0.083  0.016 -0.058 -0.033 -0.083 -0.033 -0.083 -0.008 -0.008 -0.008 -0.008 -0.058 -0.008  0.016  0.116 -0.033 -0.008  0.016  0.041  0.016  0.016 -0.008 -0.008 -0.033 -0.058 -0.058  0.141 -0.083  0.315  0.041 -0.033 -0.083 -0.058  0.041  0.016  0.041 -0.058  0.016 -0.083 -0.058  0.066 -0.008 -0.083  0.016 -0.058  0.016  0.016 
 0.099  0.049 -0.050 -0.050  0.024 -0.000 -0.075 -0.025 -0.050 -0.000 -0.025 -0.025 -0.075 -0.075 -0.075 -0.050 -0.025  0.024  0.024 -0.050 -0.075  0.049 -0.075 -0.075  0.099  0.024 -0.025  0.049  0.074 -0.025 -0.050 -0.050 -0.075 -0.075  0.024 -0.000 -0.050 -0.050 -0.025 -0.025 -0.000 -0.000 -0.000  0.074 -0.050 -0.025 -0.075 -0.050 -0.050 -0.025 -0.075 -0.075  0.099 -0.075 -0.025 -0.050 -0.025 -0.075 -0.025 -0.075 -0.000 -0.050 -0.000 -0.000 -0.050 -0.025  0.024  0.124 -0.050 -0.000  0.049  0.049  0.024 -0.025 -0.000 -0.000 -0.025 -0.050 -0.050  0.149 -0.075  0.274  0.049 -0.025 -0.075 -0.050  0.049  0.024 -0.000 -0.075 -0.000 -0.075 -0.075  0.049 -0.000 -0.075 -0.000 -0.025  0.024 -0.000 
 0.108  0.058 -0.042 -0.042 -0.017  0.008 -0.067 -0.017 -0.067  0.008 -0.042 -0.017 -0.042 -0.067 -0.067 -0.042 -0.017  0.033 -0.017 -0.042 -0.067  0.083 -0.067 -0.067  0.083  0.008 -0.017  0.058  0.083 -0.017 -0.042 -0.042 -0.067 -0.067  0.033  0.008 -0.042 -0.042 -0.017 -0.042  0.008  0.008 -0.017  0.008 -0.067 -0.042 -0.067 -0.017 -0.042 -0.017 -0.067 -0.067  0.058 -0.067 -0.017 -0.042 -0.042 -0.067 -0.042 -0.067  0.008 -0.017  0.008  0.008 -0.042 -0.017  0.058  0.058 -0.042  0.008  0.033  0.008  0.008 -0.042  0.033  0.008 -0.042 -0.042 -0.042  0.108 -0.067  0.232  0.008 -0.017 -0.042 -0.042  0.008  0.058  0.008 -0.042 -0.017 -0.067 -0.067  0.058  0.008 -0.067  0.008 -0.017  0.033 -0.017 
 0.113  0.063 -0.062 -0.037 -0.012  0.013 -0.062 -0.012 -0.062  0.013 -0.037 -0.012 -0.012 -0.062 -0.037 -0.037 -0.037  0.038 -0.012 -0.037 -0.062  0.063 -0.062 -0.062  0.063  0.013 -0.012  0.088  0.088 -0.012 -0.037 -0.037 -0.037 -0.062  0.038  0.013 -0.062 -0.037 -0.012 -0.037  0.013  0.013 -0.037  0.013 -0.062 -0.037 -0.062 -0.012 -0.037 -0.012 -0.062 -0.062  0.063 -0.062 -0.012 -0.037 -0.037 -0.062 -0.062 -0.062  0.013 -0.037  0.013  0.038 -0.037 -0.012  0.063  0.038 -0.037  0.013  0.038  0.013  0.013 -0.037  0.038  0.013 -0.037 -0.037 -0.062  0.113 -0.062  0.138 -0.012 -0.037 -0.037 -0.037 -0.012  0.063  0.013 -0.037 -0.012 -0.062 -0.062  0.063 -0.012 -0.062  0.013 -0.012  0.063 -0.012 
 0.073  0.023 -0.052 -0.027 -0.027  0.023 -0.052 -0.002 -0.052  0.023 -0.027 -0.002 -0.002 -0.052 -0.027 -0.027 -0.027  0.048 -0.052 -0.002 -0.052  0.073 -0.027 -0.027  0.048 -0.002 -0.002  0.098  0.073 -0.027 -0.027 -0.027 -0.027 -0.052  0.023 -0.002 -0.052 -0.027 -0.002 -0.002 -0.002  0.023 -0.027 -0.002 -0.052 -0.027 -0.052 -0.002 -0.027 -0.027 -0.002 -0.052  0.048 -0.052 -0.002 -0.027 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027 -0.002  0.048 -0.027 -0.002  0.023  0.023 -0.027  0.023  0.048 -0.002  0.023 -0.002  0.048  0.023 -0.052 -0.002 -0.052  0.098 -0.052  0.048 -0.002 -0.027 -0.027 -0.027 -0.027 -0.002 -0.002 -0.027 -0.027 -0.052 -0.052  0.073 -0.027 -0.052 -0.002 -0.002  0.073 -0.002 
 0.072  0.022 -0.052 -0.027 -0.027  0.022 -0.052 -0.002 -0.052  0.022 -0.027 -0.002 -0.002 -0.052 -0.027 -0.027 -0.027  0.047 -0.052 -0.002 -0.052  0.072 -0.027 -0.027  0.047 -0.002 -0.002  0.097  0.072 -0.027 -0.052 -0.027 -0.027 -0.052 -0.002 -0.002 -0.052 -0.027 -0.002  0.022 -0.002  0.022 -0.002 -0.002 -0.052 -0.052 -0.052 -0.002 -0.027 -0.027 -0.002 -0.052  0.047 -0.052 -0.002 -0.027 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.022  0.047 -0.027 -0.002  0.022  0.022 -0.027  0.047  0.047 -0.002  0.022 -0.002  0.022 -0.002 -0.052 -0.002 -0.027  0.072 -0.052  0.047  0.022 -0.027 -0.027 -0.027 -0.027 -0.002 -0.002 -0.027 -0.027 -0.052 -0.027  0.072 -0.027 -0.052 -0.002 -0.002  0.072 -0.027 
 0.073  0.048 -0.051 -0.026 -0.026  0.023 -0.051  0.023 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026  0.023 -0.051 -0.026 -0.026 -0.026 -0.026 -0.026 -0.001 -0.051  0.023 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.023  0.048 -0.026 -0.001  0.023  0.023 -0.026  0.023  0.048 -0.001  0.023 -0.001  0.023 -0.001 -0.051 -0.001 -0.026  0.073 -0.051  0.048  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.073 -0.026 -0.026 -0.026 -0.001  0.048 -0.026 
 0.073  0.048 -0.052 -0.027 -0.027  0.023 -0.052  0.023 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.023 -0.002  0.023 -0.027  0.023 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.023 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.023  0.048 -0.027 -0.002  0.023  0.023 -0.027  0.023  0.048 -0.002  0.023 -0.002  0.023 -0.002 -0.052 -0.002 -0.027  0.073 -0.052  0.048  0.023 -0.027 -0.002 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.052 -0.027  0.073 -0.027 -0.027 -0.027 -0.002  0.048 -0.027 
 0.071  0.046 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.021  0.021 -0.004  0.021 -0.029  0.021 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.029 -0.004  0.021  0.021  0.021  0.021  0.046 -0.004  0.021 -0.004  0.021 -0.004 -0.054 -0.004 -0.029  0.071 -0.054  0.046  0.021 -0.029  0.021 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.029  0.071 -0.029 -0.004 -0.029 -0.004  0.046 -0.029 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.020  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.004 -0.004  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.004  0.020  0.020 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.004  0.070 -0.029 -0.004 -0.029 -0.004  0.045 -0.029 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.090  0.040 -0.059 -0.059 -0.059 -0.009 -0.059  0.015 -0.084 -0.009 -0.009 -0.009 -0.059 -0.009 -0.059 -0.084 -0.034  0.040  0.065 -0.034 -0.084  0.090 -0.059 -0.059  0.040 -0.034  0.015  0.090  0.240 -0.009 -0.059 -0.009 -0.084 -0.084 -0.034  0.015 -0.059 -0.034 -0.009 -0.009 -0.034  0.015 -0.034  0.015 -0.059 -0.034 -0.059 -0.009 -0.034 -0.059 -0.009 -0.059  0.065 -0.034 -0.009 -0.084 -0.059 -0.084 -0.084 -0.059 -0.034 -0.059  0.040  0.015 -0.009 -0.034  0.040  0.015  0.065 -0.009  0.140  0.015  0.015  0.040 -0.009 -0.009 -0.059 -0.009  0.090  0.240 -0.084  0.090  0.140 -0.034 -0.009 -0.009 -0.034  0.015 -0.034 -0.034 -0.034 -0.059 -0.034  0.065 -0.059 -0.009  0.015 -0.009  0.040 -0.059 
 0.199  0.000 -0.125 -0.075 -0.100 -0.050 -0.025 -0.025 -0.125 -0.050 -0.025 -0.050 -0.100 -0.025 -0.075 -0.100 -0.025  0.000  0.075 -0.100 -0.100  0.149 -0.075 -0.050  0.149 -0.025  0.000  0.025  0.274 -0.025 -0.100 -0.075 -0.149 -0.149 -0.025  0.075 -0.075 -0.050 -0.075 -0.075 -0.050  0.025 -0.025  0.025 -0.100  0.000 -0.100  0.050 -0.100 -0.075 -0.075  0.000  0.075 -0.050 -0.050 -0.075 -0.050 -0.075 -0.100 -0.125 -0.100 -0.075  0.025  0.000 -0.050 -0.025  0.075 -0.025  0.100 -0.050  0.149  0.025  0.050 -0.025  0.025  0.050 -0.075 -0.050  0.100  0.374 -0.149  0.199  0.224 -0.075 -0.025 -0.025  0.000 -0.025 -0.100 -0.075 -0.075 -0.050 -0.050  0.050 -0.100 -0.025 -0.025  0.050  0.025 -0.100 
 0.260 -0.014 -0.139 -0.089 -0.089 -0.039 -0.064 -0.039 -0.114 -0.039 -0.064 -0.089 -0.089 -0.039 -0.064 -0.089 -0.064 -0.039  0.035 -0.114 -0.139  0.085 -0.089 -0.089  0.110 -0.064 -0.014 -0.014  0.235 -0.014 -0.064 -0.114 -0.189 -0.189 -0.014  0.060 -0.064 -0.064 -0.089 -0.114 -0.089  0.035 -0.064  0.010 -0.139  0.010 -0.114  0.085 -0.114 -0.114 -0.114 -0.039  0.060 -0.064 -0.089 -0.089 -0.064 -0.114 -0.139 -0.139 -0.139 -0.064 -0.014 -0.039 -0.064 -0.014  0.085 -0.014  0.185 -0.039  0.260 -0.014  0.035  0.010  0.060  0.035 -0.064 -0.014  0.110  0.459 -0.189  0.185  0.284 -0.039 -0.064 -0.114 -0.014 -0.014 -0.139 -0.114 -0.114 -0.089 -0.089  0.010 -0.139 -0.064 -0.064  0.060  0.010 -0.114 
 0.203  0.078 -0.146 -0.146 -0.046 -0.096 -0.071 -0.046 -0.121 -0.096 -0.046 -0.071 -0.071 -0.046  0.003 -0.121 -0.071 -0.046  0.028 -0.171 -0.146  0.053 -0.146 -0.096  0.153 -0.096 -0.021 -0.046  0.228 -0.071 -0.046 -0.121 -0.221 -0.246  0.028  0.103 -0.071 -0.096 -0.121 -0.121 -0.046 -0.071 -0.096  0.078 -0.096 -0.046 -0.121  0.078 -0.171 -0.096 -0.121 -0.046  0.053  0.003 -0.071 -0.071 -0.071 -0.146 -0.171 -0.146 -0.171  0.003 -0.046 -0.046 -0.096 -0.021  0.078  0.003  0.228 -0.046  0.253 -0.046 -0.021 -0.021  0.053  0.053 -0.096 -0.021  0.103  0.502 -0.246  0.253  0.352 -0.046 -0.096 -0.146 -0.021 -0.071 -0.121 -0.146 -0.046 -0.121 -0.096  0.028 -0.146 -0.096 -0.071  0.053 -0.021 -0.146 
 0.184  0.059 -0.140 -0.140  0.009 -0.140 -0.040 -0.040 -0.090 -0.065 -0.015 -0.065 -0.065 -0.065  0.009 -0.140 -0.090 -0.065  0.009 -0.190 -0.165  0.034 -0.140 -0.115  0.109 -0.090 -0.040 -0.090  0.234 -0.090 -0.040 -0.165 -0.215 -0.265  0.009  0.059 -0.065 -0.065 -0.140 -0.165 -0.065 -0.115 -0.115  0.084 -0.140 -0.015 -0.140  0.084 -0.140 -0.115 -0.140 -0.065  0.084 -0.040 -0.065 -0.090 -0.090 -0.140 -0.190 -0.190 -0.165  0.034 -0.065 -0.065 -0.090 -0.015  0.084 -0.015  0.234 -0.090  0.259 -0.015 -0.040  0.009  0.034  0.034 -0.115  0.009  0.159  0.408 -0.265  0.234  0.308 -0.040 -0.090 -0.140 -0.040 -0.090 -0.090 -0.165 -0.065 -0.140 -0.065  0.034 -0.140 -0.115 -0.015  0.059 -0.040 -0.090 
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 0.157  0.008 -0.092 -0.042 -0.017 -0.017 -0.117 -0.067 -0.092 -0.042 -0.042 -0.042 -0.117 -0.017 -0.017 -0.042 -0.042  0.058  0.108 -0.092 -0.092  0.033 -0.092 -0.067  0.058 -0.017  0.058  0.008  0.108 -0.017 -0.042 -0.092 -0.117 -0.117  0.058 -0.017 -0.067 -0.067 -0.017 -0.092  0.008 -0.042 -0.042  0.058 -0.092 -0.067 -0.117 -0.067 -0.092 -0.017 -0.117 -0.017  0.133 -0.017 -0.017 -0.042 -0.042 -0.092 -0.067 -0.067 -0.067 -0.042 -0.042 -0.017 -0.067 -0.042 -0.017  0.033 -0.042  0.008  0.008 -0.017  0.008  0.008 -0.017 -0.042 -0.067 -0.042 -0.067  0.307 -0.117  0.332  0.108 -0.042 -0.117 -0.092  0.008  0.008  0.008 -0.067 -0.017 -0.092 -0.067  0.033 -0.042 -0.067  0.033 -0.117 -0.017 -0.042 
 0.144  0.019 -0.080 -0.030 -0.005 -0.005 -0.105 -0.055 -0.080 -0.030 -0.030 -0.005 -0.105 -0.030 -0.055 -0.055 -0.030  0.069  0.094 -0.080 -0.080  0.019 -0.080 -0.080  0.069 -0.005  0.044  0.019  0.119 -0.005 -0.030 -0.080 -0.105 -0.105  0.044 -0.030 -0.080 -0.055 -0.005 -0.080  0.019 -0.030 -0.030  0.019 -0.080 -0.055 -0.105 -0.055 -0.080 -0.005 -0.105 -0.005  0.144 -0.030 -0.030 -0.055 -0.080 -0.105 -0.055 -0.055 -0.055 -0.030 -0.030 -0.030 -0.055 -0.030 -0.005  0.044 -0.055 -0.005  0.019 -0.005  0.044 -0.005 -0.005 -0.030 -0.055 -0.030 -0.080  0.293 -0.105  0.318  0.094 -0.055 -0.105 -0.080 -0.005  0.019  0.019 -0.055 -0.030 -0.080 -0.080  0.044 -0.030 -0.055  0.044 -0.080 -0.005 -0.030 
 0.156  0.031 -0.068 -0.018  0.006  0.006 -0.093 -0.043 -0.068 -0.018 -0.043  0.006 -0.093 -0.043 -0.068 -0.043 -0.043  0.056  0.081 -0.068 -0.093  0.056 -0.093 -0.068  0.056  0.006  0.031  0.031  0.106  0.031 -0.043 -0.068 -0.093 -0.093  0.056  0.006 -0.093 -0.043 -0.043 -0.068  0.031 -0.018 -0.018  0.031 -0.068 -0.068 -0.093 -0.043 -0.068 -0.018 -0.093 -0.068  0.131 -0.068 -0.018 -0.068 -0.068 -0.093 -0.068 -0.068 -0.043 -0.018 -0.018  0.006 -0.043 -0.018  0.031  0.056 -0.043 -0.018  0.031  0.006  0.056 -0.018  0.031 -0.043 -0.043 -0.018 -0.068  0.231 -0.093  0.256  0.106 -0.043 -0.093 -0.068 -0.018  0.031  0.006 -0.018 -0.018 -0.068 -0.068  0.056 -0.043 -0.043  0.031 -0.043  0.006 -0.018 
 0.141  0.041 -0.059 -0.034 -0.009  0.016 -0.084 -0.034 -0.084 -0.009 -0.034 -0.009 -0.084 -0.034 -0.059 -0.059 -0.034  0.041  0.091 -0.059 -0.084  0.066 -0.084 -0.084  0.041  0.016  0.016  0.041  0.091  0.041 -0.059 -0.059 -0.084 -0.084  0.041  0.016 -0.084 -0.034 -0.034 -0.059  0.016 -0.009 -0.009  0.041 -0.059 -0.059 -0.084 -0.034 -0.059 -0.009 -0.084 -0.059  0.116 -0.059 -0.034 -0.059 -0.059 -0.084 -0.059 -0.084 -0.034 -0.059 -0.009  0.016 -0.034  0.016  0.041  0.066 -0.034 -0.009  0.066  0.016  0.016 -0.009  0.041 -0.034 -0.034 -0.034 -0.059  0.190 -0.084  0.240  0.091 -0.034 -0.084 -0.059 -0.009  0.041 -0.009 -0.034 -0.009 -0.084 -0.059  0.041 -0.034 -0.034  0.016 -0.034  0.016 -0.034 
 0.078  0.028 -0.072 -0.047 -0.022  0.028 -0.072 -0.022 -0.072  0.003 -0.022 -0.022 -0.072 -0.047 -0.047 -0.047 -0.022  0.028  0.053 -0.022 -0.072  0.053 -0.047 -0.047  0.028  0.003  0.003  0.078  0.103  0.003 -0.047 -0.047 -0.072 -0.072 -0.022  0.028 -0.072 -0.047 -0.022 -0.022 -0.022  0.003  0.003  0.003 -0.072 -0.047 -0.072 -0.047 -0.047 -0.047 -0.022 -0.072  0.078 -0.047 -0.022 -0.047 -0.047 -0.072 -0.047 -0.072 -0.022 -0.047  0.003  0.028 -0.047 -0.022  0.028  0.028 -0.047  0.003  0.078  0.028  0.028  0.003  0.028 -0.047 -0.022  0.003 -0.047  0.152 -0.072  0.227  0.053 -0.022 -0.072 -0.047 -0.022  0.003  0.003 -0.022  0.003 -0.072 -0.072  0.053 -0.022 -0.047  0.003 -0.022  0.028 -0.047 
 0.084  0.009 -0.065 -0.040 -0.015  0.034 -0.065 -0.015 -0.065  0.009 -0.040 -0.015 -0.065 -0.065 -0.040 -0.040 -0.015  0.034  0.009 -0.015 -0.065  0.084 -0.040 -0.040  0.034 -0.015 -0.015  0.084  0.109 -0.015 -0.040 -0.040 -0.065 -0.065 -0.015  0.034 -0.065 -0.040 -0.015 -0.015 -0.015  0.009 -0.015  0.009 -0.065 -0.040 -0.065 -0.015 -0.040 -0.040 -0.015 -0.065  0.059 -0.065 -0.015 -0.040 -0.040 -0.065 -0.065 -0.065  0.009 -0.040  0.009  0.034 -0.040 -0.015  0.034  0.034 -0.040  0.009  0.059  0.034  0.009  0.009  0.034 -0.015 -0.040  0.009 -0.040  0.134 -0.065  0.209  0.059 -0.015 -0.040 -0.040 -0.040  0.034  0.009 -0.015  0.009 -0.065 -0.065  0.059 -0.015 -0.040 -0.015 -0.015  0.034 -0.040 
 0.068  0.018 -0.057 -0.032 -0.032  0.018 -0.057 -0.007 -0.057 -0.007 -0.032 -0.007 -0.032 -0.057 -0.032 -0.057 -0.032  0.043 -0.007 -0.007 -0.057  0.093 -0.032 -0.032  0.043 -0.032 -0.007  0.068  0.068 -0.032 -0.032 -0.032 -0.057 -0.057 -0.007  0.018 -0.032 -0.032 -0.007 -0.007 -0.007  0.018 -0.007 -0.007 -0.057 -0.032 -0.057 -0.007 -0.032 -0.032 -0.007 -0.057  0.018 -0.057 -0.007 -0.057 -0.032 -0.057 -0.057 -0.057 -0.032 -0.032  0.018  0.043 -0.032 -0.007  0.043  0.018 -0.032  0.018  0.043  0.018  0.018 -0.007  0.018 -0.007 -0.057 -0.007 -0.032  0.068 -0.057  0.118  0.018 -0.007 -0.007 -0.032 -0.032  0.018 -0.007 -0.032 -0.032 -0.057 -0.057  0.068 -0.007 -0.032 -0.032 -0.007  0.043 -0.032 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.071 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.028 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003 -0.003 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.028 -0.003  0.021  0.021 -0.028  0.021  0.046  0.021  0.021 -0.003  0.021 -0.003 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.003 -0.003 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.053  0.071 -0.028 -0.028 -0.028 -0.003  0.046 -0.028 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.003 -0.003  0.021  0.021 -0.003  0.021  0.046  0.021  0.021 -0.003  0.021  0.021 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.028  0.021 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.003  0.071 -0.028 -0.028 -0.028 -0.003  0.046 -0.028 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.004 -0.004  0.021  0.021 -0.004  0.021  0.046  0.021  0.021 -0.004  0.021  0.021 -0.054 -0.004 -0.029  0.071 -0.054  0.046  0.021 -0.029  0.021 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.004  0.071 -0.029 -0.029 -0.029 -0.004  0.046 -0.029 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
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 0.198 -0.051 -0.226 -0.151 -0.101 -0.126 -0.151 -0.001 -0.126 -0.051  0.023  0.123 -0.201  0.098  0.123 -0.126  0.372 -0.201 -0.076 -0.201 -0.226  0.098 -0.226 -0.176  0.223 -0.001 -0.101 -0.126 -0.026 -0.076 -0.051 -0.201 -0.251 -0.276 -0.076 -0.076 -0.251 -0.076 -0.176 -0.201 -0.051 -0.201 -0.126  0.023 -0.026 -0.226 -0.176 -0.126 -0.176 -0.151 -0.126 -0.101 -0.076 -0.126 -0.026  0.048 -0.001 -0.051 -0.276 -0.201 -0.201 -0.001 -0.151 -0.051 -0.076 -0.126 -0.051  0.198 -0.101  0.073 -0.001 -0.126 -0.026  0.422 -0.051 -0.001 -0.201 -0.101  0.223  0.447 -0.251  0.347  0.273 -0.051 -0.176 -0.051 -0.101 -0.151 -0.026 -0.201  0.123 -0.151 -0.076 -0.026 -0.201 -0.176  0.048 -0.101 -0.001  0.297 
 0.195 -0.054 -0.229 -0.154 -0.104 -0.129 -0.154  0.020 -0.129 -0.029  0.020  0.120 -0.204  0.095  0.120 -0.129  0.369 -0.204 -0.079 -0.204 -0.229  0.095 -0.229 -0.179  0.220 -0.004 -0.079 -0.129 -0.029 -0.079 -0.054 -0.204 -0.254 -0.279 -0.079 -0.079 -0.254 -0.104 -0.179 -0.204 -0.029 -0.204 -0.129  0.020 -0.029 -0.229 -0.179 -0.104 -0.179 -0.154 -0.129 -0.104 -0.054 -0.129 -0.029  0.045 -0.004 -0.079 -0.254 -0.204 -0.204 -0.004 -0.154 -0.054 -0.079 -0.104 -0.029  0.195 -0.079  0.070 -0.004 -0.129 -0.054  0.394 -0.054 -0.004 -0.204 -0.104  0.220  0.444 -0.254  0.344  0.270 -0.004 -0.179 -0.054 -0.129 -0.129 -0.079 -0.204  0.120 -0.129 -0.079 -0.029 -0.204 -0.179  0.045 -0.129 -0.004  0.294 
 0.195 -0.029 -0.228 -0.153 -0.104 -0.129 -0.153  0.021 -0.129 -0.054 -0.004  0.121 -0.178  0.121  0.121 -0.129  0.320 -0.203 -0.079 -0.203 -0.228  0.096 -0.228 -0.178  0.195 -0.029 -0.104 -0.129 -0.054 -0.079 -0.054 -0.203 -0.253 -0.278 -0.104 -0.079 -0.253 -0.104 -0.178 -0.203 -0.054 -0.203 -0.129 -0.004 -0.029 -0.228 -0.178 -0.104 -0.178 -0.153 -0.129 -0.104 -0.054 -0.129 -0.004  0.046 -0.054 -0.079 -0.253 -0.203 -0.203  0.021 -0.153 -0.079 -0.104 -0.104 -0.004  0.195 -0.079  0.071 -0.029 -0.104 -0.054  0.395 -0.054  0.021 -0.203 -0.104  0.220  0.444 -0.278  0.345  0.270 -0.004 -0.178 -0.054 -0.129 -0.129 -0.104 -0.178  0.046 -0.153 -0.104 -0.054 -0.203 -0.178  0.046 -0.178 -0.004  0.295 
 0.169 -0.030 -0.230 -0.155 -0.105 -0.130 -0.155  0.019 -0.130 -0.055 -0.030  0.119 -0.180  0.119  0.119 -0.130  0.269 -0.205 -0.080 -0.205 -0.230  0.094 -0.230 -0.205  0.169 -0.055 -0.155 -0.130 -0.055 -0.080 -0.055 -0.205 -0.255 -0.304 -0.105 -0.080 -0.255 -0.105 -0.180 -0.205 -0.055 -0.205 -0.130 -0.005 -0.030 -0.230 -0.180 -0.105 -0.205 -0.155 -0.130 -0.105 -0.055 -0.130 -0.005  0.019 -0.030 -0.105 -0.255 -0.230 -0.230  0.019 -0.155 -0.080 -0.130 -0.030 -0.005  0.194 -0.080  0.069 -0.030 -0.105 -0.055  0.368 -0.055  0.019 -0.205 -0.105  0.219  0.443 -0.280  0.318  0.194 -0.005 -0.180 -0.055 -0.130 -0.130 -0.130 -0.180 -0.005 -0.155 -0.080 -0.055 -0.180 -0.155  0.044 -0.180 -0.005  0.293 
 0.165 -0.034 -0.233 -0.158 -0.084 -0.134 -0.158  0.041 -0.158 -0.059 -0.084  0.116 -0.183  0.066  0.116 -0.109  0.215 -0.208 -0.084 -0.208 -0.233  0.091 -0.208 -0.233  0.141 -0.084 -0.158 -0.134 -0.034 -0.059 -0.034 -0.208 -0.258 -0.308 -0.109 -0.084 -0.258 -0.134 -0.208 -0.208 -0.059 -0.208 -0.158 -0.009 -0.009 -0.233 -0.183 -0.109 -0.208 -0.158 -0.084 -0.134 -0.059 -0.134  0.016  0.016 -0.009 -0.134 -0.258 -0.258 -0.233  0.016 -0.208 -0.084 -0.134 -0.009 -0.009  0.215 -0.109  0.091 -0.034 -0.109 -0.084  0.365 -0.059 -0.034 -0.208 -0.109  0.215  0.439 -0.283  0.290  0.141  0.016 -0.208 -0.059 -0.134 -0.134 -0.158 -0.208 -0.009 -0.158 -0.059 -0.059 -0.183 -0.158  0.041 -0.183 -0.034  0.290 
 0.162 -0.037 -0.236 -0.161 -0.087 -0.137 -0.161  0.038 -0.161 -0.037 -0.087  0.113 -0.186  0.063  0.138 -0.112  0.212 -0.186 -0.087 -0.211 -0.211  0.088 -0.236 -0.236  0.138 -0.087 -0.161 -0.137 -0.012 -0.062 -0.037 -0.211 -0.261 -0.311 -0.112 -0.087 -0.261 -0.137 -0.211 -0.211 -0.062 -0.186 -0.161 -0.012 -0.012 -0.236 -0.186 -0.112 -0.211 -0.161 -0.087 -0.112 -0.012 -0.137  0.013  0.013 -0.012 -0.137 -0.261 -0.261 -0.236  0.013 -0.211 -0.087 -0.137 -0.012 -0.012  0.212 -0.112  0.113 -0.012 -0.112 -0.087  0.362 -0.062 -0.037 -0.211 -0.112  0.237  0.436 -0.286  0.287  0.138  0.013 -0.211 -0.037 -0.137 -0.137 -0.161 -0.211 -0.012 -0.186 -0.062 -0.062 -0.186 -0.161  0.038 -0.186 -0.037  0.287 
 0.211 -0.038 -0.238 -0.138 -0.088 -0.138 -0.188  0.036 -0.163 -0.038 -0.063  0.111 -0.188  0.061  0.161 -0.088  0.211 -0.188 -0.088 -0.213 -0.213  0.086 -0.238 -0.238  0.136 -0.088 -0.163 -0.138 -0.013 -0.088 -0.038 -0.213 -0.263 -0.287 -0.113 -0.088 -0.263 -0.113 -0.188 -0.213 -0.063 -0.188 -0.163 -0.013  0.011 -0.213 -0.213 -0.113 -0.188 -0.163 -0.063 -0.113 -0.013 -0.138  0.036 -0.013 -0.038 -0.138 -0.263 -0.263 -0.238  0.011 -0.213 -0.088 -0.138 -0.013 -0.013  0.211 -0.088  0.136 -0.013 -0.113 -0.088  0.335 -0.063 -0.038 -0.213 -0.088  0.236  0.385 -0.287  0.285  0.136  0.011 -0.213 -0.063 -0.138 -0.138 -0.163 -0.188 -0.013 -0.188 -0.088 -0.063 -0.188 -0.163  0.036 -0.163 -0.063  0.310 
 0.167 -0.032 -0.206 -0.107 -0.032 -0.057 -0.156 -0.082 -0.107 -0.057 -0.032  0.018 -0.181  0.118  0.093 -0.057  0.167 -0.132 -0.032 -0.132 -0.181  0.043 -0.156 -0.181  0.142 -0.057 -0.107 -0.082 -0.007 -0.057 -0.007 -0.181 -0.181 -0.231 -0.082 -0.057 -0.181 -0.132 -0.156 -0.132 -0.007 -0.132 -0.156  0.043 -0.057 -0.156 -0.181 -0.107 -0.181 -0.082 -0.057 -0.107 -0.007 -0.107  0.043 -0.057 -0.007 -0.107 -0.206 -0.181 -0.181  0.043 -0.156 -0.057 -0.132 -0.007  0.018  0.192 -0.057  0.142  0.018 -0.057 -0.107  0.317 -0.032 -0.032 -0.132 -0.107  0.093  0.267 -0.206  0.267  0.093  0.018 -0.132 -0.082 -0.107 -0.057 -0.082 -0.206  0.018 -0.156 -0.057 -0.057 -0.132 -0.107  0.068 -0.132  0.018  0.267 
 0.096 -0.004 -0.104 -0.104 -0.054 -0.029 -0.104 -0.079 -0.054 -0.004 -0.054 -0.004 -0.129  0.096  0.096 -0.054  0.046 -0.054  0.046 -0.079 -0.104  0.021 -0.129 -0.104  0.121 -0.029 -0.054 -0.054  0.021 -0.004 -0.004 -0.129 -0.153 -0.153 -0.004 -0.004 -0.104 -0.079 -0.054 -0.104 -0.004 -0.054 -0.079 -0.029 -0.079 -0.079 -0.104 -0.029 -0.104 -0.029 -0.104 -0.129  0.021 -0.079 -0.029 -0.079 -0.029 -0.029 -0.104 -0.104 -0.104 -0.029 -0.079 -0.029 -0.054 -0.004 -0.029  0.195 -0.079  0.046 -0.054 -0.054 -0.029  0.145 -0.079 -0.054 -0.079 -0.054  0.046  0.270 -0.129  0.345  0.071  0.021 -0.079 -0.129 -0.054 -0.029 -0.029 -0.129 -0.029 -0.153 -0.079  0.021 -0.029 -0.129  0.071 -0.104 -0.004  0.145 
 0.042  0.017 -0.083 -0.083 -0.033 -0.033 -0.108 -0.058 -0.033 -0.008 -0.033 -0.083 -0.108  0.092  0.067 -0.058  0.017 -0.033  0.042 -0.058 -0.108  0.017 -0.108 -0.108  0.117 -0.008 -0.058 -0.033  0.042 -0.008 -0.008 -0.108 -0.133 -0.133  0.017  0.017 -0.108 -0.083 -0.033 -0.083  0.017 -0.058 -0.058 -0.008 -0.058 -0.058 -0.108 -0.033 -0.058 -0.008 -0.108 -0.133  0.017 -0.083 -0.008 -0.083 -0.033 -0.033 -0.083 -0.083 -0.083 -0.008 -0.058 -0.033 -0.033  0.017 -0.008  0.166 -0.058  0.067 -0.058 -0.033 -0.008  0.142 -0.058 -0.058 -0.058 -0.108  0.042  0.241 -0.108  0.341  0.017  0.017 -0.083 -0.108 -0.033 -0.008 -0.008 -0.108 -0.008 -0.133 -0.058  0.042 -0.008 -0.108  0.117 -0.083  0.017  0.117 
 0.015  0.040 -0.060 -0.085 -0.010 -0.010 -0.110 -0.035 -0.035  0.015 -0.010 -0.085 -0.110  0.115 -0.035 -0.060  0.015  0.015  0.065 -0.085 -0.060  0.015 -0.085 -0.085  0.090 -0.010 -0.010  0.015  0.065 -0.010 -0.010 -0.085 -0.110 -0.110  0.040  0.015 -0.085 -0.110 -0.085 -0.060  0.015 -0.035 -0.035 -0.010 -0.035 -0.085 -0.085 -0.060 -0.060 -0.010 -0.110 -0.110  0.090 -0.085 -0.010 -0.085 -0.010 -0.010 -0.060 -0.060 -0.060 -0.010 -0.035 -0.035 -0.035 -0.010 -0.010  0.164 -0.060  0.065 -0.035 -0.010  0.015  0.065 -0.035 -0.060 -0.035 -0.085 -0.010  0.140 -0.110  0.314  0.015 -0.010 -0.060 -0.085 -0.010 -0.010  0.040 -0.060  0.040 -0.110 -0.085  0.065 -0.010 -0.085  0.065 -0.060  0.015  0.115 
 0.020  0.020 -0.055 -0.080 -0.005 -0.005 -0.105 -0.055 -0.030  0.020 -0.030 -0.080 -0.105  0.095 -0.055 -0.055  0.020  0.045  0.070 -0.080 -0.055  0.020 -0.080 -0.080  0.095 -0.005 -0.005  0.020  0.070 -0.005 -0.005 -0.080 -0.105 -0.105  0.045 -0.005 -0.080 -0.105 -0.055 -0.055 -0.005 -0.030 -0.030 -0.005 -0.080 -0.080 -0.080 -0.055 -0.055 -0.005 -0.105 -0.105  0.070 -0.055 -0.005 -0.080 -0.030 -0.005 -0.055 -0.080 -0.055 -0.005 -0.030 -0.005 -0.030 -0.005 -0.005  0.144 -0.055  0.070 -0.005 -0.005  0.020  0.045 -0.005 -0.055 -0.055 -0.055 -0.055  0.120 -0.105  0.319 -0.005 -0.055 -0.055 -0.080 -0.005 -0.005  0.020 -0.055  0.045 -0.105 -0.080  0.045 -0.005 -0.080  0.045 -0.055  0.020  0.070 
 0.055  0.030 -0.045 -0.070 -0.020 -0.020 -0.095 -0.045 -0.020  0.055 -0.045 -0.045 -0.095  0.055 -0.045 -0.045  0.005  0.030  0.080 -0.070 -0.045  0.005 -0.095 -0.070  0.080  0.005 -0.020  0.055  0.080 -0.045 -0.020 -0.070 -0.095 -0.095  0.055  0.005 -0.070 -0.095 -0.045 -0.045  0.005 -0.020 -0.020 -0.020 -0.095 -0.070 -0.070 -0.045 -0.045 -0.020 -0.095 -0.095  0.055 -0.045 -0.020 -0.070 -0.045 -0.045 -0.045 -0.070 -0.045  0.005 -0.020  0.005  0.005  0.005  0.055  0.105 -0.070  0.030  0.005  0.005  0.055  0.005  0.030 -0.045 -0.045 -0.020 -0.070  0.130 -0.095  0.304  0.005 -0.045 -0.045 -0.070  0.005  0.005  0.030 -0.020  0.030 -0.095 -0.070  0.055 -0.020 -0.070  0.055 -0.045  0.005  0.055 
 0.060  0.035 -0.040 -0.065 -0.015 -0.015 -0.090 -0.040 -0.040  0.060 -0.040 -0.040 -0.090  0.010 -0.065 -0.040  0.010  0.035  0.085 -0.065 -0.065  0.010 -0.090 -0.065  0.085  0.010 -0.015  0.060  0.035 -0.040 -0.015 -0.065 -0.090 -0.090  0.060  0.010 -0.065 -0.090 -0.040 -0.065  0.010 -0.015 -0.015 -0.015 -0.090 -0.065 -0.065 -0.040 -0.040 -0.015 -0.090 -0.090  0.060 -0.065 -0.015 -0.065 -0.065 -0.040 -0.040 -0.090 -0.040  0.010 -0.015 -0.015  0.010  0.010  0.060  0.060 -0.065  0.010  0.010 -0.015  0.035  0.010  0.035 -0.040 -0.040 -0.015 -0.065  0.159 -0.090  0.309  0.035 -0.040 -0.065 -0.065  0.010  0.010  0.010 -0.040  0.035 -0.090 -0.065  0.035 -0.015 -0.065  0.060 -0.065  0.010  0.035 
 0.070  0.045 -0.079 -0.054 -0.004 -0.004 -0.079 -0.054 -0.029  0.070 -0.029 -0.029 -0.079 -0.004 -0.079 -0.029  0.020  0.045  0.070 -0.054 -0.054  0.020 -0.079 -0.054  0.045  0.020 -0.004  0.070  0.045 -0.004 -0.054 -0.054 -0.079 -0.079 -0.004 -0.004 -0.079 -0.054 -0.029 -0.054 -0.004 -0.004 -0.029 -0.004 -0.079 -0.054 -0.079 -0.029 -0.029 -0.029 -0.054 -0.079  0.070 -0.079 -0.004 -0.054 -0.054 -0.079 -0.054 -0.079 -0.029  0.020 -0.004  0.020  0.020 -0.004  0.045  0.045 -0.054  0.020  0.045 -0.004  0.045  0.020  0.045 -0.029 -0.029 -0.004 -0.054  0.170 -0.079  0.195 -0.004 -0.029 -0.054 -0.054 -0.004 -0.004  0.020 -0.029  0.045 -0.079 -0.079  0.045 -0.004 -0.054  0.070 -0.054  0.020  0.045 
 0.074  0.024 -0.075 -0.050 -0.000 -0.000 -0.050 -0.050 -0.050  0.074 -0.025 -0.025 -0.075 -0.000 -0.075 -0.025 -0.000  0.049  0.074 -0.025 -0.050  0.024 -0.050 -0.050  0.049 -0.025 -0.000  0.074  0.074 -0.000 -0.050 -0.050 -0.075 -0.075 -0.000 -0.000 -0.075 -0.050 -0.025 -0.050 -0.000 -0.000 -0.025 -0.000 -0.075 -0.075 -0.075 -0.025 -0.025 -0.025 -0.025 -0.075  0.074 -0.075 -0.000 -0.050 -0.025 -0.075 -0.050 -0.075 -0.025 -0.000 -0.000  0.024 -0.000 -0.000  0.024  0.049 -0.050  0.024  0.049 -0.000  0.049  0.049  0.049 -0.025 -0.050 -0.000 -0.050  0.124 -0.075  0.174 -0.025 -0.000 -0.025 -0.050 -0.050 -0.025  0.049 -0.025  0.049 -0.075 -0.075  0.049 -0.000 -0.050  0.074 -0.050  0.024  0.049 
 0.079  0.029 -0.070 -0.045 -0.020  0.004 -0.045 -0.020 -0.045  0.079 -0.020 -0.020 -0.070 -0.020 -0.045 -0.020 -0.020  0.029  0.054 -0.020 -0.045  0.054 -0.045 -0.045  0.029 -0.020  0.004  0.079  0.079  0.004 -0.045 -0.045 -0.070 -0.070  0.004 -0.020 -0.070 -0.045 -0.020 -0.045 -0.020  0.004 -0.045 -0.020 -0.070 -0.070 -0.070  0.004 -0.020 -0.045 -0.020 -0.070  0.054 -0.070  0.004 -0.045 -0.020 -0.070 -0.070 -0.070  0.004  0.004  0.004  0.054  0.004  0.004  0.029  0.029 -0.045  0.054  0.004  0.004  0.029  0.029  0.029  0.004 -0.045 -0.020 -0.045  0.104 -0.070  0.154 -0.045  0.004  0.004 -0.045 -0.045  0.004  0.054 -0.020  0.054 -0.070 -0.070  0.054  0.004 -0.045  0.079 -0.020  0.029  0.054 
 0.081  0.031 -0.068 -0.043 -0.018  0.006 -0.043 -0.043 -0.043  0.081 -0.043 -0.018 -0.043 -0.018 -0.043 -0.018 -0.018  0.031  0.031 -0.018 -0.043  0.031 -0.043 -0.043  0.031 -0.018 -0.018  0.081  0.081  0.006 -0.068 -0.043 -0.068 -0.068  0.006 -0.018 -0.068 -0.043 -0.018 -0.043 -0.018  0.006 -0.043 -0.018 -0.068 -0.068 -0.068  0.006 -0.018 -0.043 -0.018 -0.068  0.056 -0.068  0.006 -0.043 -0.018 -0.068 -0.068 -0.068  0.006  0.006  0.006  0.056  0.006  0.006  0.031  0.031 -0.043  0.056  0.006  0.006  0.031  0.006  0.031  0.006 -0.043 -0.018 -0.043  0.106 -0.068  0.156 -0.043  0.006  0.006 -0.043 -0.043  0.006  0.056 -0.018  0.056 -0.068 -0.068  0.056  0.006 -0.043  0.081 -0.043  0.031  0.056 
 0.084  0.034 -0.066 -0.041 -0.016  0.009 -0.041 -0.041 -0.041  0.084 -0.041 -0.016 -0.041 -0.016 -0.041 -0.016 -0.016  0.034  0.009 -0.016 -0.041  0.034 -0.016 -0.016  0.034 -0.041 -0.016  0.059  0.084 -0.016 -0.066 -0.041 -0.066 -0.066  0.009 -0.016 -0.066 -0.041 -0.016 -0.016 -0.016  0.009 -0.041 -0.016 -0.066 -0.066 -0.066  0.009 -0.016 -0.041  0.009 -0.066  0.059 -0.066  0.009 -0.066 -0.016 -0.066 -0.066 -0.066 -0.016  0.009  0.034  0.059  0.009  0.009  0.034  0.034 -0.041  0.059  0.009 -0.016  0.009  0.009  0.034  0.009 -0.041 -0.016 -0.041  0.059 -0.066  0.084 -0.066  0.009  0.009 -0.041 -0.041  0.009  0.059 -0.016  0.034 -0.066 -0.041  0.059  0.009 -0.041  0.059 -0.041  0.034  0.059 
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 0.146  0.022 -0.078 -0.028 -0.003 -0.028 -0.078 -0.053 -0.028 -0.028  0.022  0.022 -0.103  0.047 -0.053 -0.053 -0.003 -0.003  0.072 -0.053 -0.128 -0.003 -0.103 -0.103  0.047 -0.028 -0.003 -0.003  0.122  0.022 -0.028 -0.103 -0.128 -0.128  0.022 -0.028 -0.103 -0.078 -0.103 -0.078 -0.053 -0.053 -0.053 -0.003 -0.103 -0.103 -0.103  0.047 -0.078  0.022 -0.078 -0.053  0.072 -0.003 -0.028 -0.028 -0.053 -0.028 -0.053 -0.078 -0.053 -0.003 -0.053 -0.053 -0.078 -0.003  0.022  0.047 -0.078  0.022 -0.028 -0.003  0.022  0.221  0.022 -0.053 -0.078  0.022 -0.053  0.321 -0.103  0.371  0.146 -0.003 -0.103 -0.103 -0.003  0.022  0.022 -0.078  0.022 -0.128 -0.078  0.047 -0.003 -0.078  0.022 -0.053 -0.028 -0.003 
 0.115  0.015 -0.085 -0.035  0.015 -0.035 -0.085 -0.085 -0.035 -0.035 -0.010 -0.010 -0.085  0.015 -0.085 -0.060 -0.010  0.040  0.090 -0.060 -0.110  0.015 -0.110 -0.085  0.065 -0.010  0.015  0.015  0.140  0.015 -0.035 -0.085 -0.110 -0.110  0.040 -0.010 -0.085 -0.085 -0.060 -0.060 -0.010 -0.035 -0.035  0.015 -0.085 -0.085 -0.110 -0.010 -0.085 -0.010 -0.085 -0.035  0.065 -0.035 -0.035 -0.035 -0.035 -0.085 -0.060 -0.085 -0.035 -0.010 -0.035 -0.010 -0.060 -0.010  0.015  0.065 -0.085  0.040 -0.010  0.015  0.040  0.090  0.015 -0.035 -0.060 -0.035 -0.085  0.264 -0.110  0.364  0.090 -0.060 -0.085 -0.085  0.015  0.015  0.015 -0.035  0.015 -0.110 -0.085  0.040  0.015 -0.060  0.015 -0.035 -0.010  0.015 
 0.076  0.026 -0.074 -0.049  0.001 -0.024 -0.099 -0.074 -0.024 -0.024 -0.024 -0.049 -0.099  0.026 -0.099 -0.049 -0.024  0.051  0.101 -0.049 -0.099  0.001 -0.099 -0.074  0.051  0.001 -0.024  0.026  0.126  0.026 -0.024 -0.074 -0.099 -0.099  0.026  0.001 -0.074 -0.074 -0.049 -0.049  0.001 -0.024 -0.024  0.001 -0.074 -0.074 -0.099  0.001 -0.074 -0.024 -0.074 -0.024  0.076 -0.049 -0.049 -0.049 -0.024 -0.099 -0.049 -0.074 -0.049 -0.024 -0.024  0.001 -0.049  0.001  0.026  0.076 -0.074  0.026  0.026 -0.024  0.051  0.076  0.026 -0.024 -0.049 -0.049 -0.074  0.250 -0.099  0.375  0.051 -0.049 -0.099 -0.074  0.001  0.026  0.026 -0.024  0.001 -0.099 -0.074  0.026  0.001 -0.049  0.026 -0.049  0.001  0.026 
 0.093  0.043 -0.057 -0.057  0.018 -0.007 -0.082 -0.057 -0.032 -0.007 -0.007 -0.032 -0.082 -0.057 -0.082 -0.057 -0.032  0.043  0.068 -0.032 -0.082  0.018 -0.082 -0.082  0.068  0.018 -0.007  0.043  0.068  0.018 -0.057 -0.057 -0.082 -0.082  0.043  0.018 -0.057 -0.057 -0.032 -0.032  0.018 -0.007 -0.007  0.018 -0.082 -0.057 -0.082 -0.032 -0.057 -0.032 -0.057 -0.057  0.068 -0.057 -0.032 -0.057 -0.032 -0.082 -0.032 -0.082 -0.032 -0.007 -0.007 -0.007 -0.057 -0.007  0.043  0.068 -0.057 -0.007  0.043 -0.007  0.018 -0.007  0.043 -0.032 -0.032 -0.032 -0.057  0.167 -0.082  0.292  0.018 -0.032 -0.082 -0.057  0.018  0.043  0.043 -0.032 -0.007 -0.082 -0.057  0.043 -0.007 -0.032  0.043 -0.032  0.018 -0.007 
 0.074  0.049 -0.051 -0.051 -0.026 -0.001 -0.076 -0.051 -0.051 -0.001 -0.026 -0.026 -0.076 -0.076 -0.076 -0.051 -0.026  0.049  0.049 -0.051 -0.076  0.024 -0.076 -0.076  0.074  0.024 -0.001  0.049  0.074 -0.026 -0.051 -0.051 -0.076 -0.076  0.049  0.024 -0.051 -0.051 -0.026 -0.026  0.024 -0.001  0.024 -0.001 -0.076 -0.051 -0.076 -0.051 -0.051 -0.026 -0.076 -0.076  0.074 -0.051 -0.026 -0.051 -0.026 -0.076 -0.026 -0.076 -0.026 -0.001 -0.001 -0.001 -0.051 -0.001  0.049  0.074 -0.051 -0.001  0.074 -0.001  0.024 -0.026  0.049 -0.026 -0.026 -0.026 -0.051  0.148 -0.076  0.273  0.049 -0.026 -0.076 -0.051  0.024 -0.001  0.024 -0.026 -0.001 -0.076 -0.051  0.049 -0.001 -0.051  0.024 -0.051  0.024 -0.001 
 0.084  0.059 -0.066 -0.041 -0.016  0.009 -0.066 -0.016 -0.066  0.009 -0.016 -0.016 -0.041 -0.066 -0.066 -0.041 -0.016  0.059  0.034 -0.041 -0.066  0.034 -0.066 -0.066  0.059  0.009  0.009  0.059  0.084 -0.016 -0.041 -0.041 -0.066 -0.066  0.059  0.009 -0.066 -0.041 -0.016 -0.041  0.034  0.009 -0.016  0.009 -0.066 -0.041 -0.066 -0.041 -0.041 -0.016 -0.066 -0.066  0.059 -0.041 -0.016 -0.041 -0.041 -0.066 -0.041 -0.066 -0.016 -0.041  0.034  0.009 -0.041  0.009  0.034  0.059 -0.041  0.034  0.034  0.009  0.034 -0.041  0.034 -0.016 -0.041 -0.041 -0.016  0.109 -0.066  0.134  0.059 -0.016 -0.066 -0.041 -0.016 -0.016  0.009 -0.041 -0.016 -0.066 -0.041  0.034 -0.016 -0.041  0.009 -0.016  0.034 -0.016 
 0.088  0.038 -0.062 -0.037 -0.012  0.038 -0.062 -0.012 -0.062  0.013 -0.012 -0.012 -0.037 -0.062 -0.062 -0.037 -0.012  0.063 -0.012 -0.012 -0.062  0.038 -0.037 -0.037  0.038  0.013 -0.012  0.063  0.088 -0.037 -0.037 -0.037 -0.062 -0.062  0.063  0.013 -0.062 -0.037 -0.012  0.013  0.038  0.013 -0.012  0.013 -0.062 -0.037 -0.062 -0.037 -0.037 -0.012 -0.012 -0.062  0.038 -0.037 -0.012 -0.037 -0.037 -0.062 -0.062 -0.062 -0.062 -0.037  0.013  0.013 -0.037  0.013  0.038  0.063 -0.037  0.038  0.038 -0.012  0.013 -0.012  0.038 -0.012 -0.062 -0.012 -0.012  0.088 -0.062  0.088  0.038 -0.037 -0.062 -0.037 -0.012 -0.012 -0.012 -0.037 -0.037 -0.062 -0.012  0.063 -0.012 -0.037 -0.012 -0.012  0.038 -0.012 
 0.071  0.046 -0.054 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.029 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.029 -0.029 -0.054 -0.054 -0.004  0.021 -0.054 -0.029 -0.004  0.021 -0.004  0.021 -0.004  0.046 -0.054 -0.054 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.054 -0.029  0.021  0.046 -0.029 -0.004  0.021  0.021 -0.029  0.046  0.046 -0.004  0.021 -0.004  0.021 -0.029 -0.054 -0.004 -0.029  0.071 -0.054  0.071  0.021 -0.029 -0.054 -0.029 -0.029 -0.004 -0.004 -0.029 -0.029 -0.054 -0.029  0.071 -0.029 -0.029 -0.004 -0.004  0.046 -0.029 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003  0.022 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.047 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022  0.022 -0.028  0.022  0.047 -0.003  0.022 -0.003  0.022 -0.003 -0.053 -0.003 -0.028  0.072 -0.053  0.072  0.022 -0.028 -0.003 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.028  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.072  0.047 -0.053 -0.028 -0.028  0.022 -0.053  0.022 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.047 -0.003 -0.003 -0.053  0.047 -0.028 -0.028  0.047 -0.028 -0.003  0.072  0.072 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.003  0.022 -0.028  0.022 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.022 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022  0.022 -0.003  0.022  0.047 -0.003  0.022 -0.003  0.022 -0.003 -0.053 -0.003 -0.028  0.072 -0.053  0.047  0.022 -0.028  0.022 -0.028 -0.028  0.022 -0.003 -0.028 -0.028 -0.053 -0.028  0.072 -0.028 -0.028 -0.028 -0.003  0.047 -0.028 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.003 -0.003  0.021  0.021 -0.003  0.021  0.046  0.021  0.021 -0.003  0.021  0.021 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.028  0.021 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.003  0.071 -0.028 -0.028 -0.028 -0.003  0.046 -0.028 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.055 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.030 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.156  0.031 -0.068 -0.018 -0.043  0.006 -0.068  0.006 -0.093 -0.043  0.006 -0.018 -0.018 -0.018 -0.068 -0.068 -0.018  0.056 -0.043 -0.043 -0.068  0.056 -0.068 -0.043  0.081 -0.043 -0.018  0.056  0.031 -0.018 -0.068 -0.018 -0.068 -0.093  0.006  0.031 -0.068 -0.043 -0.018 -0.018  0.056  0.031 -0.043  0.131 -0.018  0.006 -0.068  0.006 -0.068 -0.018  0.006 -0.093  0.006 -0.068 -0.018 -0.093 -0.068 -0.068 -0.093 -0.093 -0.043 -0.068 -0.018  0.006 -0.018 -0.018  0.056  0.031  0.031  0.006  0.106  0.031 -0.018  0.031  0.006  0.031 -0.093 -0.043  0.106  0.081 -0.093  0.131  0.056 -0.068 -0.018 -0.043 -0.018 -0.018 -0.043 -0.068 -0.068 -0.068 -0.043  0.131 -0.018 -0.043  0.006 -0.043  0.081 -0.043 
 0.118  0.018 -0.082 -0.057 -0.032 -0.032 -0.107 -0.032 -0.107 -0.082  0.043 -0.082 -0.057 -0.032 -0.107 -0.132 -0.032  0.093  0.093 -0.107 -0.107  0.068 -0.107 -0.082  0.118 -0.032 -0.032  0.018  0.068 -0.057 -0.007 -0.057 -0.132 -0.156  0.018 -0.007 -0.057 -0.057 -0.082 -0.032  0.068  0.043 -0.057  0.142 -0.082 -0.007 -0.132  0.043 -0.107 -0.057 -0.057 -0.057  0.068 -0.107 -0.032 -0.082 -0.107 -0.107 -0.107 -0.156 -0.032 -0.032 -0.007 -0.032 -0.032 -0.007  0.068  0.018 -0.007  0.068  0.118 -0.007 -0.057  0.018 -0.007  0.043 -0.132 -0.057  0.142  0.192 -0.156  0.242  0.093 -0.107 -0.057 -0.082 -0.007 -0.032 -0.082 -0.107 -0.057 -0.107 -0.057  0.093 -0.032 -0.057  0.018 -0.082  0.118 -0.082 
 0.197  0.023 -0.151 -0.027 -0.027 -0.077 -0.127 -0.002 -0.077 -0.127 -0.002 -0.077 -0.052 -0.027 -0.027 -0.127 -0.077  0.048  0.048 -0.151 -0.151  0.048 -0.102 -0.127  0.098 -0.077 -0.052 -0.002  0.073 -0.077 -0.002 -0.102 -0.102 -0.201  0.098 -0.027 -0.027 -0.077 -0.077 -0.052  0.048 -0.027 -0.077  0.123 -0.102 -0.027 -0.127  0.023 -0.102 -0.027 -0.102 -0.002  0.123 -0.027 -0.077 -0.102 -0.127 -0.127 -0.102 -0.151 -0.077 -0.052 -0.052 -0.052 -0.052 -0.027  0.123 -0.002 -0.027  0.048  0.147  0.023 -0.077  0.073 -0.002  0.023 -0.176 -0.027  0.123  0.247 -0.201  0.297  0.172 -0.102 -0.102 -0.127 -0.052 -0.077 -0.027 -0.151 -0.027 -0.151 -0.052  0.073 -0.027 -0.102  0.023 -0.077  0.123 -0.052 
 0.265 -0.009 -0.158 -0.034 -0.084 -0.158 -0.183 -0.059 -0.109 -0.183 -0.034 -0.084 -0.084 -0.009  0.041 -0.158 -0.109  0.016  0.041 -0.208 -0.183  0.066 -0.158 -0.158  0.091 -0.134 -0.059 -0.084  0.091 -0.109 -0.009 -0.059 -0.158 -0.258  0.091 -0.034 -0.059 -0.059 -0.134 -0.084 -0.009 -0.109 -0.084  0.066 -0.158 -0.084 -0.158  0.041 -0.109 -0.059 -0.134 -0.034  0.116  0.016 -0.059 -0.109 -0.084 -0.134 -0.158 -0.183 -0.109 -0.034 -0.059 -0.084 -0.109 -0.059  0.091  0.016  0.066  0.016  0.165  0.066 -0.084  0.066  0.016  0.016 -0.158  0.041  0.165  0.315 -0.233  0.365  0.215 -0.109 -0.134 -0.158 -0.109 -0.084 -0.059 -0.134 -0.059 -0.059 -0.109  0.016 -0.084 -0.084  0.041 -0.059  0.116 -0.059 
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 0.276 -0.048 -0.197 -0.098 -0.073 -0.123 -0.222 -0.123 -0.123 -0.123  0.027  0.002 -0.172  0.052  0.077 -0.123 -0.123 -0.098  0.002 -0.222 -0.247  0.127 -0.222 -0.222  0.027 -0.172 -0.123 -0.123  0.077 -0.123 -0.048 -0.197 -0.297 -0.247  0.102 -0.098 -0.147 -0.147 -0.073 -0.222 -0.023 -0.172 -0.123  0.027 -0.147 -0.123 -0.172 -0.073 -0.222 -0.123 -0.073 -0.048  0.027 -0.048 -0.197 -0.048 -0.023 -0.197 -0.222 -0.247 -0.197  0.002 -0.172 -0.147 -0.147  0.077  0.127 -0.048  0.151  0.127  0.052 -0.123  0.027  0.127 -0.073  0.002 -0.147 -0.023  0.226  0.326 -0.272  0.426  0.226 -0.023 -0.147 -0.147 -0.123 -0.147 -0.098 -0.197 -0.048 -0.197 -0.073 -0.098 -0.147 -0.098  0.077  0.002  0.077 -0.023 
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 0.273 -0.051 -0.201 -0.051 -0.051 -0.126 -0.251 -0.126 -0.151 -0.101  0.048 -0.001 -0.201  0.073  0.073 -0.126 -0.051 -0.101 -0.001 -0.251 -0.251  0.098 -0.251 -0.251  0.023 -0.151 -0.101 -0.151  0.073 -0.126 -0.051 -0.201 -0.300 -0.251  0.073 -0.101 -0.176 -0.176 -0.076 -0.226  0.023 -0.176 -0.126  0.048 -0.051 -0.126 -0.201 -0.126 -0.226 -0.126 -0.126 -0.026  0.023 -0.051 -0.201 -0.026 -0.001 -0.201 -0.226 -0.251 -0.151  0.023 -0.176 -0.151 -0.151  0.073  0.123 -0.051  0.148  0.098  0.048 -0.126 -0.001  0.073 -0.076 -0.001 -0.126 -0.051  0.223  0.297 -0.226  0.422  0.223 -0.001 -0.151 -0.151 -0.126 -0.151 -0.126 -0.201 -0.076 -0.226 -0.076 -0.101 -0.151 -0.101  0.073  0.073  0.073 -0.001 
 0.272 -0.052 -0.201 -0.052 -0.052 -0.127 -0.251 -0.127 -0.127 -0.102  0.048 -0.002 -0.201  0.048  0.073 -0.127 -0.027 -0.102 -0.002 -0.251 -0.251  0.123 -0.251 -0.251  0.023 -0.151 -0.102 -0.127  0.073 -0.102 -0.077 -0.226 -0.301 -0.251  0.098 -0.102 -0.176 -0.176 -0.077 -0.226  0.023 -0.176 -0.127  0.048 -0.052 -0.127 -0.201 -0.127 -0.226 -0.127 -0.127 -0.027  0.048 -0.052 -0.201 -0.027 -0.002 -0.201 -0.226 -0.251 -0.151  0.023 -0.176 -0.151 -0.151  0.073  0.147 -0.052  0.147  0.098  0.048 -0.127 -0.002  0.073 -0.077 -0.027 -0.127 -0.077  0.222  0.297 -0.226  0.397  0.222 -0.002 -0.151 -0.151 -0.127 -0.151 -0.127 -0.201 -0.077 -0.226 -0.077 -0.127 -0.151 -0.077  0.098  0.073  0.073 -0.002 
 0.268 -0.031 -0.205 -0.056 -0.056 -0.131 -0.255 -0.131 -0.131 -0.106  0.044 -0.006 -0.205  0.044  0.094 -0.131  0.019 -0.106 -0.006 -0.255 -0.255  0.119 -0.255 -0.255  0.044 -0.155 -0.106 -0.131  0.069 -0.106 -0.081 -0.230 -0.305 -0.255  0.094 -0.106 -0.180 -0.180 -0.081 -0.230  0.019 -0.180 -0.131  0.069 -0.056 -0.106 -0.155 -0.131 -0.230 -0.131 -0.131 -0.031  0.069 -0.056 -0.205 -0.031 -0.006 -0.205 -0.230 -0.255 -0.155  0.019 -0.155 -0.155 -0.155  0.069  0.143 -0.056  0.143  0.094  0.044 -0.106  0.019  0.069 -0.081 -0.031 -0.131 -0.081  0.218  0.293 -0.230  0.393  0.218 -0.006 -0.155 -0.131 -0.131 -0.155 -0.131 -0.205 -0.081 -0.230 -0.081 -0.131 -0.155 -0.081  0.094  0.069  0.069 -0.006 
 0.222 -0.052 -0.177 -0.052 -0.052 -0.102 -0.202 -0.077 -0.077 -0.077 -0.052 -0.002 -0.177  0.022  0.047 -0.052 -0.002 -0.052 -0.002 -0.202 -0.202  0.147 -0.177 -0.177  0.097 -0.102 -0.027 -0.052  0.047 -0.052 -0.027 -0.177 -0.252 -0.177  0.047 -0.102 -0.102 -0.152 -0.002 -0.202  0.047 -0.102 -0.102  0.047 -0.052 -0.077 -0.152 -0.077 -0.152 -0.052 -0.127 -0.002  0.072 -0.027 -0.152 -0.077 -0.002 -0.152 -0.177 -0.177 -0.152 -0.002 -0.127 -0.127 -0.102  0.047  0.147 -0.027 -0.002  0.022 -0.002 -0.102  0.022  0.022 -0.077 -0.052 -0.152 -0.027  0.222  0.247 -0.202  0.371  0.147 -0.052 -0.152 -0.127 -0.102 -0.077 -0.077 -0.177 -0.077 -0.152 -0.102 -0.052 -0.127 -0.077  0.097  0.022  0.072  0.022 
 0.163 -0.011 -0.111 -0.111 -0.036 -0.036 -0.136 -0.086 -0.061 -0.086 -0.061 -0.061 -0.136  0.014  0.014 -0.011  0.014 -0.011  0.039 -0.111 -0.136  0.139 -0.136 -0.111  0.089 -0.061  0.014 -0.036  0.039 -0.036  0.039 -0.111 -0.160 -0.111  0.039 -0.011 -0.061 -0.111 -0.061 -0.160  0.014 -0.036 -0.086  0.039 -0.036 -0.086 -0.160 -0.036 -0.111 -0.036 -0.160  0.014  0.114 -0.011 -0.061 -0.086 -0.061 -0.111 -0.111 -0.086 -0.111 -0.011 -0.086 -0.061 -0.061  0.014  0.014  0.014 -0.086  0.014 -0.011 -0.061 -0.036  0.064 -0.036 -0.036 -0.111 -0.086  0.089  0.213 -0.160  0.338  0.064 -0.011 -0.086 -0.111 -0.036  0.014  0.014 -0.136 -0.036 -0.111 -0.061  0.014 -0.061 -0.086  0.089 -0.036 -0.011  0.014 
 0.132  0.007 -0.093 -0.093 -0.043 -0.043 -0.118 -0.068 -0.043 -0.068 -0.068 -0.043 -0.118  0.032 -0.018 -0.018  0.032  0.032  0.057 -0.093 -0.118  0.107 -0.118 -0.093  0.082 -0.043  0.032 -0.018  0.032 -0.018  0.032 -0.118 -0.142 -0.142  0.057  0.007 -0.068 -0.093 -0.068 -0.142  0.007 -0.018 -0.068  0.032 -0.068 -0.068 -0.142 -0.018 -0.093 -0.018 -0.142  0.032  0.132  0.007 -0.043 -0.068 -0.043 -0.093 -0.093 -0.068 -0.093 -0.018 -0.068 -0.043 -0.068  0.007  0.007  0.032 -0.093  0.032 -0.018 -0.043 -0.018  0.007 -0.043 -0.043 -0.093 -0.093  0.007  0.181 -0.142  0.306  0.032  0.007 -0.093 -0.093 -0.018  0.032  0.032 -0.118 -0.018 -0.093 -0.043  0.007 -0.068 -0.068  0.082 -0.018 -0.018  0.032 
 0.158  0.008 -0.091 -0.066 -0.016 -0.041 -0.091 -0.041 -0.016 -0.041 -0.041 -0.041 -0.091 -0.016 -0.066 -0.016 -0.016  0.058  0.083 -0.066 -0.116  0.033 -0.116 -0.091  0.083 -0.016  0.058  0.008  0.058  0.008  0.058 -0.091 -0.116 -0.116  0.033  0.008 -0.041 -0.066 -0.066 -0.066  0.008  0.008 -0.041  0.058 -0.066 -0.041 -0.116  0.008 -0.091  0.008 -0.116  0.008  0.108 -0.016 -0.016 -0.066 -0.016 -0.091 -0.066 -0.066 -0.066  0.008 -0.041 -0.016 -0.066 -0.041  0.008  0.083 -0.066  0.033  0.008 -0.016  0.033 -0.016 -0.016 -0.041 -0.066 -0.066 -0.066  0.133 -0.116  0.233  0.058 -0.041 -0.091 -0.091 -0.016  0.033  0.033 -0.091 -0.016 -0.066 -0.066  0.033 -0.041 -0.066  0.033 -0.041  0.008 -0.016 
 0.119  0.019 -0.081 -0.031 -0.006 -0.031 -0.081 -0.031 -0.031 -0.031 -0.031 -0.031 -0.081 -0.006 -0.081 -0.056 -0.006  0.069  0.094 -0.081 -0.106  0.044 -0.106 -0.081  0.094 -0.006  0.044  0.019  0.044  0.019 -0.006 -0.081 -0.106 -0.106  0.044 -0.006 -0.081 -0.056 -0.056 -0.056  0.019 -0.006 -0.031  0.019 -0.056 -0.056 -0.106  0.019 -0.081  0.019 -0.106  0.019  0.119 -0.031 -0.006 -0.056 -0.006 -0.106 -0.056 -0.081 -0.056 -0.006 -0.031 -0.031 -0.081 -0.031  0.019  0.069 -0.056 -0.006  0.019 -0.006  0.019 -0.006 -0.006 -0.031 -0.056 -0.056 -0.081  0.143 -0.106  0.218  0.094 -0.031 -0.106 -0.081 -0.006  0.044  0.044 -0.081 -0.006 -0.056 -0.056  0.044 -0.031 -0.056  0.019 -0.031  0.019 -0.006 
 0.083  0.033 -0.066 -0.016 -0.016 -0.016 -0.091 -0.041 -0.016 -0.016 -0.016 -0.041 -0.091 -0.091 -0.091 -0.041 -0.016  0.083  0.108 -0.066 -0.091  0.033 -0.091 -0.066  0.083  0.008  0.033  0.033  0.058  0.008 -0.041 -0.066 -0.091 -0.091  0.058  0.008 -0.066 -0.066 -0.041 -0.041  0.033 -0.016 -0.016  0.033 -0.066 -0.041 -0.091 -0.016 -0.066  0.008 -0.091 -0.041  0.133 -0.041 -0.016 -0.041 -0.016 -0.091 -0.041 -0.091 -0.041  0.008 -0.016 -0.016 -0.066 -0.041  0.033  0.083 -0.066  0.008  0.033  0.008  0.033 -0.016  0.033 -0.016 -0.041 -0.041 -0.066  0.133 -0.091  0.183  0.083 -0.041 -0.091 -0.066  0.008 -0.016  0.008 -0.041 -0.041 -0.041 -0.066  0.058 -0.016 -0.066  0.033 -0.016  0.008  0.008 
 0.091  0.016 -0.059 -0.009 -0.009 -0.009 -0.084 -0.034 -0.009 -0.009 -0.059 -0.034 -0.084 -0.084 -0.084 -0.034 -0.034  0.066  0.066 -0.059 -0.084  0.041 -0.084 -0.059  0.041 -0.009  0.016  0.041  0.066 -0.009 -0.034 -0.059 -0.084 -0.084  0.041 -0.009 -0.084 -0.059 -0.034 -0.034  0.041 -0.009 -0.009  0.016 -0.059 -0.034 -0.084 -0.034 -0.059  0.016 -0.084 -0.034  0.116 -0.034 -0.009 -0.034 -0.009 -0.084 -0.059 -0.084 -0.034  0.016 -0.009 -0.009 -0.059 -0.034 -0.009  0.091 -0.059 -0.009  0.041 -0.009  0.041 -0.034  0.041 -0.009 -0.034 -0.034 -0.059  0.141 -0.084  0.165  0.091 -0.034 -0.084 -0.059 -0.034 -0.009  0.016 -0.034 -0.034 -0.034 -0.059  0.066 -0.009 -0.059  0.041 -0.009  0.016  0.016 
 0.100  0.000 -0.075  0.000 -0.025  0.000 -0.075 -0.025  0.000  0.000 -0.050 -0.025 -0.075 -0.075 -0.075 -0.050 -0.025  0.075  0.050 -0.050 -0.075  0.025 -0.075 -0.075  0.025  0.000  0.025  0.050  0.075  0.000 -0.050 -0.050 -0.075 -0.075  0.050  0.000 -0.075 -0.050 -0.025 -0.025  0.050  0.000  0.000  0.000 -0.075 -0.075 -0.075 -0.025 -0.050  0.025 -0.075 -0.050  0.075 -0.050 -0.025 -0.050  0.000 -0.075 -0.050 -0.075 -0.025 -0.025 -0.025  0.000 -0.050  0.000  0.000  0.075 -0.050  0.000  0.075  0.000  0.025 -0.025  0.050 -0.025 -0.025 -0.025 -0.050  0.149 -0.075  0.149  0.100 -0.025 -0.075 -0.050 -0.025  0.000  0.000 -0.025 -0.025 -0.050 -0.050  0.050  0.000 -0.050  0.025  0.000  0.025  0.025 
 0.100  0.000 -0.075  0.000 -0.025  0.000 -0.075 -0.025  0.000  0.000 -0.025 -0.025 -0.050 -0.075 -0.075 -0.050 -0.025  0.075  0.050 -0.025 -0.075  0.025 -0.075 -0.075  0.025  0.000  0.025  0.050  0.075  0.000 -0.050 -0.050 -0.075 -0.075  0.050  0.000 -0.075 -0.050 -0.025 -0.025  0.050  0.000  0.000  0.000 -0.075 -0.075 -0.075 -0.025 -0.050  0.000 -0.050 -0.050  0.075 -0.050 -0.025 -0.050  0.000 -0.075 -0.050 -0.075 -0.025 -0.025  0.000  0.000 -0.050  0.000  0.000  0.075 -0.050  0.000  0.075  0.000  0.025  0.000  0.050 -0.025 -0.025 -0.025 -0.050  0.174 -0.075  0.149  0.100 -0.025 -0.075 -0.050 -0.025  0.000  0.000 -0.050 -0.025 -0.050 -0.050  0.050  0.000 -0.050  0.025  0.000  0.025  0.025 
 0.083  0.008 -0.067 -0.017 -0.017  0.008 -0.067 -0.017 -0.042  0.008 -0.017 -0.017 -0.042 -0.067 -0.042 -0.042 -0.017  0.058  0.008 -0.017 -0.067  0.058 -0.042 -0.042  0.033 -0.017  0.008  0.058  0.058 -0.017 -0.042 -0.042 -0.067 -0.067  0.058  0.008 -0.067 -0.042 -0.017  0.008  0.033  0.008 -0.017  0.008 -0.067 -0.067 -0.067  0.008 -0.042 -0.017 -0.017 -0.067  0.033 -0.042 -0.017 -0.042  0.008 -0.067 -0.042 -0.067 -0.017 -0.042  0.008  0.033 -0.042  0.008  0.008  0.058 -0.042  0.033  0.058 -0.017  0.033  0.008  0.058  0.008 -0.067  0.008 -0.017  0.108 -0.067  0.058  0.083 -0.017 -0.042 -0.042 -0.042  0.008  0.008 -0.042 -0.042 -0.042 -0.042  0.083 -0.042 -0.042  0.033 -0.017  0.033  0.008 
 0.064  0.014 -0.061 -0.036 -0.011  0.014 -0.061 -0.011 -0.061 -0.011 -0.011 -0.011 -0.036 -0.061 -0.036 -0.036 -0.011  0.039  0.014 -0.011 -0.061  0.064 -0.036 -0.036  0.039 -0.011  0.014  0.064  0.064 -0.036 -0.036 -0.036 -0.061 -0.061  0.014  0.014 -0.061 -0.036 -0.011  0.014 -0.011  0.014 -0.011  0.014 -0.061 -0.061 -0.061 -0.011 -0.036 -0.036 -0.011 -0.061  0.014 -0.036 -0.011 -0.036 -0.036 -0.061 -0.036 -0.061 -0.011 -0.036  0.014  0.039 -0.036 -0.011  0.014  0.039 -0.036  0.039  0.064 -0.011  0.039 -0.011  0.064  0.014 -0.061  0.014 -0.011  0.114 -0.061  0.064  0.064 -0.011 -0.036 -0.036 -0.036  0.014  0.014 -0.036 -0.036 -0.061 -0.036  0.064 -0.036 -0.036  0.014 -0.011  0.039 -0.011 
 0.071  0.021 -0.054 -0.029 -0.004  0.021 -0.054 -0.004 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.029 -0.004  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.004 -0.004  0.071  0.071 -0.029 -0.029 -0.029 -0.054 -0.054 -0.004  0.021 -0.054 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.054 -0.054 -0.054 -0.029 -0.029 -0.029 -0.004 -0.054  0.021 -0.054 -0.004 -0.029 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.029 -0.004  0.021  0.046 -0.029  0.046  0.046 -0.004  0.021 -0.004  0.021 -0.004 -0.054 -0.004 -0.004  0.071 -0.054  0.071  0.046 -0.029 -0.029 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.029  0.071 -0.029 -0.029 -0.029 -0.004  0.046 -0.029 
 0.073  0.023 -0.052 -0.027 -0.027  0.023 -0.052 -0.002 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.027 -0.027  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.027 -0.027 -0.052 -0.052 -0.002  0.023 -0.027 -0.027 -0.002  0.023 -0.002  0.023 -0.027  0.023 -0.052 -0.027 -0.052 -0.027 -0.027 -0.027 -0.002 -0.052  0.023 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.023  0.048 -0.027 -0.002  0.023  0.023 -0.027  0.048  0.048 -0.002  0.023 -0.002  0.023 -0.002 -0.052 -0.002 -0.027  0.048 -0.052  0.073 -0.002 -0.027 -0.002 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.052 -0.027  0.073 -0.027 -0.027 -0.027 -0.002  0.048 -0.027 
 0.073  0.048 -0.052 -0.027 -0.027  0.023 -0.052  0.023 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.023 -0.002  0.023 -0.027  0.023 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.023 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.023  0.048 -0.027 -0.002  0.023  0.023 -0.002  0.023  0.048 -0.002  0.023 -0.002  0.023 -0.002 -0.052 -0.002 -0.027  0.048 -0.052  0.048 -0.002 -0.027  0.023 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.052 -0.027  0.073 -0.027 -0.027 -0.027 -0.002  0.048 -0.027 
 0.071  0.046 -0.053 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028  0.021  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.003 -0.003  0.021  0.021 -0.003  0.021  0.046  0.021  0.021 -0.003  0.021  0.021 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.028  0.021 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.003  0.071 -0.028 -0.028 -0.028 -0.003  0.046 -0.028 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029  0.020  0.020 -0.004  0.020 -0.029  0.020 -0.054 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.004 -0.004  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.004  0.020  0.020 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.004  0.070 -0.029 -0.004 -0.029 -0.004  0.045 -0.029 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.055 -0.030 -0.030 -0.030 -0.030 -0.030 -0.005 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.120  0.045 -0.055 -0.055 -0.055 -0.005 -0.030  0.020 -0.080 -0.030 -0.005  0.045 -0.030 -0.055 -0.055 -0.080 -0.055  0.045  0.020 -0.030 -0.080  0.020 -0.030 -0.030  0.020 -0.030  0.020  0.070  0.095 -0.030 -0.080 -0.005 -0.080 -0.080 -0.005  0.045 -0.055 -0.055 -0.005  0.020 -0.030  0.070 -0.055  0.045 -0.030 -0.055 -0.030 -0.030 -0.030 -0.030 -0.005 -0.030  0.020 -0.055 -0.030 -0.080 -0.055 -0.080 -0.080 -0.080 -0.055 -0.055  0.020  0.020 -0.030 -0.005  0.070  0.020 -0.005 -0.005  0.120 -0.005 -0.005 -0.005 -0.005 -0.005 -0.080 -0.005  0.020  0.144 -0.080  0.120  0.070 -0.055 -0.005 -0.030 -0.030  0.020 -0.030 -0.055 -0.030 -0.080 -0.005  0.070 -0.055 -0.005 -0.030 -0.005  0.045 -0.055 
 0.163  0.014 -0.111 -0.061 -0.086 -0.061 -0.061 -0.011 -0.136 -0.061  0.014 -0.011 -0.061 -0.061 -0.061 -0.086 -0.061  0.089  0.064 -0.086 -0.136  0.064 -0.086 -0.086  0.039 -0.061 -0.036  0.039  0.139 -0.036 -0.111 -0.036 -0.136 -0.136 -0.011  0.039 -0.086 -0.086 -0.036 -0.036  0.039  0.039 -0.061  0.039 -0.086 -0.036 -0.086 -0.011 -0.086 -0.036 -0.036 -0.061  0.089 -0.111 -0.036 -0.111 -0.111 -0.111 -0.111 -0.111 -0.036 -0.036  0.014 -0.036 -0.036 -0.036  0.064 -0.011 -0.061 -0.011  0.213  0.039 -0.011  0.014  0.039  0.039 -0.111 -0.036  0.014  0.338 -0.136  0.238  0.188 -0.086 -0.011 -0.036 -0.061 -0.036 -0.036 -0.086 -0.011 -0.111 -0.061  0.064 -0.036 -0.036  0.014  0.014  0.089 -0.086 
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 0.228  0.004 -0.170 -0.121  0.004 -0.071 -0.145 -0.121 -0.046 -0.046  0.004 -0.021 -0.145  0.054  0.153 -0.021  0.004 -0.121  0.079 -0.170 -0.195  0.153 -0.195 -0.170  0.079 -0.071 -0.046 -0.096  0.129 -0.046  0.054 -0.195 -0.245 -0.145  0.054 -0.021 -0.121 -0.096 -0.071 -0.170 -0.046 -0.121 -0.121  0.054 -0.071 -0.071 -0.195 -0.021 -0.145 -0.071 -0.096 -0.021  0.129 -0.046 -0.096 -0.121 -0.021 -0.145 -0.170 -0.170 -0.145 -0.046 -0.145 -0.121 -0.121  0.004  0.104  0.029 -0.071  0.004  0.054 -0.121 -0.046  0.054  0.029 -0.096 -0.170  0.004  0.129  0.303 -0.220  0.353  0.203  0.004 -0.170 -0.096 -0.071 -0.046  0.004 -0.145 -0.046 -0.121 -0.096 -0.021 -0.121 -0.170  0.104 -0.121  0.029  0.029 
 0.193 -0.031 -0.106 -0.081 -0.006 -0.081 -0.131 -0.081 -0.006 -0.106 -0.056  0.019 -0.131  0.044  0.119  0.019 -0.006 -0.031  0.094 -0.106 -0.106  0.069 -0.131 -0.081  0.094 -0.056 -0.006 -0.031  0.069 -0.031  0.044 -0.131 -0.155 -0.131  0.019  0.044 -0.081 -0.081 -0.131 -0.131  0.019 -0.031 -0.056  0.044 -0.081 -0.056 -0.131 -0.031 -0.131 -0.006 -0.131 -0.031  0.143 -0.006 -0.056 -0.056 -0.006 -0.081 -0.106 -0.081 -0.106 -0.031 -0.081 -0.056 -0.081 -0.031  0.044  0.044 -0.081 -0.006 -0.031 -0.056 -0.006  0.019  0.019 -0.031 -0.106 -0.006  0.044  0.293 -0.155  0.318  0.119 -0.006 -0.131 -0.106 -0.056  0.019  0.019 -0.106 -0.031 -0.106 -0.081  0.019 -0.056 -0.106  0.094 -0.106 -0.031  0.019 
 0.165 -0.009 -0.084 -0.084 -0.034 -0.059 -0.109 -0.084 -0.084 -0.084 -0.034  0.015 -0.109  0.015  0.065 -0.034 -0.009  0.040  0.115 -0.109 -0.109 -0.009 -0.134 -0.059  0.090 -0.034  0.015 -0.009  0.065 -0.009  0.040 -0.109 -0.134 -0.109  0.015  0.015 -0.059 -0.084 -0.084 -0.134  0.065 -0.009 -0.059  0.065 -0.059 -0.059 -0.109 -0.034 -0.109 -0.009 -0.109 -0.034  0.115  0.015 -0.034 -0.059 -0.059 -0.059 -0.084 -0.109 -0.084 -0.034 -0.059 -0.034 -0.084 -0.034 -0.034  0.040 -0.109  0.015 -0.034 -0.034 -0.009  0.015  0.040 -0.059 -0.084 -0.009  0.015  0.265 -0.134  0.314  0.090 -0.034 -0.109 -0.109 -0.034  0.015 -0.009 -0.084 -0.034 -0.059 -0.059  0.040 -0.059 -0.084  0.090 -0.134 -0.034 -0.034 
 0.138  0.013 -0.087 -0.062 -0.012 -0.037 -0.087 -0.062 -0.062 -0.062 -0.037 -0.037 -0.087 -0.012 -0.012 -0.037 -0.037  0.063  0.113 -0.087 -0.112 -0.012 -0.112 -0.087  0.063 -0.012  0.038  0.013  0.088  0.013  0.038 -0.087 -0.112 -0.112  0.038  0.013 -0.037 -0.062 -0.062 -0.112  0.038  0.013 -0.037  0.063 -0.062 -0.037 -0.087 -0.037 -0.087  0.013 -0.112 -0.012  0.113  0.013 -0.012 -0.062 -0.087 -0.062 -0.062 -0.087 -0.062  0.013 -0.037  0.013 -0.062 -0.062  0.013  0.038 -0.112  0.038 -0.037 -0.012  0.038 -0.012  0.038 -0.037 -0.062 -0.062 -0.062  0.187 -0.112  0.312  0.038 -0.062 -0.087 -0.087 -0.012  0.013  0.013 -0.062 -0.012 -0.062 -0.062  0.038 -0.037 -0.062  0.013 -0.112 -0.012 -0.037 
 0.144  0.020 -0.080 -0.055 -0.005 -0.030 -0.080 -0.055 -0.055 -0.030 -0.030 -0.030 -0.080 -0.005 -0.030 -0.030 -0.030  0.070  0.120 -0.080 -0.105 -0.005 -0.105 -0.080  0.070 -0.005  0.020  0.020  0.070  0.020  0.020 -0.080 -0.105 -0.105  0.045  0.020 -0.030 -0.055 -0.055 -0.080  0.045 -0.005 -0.030  0.045 -0.080 -0.055 -0.080 -0.030 -0.080  0.020 -0.105 -0.030  0.095 -0.030 -0.005 -0.055 -0.080 -0.055 -0.055 -0.105 -0.055  0.020 -0.030  0.020 -0.055 -0.030  0.020  0.070 -0.080  0.045  0.020 -0.005  0.020 -0.005  0.045 -0.055 -0.055 -0.055 -0.055  0.169 -0.105  0.319  0.020 -0.055 -0.080 -0.080 -0.005  0.020 -0.005 -0.055 -0.005 -0.080 -0.080  0.045 -0.030 -0.055  0.020 -0.080 -0.005 -0.030 
 0.109  0.034 -0.065 -0.065  0.009 -0.015 -0.090 -0.040 -0.065 -0.015 -0.015 -0.040 -0.090 -0.015 -0.065 -0.040 -0.040  0.059  0.109 -0.065 -0.090  0.034 -0.090 -0.065  0.059  0.009  0.009  0.034  0.059  0.034 -0.040 -0.065 -0.090 -0.090  0.034  0.009 -0.065 -0.065 -0.040 -0.065  0.034 -0.015 -0.015  0.034 -0.065 -0.065 -0.090 -0.040 -0.065  0.009 -0.090 -0.065  0.084 -0.040 -0.015 -0.065 -0.065 -0.065 -0.040 -0.090 -0.040 -0.015 -0.015  0.009 -0.065 -0.015  0.034  0.084 -0.065  0.009  0.034  0.009  0.034 -0.015  0.034 -0.040 -0.040 -0.040 -0.065  0.159 -0.090  0.259  0.009 -0.040 -0.090 -0.065  0.009  0.034  0.009 -0.040 -0.015 -0.065 -0.065  0.059 -0.040 -0.040  0.034 -0.040  0.009 -0.015 
 0.092  0.042 -0.058 -0.058 -0.008 -0.008 -0.083 -0.058 -0.058 -0.008 -0.008 -0.033 -0.083 -0.083 -0.083 -0.033 -0.033  0.042  0.117 -0.058 -0.083  0.017 -0.083 -0.058  0.067  0.017  0.017  0.042  0.067 -0.008 -0.058 -0.058 -0.083 -0.083  0.042  0.017 -0.058 -0.058 -0.033 -0.058  0.017 -0.008  0.017  0.042 -0.083 -0.058 -0.083 -0.058 -0.058 -0.008 -0.083 -0.083  0.067 -0.058 -0.033 -0.058 -0.058 -0.058 -0.033 -0.083 -0.033 -0.033 -0.008  0.017 -0.058 -0.008  0.042  0.067 -0.058 -0.008  0.067  0.017  0.042 -0.033  0.042 -0.033 -0.033 -0.033 -0.058  0.142 -0.083  0.266  0.042 -0.033 -0.083 -0.058  0.017  0.017  0.017 -0.033 -0.008 -0.083 -0.058  0.067 -0.033 -0.058  0.017 -0.058  0.017 -0.008 
 0.103  0.053 -0.071 -0.046 -0.021  0.003 -0.071 -0.046 -0.071  0.003 -0.021 -0.021 -0.071 -0.071 -0.071 -0.046 -0.021  0.053  0.078 -0.046 -0.071  0.028 -0.071 -0.071  0.078  0.003  0.003  0.053  0.078 -0.021 -0.046 -0.046 -0.071 -0.071  0.028  0.028 -0.046 -0.046 -0.021 -0.046  0.028  0.003  0.028  0.028 -0.071 -0.046 -0.071 -0.046 -0.046  0.003 -0.071 -0.071  0.078 -0.046 -0.021 -0.046 -0.046 -0.071 -0.021 -0.071 -0.021 -0.021  0.003  0.003 -0.046 -0.021  0.053  0.053 -0.046  0.003  0.078  0.003  0.028 -0.021  0.053 -0.021 -0.046 -0.021 -0.046  0.103 -0.071  0.228  0.053 -0.021 -0.071 -0.046  0.003  0.028  0.028 -0.021 -0.021 -0.071 -0.071  0.078 -0.021 -0.046  0.028 -0.046  0.028 -0.021 
 0.107  0.057 -0.068 -0.043 -0.018  0.007 -0.068 -0.043 -0.068  0.007  0.007 -0.018 -0.068 -0.068 -0.043 -0.043 -0.018  0.057  0.057 -0.018 -0.068  0.032 -0.043 -0.043  0.032  0.007  0.007  0.057  0.082 -0.018 -0.043 -0.043 -0.068 -0.068  0.007  0.032 -0.068 -0.043 -0.018 -0.043  0.007  0.007  0.007  0.007 -0.068 -0.068 -0.068 -0.018 -0.043  0.007 -0.018 -0.068  0.082 -0.043 -0.018 -0.043 -0.043 -0.068 -0.043 -0.068  0.007 -0.043  0.032  0.032 -0.043 -0.018  0.057  0.057 -0.043  0.007  0.082  0.007  0.032  0.007  0.057  0.007 -0.043 -0.018 -0.043  0.132 -0.068  0.181  0.032 -0.018 -0.043 -0.043 -0.018  0.032  0.007 -0.018 -0.018 -0.068 -0.068  0.057 -0.018 -0.043  0.007 -0.043  0.032 -0.018 
 0.090  0.065 -0.060 -0.035 -0.010  0.015 -0.060 -0.010 -0.060 -0.010  0.015 -0.010 -0.035 -0.060 -0.035 -0.035 -0.035  0.040  0.040 -0.010 -0.060  0.065 -0.035 -0.035  0.040  0.015  0.015  0.090  0.090 -0.010 -0.060 -0.035 -0.060 -0.060  0.015  0.015 -0.035 -0.035 -0.010  0.015 -0.010  0.015 -0.010  0.015 -0.060 -0.035 -0.060 -0.010 -0.035 -0.035 -0.010 -0.060  0.015 -0.060 -0.010 -0.035 -0.035 -0.060 -0.035 -0.060  0.015 -0.035  0.040  0.040 -0.035 -0.010  0.040  0.015 -0.035  0.040  0.065  0.015  0.040 -0.010  0.065  0.015 -0.060  0.015 -0.035  0.115 -0.060  0.115  0.015 -0.010 -0.010 -0.035 -0.010  0.015  0.015 -0.035 -0.010 -0.060 -0.035  0.065 -0.010 -0.035 -0.010 -0.010  0.040 -0.010 
 0.092  0.067 -0.057 -0.032 -0.007  0.017 -0.057  0.017 -0.057 -0.007 -0.007 -0.007 -0.032 -0.057 -0.032 -0.057 -0.032  0.042  0.042 -0.007 -0.057  0.067 -0.032 -0.032  0.042 -0.032  0.017  0.092  0.092 -0.007 -0.057 -0.032 -0.057 -0.057 -0.007 -0.007 -0.032 -0.032 -0.007  0.017 -0.007  0.017 -0.007  0.017 -0.057 -0.032 -0.032 -0.007 -0.032 -0.032 -0.007 -0.057  0.017 -0.057 -0.007 -0.057 -0.032 -0.057 -0.057 -0.057  0.017 -0.032  0.042  0.042 -0.032 -0.007  0.017  0.017 -0.032  0.017  0.067  0.017  0.017 -0.007  0.042 -0.007 -0.057  0.017 -0.032  0.092 -0.057  0.067  0.017 -0.007 -0.007 -0.032 -0.032  0.017  0.017 -0.032 -0.007 -0.057 -0.032  0.067 -0.032 -0.032 -0.007 -0.007  0.042 -0.032 
 0.073  0.048 -0.052 -0.027 -0.027  0.023 -0.052  0.023 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.023 -0.002  0.023 -0.027  0.023 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.023 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.023  0.048 -0.027 -0.002  0.023  0.023 -0.027  0.023  0.048 -0.002  0.023 -0.002  0.023 -0.002 -0.052 -0.002 -0.027  0.073 -0.052  0.048  0.023 -0.027 -0.002 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.052 -0.027  0.073 -0.027 -0.027 -0.027 -0.002  0.048 -0.027 
 0.071  0.046 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.029 -0.004  0.021  0.021  0.021  0.021  0.046 -0.004  0.021 -0.004  0.021 -0.004 -0.054 -0.004 -0.029  0.071 -0.054  0.046  0.021 -0.029  0.021 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.029  0.071 -0.029 -0.004 -0.029 -0.004  0.046 -0.029 
 0.071  0.046 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.054 -0.029  0.046 -0.004 -0.004 -0.054  0.046 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.054 -0.029 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.021 -0.004  0.021 -0.029  0.021 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.021 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.021  0.046 -0.029 -0.004  0.021  0.021  0.021  0.021  0.046 -0.004  0.021 -0.004  0.021 -0.004 -0.054 -0.004 -0.029  0.071 -0.054  0.046  0.021 -0.029  0.021 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.029  0.071 -0.029 -0.004 -0.029 -0.004  0.046 -0.029 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030 -0.005  0.020 -0.005  0.020 -0.030  0.020 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.005 -0.005  0.020  0.020  0.020  0.020  0.045  0.020  0.020 -0.005  0.020  0.020 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.005  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.091  0.016 -0.033 -0.058 -0.008  0.016 -0.033 -0.008 -0.083 -0.008 -0.008 -0.033 -0.058 -0.058 -0.058 -0.083 -0.033  0.041  0.016 -0.033 -0.083  0.116 -0.058 -0.033  0.041 -0.033 -0.033  0.091  0.091 -0.008 -0.058 -0.008 -0.083 -0.083 -0.033 -0.008 -0.058 -0.058 -0.008 -0.008 -0.033 -0.008 -0.033  0.016 -0.033 -0.033 -0.058 -0.033 -0.033 -0.008 -0.008 -0.083  0.091 -0.083 -0.033 -0.058 -0.058 -0.058 -0.083 -0.083 -0.008 -0.008 -0.008  0.041 -0.008 -0.008  0.016  0.041  0.041 -0.008  0.091  0.066 -0.008  0.016  0.016 -0.008 -0.083 -0.033 -0.008  0.116 -0.083  0.166  0.016 -0.058  0.016 -0.008 -0.033  0.041 -0.033 -0.058 -0.008 -0.083 -0.033  0.091 -0.033 -0.033 -0.058  0.016  0.041 -0.058 
 0.101  0.051 -0.073 -0.073  0.026 -0.048 -0.073 -0.023 -0.123 -0.073  0.001 -0.023 -0.073 -0.023 -0.098 -0.148 -0.023  0.026  0.101 -0.073 -0.123  0.126 -0.098 -0.098  0.051 -0.048  0.001  0.051  0.126  0.001 -0.048 -0.048 -0.123 -0.148  0.026 -0.023 -0.123 -0.098 -0.073 -0.048  0.026 -0.023 -0.073  0.001 -0.098 -0.023 -0.098 -0.048 -0.098 -0.048 -0.073 -0.048  0.101 -0.048 -0.023 -0.073 -0.023 -0.098 -0.123 -0.123 -0.048  0.076 -0.023 -0.023 -0.073  0.001  0.051  0.001 -0.023 -0.073  0.176  0.026 -0.023  0.001  0.001  0.026 -0.098 -0.048  0.001  0.325 -0.148  0.300  0.051 -0.123 -0.023 -0.048  0.001  0.026 -0.048 -0.098  0.001 -0.098 -0.023  0.126 -0.023 -0.023  0.026  0.001  0.051 -0.073 
 0.132  0.082 -0.093 -0.093 -0.018 -0.068 -0.043 -0.043 -0.142 -0.118  0.007 -0.068 -0.093 -0.068 -0.043 -0.118 -0.068 -0.018  0.107 -0.118 -0.142  0.132 -0.118 -0.118  0.082 -0.093  0.032  0.007  0.107 -0.043 -0.018 -0.093 -0.167 -0.192 -0.018  0.032 -0.118 -0.142 -0.093 -0.018 -0.018 -0.068 -0.093  0.032 -0.142 -0.043 -0.093 -0.068 -0.142  0.007 -0.118 -0.093  0.082  0.007 -0.068 -0.018  0.057 -0.068 -0.142 -0.167 -0.043  0.057 -0.043 -0.068 -0.093  0.007  0.057  0.082 -0.043  0.007  0.231 -0.018 -0.043  0.007 -0.018  0.007 -0.093  0.032  0.007  0.356 -0.192  0.331  0.032 -0.093 -0.043  0.032 -0.018 -0.043 -0.068 -0.118 -0.043 -0.118 -0.043  0.132  0.007 -0.068  0.007 -0.018  0.007 -0.018 
 0.169  0.045 -0.130 -0.080 -0.080 -0.105 -0.130 -0.055 -0.130 -0.179  0.045 -0.080 -0.130 -0.080 -0.005 -0.154 -0.055 -0.055  0.045 -0.179 -0.204  0.095 -0.179 -0.130  0.070 -0.030 -0.030 -0.055  0.095 -0.105  0.020 -0.130 -0.229 -0.254 -0.055  0.020 -0.179 -0.130 -0.154 -0.080 -0.005 -0.130 -0.105  0.070 -0.179 -0.080 -0.154 -0.030 -0.130 -0.055 -0.179 -0.105  0.070 -0.005 -0.105 -0.030  0.045 -0.055 -0.179 -0.179 -0.080  0.070 -0.105 -0.130 -0.080 -0.005  0.095  0.070 -0.005 -0.005  0.244 -0.055 -0.055  0.095 -0.030  0.045 -0.130  0.045  0.095  0.394 -0.229  0.394  0.120 -0.105 -0.105 -0.005 -0.080 -0.080 -0.030 -0.179 -0.030 -0.154 -0.080  0.095 -0.030 -0.080 -0.030 -0.030 -0.030  0.070 
 0.231  0.006 -0.143 -0.093 -0.018 -0.118 -0.168 -0.068 -0.143 -0.168  0.056 -0.068 -0.068 -0.068  0.031 -0.118 -0.093 -0.068  0.031 -0.193 -0.193  0.056 -0.193 -0.093  0.056 -0.018 -0.068 -0.043  0.106 -0.093  0.006 -0.143 -0.243 -0.268 -0.068  0.031 -0.168 -0.143 -0.193 -0.043 -0.018 -0.118 -0.118  0.106 -0.168 -0.093 -0.168 -0.018 -0.143 -0.068 -0.193 -0.093  0.031 -0.018 -0.118 -0.043  0.031 -0.068 -0.193 -0.193 -0.093  0.081 -0.118 -0.118 -0.043 -0.018  0.081  0.031  0.006  0.106  0.256 -0.068 -0.068  0.081 -0.018  0.006 -0.143  0.056  0.131  0.405 -0.243  0.330  0.206 -0.118 -0.093  0.006 -0.068 -0.093 -0.018 -0.193 -0.018 -0.118 -0.093  0.081 -0.068 -0.093 -0.018 -0.043  0.031  0.106 
 0.239 -0.035 -0.210 -0.060 -0.010 -0.160 -0.185 -0.110 -0.110 -0.160  0.039 -0.060 -0.060 -0.085  0.114 -0.135 -0.060 -0.085  0.014 -0.185 -0.185  0.039 -0.210 -0.085  0.089 -0.035 -0.060 -0.035  0.089 -0.085  0.039 -0.160 -0.260 -0.284 -0.035  0.014 -0.110 -0.110 -0.160 -0.060 -0.035 -0.135 -0.135  0.064 -0.185 -0.085 -0.185  0.064 -0.135 -0.060 -0.160 -0.060  0.014 -0.035 -0.110 -0.035  0.039 -0.085 -0.210 -0.210 -0.110  0.064 -0.135 -0.085 -0.060 -0.010  0.064  0.014 -0.035  0.139  0.239 -0.085 -0.085  0.114  0.014  0.014 -0.160  0.014  0.164  0.388 -0.235  0.338  0.239 -0.135 -0.110  0.039 -0.085 -0.110 -0.035 -0.210 -0.035 -0.135 -0.110  0.039 -0.085 -0.135 -0.010 -0.060  0.039  0.089 
 0.232 -0.042 -0.216 -0.042  0.033 -0.166 -0.191 -0.117 -0.092 -0.166  0.083 -0.042 -0.067 -0.092  0.108 -0.142 -0.067 -0.067  0.008 -0.191 -0.166  0.033 -0.191 -0.092  0.108 -0.017 -0.067 -0.042  0.058 -0.092  0.033 -0.166 -0.241 -0.266 -0.017  0.008 -0.117 -0.117 -0.117 -0.092 -0.042 -0.142 -0.142  0.058 -0.191 -0.067 -0.166  0.033 -0.142 -0.092 -0.142 -0.067  0.008 -0.042 -0.092 -0.017  0.033 -0.092 -0.216 -0.216 -0.142  0.058 -0.142 -0.067 -0.067 -0.017  0.058  0.033 -0.042  0.133  0.207 -0.092 -0.067  0.108  0.008 -0.017 -0.166  0.008  0.182  0.382 -0.241  0.332  0.257 -0.142 -0.142  0.033 -0.092 -0.142 -0.042 -0.166 -0.017 -0.142 -0.117  0.058 -0.092 -0.166  0.008 -0.042  0.033  0.083 
 0.250 -0.049 -0.223 -0.024  0.026 -0.173 -0.198 -0.099 -0.074 -0.148  0.101 -0.024 -0.074 -0.099  0.126 -0.124 -0.074 -0.074  0.001 -0.198 -0.173  0.051 -0.198 -0.124  0.126  0.001 -0.049 -0.049  0.051 -0.099  0.026 -0.173 -0.248 -0.273  0.101 -0.024 -0.099 -0.099 -0.099 -0.148 -0.049 -0.148 -0.124  0.026 -0.173 -0.074 -0.124  0.026 -0.148 -0.099 -0.099 -0.049  0.076 -0.049 -0.099  0.001  0.026 -0.099 -0.198 -0.223 -0.148  0.051 -0.124 -0.074 -0.099 -0.024  0.051  0.026 -0.074  0.126  0.200 -0.074 -0.074  0.126  0.001 -0.024 -0.173  0.026  0.200  0.350 -0.223  0.325  0.250 -0.148 -0.173  0.026 -0.099 -0.124 -0.024 -0.173 -0.024 -0.124 -0.099  0.051 -0.099 -0.173  0.026 -0.049  0.026  0.051 
 0.248 -0.051 -0.226 -0.001  0.023 -0.176 -0.201 -0.101 -0.101 -0.176  0.073 -0.001 -0.076 -0.051  0.123 -0.126 -0.076 -0.076 -0.001 -0.201 -0.151  0.048 -0.201 -0.126  0.148 -0.051 -0.051 -0.051  0.073 -0.101  0.023 -0.151 -0.251 -0.276  0.123 -0.026 -0.101 -0.126 -0.101 -0.151 -0.051 -0.151 -0.126  0.023 -0.176 -0.101 -0.126  0.023 -0.151 -0.101 -0.101 -0.026  0.073 -0.051 -0.101 -0.001  0.023 -0.101 -0.201 -0.226 -0.151  0.048 -0.126 -0.076 -0.101 -0.026  0.048  0.023 -0.076  0.123  0.198 -0.076 -0.076  0.123 -0.001 -0.026 -0.201  0.023  0.173  0.322 -0.251  0.322  0.248 -0.151 -0.176  0.023 -0.101 -0.126 -0.026 -0.176 -0.026 -0.101 -0.101  0.048 -0.101 -0.151 -0.001 -0.051  0.023  0.048 
 0.248 -0.051 -0.226 -0.026  0.023 -0.176 -0.201 -0.101 -0.101 -0.176  0.073 -0.001 -0.101 -0.051  0.123 -0.126 -0.076 -0.126 -0.001 -0.201 -0.151  0.073 -0.201 -0.126  0.148 -0.051 -0.076 -0.051  0.048 -0.101  0.023 -0.151 -0.251 -0.276  0.123 -0.026 -0.101 -0.126 -0.101 -0.151 -0.051 -0.151 -0.126  0.023 -0.176 -0.101 -0.126  0.023 -0.151 -0.101 -0.076 -0.026  0.073 -0.051 -0.101 -0.001  0.023 -0.126 -0.201 -0.226 -0.151  0.048 -0.126 -0.076 -0.126 -0.026  0.048  0.023 -0.076  0.123  0.198 -0.076 -0.076  0.148 -0.001 -0.026 -0.201  0.023  0.173  0.322 -0.251  0.322  0.248 -0.126 -0.201  0.023 -0.101 -0.101 -0.026 -0.151 -0.026 -0.101 -0.101  0.048 -0.101 -0.151 -0.001 -0.076 -0.026  0.048 
 0.246 -0.053 -0.203 -0.028  0.021 -0.178 -0.178 -0.103 -0.078 -0.153  0.121 -0.028 -0.103 -0.078  0.121 -0.103 -0.078 -0.128 -0.003 -0.203 -0.178  0.071 -0.203 -0.128  0.146 -0.028 -0.078 -0.053  0.046 -0.103  0.046 -0.178 -0.253 -0.253  0.096 -0.053 -0.103 -0.128 -0.103 -0.153 -0.053 -0.153 -0.128  0.021 -0.178 -0.078 -0.128  0.021 -0.153 -0.103 -0.103 -0.028  0.071 -0.053 -0.103 -0.003  0.046 -0.128 -0.203 -0.228 -0.153  0.046 -0.128 -0.103 -0.128 -0.028  0.046 -0.003 -0.078  0.121  0.196 -0.078 -0.078  0.171 -0.003 -0.028 -0.203  0.046  0.196  0.320 -0.228  0.320  0.246 -0.128 -0.203  0.021 -0.103 -0.103 -0.028 -0.178 -0.028 -0.103 -0.103 -0.003 -0.103 -0.153 -0.003 -0.078 -0.028  0.046 
 0.241 -0.033 -0.182 -0.033  0.017 -0.182 -0.157 -0.108 -0.083 -0.157  0.117 -0.058 -0.108 -0.083  0.117 -0.108 -0.083 -0.133 -0.008 -0.207 -0.182  0.092 -0.207 -0.133  0.142 -0.008 -0.083 -0.033  0.017 -0.083  0.042 -0.182 -0.257 -0.257  0.092 -0.058 -0.108 -0.083 -0.083 -0.157 -0.033 -0.157 -0.108  0.017 -0.182 -0.083 -0.108  0.017 -0.157 -0.108 -0.108 -0.033  0.067 -0.033 -0.108 -0.008  0.042 -0.133 -0.207 -0.232 -0.157  0.042 -0.108 -0.108 -0.133 -0.033  0.042 -0.008 -0.083  0.117  0.191 -0.083 -0.058  0.216 -0.008 -0.033 -0.207  0.067  0.191  0.316 -0.232  0.316  0.241 -0.157 -0.207  0.017 -0.108 -0.108 -0.033 -0.182 -0.058 -0.083 -0.108 -0.008 -0.108 -0.182 -0.008 -0.108 -0.008  0.042 
 0.238 -0.036 -0.186 -0.036  0.013 -0.211 -0.161 -0.111 -0.086 -0.136  0.138 -0.061 -0.111 -0.086  0.113 -0.111 -0.086 -0.136 -0.011 -0.211 -0.186  0.088 -0.211 -0.136  0.138 -0.011 -0.086 -0.036  0.013 -0.061  0.038 -0.186 -0.261 -0.261  0.088 -0.061 -0.111 -0.086 -0.061 -0.161 -0.036 -0.136 -0.111  0.013 -0.186 -0.086 -0.111  0.013 -0.186 -0.111 -0.111 -0.036  0.063 -0.036 -0.111 -0.011  0.038 -0.136 -0.211 -0.236 -0.161  0.038 -0.111 -0.111 -0.136 -0.036  0.038 -0.011 -0.086  0.113  0.188 -0.086 -0.061  0.213  0.013 -0.036 -0.211  0.063  0.213  0.337 -0.236  0.312  0.213 -0.161 -0.211  0.013 -0.111 -0.111 -0.036 -0.186 -0.061 -0.086 -0.111 -0.011 -0.111 -0.186  0.013 -0.111  0.013  0.038 
 0.233 -0.041 -0.190 -0.041  0.009 -0.190 -0.165 -0.116 -0.091 -0.141  0.134  0.009 -0.116 -0.091  0.109 -0.116 -0.091 -0.116 -0.016 -0.215 -0.190  0.084 -0.215 -0.141  0.134  0.009 -0.091 -0.041  0.009 -0.041  0.034 -0.190 -0.265 -0.265  0.084 -0.066 -0.116 -0.091 -0.066 -0.165 -0.066 -0.141 -0.116  0.009 -0.190 -0.091 -0.116  0.009 -0.190 -0.116 -0.091 -0.041  0.059 -0.041 -0.116 -0.041  0.059 -0.165 -0.215 -0.240 -0.190  0.034 -0.116 -0.116 -0.141 -0.041  0.034 -0.041 -0.091  0.109  0.183 -0.091 -0.066  0.208  0.009 -0.066 -0.215  0.059  0.208  0.333 -0.215  0.308  0.208 -0.165 -0.215  0.009 -0.116 -0.116 -0.041 -0.190 -0.066 -0.091 -0.091 -0.016 -0.091 -0.165  0.034 -0.116  0.009  0.009 
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 0.280 -0.044 -0.194 -0.044 -0.069 -0.169 -0.169 -0.119 -0.094 -0.144  0.130  0.030 -0.144 -0.094  0.105 -0.119 -0.069 -0.119 -0.019 -0.219 -0.244  0.080 -0.219 -0.144  0.130  0.005 -0.094 -0.044  0.030 -0.019  0.030 -0.219 -0.269 -0.269  0.080 -0.069 -0.119 -0.094 -0.094 -0.194 -0.044 -0.144 -0.119  0.005 -0.219 -0.094 -0.119  0.005 -0.169 -0.119 -0.094 -0.044  0.055 -0.044 -0.119 -0.044  0.055 -0.169 -0.219 -0.244 -0.194  0.055 -0.119 -0.144 -0.144 -0.044  0.055 -0.044 -0.094  0.105  0.130 -0.119 -0.069  0.230  0.005 -0.019 -0.219  0.055  0.205  0.329 -0.219  0.304  0.230 -0.144 -0.219 -0.019 -0.144 -0.119 -0.019 -0.194 -0.044 -0.119 -0.094 -0.019 -0.119 -0.144  0.030 -0.119 -0.019  0.005 
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 0.303 -0.046 -0.195 -0.046 -0.096 -0.170 -0.195 -0.145 -0.096 -0.145  0.079  0.079 -0.170 -0.096  0.104 -0.121 -0.046 -0.096  0.004 -0.220 -0.195  0.079 -0.220 -0.145  0.129  0.004 -0.096 -0.071  0.029 -0.046  0.029 -0.195 -0.295 -0.270  0.079 -0.121 -0.121 -0.096 -0.096 -0.170 -0.021 -0.170 -0.096  0.029 -0.220 -0.121 -0.220  0.004 -0.170 -0.121 -0.071 -0.046  0.054 -0.071 -0.121 -0.046  0.029 -0.170 -0.220 -0.245 -0.195  0.054 -0.121 -0.145 -0.145 -0.046  0.029 -0.046 -0.096  0.104  0.054 -0.145 -0.021  0.203  0.029 -0.021 -0.220  0.054  0.253  0.353 -0.220  0.303  0.228 -0.170 -0.220  0.004 -0.145 -0.121 -0.046 -0.195 -0.071 -0.096 -0.096  0.004 -0.121 -0.121  0.029 -0.096 -0.046  0.004 
 0.303 -0.045 -0.195 -0.045 -0.095 -0.170 -0.195 -0.145 -0.095 -0.145  0.104  0.079 -0.195 -0.070  0.104 -0.120 -0.045 -0.095  0.004 -0.220 -0.195  0.079 -0.245 -0.170  0.129  0.004 -0.095 -0.070  0.029 -0.045  0.029 -0.195 -0.294 -0.270  0.079 -0.095 -0.145 -0.095 -0.095 -0.170 -0.020 -0.170 -0.095  0.029 -0.220 -0.120 -0.220  0.004 -0.170 -0.120 -0.120 -0.045  0.054 -0.070 -0.120 -0.045  0.029 -0.170 -0.220 -0.245 -0.195  0.054 -0.120 -0.145 -0.145 -0.020  0.029 -0.045 -0.095  0.104  0.054 -0.170 -0.020  0.204  0.029 -0.020 -0.220  0.054  0.254  0.353 -0.220  0.303  0.229 -0.145 -0.220  0.004 -0.145 -0.120 -0.045 -0.195 -0.070 -0.120 -0.095  0.004 -0.120 -0.120  0.029 -0.095 -0.045  0.004 
 0.301 -0.048 -0.197 -0.048 -0.098 -0.123 -0.197 -0.147 -0.098 -0.147  0.102  0.102 -0.222 -0.073  0.102 -0.123 -0.023 -0.098  0.002 -0.222 -0.197  0.077 -0.247 -0.172  0.127  0.002 -0.098 -0.073  0.002 -0.048  0.027 -0.197 -0.297 -0.247  0.077 -0.098 -0.147 -0.098 -0.098 -0.172 -0.023 -0.172 -0.073  0.027 -0.222 -0.123 -0.222  0.002 -0.172 -0.123 -0.123 -0.023  0.052 -0.073 -0.123 -0.048  0.027 -0.172 -0.222 -0.247 -0.197  0.052 -0.123 -0.147 -0.147  0.027  0.027 -0.048 -0.073  0.102  0.052 -0.172  0.002  0.201  0.027 -0.023 -0.222  0.027  0.226  0.326 -0.222  0.326  0.226 -0.123 -0.222  0.027 -0.147 -0.123 -0.048 -0.197 -0.073 -0.123 -0.098 -0.023 -0.123 -0.123  0.052 -0.098 -0.048  0.002 
 0.328 -0.046 -0.121 -0.046 -0.121 -0.096 -0.121 -0.121 -0.096 -0.121  0.004  0.079 -0.220 -0.121  0.129 -0.071  0.004 -0.021  0.029 -0.170 -0.170  0.029 -0.195 -0.121  0.153  0.004 -0.046 -0.046  0.054  0.004  0.054 -0.170 -0.220 -0.170  0.054 -0.071 -0.145 -0.071 -0.021 -0.170  0.004 -0.096 -0.046  0.104 -0.170 -0.145 -0.195 -0.096 -0.170 -0.071 -0.145  0.054  0.079  0.004 -0.071 -0.046  0.029 -0.096 -0.145 -0.170 -0.195 -0.071 -0.046 -0.096 -0.096  0.029  0.004 -0.021 -0.021  0.129  0.079 -0.145  0.004  0.129  0.029 -0.071 -0.195  0.029  0.178  0.278 -0.195  0.328  0.203 -0.096 -0.195 -0.121 -0.096 -0.071 -0.046 -0.170 -0.071 -0.121 -0.121  0.004 -0.096 -0.046 -0.046 -0.096 -0.046  0.029 
 0.216 -0.033 -0.108 -0.058 -0.058 -0.058 -0.157 -0.108 -0.008 -0.108 -0.058 -0.008 -0.157 -0.033  0.042  0.017 -0.033 -0.008  0.092 -0.108 -0.133  0.067 -0.133 -0.083  0.117 -0.058  0.017 -0.033  0.092 -0.033  0.067 -0.108 -0.157 -0.133  0.017 -0.008 -0.083 -0.108 -0.058 -0.133 -0.008 -0.033 -0.058  0.042 -0.108 -0.108 -0.157 -0.033 -0.108 -0.033 -0.133 -0.008  0.117 -0.033 -0.058 -0.058  0.042 -0.083 -0.083 -0.083 -0.108 -0.033 -0.058 -0.058 -0.058 -0.033  0.017  0.017 -0.083  0.067 -0.008 -0.058 -0.008  0.042 -0.033  0.017 -0.108  0.017  0.092  0.266 -0.133  0.291  0.142 -0.058 -0.133 -0.108 -0.033  0.017 -0.008 -0.108 -0.008 -0.108 -0.108  0.042 -0.033 -0.108 -0.008 -0.083  0.017  0.042 
 0.210 -0.014 -0.089 -0.039 -0.039 -0.039 -0.139 -0.089  0.010 -0.089 -0.064  0.010 -0.139 -0.014  0.035  0.035 -0.014  0.010  0.110 -0.089 -0.114  0.010 -0.114 -0.064  0.135 -0.039  0.010 -0.014  0.110 -0.014  0.085 -0.089 -0.139 -0.114  0.010  0.010 -0.064 -0.089 -0.064 -0.114  0.010 -0.014 -0.064  0.060 -0.089 -0.089 -0.139 -0.039 -0.114 -0.039 -0.114 -0.039  0.135 -0.014 -0.039 -0.064  0.035 -0.089 -0.064 -0.064 -0.089 -0.014 -0.064 -0.039 -0.039 -0.039 -0.014  0.035 -0.089  0.010  0.010 -0.039 -0.014  0.035 -0.039 -0.014 -0.089  0.035  0.085  0.235 -0.114  0.309  0.060 -0.064 -0.139 -0.114 -0.014 -0.014  0.010 -0.114  0.010 -0.089 -0.089  0.085 -0.014 -0.089  0.010 -0.089 -0.014  0.035 
 0.136  0.011 -0.089 -0.064 -0.014 -0.039 -0.114 -0.089  0.011 -0.064 -0.039 -0.014 -0.114 -0.014 -0.064 -0.039 -0.014  0.061  0.136 -0.089 -0.114 -0.014 -0.114 -0.089  0.086 -0.014  0.011  0.011  0.111  0.011  0.061 -0.089 -0.114 -0.114  0.036  0.036 -0.089 -0.064 -0.064 -0.089  0.036 -0.014 -0.039  0.036 -0.064 -0.064 -0.114 -0.039 -0.089 -0.014 -0.114 -0.039  0.136 -0.039 -0.014 -0.039  0.036 -0.089 -0.039 -0.064 -0.064 -0.014 -0.039 -0.014 -0.039 -0.064  0.011  0.086 -0.114  0.011 -0.039 -0.014  0.011  0.011 -0.014 -0.014 -0.064 -0.014 -0.039  0.185 -0.114  0.260  0.036 -0.064 -0.114 -0.089 -0.014  0.011  0.011 -0.089  0.036 -0.064 -0.089  0.111  0.011 -0.064  0.036 -0.039 -0.014 -0.014 
 0.121  0.021 -0.078 -0.028 -0.003 -0.028 -0.103 -0.078 -0.003 -0.053 -0.028 -0.003 -0.103 -0.003 -0.103 -0.028 -0.028  0.046  0.096 -0.078 -0.103 -0.003 -0.103 -0.078  0.071 -0.003 -0.003  0.021  0.096 -0.003  0.021 -0.078 -0.103 -0.103  0.046  0.021 -0.078 -0.078 -0.053 -0.078  0.046 -0.028 -0.028  0.021 -0.053 -0.078 -0.103 -0.053 -0.078 -0.003 -0.103 -0.028  0.146 -0.053 -0.003 -0.028  0.046 -0.078 -0.028 -0.053 -0.053 -0.003 -0.028 -0.028 -0.028 -0.053  0.021  0.096 -0.103 -0.003 -0.028 -0.003  0.046 -0.003 -0.003 -0.028 -0.053 -0.028 -0.053  0.171 -0.103  0.271  0.071 -0.053 -0.103 -0.078 -0.003  0.021  0.021 -0.078  0.046 -0.053 -0.078  0.096  0.021 -0.053  0.021 -0.028 -0.003 -0.003 
 0.107  0.032 -0.092 -0.017 -0.017 -0.017 -0.092 -0.067  0.007 -0.042 -0.042 -0.017 -0.092 -0.017 -0.092 -0.042 -0.042  0.057  0.107 -0.067 -0.092  0.007 -0.092 -0.067  0.032  0.007  0.007  0.032  0.107  0.007  0.007 -0.067 -0.092 -0.092  0.032  0.032 -0.067 -0.067 -0.042 -0.042  0.032 -0.017  0.007  0.007 -0.042 -0.067 -0.092 -0.042 -0.067 -0.017 -0.092 -0.017  0.107 -0.042  0.007 -0.017  0.007 -0.067 -0.017 -0.067 -0.042  0.007 -0.017 -0.017 -0.042 -0.017  0.032  0.082 -0.067  0.007  0.032  0.007  0.057 -0.042  0.032 -0.017 -0.042 -0.017 -0.067  0.132 -0.092  0.257  0.082 -0.042 -0.092 -0.067  0.007  0.007  0.032 -0.042 -0.017 -0.067 -0.067  0.057  0.007 -0.042  0.032 -0.042  0.007  0.007 
 0.089  0.039 -0.086 -0.011 -0.011 -0.011 -0.086 -0.061  0.014 -0.036 -0.036 -0.011 -0.086 -0.036 -0.086 -0.036 -0.036  0.064  0.114 -0.061 -0.086  0.014 -0.086 -0.061  0.039  0.014  0.014  0.039  0.114  0.014 -0.036 -0.061 -0.086 -0.086  0.039  0.039 -0.061 -0.061 -0.036 -0.036  0.039 -0.011  0.014  0.014 -0.061 -0.086 -0.086 -0.036 -0.061 -0.036 -0.086 -0.011  0.114 -0.036 -0.011 -0.011  0.014 -0.086 -0.011 -0.061 -0.036 -0.036 -0.011 -0.011 -0.036 -0.011  0.039  0.089 -0.061 -0.011  0.039 -0.011  0.064 -0.036  0.039 -0.011 -0.036 -0.011 -0.061  0.139 -0.086  0.263  0.089 -0.036 -0.086 -0.061  0.014  0.014  0.014 -0.036 -0.011 -0.061 -0.061  0.014  0.014 -0.036  0.014 -0.036  0.014  0.014 
 0.072  0.022 -0.078 -0.003 -0.028 -0.003 -0.078 -0.053 -0.028 -0.028 -0.028 -0.003 -0.078 -0.078 -0.078 -0.028 -0.028  0.072  0.097 -0.053 -0.078 -0.003 -0.078 -0.053  0.047 -0.028  0.022  0.047  0.097 -0.003 -0.053 -0.053 -0.078 -0.078  0.047  0.022 -0.053 -0.053 -0.028 -0.028  0.047 -0.003  0.022 -0.003 -0.078 -0.078 -0.078 -0.028 -0.053 -0.028 -0.078 -0.028  0.097 -0.028 -0.028 -0.003 -0.003 -0.078 -0.003 -0.078 -0.028 -0.028 -0.003 -0.003 -0.028 -0.003  0.022  0.072 -0.053 -0.003  0.047 -0.003  0.047 -0.028  0.047 -0.003 -0.053  0.022 -0.053  0.122 -0.078  0.221  0.097 -0.028 -0.078 -0.053 -0.028 -0.003 -0.003 -0.028 -0.028 -0.053 -0.053  0.022  0.022 -0.053  0.022 -0.053  0.022  0.022 
 0.076  0.026 -0.073  0.001 -0.023  0.001 -0.073 -0.048 -0.048  0.001 -0.023  0.001 -0.073 -0.073 -0.048 -0.048 -0.023  0.051  0.076 -0.048 -0.073  0.001 -0.048 -0.048  0.051 -0.023  0.026  0.051  0.101  0.001 -0.048 -0.048 -0.073 -0.073  0.051  0.001 -0.048 -0.048 -0.023 -0.023  0.026  0.001  0.026  0.001 -0.073 -0.073 -0.073 -0.023 -0.048 -0.048 -0.048 -0.023  0.076 -0.048 -0.023  0.001  0.001 -0.073 -0.023 -0.073 -0.023 -0.023  0.001  0.026 -0.023  0.001  0.026  0.076 -0.048  0.001  0.076  0.001  0.026 -0.023  0.051  0.001 -0.048  0.026 -0.048  0.126 -0.073  0.176  0.101 -0.023 -0.073 -0.048 -0.023  0.001  0.001 -0.048 -0.023 -0.048 -0.048  0.026  0.026 -0.048  0.026 -0.048  0.026  0.001 
 0.059  0.034 -0.066 -0.016 -0.016  0.009 -0.066 -0.041 -0.041  0.009 -0.016  0.009 -0.066 -0.066 -0.041 -0.041 -0.016  0.059  0.034 -0.016 -0.066  0.034 -0.041 -0.041  0.034 -0.016  0.009  0.034  0.084 -0.016 -0.041 -0.041 -0.066 -0.066  0.059  0.009 -0.066 -0.041 -0.016 -0.016  0.034  0.009  0.009  0.009 -0.066 -0.066 -0.066  0.009 -0.041 -0.041 -0.016 -0.066  0.059 -0.041 -0.016 -0.016 -0.016 -0.066 -0.041 -0.066 -0.016 -0.041  0.034  0.034 -0.041  0.009  0.009  0.084 -0.041  0.034  0.084 -0.016  0.034  0.009  0.059  0.009 -0.066  0.009 -0.016  0.084 -0.066  0.084  0.084 -0.016 -0.041 -0.041 -0.041  0.009  0.009 -0.041 -0.041 -0.041 -0.041  0.034 -0.016 -0.041  0.034 -0.041  0.034  0.009 
 0.062  0.037 -0.062 -0.037 -0.012  0.037 -0.062 -0.037 -0.037 -0.012 -0.012 -0.012 -0.037 -0.062 -0.037 -0.037 -0.012  0.037  0.037 -0.012 -0.062  0.037 -0.037 -0.037  0.037 -0.012  0.012  0.062  0.062 -0.037 -0.037 -0.037 -0.062 -0.062  0.037  0.012 -0.062 -0.037 -0.012  0.037  0.012  0.012  0.012  0.012 -0.062 -0.062 -0.062 -0.012 -0.037 -0.037 -0.012 -0.062  0.037 -0.037 -0.012 -0.037 -0.012 -0.062 -0.037 -0.062 -0.037 -0.037  0.037  0.037 -0.037  0.012  0.012  0.087 -0.037  0.037  0.087 -0.012  0.037  0.012  0.037 -0.012 -0.062  0.012 -0.012  0.062 -0.062  0.062  0.062 -0.037 -0.037 -0.037 -0.037  0.012 -0.012 -0.037 -0.037 -0.062 -0.012  0.062 -0.037 -0.037 -0.012 -0.037  0.037 -0.012 
 0.071  0.021 -0.054 -0.029 -0.004  0.021 -0.054 -0.004 -0.054 -0.004 -0.029 -0.004 -0.029 -0.054 -0.029 -0.029 -0.004  0.046 -0.004 -0.004 -0.054  0.071 -0.029 -0.029  0.046 -0.029 -0.004  0.071  0.071 -0.029 -0.029 -0.029 -0.054 -0.054  0.021 -0.004 -0.054 -0.029 -0.004  0.021  0.021  0.021 -0.004 -0.004 -0.054 -0.054 -0.054 -0.004 -0.029 -0.029 -0.004 -0.054  0.021 -0.054 -0.004 -0.054 -0.029 -0.054 -0.029 -0.054 -0.029 -0.029  0.021  0.046 -0.029 -0.004  0.021  0.046 -0.029  0.046  0.046 -0.004  0.046 -0.004  0.021 -0.004 -0.054 -0.004 -0.004  0.071 -0.054  0.046  0.071 -0.029 -0.029 -0.029 -0.029  0.021 -0.004 -0.029 -0.029 -0.054 -0.029  0.071 -0.029 -0.029 -0.029 -0.004  0.046 -0.029 
 0.073  0.048 -0.052 -0.027 -0.002  0.023 -0.052  0.023 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.048 -0.002 -0.002 -0.052  0.048 -0.027 -0.027  0.048 -0.027 -0.002  0.073  0.073 -0.027 -0.052 -0.027 -0.052 -0.052  0.023 -0.002 -0.052 -0.027 -0.002  0.023  0.023  0.023 -0.027  0.023 -0.052 -0.052 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.023 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.023  0.048 -0.027 -0.002  0.023  0.023 -0.027  0.023  0.048 -0.002  0.023 -0.002  0.023 -0.002 -0.052 -0.002 -0.027  0.073 -0.052  0.048  0.023 -0.027 -0.027 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.052 -0.027  0.073 -0.027 -0.027 -0.027 -0.002  0.048 -0.027 
 0.073  0.048 -0.051 -0.026 -0.026  0.023 -0.051  0.023 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026  0.023 -0.051 -0.026 -0.026 -0.026 -0.026 -0.026 -0.001 -0.051  0.023 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.023  0.048 -0.026 -0.001  0.023  0.023 -0.026  0.023  0.048 -0.001  0.023 -0.001  0.023 -0.001 -0.051 -0.001 -0.026  0.073 -0.051  0.048  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.073 -0.026 -0.026 -0.026 -0.001  0.048 -0.026 
 0.073  0.048 -0.051 -0.026 -0.026  0.023 -0.051  0.023 -0.051 -0.001 -0.026 -0.001 -0.026 -0.051 -0.026 -0.051 -0.026  0.048 -0.001 -0.001 -0.051  0.048 -0.026 -0.026  0.048 -0.026 -0.001  0.073  0.073 -0.026 -0.051 -0.026 -0.051 -0.051 -0.001 -0.001 -0.026 -0.026 -0.001  0.023 -0.001  0.023 -0.026  0.023 -0.051 -0.026 -0.026 -0.026 -0.026 -0.026 -0.001 -0.051  0.023 -0.051 -0.001 -0.051 -0.026 -0.051 -0.051 -0.051 -0.026 -0.026  0.023  0.048 -0.026 -0.001  0.023  0.023 -0.026  0.023  0.048 -0.001  0.023 -0.001  0.023 -0.001 -0.051 -0.001 -0.026  0.073 -0.051  0.048  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.001 -0.026 -0.026 -0.051 -0.026  0.073 -0.026 -0.026 -0.026 -0.001  0.048 -0.026 
 0.072  0.047 -0.052 -0.027 -0.027  0.022 -0.052  0.022 -0.052 -0.002 -0.027 -0.002 -0.027 -0.052 -0.027 -0.052 -0.027  0.047 -0.002 -0.002 -0.052  0.047 -0.027 -0.027  0.047 -0.027 -0.002  0.072  0.072 -0.027 -0.052 -0.027 -0.052 -0.052 -0.002 -0.002 -0.027 -0.027 -0.002  0.022 -0.002  0.022 -0.027  0.022 -0.052 -0.027 -0.027 -0.027 -0.027 -0.027 -0.002 -0.052  0.022 -0.052 -0.002 -0.052 -0.027 -0.052 -0.052 -0.052 -0.027 -0.027  0.022  0.047 -0.027 -0.002  0.022  0.022 -0.002  0.022  0.047 -0.002  0.022 -0.002  0.022 -0.002 -0.052 -0.002 -0.027  0.072 -0.052  0.047  0.022 -0.027  0.022 -0.027 -0.027  0.022 -0.002 -0.027 -0.027 -0.052 -0.027  0.072 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 
 0.071  0.046 -0.028 -0.028 -0.028  0.021 -0.053  0.021 -0.053 -0.003 -0.028 -0.003 -0.028 -0.053 -0.028 -0.053 -0.028  0.046 -0.003 -0.003 -0.053  0.046 -0.028 -0.028  0.046 -0.028 -0.003  0.071  0.071 -0.028 -0.053 -0.028 -0.053 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 -0.003  0.021 -0.028  0.021 -0.053 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.053  0.021 -0.053 -0.003 -0.053 -0.028 -0.053 -0.053 -0.053 -0.028 -0.028  0.021  0.046 -0.028 -0.003  0.021  0.021  0.021  0.021  0.046 -0.003  0.021 -0.003  0.021 -0.003 -0.053 -0.003 -0.028  0.071 -0.053  0.046  0.021 -0.028  0.021 -0.028 -0.028  0.021 -0.003 -0.028 -0.028 -0.053 -0.028  0.071 -0.028 -0.003 -0.028 -0.003  0.046 -0.028 
 0.070  0.045 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 -0.054 -0.029  0.045 -0.004 -0.004 -0.054  0.045 -0.029 -0.029  0.045 -0.029 -0.004  0.070  0.070 -0.029 -0.054 -0.004 -0.054 -0.054 -0.004 -0.004 -0.029 -0.029 -0.004  0.020 -0.004  0.020 -0.029  0.020 -0.029 -0.029 -0.029 -0.029 -0.029 -0.029  0.020 -0.054  0.020 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.054 -0.029 -0.029  0.020  0.045 -0.029 -0.004  0.020  0.020  0.020  0.020  0.045 -0.004  0.020 -0.004  0.020 -0.004 -0.054 -0.004 -0.029  0.070 -0.054  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.020 -0.004 -0.029 -0.029 -0.054 -0.029  0.070 -0.029 -0.004 -0.029 -0.004  0.045 -0.029 
 0.070  0.045 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.045 -0.005 -0.005 -0.055  0.045 -0.030 -0.030  0.045 -0.030 -0.005  0.070  0.070 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.020  0.020 -0.005  0.020 -0.030  0.020 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.020 -0.055  0.020 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.020  0.045 -0.030 -0.005  0.020  0.020  0.020  0.020  0.045 -0.005  0.020 -0.005  0.020 -0.005 -0.055 -0.005 -0.030  0.070 -0.055  0.045  0.020 -0.030  0.020 -0.030 -0.030  0.020 -0.005 -0.030 -0.030 -0.055 -0.030  0.070 -0.030 -0.005 -0.030 -0.005  0.045 -0.030 
 0.069  0.044 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.055 -0.030  0.044 -0.005 -0.005 -0.055  0.044 -0.030 -0.030  0.044 -0.030 -0.005  0.069  0.069 -0.030 -0.055 -0.005 -0.055 -0.055 -0.005 -0.005 -0.030 -0.030  0.019  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.055  0.019 -0.055 -0.005 -0.055 -0.030 -0.055 -0.055 -0.055 -0.030 -0.030  0.019  0.044 -0.005 -0.005  0.019  0.019  0.019  0.019  0.044  0.019  0.019 -0.005  0.019  0.019 -0.055 -0.005 -0.030  0.069 -0.055  0.044  0.019 -0.030  0.019 -0.030 -0.030  0.019 -0.005 -0.030 -0.030 -0.055 -0.005  0.069 -0.030 -0.005 -0.030 -0.005  0.044 -0.030 
 0.095  0.045 -0.054 -0.029 -0.054  0.020 -0.079  0.020 -0.079 -0.004 -0.054 -0.029 -0.029 -0.029 -0.054 -0.079 -0.029  0.070 -0.029 -0.029 -0.079  0.045 -0.029 -0.054  0.045 -0.029  0.020  0.070  0.070 -0.054 -0.079 -0.029 -0.054 -0.079 -0.004 -0.029 -0.054 -0.054 -0.004  0.020 -0.004  0.045 -0.054 -0.004 -0.054 -0.029 -0.054 -0.029 -0.054 -0.004 -0.004 -0.004  0.020 -0.054 -0.004 -0.054 -0.054 -0.079 -0.079 -0.079 -0.054 -0.054  0.045  0.120 -0.004 -0.029  0.020 -0.004 -0.004 -0.004  0.045  0.045 -0.004 -0.004 -0.004  0.020 -0.079 -0.029 -0.054  0.095 -0.079  0.070 -0.004 -0.054  0.045 -0.054 -0.054  0.020 -0.029 -0.029  0.045 -0.079 -0.029  0.095 -0.054 -0.029 -0.054  0.045  0.145 -0.054 
 0.084  0.109 -0.065 -0.065 -0.115  0.009 -0.140  0.034 -0.140 -0.040 -0.065 -0.065 -0.065 -0.015 -0.115 -0.115  0.009  0.034  0.059 -0.090 -0.115 -0.015 -0.090 -0.115  0.109 -0.040 -0.015  0.034  0.084 -0.015 -0.065 -0.040 -0.115 -0.140 -0.040 -0.015 -0.090 -0.090 -0.065 -0.015 -0.015  0.059 -0.040  0.009 -0.040 -0.040 -0.115 -0.040 -0.115 -0.040 -0.015 -0.065  0.059 -0.090 -0.040 -0.090 -0.065 -0.115 -0.090 -0.090 -0.090 -0.040  0.059  0.109 -0.040  0.009  0.109  0.059 -0.040 -0.015  0.059  0.009 -0.015  0.009 -0.065  0.009 -0.140 -0.090  0.109  0.184 -0.140  0.259  0.159 -0.065  0.034 -0.115 -0.065 -0.015 -0.090 -0.090  0.134 -0.140 -0.040  0.109 -0.065 -0.040 -0.015  0.059  0.234 -0.115 
 0.064  0.064 -0.111 -0.061 -0.160 -0.036 -0.160 -0.036 -0.136 -0.061 -0.086 -0.061 -0.086 -0.061 -0.136 -0.136  0.014  0.014  0.064 -0.136 -0.136 -0.036 -0.136 -0.160  0.139 -0.036 -0.036 -0.011  0.064 -0.061 -0.036 -0.086 -0.136 -0.185 -0.061 -0.061 -0.136 -0.086 -0.111 -0.061 -0.011 -0.011 -0.086 -0.011 -0.111 -0.061 -0.111 -0.011 -0.160 -0.061 -0.111 -0.061  0.089 -0.086 -0.011 -0.111 -0.061 -0.111 -0.136 -0.136 -0.111 -0.036 -0.011  0.039 -0.061 -0.036  0.039  0.064  0.014 -0.011  0.064 -0.036 -0.011  0.014 -0.061  0.089 -0.136 -0.111  0.139  0.288 -0.185  0.313  0.188 -0.111 -0.011 -0.111 -0.086 -0.036 -0.111 -0.111  0.163 -0.136 -0.036  0.089 -0.086 -0.086 -0.036  0.064  0.238 -0.061 
 0.098  0.048 -0.102 -0.127 -0.127 -0.102 -0.151 -0.027 -0.127 -0.102 -0.127 -0.077 -0.127 -0.027 -0.077 -0.151 -0.027 -0.002  0.023 -0.176 -0.176  0.048 -0.176 -0.151  0.098  0.023 -0.052 -0.052  0.073 -0.127 -0.027 -0.151 -0.201 -0.251 -0.077 -0.027 -0.151 -0.127 -0.151 -0.127  0.023 -0.077 -0.102 -0.002 -0.176 -0.127 -0.151  0.023 -0.201 -0.052 -0.151 -0.027  0.048 -0.052 -0.027 -0.127 -0.052 -0.102 -0.201 -0.176 -0.151 -0.002 -0.102 -0.027 -0.102 -0.027  0.048  0.098  0.023  0.023  0.073 -0.052 -0.052 -0.002 -0.077  0.073 -0.102 -0.127  0.172  0.397 -0.226  0.347  0.297 -0.102 -0.077 -0.102 -0.102 -0.102 -0.127 -0.151  0.123 -0.151 -0.077  0.023 -0.102 -0.127 -0.002  0.098  0.222 -0.052 
 0.181  0.032 -0.093 -0.118 -0.093 -0.142 -0.118 -0.068 -0.118 -0.167 -0.167 -0.068 -0.118  0.032 -0.043 -0.142 -0.093 -0.018  0.007 -0.217 -0.167  0.057 -0.167 -0.118  0.082  0.007 -0.068 -0.093  0.057 -0.118 -0.018 -0.167 -0.242 -0.267 -0.043 -0.018 -0.142 -0.118 -0.142 -0.167  0.007 -0.118 -0.118 -0.018 -0.192 -0.118 -0.192 -0.018 -0.192 -0.068 -0.192 -0.018  0.007 -0.068 -0.068 -0.142 -0.043 -0.068 -0.217 -0.192 -0.192  0.032 -0.068 -0.068 -0.093 -0.043  0.057  0.107  0.057  0.007  0.057 -0.093 -0.043 -0.043 -0.068  0.032 -0.118 -0.093  0.206  0.356 -0.242  0.356  0.331 -0.118 -0.093 -0.068 -0.118 -0.118 -0.118 -0.167  0.057 -0.142 -0.142  0.007 -0.142 -0.093  0.007  0.032  0.231 -0.018 
 0.174  0.024 -0.125 -0.125 -0.125 -0.175 -0.100 -0.100 -0.125 -0.175 -0.150 -0.075 -0.150 -0.000  0.024 -0.150 -0.075 -0.050 -0.000 -0.225 -0.175  0.024 -0.175 -0.125  0.074 -0.025 -0.075 -0.100  0.049 -0.150 -0.025 -0.200 -0.275 -0.299 -0.050 -0.025 -0.125 -0.125 -0.150 -0.200  0.049 -0.125 -0.100  0.024 -0.225 -0.150 -0.225 -0.000 -0.200 -0.100 -0.250 -0.025  0.024 -0.050 -0.075 -0.150 -0.000 -0.100 -0.225 -0.225 -0.225  0.024 -0.125 -0.100 -0.100 -0.050  0.049  0.074  0.074  0.024  0.074 -0.150 -0.050 -0.075 -0.025 -0.000 -0.150 -0.075  0.199  0.323 -0.275  0.323  0.298 -0.125 -0.125 -0.100 -0.150 -0.100 -0.075 -0.175  0.049 -0.150 -0.150 -0.000 -0.150 -0.150  0.024  0.049  0.199 -0.000 
 0.190  0.016 -0.134 -0.134 -0.134 -0.158 -0.109 -0.109 -0.134 -0.183 -0.158  0.016 -0.183 -0.009  0.091 -0.109 -0.084 -0.034  0.016 -0.233 -0.183  0.041 -0.183 -0.134  0.091 -0.034 -0.084 -0.109  0.041 -0.158 -0.034 -0.208 -0.283 -0.308 -0.059 -0.059 -0.134 -0.134 -0.109 -0.233  0.041 -0.134 -0.109  0.016 -0.233 -0.158 -0.233 -0.009 -0.208 -0.109 -0.208 -0.059  0.016 -0.059 -0.084 -0.109 -0.009 -0.109 -0.233 -0.233 -0.233  0.016 -0.134 -0.109 -0.109 -0.059  0.066  0.066  0.041  0.016  0.091 -0.183 -0.034 -0.084 -0.034 -0.009 -0.183 -0.059  0.215  0.315 -0.283  0.340  0.265 -0.134 -0.134 -0.109 -0.158 -0.109 -0.084 -0.183  0.066 -0.158 -0.183 -0.009 -0.158 -0.158  0.016  0.041  0.215 -0.009 
 0.232  0.007 -0.192 -0.117 -0.142 -0.142 -0.092 -0.092 -0.142 -0.167 -0.167  0.057 -0.192  0.007  0.132 -0.117 -0.092 -0.042  0.007 -0.242 -0.192  0.032 -0.217 -0.167  0.082 -0.042 -0.092 -0.092  0.032 -0.142 -0.017 -0.217 -0.291 -0.316 -0.067 -0.067 -0.142 -0.117 -0.092 -0.242  0.032 -0.142 -0.092  0.007 -0.242 -0.167 -0.242 -0.017 -0.217 -0.117 -0.167 -0.067  0.007 -0.042 -0.092 -0.117  0.007 -0.142 -0.242 -0.242 -0.242 -0.042 -0.142 -0.067 -0.117 -0.067  0.057  0.057  0.032  0.057  0.082 -0.192 -0.042 -0.067 -0.042  0.007 -0.217 -0.017  0.232  0.306 -0.291  0.331  0.257 -0.117 -0.142 -0.117 -0.167 -0.117 -0.092 -0.192  0.057 -0.167 -0.192  0.007 -0.142 -0.142  0.032 -0.017  0.232  0.007 
 0.224  0.000 -0.199 -0.100 -0.149 -0.125 -0.100 -0.100 -0.149 -0.149 -0.149  0.050 -0.224  0.000  0.125 -0.125 -0.100 -0.050  0.000 -0.249 -0.199  0.050 -0.224 -0.174  0.075 -0.050 -0.100 -0.100  0.075 -0.149 -0.025 -0.199 -0.299 -0.324 -0.050 -0.075 -0.149 -0.125 -0.100 -0.249  0.025 -0.149 -0.100  0.000 -0.249 -0.174 -0.224 -0.025 -0.224 -0.125 -0.174 -0.075  0.000 -0.025 -0.100 -0.125  0.000 -0.149 -0.249 -0.249 -0.249 -0.050 -0.149 -0.075 -0.125 -0.050  0.075  0.075  0.025  0.100  0.100 -0.199 -0.050 -0.075 -0.050  0.000 -0.224 -0.025  0.224  0.324 -0.274  0.324  0.249 -0.100 -0.149 -0.100 -0.174 -0.125 -0.100 -0.199  0.050 -0.174 -0.199  0.000 -0.149 -0.149  0.050 -0.025  0.199  0.025 
 0.218 -0.031 -0.205 -0.106 -0.131 -0.131 -0.106 -0.106 -0.131 -0.131 -0.131  0.044 -0.230 -0.006  0.143 -0.131 -0.106 -0.056 -0.006 -0.255 -0.205  0.069 -0.230 -0.205  0.069 -0.056 -0.106 -0.131  0.069 -0.155 -0.056 -0.230 -0.305 -0.330 -0.031 -0.081 -0.180 -0.131 -0.106 -0.255 -0.006 -0.155 -0.081 -0.006 -0.230 -0.155 -0.230 -0.106 -0.230 -0.131 -0.155 -0.081 -0.006 -0.006 -0.106 -0.131 -0.006 -0.155 -0.255 -0.255 -0.255  0.019 -0.155 -0.081 -0.131 -0.031  0.069  0.094  0.019  0.143  0.094 -0.180 -0.056 -0.006 -0.081 -0.006 -0.205 -0.056  0.243  0.318 -0.280  0.318  0.218 -0.081 -0.155 -0.056 -0.180 -0.131 -0.106 -0.205  0.044 -0.180 -0.205 -0.031 -0.155 -0.155  0.069 -0.056  0.168  0.019 
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 0.363  0.089 -0.060  0.089  0.014 -0.010 -0.085 -0.060  0.039 -0.185  0.513  0.264  0.164 -0.035  0.338  0.064 -0.010 -0.085  0.164  0.114 -0.160  0.039 -0.160  0.164  0.139  0.288 -0.035 -0.060  0.064 -0.135 -0.085 -0.085 -0.160  0.139  0.039 -0.010  0.189 -0.085  0.039 -0.060  0.264  0.114  0.139  0.737 -0.160  0.014  0.089 -0.010  0.039  0.139  0.139  0.264  0.114  0.239 -0.235  0.264 -0.110  0.388  0.239 -0.160  0.712 -0.060 -0.085 -0.060  0.089  0.039 -0.135 -0.210 -0.135 -0.035  0.288  0.313 -0.110  0.014  0.239  0.114  0.014  0.014  0.189  0.363  0.139  0.413  0.164 -0.235 -0.010  0.164  0.039  0.363  0.687 -0.060 -0.110  0.014 -0.135 -0.010  0.712 -0.085 -0.010 -0.010 -0.185 -0.060 
 0.412  0.088 -0.062  0.113  0.063 -0.012 -0.087 -0.037  0.038 -0.211  0.511  0.287  0.162 -0.037  0.287  0.063 -0.037 -0.087  0.138  0.113 -0.161  0.113 -0.161  0.138  0.162  0.287 -0.037 -0.087  0.088 -0.137 -0.087 -0.087 -0.161  0.187  0.038 -0.012  0.162 -0.112  0.038 -0.062  0.262  0.113  0.138  0.735 -0.161  0.063  0.063  0.013  0.088  0.138  0.138  0.287  0.113  0.287 -0.261  0.287 -0.112  0.387  0.237 -0.186  0.636 -0.062 -0.012 -0.062  0.088  0.063 -0.112 -0.211 -0.137 -0.037  0.287  0.312 -0.112  0.013  0.237  0.063  0.013  0.063  0.187  0.337  0.162  0.412  0.212 -0.236 -0.062  0.187  0.038  0.412  0.686 -0.037 -0.112  0.063 -0.137 -0.012  0.710 -0.062  0.038 -0.012 -0.211 -0.012 
 0.479  0.105 -0.019  0.130  0.055  0.005 -0.069 -0.044  0.030 -0.219  0.529  0.329  0.180 -0.044  0.255  0.055  0.005 -0.094  0.205  0.105 -0.144  0.180 -0.169  0.155  0.180  0.304 -0.019 -0.094  0.080 -0.119 -0.044 -0.094 -0.194  0.230  0.080  0.005  0.155 -0.119  0.030 -0.044  0.230  0.130  0.180  0.678 -0.169  0.055  0.030  0.130  0.130  0.155  0.155  0.280  0.105  0.404 -0.269  0.280 -0.119  0.404  0.255 -0.169  0.578 -0.044  0.030 -0.069  0.105  0.080 -0.119 -0.219 -0.144 -0.044  0.280  0.304 -0.069  0.005  0.329  0.030 -0.019  0.105  0.280  0.354  0.180  0.404  0.205 -0.244 -0.069  0.180  0.055  0.429  0.678 -0.044 -0.119  0.105 -0.144  0.005  0.703 -0.069  0.030  0.005 -0.169  0.005 
 0.525  0.126 -0.048  0.176  0.051  0.026 -0.073 -0.073  0.051 -0.223  0.525  0.375  0.151 -0.073  0.300  0.051  0.076 -0.123  0.251  0.101 -0.148  0.176 -0.173  0.151  0.176  0.325  0.076 -0.073  0.076 -0.098 -0.023 -0.098 -0.198  0.226  0.126  0.001  0.151 -0.123  0.026 -0.048  0.226  0.201  0.176  0.649 -0.198  0.051 -0.023  0.126  0.201  0.176  0.176  0.300  0.076  0.400 -0.223  0.276 -0.123  0.450  0.226 -0.173  0.525 -0.048  0.051 -0.073  0.101  0.101 -0.123 -0.223 -0.148 -0.048  0.276  0.300 -0.073  0.026  0.325 -0.023 -0.023  0.126  0.276  0.350  0.176  0.375  0.176 -0.248 -0.073  0.176  0.026  0.425  0.674 -0.048 -0.148  0.101 -0.198  0.026  0.699 -0.098  0.026  0.001 -0.148  0.026 
 0.545  0.146 -0.103  0.196  0.097  0.122 -0.028 -0.078  0.072 -0.202  0.545  0.396  0.171 -0.103  0.296  0.072  0.097 -0.128  0.246  0.122 -0.152  0.246 -0.177  0.171  0.171  0.371  0.097 -0.078  0.097 -0.003 -0.003 -0.078 -0.177  0.321  0.171 -0.003  0.171 -0.103 -0.003 -0.028  0.171  0.221  0.171  0.620 -0.202  0.097 -0.053  0.196  0.196  0.196  0.196  0.346  0.097  0.470 -0.227  0.271 -0.177  0.445  0.221 -0.177  0.421 -0.078  0.097 -0.103  0.097  0.122 -0.128 -0.202 -0.152 -0.053  0.271  0.296 -0.078  0.022  0.321 -0.028 -0.028  0.122  0.271  0.346  0.146  0.371  0.171 -0.252 -0.053  0.171  0.047  0.445  0.620 -0.053 -0.152  0.122 -0.202  0.022  0.645 -0.078  0.022 -0.003 -0.152 -0.003 
 0.541  0.142 -0.107  0.242  0.118  0.267 -0.007 -0.057  0.142 -0.181  0.541  0.392  0.242 -0.082  0.342  0.068  0.142 -0.107  0.267  0.118 -0.082  0.267 -0.181  0.217  0.142  0.342  0.118 -0.082  0.142  0.018  0.018 -0.057 -0.181  0.317  0.242  0.043  0.217 -0.107 -0.007 -0.032  0.142  0.217  0.167  0.616 -0.181  0.118 -0.057  0.217  0.192  0.217  0.192  0.342  0.093  0.466 -0.231  0.292 -0.181  0.417  0.167 -0.181  0.392 -0.082  0.142 -0.107  0.093  0.118 -0.107 -0.206 -0.156 -0.057  0.267  0.292 -0.107  0.018  0.317 -0.032 -0.032  0.167  0.317  0.342  0.142  0.342  0.142 -0.256 -0.057  0.142  0.068  0.441  0.616 -0.057 -0.156  0.118 -0.181  0.018  0.641 -0.057  0.018 -0.007 -0.156 -0.007 
 0.537  0.139 -0.111  0.263  0.114  0.263  0.039 -0.061  0.163 -0.160  0.562  0.437  0.313 -0.061  0.338  0.114  0.188 -0.111  0.213  0.188 -0.061  0.263 -0.185  0.313  0.114  0.363  0.139  0.039  0.238  0.089  0.064 -0.036 -0.185  0.263  0.238  0.039  0.238 -0.136  0.014 -0.011  0.114  0.213  0.139  0.612 -0.185  0.139 -0.061  0.238  0.263  0.263  0.213  0.338  0.089  0.437 -0.210  0.263 -0.185  0.388  0.188 -0.185  0.313 -0.086  0.188 -0.160  0.114  0.114 -0.061 -0.210 -0.160 -0.086  0.263  0.288 -0.136  0.039  0.313  0.014 -0.011  0.188  0.263  0.313  0.139  0.313  0.114 -0.260 -0.061  0.139  0.064  0.413  0.612 -0.061 -0.136  0.114 -0.160  0.014  0.612 -0.061  0.039 -0.011 -0.160 -0.011 
 0.502  0.128 -0.096  0.278  0.103  0.278  0.028 -0.071  0.153 -0.146  0.576  0.452  0.327 -0.096  0.352  0.178  0.203 -0.121  0.203  0.203 -0.071  0.253 -0.171  0.352  0.103  0.352  0.178  0.028  0.278  0.178  0.078 -0.021 -0.196  0.228  0.253  0.053  0.228 -0.146  0.003  0.128  0.103  0.228  0.128  0.601 -0.196  0.178 -0.071  0.253  0.302  0.278  0.253  0.327  0.078  0.427 -0.171  0.253 -0.196  0.377  0.178 -0.171  0.302 -0.096  0.203 -0.171  0.153  0.128  0.003 -0.196 -0.146 -0.096  0.253  0.278 -0.071  0.028  0.302  0.003  0.003  0.253  0.253  0.327  0.103  0.253  0.103 -0.271 -0.046  0.128  0.053  0.427  0.601 -0.071 -0.171  0.103 -0.096  0.053  0.552 -0.046  0.028 -0.021 -0.096  0.003 
 0.499  0.126 -0.099  0.300  0.101  0.275  0.051 -0.099  0.150 -0.124  0.574  0.449  0.325 -0.099  0.350  0.175  0.250 -0.099  0.175  0.225 -0.124  0.275 -0.173  0.375  0.101  0.325  0.175  0.026  0.375  0.225  0.101  0.051 -0.198  0.175  0.250  0.076  0.325 -0.124  0.001  0.150  0.051  0.275  0.126  0.599 -0.198  0.225 -0.074  0.325  0.325  0.325  0.250  0.300  0.076  0.400 -0.173  0.200 -0.198  0.300  0.150 -0.173  0.325 -0.099  0.225 -0.148  0.150  0.150  0.001 -0.173 -0.148 -0.099  0.225  0.275 -0.074  0.026  0.275 -0.074  0.001  0.250  0.250  0.325  0.150  0.175  0.101 -0.298  0.001  0.126  0.076  0.449  0.549 -0.074 -0.198  0.126 -0.074  0.101  0.499 -0.024  0.026 -0.024 -0.074  0.001 
 0.522  0.148 -0.101  0.298  0.099  0.248  0.074 -0.101  0.148 -0.126  0.547  0.472  0.348 -0.101  0.348  0.173  0.248 -0.101  0.173  0.323 -0.126  0.273 -0.150  0.398  0.049  0.348  0.173  0.024  0.348  0.273  0.148  0.074 -0.200  0.173  0.248  0.074  0.323 -0.126  0.024  0.198  0.049  0.248  0.099  0.597 -0.175  0.273 -0.001  0.323  0.348  0.373  0.273  0.298  0.099  0.373 -0.175  0.198 -0.200  0.298  0.099 -0.200  0.298 -0.101  0.223 -0.150  0.148  0.148 -0.026 -0.175 -0.175 -0.101  0.223  0.248 -0.051  0.024  0.273 -0.101 -0.001  0.223  0.198  0.348  0.148  0.148  0.099 -0.300  0.024  0.124  0.049  0.447  0.547 -0.076 -0.200  0.124 -0.076  0.099  0.497 -0.026  0.024 -0.051 -0.076 -0.001 
 0.520  0.196 -0.103  0.246  0.146  0.320  0.071 -0.103  0.146 -0.103  0.545  0.470  0.370 -0.103  0.345  0.196  0.271 -0.153  0.146  0.445 -0.128  0.271 -0.128  0.420  0.046  0.295  0.246  0.121  0.370  0.271  0.246  0.096 -0.203  0.146  0.246  0.071  0.345 -0.128 -0.003  0.246 -0.003  0.221  0.071  0.594 -0.178  0.295  0.021  0.345  0.370  0.370  0.271  0.295  0.121  0.345 -0.178  0.121 -0.203  0.295  0.096 -0.203  0.271 -0.103  0.221 -0.128  0.171  0.146 -0.003 -0.178 -0.153 -0.103  0.221  0.221 -0.078  0.021  0.246 -0.053 -0.003  0.196  0.171  0.345  0.146  0.121  0.071 -0.278  0.021  0.096 -0.003  0.470  0.545 -0.103 -0.203  0.096 -0.078  0.121  0.495  0.021  0.071 -0.053 -0.053 -0.003 
 0.518  0.244 -0.105  0.269  0.169  0.319  0.070 -0.105  0.144 -0.105  0.543  0.468  0.344 -0.130  0.344  0.194  0.269 -0.154  0.144  0.443 -0.130  0.219 -0.130  0.493  0.045  0.269  0.244  0.120  0.369  0.294  0.244  0.095 -0.179  0.169  0.269  0.045  0.344 -0.130 -0.005  0.244 -0.005  0.244  0.120  0.568 -0.179  0.294  0.070  0.344  0.394  0.443  0.244  0.294  0.120  0.369 -0.179  0.095 -0.179  0.244  0.095 -0.204  0.269 -0.105  0.219 -0.080  0.169  0.144 -0.005 -0.179 -0.154 -0.130  0.219  0.219 -0.080  0.020  0.244 -0.055 -0.005  0.194  0.194  0.294  0.144  0.045  0.045 -0.279  0.020  0.095 -0.005  0.468  0.543 -0.080 -0.204  0.095 -0.080  0.120  0.468  0.020  0.070 -0.055 -0.055 -0.005 
 0.545  0.246 -0.128  0.271  0.221  0.370  0.146 -0.053  0.121 -0.028  0.569  0.445  0.370 -0.128  0.345  0.196  0.271 -0.203  0.121  0.470 -0.128  0.221 -0.128  0.495  0.046  0.271  0.271  0.171  0.420  0.295  0.246  0.121 -0.178  0.171  0.246  0.021  0.345 -0.128 -0.003  0.271 -0.028  0.271  0.196  0.569 -0.178  0.295  0.146  0.370  0.445  0.420  0.221  0.320  0.071  0.370 -0.178  0.071 -0.178  0.096  0.096 -0.228  0.271 -0.053  0.221 -0.053  0.146  0.121 -0.003 -0.178 -0.128 -0.103  0.221  0.221 -0.053 -0.028  0.196 -0.053 -0.028  0.196  0.171  0.246  0.146 -0.028  0.046 -0.278 -0.028  0.096 -0.003  0.445  0.545 -0.078 -0.203  0.121 -0.103  0.121  0.370 -0.003  0.096 -0.053 -0.028 -0.028 
 0.421  0.246 -0.128  0.271  0.171  0.346  0.146 -0.078  0.047 -0.028  0.495  0.421  0.346 -0.078  0.396  0.171  0.296 -0.177 -0.028  0.445 -0.128  0.146 -0.103  0.346  0.072  0.271  0.221  0.122  0.346  0.271  0.246  0.022 -0.103  0.171  0.146  0.072  0.396 -0.152 -0.003  0.171 -0.078  0.271  0.097  0.620 -0.128  0.271  0.072  0.421  0.421  0.246  0.171  0.371  0.122  0.271 -0.128  0.097 -0.103  0.072  0.072 -0.177  0.196 -0.028  0.097 -0.053  0.072  0.146  0.022 -0.128 -0.128 -0.053  0.196  0.122 -0.053 -0.078  0.146 -0.028  0.022  0.097  0.122  0.196  0.221 -0.028 -0.028 -0.202  0.047  0.122  0.047  0.421  0.520 -0.028 -0.128  0.122 -0.053  0.097  0.296 -0.003  0.122 -0.028 -0.053  0.022 
 0.385  0.086 -0.088  0.211  0.186  0.335  0.161 -0.038  0.036  0.036  0.435  0.310  0.360 -0.013  0.310  0.136  0.186 -0.113  0.011  0.485 -0.113  0.136 -0.088  0.310  0.011  0.211  0.136  0.186  0.285  0.236  0.111  0.036 -0.038  0.086  0.111  0.111  0.410 -0.138 -0.013  0.161 -0.013  0.310  0.011  0.684 -0.088  0.236 -0.013  0.435  0.360  0.136  0.111  0.335  0.061  0.111 -0.113  0.011 -0.063  0.036  0.061 -0.113  0.186  0.061  0.086 -0.088  0.061  0.061 -0.038 -0.113 -0.138 -0.038  0.186  0.111 -0.013 -0.063  0.161  0.011  0.011  0.061 -0.013  0.161  0.136 -0.013 -0.088 -0.163  0.086  0.086  0.036  0.261  0.335 -0.013 -0.088  0.061 -0.038  0.086  0.161  0.036  0.036 -0.038 -0.088  0.011 
 0.377  0.103 -0.071  0.178  0.178  0.377  0.178 -0.021  0.028  0.028  0.427  0.302  0.278  0.003  0.327  0.128  0.178 -0.096  0.003  0.427 -0.096  0.153 -0.096  0.278  0.028  0.228  0.128  0.203  0.278  0.203  0.028  0.028 -0.021  0.053  0.128  0.128  0.477 -0.071  0.003  0.128 -0.021  0.302  0.028  0.676 -0.096  0.203 -0.021  0.502  0.352  0.078  0.103  0.327  0.053  0.078 -0.096  0.028 -0.046  0.053  0.078 -0.096  0.153  0.103  0.078 -0.096  0.078  0.053 -0.071 -0.096 -0.146 -0.046  0.078  0.103 -0.021 -0.071  0.178  0.028  0.003  0.003  0.003  0.178  0.153 -0.021 -0.071 -0.146  0.103  0.028  0.003  0.278  0.253 -0.021 -0.071  0.078 -0.046  0.028  0.078  0.053  0.028 -0.021 -0.046 -0.021 
 0.331  0.107 -0.043  0.107  0.181  0.430  0.156 -0.018  0.032  0.057  0.406  0.306  0.281  0.007  0.281  0.156  0.181 -0.068 -0.018  0.406 -0.068  0.181 -0.093  0.256  0.032  0.181  0.057  0.256  0.281  0.206  0.007  0.057  0.007  0.082  0.107  0.181  0.530 -0.043 -0.018  0.082  0.007  0.306  0.057  0.680 -0.093  0.231 -0.018  0.530  0.281  0.107  0.156  0.331  0.057  0.057 -0.068  0.057 -0.018  0.057  0.057 -0.093  0.107  0.032 -0.018 -0.068  0.032  0.007 -0.018 -0.068 -0.118 -0.093  0.057  0.057 -0.043 -0.068  0.156  0.007  0.007 -0.093 -0.018  0.132  0.132 -0.018 -0.068 -0.118  0.107 -0.018  0.007  0.181  0.107  0.007 -0.043  0.032  0.007  0.007  0.032  0.057 -0.018 -0.018 -0.043 -0.018 
 0.266  0.092 -0.033  0.092  0.191  0.416  0.166 -0.008  0.042  0.092  0.366  0.241  0.291  0.017  0.241  0.142  0.142 -0.058 -0.008  0.416 -0.058  0.191 -0.083  0.241  0.042  0.166  0.067  0.241  0.266  0.191  0.017  0.067 -0.008  0.092  0.092  0.191  0.540 -0.033 -0.058  0.092  0.017  0.316  0.092  0.714 -0.083  0.241 -0.058  0.540  0.291  0.117  0.166  0.341  0.067  0.017 -0.058  0.067 -0.008  0.017  0.042 -0.083  0.117 -0.008 -0.008 -0.058 -0.008 -0.033 -0.008 -0.058 -0.108 -0.083  0.067  0.067 -0.058 -0.058  0.142  0.017 -0.033 -0.083 -0.008  0.067  0.067 -0.008 -0.058 -0.108  0.117 -0.033  0.017  0.166  0.042  0.017 -0.033  0.017 -0.008  0.017  0.017  0.067 -0.008 -0.008 -0.033 -0.008 
 0.211  0.111 -0.013  0.061  0.211  0.335  0.161  0.011  0.036  0.111  0.360  0.211  0.285  0.011  0.136  0.061  0.061 -0.038 -0.038  0.335 -0.038  0.211 -0.063  0.211  0.061  0.161  0.036  0.236  0.161  0.161  0.036  0.036 -0.063  0.086  0.111  0.186  0.560 -0.013 -0.063  0.061  0.036  0.310  0.086  0.709 -0.063  0.261 -0.038  0.485  0.236  0.086  0.186  0.310  0.061 -0.038 -0.038  0.036 -0.013  0.036  0.061 -0.063  0.086 -0.013 -0.038 -0.038  0.011 -0.038 -0.013 -0.063 -0.088 -0.063  0.061  0.036 -0.038 -0.038  0.111  0.036 -0.038 -0.088  0.011  0.011  0.061  0.011 -0.038 -0.088  0.136 -0.063  0.036  0.111 -0.013  0.036  0.011  0.011  0.011  0.036 -0.038  0.086 -0.013 -0.038 -0.038 -0.013 
 0.195  0.096 -0.004  0.071  0.170  0.345  0.170  0.021 -0.029  0.121  0.245  0.220  0.295 -0.029  0.096  0.046 -0.004 -0.029 -0.029  0.295 -0.029  0.195 -0.054  0.145 -0.004  0.121  0.021  0.220  0.145  0.145  0.021 -0.004 -0.054  0.021  0.096  0.195  0.569 -0.004 -0.079  0.046  0.021  0.270  0.071  0.743 -0.079  0.195 -0.054  0.469  0.195  0.096  0.170  0.295  0.021 -0.029 -0.054 -0.004 -0.004  0.046  0.021 -0.079  0.096 -0.029 -0.054 -0.029 -0.004 -0.029 -0.004 -0.079 -0.054 -0.054  0.046  0.021 -0.029 -0.029  0.121  0.021 -0.029 -0.079  0.021  0.021  0.046 -0.004 -0.054 -0.079  0.121 -0.054  0.046  0.121 -0.029  0.021 -0.029 -0.004  0.021  0.021 -0.029  0.096 -0.004 -0.029 -0.029 -0.004 
 0.064  0.014 -0.035  0.014  0.139  0.338  0.189  0.014 -0.060  0.089  0.164  0.164  0.239 -0.010  0.064  0.039 -0.010 -0.010 -0.035  0.264 -0.010  0.114 -0.060  0.139 -0.010  0.089  0.014  0.164  0.089  0.114  0.039  0.014 -0.035  0.014  0.039  0.164  0.587  0.014 -0.060 -0.010  0.039  0.264  0.064  0.787 -0.060  0.189 -0.060  0.438  0.064  0.089  0.089  0.239 -0.010 -0.010 -0.060 -0.010  0.014  0.039  0.014 -0.060 -0.010 -0.035 -0.035 -0.010  0.014 -0.010  0.014 -0.060 -0.035 -0.035  0.064  0.014 -0.035 -0.035  0.039  0.039 -0.035 -0.060  0.039 -0.010  0.014 -0.010 -0.060 -0.060  0.139 -0.035  0.064  0.114 -0.010  0.014 -0.035 -0.010  0.039  0.014 -0.010  0.064  0.014 -0.010 -0.010 -0.010 
 0.076  0.026 -0.024  0.026  0.051  0.250  0.150  0.001 -0.049  0.076  0.101  0.101  0.200  0.001  0.051  0.026  0.001 -0.024 -0.024  0.225  0.001  0.076 -0.049  0.126 -0.024  0.101 -0.024  0.076  0.051  0.026  0.001  0.001 -0.024 -0.024  0.001  0.175  0.599  0.026 -0.049  0.001  0.051  0.225  0.076  0.798 -0.049  0.175 -0.049  0.375  0.001  0.076  0.051  0.225  0.001  0.001 -0.049  0.001  0.001  0.001  0.001 -0.049 -0.024 -0.024 -0.024  0.001  0.026 -0.024  0.026 -0.049 -0.024 -0.024  0.076  0.001 -0.024 -0.049  0.026  0.026 -0.024 -0.049  0.051  0.001  0.001  0.001 -0.049 -0.049  0.126 -0.024  0.051  0.076  0.001  0.026 -0.049 -0.024  0.051  0.026  0.001  0.026 -0.024  0.001  0.001  0.001 
 0.013  0.038 -0.036 -0.011  0.013  0.038  0.088  0.013 -0.036 -0.011  0.063  0.013  0.113  0.013  0.038  0.013  0.013 -0.011 -0.011  0.113 -0.036  0.038 -0.036  0.063 -0.036  0.013 -0.011  0.013  0.013 -0.011 -0.011  0.013 -0.011 -0.011  0.013  0.063  0.636  0.013 -0.036  0.013  0.038  0.113  0.038  0.910 -0.036  0.163 -0.011  0.213 -0.011  0.013  0.063  0.113 -0.011  0.038 -0.036  0.013 -0.011  0.013 -0.011 -0.036  0.013 -0.036 -0.011 -0.036  0.038 -0.011  0.013 -0.036 -0.011 -0.036  0.063  0.013 -0.011 -0.036  0.013  0.038 -0.011 -0.036  0.038  0.013 -0.011  0.013 -0.036 -0.036  0.113 -0.011  0.063  0.038  0.013  0.038 -0.036 -0.011  0.063  0.013  0.038  0.013 -0.036 -0.011  0.013  0.013 
 0.016  0.041 -0.033 -0.008 -0.008  0.016  0.091 -0.008 -0.033 -0.008  0.016  0.016  0.066  0.016  0.041  0.016  0.016 -0.008 -0.008  0.091 -0.033  0.016 -0.033  0.016 -0.033 -0.008  0.016  0.016 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008  0.016  0.066  0.589  0.016 -0.033  0.016  0.041  0.091  0.016  0.963 -0.033  0.091 -0.008  0.166 -0.008 -0.008  0.041  0.116 -0.008  0.041 -0.033  0.016 -0.008 -0.008 -0.008 -0.033  0.016 -0.033 -0.008 -0.033  0.016 -0.008 -0.008 -0.033 -0.008 -0.033  0.016 -0.008 -0.008 -0.008  0.041  0.041 -0.008 -0.033  0.041  0.016 -0.008  0.016 -0.033 -0.033  0.116 -0.008  0.066  0.041  0.041  0.066 -0.033 -0.033 -0.008  0.016  0.041  0.016 -0.033 -0.008  0.016  0.016 
 0.020  0.045 -0.029 -0.004 -0.004  0.020  0.070 -0.004 -0.029 -0.029  0.020  0.020  0.070  0.020  0.045  0.045  0.020 -0.029 -0.004  0.045 -0.029 -0.029 -0.029  0.020 -0.029 -0.004  0.020  0.020 -0.029 -0.004 -0.029 -0.004 -0.004 -0.004 -0.004  0.070  0.494  0.020 -0.029 -0.004  0.020  0.045  0.020  0.992 -0.029  0.070 -0.004  0.070 -0.004 -0.004  0.045  0.095 -0.004  0.045 -0.029  0.020 -0.004 -0.004 -0.004 -0.029 -0.004 -0.029 -0.004 -0.029  0.020 -0.004 -0.004 -0.029 -0.004 -0.029  0.020 -0.004 -0.004 -0.004  0.045  0.020 -0.004 -0.029  0.045  0.020 -0.029  0.020 -0.029 -0.029  0.095 -0.004  0.070  0.020  0.020  0.045 -0.029 -0.029 -0.004  0.020  0.045  0.020 -0.029 -0.004  0.020  0.020 
 0.023  0.023 -0.026 -0.001 -0.001  0.023  0.048 -0.001 -0.026 -0.026  0.023  0.023  0.023  0.023  0.023  0.048  0.023 -0.026 -0.001  0.048 -0.026 -0.026 -0.026  0.023 -0.026 -0.026 -0.001 -0.001 -0.026 -0.026 -0.026 -0.026 -0.001 -0.001 -0.001  0.048  0.347  0.023 -0.026 -0.001  0.023  0.048 -0.001  0.995 -0.026  0.073 -0.001  0.048 -0.001 -0.001  0.048  0.098 -0.001  0.023 -0.026 -0.001 -0.001 -0.001 -0.001 -0.026 -0.001 -0.026 -0.001 -0.026 -0.001 -0.001 -0.001 -0.026 -0.001 -0.026  0.023 -0.001 -0.001 -0.026  0.048  0.023 -0.001 -0.026  0.048  0.023 -0.026  0.023 -0.026 -0.026  0.098 -0.001  0.073  0.023  0.023  0.023 -0.026 -0.026 -0.026 -0.001  0.048 -0.001 -0.026 -0.001  0.023  0.023 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
 0.029  0.029 -0.020  0.004 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029  0.029  0.029  0.029  0.004  0.029  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.079  0.004 -0.020  0.004  0.004  0.029  0.004  1.001 -0.020  0.054  0.004  0.004  0.004  0.004  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
 0.051  0.026 -0.024  0.001 -0.024  0.026  0.076  0.001 -0.024 -0.024  0.026  0.051  0.026  0.026  0.001  0.026  0.001 -0.024  0.001  0.076 -0.024 -0.024 -0.024  0.026 -0.024 -0.024  0.001  0.001 -0.024 -0.024 -0.024 -0.024  0.001 -0.024  0.001  0.076  0.101  0.001 -0.024  0.001  0.001  0.026  0.001  0.997 -0.024  0.051  0.001  0.001  0.001  0.026  0.076  0.001  0.001  0.051 -0.024  0.001  0.026 -0.024  0.001 -0.024  0.001 -0.024  0.001 -0.024  0.001 -0.024  0.001 -0.024  0.001 -0.024  0.026  0.001  0.001 -0.024  0.076  0.026  0.001 -0.024  0.076  0.026 -0.024  0.001 -0.024 -0.024  0.001  0.001  0.001  0.026  0.026  0.001 -0.024 -0.024 -0.024  0.026  0.051  0.001 -0.024  0.001  0.001  0.026 
 0.062  0.037 -0.038 -0.013 -0.013  0.012  0.112  0.012 -0.038 -0.038  0.012  0.062  0.037  0.012  0.062  0.062  0.037 -0.038 -0.013  0.112 -0.038 -0.013 -0.038  0.037 -0.038 -0.038 -0.013  0.012 -0.013 -0.038 -0.013 -0.013 -0.013  0.012 -0.013  0.087  0.211 -0.013 -0.038  0.037 -0.013  0.037  0.012  0.984 -0.038  0.087 -0.013 -0.013 -0.013  0.012  0.087  0.037 -0.013  0.087 -0.038  0.012  0.012 -0.013  0.012 -0.038 -0.013 -0.013  0.012 -0.013  0.037 -0.013 -0.013 -0.038  0.012 -0.038  0.037 -0.013 -0.013 -0.038  0.062  0.037 -0.013 -0.038  0.112  0.037 -0.038 -0.013 -0.038 -0.038  0.012  0.012 -0.013  0.037  0.012 -0.013 -0.013 -0.038 -0.038  0.037  0.037 -0.013 -0.038 -0.013 -0.013  0.037 
 0.071  0.021 -0.079  0.021  0.046 -0.029  0.121 -0.029 -0.029 -0.054  0.145  0.071  0.096 -0.004  0.295  0.170  0.021 -0.054 -0.029  0.245 -0.054 -0.054 -0.079  0.195  0.121 -0.004 -0.004  0.096 -0.054 -0.054 -0.029 -0.054 -0.004 -0.004  0.071  0.121  0.295 -0.029  0.021  0.021  0.071  0.071  0.021  0.943 -0.079  0.071 -0.004 -0.029  0.021 -0.029  0.071  0.071 -0.029  0.071 -0.079  0.046  0.046 -0.054  0.046 -0.079  0.046 -0.029 -0.029 -0.029  0.021 -0.054 -0.054 -0.029 -0.004 -0.029  0.096 -0.054 -0.029 -0.079  0.096  0.071  0.046 -0.054  0.121  0.071 -0.004  0.046 -0.029 -0.079 -0.004 -0.004  0.021 -0.004 -0.029 -0.004 -0.054 -0.029 -0.079  0.021  0.046 -0.004 -0.004 -0.029  0.021  0.071 
 0.117  0.166 -0.133  0.017  0.067  0.042  0.166 -0.108 -0.008 -0.008  0.391  0.191  0.092 -0.033  0.665  0.142  0.042 -0.033 -0.033  0.366 -0.108  0.017 -0.157  0.266  0.216  0.117  0.017  0.142  0.017 -0.083 -0.058  0.042  0.042  0.092  0.166  0.166  0.515 -0.083  0.166 -0.008  0.166  0.191 -0.008  0.864 -0.157  0.092 -0.008 -0.058  0.017 -0.033  0.067  0.092  0.067  0.067 -0.058  0.042 -0.033  0.042  0.092 -0.108  0.117 -0.083 -0.008 -0.008  0.042 -0.108 -0.058 -0.108 -0.058 -0.033  0.191 -0.033 -0.033  0.017  0.117  0.092  0.042 -0.058  0.191  0.291  0.092  0.067 -0.033 -0.157  0.042  0.042  0.042 -0.033  0.067  0.042 -0.058 -0.058 -0.083  0.042  0.042 -0.058 -0.033 -0.058 -0.008  0.067 
 0.159  0.209 -0.164  0.060  0.060  0.135  0.184 -0.140 -0.015  0.010  0.433  0.234  0.135 -0.040  0.683  0.184  0.060 -0.065  0.010  0.483 -0.115  0.060 -0.189  0.259  0.184  0.209  0.010  0.259  0.135 -0.015 -0.015  0.135  0.035  0.085  0.209  0.284  0.583 -0.065  0.184 -0.040  0.159  0.184  0.010  0.832 -0.189  0.085 -0.015 -0.090  0.135 -0.065  0.110  0.159  0.159  0.035 -0.090  0.010 -0.065  0.035  0.085 -0.140  0.085 -0.065  0.035  0.085  0.010 -0.090 -0.065 -0.090 -0.090 -0.040  0.209  0.010 -0.065  0.035  0.209  0.135  0.010 -0.040  0.159  0.359  0.060  0.135 -0.040 -0.189  0.010  0.060  0.035 -0.015  0.110  0.010 -0.090 -0.015 -0.090  0.010  0.010 -0.040 -0.040 -0.090 -0.065  0.035 
 0.254  0.254 -0.194  0.279  0.080  0.229  0.254 -0.045 -0.045  0.005  0.553  0.354  0.279 -0.020  0.727  0.204  0.130 -0.045 -0.045  0.578 -0.095  0.080 -0.219  0.254  0.154  0.229  0.080  0.304  0.204  0.105  0.030  0.204  0.005  0.080  0.354  0.304  0.603 -0.120  0.154 -0.095  0.204  0.229  0.055  0.777 -0.219  0.179  0.105  0.030  0.229 -0.070  0.080  0.179  0.179  0.030 -0.070 -0.020 -0.095  0.080  0.055 -0.194  0.055  0.030  0.030  0.080 -0.020 -0.045 -0.120 -0.095 -0.144 -0.070  0.179  0.005 -0.070 -0.020  0.229  0.154  0.030  0.005  0.179  0.404  0.080  0.229 -0.020 -0.219 -0.020  0.055 -0.020 -0.020  0.179  0.005 -0.144 -0.020 -0.045  0.005 -0.045  0.030 -0.020 -0.120 -0.120  0.005 
 0.331  0.282 -0.167  0.356  0.082  0.232  0.282 -0.042 -0.042 -0.017  0.556  0.356  0.356 -0.067  0.630  0.207  0.182 -0.017 -0.042  0.531 -0.067  0.057 -0.242  0.232  0.157  0.257  0.082  0.306  0.207  0.132  0.032  0.282 -0.017  0.082  0.406  0.406  0.580 -0.142  0.182 -0.042  0.182  0.232  0.082  0.755 -0.242  0.132  0.207  0.082  0.257 -0.092  0.082  0.207  0.182  0.007 -0.067 -0.017 -0.117  0.057  0.032 -0.167  0.032  0.007  0.057  0.032 -0.042  0.007 -0.142 -0.117 -0.167 -0.117  0.157  0.032 -0.042 -0.017  0.207  0.132  0.032 -0.042  0.232  0.356  0.082  0.207 -0.017 -0.242 -0.042  0.032 -0.042 -0.017  0.232 -0.017 -0.167  0.032 -0.067  0.007 -0.067  0.082 -0.067 -0.117 -0.142 -0.017 
 0.352  0.302 -0.146  0.352  0.153  0.302  0.352 -0.021 -0.021 -0.021  0.576  0.377  0.477 -0.071  0.601  0.302  0.278 -0.046 -0.071  0.527  0.053  0.103 -0.221  0.278  0.253  0.253  0.253  0.302  0.278  0.253  0.103  0.352 -0.046  0.103  0.452  0.402  0.527 -0.196  0.203  0.078  0.178  0.253  0.053  0.726 -0.246  0.203  0.253  0.228  0.327 -0.021  0.103  0.278  0.203  0.028 -0.096 -0.046 -0.121  0.053  0.078 -0.121  0.003  0.003  0.078  0.003 -0.046  0.028 -0.121 -0.171 -0.221 -0.171  0.128  0.053 -0.071 -0.046  0.228  0.078  0.053 -0.021  0.228  0.352  0.053  0.203 -0.021 -0.271 -0.021  0.028 -0.071  0.003  0.228 -0.046 -0.196  0.053 -0.046  0.028 -0.046  0.128 -0.096 -0.096 -0.171 -0.046 
 0.416  0.316 -0.157  0.341  0.216  0.366  0.366  0.017 -0.033  0.017  0.565  0.391  0.465 -0.083  0.565  0.291  0.291 -0.058 -0.083  0.515  0.092  0.117 -0.232  0.291  0.216  0.291  0.266  0.341  0.316  0.291  0.117  0.440 -0.058  0.092  0.440  0.440  0.515 -0.157  0.191  0.166  0.166  0.241  0.117  0.714 -0.257  0.216  0.291  0.316  0.366  0.017  0.142  0.291  0.166  0.142 -0.157 -0.058 -0.108  0.017  0.092 -0.133 -0.008  0.017  0.092 -0.033 -0.008  0.017 -0.083 -0.182 -0.207 -0.157  0.092  0.042 -0.083 -0.058  0.191  0.067  0.042 -0.008  0.216  0.341  0.067  0.166 -0.058 -0.282  0.017 -0.008 -0.083  0.017  0.216 -0.058 -0.182  0.067 -0.058  0.092 -0.008  0.142 -0.108 -0.108 -0.157 -0.083 
 0.481  0.357 -0.117  0.332  0.257  0.357  0.382  0.033 -0.042  0.008  0.531  0.407  0.481 -0.067  0.531  0.282  0.307 -0.067 -0.117  0.481  0.083  0.083 -0.191  0.282  0.232  0.282  0.332  0.332  0.357  0.382  0.157  0.481 -0.017  0.108  0.506  0.481  0.456 -0.142  0.182  0.207  0.157  0.232  0.157  0.706 -0.266  0.207  0.332  0.332  0.481  0.083  0.133  0.332  0.157  0.182 -0.191 -0.067 -0.092  0.008  0.108 -0.142 -0.017  0.008  0.083 -0.067 -0.017  0.058 -0.067 -0.142 -0.216 -0.117  0.058  0.083 -0.042 -0.042  0.207  0.008  0.058  0.008  0.232  0.332  0.083  0.157 -0.067 -0.291  0.008 -0.042 -0.067  0.008  0.207 -0.067 -0.191  0.133 -0.042  0.157  0.058  0.108 -0.117 -0.117 -0.142 -0.117 
 0.482  0.357 -0.116  0.307  0.283  0.382  0.357  0.008 -0.041  0.058  0.532  0.432  0.482 -0.091  0.482  0.283  0.332 -0.066 -0.116  0.482  0.058  0.083 -0.141  0.283  0.208  0.233  0.332  0.332  0.407  0.382  0.158  0.457 -0.016  0.083  0.507  0.507  0.457 -0.141  0.183  0.258  0.158  0.258  0.158  0.681 -0.266  0.208  0.307  0.407  0.532  0.083  0.133  0.332  0.108  0.208 -0.191 -0.066 -0.091  0.008  0.108 -0.141 -0.016  0.008  0.083 -0.041 -0.016  0.108 -0.066 -0.141 -0.216 -0.116  0.058  0.083 -0.041 -0.041  0.183 -0.016  0.008  0.008  0.183  0.307  0.058  0.108 -0.116 -0.315  0.008 -0.041 -0.016  0.058  0.183 -0.066 -0.191  0.133 -0.041  0.158  0.058  0.133 -0.116 -0.116 -0.116 -0.116 
 0.504  0.355 -0.119  0.330  0.380  0.429  0.355  0.031 -0.019  0.031  0.529  0.405  0.454 -0.094  0.479  0.280  0.305 -0.069 -0.119  0.479  0.056  0.081 -0.119  0.355  0.180  0.230  0.429  0.355  0.405  0.405  0.155  0.454 -0.044  0.106  0.504  0.504  0.454 -0.143  0.180  0.280  0.155  0.255  0.155  0.679 -0.268  0.205  0.355  0.479  0.529  0.131  0.131  0.330  0.081  0.180 -0.193 -0.069 -0.094  0.006  0.106 -0.119 -0.019  0.006  0.056 -0.044 -0.019  0.081 -0.069 -0.143 -0.218 -0.119  0.056  0.081 -0.044 -0.044  0.180 -0.044  0.006 -0.019  0.180  0.205  0.056  0.031 -0.168 -0.318  0.006 -0.044 -0.019  0.081  0.180 -0.069 -0.193  0.131 -0.069  0.155  0.056  0.131 -0.044 -0.119 -0.119 -0.094 
 0.506  0.356 -0.117  0.331  0.406  0.431  0.356  0.032  0.007  0.032  0.531  0.406  0.456 -0.092  0.481  0.282  0.306 -0.067 -0.117  0.456  0.057  0.082 -0.092  0.356  0.182  0.232  0.456  0.356  0.406  0.406  0.157  0.456 -0.042  0.107  0.506  0.506  0.456 -0.142  0.157  0.282  0.157  0.232  0.157  0.680 -0.267  0.207  0.356  0.481  0.531  0.132  0.132  0.331  0.057  0.182 -0.192 -0.067 -0.092  0.007  0.107 -0.117  0.007  0.007  0.057 -0.042 -0.017  0.057 -0.067 -0.142 -0.217 -0.117  0.032  0.082 -0.042 -0.067  0.182 -0.042  0.007 -0.017  0.182  0.207  0.057  0.032 -0.167 -0.316  0.007 -0.042 -0.017  0.082  0.182 -0.067 -0.192  0.132 -0.067  0.157  0.057  0.132 -0.042 -0.117 -0.117 -0.092 
 0.480  0.355 -0.118  0.305  0.505  0.455  0.355  0.056  0.081  0.031  0.505  0.430  0.480 -0.093  0.380  0.281  0.281 -0.068 -0.118  0.455  0.081  0.081 -0.068  0.405  0.106  0.206  0.480  0.355  0.430  0.380  0.156  0.455 -0.043  0.131  0.530  0.505  0.430 -0.168  0.156  0.405  0.181  0.231  0.106  0.679 -0.218  0.181  0.380  0.480  0.530  0.181  0.156  0.281  0.056  0.181 -0.193 -0.093 -0.093  0.006  0.081 -0.118  0.031  0.006  0.056 -0.068 -0.018  0.056 -0.068 -0.143 -0.218 -0.143  0.006  0.081 -0.018 -0.093  0.156 -0.043 -0.018 -0.043  0.156  0.106  0.056  0.006 -0.193 -0.317  0.006 -0.018 -0.068  0.106  0.206 -0.068 -0.193  0.106 -0.093  0.181  0.056  0.106 -0.018 -0.068 -0.093 -0.118 
 0.455  0.355 -0.118  0.305  0.530  0.455  0.355  0.081  0.131  0.056  0.505  0.430  0.480 -0.093  0.330  0.281  0.281 -0.068 -0.093  0.455  0.081  0.106 -0.018  0.505  0.106  0.206  0.480  0.380  0.430  0.380  0.181  0.455 -0.043  0.131  0.555  0.505  0.430 -0.168  0.181  0.405  0.181  0.231  0.081  0.679 -0.193  0.181  0.380  0.480  0.530  0.256  0.206  0.281  0.031  0.181 -0.193 -0.093 -0.093 -0.018  0.081 -0.118  0.081 -0.018  0.081 -0.043 -0.018  0.056 -0.043 -0.118 -0.218 -0.143  0.006  0.081 -0.018 -0.093  0.156 -0.018 -0.018  0.006  0.156  0.056  0.081 -0.018 -0.243 -0.317  0.006 -0.018 -0.068  0.106  0.206 -0.068 -0.168  0.081 -0.093  0.181  0.031  0.106  0.006 -0.043 -0.093 -0.118 
 0.452  0.353 -0.096  0.303  0.552  0.452  0.353  0.079  0.253  0.054  0.477  0.427  0.477 -0.096  0.328  0.278  0.278 -0.021 -0.096  0.452  0.054  0.104  0.004  0.527  0.079  0.228  0.527  0.403  0.452  0.328  0.203  0.378 -0.021  0.129  0.527  0.502  0.427 -0.145  0.178  0.403  0.178  0.228  0.079  0.677 -0.145  0.178  0.403  0.477  0.527  0.278  0.228  0.328  0.004  0.178 -0.195 -0.046 -0.096 -0.021  0.079 -0.096  0.079 -0.021  0.079 -0.021  0.004  0.054 -0.046 -0.096 -0.220 -0.145  0.029  0.104 -0.021 -0.096  0.178 -0.021  0.029  0.054  0.178  0.029  0.079 -0.021 -0.245 -0.320  0.004 -0.046 -0.046  0.104  0.253 -0.096 -0.121  0.079 -0.096  0.178  0.029  0.129  0.004 -0.046 -0.096 -0.121 
 0.476  0.351 -0.097  0.301  0.551  0.426  0.351  0.077  0.277  0.052  0.451  0.426  0.476 -0.097  0.326  0.277  0.277 -0.022 -0.097  0.451  0.027  0.127  0.002  0.575  0.102  0.227  0.526  0.401  0.476  0.351  0.227  0.376  0.002  0.152  0.526  0.501  0.426 -0.147  0.177  0.426  0.127  0.227  0.077  0.675 -0.147  0.177  0.401  0.501  0.526  0.301  0.277  0.351  0.002  0.152 -0.197 -0.022 -0.122 -0.022  0.077 -0.097  0.102 -0.022  0.077 -0.022  0.027  0.052 -0.047 -0.097 -0.197 -0.147  0.002  0.077 -0.022 -0.097  0.152  0.002  0.027  0.027  0.202  0.027  0.102 -0.047 -0.222 -0.321  0.002 -0.022 -0.047  0.127  0.301 -0.097 -0.122  0.077 -0.072  0.177  0.002  0.152  0.002 -0.047 -0.072 -0.122 
 0.472  0.347 -0.101  0.297  0.571  0.422  0.347  0.098  0.273  0.048  0.447  0.422  0.497 -0.101  0.322  0.297  0.248 -0.026 -0.101  0.447  0.023  0.148 -0.001  0.596  0.098  0.273  0.522  0.422  0.472  0.322  0.223  0.322 -0.001  0.148  0.497  0.497  0.422 -0.151  0.173  0.447  0.123  0.223  0.073  0.671 -0.126  0.198  0.397  0.497  0.522  0.347  0.273  0.347  0.023  0.123 -0.201 -0.026 -0.126 -0.026  0.073 -0.126  0.123 -0.051  0.098 -0.026  0.048  0.048 -0.076 -0.101 -0.176 -0.151  0.048  0.098 -0.026 -0.101  0.148 -0.001  0.023  0.048  0.198 -0.001  0.098 -0.051 -0.226 -0.325 -0.026 -0.026 -0.026  0.123  0.322 -0.101 -0.126  0.073 -0.076  0.173 -0.001  0.148 -0.001 -0.051 -0.101 -0.126 
 0.474  0.349 -0.099  0.324  0.549  0.424  0.349  0.100  0.275  0.050  0.449  0.424  0.499 -0.099  0.324  0.299  0.250 -0.024 -0.099  0.449  0.000  0.150  0.000  0.598  0.100  0.299  0.524  0.424  0.474  0.299  0.200  0.324  0.000  0.125  0.499  0.499  0.424 -0.149  0.175  0.449  0.125  0.250  0.075  0.673 -0.124  0.200  0.399  0.474  0.524  0.324  0.275  0.324  0.025  0.100 -0.199 -0.024 -0.124 -0.024  0.075 -0.124  0.125 -0.049  0.100 -0.024  0.025  0.050 -0.074 -0.099 -0.174 -0.149  0.050  0.100  0.000 -0.049  0.150  0.000  0.025  0.050  0.200  0.000  0.125 -0.049 -0.249 -0.323 -0.024 -0.049 -0.024  0.125  0.324 -0.099 -0.124  0.075 -0.074  0.175  0.000  0.150  0.000 -0.049 -0.124 -0.124 
 0.474  0.349 -0.074  0.324  0.549  0.424  0.374  0.100  0.250  0.050  0.474  0.424  0.499 -0.099  0.299  0.299  0.225 -0.049 -0.099  0.449  0.000  0.125  0.000  0.623  0.050  0.299  0.524  0.424  0.449  0.299  0.200  0.324  0.025  0.150  0.499  0.499  0.424 -0.149  0.175  0.449  0.125  0.225  0.075  0.673 -0.124  0.200  0.399  0.424  0.524  0.324  0.275  0.324  0.025  0.050 -0.199 -0.024 -0.124 -0.024  0.100 -0.124  0.125 -0.049  0.150 -0.024  0.025  0.050 -0.074 -0.099 -0.174 -0.174  0.050  0.100  0.025 -0.049  0.150 -0.024  0.075  0.050  0.175  0.000  0.125 -0.049 -0.249 -0.323 -0.024 -0.074 -0.024  0.150  0.299 -0.099 -0.124  0.075 -0.074  0.175  0.000  0.225  0.000 -0.049 -0.124 -0.124 
 0.496  0.372 -0.077  0.347  0.496  0.446  0.397  0.123  0.098  0.098  0.422  0.446  0.446 -0.052  0.347  0.222  0.222 -0.052 -0.151  0.446 -0.052  0.172 -0.077  0.471  0.048  0.297  0.546  0.422  0.446  0.247  0.222  0.372 -0.002  0.147  0.397  0.422  0.347 -0.077  0.098  0.446  0.073  0.272  0.023  0.596 -0.077  0.222  0.347  0.347  0.471  0.147  0.222  0.322  0.048 -0.027 -0.151 -0.077 -0.102 -0.027  0.147 -0.102  0.023 -0.077  0.123  0.048  0.023  0.098 -0.027 -0.077 -0.151 -0.151 -0.002  0.172  0.073 -0.002  0.147 -0.002 -0.002 -0.002  0.147 -0.002  0.098 -0.002 -0.176 -0.251 -0.027 -0.127 -0.052  0.123  0.147 -0.052 -0.102  0.098 -0.002  0.222 -0.052  0.098 -0.127 -0.077 -0.052 -0.077 
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 0.004  0.004 -0.020  0.004 -0.020  0.104  0.004  0.004 -0.020  0.029  0.004  0.029  0.054  0.004  0.004  0.004  0.029 -0.020 -0.020  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004  0.079  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.029  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029  0.004  0.054 -0.020 
 0.004  0.004 -0.021  0.004 -0.021  0.104  0.004  0.004 -0.021  0.029  0.004  0.029  0.054  0.004  0.004  0.004  0.029 -0.021 -0.021  0.054  0.004 -0.021  0.004 -0.021 -0.021  0.029  0.004 -0.021  0.004 -0.021 -0.021 -0.021  0.004  0.029 -0.021  0.004  0.004 -0.021 -0.021  0.004  0.004  0.104  0.029  0.029 -0.021 -0.021 -0.021  0.004  0.029  0.004 -0.021  0.004  0.029  0.004 -0.021  0.004 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021 -0.021 -0.021  0.004 -0.021  0.029  0.004 -0.021  0.004 -0.021  0.029 -0.021  0.004  0.004 -0.021  0.004 -0.021 -0.021  0.054  0.004  0.029  0.004  0.004  0.029  0.004 -0.021  0.004  0.004 -0.021  0.004 -0.021  0.004  0.029 -0.021  0.029  0.004  0.054 -0.021 
 0.001  0.001 -0.023  0.001 -0.023  0.176  0.001  0.001 -0.023  0.026  0.001  0.026  0.051  0.001  0.001  0.001  0.026 -0.023 -0.023  0.051  0.001 -0.023  0.001 -0.023 -0.023  0.051  0.001  0.026  0.001 -0.023 -0.023 -0.023  0.001  0.026 -0.023  0.001  0.001 -0.023 -0.023  0.001  0.001  0.126  0.026  0.026 -0.023 -0.023 -0.023  0.001  0.026  0.001 -0.023  0.076  0.026  0.001 -0.023  0.026 -0.023 -0.023  0.001 -0.023 -0.023  0.001 -0.023 -0.023 -0.023  0.001 -0.023  0.026  0.001 -0.023  0.001 -0.023  0.026 -0.023  0.026  0.001 -0.023  0.001 -0.023  0.001  0.051  0.001  0.026  0.001  0.001  0.051  0.001 -0.023  0.001  0.001 -0.023  0.001 -0.023  0.001  0.051 -0.023  0.026  0.001  0.051 -0.023 
-0.012  0.013 -0.037  0.013 -0.037  0.486  0.013  0.013 -0.012  0.063 -0.012  0.138  0.162  0.013  0.013 -0.012  0.063 -0.037 -0.037  0.187  0.038 -0.037 -0.012 -0.012 -0.012  0.088  0.013  0.088  0.013 -0.037 -0.012 -0.037 -0.012  0.013  0.013  0.013  0.013 -0.037 -0.037 -0.012 -0.012  0.187  0.013  0.063 -0.037 -0.012 -0.037  0.013  0.013  0.038 -0.037  0.187  0.013 -0.012 -0.037  0.038 -0.037 -0.037 -0.012 -0.012 -0.037 -0.012 -0.037 -0.037 -0.037  0.013 -0.037  0.038 -0.012 -0.037  0.038 -0.037  0.038 -0.037  0.013  0.038 -0.037 -0.012 -0.037 -0.012  0.063 -0.012  0.038 -0.012 -0.012  0.038 -0.012 -0.037 -0.012  0.013 -0.012 -0.012 -0.012  0.013  0.038 -0.012  0.063 -0.012  0.063 -0.037 
-0.046  0.003 -0.046  0.053 -0.021  0.676  0.028 -0.021 -0.046  0.078  0.078  0.327  0.302  0.003  0.028 -0.046  0.103 -0.071 -0.021  0.327  0.078 -0.071 -0.021  0.103  0.028  0.203  0.003  0.153  0.028  0.053  0.003 -0.046 -0.046  0.003  0.053  0.003  0.228 -0.021 -0.021 -0.046 -0.046  0.552  0.053  0.128 -0.071  0.003 -0.071  0.128  0.028  0.078 -0.046  0.402  0.028  0.053 -0.046  0.103 -0.046 -0.021 -0.046 -0.046 -0.021  0.003 -0.021 -0.071 -0.046  0.028 -0.046  0.028 -0.046 -0.071  0.078 -0.021  0.028  0.003  0.053  0.028 -0.021 -0.021  0.053  0.053  0.028 -0.021  0.003 -0.046  0.003  0.178  0.053  0.003 -0.046  0.028 -0.046  0.028  0.003  0.003  0.128 -0.021  0.078 -0.021  0.028 -0.046 
 0.062  0.012 -0.038  0.037 -0.063  0.884  0.037 -0.063  0.037  0.112  0.037  0.585  0.435 -0.063  0.037 -0.038  0.211 -0.138 -0.088  0.610  0.112 -0.138 -0.063  0.286  0.137  0.286  0.087  0.311  0.112  0.087  0.137 -0.013 -0.038 -0.013  0.037  0.087  0.411 -0.013  0.037  0.161 -0.063  0.784  0.137  0.236 -0.063  0.037 -0.113  0.112  0.137  0.087 -0.013  0.710  0.037  0.137 -0.038  0.186 -0.088  0.037  0.112 -0.088 -0.013  0.037  0.112 -0.138 -0.038  0.037 -0.088 -0.038 -0.088 -0.113  0.062 -0.013  0.087 -0.063  0.211  0.012 -0.038 -0.013  0.012  0.037  0.112 -0.013  0.012 -0.063 -0.038  0.236  0.012 -0.038 -0.063 -0.013 -0.088  0.062 -0.063  0.062  0.311 -0.038  0.012 -0.013  0.087 -0.113 
 0.070  0.045 -0.079  0.045 -0.054  0.843  0.120 -0.079  0.045  0.070  0.095  0.593  0.544 -0.054  0.095 -0.029  0.245 -0.179 -0.129  0.693  0.095 -0.129 -0.079  0.519  0.120  0.319  0.045  0.344  0.145  0.095  0.145  0.070 -0.054  0.020 -0.004  0.095  0.544 -0.004  0.070  0.270 -0.079  0.818  0.170  0.369 -0.079  0.070 -0.129  0.170  0.220  0.170  0.045  0.718  0.045  0.120 -0.054  0.170 -0.129  0.020  0.070 -0.129 -0.004 -0.004  0.195 -0.179 -0.029  0.045 -0.104 -0.054 -0.104 -0.129  0.095 -0.029  0.045 -0.079  0.195  0.020  0.020 -0.029  0.070  0.020  0.120 -0.054  0.020 -0.104 -0.004  0.220  0.045  0.045 -0.054 -0.004 -0.079  0.070 -0.079  0.095  0.319  0.045  0.020  0.045  0.120 -0.079 
 0.234  0.034 -0.115  0.059  0.009  0.757  0.284 -0.115  0.134  0.059  0.184  0.607  0.657 -0.040  0.084  0.034  0.284 -0.240 -0.115  0.732  0.084 -0.065 -0.065  0.607  0.134  0.259  0.059  0.483  0.134  0.234  0.109  0.109  0.009 -0.040 -0.065  0.308  0.682 -0.040  0.084  0.408 -0.065  0.782  0.159  0.558 -0.090  0.084 -0.090  0.358  0.284  0.259  0.134  0.707  0.059  0.159 -0.065  0.184 -0.115 -0.040  0.059 -0.140  0.034 -0.040  0.209 -0.165  0.034  0.009 -0.040 -0.115 -0.140 -0.140  0.159 -0.065  0.059 -0.065  0.259  0.034  0.009  0.009  0.034  0.009  0.209 -0.040  0.009 -0.115  0.034  0.159  0.059  0.134 -0.040 -0.015 -0.090  0.034 -0.090  0.084  0.358  0.134 -0.015  0.059  0.134 -0.140 
 0.239  0.015 -0.159  0.040  0.015  0.638  0.389 -0.110  0.164  0.065  0.289  0.588  0.638 -0.085  0.115  0.065  0.289 -0.259 -0.035  0.712  0.115 -0.060 -0.010  0.613  0.140  0.239  0.040  0.538  0.140  0.314  0.115  0.140  0.015  0.015 -0.085  0.314  0.663 -0.060  0.065  0.488 -0.060  0.762  0.189  0.563 -0.110  0.090 -0.085  0.414  0.414  0.339  0.140  0.663  0.065  0.140 -0.085  0.189 -0.060 -0.035  0.090 -0.110  0.040 -0.060  0.189 -0.159  0.015  0.015 -0.035 -0.085 -0.135 -0.159  0.140 -0.010  0.115 -0.085  0.289 -0.010  0.015 -0.010  0.090  0.015  0.189 -0.060  0.015 -0.159  0.015  0.214  0.040  0.164  0.040  0.040 -0.060 -0.010 -0.060  0.115  0.339  0.115  0.040  0.015  0.040 -0.110 
 0.429  0.056 -0.143  0.056  0.056  0.529  0.429 -0.094  0.180  0.106  0.330  0.529  0.629 -0.094  0.230  0.081  0.280 -0.218 -0.019  0.679  0.155 -0.019  0.006  0.604  0.106  0.205  0.081  0.504  0.255  0.405  0.180  0.205  0.031  0.081  0.006  0.429  0.604 -0.094  0.131  0.479 -0.069  0.679  0.230  0.579 -0.143  0.180  0.006  0.554  0.529  0.454  0.155  0.529  0.056  0.180 -0.094  0.180 -0.069  0.006  0.131 -0.069  0.081 -0.044  0.180 -0.193  0.031 -0.019 -0.044 -0.119 -0.119 -0.143  0.180  0.081  0.131 -0.069  0.280 -0.019 -0.019  0.056  0.106  0.006  0.205 -0.094 -0.044 -0.143 -0.044  0.205  0.006  0.205  0.155  0.056 -0.069 -0.044 -0.094  0.131  0.305  0.131  0.081  0.031  0.006 -0.094 
 0.444  0.095 -0.079  0.045  0.070  0.494  0.419 -0.079  0.170  0.120  0.344  0.519  0.593 -0.104  0.270  0.145  0.270 -0.229 -0.004  0.668  0.145  0.045  0.045  0.618  0.095  0.245  0.145  0.494  0.245  0.419  0.170  0.270 -0.029  0.070  0.045  0.419  0.593 -0.104  0.120  0.519 -0.029  0.618  0.245  0.593 -0.154  0.220  0.020  0.593  0.568  0.469  0.220  0.494  0.070  0.270 -0.104  0.170 -0.054  0.020  0.170 -0.079  0.120 -0.054  0.170 -0.204  0.045  0.020 -0.029 -0.104 -0.154 -0.129  0.195  0.120  0.095 -0.054  0.270 -0.029 -0.004  0.120  0.145 -0.004  0.245 -0.079 -0.054 -0.129 -0.004  0.120 -0.004  0.195  0.195  0.020 -0.054 -0.004 -0.079  0.095  0.270  0.120  0.095  0.020 -0.054 -0.104 
 0.458  0.159 -0.090  0.110  0.135  0.458  0.483 -0.040  0.184  0.110  0.359  0.508  0.533 -0.115  0.334  0.209  0.259 -0.189  0.010  0.583  0.159  0.060  0.085  0.608  0.060  0.234  0.259  0.483  0.334  0.409  0.159  0.259 -0.040  0.060  0.135  0.508  0.483 -0.115  0.135  0.558 -0.015  0.583  0.259  0.608 -0.164  0.259  0.110  0.583  0.583  0.433  0.234  0.433  0.060  0.259 -0.164  0.209 -0.015 -0.015  0.159 -0.115  0.184 -0.065  0.184 -0.140  0.010  0.035 -0.040 -0.090 -0.164 -0.164  0.209  0.110  0.110 -0.065  0.259 -0.040  0.010  0.135  0.110 -0.015  0.234 -0.115 -0.065 -0.164 -0.040  0.110  0.035  0.209  0.184 -0.015 -0.090  0.035 -0.090  0.135  0.209  0.085  0.085  0.010 -0.040 -0.115 
 0.458  0.159 -0.090  0.159  0.159  0.458  0.483 -0.040  0.184  0.134  0.383  0.433  0.533 -0.115  0.333  0.234  0.234 -0.190  0.009  0.582  0.134  0.059  0.084  0.607  0.059  0.234  0.284  0.483  0.333  0.408  0.109  0.259 -0.040  0.059  0.184  0.508  0.483 -0.115  0.159  0.558 -0.015  0.558  0.234  0.607 -0.140  0.308  0.134  0.558  0.582  0.408  0.209  0.358  0.059  0.209 -0.165  0.209 -0.015 -0.040  0.109 -0.115  0.209 -0.065  0.159 -0.115  0.009  0.059 -0.040 -0.090 -0.115 -0.165  0.234  0.159  0.109 -0.065  0.259 -0.015  0.009  0.134  0.134  0.009  0.209 -0.115 -0.065 -0.165 -0.065  0.109  0.034  0.159  0.159 -0.015 -0.090  0.034 -0.090  0.134  0.184  0.084  0.084 -0.040 -0.065 -0.090 
 0.426  0.201 -0.098  0.226  0.276  0.450  0.475  0.052  0.176  0.176  0.401  0.376  0.525 -0.123  0.376  0.226  0.226 -0.147  0.002  0.550  0.102  0.151  0.052  0.600  0.027  0.276  0.326  0.475  0.376  0.401  0.127  0.276 -0.048  0.077  0.301  0.475  0.426 -0.147  0.176  0.575  0.002  0.500  0.251  0.625 -0.123  0.351  0.276  0.550  0.575  0.401  0.201  0.351  0.077  0.201 -0.172  0.201  0.002 -0.048  0.127 -0.123  0.251 -0.073  0.151 -0.048  0.002  0.077 -0.023 -0.073 -0.123 -0.172  0.226  0.151  0.102 -0.073  0.276  0.002  0.027  0.151  0.127  0.002  0.176 -0.073 -0.048 -0.172 -0.073  0.151  0.002  0.127  0.151  0.002 -0.073  0.052 -0.098  0.127  0.127  0.102  0.102 -0.048 -0.098 -0.098 
 0.426  0.252 -0.097  0.227  0.301  0.426  0.476  0.052  0.202  0.177  0.351  0.277  0.501 -0.097  0.376  0.252  0.177 -0.147  0.002  0.551  0.102  0.152  0.052  0.600  0.002  0.301  0.326  0.426  0.426  0.401  0.177  0.252 -0.072  0.077  0.351  0.476  0.451 -0.147  0.127  0.551  0.077  0.476  0.227  0.625 -0.097  0.401  0.351  0.501  0.551  0.401  0.252  0.326  0.052  0.177 -0.172  0.227  0.002  0.002  0.127 -0.122  0.252 -0.072  0.127 -0.047  0.027  0.077 -0.022 -0.097 -0.147 -0.172  0.227  0.177  0.102 -0.097  0.252  0.027  0.027  0.102  0.102  0.002  0.177 -0.072 -0.122 -0.172  0.002  0.152  0.002  0.127  0.177 -0.072 -0.072  0.052 -0.072  0.127  0.127  0.102  0.127 -0.072 -0.122 -0.097 
 0.398  0.273 -0.101  0.223  0.423  0.398  0.497  0.099  0.223  0.198  0.348  0.273  0.497 -0.076  0.373  0.298  0.173 -0.150  0.024  0.547  0.074  0.173  0.074  0.597 -0.001  0.323  0.298  0.398  0.423  0.373  0.223  0.248 -0.126  0.074  0.423  0.472  0.447 -0.126  0.124  0.547  0.099  0.472  0.198  0.622 -0.076  0.423  0.373  0.497  0.522  0.398  0.248  0.323  0.049  0.074 -0.175  0.223 -0.051 -0.001  0.124 -0.126  0.273 -0.076  0.124 -0.026  0.049  0.099 -0.051 -0.101 -0.150 -0.175  0.198  0.173  0.099 -0.101  0.248  0.024 -0.001  0.099  0.099 -0.001  0.148 -0.076 -0.150 -0.200 -0.001  0.198 -0.026  0.124  0.173 -0.051 -0.101  0.049 -0.051  0.124  0.099  0.124  0.124 -0.076 -0.150 -0.101 
 0.398  0.298 -0.125  0.274  0.423  0.398  0.473  0.124  0.224  0.174  0.348  0.249  0.498 -0.075  0.373  0.298  0.124 -0.175 -0.000  0.548  0.049  0.174  0.074  0.597 -0.000  0.348  0.323  0.398  0.423  0.373  0.224  0.249 -0.125  0.074  0.448  0.473  0.423 -0.150  0.149  0.548  0.124  0.473  0.174  0.622 -0.075  0.423  0.398  0.498  0.548  0.423  0.274  0.298  0.049  0.074 -0.200  0.174 -0.100  0.024  0.124 -0.125  0.298 -0.075  0.074 -0.025  0.024  0.124 -0.050 -0.100 -0.150 -0.175  0.199  0.149  0.124 -0.100  0.274 -0.000 -0.000  0.074  0.074 -0.000  0.149 -0.050 -0.150 -0.225 -0.000  0.199 -0.025  0.124  0.199 -0.075 -0.100  0.049 -0.075  0.124  0.099  0.124  0.124 -0.075 -0.150 -0.100 
 0.399  0.299 -0.100  0.299  0.424  0.374  0.473  0.125  0.224  0.174  0.349  0.224  0.498 -0.075  0.374  0.399  0.125 -0.174  0.000  0.548  0.000  0.174  0.075  0.598  0.000  0.349  0.324  0.349  0.424  0.399  0.249  0.224 -0.125  0.100  0.498  0.498  0.424 -0.174  0.125  0.523  0.125  0.424  0.100  0.648 -0.075  0.424  0.448  0.498  0.548  0.424  0.299  0.249  0.050  0.050 -0.174  0.149 -0.100  0.000  0.125 -0.125  0.299 -0.050  0.075 -0.025  0.025  0.125 -0.050 -0.100 -0.149 -0.199  0.149  0.100  0.125 -0.075  0.249  0.000 -0.025  0.075  0.075  0.025  0.100  0.000 -0.174 -0.224  0.025  0.199 -0.050  0.125  0.199 -0.075 -0.125  0.000 -0.075  0.149  0.075  0.174  0.125 -0.100 -0.149 -0.125 
 0.398  0.298 -0.125  0.323  0.423  0.373  0.448  0.124  0.224  0.174  0.348  0.224  0.523 -0.075  0.348  0.398  0.124 -0.175 -0.000  0.523 -0.025  0.174  0.074  0.572 -0.000  0.348  0.323  0.373  0.423  0.423  0.249  0.249 -0.150  0.099  0.548  0.498  0.423 -0.175  0.099  0.498  0.099  0.423  0.099  0.647 -0.075  0.398  0.448  0.498  0.548  0.423  0.298  0.249  0.024  0.024 -0.175  0.174 -0.100 -0.000  0.124 -0.125  0.274 -0.050  0.074 -0.000  0.024  0.099 -0.075 -0.100 -0.150 -0.200  0.124  0.099  0.124 -0.075  0.249 -0.000 -0.025  0.099  0.074  0.024  0.074 -0.000 -0.175 -0.225  0.024  0.199 -0.050  0.124  0.199 -0.075 -0.125 -0.000 -0.075  0.149  0.074  0.174  0.149 -0.100 -0.150 -0.125 
 0.398  0.323 -0.101  0.323  0.423  0.348  0.447  0.124  0.223  0.173  0.373  0.223  0.522 -0.051  0.348  0.423  0.124 -0.175 -0.026  0.522 -0.026  0.173  0.074  0.547 -0.001  0.398  0.323  0.373  0.447  0.423  0.273  0.248 -0.150  0.099  0.597  0.472  0.423 -0.175  0.099  0.472  0.099  0.398  0.099  0.622 -0.076  0.398  0.472  0.497  0.547  0.447  0.323  0.273  0.024 -0.001 -0.175  0.148 -0.126 -0.001  0.099 -0.126  0.273 -0.026  0.074  0.024  0.024  0.099 -0.076 -0.076 -0.150 -0.200  0.099  0.099  0.099 -0.076  0.223 -0.001 -0.051  0.099  0.074  0.024  0.074 -0.026 -0.175 -0.225  0.024  0.173 -0.026  0.124  0.223 -0.076 -0.150 -0.001 -0.076  0.173  0.074  0.198  0.173 -0.101 -0.126 -0.126 
 0.395  0.395 -0.053  0.345  0.345  0.420  0.470  0.096  0.196  0.171  0.370  0.246  0.470 -0.053  0.345  0.370  0.146 -0.153 -0.028  0.495 -0.003  0.196  0.071  0.495  0.021  0.295  0.295  0.345  0.420  0.271  0.246  0.196 -0.128  0.071  0.569  0.420  0.345 -0.153  0.071  0.420  0.046  0.370  0.071  0.569 -0.103  0.345  0.470  0.395  0.470  0.445  0.196  0.196 -0.003 -0.003 -0.128  0.071 -0.128  0.021  0.096 -0.128  0.146 -0.028  0.021 -0.003  0.046  0.096 -0.053 -0.178 -0.178 -0.128  0.146  0.021  0.046 -0.103  0.121  0.071 -0.028  0.046  0.071  0.021  0.071 -0.028 -0.153 -0.178  0.071  0.096  0.021  0.146  0.146 -0.103 -0.178 -0.028 -0.003  0.071 -0.028  0.146  0.121 -0.078 -0.103 -0.103 
 0.307  0.382 -0.042  0.282  0.407  0.506  0.382  0.108  0.083  0.157  0.307  0.207  0.282  0.008  0.257  0.257  0.133 -0.092 -0.142  0.456 -0.017  0.182 -0.042  0.456  0.008  0.182  0.332  0.357  0.382  0.232  0.257  0.207 -0.042  0.058  0.382  0.407  0.232 -0.117 -0.017  0.407  0.083  0.357  0.083  0.481 -0.092  0.257  0.456  0.431  0.481  0.357  0.133  0.182  0.058 -0.042 -0.067 -0.017 -0.092  0.058  0.157 -0.067  0.133  0.008  0.033  0.033  0.008  0.033 -0.042 -0.142 -0.142 -0.067  0.108  0.058  0.008 -0.067  0.108  0.058 -0.017 -0.067  0.008  0.033  0.083 -0.042 -0.117 -0.166  0.058 -0.042  0.033  0.157  0.033 -0.042 -0.117  0.058  0.008  0.083 -0.067  0.133 -0.017 -0.042 -0.117 -0.092 
 0.249  0.398 -0.025  0.224  0.423  0.498  0.373  0.124  0.049  0.149  0.249  0.174  0.298 -0.000  0.224  0.224  0.124 -0.075 -0.125  0.448 -0.000  0.174 -0.025  0.448 -0.000  0.124  0.298  0.348  0.373  0.249  0.199  0.174 -0.025  0.074  0.348  0.398  0.199 -0.100 -0.050  0.373  0.099  0.348  0.099  0.498 -0.100  0.274  0.448  0.348  0.523  0.298  0.099  0.124  0.074 -0.050 -0.075 -0.025 -0.100  0.074  0.174 -0.050  0.074  0.024  0.049  0.024  0.024  0.049 -0.075 -0.125 -0.125 -0.050  0.149  0.074  0.024 -0.050  0.024  0.074 -0.000 -0.075 -0.000  0.024  0.074 -0.050 -0.125 -0.150 -0.000 -0.075 -0.000  0.149  0.024 -0.025 -0.100  0.074 -0.000  0.049 -0.050  0.099 -0.075 -0.025 -0.125 -0.075 
 0.220  0.394 -0.029  0.220  0.419  0.519  0.344  0.145  0.045  0.145  0.170  0.170  0.319  0.020  0.170  0.170  0.045 -0.054 -0.129  0.419  0.020  0.170 -0.029  0.469 -0.004  0.120  0.294  0.344  0.294  0.245  0.170  0.195 -0.004 -0.004  0.245  0.419  0.170 -0.104 -0.029  0.344  0.045  0.344  0.120  0.444 -0.079  0.270  0.444  0.294  0.494  0.294  0.095  0.120  0.095 -0.054 -0.054 -0.054 -0.079  0.045  0.120 -0.054 -0.004  0.020  0.045 -0.004  0.020  0.045 -0.079 -0.104 -0.104 -0.054  0.145  0.020 -0.004 -0.029 -0.054  0.070 -0.004 -0.079 -0.004 -0.004  0.045 -0.054 -0.129 -0.129 -0.029 -0.054 -0.054  0.170  0.020 -0.004 -0.079  0.095 -0.029  0.020 -0.054  0.120 -0.079 -0.054 -0.104 -0.079 
 0.127  0.376 -0.023  0.226  0.426  0.500  0.351  0.151  0.027  0.151  0.151  0.176  0.326  0.027  0.151  0.127  0.052 -0.073 -0.123  0.450  0.027  0.176 -0.023  0.475  0.002  0.127  0.301  0.376  0.226  0.251  0.127  0.176  0.002 -0.023  0.251  0.450  0.201 -0.098 -0.023  0.351  0.027  0.351  0.102  0.426 -0.073  0.251  0.450  0.226  0.500  0.276  0.052  0.127  0.102 -0.073 -0.048 -0.048 -0.073  0.027  0.127 -0.048  0.002  0.027  0.052  0.002  0.002  0.052 -0.073 -0.098 -0.098 -0.048  0.127  0.002  0.002 -0.023 -0.048  0.077  0.002 -0.073  0.002  0.002  0.052 -0.048 -0.123 -0.123 -0.048 -0.048 -0.048  0.176 -0.023  0.002 -0.073  0.102 -0.023  0.027 -0.048  0.127 -0.073 -0.048 -0.073 -0.073 
 0.140  0.339 -0.009  0.190  0.439  0.514  0.339  0.115  0.015  0.165  0.115  0.140  0.364  0.015  0.140  0.065  0.065 -0.059 -0.109  0.464  0.015  0.190  0.015  0.439  0.015  0.140  0.289  0.414  0.190  0.240  0.140  0.165  0.015 -0.034  0.240  0.464  0.215 -0.084 -0.009  0.240  0.015  0.364  0.115  0.289 -0.034  0.240  0.464  0.165  0.464  0.240  0.065  0.090  0.065 -0.059 -0.034 -0.034 -0.059  0.040  0.140 -0.034  0.040  0.015  0.065  0.015  0.015  0.065 -0.084 -0.084 -0.084 -0.059  0.040 -0.009  0.015 -0.034 -0.034  0.115 -0.009 -0.059 -0.009  0.015  0.015 -0.059 -0.109 -0.109 -0.059 -0.034 -0.059  0.165 -0.009  0.015 -0.059  0.090 -0.034  0.015 -0.034  0.140 -0.059 -0.034 -0.059 -0.084 
 0.145  0.294 -0.004  0.195  0.444  0.519  0.344  0.120  0.020  0.195  0.120  0.145  0.369  0.020  0.120  0.045  0.070 -0.054 -0.104  0.494  0.020  0.195  0.020  0.419  0.020  0.145  0.294  0.419  0.170  0.245  0.145  0.170  0.020 -0.029  0.195  0.444  0.220 -0.079 -0.029  0.220 -0.004  0.344  0.120  0.245 -0.029  0.245  0.444  0.145  0.469  0.220  0.070  0.070  0.070 -0.054 -0.029 -0.029 -0.054  0.045  0.145 -0.029  0.045 -0.004  0.020 -0.004  0.020  0.070 -0.079 -0.079 -0.079 -0.054  0.020 -0.004  0.020 -0.029 -0.029  0.120 -0.004 -0.079 -0.004 -0.004  0.020 -0.054 -0.104 -0.104 -0.054 -0.029 -0.054  0.170 -0.004  0.020 -0.054  0.070 -0.029  0.020 -0.029  0.120 -0.054 -0.029 -0.054 -0.079 
 0.131  0.305  0.006  0.156  0.380  0.555  0.305  0.131  0.006  0.206  0.131  0.131  0.330  0.006  0.131  0.031  0.081 -0.043 -0.093  0.455  0.006  0.206  0.006  0.380  0.006  0.156  0.281  0.430  0.181  0.256  0.156  0.106  0.031 -0.018  0.181  0.455  0.181 -0.068 -0.043  0.156 -0.043  0.355  0.131  0.231 -0.043  0.231  0.380  0.156  0.455  0.231  0.081  0.081  0.081 -0.018 -0.018 -0.018 -0.068  0.056  0.156 -0.018  0.031 -0.018  0.031  0.006  0.056  0.081 -0.068 -0.068 -0.068 -0.043  0.006  0.006  0.006 -0.018 -0.018  0.131 -0.018 -0.068  0.006  0.006  0.006 -0.043 -0.093 -0.093 -0.043 -0.018 -0.043  0.156  0.031  0.031 -0.043  0.081 -0.018  0.031 -0.018  0.106 -0.043 -0.018 -0.068 -0.068 
 0.043  0.243 -0.006  0.118  0.292  0.567  0.268  0.118  0.018  0.143  0.118  0.118  0.292 -0.006  0.143  0.018  0.093 -0.031 -0.081  0.442  0.018  0.143  0.018  0.367  0.018  0.168  0.268  0.442  0.093  0.243  0.168  0.093  0.018 -0.031  0.168  0.442  0.168 -0.056 -0.056  0.143 -0.031  0.317  0.118  0.168 -0.056  0.168  0.292  0.118  0.467  0.243  0.043  0.068  0.068 -0.006 -0.031 -0.006 -0.056  0.068  0.118 -0.006  0.018 -0.006  0.043  0.018  0.068  0.068 -0.056 -0.056 -0.081 -0.031  0.018  0.018  0.018 -0.006 -0.031  0.118 -0.031 -0.056 -0.006  0.018 -0.006 -0.031 -0.081 -0.081 -0.056 -0.006 -0.031  0.093  0.043  0.043 -0.031  0.093 -0.006  0.043 -0.006  0.093 -0.031 -0.031 -0.056 -0.081 
 0.005  0.154 -0.020  0.080  0.179  0.653  0.229  0.105  0.030  0.130  0.080  0.130  0.229 -0.020  0.080  0.005  0.080 -0.020 -0.070  0.379  0.030  0.105  0.005  0.354  0.030  0.179  0.279  0.404  0.105  0.204  0.179  0.105  0.005 -0.020  0.130  0.404  0.130 -0.045 -0.045  0.005 -0.045  0.329  0.130  0.154 -0.045  0.154  0.254  0.080  0.453  0.304  0.030  0.030  0.080  0.005  0.005 -0.020 -0.045  0.055  0.130  0.005 -0.020  0.005  0.055  0.030  0.055  0.055 -0.045 -0.045 -0.045 -0.045  0.030 -0.045  0.030 -0.020 -0.020  0.080 -0.045 -0.045 -0.020  0.030 -0.045 -0.020 -0.070 -0.070 -0.045  0.005 -0.045  0.105  0.005  0.005 -0.045  0.105  0.005  0.055  0.005  0.080 -0.020 -0.020 -0.070 -0.070 
 0.009  0.134 -0.041  0.084  0.183  0.682  0.233  0.109  0.009  0.134  0.059  0.134  0.233 -0.016  0.084  0.009  0.059 -0.016 -0.066  0.358  0.009  0.059  0.034  0.358  0.009  0.158  0.258  0.408  0.084  0.208  0.183  0.109  0.009 -0.016  0.084  0.383  0.084 -0.041 -0.041 -0.016 -0.041  0.308  0.134  0.134 -0.041  0.109  0.258  0.084  0.408  0.308  0.009  0.034  0.059  0.009 -0.016 -0.016 -0.041  0.059  0.084 -0.016  0.009  0.009  0.034  0.034  0.034  0.059 -0.041 -0.041 -0.041 -0.041  0.034 -0.041  0.034 -0.041 -0.041  0.109 -0.041 -0.041 -0.016  0.034 -0.041 -0.016 -0.066 -0.066 -0.041  0.009 -0.041  0.109  0.009  0.009 -0.041  0.109  0.009  0.059  0.009  0.084 -0.016 -0.016 -0.066 -0.066 
-0.000  0.049 -0.025  0.049  0.124  0.697  0.224  0.099  0.024  0.124  0.049  0.099  0.224 -0.025  0.099 -0.000  0.049 -0.025 -0.050  0.124  0.024  0.049  0.024  0.298 -0.025  0.149  0.199  0.398  0.099  0.199  0.174  0.099 -0.000 -0.000  0.099  0.323  0.074 -0.025 -0.025 -0.000 -0.025  0.323  0.124  0.124 -0.025  0.074  0.099  0.099  0.274  0.298 -0.000  0.024  0.049 -0.000 -0.000 -0.000 -0.025  0.074  0.074 -0.000 -0.000  0.024  0.024  0.049  0.049  0.049 -0.025 -0.025 -0.025 -0.025 -0.025 -0.025 -0.000 -0.050 -0.025  0.099 -0.050 -0.025 -0.000 -0.000 -0.025 -0.000 -0.050 -0.050 -0.025  0.024 -0.025  0.024 -0.000  0.024 -0.025  0.074 -0.000  0.024  0.024  0.024 -0.025 -0.000 -0.050 -0.050 
-0.013  0.037 -0.013  0.037  0.087  0.734  0.186  0.037  0.037  0.087  0.062  0.137  0.211 -0.013  0.087 -0.013 -0.013 -0.038 -0.038  0.112  0.012  0.037  0.012  0.211 -0.013  0.112  0.037  0.261  0.062  0.137  0.161  0.087 -0.013  0.012  0.087  0.311  0.037 -0.013 -0.013 -0.013 -0.013  0.211  0.087  0.112 -0.013  0.037  0.037  0.087  0.137  0.261 -0.038  0.012  0.012  0.012 -0.013 -0.038 -0.013  0.062  0.012 -0.038 -0.013  0.012  0.012  0.037  0.037  0.037 -0.013 -0.038 -0.013 -0.013 -0.013 -0.013 -0.013 -0.038 -0.013  0.087 -0.038 -0.013  0.012  0.012 -0.013 -0.013 -0.038 -0.038 -0.013  0.037 -0.038  0.012 -0.013  0.012 -0.038  0.037 -0.013  0.012  0.037  0.012 -0.013  0.012 -0.038 -0.038 
-0.022  0.027 -0.022  0.052  0.002  0.825  0.102  0.027  0.052  0.077  0.002  0.102  0.152  0.002  0.052  0.002  0.002 -0.022 -0.022  0.027  0.027  0.002  0.002  0.102  0.002  0.027  0.002  0.177  0.052  0.052  0.077  0.002  0.002  0.027  0.052  0.152 -0.022  0.002 -0.022  0.002  0.002  0.077  0.027  0.052  0.002 -0.022 -0.022  0.077  0.077  0.077 -0.022  0.027 -0.022  0.027  0.002 -0.022 -0.022  0.002  0.002 -0.022 -0.022  0.027  0.002  0.002  0.002  0.002  0.002 -0.022  0.002 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022  0.027 -0.022  0.002  0.002  0.027  0.002  0.002 -0.022 -0.022  0.002  0.027 -0.022  0.002  0.002 -0.022 -0.022 -0.022  0.002  0.027  0.002  0.002  0.027  0.002 -0.022 -0.022 
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-0.020  0.004 -0.020  0.004 -0.020  1.001  0.029  0.029  0.029  0.079  0.004  0.079  0.079 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004 -0.020  0.079  0.029  0.004  0.004  0.004  0.004  0.029  0.029  0.079 -0.020  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029 -0.020 -0.020 -0.020  0.054 -0.020  0.079 -0.020  0.029 -0.020  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004 -0.020 -0.020 
-0.020  0.004 -0.020  0.004 -0.020  1.001  0.029  0.029  0.029  0.079  0.004  0.079  0.079 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004 -0.020  0.079  0.029  0.004  0.004  0.004  0.004  0.029  0.029  0.079 -0.020  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029 -0.020 -0.020 -0.020  0.054 -0.020  0.079 -0.020  0.029 -0.020  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004 -0.020 -0.020 
-0.020  0.004 -0.020  0.004 -0.020  1.001  0.029  0.029  0.029  0.079  0.004  0.079  0.079 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004 -0.020  0.079  0.029  0.004  0.004  0.004  0.004  0.029  0.029  0.079 -0.020  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029 -0.020 -0.020 -0.020  0.054 -0.020  0.079 -0.020  0.029 -0.020  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004 -0.020 -0.020 
-0.020  0.004 -0.020  0.004 -0.020  1.001  0.029  0.029  0.029  0.079  0.004  0.079  0.079 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004 -0.020  0.079  0.029  0.004  0.004  0.004  0.004  0.029  0.029  0.079 -0.020  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029 -0.020 -0.020 -0.020  0.054 -0.020  0.079 -0.020  0.029 -0.020  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004 -0.020 -0.020 
-0.020  0.004 -0.020  0.004 -0.020  1.001  0.029  0.029  0.029  0.079  0.004  0.079  0.079 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004 -0.020  0.079  0.029  0.004  0.004  0.004  0.004  0.029  0.029  0.079 -0.020  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029 -0.020 -0.020 -0.020  0.054 -0.020  0.079 -0.020  0.029 -0.020  0.029  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004 -0.020 -0.020 
-0.003 -0.003 -0.028 -0.003 -0.028  0.994  0.047  0.047  0.022  0.221 -0.003  0.271  0.072 -0.028  0.047 -0.003 -0.003 -0.028 -0.028  0.022  0.047 -0.028 -0.003  0.022 -0.028 -0.003 -0.028  0.122  0.072  0.022 -0.003 -0.003 -0.003  0.022  0.022  0.072 -0.028  0.022 -0.003  0.022 -0.028  0.047 -0.003  0.022 -0.028 -0.028 -0.028  0.072 -0.028  0.122 -0.028  0.022 -0.028  0.022 -0.003 -0.003 -0.028 -0.003 -0.003 -0.003 -0.028  0.047  0.047 -0.028  0.022  0.022  0.047 -0.003  0.022 -0.028  0.047 -0.028 -0.028 -0.028 -0.028 -0.003 -0.003  0.072 -0.028  0.072  0.047  0.022  0.022 -0.028 -0.028  0.022 -0.028 -0.003 -0.003 -0.028  0.022 -0.028 -0.003 -0.003 -0.003 -0.003  0.047  0.022 -0.028 -0.028 
 0.044  0.044 -0.055  0.044 -0.030  0.966  0.019  0.094 -0.005  0.543  0.019  0.617  0.094 -0.055  0.019  0.019  0.019 -0.030 -0.055  0.019  0.044 -0.005 -0.030  0.044 -0.005  0.044 -0.030  0.119  0.094  0.044 -0.005 -0.030  0.019 -0.005 -0.005  0.219 -0.055 -0.005 -0.005  0.019 -0.030  0.019  0.019  0.019 -0.030 -0.030 -0.055  0.069  0.044  0.219 -0.030  0.069 -0.005  0.019 -0.005 -0.005 -0.055 -0.005 -0.005 -0.030 -0.055  0.044  0.019 -0.030 -0.005  0.044  0.069  0.044 -0.005 -0.055  0.019 -0.005  0.019 -0.005 -0.055 -0.005 -0.030  0.044 -0.005  0.044  0.144 -0.005 -0.005 -0.055 -0.030  0.019 -0.055  0.019 -0.005 -0.005  0.019 -0.030 -0.005  0.019 -0.030 -0.005  0.019  0.019 -0.030 -0.055 
 0.111  0.111 -0.014  0.061 -0.014  0.933  0.061  0.111 -0.039  0.659  0.011  0.808  0.111 -0.089 -0.014  0.061  0.160  0.011 -0.089  0.086  0.011  0.011 -0.039  0.011 -0.014  0.036 -0.039  0.360  0.136  0.036  0.011 -0.064  0.136 -0.039  0.011  0.285  0.011 -0.039 -0.014  0.061 -0.039  0.061  0.061  0.061 -0.014 -0.039 -0.014  0.111  0.011  0.260  0.011  0.111 -0.014  0.036 -0.039 -0.014 -0.089 -0.014  0.061 -0.064 -0.089  0.036  0.036 -0.064  0.011  0.061  0.036  0.061  0.036 -0.064  0.011  0.011  0.036  0.036 -0.064  0.011 -0.039  0.011  0.011  0.061  0.260 -0.039 -0.014 -0.089 -0.039  0.036 -0.064  0.036 -0.014  0.111 -0.014 -0.039 -0.014  0.036 -0.014 -0.014  0.061  0.011 -0.039 -0.039 
 0.252  0.053 -0.022  0.003  0.028  0.875  0.152  0.103 -0.047  0.875  0.003  0.875  0.252 -0.122  0.028  0.128  0.152 -0.022 -0.122  0.128  0.053  0.028 -0.047  0.078  0.003  0.053  0.003  0.701  0.302  0.152 -0.022  0.078  0.177 -0.047  0.028  0.402  0.078 -0.097  0.003  0.252  0.053  0.053  0.177  0.053 -0.022 -0.047  0.028  0.227  0.152  0.352  0.028  0.103  0.028  0.028 -0.072 -0.072 -0.072 -0.047  0.078 -0.047 -0.072  0.053  0.053 -0.122 -0.022  0.028  0.103  0.078  0.103 -0.122  0.053 -0.047  0.028  0.028 -0.022 -0.022 -0.097 -0.022 -0.022  0.003  0.402 -0.072 -0.022 -0.047  0.028  0.028 -0.097  0.053  0.003  0.053 -0.047 -0.022  0.003  0.053 -0.022  0.152  0.078  0.028 -0.022 -0.047 
 0.393  0.019  0.019  0.019  0.094  0.841  0.193  0.094 -0.081  0.841  0.069  0.841  0.268 -0.106  0.044  0.119  0.143 -0.056 -0.106  0.268  0.044  0.069  0.019  0.119 -0.006  0.069 -0.006  0.716  0.368  0.193  0.019  0.119  0.193 -0.056  0.044  0.492  0.119 -0.131 -0.006  0.368  0.094  0.094  0.193  0.019 -0.056  0.019  0.094  0.393  0.218  0.393  0.069  0.094  0.019  0.044 -0.056 -0.081 -0.081 -0.081  0.143 -0.006 -0.106  0.119  0.044 -0.131 -0.031 -0.006  0.119  0.069  0.069 -0.131  0.069 -0.056  0.069  0.094 -0.056 -0.031 -0.155 -0.056 -0.006  0.019  0.442 -0.106 -0.031 -0.006 -0.006  0.044 -0.131  0.044  0.019  0.044 -0.031 -0.031  0.094  0.094 -0.056  0.143  0.143 -0.006 -0.006 -0.081 
 0.484  0.036  0.036 -0.014  0.260  0.758  0.385  0.111 -0.064  0.733  0.061  0.783  0.484 -0.089  0.036  0.061  0.185 -0.064 -0.163  0.634  0.061  0.111  0.011  0.285  0.036  0.136  0.111  0.709  0.459  0.310  0.061  0.185  0.235 -0.114  0.061  0.709  0.260 -0.163 -0.014  0.434  0.111  0.235  0.260  0.086 -0.064  0.061  0.160  0.584  0.410  0.459  0.061  0.111  0.036  0.086 -0.139 -0.114 -0.089 -0.039  0.210  0.011 -0.089  0.136  0.061 -0.139 -0.039 -0.014  0.210  0.011  0.061 -0.163  0.086 -0.039  0.111  0.111 -0.064 -0.064 -0.039 -0.114  0.061 -0.039  0.459 -0.114 -0.089 -0.014  0.011  0.061 -0.163  0.136  0.036 -0.014 -0.014 -0.014  0.086  0.136 -0.114  0.260  0.111 -0.064 -0.039 -0.163 
 0.493  0.045  0.070  0.020  0.244  0.693  0.369  0.095 -0.055  0.717  0.144  0.693  0.468 -0.105  0.020  0.144  0.219 -0.105 -0.130  0.693  0.070  0.120 -0.005  0.419  0.045  0.144  0.120  0.717  0.493  0.394  0.070  0.194  0.244 -0.105  0.020  0.693  0.269 -0.179  0.020  0.493  0.095  0.244  0.244  0.070 -0.055  0.095  0.144  0.643  0.443  0.419  0.045  0.120  0.045  0.070 -0.130 -0.130 -0.055 -0.030  0.194  0.045 -0.055  0.120  0.020 -0.154 -0.030  0.020  0.219  0.020  0.070 -0.154  0.120 -0.030  0.194  0.144 -0.055 -0.055 -0.005 -0.130  0.045 -0.030  0.468 -0.105 -0.105 -0.005  0.020  0.020 -0.154  0.120  0.070 -0.055  0.045 -0.030  0.070  0.120 -0.130  0.319  0.095 -0.080 -0.055 -0.179 
 0.487  0.063  0.088  0.113  0.337  0.661  0.487  0.063 -0.061  0.686  0.213  0.586  0.512 -0.136  0.113  0.163  0.238 -0.111 -0.111  0.686  0.063  0.163 -0.036  0.562  0.013  0.138  0.263  0.686  0.487  0.462  0.188  0.263  0.213 -0.086 -0.011  0.661  0.287 -0.186  0.013  0.562  0.063  0.337  0.312  0.188 -0.036  0.088  0.287  0.661  0.537  0.387  0.013  0.113  0.088  0.038 -0.136 -0.136 -0.061 -0.011  0.188  0.038  0.063  0.088  0.013 -0.161 -0.036  0.013  0.263 -0.011  0.063 -0.136  0.163  0.063  0.213  0.113 -0.061 -0.011  0.063 -0.086  0.063 -0.036  0.387 -0.136 -0.086 -0.011  0.013 -0.036 -0.136  0.213  0.113 -0.061  0.088  0.063  0.013  0.163 -0.161  0.312  0.063 -0.036 -0.061 -0.211 
 0.479  0.130  0.105  0.180  0.354  0.628  0.479  0.055 -0.069  0.653  0.230  0.554  0.504 -0.144  0.130  0.180  0.230 -0.094 -0.119  0.678  0.055  0.155 -0.019  0.554  0.005  0.130  0.280  0.628  0.454  0.454  0.230  0.280  0.205 -0.069  0.055  0.653  0.329 -0.169  0.030  0.578  0.105  0.379  0.280  0.180 -0.044  0.105  0.354  0.653  0.529  0.404  0.080  0.130  0.105 -0.019 -0.144 -0.094 -0.044  0.030  0.180  0.030  0.080  0.080  0.030 -0.169 -0.044  0.030  0.255 -0.044  0.080 -0.144  0.180  0.080  0.205  0.105 -0.094 -0.019  0.055 -0.094  0.080 -0.044  0.379 -0.144 -0.094 -0.019  0.055 -0.044 -0.144  0.205  0.105 -0.069  0.130  0.030  0.005  0.180 -0.169  0.304  0.055 -0.044 -0.069 -0.219 
 0.442  0.193  0.069  0.168  0.442  0.517  0.467  0.094  0.019  0.642  0.268  0.492  0.492 -0.131  0.143  0.193  0.293 -0.106 -0.131  0.667  0.069  0.168 -0.006  0.592  0.044  0.119  0.368  0.617  0.442  0.442  0.243  0.268  0.168 -0.081  0.119  0.592  0.368 -0.180  0.019  0.567  0.119  0.418  0.268  0.318 -0.056  0.168  0.442  0.667  0.517  0.418  0.119  0.143  0.094 -0.056 -0.155 -0.081 -0.031  0.019  0.193  0.019  0.119  0.044 -0.006 -0.131 -0.056  0.069  0.243 -0.081  0.044 -0.155  0.168  0.094  0.193  0.094 -0.081 -0.031  0.019 -0.131  0.069 -0.031  0.343 -0.131 -0.155 -0.031  0.094 -0.081 -0.155  0.193  0.069 -0.081  0.143  0.019 -0.031  0.193 -0.180  0.293  0.044 -0.056 -0.131 -0.180 
 0.391  0.266  0.042  0.191  0.540  0.515  0.440  0.142  0.042  0.615  0.266  0.465  0.490 -0.083  0.166  0.216  0.291 -0.108 -0.133  0.665  0.017  0.166  0.017  0.565  0.042  0.142  0.366  0.590  0.490  0.440  0.241  0.266  0.166 -0.058  0.241  0.590  0.366 -0.182  0.042  0.565  0.117  0.440  0.266  0.366 -0.058  0.191  0.490  0.665  0.540  0.440  0.117  0.142  0.092 -0.058 -0.157 -0.083 -0.008  0.067  0.142 -0.008  0.117  0.042  0.017 -0.133 -0.058  0.067  0.266 -0.083 -0.033 -0.157  0.216  0.067  0.191  0.092 -0.058 -0.033  0.017 -0.157  0.067 -0.033  0.291 -0.083 -0.157 -0.058  0.042 -0.083 -0.108  0.191  0.042 -0.108  0.117 -0.008 -0.033  0.166 -0.157  0.291  0.017 -0.083 -0.133 -0.182 
 0.409  0.260  0.060  0.185  0.534  0.509  0.459  0.160  0.085  0.534  0.284  0.409  0.484 -0.039  0.160  0.260  0.260 -0.089 -0.139  0.658  0.010  0.160  0.010  0.559  0.010  0.110  0.384  0.534  0.509  0.434  0.260  0.235  0.135  0.035  0.309  0.583  0.359 -0.139  0.035  0.583  0.085  0.434  0.235  0.459 -0.064  0.260  0.559  0.633  0.509  0.434  0.135  0.135  0.085 -0.064 -0.164 -0.089 -0.014  0.060  0.135 -0.014  0.110  0.060  0.085 -0.114 -0.089  0.060  0.235 -0.089 -0.039 -0.139  0.210  0.085  0.185  0.085 -0.039 -0.039  0.035 -0.164  0.060 -0.039  0.284 -0.089 -0.189 -0.089  0.035 -0.114 -0.089  0.160  0.010 -0.114  0.110 -0.039 -0.039  0.235 -0.139  0.284 -0.064 -0.064 -0.139 -0.164 
 0.409  0.259  0.060  0.209  0.483  0.508  0.458  0.159  0.135  0.483  0.284  0.384  0.483 -0.040  0.209  0.284  0.259 -0.065 -0.115  0.658  0.010  0.159  0.010  0.608 -0.015  0.135  0.384  0.533  0.533  0.433  0.259  0.209  0.135  0.085  0.384  0.558  0.359 -0.140  0.010  0.583  0.085  0.409  0.209  0.483 -0.065  0.259  0.608  0.608  0.508  0.433  0.159  0.135  0.060 -0.065 -0.164 -0.065 -0.015  0.060  0.135 -0.065  0.110  0.060  0.085 -0.090 -0.115  0.060  0.209 -0.090 -0.040 -0.164  0.209  0.085  0.159  0.085 -0.015 -0.065  0.060 -0.140  0.060 -0.040  0.284 -0.090 -0.189 -0.090 -0.015 -0.115 -0.065  0.159  0.060 -0.115  0.085 -0.040 -0.040  0.234 -0.140  0.309 -0.065 -0.040 -0.140 -0.140 
 0.428  0.279  0.054  0.204  0.478  0.503  0.478  0.129  0.179  0.403  0.279  0.378  0.528 -0.045  0.229  0.328  0.229 -0.070 -0.120  0.652  0.004  0.154  0.004  0.602  0.004  0.129  0.378  0.478  0.553  0.428  0.254  0.204  0.129  0.104  0.428  0.528  0.378 -0.145 -0.020  0.577  0.104  0.378  0.179  0.553 -0.045  0.353  0.602  0.602  0.478  0.428  0.179  0.129  0.054 -0.045 -0.145 -0.070 -0.020  0.054  0.129 -0.070  0.104  0.054  0.079 -0.070 -0.120  0.054  0.204 -0.095 -0.045 -0.170  0.179  0.104  0.154  0.054 -0.020 -0.070  0.079 -0.120  0.079 -0.045  0.229 -0.095 -0.170 -0.095 -0.020 -0.120 -0.070  0.154  0.079 -0.120  0.079 -0.020 -0.045  0.229 -0.120  0.353 -0.070 -0.020 -0.145 -0.145 
 0.427  0.278  0.054  0.228  0.477  0.502  0.477  0.129  0.178  0.378  0.278  0.328  0.527 -0.046  0.228  0.378  0.203 -0.071 -0.096  0.652  0.004  0.178 -0.021  0.602  0.004  0.153  0.378  0.427  0.552  0.403  0.253  0.228  0.104  0.153  0.452  0.552  0.403 -0.145 -0.021  0.577  0.104  0.353  0.153  0.577 -0.046  0.403  0.602  0.577  0.477  0.403  0.178  0.129  0.054 -0.046 -0.121 -0.046 -0.021  0.054  0.129 -0.071  0.129  0.054  0.079 -0.046 -0.121  0.054  0.178 -0.096  0.004 -0.170  0.153  0.104  0.153 -0.021 -0.021 -0.071  0.104 -0.121  0.079 -0.046  0.228 -0.071 -0.145 -0.071 -0.021 -0.145 -0.071  0.129  0.129 -0.145  0.079 -0.021 -0.046  0.228 -0.121  0.353 -0.071 -0.021 -0.145 -0.145 
 0.451  0.302  0.053  0.227  0.451  0.501  0.476  0.128  0.177  0.377  0.277  0.327  0.526 -0.047  0.302  0.426  0.177 -0.072 -0.122  0.651  0.003  0.177 -0.022  0.601  0.003  0.177  0.377  0.426  0.526  0.402  0.252  0.227  0.128  0.152  0.476  0.551  0.402 -0.146 -0.022  0.551  0.103  0.352  0.128  0.576 -0.047  0.402  0.601  0.576  0.476  0.402  0.177  0.128  0.028 -0.047 -0.122 -0.047 -0.022  0.053  0.128 -0.122  0.103  0.053  0.078 -0.047 -0.122  0.053  0.152 -0.072  0.003 -0.171  0.128  0.128  0.078 -0.022  0.003 -0.072  0.103 -0.122  0.078 -0.047  0.227 -0.072 -0.122 -0.072 -0.022 -0.146 -0.072  0.128  0.152 -0.146  0.053  0.003 -0.072  0.202 -0.122  0.377 -0.072 -0.022 -0.146 -0.146 
 0.453  0.303  0.054  0.229  0.453  0.503  0.478  0.129  0.179  0.378  0.279  0.328  0.528 -0.045  0.303  0.428  0.179 -0.070 -0.120  0.652  0.004  0.204 -0.020  0.602  0.004  0.179  0.378  0.428  0.528  0.403  0.254  0.229  0.104  0.154  0.478  0.553  0.403 -0.145 -0.045  0.553  0.079  0.328  0.129  0.577 -0.045  0.403  0.602  0.528  0.478  0.403  0.179  0.129  0.029 -0.070 -0.120 -0.045 -0.045  0.054  0.129 -0.120  0.104  0.054  0.054 -0.045 -0.120  0.054  0.129 -0.070  0.004 -0.170  0.129  0.129  0.079 -0.020  0.004 -0.070  0.079 -0.120  0.079 -0.045  0.254 -0.070 -0.120 -0.070 -0.020 -0.145 -0.070  0.129  0.154 -0.145  0.054  0.004 -0.070  0.204 -0.120  0.353 -0.095 -0.020 -0.145 -0.145 
 0.404  0.304  0.055  0.229  0.453  0.503  0.478  0.130  0.179  0.379  0.279  0.329  0.528 -0.045  0.304  0.428  0.179 -0.070 -0.144  0.653  0.005  0.204 -0.020  0.603  0.005  0.179  0.379  0.404  0.528  0.354  0.254  0.229  0.130  0.154  0.528  0.553  0.404 -0.144 -0.045  0.553  0.080  0.329  0.105  0.628 -0.045  0.404  0.578  0.503  0.478  0.379  0.179  0.130  0.030 -0.045 -0.120 -0.045 -0.045  0.030  0.130 -0.120  0.130  0.055  0.055 -0.045 -0.120  0.030  0.080 -0.070 -0.020 -0.169  0.130  0.130  0.080 -0.045  0.030 -0.045  0.080 -0.120  0.080 -0.020  0.254 -0.070 -0.120 -0.095 -0.020 -0.144 -0.070  0.105  0.154 -0.144  0.055  0.005 -0.070  0.204 -0.095  0.354 -0.095 -0.020 -0.144 -0.120 
 0.402  0.302  0.053  0.228  0.452  0.502  0.477  0.128  0.178  0.377  0.278  0.327  0.527 -0.046  0.302  0.427  0.178 -0.071 -0.146  0.626  0.003  0.203 -0.021  0.601  0.003  0.178  0.377  0.402  0.552  0.352  0.253  0.228  0.128  0.153  0.527  0.552  0.402 -0.146 -0.046  0.552  0.078  0.327  0.103  0.626 -0.046  0.402  0.576  0.502  0.477  0.377  0.178  0.128  0.028 -0.046 -0.121 -0.046 -0.046  0.028  0.128 -0.096  0.128  0.053  0.053 -0.046 -0.121  0.028  0.053 -0.071 -0.021 -0.171  0.128  0.128  0.103 -0.046  0.028 -0.046  0.078 -0.121  0.078 -0.021  0.253 -0.071 -0.121 -0.096 -0.021 -0.146 -0.071  0.103  0.153 -0.146  0.053  0.028 -0.071  0.203 -0.096  0.352 -0.096  0.003 -0.146 -0.121 
 0.377  0.327  0.028  0.252  0.451  0.501  0.476  0.128  0.202  0.377  0.277  0.327  0.526 -0.047  0.302  0.426  0.152 -0.072 -0.122  0.601  0.003  0.202 -0.022  0.626  0.003  0.177  0.377  0.426  0.551  0.352  0.252  0.202  0.152  0.152  0.526  0.551  0.402 -0.146  0.028  0.551  0.128  0.327  0.078  0.626 -0.047  0.402  0.576  0.476  0.476  0.402  0.177  0.128  0.003 -0.097 -0.122 -0.047 -0.047  0.028  0.128 -0.097  0.152  0.028  0.053 -0.047 -0.122  0.028  0.003 -0.072 -0.022 -0.196  0.103  0.128  0.103 -0.047  0.028 -0.047  0.128 -0.097  0.053  0.003  0.252 -0.072 -0.122 -0.097 -0.022 -0.146 -0.072  0.103  0.152 -0.146  0.053  0.028 -0.072  0.227 -0.122  0.352 -0.072  0.003 -0.146 -0.122 
 0.398  0.348 -0.051  0.273  0.373  0.497  0.423  0.148  0.198  0.373  0.223  0.273  0.497 -0.026  0.323  0.348  0.124 -0.051 -0.051  0.547 -0.026  0.248 -0.026  0.622 -0.076  0.148  0.298  0.472  0.597  0.248  0.248  0.223  0.148  0.099  0.472  0.423  0.298 -0.126  0.099  0.447  0.099  0.298  0.074  0.547 -0.101  0.273  0.447  0.472  0.522  0.398  0.074  0.124  0.024 -0.076 -0.076 -0.051 -0.076  0.049  0.148 -0.101  0.198  0.074  0.024 -0.001 -0.076  0.024 -0.001 -0.051 -0.051 -0.150  0.099  0.049  0.148 -0.051  0.024  0.024  0.148 -0.051  0.024  0.049  0.173 -0.026 -0.150 -0.200 -0.051 -0.101 -0.101  0.124  0.124 -0.101  0.024  0.049 -0.051  0.173 -0.101  0.273 -0.026 -0.051 -0.126 -0.076 
 0.285  0.360 -0.038  0.211  0.385  0.485  0.385  0.186  0.086  0.236  0.211  0.161  0.435 -0.013  0.211  0.285  0.086 -0.063 -0.113  0.485 -0.013  0.211 -0.038  0.535 -0.013  0.086  0.335  0.410  0.460  0.211  0.186  0.161  0.036  0.036  0.310  0.435  0.285 -0.113 -0.063  0.360  0.011  0.310  0.086  0.485 -0.088  0.261  0.435  0.335  0.535  0.310 -0.013  0.086  0.061 -0.038 -0.063 -0.063 -0.088  0.036  0.161 -0.063  0.111  0.036  0.086  0.011 -0.038  0.036 -0.038 -0.063 -0.088 -0.063  0.136  0.036  0.086 -0.013 -0.013  0.036  0.086 -0.063  0.061  0.061  0.061 -0.038 -0.163 -0.163 -0.063 -0.088 -0.063  0.136  0.061 -0.038 -0.088  0.086 -0.013  0.111 -0.088  0.285 -0.113  0.011 -0.063 -0.063 
 0.274  0.374 -0.025  0.199  0.399  0.498  0.374  0.199  0.075  0.224  0.174  0.125  0.374  0.000  0.125  0.249  0.100 -0.075 -0.100  0.473  0.000  0.199 -0.025  0.498 -0.025  0.100  0.324  0.399  0.448  0.224  0.149  0.174 -0.025 -0.025  0.324  0.448  0.274 -0.100 -0.050  0.299  0.025  0.324  0.100  0.424 -0.075  0.274  0.448  0.299  0.548  0.299 -0.025  0.050  0.050 -0.050 -0.050 -0.075 -0.100  0.025  0.149 -0.050  0.075  0.050  0.100  0.025 -0.025  0.025 -0.050 -0.075 -0.075 -0.050  0.149  0.025  0.075  0.000 -0.025  0.050  0.050 -0.050  0.075  0.025  0.075 -0.050 -0.149 -0.149 -0.050 -0.075 -0.050  0.149  0.025 -0.025 -0.075  0.100 -0.025  0.100 -0.075  0.249 -0.100  0.025 -0.100 -0.075 
 0.293  0.318 -0.005  0.194  0.443  0.468  0.318  0.169  0.044  0.219  0.094  0.144  0.368 -0.005  0.069  0.144  0.094 -0.055 -0.130  0.443 -0.005  0.194 -0.005  0.468 -0.005  0.119  0.368  0.418  0.368  0.244  0.119  0.144 -0.005 -0.080  0.269  0.468  0.219 -0.105 -0.030  0.269  0.019  0.343  0.094  0.293 -0.005  0.269  0.443  0.269  0.568  0.269 -0.005  0.069  0.044 -0.055 -0.055 -0.080 -0.080  0.019  0.169 -0.055  0.019  0.044  0.044  0.044 -0.005  0.019 -0.105 -0.055 -0.105 -0.030  0.144 -0.005  0.044  0.044 -0.030  0.069 -0.005 -0.030  0.044 -0.005  0.069 -0.080 -0.130 -0.130 -0.055 -0.055 -0.055  0.144  0.019  0.019 -0.080  0.094 -0.005  0.094 -0.055  0.169 -0.080 -0.005 -0.105 -0.105 
 0.299  0.324  0.000  0.174  0.448  0.424  0.299  0.174  0.025  0.224  0.100  0.149  0.374  0.000  0.050  0.075  0.075 -0.075 -0.125  0.448  0.000  0.174  0.000  0.424  0.050  0.149  0.399  0.424  0.324  0.249  0.125  0.149  0.025 -0.075  0.249  0.473  0.224 -0.100 -0.025  0.224  0.000  0.349  0.100  0.299  0.000  0.274  0.424  0.224  0.573  0.249  0.025  0.075  0.050 -0.075 -0.050 -0.075 -0.050  0.025  0.149 -0.050  0.025  0.050  0.050  0.050 -0.025  0.025 -0.100 -0.050 -0.100 -0.025  0.125 -0.025  0.050  0.025 -0.050  0.075  0.000 -0.025  0.025  0.000  0.075 -0.075 -0.125 -0.125 -0.050 -0.050 -0.050  0.149  0.000  0.025 -0.075  0.100  0.000  0.100 -0.050  0.174 -0.075 -0.050 -0.100 -0.100 
 0.212  0.286  0.037  0.137  0.461  0.436  0.286  0.137  0.012  0.187  0.112  0.137  0.361  0.012  0.012  0.012  0.037 -0.062 -0.087  0.486 -0.012  0.212 -0.012  0.411  0.062  0.162  0.436  0.386  0.237  0.262  0.137  0.112  0.037 -0.062  0.237  0.461  0.262 -0.087 -0.037  0.237 -0.012  0.336  0.112  0.262 -0.037  0.262  0.436  0.212  0.536  0.212  0.037  0.062  0.062 -0.062 -0.062 -0.062 -0.037  0.037  0.162 -0.037  0.037  0.037  0.012  0.012 -0.012  0.037 -0.087 -0.087 -0.087 -0.037  0.087 -0.012  0.012  0.012 -0.037  0.062 -0.012 -0.037  0.012  0.012  0.037 -0.062 -0.112 -0.112 -0.062 -0.037 -0.062  0.137 -0.012  0.037 -0.087  0.112  0.012  0.112 -0.037  0.112 -0.062 -0.037 -0.062 -0.087 
 0.168  0.268  0.018  0.143  0.467  0.467  0.292  0.143  0.018  0.193  0.118  0.118  0.342  0.018  0.043  0.018  0.043 -0.056 -0.106  0.442 -0.006  0.243  0.018  0.367  0.068  0.168  0.417  0.417  0.218  0.268  0.143  0.093  0.043 -0.031  0.243  0.492  0.243 -0.081 -0.031  0.218 -0.006  0.342  0.118  0.243 -0.031  0.243  0.442  0.193  0.517  0.193  0.043  0.068  0.068 -0.056 -0.056 -0.056 -0.031  0.043  0.168 -0.031  0.068  0.043  0.018 -0.006 -0.006  0.068 -0.081 -0.081 -0.081 -0.031  0.043 -0.006  0.018  0.018 -0.006  0.093 -0.006 -0.031 -0.006  0.018  0.043 -0.031 -0.106 -0.106 -0.056 -0.031 -0.056  0.143 -0.006  0.043 -0.081  0.118  0.018  0.093 -0.031  0.118 -0.056 -0.031 -0.081 -0.081 
 0.078  0.277  0.028  0.103  0.451  0.451  0.302  0.128  0.028  0.177  0.128  0.128  0.377  0.003  0.053 -0.022  0.028 -0.047 -0.097  0.402  0.003  0.252  0.053  0.327  0.053  0.177  0.426  0.426  0.152  0.252  0.152  0.078  0.053 -0.047  0.252  0.476  0.227 -0.072 -0.022  0.202 -0.047  0.352  0.128  0.202 -0.022  0.252  0.426  0.177  0.476  0.202  0.053  0.078  0.078 -0.047 -0.047 -0.047 -0.022  0.053  0.177 -0.022  0.078  0.003  0.028  0.003  0.003  0.103 -0.047 -0.072 -0.072 -0.022  0.028  0.003  0.003  0.003  0.003  0.103  0.003 -0.022 -0.022  0.028  0.003 -0.022 -0.097 -0.097 -0.047 -0.022 -0.047  0.152  0.003  0.053 -0.072  0.103  0.028  0.053 -0.022  0.128 -0.047 -0.047 -0.072 -0.097 
 0.061  0.261  0.036  0.086  0.410  0.435  0.285  0.136 -0.013  0.161  0.111  0.136  0.360 -0.038  0.061 -0.013  0.036 -0.038 -0.088  0.335  0.011  0.261  0.061  0.236  0.036  0.186  0.435  0.435  0.111  0.261  0.161  0.061  0.011 -0.038  0.261  0.460  0.161 -0.063 -0.038  0.111 -0.038  0.360  0.136  0.186 -0.013  0.261  0.410  0.186  0.485  0.211  0.061  0.086  0.086 -0.038 -0.038 -0.038 -0.013  0.061  0.186 -0.013  0.061 -0.013  0.011  0.011  0.011  0.111 -0.038 -0.063 -0.063 -0.013  0.036 -0.013  0.011 -0.013  0.011  0.086 -0.013 -0.038 -0.013  0.011  0.011 -0.013 -0.088 -0.088 -0.038 -0.013 -0.063  0.161  0.011  0.061 -0.063  0.111  0.036  0.061 -0.013  0.136 -0.038 -0.038 -0.063 -0.088 
 0.026  0.200  0.026  0.101  0.449  0.425  0.300  0.150  0.001  0.175  0.051  0.126  0.350 -0.024  0.026  0.001  0.026 -0.024 -0.074  0.225  0.026  0.275  0.026  0.150  0.001  0.175  0.449  0.449  0.126  0.250  0.175  0.076 -0.024 -0.049  0.275  0.449  0.150 -0.049 -0.024  0.126 -0.024  0.225  0.126  0.175  0.001  0.200  0.375  0.200  0.375  0.200  0.026  0.076  0.101 -0.024 -0.074 -0.049 -0.024  0.076  0.200 -0.024  0.051 -0.024  0.001  0.026  0.026  0.051 -0.049 -0.049 -0.049  0.001 -0.024  0.026  0.001 -0.049  0.026  0.076 -0.049 -0.024 -0.024  0.001  0.026 -0.049 -0.074 -0.074 -0.024  0.001 -0.049  0.175  0.026  0.076 -0.074  0.101  0.001  0.026  0.001  0.126 -0.024 -0.024 -0.049 -0.074 
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 0.331  0.356 -0.167  0.306  0.331  0.455  0.306  0.132  0.156  0.007  0.530  0.206  0.655 -0.093  0.356  0.480  0.007 -0.192 -0.068  0.505  0.132  0.156  0.107  0.630  0.032  0.331  0.281  0.256  0.406  0.206  0.356  0.181 -0.093  0.057  0.406  0.356  0.306 -0.118  0.032  0.455  0.007  0.381 -0.068  0.680 -0.068  0.156  0.331  0.231  0.356  0.605  0.381  0.306 -0.018 -0.043 -0.167  0.381 -0.167  0.156  0.007 -0.192  0.206  0.032  0.082 -0.043  0.356  0.107  0.007 -0.167 -0.192 -0.118  0.132  0.132 -0.043 -0.018  0.256  0.007 -0.118  0.082 -0.068  0.181 -0.018  0.082 -0.142 -0.317 -0.043  0.181 -0.043  0.057  0.331 -0.093 -0.142 -0.018 -0.118  0.032  0.256  0.032 -0.118 -0.118 -0.043 -0.093 
 0.404  0.354 -0.144  0.304  0.354  0.428  0.304  0.179  0.130  0.030  0.553  0.204  0.628 -0.095  0.354  0.478  0.005 -0.169 -0.070  0.503  0.055  0.179  0.105  0.603  0.055  0.354  0.329  0.304  0.428  0.229  0.354  0.204 -0.120  0.080  0.404  0.379  0.354 -0.144  0.080  0.428  0.105  0.404 -0.070  0.678 -0.070  0.179  0.404  0.279  0.428  0.603  0.379  0.304 -0.020 -0.045 -0.144  0.229 -0.144  0.105  0.005 -0.219  0.254  0.055  0.105 -0.045  0.329  0.105  0.005 -0.169 -0.169 -0.120  0.080  0.105 -0.045  0.005  0.229 -0.020 -0.070  0.055 -0.120  0.179  0.030  0.055 -0.144 -0.319 -0.045  0.179 -0.045  0.080  0.304 -0.095 -0.144 -0.020 -0.095  0.130  0.204  0.080 -0.120 -0.095 -0.045 -0.095 
 0.406  0.356 -0.142  0.306  0.356  0.406  0.306  0.156  0.156  0.007  0.555  0.231  0.605 -0.093  0.356  0.480  0.007 -0.142 -0.093  0.505  0.032  0.181  0.107  0.605  0.057  0.356  0.356  0.306  0.455  0.231  0.356  0.206 -0.118  0.082  0.430  0.381  0.381 -0.142  0.082  0.406  0.107  0.381 -0.068  0.680 -0.068  0.231  0.406  0.306  0.430  0.605  0.381  0.306 -0.018 -0.043 -0.167  0.132 -0.142  0.107  0.007 -0.217  0.281  0.057  0.107 -0.018  0.281  0.082  0.007 -0.167 -0.167 -0.118  0.082  0.107 -0.068  0.007  0.206 -0.043 -0.068  0.032 -0.093  0.156  0.032  0.032 -0.142 -0.317 -0.018  0.181 -0.043  0.082  0.331 -0.093 -0.142 -0.018 -0.093  0.132  0.206  0.082 -0.118 -0.093 -0.043 -0.118 
 0.407  0.357 -0.092  0.307  0.407  0.382  0.257  0.157  0.207  0.033  0.556  0.232  0.556 -0.092  0.357  0.481  0.008 -0.166 -0.117  0.506  0.033  0.207  0.083  0.631  0.033  0.332  0.357  0.332  0.481  0.232  0.357  0.207 -0.067  0.108  0.481  0.357  0.407 -0.142  0.058  0.407  0.108  0.382 -0.042  0.606 -0.067  0.282  0.481  0.307  0.431  0.581  0.332  0.332 -0.017 -0.042 -0.166  0.083 -0.142  0.108  0.033 -0.191  0.282  0.058  0.133 -0.042  0.232  0.083  0.008 -0.166 -0.191 -0.117  0.058  0.108 -0.067  0.008  0.182 -0.042 -0.042  0.033 -0.092  0.133  0.033  0.008 -0.166 -0.316 -0.017  0.207 -0.042  0.083  0.332 -0.067 -0.142 -0.017 -0.092  0.133  0.182  0.133 -0.092 -0.092 -0.017 -0.092 
 0.404  0.354 -0.094  0.304  0.404  0.379  0.280  0.155  0.255  0.030  0.554  0.230  0.529 -0.094  0.329  0.479  0.030 -0.169 -0.119  0.504  0.005  0.205  0.055  0.603  0.055  0.304  0.354  0.329  0.479  0.230  0.354  0.205 -0.044  0.105  0.479  0.354  0.429 -0.144  0.080  0.429  0.105  0.354 -0.044  0.603 -0.069  0.280  0.504  0.304  0.479  0.578  0.329  0.329  0.005 -0.044 -0.169  0.080 -0.144  0.105  0.030 -0.194  0.280  0.055  0.130 -0.044  0.230  0.030  0.005 -0.169 -0.194 -0.119  0.080  0.105 -0.044  0.005  0.180 -0.044 -0.044  0.030 -0.094  0.080  0.030 -0.019 -0.194 -0.318 -0.019  0.205 -0.044  0.080  0.304 -0.069 -0.144 -0.019 -0.094  0.130  0.155  0.130 -0.069 -0.069 -0.044 -0.094 
 0.405  0.355 -0.093  0.305  0.455  0.380  0.281  0.156  0.256  0.031  0.555  0.231  0.530 -0.068  0.305  0.480  0.031 -0.168 -0.143  0.505  0.006  0.206  0.056  0.604  0.056  0.305  0.330  0.305  0.480  0.231  0.355  0.181 -0.043  0.106  0.480  0.355  0.430 -0.143  0.081  0.430  0.106  0.355 -0.043  0.629 -0.068  0.281  0.530  0.305  0.505  0.530  0.305  0.330  0.006 -0.018 -0.168  0.081 -0.143  0.106  0.031 -0.193  0.256  0.081  0.131 -0.093  0.181  0.031 -0.018 -0.168 -0.193 -0.118  0.081  0.106 -0.043  0.031  0.181 -0.043 -0.043  0.031 -0.093  0.081  0.031 -0.018 -0.193 -0.317 -0.018  0.181 -0.043  0.106  0.281 -0.068 -0.143 -0.018 -0.068  0.181  0.156  0.131 -0.018 -0.043 -0.068 -0.118 
 0.401  0.351 -0.048  0.301  0.475  0.376  0.251  0.127  0.251  0.052  0.550  0.226  0.525 -0.098  0.301  0.475  0.052 -0.147 -0.098  0.500  0.002  0.201  0.052  0.600  0.077  0.301  0.376  0.351  0.500  0.226  0.351  0.151 -0.048  0.102  0.500  0.351  0.426 -0.147  0.077  0.401  0.102  0.351 -0.048  0.600 -0.073  0.301  0.525  0.301  0.500  0.550  0.301  0.326  0.002 -0.023 -0.172  0.077 -0.147  0.102  0.027 -0.197  0.251  0.052  0.127 -0.098  0.176  0.027 -0.048 -0.172 -0.197 -0.123  0.077  0.102 -0.048  0.052  0.176 -0.048 -0.048  0.027 -0.098  0.052  0.077 -0.023 -0.197 -0.322 -0.023  0.176 -0.048  0.102  0.301 -0.073 -0.147 -0.023 -0.073  0.201  0.151  0.127  0.027 -0.048 -0.048 -0.123 
 0.402  0.352 -0.046  0.302  0.477  0.377  0.253  0.103  0.253  0.053  0.552  0.228  0.552 -0.096  0.278  0.477  0.053 -0.146 -0.096  0.502  0.003  0.203  0.053  0.601  0.078  0.302  0.377  0.377  0.502  0.228  0.327  0.153 -0.046  0.103  0.527  0.352  0.402 -0.146  0.103  0.402  0.103  0.352 -0.046  0.601 -0.071  0.327  0.552  0.302  0.502  0.552  0.302  0.302  0.003  0.003 -0.171  0.078 -0.146  0.103  0.028 -0.196  0.253  0.053  0.128 -0.096  0.178  0.028 -0.046 -0.171 -0.196 -0.146  0.053  0.078 -0.046  0.028  0.178 -0.071 -0.046  0.028 -0.096  0.053  0.103 -0.046 -0.196 -0.320  0.003  0.178 -0.046  0.103  0.278 -0.071 -0.146 -0.021 -0.071  0.203  0.153  0.128  0.028 -0.046 -0.046 -0.121 
 0.402  0.352 -0.072  0.302  0.476  0.377  0.227  0.103  0.252  0.053  0.551  0.227  0.551 -0.097  0.277  0.476  0.053 -0.146 -0.097  0.501  0.003  0.202  0.028  0.601  0.078  0.302  0.377  0.377  0.501  0.227  0.327  0.152 -0.047  0.103  0.551  0.352  0.402 -0.146  0.078  0.402  0.103  0.352 -0.047  0.601 -0.072  0.327  0.551  0.327  0.501  0.551  0.302  0.302  0.003  0.003 -0.171  0.078 -0.146  0.103  0.028 -0.196  0.252  0.053  0.128 -0.097  0.177  0.028 -0.047 -0.171 -0.196 -0.146  0.053  0.078 -0.047  0.028  0.177 -0.072 -0.047  0.028 -0.097  0.053  0.103 -0.047 -0.196 -0.321  0.003  0.177 -0.047  0.103  0.302 -0.072 -0.122 -0.022 -0.072  0.202  0.152  0.128  0.028 -0.047 -0.047 -0.122 
 0.406  0.356 -0.067  0.306  0.506  0.381  0.257  0.107  0.257  0.007  0.506  0.232  0.556 -0.092  0.282  0.481  0.057 -0.117 -0.067  0.506  0.007  0.207  0.032  0.605  0.082  0.306  0.381  0.381  0.506  0.257  0.331  0.157 -0.017  0.107  0.556  0.356  0.431 -0.142  0.032  0.406  0.107  0.356 -0.042  0.605 -0.067  0.306  0.556  0.381  0.506  0.556  0.306  0.306  0.007  0.007 -0.167  0.082 -0.142  0.082  0.032 -0.142  0.207  0.057  0.107 -0.092  0.157  0.032 -0.042 -0.167 -0.217 -0.142  0.032  0.107 -0.017  0.007  0.182 -0.067 -0.042  0.007 -0.067  0.057  0.107 -0.042 -0.217 -0.316  0.007  0.182 -0.042  0.107  0.257 -0.067 -0.092 -0.017 -0.067  0.207  0.157  0.132  0.057 -0.042 -0.067 -0.117 
 0.324  0.299 -0.049  0.299  0.524  0.399  0.275  0.125  0.100  0.050  0.424  0.225  0.524 -0.099  0.225  0.424  0.075 -0.074 -0.074  0.449 -0.024  0.225  0.025  0.623  0.075  0.225  0.374  0.399  0.474  0.250  0.349  0.150 -0.049  0.125  0.573  0.324  0.324 -0.124  0.025  0.374  0.025  0.374  0.025  0.524 -0.099  0.299  0.573  0.374  0.549  0.474  0.250  0.200  0.050 -0.049 -0.149  0.075 -0.149  0.050  0.100 -0.074  0.175 -0.049  0.125 -0.074  0.125  0.050 -0.024 -0.124 -0.174 -0.149  0.075  0.100  0.000 -0.024  0.175  0.000  0.000 -0.024 -0.074  0.100  0.150 -0.049 -0.224 -0.249  0.000  0.050 -0.074  0.150  0.200 -0.049 -0.074  0.025  0.000  0.150  0.075  0.125  0.025 -0.049 -0.099 -0.074 
 0.228  0.253 -0.046  0.278  0.427  0.452  0.302  0.153  0.078  0.053  0.278  0.153  0.377 -0.046  0.153  0.302  0.078 -0.096 -0.121  0.402 -0.046  0.228 -0.021  0.576  0.003  0.128  0.302  0.377  0.352  0.253  0.377  0.153 -0.071  0.028  0.452  0.402  0.327 -0.121  0.003  0.377  0.078  0.377  0.078  0.502 -0.071  0.228  0.502  0.402  0.477  0.427  0.128  0.178  0.053 -0.046 -0.071 -0.021 -0.071  0.078  0.153 -0.096  0.153  0.003  0.128 -0.046  0.028 -0.021 -0.021 -0.096 -0.096 -0.071  0.128  0.078 -0.021 -0.046  0.128  0.078 -0.021 -0.021 -0.046  0.128  0.103  0.003 -0.171 -0.171  0.028 -0.046 -0.071  0.178  0.103 -0.046 -0.046  0.078  0.003  0.153 -0.071  0.128 -0.046  0.003 -0.096 -0.046 
 0.146  0.271 -0.028  0.295  0.370  0.495  0.320  0.146  0.046  0.071  0.221  0.146  0.320 -0.028  0.146  0.320  0.071 -0.078 -0.153  0.445 -0.028  0.246 -0.003  0.569 -0.028  0.121  0.320  0.370  0.246  0.196  0.370  0.171 -0.053 -0.028  0.420  0.395  0.271 -0.128 -0.003  0.395  0.046  0.395  0.071  0.470 -0.078  0.221  0.470  0.395  0.495  0.395  0.121  0.071  0.071 -0.028 -0.028 -0.028 -0.078  0.121  0.196 -0.053  0.146  0.046  0.146 -0.028  0.021 -0.003 -0.028 -0.103 -0.103 -0.053  0.121  0.021 -0.003 -0.053  0.046  0.096 -0.053 -0.053 -0.028  0.071  0.046 -0.028 -0.153 -0.153 -0.003 -0.053 -0.103  0.171  0.096 -0.028 -0.053  0.071  0.021  0.146 -0.053  0.121 -0.053  0.021 -0.078 -0.028 
 0.118  0.292 -0.007  0.267  0.342  0.491  0.292  0.118  0.018  0.093  0.118  0.142  0.242 -0.057  0.043  0.242  0.043 -0.057 -0.132  0.441 -0.007  0.242 -0.032  0.566 -0.007  0.118  0.342  0.392  0.167  0.192  0.367  0.167 -0.032 -0.057  0.367  0.417  0.167 -0.107 -0.032  0.342  0.068  0.417  0.043  0.367 -0.057  0.242  0.466  0.317  0.491  0.367  0.018  0.093  0.093 -0.032 -0.007 -0.057 -0.082  0.068  0.217 -0.032  0.142  0.068  0.142 -0.007 -0.007 -0.007 -0.032 -0.107 -0.082 -0.032  0.142  0.018 -0.007 -0.007  0.043  0.093 -0.057 -0.057 -0.007  0.018  0.043 -0.032 -0.132 -0.132 -0.007 -0.057 -0.082  0.192 -0.007 -0.007 -0.057  0.093 -0.007  0.118 -0.057  0.142 -0.032 -0.007 -0.082 -0.057 
 0.103  0.277  0.003  0.227  0.277  0.476  0.302  0.128  0.028  0.078  0.128  0.128  0.227 -0.072  0.028  0.177  0.053 -0.047 -0.122  0.451  0.003  0.252 -0.022  0.551 -0.022  0.128  0.352  0.402  0.152  0.202  0.277  0.152 -0.022 -0.072  0.327  0.426  0.177 -0.097 -0.022  0.277 -0.022  0.426  0.053  0.377 -0.022  0.252  0.426  0.302  0.501  0.377  0.003  0.103  0.103 -0.022 -0.022 -0.047 -0.072  0.028  0.227 -0.022  0.152  0.053  0.128 -0.022  0.003  0.003 -0.047 -0.097 -0.097 -0.022  0.177  0.003  0.003  0.003  0.028  0.078 -0.047 -0.047  0.003  0.003  0.053 -0.072 -0.122 -0.122 -0.072 -0.047 -0.072  0.152  0.003  0.003 -0.047  0.103  0.003  0.103 -0.047  0.128 -0.047 -0.022 -0.097 -0.072 
 0.065  0.265  0.015  0.215  0.215  0.489  0.314  0.115  0.015  0.090  0.115  0.115  0.240 -0.059  0.040  0.140  0.040 -0.034 -0.084  0.439 -0.009  0.265 -0.009  0.539 -0.009  0.140  0.339  0.414  0.115  0.190  0.265  0.090 -0.009 -0.059  0.314  0.414  0.165 -0.084 -0.034  0.240 -0.034  0.439  0.090  0.289 -0.009  0.265  0.389  0.314  0.514  0.364  0.015  0.065  0.090 -0.009 -0.009 -0.059 -0.084  0.040  0.190 -0.009  0.090  0.065  0.115 -0.009  0.015  0.015 -0.059 -0.084 -0.084 -0.009  0.165 -0.059  0.040 -0.034  0.040  0.090 -0.059 -0.034  0.015  0.015  0.015 -0.059 -0.109 -0.109 -0.059 -0.034 -0.084  0.140 -0.009  0.015 -0.034  0.090  0.015  0.090 -0.034  0.140 -0.059 -0.009 -0.084 -0.084 
 0.021  0.246  0.021  0.196  0.196  0.420  0.271  0.121  0.021  0.096  0.121  0.096  0.246 -0.053  0.046  0.146  0.021 -0.028 -0.103  0.445 -0.003  0.271 -0.003  0.545 -0.003  0.146  0.320  0.420  0.096  0.196  0.246  0.071 -0.003 -0.078  0.320  0.395  0.171 -0.078 -0.028  0.246 -0.028  0.445  0.096  0.246 -0.028  0.246  0.395  0.295  0.520  0.271  0.021  0.071  0.096 -0.053 -0.028 -0.053 -0.078  0.021  0.196 -0.028  0.071  0.021  0.096 -0.003 -0.003  0.021 -0.053 -0.078 -0.078 -0.003  0.146 -0.053  0.021 -0.028  0.046  0.096 -0.053 -0.028 -0.028  0.021  0.021 -0.053 -0.103 -0.103 -0.053 -0.028 -0.078  0.146 -0.028  0.021 -0.028  0.096  0.021  0.096 -0.028  0.146 -0.053 -0.003 -0.078 -0.103 
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FILE: hippocampus/out/oscillation/baseline_msparse.txt
================================================
 0.967  0.020 -0.029 -0.004 -0.029 -0.029  0.020 -0.004 -0.029 -0.004  0.020 -0.004 -0.029 -0.004 -0.029 -0.004 -0.029  0.045 -0.004 -0.029 -0.004 -0.004 -0.004 -0.029  0.020 -0.004  0.045 -0.029 -0.004 -0.004 -0.004 -0.029  0.020 -0.004  0.070 -0.004 -0.029 -0.004  0.045 -0.004 -0.029  0.020  0.070 -0.029 -0.029 -0.004  0.045 -0.004  0.020 -0.029 
 0.973  0.026 -0.024 -0.024 -0.024 -0.024  0.026  0.001 -0.024  0.001  0.001  0.001 -0.024  0.001 -0.024  0.001 -0.024  0.051  0.001 -0.024  0.001  0.001  0.001 -0.024  0.026  0.001  0.051 -0.024  0.001 -0.024  0.001 -0.024  0.026 -0.024  0.026  0.001 -0.024  0.001  0.026  0.001 -0.024  0.026  0.076 -0.024 -0.024  0.001  0.051  0.001  0.001 -0.024 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 1.001  0.029 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.004 
 0.999  0.103 -0.022 -0.022 -0.022 -0.022  0.028 -0.022 -0.022  0.003  0.003  0.003 -0.022  0.003 -0.022  0.003 -0.022  0.028  0.003 -0.022  0.003 -0.022  0.003 -0.022  0.028  0.003  0.053 -0.022  0.028 -0.022  0.003 -0.022  0.028 -0.022  0.003  0.003 -0.022  0.003  0.028  0.003 -0.022  0.003  0.078 -0.022 -0.022 -0.022  0.078  0.003 -0.022  0.003 
 0.997  0.101 -0.024 -0.024 -0.024 -0.024  0.026 -0.024 -0.024  0.001  0.001  0.001 -0.024  0.001 -0.024  0.026 -0.024  0.026  0.001 -0.024  0.001 -0.024  0.001 -0.024  0.051  0.001  0.051 -0.024  0.026 -0.024  0.001 -0.024  0.026 -0.024  0.001  0.001 -0.024  0.001  0.026  0.001 -0.024  0.001  0.076 -0.024 -0.024  0.001  0.076  0.001 -0.024  0.026 
 0.990  0.093 -0.031 -0.031 -0.006 -0.031  0.018 -0.006 -0.006  0.018 -0.006  0.018 -0.031 -0.006 -0.031  0.043 -0.031  0.043  0.018 -0.031 -0.006 -0.006 -0.006 -0.031  0.043 -0.006  0.043 -0.006  0.018 -0.006  0.018  0.018  0.068 -0.031 -0.006  0.068 -0.031 -0.006  0.018  0.018 -0.031 -0.006  0.118  0.018 -0.031  0.018  0.068 -0.006 -0.031  0.018 
 0.976  0.129 -0.045 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.045  0.079 -0.045  0.054  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.004  0.029  0.004  0.079  0.054  0.029  0.004  0.154  0.004  0.054  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.104  0.004 -0.045  0.054  0.079 -0.020 -0.020  0.004 
 0.954  0.256 -0.018  0.107  0.082 -0.043  0.057 -0.043 -0.043  0.007 -0.043  0.032  0.032 -0.018 -0.018  0.206 -0.043  0.057  0.007  0.007  0.007  0.107  0.007  0.007  0.057  0.007  0.156  0.107  0.082  0.181  0.057  0.032  0.306 -0.018  0.156  0.156 -0.018 -0.043  0.007  0.007  0.032  0.032  0.181 -0.018 -0.068  0.082  0.181  0.007  0.107  0.057 
 0.892  0.269 -0.005  0.219  0.294 -0.005  0.219  0.070  0.020  0.070 -0.105 -0.030  0.020 -0.080 -0.030  0.244 -0.080  0.120 -0.005 -0.005 -0.030  0.369  0.045 -0.055  0.070 -0.005  0.269  0.144  0.244  0.394  0.169 -0.005  0.568  0.020  0.344  0.319  0.045 -0.105 -0.030  0.045 -0.005  0.020  0.269 -0.055 -0.105  0.095  0.344  0.144  0.369  0.194 
 0.827  0.279  0.079  0.204  0.428  0.054  0.254  0.104  0.079  0.054 -0.020 -0.045  0.129 -0.145 -0.095  0.353 -0.095  0.179 -0.020  0.029 -0.070  0.428  0.029 -0.070  0.104  0.054  0.378  0.079  0.428  0.528  0.254 -0.045  0.602  0.054  0.428  0.403  0.004 -0.095 -0.070  0.029 -0.020  0.029  0.303 -0.070 -0.045  0.303  0.528  0.303  0.503  0.328 
 0.734  0.386  0.186  0.361  0.560  0.186  0.311  0.137  0.137  0.161 -0.038 -0.038  0.236 -0.162 -0.138  0.361 -0.113  0.286 -0.038  0.037 -0.063  0.386  0.012 -0.013  0.062  0.087  0.435  0.186  0.510  0.560  0.311 -0.013  0.685  0.037  0.510  0.435  0.062 -0.138 -0.088  0.062  0.012  0.137  0.361  0.037 -0.038  0.485  0.685  0.336  0.585  0.460 
 0.639  0.390  0.290  0.415  0.589  0.290  0.315  0.240  0.116  0.190 -0.009  0.016  0.240 -0.158 -0.109  0.464 -0.109  0.265 -0.059  0.091 -0.059  0.340 -0.034  0.066 -0.009  0.091  0.439  0.265  0.564  0.514  0.315  0.016  0.614  0.066  0.539  0.464  0.066 -0.158 -0.059  0.066  0.091  0.290  0.390  0.165 -0.034  0.489  0.689  0.365  0.564  0.564 
 0.586  0.387  0.337  0.412  0.611  0.362  0.312  0.263  0.113  0.238 -0.011  0.013  0.263 -0.136 -0.111  0.462 -0.061  0.213 -0.111  0.138 -0.086  0.312 -0.011  0.113 -0.011  0.113  0.462  0.337  0.537  0.487  0.337 -0.011  0.611  0.038  0.562  0.462  0.138 -0.211 -0.061  0.113  0.113  0.312  0.312  0.337  0.038  0.512  0.661  0.362  0.611  0.586 
 0.581  0.357  0.332  0.407  0.606  0.382  0.332  0.258  0.108  0.258  0.008  0.033  0.332 -0.166 -0.091  0.482 -0.066  0.183 -0.066  0.233 -0.091  0.258  0.008  0.158 -0.016  0.133  0.457  0.357  0.557  0.482  0.332  0.033  0.532  0.083  0.557  0.482  0.133 -0.216 -0.091  0.208  0.108  0.283  0.258  0.332  0.033  0.532  0.656  0.357  0.581  0.606 
 0.503  0.353  0.353  0.428  0.627  0.403  0.279  0.279  0.154  0.303  0.079  0.029  0.378 -0.170 -0.045  0.478 -0.045  0.154 -0.070  0.353 -0.095  0.229  0.029  0.328  0.004  0.179  0.478  0.353  0.528  0.453  0.328  0.029  0.478  0.129  0.553  0.453  0.229 -0.220 -0.020  0.254  0.154  0.328  0.204  0.328 -0.020  0.503  0.652  0.378  0.553  0.602 
 0.428  0.379  0.354  0.453  0.628  0.404  0.279  0.279  0.154  0.304  0.105  0.030  0.404 -0.120 -0.045  0.453 -0.070  0.105 -0.070  0.453 -0.095  0.229  0.005  0.404  0.005  0.179  0.478  0.379  0.528  0.379  0.329  0.030  0.478  0.130  0.528  0.478  0.229 -0.194 -0.020  0.254  0.154  0.329  0.204  0.354 -0.045  0.478  0.628  0.379  0.528  0.603 
 0.373  0.373  0.348  0.423  0.622  0.398  0.298  0.274  0.124  0.298  0.099  0.049  0.473 -0.125 -0.025  0.448 -0.075  0.099 -0.075  0.548 -0.125  0.224 -0.000  0.473 -0.025  0.174  0.473  0.373  0.523  0.348  0.323  0.024  0.423  0.099  0.523  0.448  0.249 -0.175 -0.000  0.249  0.174  0.398  0.199  0.398 -0.075  0.473  0.622  0.373  0.523  0.597 
 0.375  0.325  0.350  0.350  0.624  0.400  0.300  0.276  0.126  0.300  0.101  0.051  0.500 -0.123 -0.023  0.450 -0.073  0.076 -0.048  0.550 -0.123  0.226  0.001  0.475 -0.023  0.126  0.475  0.400  0.525  0.276  0.325  0.026  0.425  0.101  0.525  0.450  0.251 -0.198  0.026  0.251  0.251  0.375  0.201  0.400 -0.073  0.475  0.624  0.375  0.550  0.550 
 0.376  0.326  0.351  0.351  0.625  0.426  0.326  0.277  0.152  0.301  0.127  0.077  0.501 -0.122  0.027  0.451 -0.072  0.077 -0.047  0.551 -0.122  0.227 -0.022  0.526 -0.022  0.127  0.451  0.401  0.526  0.227  0.326  0.052  0.451  0.077  0.501  0.451  0.326 -0.172  0.077  0.252  0.252  0.401  0.202  0.451 -0.072  0.476  0.625  0.351  0.526  0.575 
 0.376  0.326  0.351  0.351  0.625  0.451  0.326  0.277  0.152  0.301  0.152  0.027  0.501 -0.122  0.052  0.451 -0.072  0.052 -0.072  0.551 -0.097  0.227  0.027  0.551 -0.022  0.127  0.501  0.401  0.526  0.177  0.326  0.052  0.451  0.077  0.501  0.451  0.326 -0.172  0.077  0.252  0.227  0.426  0.152  0.476 -0.097  0.476  0.625  0.351  0.501  0.600 
 0.373  0.323  0.348  0.373  0.597  0.448  0.348  0.274  0.124  0.298  0.149  0.024  0.498 -0.075  0.074  0.448 -0.100  0.049 -0.075  0.548 -0.075  0.224  0.024  0.572 -0.075  0.124  0.498  0.398  0.473  0.174  0.323  0.074  0.448  0.074  0.523  0.523  0.348 -0.150  0.099  0.249  0.224  0.448  0.174  0.548 -0.100  0.473  0.597  0.348  0.498  0.622 
 0.373  0.348  0.348  0.423  0.572  0.448  0.348  0.249  0.124  0.298  0.174  0.074  0.498 -0.075  0.099  0.448 -0.075  0.049 -0.100  0.548 -0.050  0.224  0.024  0.572 -0.075  0.099  0.448  0.398  0.423  0.199  0.323  0.074  0.448  0.074  0.498  0.523  0.348 -0.150  0.099  0.249  0.224  0.448  0.174  0.548 -0.125  0.473  0.597  0.373  0.498  0.597 
 0.376  0.351  0.326  0.426  0.550  0.450  0.351  0.226  0.127  0.301  0.176  0.102  0.500 -0.073  0.151  0.475 -0.073  0.052 -0.123  0.550 -0.048  0.226  0.102  0.600 -0.073  0.102  0.426  0.401  0.426  0.201  0.301  0.077  0.450  0.077  0.500  0.525  0.351 -0.197  0.102  0.251  0.201  0.475  0.176  0.525 -0.123  0.475  0.600  0.376  0.475  0.525 
 0.242  0.317  0.342  0.417  0.541  0.342  0.317  0.217  0.142  0.242  0.192  0.068  0.441 -0.057  0.118  0.491 -0.082  0.093 -0.132  0.541 -0.007  0.267  0.118  0.566 -0.032  0.118  0.466  0.367  0.466  0.167  0.342  0.068  0.441  0.093  0.491  0.516  0.392 -0.181  0.093  0.192  0.142  0.466  0.192  0.491 -0.057  0.441  0.591  0.392  0.417  0.342 
 0.103  0.278  0.327  0.278  0.477  0.352  0.302  0.228  0.128  0.253  0.178  0.078  0.352  0.003  0.053  0.427 -0.021  0.053 -0.121  0.427 -0.021  0.253 -0.046  0.502  0.003  0.128  0.377  0.377  0.452  0.178  0.327  0.103  0.302  0.053  0.477  0.477  0.302 -0.121  0.028  0.203  0.128  0.427  0.178  0.402  0.003  0.377  0.576  0.278  0.427  0.327 
 0.076  0.251  0.350  0.300  0.375  0.325  0.276  0.176  0.126  0.201  0.126  0.126  0.300 -0.023  0.026  0.325 -0.023  0.051 -0.098  0.400 -0.023  0.251 -0.023  0.475  0.001  0.126  0.350  0.350  0.475  0.151  0.350  0.076  0.251  0.026  0.500  0.425  0.251 -0.098  0.001  0.151  0.076  0.425  0.176  0.400 -0.073  0.300  0.574  0.251  0.425  0.300 
 0.076  0.250  0.275  0.275  0.325  0.325  0.225  0.150  0.101  0.175  0.051  0.150  0.225 -0.049  0.001  0.225  0.001  0.076 -0.074  0.350 -0.024  0.275 -0.024  0.449  0.026  0.126  0.375  0.375  0.449  0.175  0.225  0.051  0.150 -0.099  0.499  0.425  0.126 -0.099 -0.024  0.126  0.026  0.425  0.126  0.300 -0.074  0.275  0.574  0.200  0.474  0.225 
 0.086  0.235  0.260  0.285  0.310  0.310  0.235  0.160  0.011  0.185  0.036  0.160  0.235 -0.064  0.011  0.185  0.011  0.036 -0.064  0.335 -0.014  0.285 -0.014  0.410 -0.014  0.136  0.385  0.385  0.360  0.185  0.160  0.061  0.086 -0.089  0.509  0.459  0.136 -0.089 -0.014  0.136  0.011  0.410  0.136  0.285 -0.064  0.260  0.534  0.235  0.509  0.235 
 0.023  0.123  0.247  0.222  0.322  0.322  0.197  0.172  0.023  0.172  0.048  0.147  0.222 -0.077  0.023  0.123  0.023 -0.027 -0.077  0.247 -0.002  0.297 -0.002  0.297 -0.052  0.147  0.347  0.397  0.322  0.222  0.172  0.073  0.048 -0.077  0.521  0.446  0.147 -0.077 -0.002  0.073 -0.002  0.422  0.147  0.247 -0.052  0.272  0.496  0.197  0.546  0.247 
 0.030  0.105  0.255  0.205  0.280  0.354  0.205  0.180  0.005  0.155  0.030  0.130  0.230 -0.069  0.030  0.105  0.030 -0.044 -0.094  0.205  0.005  0.255  0.005  0.230 -0.044  0.105  0.329  0.429  0.304  0.230  0.180  0.055  0.055 -0.069  0.454  0.479  0.155 -0.069 -0.044  0.055  0.005  0.379  0.130  0.255 -0.044  0.255  0.479  0.205  0.554  0.230 
-0.008  0.116  0.266  0.191  0.216  0.415  0.216  0.191  0.016  0.166  0.041  0.116  0.241 -0.058  0.066  0.066 -0.008 -0.033 -0.083  0.141  0.016  0.241  0.016  0.091 -0.033  0.116  0.290  0.440  0.266  0.290  0.141  0.066  0.016 -0.033  0.440  0.565  0.166 -0.058 -0.033  0.066  0.016  0.365  0.141  0.266 -0.033  0.191  0.465  0.191  0.540  0.216 
 0.002  0.127  0.277  0.177  0.202  0.401  0.227  0.202  0.027  0.177  0.027  0.102  0.252 -0.047  0.052  0.027 -0.022 -0.022 -0.072  0.077  0.027  0.227  0.027  0.052 -0.022  0.127  0.277  0.376  0.252  0.301  0.152  0.077  0.027 -0.022  0.351  0.575  0.152 -0.047 -0.022 -0.022  0.002  0.301  0.127  0.127 -0.022  0.102  0.426  0.152  0.426  0.202 
 0.013  0.113  0.238  0.163  0.188  0.437  0.213  0.188 -0.011  0.138  0.038  0.088  0.238 -0.036  0.038  0.013 -0.011 -0.011 -0.061  0.013  0.038  0.213  0.013 -0.011 -0.011  0.138  0.188  0.312  0.238  0.312  0.113  0.088  0.038 -0.036  0.312  0.611  0.138 -0.036 -0.011 -0.011  0.013  0.163  0.138  0.113 -0.036  0.088  0.437  0.138  0.437  0.188 
 0.021  0.121  0.121  0.145  0.170  0.444  0.245  0.121 -0.004  0.145  0.021  0.096  0.195 -0.029  0.046  0.021 -0.004 -0.004 -0.054 -0.004  0.046  0.195  0.021 -0.004 -0.004  0.121  0.170  0.270  0.195  0.295  0.071  0.096  0.021 -0.029  0.245  0.644  0.071 -0.029 -0.004 -0.029 -0.029  0.145  0.145  0.121 -0.029  0.096  0.370  0.121  0.395  0.220 
-0.011  0.013  0.013  0.163  0.088  0.337  0.213  0.088  0.013  0.088  0.038  0.113  0.163 -0.011  0.038  0.038 -0.011  0.013 -0.036  0.013  0.013  0.088  0.013 -0.011  0.013  0.113  0.088  0.213  0.088  0.263  0.063  0.088  0.013 -0.011  0.138  0.661  0.013 -0.011 -0.011 -0.036 -0.011  0.013  0.113  0.063 -0.036  0.088  0.213  0.063  0.263  0.138 
 0.000  0.000  0.000  0.100  0.075  0.250  0.175  0.075  0.025  0.050  0.025  0.050  0.075  0.000  0.050  0.000 -0.024  0.000 -0.024  0.000  0.025  0.050  0.025 -0.024  0.025  0.025  0.100  0.100  0.075  0.125  0.050  0.075  0.000  0.000  0.125  0.648  0.025 -0.024  0.000 -0.024  0.000  0.025  0.050  0.000 -0.024  0.025  0.125  0.025  0.075  0.075 
 0.011 -0.014  0.011  0.011  0.036  0.086  0.111  0.061 -0.014  0.011  0.011 -0.014  0.011  0.011  0.036  0.011 -0.014  0.011 -0.014 -0.014  0.011  0.011  0.011 -0.014  0.036  0.011  0.036  0.061  0.086  0.036  0.011  0.036  0.011 -0.014  0.061  0.634 -0.014 -0.014 -0.014 -0.014  0.011  0.011  0.036  0.011 -0.014  0.011  0.011  0.036  0.036  0.036 
 0.010  0.010  0.010  0.010  0.035  0.085  0.110  0.060 -0.015  0.010  0.010 -0.015  0.010  0.010  0.035  0.010 -0.015  0.010 -0.015 -0.015  0.010  0.010  0.010 -0.015  0.035  0.010  0.035  0.060  0.085  0.035  0.010  0.060  0.010 -0.015  0.060  0.683 -0.015 -0.015 -0.015 -0.015  0.010  0.010  0.010  0.035 -0.015  0.010  0.010  0.035  0.035  0.035 
 0.007  0.032  0.007  0.032  0.032  0.082  0.082  0.057 -0.017  0.007  0.007 -0.017  0.007  0.032  0.007  0.007  0.007  0.007 -0.017 -0.017  0.007  0.007  0.007 -0.017  0.032  0.007  0.032  0.007  0.057  0.007 -0.017  0.057  0.007 -0.017  0.032  0.854  0.007 -0.017 -0.017 -0.017  0.007  0.007  0.007  0.057 -0.017  0.007  0.007  0.032 -0.017  0.032 
 0.006  0.031  0.006  0.031  0.031  0.081  0.081  0.056 -0.019  0.006  0.006 -0.019  0.006  0.031  0.006  0.006  0.006  0.006 -0.019 -0.019  0.006  0.006  0.006 -0.019  0.031  0.006  0.031  0.006  0.056  0.006 -0.019  0.056  0.006 -0.019  0.031  0.928  0.006 -0.019 -0.019 -0.019  0.006  0.006  0.006  0.056 -0.019  0.006  0.006  0.031 -0.019  0.031 
 0.004  0.029  0.004  0.029  0.029  0.079  0.079  0.054 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020  0.054  0.004 -0.020  0.029  1.001  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004  0.004  0.029 -0.020  0.029 
 0.004  0.029  0.004  0.029  0.029  0.079  0.079  0.054 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020  0.054  0.004 -0.020  0.029  1.001  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004  0.004  0.029 -0.020  0.029 
 0.004  0.029  0.004  0.029  0.029  0.079  0.079  0.054 -0.020  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020  0.054  0.004 -0.020  0.029  1.001  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004  0.004  0.029 -0.020  0.029 
 0.025  0.025  0.000  0.025  0.025  0.075  0.100  0.050  0.000  0.000  0.000 -0.024  0.025  0.025  0.000  0.000  0.000  0.025 -0.024 -0.024  0.000  0.000  0.025 -0.024  0.025  0.000  0.075  0.000  0.050  0.025 -0.024  0.050  0.000 -0.024  0.025  0.997  0.000 -0.024 -0.024 -0.024  0.025  0.000  0.025  0.050 -0.024  0.025  0.000  0.025 -0.024  0.025 
 0.051  0.026  0.001  0.101  0.051  0.200  0.250  0.101 -0.024  0.026  0.076 -0.024  0.126  0.051  0.051 -0.024  0.001  0.001 -0.049 -0.049  0.026 -0.024  0.001 -0.049  0.101  0.001  0.150 -0.024  0.076  0.101 -0.049  0.101  0.001  0.051  0.051  0.973  0.076 -0.049  0.051  0.001  0.076  0.001  0.101  0.076 -0.024  0.076  0.001  0.026 -0.049  0.101 
 0.033 -0.017 -0.017  0.157  0.108  0.357  0.506  0.207 -0.017  0.033  0.033  0.033  0.307  0.157  0.108 -0.017  0.008 -0.042 -0.067 -0.067  0.033 -0.017  0.058 -0.067  0.133  0.008  0.232  0.033  0.058  0.182 -0.092  0.133  0.033  0.058  0.133  0.930  0.157 -0.067  0.033  0.033  0.157  0.008  0.083  0.182 -0.017  0.207  0.033  0.133 -0.092  0.232 
 0.275  0.000 -0.024  0.125  0.324  0.449  0.823  0.324 -0.024  0.150  0.075  0.100  0.524  0.150  0.175 -0.074  0.000 -0.049 -0.124  0.050  0.150 -0.024  0.075  0.000  0.125  0.050  0.374  0.100  0.100  0.225 -0.049  0.200  0.050  0.100  0.150  0.848  0.374 -0.024  0.025  0.050  0.150  0.000  0.175  0.275 -0.024  0.324  0.100  0.150  0.000  0.349 
 0.249 -0.000  0.149  0.124  0.373  0.473  0.797  0.348 -0.000  0.224  0.049  0.099  0.622  0.124  0.249 -0.075 -0.000 -0.100 -0.175  0.174  0.224 -0.050  0.124  0.024  0.074  0.049  0.423  0.174  0.074  0.348  0.074  0.224  0.074  0.099  0.149  0.797  0.398 -0.025 -0.000  0.049  0.174  0.099  0.149  0.373 -0.000  0.423  0.249  0.099  0.124  0.498 
 0.291  0.042  0.242  0.092  0.541  0.441  0.715  0.366  0.017  0.291  0.067  0.167  0.566  0.167  0.217 -0.032 -0.007 -0.107 -0.232  0.316  0.167  0.117  0.192  0.167  0.117  0.017  0.466  0.267  0.067  0.316  0.217  0.341  0.117  0.092  0.192  0.715  0.491 -0.082 -0.007  0.092  0.142  0.142  0.217  0.441 -0.007  0.491  0.516  0.092  0.242  0.590 
 0.328  0.104  0.279  0.129  0.577  0.453  0.677  0.328  0.079  0.303  0.179  0.204  0.528  0.179  0.204  0.029 -0.020 -0.120 -0.220  0.428  0.129  0.104  0.229  0.303  0.129  0.004  0.478  0.303  0.129  0.328  0.229  0.328  0.054  0.129  0.179  0.652  0.528 -0.095 -0.020  0.104  0.104  0.154  0.279  0.478 -0.020  0.478  0.528  0.079  0.279  0.528 
 0.306  0.182  0.257  0.132  0.580  0.406  0.556  0.306  0.107  0.306  0.257  0.182  0.481  0.157  0.232  0.082 -0.017 -0.067 -0.242  0.456  0.107  0.132  0.257  0.431  0.107  0.032  0.506  0.282  0.232  0.331  0.331  0.306  0.057  0.182  0.207  0.605  0.531 -0.092 -0.017  0.232  0.132  0.182  0.306  0.531 -0.017  0.481  0.605  0.182  0.356  0.506 
 0.303  0.178  0.253  0.129  0.577  0.403  0.552  0.303  0.129  0.378  0.278  0.153  0.477  0.129  0.228  0.153  0.004 -0.071 -0.245  0.502  0.079  0.129  0.278  0.452  0.129  0.029  0.502  0.278  0.228  0.278  0.328  0.303  0.054  0.203  0.253  0.577  0.527 -0.071 -0.046  0.228  0.153  0.203  0.303  0.527 -0.046  0.477  0.602  0.203  0.403  0.477 
 0.274  0.199  0.224  0.149  0.498  0.398  0.523  0.298  0.124  0.423  0.298  0.149  0.448  0.074  0.224  0.348  0.024 -0.050 -0.275  0.498  0.074  0.124  0.323  0.473  0.124  0.049  0.473  0.249  0.298  0.249  0.323  0.298  0.024  0.174  0.348  0.572  0.498 -0.075  0.049  0.249  0.149  0.224  0.298  0.572 -0.050  0.473  0.622  0.174  0.398  0.473 
 0.270  0.170  0.220  0.195  0.494  0.420  0.494  0.295  0.121  0.420  0.320  0.145  0.444  0.071  0.245  0.420  0.046 -0.029 -0.278  0.494  0.071  0.121  0.320  0.469  0.096  0.046  0.420  0.245  0.270  0.220  0.320  0.295  0.046  0.170  0.370  0.594  0.494 -0.104  0.096  0.270  0.145  0.245  0.245  0.569 -0.054  0.494  0.644  0.220  0.420  0.469 
 0.243  0.193  0.243  0.193  0.467  0.417  0.492  0.268  0.093  0.467  0.367  0.168  0.442  0.068  0.268  0.467  0.068 -0.031 -0.281  0.517  0.043  0.118  0.292  0.467  0.043  0.068  0.367  0.243  0.268  0.243  0.317  0.292  0.043  0.168  0.367  0.591  0.492 -0.131  0.093  0.342  0.118  0.243  0.193  0.567 -0.031  0.492  0.666  0.243  0.467  0.467 
 0.216  0.191  0.241  0.191  0.465  0.416  0.490  0.266  0.092  0.490  0.366  0.166  0.440  0.067  0.266  0.490  0.067 -0.033 -0.282  0.515 -0.008  0.117  0.241  0.540  0.042  0.067  0.366  0.241  0.266  0.191  0.316  0.291  0.042  0.166  0.366  0.590  0.565 -0.133  0.092  0.341  0.117  0.266  0.142  0.565 -0.033  0.490  0.640  0.241  0.465  0.465 
 0.217  0.192  0.267  0.217  0.441  0.441  0.491  0.242  0.093  0.491  0.367  0.167  0.441  0.068  0.317  0.541  0.018 -0.057 -0.256  0.516 -0.007  0.118  0.242  0.566 -0.007  0.068  0.342  0.267  0.292  0.167  0.292  0.267  0.068  0.167  0.367  0.541  0.566 -0.132  0.118  0.367  0.068  0.292  0.118  0.566 -0.032  0.491  0.641  0.242  0.466  0.441 
 0.194  0.194  0.269  0.244  0.443  0.443  0.493  0.244  0.094  0.493  0.368  0.169  0.443  0.069  0.343  0.543  0.019 -0.055 -0.255  0.518  0.019  0.119  0.219  0.568  0.019  0.119  0.343  0.244  0.293  0.169  0.293  0.269  0.069  0.169  0.368  0.518  0.568 -0.130  0.119  0.368  0.069  0.293  0.069  0.568 -0.055  0.468  0.642  0.244  0.468  0.443 
 0.194  0.219  0.294  0.244  0.419  0.419  0.468  0.269  0.095  0.543  0.369  0.219  0.443  0.045  0.344  0.543  0.020 -0.055 -0.254  0.518  0.045  0.144  0.169  0.568  0.045  0.144  0.369  0.244  0.344  0.120  0.269  0.269  0.070  0.169  0.419  0.493  0.568 -0.130  0.120  0.344  0.070  0.294  0.045  0.568 -0.055  0.468  0.643  0.244  0.468  0.443 
 0.194  0.244  0.294  0.244  0.419  0.419  0.468  0.269  0.095  0.543  0.369  0.219  0.443  0.045  0.344  0.543  0.020 -0.055 -0.254  0.518  0.045  0.144  0.169  0.568  0.070  0.144  0.369  0.269  0.344  0.120  0.269  0.244  0.095  0.194  0.419  0.493  0.568 -0.130  0.120  0.344  0.070  0.294  0.045  0.568 -0.055  0.493  0.643  0.244  0.468  0.443 
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 0.995 -0.001  0.024 -0.026  0.049 -0.001  0.074  0.024  0.074 -0.001  0.024  0.024 -0.001 -0.026 -0.026 -0.001 -0.001  0.074 -0.026  0.024  0.024  0.024  0.024 -0.026 -0.026 -0.001 -0.001 -0.001  0.099  0.024 -0.001 -0.026  0.099 -0.026 -0.026 -0.001 -0.001 -0.001 -0.001 -0.001 -0.026 -0.001  0.049 -0.001 -0.001  0.024  0.049 -0.001  0.024 -0.001 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 1.001  0.004  0.004 -0.020  0.004  0.004  0.079  0.029  0.054  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.029  0.029  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.104  0.004  0.004 -0.020  0.104 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.054 -0.020  0.004  0.029  0.004 -0.020  0.029  0.004 
 0.998  0.002  0.002 -0.023  0.002  0.002  0.102  0.027  0.077  0.002  0.002  0.027  0.002 -0.023 -0.023  0.002  0.002  0.052 -0.023  0.027  0.027  0.027  0.002 -0.023 -0.023  0.002 -0.023  0.027  0.201  0.002  0.002 -0.023  0.127 -0.023 -0.023  0.027  0.002  0.002  0.002  0.002 -0.023  0.002  0.052 -0.023  0.002  0.027  0.002  0.002  0.027  0.002 
 0.992 -0.004 -0.004 -0.029 -0.004 -0.004  0.145  0.045  0.195 -0.004 -0.004  0.020 -0.004 -0.029 -0.029 -0.004 -0.004  0.045 -0.029  0.045  0.070  0.070 -0.004 -0.029 -0.029 -0.004 -0.029  0.095  0.294 -0.004  0.020 -0.029  0.145 -0.004 -0.004  0.020 -0.004 -0.004 -0.004 -0.004 -0.029 -0.004  0.045 -0.029  0.020  0.020  0.020 -0.004  0.070 -0.004 
 0.975  0.028  0.003  0.003  0.003 -0.021  0.228  0.078  0.228 -0.021 -0.021  0.028  0.003 -0.046 -0.021  0.003 -0.021  0.028 -0.046  0.053  0.053  0.053 -0.021 -0.046 -0.046  0.003 -0.021  0.128  0.651  0.003  0.003 -0.046  0.128  0.053  0.003  0.053  0.003 -0.021 -0.021  0.003 -0.021  0.003  0.053 -0.046  0.003  0.053  0.028  0.003  0.103  0.003 
 0.936  0.089  0.039 -0.010  0.014 -0.035  0.538  0.164  0.488  0.014  0.014  0.114  0.064 -0.035 -0.010  0.039 -0.035 -0.010 -0.035  0.089  0.064  0.064 -0.060 -0.010 -0.085  0.039 -0.035  0.338  0.936  0.014 -0.010 -0.085  0.139  0.039  0.014  0.139 -0.035 -0.010 -0.035 -0.010 -0.060  0.014  0.089 -0.060  0.014  0.114  0.039  0.039  0.164  0.139 
 0.898  0.101  0.150  0.001 -0.024 -0.024  0.723  0.225  0.649 -0.024  0.001  0.225  0.126 -0.024  0.076  0.026 -0.049 -0.024  0.001  0.076  0.051  0.101 -0.074  0.026 -0.049  0.001  0.026  0.425  0.898  0.051  0.001 -0.074  0.150  0.051  0.001  0.175 -0.074 -0.024 -0.074 -0.024 -0.024  0.001  0.076 -0.049 -0.024  0.150  0.101  0.126  0.449  0.225 
 0.827  0.229  0.254  0.005 -0.020  0.055  0.827  0.279  0.777  0.080 -0.020  0.304  0.304 -0.045  0.130  0.080 -0.045  0.030  0.030  0.229  0.030  0.154 -0.070  0.154 -0.045  0.130  0.204  0.703  0.827  0.080  0.030  0.030  0.154  0.005  0.130  0.329 -0.020 -0.070 -0.020 -0.020  0.080  0.030  0.179  0.005 -0.045  0.254  0.229  0.204  0.703  0.304 
 0.796  0.223  0.297  0.098  0.073  0.023  0.771  0.273  0.721  0.098  0.098  0.297  0.347 -0.076  0.198  0.173  0.023  0.048  0.023  0.397 -0.001  0.223 -0.076  0.248 -0.051  0.123  0.322  0.696  0.796  0.073  0.148  0.023  0.223  0.048  0.173  0.372 -0.001 -0.101  0.073  0.048  0.123  0.098  0.148  0.023 -0.051  0.322  0.347  0.297  0.721  0.322 
 0.745  0.222  0.247  0.122  0.097  0.197  0.670  0.296  0.645  0.172  0.122  0.346  0.421 -0.052  0.197  0.197  0.047  0.022 -0.002  0.546 -0.002  0.296 -0.027  0.421 -0.002  0.172  0.446  0.670  0.745  0.122  0.147  0.097  0.222  0.072  0.272  0.446  0.097 -0.127  0.047  0.222  0.122  0.247  0.147  0.172 -0.002  0.446  0.546  0.321  0.695  0.446 
 0.683  0.235  0.260  0.110  0.135  0.260  0.583  0.409  0.559  0.160  0.210  0.334  0.434 -0.064  0.185  0.235  0.110 -0.014 -0.014  0.559 -0.014  0.284 -0.039  0.509  0.060  0.210  0.434  0.633  0.683  0.135  0.160  0.110  0.210  0.135  0.384  0.484  0.110 -0.139  0.060  0.235  0.160  0.284  0.135  0.210  0.035  0.459  0.583  0.309  0.683  0.434 
 0.583  0.260  0.235  0.060  0.185  0.359  0.534  0.384  0.484  0.135  0.185  0.359  0.434 -0.089  0.185  0.334  0.135 -0.039 -0.039  0.608  0.010  0.260 -0.039  0.633  0.035  0.185  0.434  0.559  0.658  0.160  0.260  0.110  0.210  0.135  0.409  0.459  0.210 -0.139  0.035  0.309  0.185  0.309  0.110  0.284  0.035  0.509  0.633  0.334  0.633  0.434 
 0.561  0.262  0.237  0.087  0.187  0.361  0.511  0.386  0.461  0.162  0.187  0.361  0.436 -0.062  0.187  0.361  0.162 -0.037 -0.037  0.610  0.012  0.212 -0.012  0.635  0.012  0.187  0.411  0.561  0.610  0.162  0.286  0.112  0.212  0.137  0.411  0.461  0.212 -0.137  0.037  0.336  0.187  0.311  0.087  0.311  0.037  0.486  0.660  0.311  0.610  0.436 
 0.506  0.282  0.257  0.057  0.182  0.406  0.481  0.381  0.406  0.182  0.257  0.331  0.456 -0.067  0.232  0.431  0.157 -0.042 -0.042  0.630  0.007  0.207  0.007  0.655  0.007  0.182  0.431  0.531  0.605  0.157  0.331  0.107  0.207  0.157  0.406  0.456  0.257 -0.142  0.057  0.381  0.157  0.331  0.082  0.406  0.032  0.481  0.655  0.306  0.506  0.431 
 0.506  0.306  0.257  0.057  0.182  0.406  0.456  0.406  0.406  0.182  0.282  0.331  0.456 -0.017  0.257  0.456  0.157 -0.042 -0.042  0.630  0.007  0.207  0.032  0.630  0.007  0.182  0.431  0.506  0.556  0.132  0.331  0.132  0.207  0.157  0.406  0.431  0.282 -0.142  0.057  0.381  0.157  0.356  0.082  0.456  0.032  0.481  0.655  0.282  0.506  0.406 
 0.505  0.331  0.256  0.057  0.206  0.430  0.455  0.406  0.381  0.156  0.281  0.331  0.455 -0.018  0.306  0.505  0.156 -0.068 -0.093  0.630  0.007  0.206  0.032  0.605  0.007  0.181  0.455  0.430  0.555  0.107  0.331  0.156  0.181  0.156  0.430  0.406  0.306 -0.142  0.007  0.430  0.132  0.356  0.057  0.505  0.007  0.480  0.655  0.306  0.455  0.406 
 0.502  0.327  0.278  0.053  0.228  0.452  0.452  0.452  0.327  0.153  0.278  0.327  0.502 -0.021  0.327  0.527  0.128 -0.071 -0.121  0.626  0.003  0.203  0.028  0.601 -0.021  0.178  0.527  0.402  0.552  0.103  0.327  0.203  0.178  0.153  0.427  0.427  0.352 -0.146  0.003  0.402  0.128  0.352  0.028  0.527 -0.021  0.477  0.651  0.302  0.452  0.402 
 0.498  0.323  0.298  0.049  0.224  0.448  0.448  0.448  0.323  0.149  0.298  0.323  0.498 -0.000  0.348  0.523  0.124 -0.075 -0.150  0.622 -0.000  0.199  0.024  0.597 -0.025  0.174  0.548  0.348  0.548  0.074  0.323  0.199  0.149  0.149  0.473  0.423  0.398 -0.150 -0.000  0.398  0.149  0.348  0.024  0.523 -0.025  0.448  0.672  0.298  0.473  0.398 
 0.497  0.322  0.297  0.048  0.223  0.447  0.447  0.447  0.322  0.173  0.322  0.322  0.497  0.023  0.347  0.522  0.123 -0.076 -0.176  0.621 -0.001  0.198  0.073  0.596 -0.026  0.173  0.547  0.297  0.547  0.048  0.322  0.223  0.148  0.173  0.472  0.422  0.397 -0.151  0.023  0.422  0.148  0.347  0.023  0.522 -0.026  0.447  0.646  0.297  0.472  0.372 
 0.472  0.323  0.298  0.049  0.223  0.423  0.423  0.447  0.323  0.173  0.323  0.273  0.472  0.049  0.348  0.547  0.124 -0.076 -0.175  0.597  0.024  0.198  0.074  0.597 -0.026  0.173  0.547  0.248  0.522  0.074  0.323  0.248  0.124  0.173  0.522  0.423  0.398 -0.150  0.024  0.423  0.148  0.348  0.024  0.522 -0.026  0.447  0.647  0.298  0.472  0.373 
 0.445  0.320  0.295  0.046  0.246  0.420  0.420  0.445  0.320  0.196  0.320  0.271  0.470  0.046  0.345  0.545  0.121 -0.078 -0.178  0.594  0.046  0.196  0.046  0.594 -0.028  0.171  0.545  0.246  0.520  0.096  0.320  0.246  0.121  0.146  0.520  0.420  0.420 -0.153  0.046  0.445  0.146  0.345  0.021  0.545 -0.003  0.445  0.669  0.271  0.470  0.370 
 0.446  0.321  0.296  0.047  0.272  0.421  0.421  0.446  0.321  0.197  0.321  0.272  0.471  0.047  0.346  0.546  0.122 -0.077 -0.177  0.595  0.047  0.197  0.022  0.595 -0.002  0.172  0.446  0.247  0.521  0.122  0.321  0.247  0.047  0.122  0.521  0.421  0.421 -0.152  0.047  0.446  0.147  0.296  0.022  0.546 -0.002  0.496  0.670  0.272  0.471  0.371 
 0.292  0.243  0.342  0.093  0.268  0.417  0.467  0.367  0.292  0.168  0.193  0.218  0.492  0.068  0.268  0.517  0.068 -0.031 -0.181  0.542  0.018  0.218 -0.056  0.442 -0.006  0.118  0.367  0.268  0.467  0.193  0.292  0.168  0.018  0.093  0.517  0.392  0.392 -0.156  0.068  0.417  0.093  0.292  0.043  0.392 -0.081  0.542  0.716  0.292  0.467  0.342 
 0.248  0.248  0.347  0.048  0.273  0.422  0.447  0.322  0.248  0.173  0.248  0.173  0.497  0.023  0.223  0.397  0.023 -0.051 -0.126  0.497 -0.051  0.173 -0.051  0.447 -0.001  0.123  0.372  0.297  0.397  0.198  0.248  0.198  0.023  0.073  0.447  0.422  0.397 -0.101  0.048  0.347  0.073  0.322  0.048  0.447 -0.051  0.422  0.596  0.297  0.422  0.372 
 0.267  0.192  0.367  0.043  0.192  0.417  0.491  0.342  0.242  0.192  0.118  0.192  0.441  0.018  0.167  0.342 -0.007 -0.082 -0.132  0.441 -0.032  0.167 -0.032  0.417  0.018  0.118  0.317  0.317  0.367  0.217  0.242  0.167  0.018  0.043  0.342  0.417  0.317 -0.107 -0.057  0.367  0.093  0.317  0.068  0.417 -0.007  0.441  0.616  0.292  0.392  0.367 
 0.139  0.139  0.363  0.014  0.163  0.437  0.487  0.263  0.213  0.139  0.114  0.163  0.413  0.014  0.163  0.288 -0.011 -0.086 -0.136  0.437 -0.036  0.188 -0.011  0.437  0.014  0.139  0.338  0.338  0.263  0.238  0.238  0.139  0.014  0.039  0.313  0.437  0.338 -0.111 -0.061  0.388  0.114  0.338  0.089  0.437 -0.036  0.413  0.587  0.188  0.413  0.338 
 0.147  0.123  0.347  0.023  0.172  0.446  0.471  0.272  0.147  0.073  0.123  0.147  0.422  0.023  0.123  0.247 -0.002 -0.077 -0.127  0.446 -0.027  0.172 -0.002  0.446  0.023  0.123  0.347  0.322  0.222  0.247  0.222  0.147  0.023  0.023  0.297  0.422  0.297 -0.102 -0.052  0.397  0.073  0.347  0.098  0.422 -0.052  0.347  0.546  0.172  0.397  0.272 
 0.162  0.088  0.312  0.038  0.162  0.461  0.436  0.287  0.138  0.063  0.138  0.138  0.412  0.013  0.038  0.113  0.013 -0.062 -0.112  0.436 -0.012  0.162  0.013  0.412  0.013  0.138  0.362  0.337  0.212  0.262  0.113  0.088  0.038 -0.012  0.262  0.461  0.262 -0.087 -0.037  0.362  0.038  0.362  0.113  0.362 -0.037  0.337  0.511  0.162  0.412  0.237 
 0.168  0.094  0.318  0.044  0.168  0.467  0.442  0.293  0.143  0.069  0.143  0.143  0.418 -0.006  0.019  0.019 -0.006 -0.056 -0.106  0.442 -0.006  0.168  0.019  0.343 -0.006  0.143  0.368  0.343  0.218  0.268  0.119  0.094  0.019 -0.006  0.268  0.442  0.268 -0.081 -0.056  0.293 -0.006  0.343  0.094  0.343 -0.031  0.343  0.492  0.168  0.368  0.193 
 0.177  0.103  0.327  0.053  0.152  0.476  0.426  0.302  0.152  0.003  0.128  0.103  0.426  0.003  0.003 -0.022  0.003 -0.047 -0.097  0.426  0.003  0.177  0.028  0.227  0.003  0.177  0.377  0.377  0.227  0.277  0.128  0.103  0.003 -0.022  0.277  0.476  0.252 -0.072 -0.047  0.252  0.003  0.327  0.103  0.277 -0.022  0.302  0.476  0.202  0.327  0.202 
 0.181  0.081  0.330  0.031  0.156  0.530  0.430  0.305  0.156 -0.018  0.081  0.106  0.455  0.006 -0.018 -0.018  0.006 -0.043 -0.093  0.405  0.006  0.181  0.056  0.206  0.006  0.181  0.355  0.430  0.206  0.281  0.131  0.081 -0.018 -0.043  0.231  0.455  0.305 -0.068 -0.043  0.206 -0.018  0.305  0.106  0.231 -0.018  0.305  0.430  0.256  0.330  0.206 
 0.192  0.067  0.267  0.017  0.142  0.516  0.441  0.316  0.167 -0.007  0.017  0.117  0.466 -0.007 -0.007 -0.007  0.017 -0.032 -0.082  0.291  0.017  0.192  0.042  0.142 -0.032  0.142  0.341  0.441  0.192  0.316  0.142  0.092 -0.007 -0.032  0.217  0.466  0.291 -0.057 -0.032  0.192 -0.007  0.267  0.117  0.242 -0.007  0.267  0.366  0.267  0.217  0.217 
 0.172  0.023  0.272  0.023  0.147  0.521  0.446  0.272  0.172 -0.002  0.023  0.123  0.471 -0.027 -0.002 -0.002  0.023 -0.027 -0.077  0.197  0.023  0.222  0.048  0.123 -0.027  0.123  0.372  0.422  0.172  0.297  0.147  0.098 -0.002 -0.027  0.172  0.471  0.222 -0.052 -0.027  0.172 -0.027  0.272  0.098  0.222 -0.027  0.247  0.297  0.272  0.197  0.172 
 0.158  0.008  0.158  0.008  0.158  0.507  0.432  0.233  0.208  0.008 -0.016  0.133  0.382 -0.016  0.008  0.008  0.008 -0.016 -0.066  0.133  0.008  0.208  0.033  0.058 -0.016  0.133  0.357  0.457  0.108  0.332  0.133  0.083 -0.016 -0.016  0.158  0.457  0.208 -0.041 -0.016  0.058 -0.016  0.183  0.083  0.183 -0.041  0.208  0.307  0.233  0.158  0.183 
 0.142  0.017  0.067 -0.008  0.142  0.416  0.440  0.241  0.191  0.017 -0.008  0.142  0.366 -0.033 -0.008  0.017  0.017 -0.008 -0.058  0.117 -0.008  0.216  0.042 -0.008 -0.008  0.142  0.291  0.440  0.092  0.341  0.117  0.092 -0.008 -0.008  0.117  0.465  0.191 -0.033 -0.008  0.017 -0.033  0.191  0.067  0.142 -0.033  0.166  0.266  0.216  0.166  0.142 
 0.131 -0.018 -0.018 -0.018  0.106  0.330  0.455  0.256  0.181  0.006  0.006  0.131  0.256 -0.018  0.006  0.031  0.006  0.006 -0.043  0.006 -0.018  0.131  0.006  0.006 -0.018  0.131  0.131  0.355  0.081  0.330  0.106  0.106  0.006  0.006  0.056  0.480  0.081 -0.018 -0.018  0.031 -0.018  0.081  0.081  0.056 -0.043  0.106  0.181  0.206  0.181  0.131 
 0.140 -0.009 -0.009 -0.009  0.090  0.215  0.414  0.215  0.190  0.015 -0.009  0.090  0.190 -0.009  0.015  0.040 -0.009  0.015 -0.034 -0.009 -0.009  0.065  0.015 -0.009 -0.009  0.065  0.090  0.314  0.090  0.314  0.065  0.090  0.015  0.015  0.065  0.489  0.040 -0.034 -0.009  0.015 -0.009  0.040  0.040  0.040 -0.034  0.065  0.165  0.115  0.165  0.090 
 0.131  0.006  0.006 -0.018  0.056  0.106  0.256  0.081  0.106  0.006  0.006  0.031  0.131  0.006  0.006  0.006 -0.018  0.031 -0.018 -0.018  0.006  0.056  0.031  0.006  0.006  0.031  0.031  0.056  0.081  0.181  0.031  0.031  0.006  0.006  0.081  0.455  0.006 -0.018 -0.018  0.006  0.006  0.031  0.031  0.031 -0.018  0.031  0.056  0.031  0.081  0.056 
 0.065 -0.009  0.015 -0.009  0.040  0.065  0.140  0.040  0.065  0.015  0.015  0.015  0.040  0.015  0.015  0.015 -0.009  0.015 -0.009 -0.009 -0.009  0.040  0.040 -0.009  0.015 -0.009  0.040  0.040  0.040  0.115  0.015  0.015  0.015  0.015  0.015  0.265 -0.009 -0.009 -0.009  0.015  0.015  0.015 -0.009  0.015 -0.009  0.015  0.015  0.040  0.040 -0.009 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.054 -0.020  0.004  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.029 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 
 1.000  0.078 -0.021  0.003  0.003  0.028  0.103  0.003 -0.021 -0.021  0.028 -0.021  0.028 -0.021  0.003  0.028  0.028  0.003 -0.021  0.003 -0.021  0.003 -0.021 -0.021  0.028  0.003 -0.021  0.053  0.003  0.053 -0.021  0.003 -0.021 -0.021  0.003 -0.021 -0.021 -0.021  0.003  0.028 -0.021 -0.021  0.028  0.028  0.003 -0.021 -0.021 -0.021 -0.021  0.003 
 0.999  0.078 -0.022  0.003  0.003  0.028  0.128  0.003 -0.022 -0.022  0.028 -0.022  0.028 -0.022  0.028  0.028  0.028  0.003 -0.022  0.003 -0.022  0.003 -0.022 -0.022  0.028  0.003 -0.022  0.053  0.003  0.053 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022 -0.022  0.003  0.028 -0.022 -0.022  0.028  0.028  0.003 -0.022 -0.022 -0.022 -0.022  0.003 
 0.994  0.221 -0.028 -0.003 -0.003  0.022  0.221 -0.003 -0.028 -0.028  0.047 -0.028  0.022 -0.028  0.072  0.047  0.022 -0.003 -0.028 -0.003 -0.028 -0.003 -0.028 -0.028  0.022  0.022 -0.028  0.047 -0.003  0.072 -0.028  0.097 -0.028 -0.028 -0.003 -0.003 -0.028 -0.028 -0.003  0.022 -0.028 -0.003  0.047  0.047 -0.003 -0.028 -0.028 -0.028 -0.028 -0.003 
 0.969  0.645 -0.053 -0.003  0.022  0.022  0.670 -0.028 -0.028 -0.028  0.171 -0.053  0.097 -0.053  0.072  0.022 -0.003 -0.028 -0.053  0.022 -0.028 -0.028 -0.028 -0.028  0.022 -0.003 -0.028  0.146  0.072  0.072 -0.028  0.097 -0.028 -0.003 -0.028  0.022 -0.053 -0.028  0.022  0.047 -0.053 -0.003  0.047  0.047 -0.028 -0.053 -0.028  0.022 -0.053  0.072 
 0.951  0.776 -0.021 -0.021  0.004  0.004  0.776 -0.046 -0.021 -0.021  0.253 -0.071  0.178 -0.071  0.129  0.029  0.004 -0.046 -0.071  0.054 -0.046 -0.021 -0.046 -0.021  0.029  0.004 -0.021  0.178  0.153  0.104 -0.046  0.079  0.004 -0.021  0.004  0.079 -0.046 -0.046  0.029  0.079 -0.071  0.029  0.029  0.029 -0.046 -0.071  0.004  0.054  0.029  0.079 
 0.903  0.903 -0.043  0.006  0.031  0.031  0.903 -0.018  0.031 -0.043  0.530 -0.018  0.206 -0.093  0.081  0.006  0.006 -0.043 -0.093  0.056  0.031  0.006 -0.068 -0.043  0.006  0.031  0.031  0.305  0.330  0.131 -0.068  0.081  0.081 -0.018  0.081  0.056 -0.043 -0.093 -0.018  0.281 -0.043  0.031  0.081  0.081 -0.068 -0.068  0.031  0.031  0.106  0.181 
 0.866  0.866  0.069  0.044  0.044  0.044  0.866  0.094  0.044 -0.030  0.617 -0.030  0.244 -0.130  0.094  0.019  0.044 -0.055 -0.055  0.094  0.044  0.019 -0.105 -0.055  0.019  0.044  0.044  0.493  0.568  0.244 -0.105  0.119  0.144 -0.030  0.119  0.069 -0.030 -0.130 -0.005  0.468 -0.055  0.044  0.144  0.069 -0.055 -0.080  0.144  0.044  0.219  0.194 
 0.808  0.808  0.061  0.111  0.086  0.136  0.808  0.310  0.036 -0.014  0.659 -0.039  0.484 -0.114  0.086  0.036  0.061 -0.089 -0.114  0.111  0.036  0.061 -0.163 -0.089  0.036  0.086  0.185  0.684  0.758  0.360 -0.014  0.160  0.210 -0.039  0.235  0.210 -0.014 -0.139  0.011  0.634 -0.064  0.111  0.210  0.136 -0.039 -0.014  0.335  0.260  0.385  0.335 
 0.783  0.758  0.061  0.086  0.136  0.185  0.758  0.360  0.036  0.036  0.634 -0.014  0.509 -0.139  0.086  0.011  0.036 -0.039 -0.139  0.136  0.036  0.036 -0.188  0.036  0.011  0.111  0.260  0.684  0.758  0.410  0.086  0.136  0.210 -0.039  0.335  0.285  0.086 -0.139  0.011  0.659 -0.089  0.185  0.210  0.210  0.011  0.036  0.534  0.310  0.385  0.385 
 0.596  0.696  0.172  0.098  0.172  0.247  0.696  0.397  0.123  0.098  0.521 -0.002  0.571 -0.176  0.098  0.048  0.048 -0.052 -0.127  0.272  0.048  0.222 -0.176  0.272 -0.002  0.098  0.397  0.671  0.745  0.397  0.123  0.172  0.222 -0.077  0.496  0.372  0.172 -0.176 -0.002  0.696 -0.077  0.297  0.222  0.322 -0.027  0.023  0.671  0.422  0.521  0.422 
 0.530  0.655  0.231  0.107  0.206  0.356  0.655  0.381  0.132  0.082  0.455  0.032  0.580 -0.142  0.132  0.132  0.057 -0.068 -0.142  0.430  0.032  0.206 -0.093  0.406 -0.018  0.082  0.430  0.580  0.705  0.406  0.181  0.181  0.206 -0.093  0.505  0.381  0.231 -0.192 -0.018  0.630 -0.068  0.331  0.231  0.356 -0.018  0.156  0.680  0.455  0.505  0.530 
 0.440  0.540  0.266  0.142  0.216  0.416  0.540  0.440  0.142  0.117  0.416  0.142  0.565 -0.083  0.117  0.166  0.092 -0.083 -0.157  0.465 -0.058  0.266 -0.033  0.490  0.042  0.092  0.490  0.565  0.665  0.416  0.216  0.191  0.216 -0.033  0.515  0.465  0.266 -0.207 -0.033  0.590 -0.008  0.366  0.241  0.416 -0.008  0.241  0.665  0.515  0.540  0.515 
 0.434  0.509  0.260  0.160  0.210  0.409  0.509  0.434  0.135  0.110  0.409  0.185  0.559 -0.089  0.135  0.210  0.110 -0.089 -0.164  0.484 -0.039  0.235 -0.014  0.534  0.060  0.110  0.484  0.559  0.633  0.434  0.235  0.185  0.210  0.060  0.534  0.459  0.309 -0.214 -0.039  0.583 -0.014  0.359  0.260  0.409 -0.014  0.309  0.658  0.509  0.534  0.484 
 0.402  0.451  0.277  0.177  0.177  0.451  0.501  0.426  0.202  0.128  0.402  0.202  0.551 -0.047  0.152  0.277  0.128 -0.097 -0.171  0.551 -0.072  0.252 -0.022  0.576  0.053  0.152  0.526  0.526  0.626  0.426  0.252  0.177  0.202  0.152  0.551  0.501  0.327 -0.221 -0.047  0.551  0.028  0.377  0.227  0.426 -0.022  0.377  0.676  0.501  0.526  0.451 
 0.351  0.426  0.276  0.151  0.176  0.500  0.500  0.450  0.201  0.176  0.401  0.201  0.550 -0.048  0.201  0.301  0.127 -0.098 -0.123  0.575 -0.048  0.251 -0.023  0.575  0.052  0.151  0.525  0.450  0.625  0.426  0.251  0.176  0.127  0.176  0.575  0.475  0.351 -0.197 -0.073  0.550  0.052  0.326  0.176  0.426 -0.023  0.401  0.675  0.525  0.525  0.450 
 0.327  0.427  0.278  0.153  0.203  0.502  0.502  0.452  0.203  0.178  0.402  0.228  0.527 -0.046  0.228  0.352  0.153 -0.096 -0.121  0.576 -0.021  0.228 -0.021  0.601  0.053  0.153  0.527  0.427  0.626  0.402  0.253  0.153  0.103  0.178  0.576  0.477  0.402 -0.196 -0.071  0.527  0.053  0.278  0.128  0.477 -0.021  0.427  0.676  0.477  0.502  0.402 
 0.324  0.424  0.299  0.125  0.225  0.499  0.499  0.449  0.225  0.175  0.424  0.250  0.524 -0.024  0.225  0.424  0.150 -0.099 -0.149  0.573 -0.024  0.225 -0.024  0.598  0.050  0.150  0.499  0.374  0.623  0.399  0.250  0.150  0.100  0.175  0.598  0.524  0.399 -0.199 -0.074  0.499  0.050  0.275  0.100  0.524 -0.024  0.424  0.673  0.449  0.474  0.374 
 0.323  0.373  0.323  0.099  0.248  0.497  0.497  0.447  0.248  0.173  0.447  0.273  0.522 -0.001  0.223  0.497  0.148 -0.101 -0.150  0.547 -0.026  0.223 -0.026  0.597  0.049  0.148  0.447  0.373  0.597  0.348  0.248  0.124  0.099  0.173  0.597  0.522  0.398 -0.150 -0.076  0.472  0.049  0.298  0.049  0.547 -0.026  0.423  0.672  0.447  0.497  0.398 
 0.323  0.348  0.348  0.074  0.248  0.497  0.497  0.472  0.248  0.173  0.447  0.273  0.522 -0.001  0.248  0.497  0.124 -0.076 -0.175  0.547 -0.026  0.223 -0.026  0.597  0.049  0.148  0.447  0.323  0.572  0.323  0.248  0.173  0.099  0.173  0.597  0.522  0.398 -0.150 -0.051  0.497  0.074  0.298  0.049  0.547 -0.026  0.423  0.672  0.447  0.497  0.398 
 0.324  0.374  0.324  0.050  0.224  0.473  0.498  0.473  0.249  0.174  0.448  0.274  0.523  0.000  0.274  0.498  0.125 -0.075 -0.174  0.573 -0.025  0.224 -0.025  0.573  0.000  0.149  0.498  0.324  0.548  0.324  0.224  0.174  0.100  0.174  0.598  0.548  0.399 -0.149 -0.050  0.498  0.075  0.299  0.050  0.573 -0.025  0.424  0.673  0.448  0.498  0.374 
 0.123  0.347  0.297  0.048  0.197  0.446  0.471  0.471  0.247  0.172  0.422  0.197  0.471 -0.002  0.197  0.422 -0.002 -0.027 -0.127  0.471 -0.002  0.172 -0.077  0.521  0.023  0.147  0.422  0.322  0.521  0.297  0.123  0.222  0.048  0.098  0.596  0.521  0.422 -0.102 -0.052  0.471  0.098  0.297  0.048  0.546 -0.027  0.397  0.596  0.347  0.471  0.372 
 0.179  0.353  0.303  0.029  0.179  0.403  0.478  0.428  0.179  0.129  0.303  0.129  0.453 -0.045  0.204  0.279  0.029 -0.045 -0.095  0.453 -0.020  0.204 -0.045  0.403  0.029  0.154  0.453  0.353  0.503  0.204  0.129  0.179  0.029  0.029  0.353  0.428  0.403 -0.095 -0.045  0.453  0.029  0.279  0.054  0.453 -0.020  0.353  0.553  0.353  0.478  0.378 
 0.121  0.345  0.295  0.021  0.146  0.420  0.495  0.420  0.146  0.046  0.246  0.096  0.395 -0.053  0.196  0.221  0.046 -0.078 -0.078  0.495 -0.003  0.221 -0.028  0.370 -0.003  0.146  0.445  0.345  0.495  0.221  0.071  0.146 -0.003  0.021  0.320  0.445  0.345 -0.078 -0.028  0.395 -0.003  0.295  0.046  0.445 -0.028  0.320  0.520  0.246  0.470  0.370 
 0.144  0.294  0.294  0.020  0.169  0.443  0.443  0.394  0.144 -0.005  0.194  0.120  0.419 -0.030  0.045  0.070 -0.005 -0.080 -0.080  0.493 -0.005  0.219 -0.005  0.344  0.020  0.144  0.443  0.344  0.419  0.244  0.095  0.144 -0.005 -0.005  0.269  0.468  0.294 -0.080 -0.030  0.294 -0.005  0.319  0.070  0.344 -0.005  0.294  0.493  0.244  0.468  0.294 
 0.128  0.252  0.302  0.028  0.152  0.451  0.402  0.402  0.152 -0.022  0.202  0.128  0.451  0.003  0.028 -0.022  0.003 -0.072 -0.047  0.526  0.003  0.227  0.003  0.277  0.078  0.152  0.451  0.352  0.377  0.252  0.078  0.128  0.028 -0.047  0.277  0.476  0.227 -0.072 -0.022  0.227  0.003  0.277  0.078  0.327  0.003  0.302  0.451  0.252  0.526  0.202 
 0.115  0.240  0.314  0.040  0.140  0.464  0.389  0.339  0.165 -0.034  0.215  0.140  0.464  0.015  0.040 -0.009 -0.009 -0.059 -0.059  0.464 -0.009  0.215  0.015  0.190  0.040  0.165  0.464  0.339  0.289  0.265  0.090  0.115  0.040 -0.034  0.240  0.489  0.240 -0.059 -0.034  0.240 -0.009  0.289  0.090  0.314  0.015  0.289  0.439  0.215  0.514  0.215 
 0.123  0.173  0.297  0.048  0.148  0.422  0.397  0.347  0.173 -0.051  0.223  0.148  0.472  0.023  0.023 -0.026 -0.001 -0.051 -0.051  0.447 -0.001  0.198  0.023  0.173  0.023  0.173  0.472  0.347  0.273  0.273  0.073  0.098 -0.001 -0.026  0.223  0.472  0.223 -0.051 -0.051  0.223 -0.001  0.273  0.098  0.322 -0.001  0.297  0.447  0.173  0.447  0.223 
 0.137  0.112  0.286  0.062  0.137  0.386  0.411  0.311  0.162 -0.037  0.212  0.087  0.461 -0.012  0.012 -0.012  0.012 -0.037 -0.062  0.386 -0.012  0.212  0.037  0.112 -0.012  0.162  0.436  0.386  0.212  0.286  0.087  0.087  0.012 -0.012  0.162  0.461  0.162 -0.037 -0.037  0.212 -0.012  0.212  0.112  0.212 -0.062  0.262  0.436  0.162  0.436  0.162 
 0.146  0.071  0.221  0.021  0.146  0.395  0.445  0.320  0.171 -0.028  0.221 -0.028  0.470 -0.028  0.021 -0.003  0.021 -0.028 -0.078  0.246  0.021  0.171  0.046  0.071 -0.003  0.121  0.420  0.395  0.171  0.295  0.096  0.096 -0.003 -0.028  0.221  0.445  0.121 -0.028 -0.028  0.221 -0.003  0.196  0.121  0.196 -0.053  0.221  0.445  0.146  0.395  0.171 
 0.130  0.055  0.180  0.005  0.155  0.379  0.454  0.255  0.180 -0.019  0.205 -0.019  0.404 -0.044  0.005  0.005  0.005 -0.019 -0.069  0.205  0.030  0.180  0.055  0.055  0.005  0.130  0.404  0.404  0.155  0.280  0.105  0.105  0.005 -0.019  0.230  0.454  0.105 -0.044 -0.019  0.155  0.005  0.205  0.130  0.155 -0.044  0.180  0.429  0.130  0.304  0.180 
 0.113  0.038  0.162  0.013  0.162  0.337  0.436  0.262  0.187 -0.012  0.187 -0.012  0.362 -0.037  0.013  0.013  0.013 -0.012 -0.062  0.187  0.013  0.187  0.038  0.013  0.013  0.138  0.387  0.362  0.113  0.237  0.063  0.113 -0.012 -0.012  0.237  0.436  0.113 -0.062 -0.012  0.138  0.013  0.212  0.138  0.138 -0.062  0.187  0.436  0.063  0.262  0.162 
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 0.995  0.024  0.024  0.049  0.024 -0.001 -0.001 -0.001 -0.001 -0.026 -0.001 -0.001  0.024 -0.001 -0.001  0.049  0.024 -0.001 -0.026 -0.001 -0.001 -0.001  0.024 -0.001 -0.001 -0.001 -0.026 -0.001 -0.026  0.024  0.049 -0.026 -0.001 -0.001 -0.001 -0.001 -0.001 -0.026 -0.026 -0.001 -0.001  0.024 -0.001  0.024 -0.001  0.024 -0.001  0.024 -0.026 -0.001 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029  0.004  0.004  0.029  0.029  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004  0.029  0.004  0.029 -0.020  0.004 
 1.000  0.028  0.003  0.003  0.028  0.003 -0.021 -0.021  0.003 -0.021  0.003  0.003  0.028  0.003  0.003  0.028  0.053  0.003 -0.021  0.003 -0.021  0.003  0.028  0.003 -0.021  0.003 -0.021  0.003 -0.021  0.028  0.078 -0.021  0.003  0.003  0.003  0.003  0.028 -0.021 -0.021  0.003  0.003  0.003 -0.021  0.053  0.003  0.053  0.003  0.028 -0.021  0.003 
 0.997  0.026  0.001  0.001  0.051  0.026 -0.024 -0.024  0.001 -0.024  0.001  0.001  0.026  0.001  0.001  0.026  0.076  0.001 -0.024  0.001 -0.024  0.001  0.026  0.001 -0.024  0.026 -0.024  0.001 -0.024  0.026  0.076  0.001  0.001  0.001  0.026  0.001  0.051 -0.024 -0.024  0.001  0.001  0.026 -0.024  0.051  0.001  0.051  0.001  0.026 -0.024  0.001 
 0.993  0.021 -0.004 -0.004  0.046  0.021 -0.029 -0.029 -0.004 -0.029 -0.004 -0.004  0.021 -0.004 -0.004  0.021  0.071 -0.004 -0.029 -0.004 -0.029 -0.004  0.021  0.021 -0.029  0.046 -0.029 -0.004 -0.029  0.046  0.145  0.021  0.021 -0.004  0.046 -0.004  0.121 -0.029 -0.029 -0.004  0.021  0.046 -0.029  0.071  0.021  0.071 -0.004  0.021 -0.029 -0.004 
 0.975  0.003  0.028 -0.022  0.053  0.003 -0.047  0.028 -0.022 -0.047  0.003 -0.022  0.078  0.078 -0.022  0.053  0.053 -0.022 -0.047 -0.022 -0.047  0.028  0.003  0.053  0.003  0.078 -0.047  0.078 -0.022  0.078  0.252  0.028  0.028 -0.022  0.028  0.003  0.252 -0.047 -0.022  0.003  0.003  0.028  0.003  0.128  0.003  0.177  0.003  0.078 -0.022  0.053 
 0.935 -0.011  0.013 -0.011  0.063  0.088 -0.011  0.113 -0.011 -0.011  0.063 -0.036  0.088  0.088 -0.011  0.088  0.013  0.013 -0.061  0.013 -0.061  0.138  0.063  0.038 -0.011  0.138 -0.086  0.063 -0.061  0.138  0.437  0.063 -0.011  0.013  0.063 -0.011  0.562 -0.036 -0.011  0.088  0.013  0.088  0.063  0.312 -0.011  0.387  0.038  0.263  0.063  0.038 
 0.860  0.063  0.088  0.038  0.088  0.138  0.038  0.237 -0.062 -0.012  0.138  0.038  0.113  0.237 -0.037  0.088 -0.037  0.063 -0.087  0.088 -0.087  0.237  0.088  0.063  0.088  0.113 -0.062  0.187  0.038  0.312  0.810  0.063 -0.037 -0.012  0.187 -0.037  0.785 -0.037  0.013  0.063  0.138  0.138  0.038  0.486 -0.037  0.561  0.038  0.511  0.113  0.162 
 0.820  0.147  0.123 -0.002  0.048  0.197 -0.002  0.297 -0.052  0.073  0.123  0.147  0.172  0.197 -0.052  0.073 -0.077  0.073 -0.102  0.147 -0.102  0.347  0.098  0.147  0.073  0.123  0.048  0.197  0.172  0.322  0.795  0.048 -0.027  0.023  0.297  0.023  0.770 -0.077 -0.027  0.098  0.123  0.123  0.023  0.646 -0.027  0.720  0.048  0.546  0.172  0.222 
 0.765  0.192  0.067 -0.007  0.142  0.291  0.167  0.366  0.017  0.092  0.142  0.341  0.117  0.217 -0.082  0.142 -0.082  0.017 -0.107  0.242 -0.132  0.391  0.142  0.291  0.142  0.167  0.142  0.242  0.341  0.441  0.740  0.042 -0.007  0.017  0.391  0.142  0.740 -0.107  0.017  0.142  0.067  0.142 -0.007  0.740 -0.057  0.690  0.167  0.640  0.341  0.316 
 0.748  0.275  0.125 -0.024  0.125  0.374  0.175  0.349  0.025  0.100  0.150  0.399  0.125  0.250 -0.074  0.125 -0.049 -0.024 -0.124  0.275 -0.124  0.399  0.175  0.424  0.150  0.150  0.150  0.200  0.349  0.424  0.673  0.100 -0.024  0.075  0.374  0.125  0.723 -0.124  0.075  0.225  0.100  0.200 -0.049  0.723 -0.099  0.648  0.275  0.623  0.349  0.324 
 0.619  0.345  0.221 -0.028  0.171  0.370  0.271  0.370  0.096  0.146  0.171  0.495  0.171  0.345 -0.078  0.146  0.021 -0.053 -0.128  0.345 -0.128  0.271  0.146  0.569  0.221  0.146  0.221  0.295  0.370  0.420  0.619  0.146 -0.003  0.146  0.520  0.221  0.694 -0.178  0.196  0.246  0.071  0.271  0.021  0.694 -0.128  0.594  0.445  0.619  0.470  0.420 
 0.616  0.342  0.243 -0.006  0.193  0.392  0.317  0.392  0.143  0.168  0.168  0.517  0.168  0.392 -0.106  0.218  0.018 -0.081 -0.156  0.392 -0.106  0.268  0.118  0.616  0.168  0.168  0.243  0.317  0.392  0.442  0.517  0.168 -0.006  0.168  0.542  0.317  0.691 -0.181  0.243  0.268  0.068  0.292  0.043  0.666 -0.131  0.591  0.467  0.492  0.467  0.392 
 0.611  0.412  0.287  0.013  0.212  0.436  0.337  0.412  0.138  0.212  0.187  0.536  0.162  0.461 -0.087  0.237  0.038 -0.137 -0.137  0.461 -0.087  0.237  0.113  0.636  0.138  0.187  0.312  0.312  0.412  0.412  0.486  0.162 -0.037  0.162  0.586  0.412  0.611 -0.161  0.237  0.287  0.088  0.312  0.088  0.661 -0.137  0.536  0.486  0.436  0.486  0.412 
 0.613  0.414  0.314  0.015  0.239  0.463  0.339  0.414  0.164  0.239  0.189  0.538  0.189  0.488 -0.035  0.289  0.065 -0.135 -0.135  0.463 -0.060  0.214  0.090  0.638  0.115  0.214  0.314  0.314  0.414  0.414  0.463  0.164 -0.035  0.164  0.563  0.414  0.538 -0.159  0.214  0.314  0.090  0.314  0.065  0.663 -0.135  0.538  0.563  0.438  0.488  0.414 
 0.585  0.386  0.336  0.012  0.236  0.485  0.361  0.435  0.161  0.236  0.161  0.535  0.161  0.535 -0.038  0.286  0.062 -0.138 -0.138  0.485 -0.038  0.186  0.062  0.635  0.062  0.186  0.336  0.311  0.386  0.411  0.435  0.211 -0.038  0.161  0.560  0.535  0.485 -0.162  0.186  0.386  0.087  0.311  0.062  0.635 -0.113  0.510  0.585  0.435  0.485  0.411 
 0.557  0.382  0.332  0.008  0.233  0.432  0.382  0.432  0.158  0.208  0.208  0.532  0.158  0.532 -0.041  0.283  0.058 -0.141 -0.116  0.507 -0.041  0.183  0.083  0.606  0.033  0.158  0.407  0.307  0.382  0.407  0.357  0.183 -0.016  0.158  0.581  0.557  0.507 -0.166  0.233  0.407  0.108  0.307  0.058  0.631 -0.116  0.482  0.581  0.432  0.482  0.407 
 0.555  0.405  0.330  0.006  0.256  0.430  0.380  0.455  0.156  0.206  0.206  0.530  0.181  0.505 -0.018  0.355  0.056 -0.118 -0.168  0.505 -0.018  0.181  0.056  0.604  0.031  0.181  0.405  0.281  0.405  0.330  0.355  0.206 -0.018  0.156  0.604  0.555  0.480 -0.168  0.231  0.405  0.106  0.305  0.031  0.629 -0.118  0.455  0.604  0.405  0.455  0.380 
 0.555  0.380  0.330  0.056  0.256  0.430  0.355  0.455  0.156  0.206  0.231  0.505  0.231  0.530 -0.018  0.330  0.056 -0.093 -0.168  0.530 -0.018  0.181  0.056  0.604  0.031  0.156  0.405  0.281  0.405  0.305  0.380  0.206  0.056  0.131  0.604  0.530  0.480 -0.168  0.231  0.430  0.106  0.281  0.031  0.629 -0.093  0.455  0.629  0.380  0.455  0.380 
 0.554  0.404  0.329  0.055  0.280  0.454  0.354  0.479  0.155  0.230  0.255  0.479  0.230  0.529 -0.019  0.329  0.030 -0.069 -0.194  0.504  0.005  0.205  0.030  0.603  0.030  0.180  0.404  0.280  0.454  0.280  0.329  0.205  0.080  0.155  0.603  0.529  0.454 -0.144  0.230  0.429  0.105  0.280  0.030  0.628 -0.069  0.454  0.653  0.379  0.479  0.379 
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 0.955 -0.016  0.008  0.008  0.058  0.108 -0.016  0.183 -0.041  0.008  0.008  0.158  0.183  0.008  0.058  0.033  0.033 -0.041  0.008  0.058 -0.016 -0.016 -0.041 -0.016  0.058  0.108  0.008  0.058 -0.016  0.382 -0.041  0.108 -0.041  0.058 -0.016  0.033  0.058 -0.016  0.008 -0.066 -0.066  0.033  0.008  0.058  0.008  0.008  0.008  0.283  0.033 -0.041 
 0.909  0.012  0.012  0.012  0.037  0.112  0.037  0.336 -0.062  0.062  0.037  0.137  0.336  0.062  0.162  0.062  0.012 -0.012  0.012  0.037 -0.012 -0.037 -0.087 -0.012  0.187  0.137  0.012  0.112  0.012  0.660 -0.062  0.187 -0.062  0.037  0.012  0.112  0.087  0.037 -0.012 -0.087 -0.062  0.012  0.137  0.087 -0.012 -0.012  0.012  0.336  0.037 -0.037 
 0.848  0.075  0.025 -0.024  0.025  0.200  0.175  0.499  0.025  0.025  0.025  0.200  0.424  0.150  0.200  0.100  0.025 -0.024 -0.049  0.125  0.000 -0.024 -0.124  0.000  0.225  0.250  0.050  0.125  0.050  0.823 -0.074  0.349 -0.124  0.025  0.025  0.349  0.100  0.050 -0.024 -0.024 -0.024  0.075  0.200  0.225 -0.024 -0.024 -0.024  0.623  0.025  0.000 
 0.813  0.065 -0.009 -0.059  0.015  0.215  0.289  0.613 -0.009 -0.009  0.090  0.215  0.414  0.190  0.215  0.165 -0.009 -0.034 -0.059  0.190  0.015 -0.034 -0.084  0.040  0.215  0.240  0.040  0.115  0.090  0.788 -0.084  0.464 -0.159 -0.009  0.090  0.539  0.090  0.065  0.015 -0.034 -0.059  0.090  0.190  0.339 -0.084  0.040  0.065  0.738  0.040  0.015 
 0.761  0.213  0.013 -0.061  0.038  0.238  0.312  0.661  0.038 -0.036  0.213  0.337  0.487  0.287  0.188  0.213 -0.011 -0.036 -0.061  0.412  0.038 -0.011 -0.136  0.063  0.238  0.287  0.013  0.163  0.138  0.761 -0.086  0.562 -0.111 -0.061  0.163  0.661  0.063  0.013 -0.011  0.013 -0.086  0.088  0.238  0.437 -0.136  0.088  0.138  0.761  0.163  0.038 
 0.748  0.200  0.101 -0.074  0.051  0.225  0.350  0.649  0.026 -0.049  0.250  0.425  0.474  0.350  0.126  0.250  0.001 -0.074 -0.074  0.425  0.076  0.001 -0.124  0.101  0.225  0.250  0.001  0.200  0.150  0.699 -0.124  0.599 -0.124 -0.049  0.200  0.649  0.126  0.001 -0.024  0.026 -0.049  0.126  0.275  0.524 -0.148  0.175  0.126  0.723  0.275  0.026 
 0.727  0.254  0.130 -0.070  0.055  0.304  0.329  0.603  0.030 -0.070  0.254  0.453  0.453  0.428  0.105  0.254  0.005 -0.120 -0.070  0.503  0.055 -0.020 -0.070  0.154  0.179  0.279 -0.020  0.254  0.204  0.653 -0.169  0.678 -0.144 -0.045  0.254  0.678  0.179 -0.020 -0.045  0.105 -0.045  0.179  0.254  0.553 -0.169  0.179  0.229  0.653  0.404  0.030 
 0.694  0.270  0.145 -0.079  0.046  0.320  0.320  0.569  0.021 -0.054  0.245  0.519  0.444  0.420  0.096  0.295 -0.004 -0.129 -0.054  0.519  0.046 -0.004 -0.079  0.195  0.170  0.270  0.021  0.220  0.220  0.644 -0.178  0.694 -0.153 -0.054  0.245  0.669  0.195 -0.029 -0.079  0.121 -0.004  0.170  0.245  0.594 -0.178  0.170  0.220  0.644  0.494  0.021 
 0.664  0.290  0.141 -0.059  0.091  0.439  0.340  0.489  0.041 -0.034  0.190  0.539  0.439  0.439  0.091  0.315 -0.009 -0.158 -0.059  0.539 -0.009  0.016 -0.059  0.240  0.165  0.265  0.116  0.265  0.240  0.614 -0.183  0.689 -0.134 -0.034  0.265  0.639  0.190 -0.034 -0.109  0.141 -0.009  0.165  0.240  0.589 -0.183  0.215  0.240  0.614  0.514  0.041 
 0.659  0.260  0.136 -0.114  0.136  0.459  0.385  0.459  0.036  0.011  0.160  0.534  0.434  0.484  0.086  0.310  0.011 -0.114 -0.064  0.534 -0.014  0.011 -0.039  0.235  0.160  0.260  0.160  0.285  0.235  0.609 -0.114  0.659 -0.139 -0.039  0.285  0.634  0.210 -0.039 -0.089  0.136  0.036  0.210  0.235  0.584 -0.188  0.210  0.310  0.584  0.509  0.061 
 0.659  0.260  0.160 -0.114  0.160  0.509  0.410  0.459  0.036  0.036  0.160  0.534  0.434  0.484  0.061  0.310  0.036 -0.114 -0.089  0.534  0.011  0.011 -0.039  0.260  0.160  0.235  0.210  0.335  0.260  0.559 -0.064  0.609 -0.139 -0.014  0.335  0.609  0.235 -0.114 -0.089  0.160  0.036  0.210  0.235  0.584 -0.188  0.210  0.360  0.559  0.484  0.086 
 0.656  0.233  0.208 -0.116  0.183  0.482  0.457  0.457  0.033  0.033  0.183  0.532  0.432  0.482  0.058  0.307  0.058 -0.116 -0.116  0.532  0.008  0.008 -0.041  0.307  0.183  0.233  0.233  0.332  0.307  0.557 -0.066  0.606 -0.116 -0.016  0.357  0.606  0.233 -0.116 -0.091  0.183  0.033  0.233  0.233  0.606 -0.191  0.208  0.382  0.557  0.482  0.183 
 0.650  0.227  0.277 -0.122  0.202  0.501  0.476  0.426  0.027  0.027  0.177  0.526  0.451  0.476  0.027  0.301  0.102 -0.122 -0.122  0.526  0.052  0.052 -0.022  0.326  0.177  0.202  0.252  0.326  0.326  0.526 -0.047  0.551 -0.122 -0.022  0.451  0.600  0.277 -0.122 -0.072  0.227  0.052  0.252  0.227  0.650 -0.172  0.177  0.401  0.551  0.501  0.202 
 0.649  0.226  0.276 -0.098  0.201  0.525  0.475  0.425  0.026  0.076  0.151  0.525  0.450  0.475  0.026  0.300  0.126 -0.098 -0.123  0.525  0.051  0.051 -0.023  0.400  0.176  0.201  0.276  0.325  0.325  0.550 -0.023  0.550 -0.123 -0.023  0.475  0.599  0.276 -0.148 -0.048  0.300  0.076  0.276  0.201  0.649 -0.148  0.176  0.400  0.550  0.500  0.176 
 0.599  0.300  0.276 -0.098  0.201  0.550  0.475  0.450  0.026  0.101  0.151  0.475  0.450  0.475  0.026  0.375  0.251 -0.073 -0.098  0.525  0.051  0.051 -0.023  0.425  0.176  0.201  0.276  0.300  0.300  0.500  0.026  0.525 -0.123  0.001  0.525  0.599  0.300 -0.173 -0.023  0.300  0.051  0.300  0.201  0.624 -0.173  0.176  0.400  0.525  0.525  0.201 
 0.602  0.353  0.279 -0.095  0.229  0.528  0.478  0.453  0.054  0.104  0.154  0.478  0.453  0.478  0.029  0.353  0.229 -0.095 -0.095  0.503  0.054  0.054  0.004  0.503  0.129  0.204  0.279  0.328  0.328  0.503  0.054  0.528 -0.120 -0.020  0.553  0.602  0.279 -0.195 -0.020  0.303  0.029  0.303  0.154  0.627 -0.170  0.204  0.403  0.528  0.528  0.254 
 0.528  0.403  0.328 -0.070  0.229  0.528  0.478  0.453  0.079  0.179  0.129  0.453  0.453  0.453  0.004  0.353  0.254 -0.095 -0.070  0.528  0.054  0.029  0.004  0.528  0.104  0.204  0.303  0.328  0.328  0.503  0.129  0.503 -0.145  0.029  0.577  0.577  0.254 -0.195 -0.020  0.353  0.029  0.303  0.129  0.627 -0.170  0.204  0.403  0.503  0.528  0.303 
 0.547  0.347  0.273 -0.076  0.223  0.522  0.422  0.422  0.098  0.148  0.148  0.472  0.422  0.447  0.023  0.297  0.198 -0.076 -0.101  0.497 -0.001  0.048  0.048  0.447  0.098  0.248  0.273  0.372  0.273  0.347  0.073  0.472 -0.151 -0.001  0.522  0.497  0.297 -0.126 -0.026  0.322  0.023  0.297  0.098  0.571 -0.126  0.248  0.347  0.397  0.547  0.248 
 0.453  0.303  0.254 -0.020  0.279  0.503  0.403  0.353  0.154  0.054  0.179  0.478  0.378  0.453  0.054  0.254  0.179 -0.070 -0.120  0.503 -0.020  0.104 -0.020  0.353  0.129  0.204  0.328  0.303  0.229  0.353  0.054  0.353 -0.070  0.029  0.328  0.478  0.303 -0.120  0.004  0.204  0.004  0.303  0.154  0.528 -0.070  0.279  0.353  0.303  0.553  0.204 
 0.370  0.270  0.245 -0.004  0.220  0.519  0.395  0.345  0.096  0.071  0.170  0.469  0.370  0.444  0.046  0.220  0.096 -0.054 -0.104  0.544 -0.004  0.121 -0.004  0.345  0.096  0.245  0.345  0.245  0.220  0.345  0.071  0.270 -0.054 -0.004  0.295  0.370  0.320 -0.129 -0.054  0.170 -0.004  0.270  0.145  0.494 -0.079  0.295  0.370  0.320  0.569  0.170 
 0.320  0.195  0.270  0.021  0.195  0.494  0.345  0.345  0.121  0.046  0.195  0.320  0.345  0.444  0.021  0.046  0.046 -0.054 -0.104  0.544 -0.004  0.121 -0.004  0.295  0.071  0.220  0.370  0.270  0.195  0.345  0.096  0.195 -0.029 -0.004  0.245  0.395  0.295 -0.104 -0.079  0.195 -0.029  0.270  0.121  0.395 -0.054  0.295  0.320  0.295  0.594  0.121 
 0.281  0.206  0.231  0.006  0.181  0.505  0.355  0.281  0.106  0.031  0.206  0.281  0.281  0.480  0.031  0.031  0.031 -0.043 -0.118  0.579 -0.043  0.106  0.006  0.305  0.081  0.231  0.380  0.281  0.181  0.305  0.081  0.131 -0.018  0.006  0.156  0.405  0.305 -0.093 -0.093  0.156 -0.043  0.256  0.131  0.380 -0.043  0.305  0.281  0.231  0.604  0.106 
 0.148  0.123  0.173 -0.001  0.148  0.472  0.397  0.273  0.073 -0.026  0.223  0.198  0.198  0.497  0.023  0.023  0.023 -0.051 -0.101  0.596 -0.051  0.098  0.023  0.347  0.073  0.223  0.372  0.273  0.123  0.297  0.098  0.098 -0.001 -0.026  0.123  0.372  0.273 -0.076 -0.076  0.123 -0.026  0.297  0.123  0.273 -0.051  0.273  0.223  0.123  0.646  0.073 
 0.132  0.107  0.157  0.007  0.132  0.481  0.356  0.257  0.057 -0.042  0.207  0.157  0.182  0.456  0.032  0.032  0.007 -0.042 -0.092  0.605 -0.042  0.082  0.032  0.306  0.057  0.232  0.356  0.282  0.107  0.232  0.107  0.082  0.007 -0.017  0.132  0.331  0.232 -0.092 -0.067  0.107 -0.017  0.306  0.132  0.207 -0.042  0.282  0.207  0.032  0.680  0.057 
 0.098  0.023  0.098 -0.027  0.073  0.422  0.347  0.272  0.048 -0.052  0.222  0.172  0.147  0.471  0.048  0.023  0.023 -0.027 -0.077  0.621 -0.052  0.098  0.048  0.272  0.023  0.222  0.297  0.222  0.073  0.247  0.073  0.073 -0.002 -0.027  0.098  0.272  0.222 -0.077 -0.052  0.123 -0.002  0.247  0.147  0.197 -0.052  0.222  0.147  0.023  0.671  0.048 
 0.080  0.005  0.080 -0.019  0.055  0.404  0.329  0.230  0.055 -0.044  0.230  0.180  0.155  0.479  0.005  0.030  0.030 -0.019 -0.069  0.628 -0.044  0.080  0.055  0.255  0.005  0.230  0.304  0.230  0.055  0.255  0.055  0.055  0.005 -0.019  0.055  0.255  0.155 -0.069 -0.044  0.105 -0.019  0.255  0.155  0.180 -0.044  0.230  0.130  0.030  0.628  0.005 
 0.068 -0.006  0.043 -0.031  0.043  0.367  0.317  0.218  0.068 -0.031  0.243  0.093  0.168  0.467 -0.006  0.018  0.043 -0.006 -0.056  0.641 -0.031  0.093  0.068  0.143 -0.006  0.243  0.193  0.193  0.043  0.218  0.043  0.068  0.018 -0.006  0.018  0.193  0.118 -0.056 -0.031  0.043 -0.031  0.193  0.143  0.143 -0.031  0.193  0.068  0.043  0.567  0.018 
 0.027 -0.023  0.002 -0.048  0.052  0.326  0.276  0.226  0.077 -0.023  0.176  0.077  0.176  0.450  0.002  0.002  0.002  0.002 -0.023  0.650 -0.023  0.102  0.077  0.127 -0.048  0.176  0.151  0.176  0.052  0.201  0.002  0.052 -0.023  0.002  0.027  0.127  0.127 -0.048 -0.023  0.052 -0.048  0.151  0.102  0.151 -0.023  0.176  0.052  0.027  0.450  0.027 
 0.018 -0.031 -0.031 -0.031  0.018  0.193  0.143  0.093  0.018 -0.031  0.093  0.068  0.068  0.467  0.018  0.018 -0.006 -0.006 -0.006  0.616 -0.006  0.093  0.043  0.118 -0.031  0.168  0.093  0.143  0.018  0.093 -0.031  0.018 -0.031 -0.031  0.018  0.068  0.143 -0.031 -0.006 -0.006 -0.031  0.143  0.118  0.068 -0.006  0.143  0.018 -0.006  0.268  0.043 
 0.001 -0.023  0.001 -0.023  0.026  0.051  0.126  0.051  0.001 -0.023  0.051  0.051  0.051  0.325  0.026  0.001  0.001 -0.023  0.001  0.649  0.001  0.051  0.026  0.126 -0.023  0.176  0.076  0.126  0.026  0.051 -0.023 -0.023 -0.023 -0.023  0.001  0.076  0.101 -0.023 -0.023 -0.023 -0.023  0.076  0.076  0.051 -0.023  0.076 -0.023  0.001  0.176  0.026 
 0.009  0.009  0.009 -0.015 -0.015 -0.015  0.009  0.009 -0.015 -0.015  0.034  0.034  0.009  0.109  0.009 -0.015  0.009 -0.015  0.009  0.732 -0.015 -0.015 -0.015  0.109 -0.015  0.109  0.059  0.059 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015  0.084  0.009 -0.015 -0.015 -0.015  0.034  0.034  0.034 -0.015  0.034 -0.015 -0.015  0.009 -0.015 
 0.008  0.008  0.008 -0.016 -0.016 -0.016  0.008  0.008 -0.016 -0.016  0.033  0.033  0.008  0.108  0.008 -0.016  0.008 -0.016  0.008  0.781 -0.016 -0.016 -0.016  0.108 -0.016  0.108  0.058  0.058 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016  0.083  0.008 -0.016 -0.016 -0.016  0.033  0.033  0.033 -0.016  0.033 -0.016 -0.016  0.008 -0.016 
 0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.029  0.004  0.079  0.004 -0.020  0.004 -0.020  0.004  1.001 -0.020 -0.020 -0.020  0.129  0.004  0.079  0.054  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020 -0.020  0.004  0.029  0.029  0.029 -0.020  0.029  0.004 -0.020  0.004 -0.020 
 0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.029  0.004  0.079  0.004 -0.020  0.004 -0.020  0.004  1.001 -0.020 -0.020 -0.020  0.129  0.004  0.079  0.054  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020 -0.020  0.004  0.029  0.029  0.029 -0.020  0.029  0.004 -0.020  0.004 -0.020 
 0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.029  0.004  0.079  0.004 -0.020  0.004 -0.020  0.004  1.001 -0.020 -0.020 -0.020  0.129  0.004  0.079  0.054  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020 -0.020  0.004  0.029  0.029  0.029 -0.020  0.029  0.004 -0.020  0.004 -0.020 
 0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.029  0.004  0.079  0.004 -0.020  0.004 -0.020  0.004  1.001 -0.020 -0.020 -0.020  0.129  0.004  0.079  0.054  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020 -0.020  0.004  0.029  0.029  0.029 -0.020  0.029  0.004 -0.020  0.004 -0.020 
 0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.029  0.029  0.004  0.079  0.004 -0.020  0.004 -0.020  0.004  1.001 -0.020 -0.020 -0.020  0.129  0.004  0.079  0.054  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.054  0.004 -0.020 -0.020  0.004  0.029  0.029  0.029 -0.020  0.029  0.004 -0.020  0.004 -0.020 
 0.002  0.002  0.002 -0.022 -0.022 -0.022  0.002  0.002 -0.022 -0.022  0.027  0.027  0.002  0.077  0.002 -0.022  0.002 -0.022  0.002  0.999 -0.022 -0.022 -0.022  0.152  0.002  0.077  0.077  0.027 -0.022  0.002 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022  0.102  0.002 -0.022 -0.022  0.002  0.077  0.052  0.052 -0.022  0.027  0.002 -0.022  0.002 -0.022 
-0.012 -0.012  0.038 -0.037 -0.012 -0.037  0.013 -0.012 -0.037 -0.012  0.013  0.063  0.013  0.237 -0.012  0.038  0.038 -0.037 -0.012  0.985 -0.037 -0.037 -0.037  0.586 -0.012  0.138  0.113  0.088 -0.037  0.013  0.013 -0.037 -0.012 -0.012 -0.037 -0.037  0.113 -0.012 -0.012 -0.012 -0.012  0.113  0.088  0.088  0.013  0.038 -0.012 -0.037  0.038 -0.012 
-0.013 -0.038  0.061 -0.013 -0.038 -0.038  0.061  0.036 -0.063  0.036  0.011  0.136 -0.013  0.510 -0.038  0.086  0.011 -0.063 -0.013  0.958 -0.038 -0.063 -0.038  0.684 -0.038  0.186  0.161  0.186 -0.038  0.061  0.061 -0.013 -0.013 -0.038 -0.013 -0.013  0.261 -0.013 -0.013  0.011 -0.038  0.261  0.086  0.236  0.036  0.111 -0.038 -0.013  0.061 -0.013 
 0.096  0.096  0.146  0.021 -0.028 -0.003  0.171  0.121 -0.078  0.071  0.096  0.271  0.046  0.819 -0.053  0.246  0.021 -0.128 -0.028  0.893 -0.078 -0.078  0.046  0.893  0.021  0.295  0.320  0.295 -0.003  0.096  0.096  0.046  0.021 -0.003 -0.003  0.121  0.495 -0.053 -0.053  0.096 -0.028  0.320  0.096  0.370  0.021  0.171 -0.028 -0.003  0.096 -0.003 
 0.144  0.120  0.169  0.045 -0.030  0.095  0.294  0.269 -0.055  0.070  0.045  0.419 -0.005  0.792 -0.080  0.319  0.070 -0.105  0.045  0.842 -0.080 -0.130  0.020  0.842  0.070  0.369  0.419  0.344  0.120  0.294  0.120  0.095  0.020  0.045  0.070  0.344  0.518 -0.030 -0.055  0.095 -0.030  0.319  0.144  0.518  0.045  0.144  0.120 -0.005  0.120  0.045 
 0.213  0.188  0.263  0.014  0.039  0.163  0.437  0.413  0.114  0.114  0.188  0.512  0.014  0.761 -0.061  0.413  0.114 -0.136  0.064  0.761  0.014 -0.111  0.114  0.761  0.064  0.313  0.487  0.437  0.288  0.313  0.139  0.188 -0.036  0.089  0.089  0.462  0.637 -0.086 -0.086  0.139 -0.061  0.363  0.188  0.687  0.014  0.363  0.338  0.114  0.313  0.188 
 0.186  0.211  0.335  0.011  0.061  0.236  0.410  0.435  0.136  0.136  0.211  0.485  0.086  0.734 -0.038  0.485  0.186 -0.163  0.086  0.709 -0.063  0.011  0.136  0.734  0.036  0.310  0.485  0.410  0.285  0.360  0.186  0.236 -0.038  0.136  0.136  0.584  0.609 -0.138 -0.063  0.186 -0.013  0.360  0.136  0.684 -0.013  0.410  0.460  0.086  0.310  0.360 
 0.213  0.238  0.338  0.014  0.114  0.313  0.413  0.512  0.139  0.139  0.288  0.487  0.114  0.637  0.014  0.437  0.363 -0.136  0.039  0.662 -0.061  0.039  0.139  0.662  0.039  0.288  0.512  0.388  0.313  0.363  0.238  0.238  0.014  0.213  0.188  0.587  0.587 -0.111 -0.111  0.263 -0.036  0.338  0.089  0.662 -0.036  0.487  0.537  0.163  0.388  0.413 
 0.235  0.284  0.334  0.010  0.110  0.334  0.409  0.509  0.135  0.135  0.309  0.484  0.160  0.608  0.010  0.434  0.434 -0.114 -0.014  0.658 -0.064  0.060  0.160  0.658  0.060  0.260  0.484  0.359  0.359  0.359  0.260  0.210  0.035  0.210  0.185  0.583  0.608 -0.114 -0.114  0.260 -0.014  0.334  0.085  0.658 -0.039  0.484  0.583  0.260  0.384  0.409 
 0.207  0.307  0.357  0.008  0.157  0.382  0.407  0.506  0.133  0.133  0.332  0.481  0.182  0.531  0.033  0.357  0.531 -0.092 -0.092  0.656 -0.092  0.133  0.182  0.656  0.058  0.257  0.481  0.307  0.407  0.257  0.257  0.207  0.033  0.207  0.282  0.581  0.606 -0.117 -0.067  0.282  0.008  0.332  0.033  0.631 -0.042  0.456  0.631  0.282  0.431  0.407 
 0.207  0.307  0.357  0.008  0.157  0.431  0.407  0.506  0.133  0.157  0.332  0.456  0.207  0.531  0.033  0.357  0.556 -0.092 -0.092  0.631 -0.092  0.157  0.157  0.631  0.058  0.232  0.481  0.282  0.431  0.257  0.257  0.207  0.058  0.207  0.332  0.531  0.606 -0.142 -0.067  0.307  0.008  0.332  0.008  0.606 -0.042  0.456  0.631  0.332  0.431  0.357 
 0.227  0.302  0.352  0.003  0.152  0.451  0.377  0.501  0.128  0.152  0.476  0.451  0.227  0.501  0.028  0.352  0.551 -0.072 -0.122  0.626 -0.047  0.177  0.152  0.626  0.053  0.227  0.501  0.252  0.426  0.227  0.277  0.227  0.078  0.202  0.402  0.526  0.551 -0.122 -0.022  0.352  0.003  0.302  0.028  0.576  0.003  0.451  0.626  0.352  0.451  0.352 
 0.223  0.297  0.397  0.023  0.223  0.447  0.372  0.497  0.148  0.148  0.472  0.422  0.248  0.497  0.023  0.347  0.547 -0.076 -0.126  0.621 -0.051  0.198  0.148  0.596  0.048  0.273  0.497  0.248  0.422  0.223  0.273  0.223  0.073  0.223  0.447  0.522  0.522 -0.101 -0.026  0.347 -0.001  0.297  0.023  0.571 -0.026  0.447  0.621  0.322  0.472  0.347 
 0.196  0.296  0.371  0.047  0.221  0.445  0.346  0.495  0.146  0.146  0.470  0.371  0.271  0.495  0.047  0.346  0.570 -0.078 -0.152  0.595 -0.053  0.196  0.171  0.595  0.022  0.246  0.495  0.246  0.421  0.246  0.271  0.246  0.072  0.196  0.445  0.520  0.520 -0.103 -0.003  0.371 -0.003  0.296  0.022  0.570 -0.028  0.445  0.645  0.296  0.470  0.321 
 0.150  0.299  0.374  0.050  0.225  0.449  0.374  0.499  0.150  0.150  0.474  0.374  0.275  0.474  0.050  0.349  0.573 -0.074 -0.149  0.598 -0.049  0.200  0.100  0.598  0.025  0.250  0.524  0.275  0.424  0.175  0.275  0.200  0.075  0.200  0.449  0.499  0.524 -0.099  0.000  0.424  0.025  0.324  0.025  0.573 -0.024  0.449  0.648  0.299  0.474  0.324 
 0.101  0.300  0.375  0.076  0.226  0.450  0.375  0.500  0.176  0.126  0.475  0.350  0.276  0.475  0.026  0.350  0.550 -0.073 -0.148  0.624 -0.023  0.201  0.101  0.599  0.026  0.201  0.525  0.251  0.425  0.176  0.276  0.201  0.076  0.201  0.475  0.475  0.525 -0.123  0.001  0.450  0.026  0.350  0.026  0.574 -0.048  0.400  0.649  0.300  0.475  0.325 
 0.101  0.300  0.375  0.076  0.225  0.474  0.375  0.499  0.175  0.126  0.449  0.350  0.275  0.474  0.026  0.350  0.549 -0.074 -0.148  0.624 -0.024  0.200  0.101  0.599  0.001  0.200  0.524  0.250  0.425  0.200  0.275  0.200  0.076  0.200  0.499  0.474  0.524 -0.124  0.001  0.449  0.026  0.350  0.026  0.574 -0.049  0.400  0.649  0.300  0.474  0.325 
 0.100  0.299  0.374  0.075  0.225  0.474  0.374  0.499  0.175  0.125  0.449  0.349  0.275  0.474  0.050  0.349  0.573 -0.074 -0.149  0.623 -0.024  0.200  0.100  0.598  0.000  0.200  0.524  0.250  0.424  0.225  0.275  0.200  0.050  0.175  0.524  0.474  0.549 -0.124  0.000  0.449  0.025  0.349  0.025  0.549 -0.049  0.399  0.648  0.299  0.474  0.299 
 0.101  0.300  0.375  0.126  0.225  0.474  0.375  0.499  0.175  0.126  0.449  0.350  0.275  0.474  0.051  0.350  0.574 -0.049 -0.148  0.624 -0.024  0.200  0.101  0.599  0.001  0.200  0.524  0.250  0.449  0.200  0.275  0.200  0.051  0.175  0.524  0.474  0.524 -0.124  0.001  0.449  0.026  0.350  0.026  0.524 -0.024  0.400  0.649  0.300  0.474  0.300 
 0.101  0.325  0.350  0.151  0.201  0.450  0.375  0.500  0.176  0.151  0.450  0.325  0.276  0.475  0.051  0.350  0.574 -0.048 -0.148  0.624 -0.023  0.201  0.101  0.599  0.001  0.151  0.525  0.251  0.475  0.201  0.276  0.226  0.051  0.176  0.525  0.475  0.525 -0.123  0.001  0.450  0.026  0.350  0.026  0.525  0.001  0.400  0.649  0.276  0.475  0.300 
 0.117  0.366  0.316  0.117  0.242  0.391  0.341  0.491  0.192  0.142  0.416  0.316  0.242  0.416  0.017  0.316  0.516  0.017 -0.132  0.590 -0.007  0.217  0.017  0.615 -0.007  0.192  0.491  0.242  0.416  0.142  0.291  0.217  0.092  0.167  0.466  0.441  0.416 -0.132  0.017  0.441  0.042  0.316  0.017  0.541 -0.032  0.341  0.516  0.291  0.466  0.316 
 0.050  0.374  0.374  0.025  0.224  0.399  0.374  0.374  0.199  0.149  0.349  0.224  0.174  0.374 -0.025  0.224  0.448 -0.050 -0.125  0.448 -0.050  0.199 -0.075  0.523 -0.025  0.174  0.399  0.274  0.399  0.174  0.224  0.224  0.075  0.075  0.349  0.424  0.399 -0.100  0.000  0.399  0.075  0.324  0.050  0.498 -0.025  0.349  0.473  0.349  0.424  0.324 
 0.063  0.362  0.362  0.013  0.237  0.387  0.387  0.312  0.212  0.162  0.337  0.237  0.187  0.387 -0.012  0.187  0.412 -0.062 -0.137  0.412 -0.037  0.212 -0.062  0.486 -0.012  0.162  0.412  0.262  0.362  0.212  0.187  0.212  0.038  0.038  0.312  0.412  0.412 -0.087 -0.037  0.412  0.063  0.337  0.063  0.511 -0.062  0.362  0.486  0.337  0.436  0.287 
 0.034  0.283  0.358  0.034  0.158  0.408  0.408  0.283  0.233  0.084  0.208  0.208  0.208  0.358  0.009  0.158  0.258 -0.091 -0.116  0.408 -0.041  0.208 -0.016  0.432  0.009  0.134  0.408  0.333  0.308  0.233  0.183  0.233  0.034  0.009  0.233  0.432  0.432 -0.091 -0.041  0.457  0.084  0.333  0.084  0.432 -0.041  0.383  0.507  0.283  0.457  0.283 
 0.016  0.216  0.315  0.041  0.141  0.415  0.440  0.290  0.241  0.091  0.191  0.216  0.166  0.365  0.016  0.166  0.216 -0.083 -0.108  0.415 -0.008  0.191 -0.008  0.440  0.016  0.141  0.390  0.340  0.216  0.241  0.141  0.241  0.041  0.016  0.241  0.440  0.390 -0.083 -0.033  0.465  0.091  0.340  0.116  0.415 -0.008  0.415  0.490  0.241  0.465  0.290 
 0.005  0.130  0.329  0.030  0.130  0.428  0.453  0.279  0.254  0.080  0.154  0.154  0.130  0.379  0.030  0.055  0.080 -0.070 -0.120  0.428 -0.020  0.179  0.005  0.428  0.055  0.179  0.404  0.379  0.204  0.254  0.154  0.179  0.055  0.030  0.204  0.428  0.329 -0.095 -0.045  0.428  0.105  0.329  0.130  0.379 -0.070  0.379  0.453  0.229  0.453  0.304 
 0.012  0.137  0.336  0.012  0.137  0.435  0.460  0.286  0.211  0.037  0.161  0.161  0.137  0.386  0.037  0.062  0.037 -0.063 -0.113  0.411 -0.013  0.186  0.012  0.435  0.062  0.186  0.386  0.361  0.211  0.261  0.161  0.186  0.037  0.012  0.186  0.435  0.311 -0.088 -0.038  0.411  0.087  0.336  0.112  0.311 -0.063  0.361  0.411  0.236  0.460  0.261 
 0.019  0.094  0.318  0.019  0.144  0.468  0.468  0.293  0.194  0.044  0.169  0.144  0.119  0.418  0.044  0.069 -0.030 -0.055 -0.105  0.393 -0.005  0.194  0.019  0.368  0.069  0.194  0.368  0.393  0.194  0.269  0.144  0.169  0.044 -0.005  0.169  0.443  0.293 -0.080 -0.030  0.343  0.019  0.343  0.119  0.244 -0.055  0.343  0.418  0.219  0.443  0.194 
 0.026  0.076  0.325  0.026  0.150  0.449  0.499  0.300  0.200  0.051  0.175  0.126  0.126  0.425  0.026  0.051 -0.024 -0.049 -0.099  0.375  0.001  0.200  0.026  0.325  0.051  0.200  0.375  0.400  0.200  0.275  0.150  0.150  0.051  0.001  0.150  0.449  0.250 -0.074 -0.024  0.275  0.001  0.300  0.101  0.225 -0.049  0.325  0.400  0.225  0.425  0.175 
 0.038  0.088  0.287  0.038  0.138  0.412  0.462  0.263  0.188 -0.011  0.188  0.113  0.113  0.412 -0.011  0.038 -0.011 -0.036 -0.086  0.387  0.013  0.188  0.013  0.238  0.063  0.213  0.387  0.387  0.188  0.287  0.138  0.088  0.038 -0.036  0.163  0.462  0.238 -0.061 -0.011  0.238 -0.036  0.312  0.113  0.188 -0.036  0.287  0.387  0.188  0.362  0.188 
 0.025  0.075  0.275  0.025  0.150  0.324  0.424  0.250  0.200 -0.024  0.200  0.050  0.125  0.299 -0.049  0.025  0.000 -0.024 -0.074  0.275  0.025  0.200  0.025  0.150  0.000  0.200  0.349  0.399  0.200  0.299  0.100  0.075  0.025 -0.049  0.200  0.474  0.175 -0.049 -0.024  0.175 -0.024  0.250  0.100  0.200 -0.074  0.299  0.399  0.175  0.275  0.225 
 0.039  0.014  0.214  0.014  0.164  0.214  0.463  0.239  0.189 -0.010  0.189  0.039  0.139  0.239 -0.035  0.014  0.014 -0.010 -0.060  0.189  0.039  0.164  0.014  0.064  0.014  0.214  0.338  0.363  0.164  0.264  0.114  0.089  0.014 -0.035  0.214  0.488  0.114 -0.035 -0.010  0.114 -0.010  0.189  0.039  0.164 -0.060  0.264  0.338  0.164  0.214  0.214 
 0.023 -0.002  0.172 -0.002  0.147  0.172  0.446  0.222  0.197 -0.002  0.172  0.048  0.123  0.222 -0.027  0.023  0.023 -0.002 -0.052  0.123  0.048  0.147  0.023  0.073 -0.002  0.222  0.222  0.297  0.147  0.272  0.123  0.098 -0.002 -0.027  0.197  0.422  0.073 -0.027 -0.002  0.048 -0.027  0.123  0.048  0.123 -0.052  0.272  0.322  0.172  0.172  0.222 
 0.021 -0.028  0.071  0.021  0.121  0.096  0.271  0.121  0.146 -0.003  0.121 -0.003  0.071  0.146 -0.003  0.021  0.046  0.021 -0.028  0.071  0.071  0.046  0.021 -0.003  0.021  0.171  0.146  0.146  0.096  0.146  0.046  0.071  0.021 -0.028  0.146  0.395 -0.003 -0.028  0.021 -0.028 -0.003  0.146  0.021 -0.003 -0.028  0.171  0.221  0.046  0.121  0.121 
 0.011 -0.014 -0.014  0.011  0.036  0.061  0.136  0.061  0.036 -0.014  0.061 -0.014 -0.014  0.061  0.011  0.011 -0.014 -0.014 -0.014  0.061  0.086  0.036 -0.014  0.011  0.011  0.061  0.086  0.111  0.111  0.036  0.011  0.061  0.011 -0.014  0.111  0.235  0.011 -0.014  0.036 -0.014 -0.014  0.061  0.011  0.011 -0.014  0.061  0.111  0.036  0.086  0.036 
-0.001 -0.001 -0.001 -0.001  0.048  0.023  0.048  0.023  0.023 -0.001  0.023 -0.001 -0.001  0.023  0.023 -0.001 -0.001 -0.001 -0.001 -0.001  0.023  0.023 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.023 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.048 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.023 -0.001  0.023 
-0.001 -0.001 -0.001 -0.001  0.024  0.024  0.024  0.024  0.024 -0.001 -0.001 -0.001 -0.001 -0.001  0.024 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.024 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.024 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.049 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.024 -0.001 -0.001 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.001  0.004 -0.020  0.004  0.029  0.004  0.029  0.054  0.004  0.004  0.029  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.054 -0.020 -0.020  0.054  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.029 
 1.000  0.003 -0.021  0.003  0.028  0.003  0.028  0.053  0.003  0.003  0.028  0.003 -0.021  0.003 -0.021  0.003 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021  0.028 -0.021  0.003 -0.021  0.003 -0.021  0.003 -0.021 -0.021  0.053 -0.021 -0.021  0.053  0.003  0.003  0.003  0.028  0.028 -0.021  0.003  0.028 -0.021 -0.021 -0.021 -0.021  0.003 -0.021  0.028 
 0.998  0.001 -0.023  0.026  0.026  0.026  0.026  0.051  0.001  0.001  0.026  0.001  0.001  0.001 -0.023  0.001 -0.023 -0.023 -0.023 -0.023 -0.023 -0.023  0.026 -0.023  0.001 -0.023  0.001 -0.023  0.001 -0.023 -0.023  0.051 -0.023 -0.023  0.051  0.001  0.001  0.001  0.026  0.026 -0.023  0.001  0.026 -0.023 -0.023 -0.023 -0.023  0.026 -0.023  0.026 
 0.991 -0.005 -0.030  0.044  0.019  0.019  0.019  0.094 -0.005 -0.005  0.044 -0.005 -0.005 -0.005 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.030 -0.030  0.019 -0.030 -0.005 -0.030  0.044 -0.030 -0.005 -0.030 -0.005  0.094 -0.030 -0.030  0.044  0.019  0.044 -0.005  0.019  0.044 -0.030 -0.005  0.044 -0.030 -0.005 -0.030 -0.030  0.019 -0.030  0.019 
 0.977 -0.020 -0.020  0.055  0.005  0.005  0.005  0.130 -0.020 -0.020  0.080  0.030 -0.020  0.030 -0.045  0.030 -0.020 -0.045 -0.045 -0.045 -0.045 -0.045  0.005  0.005 -0.020 -0.045  0.030 -0.045 -0.020 -0.045 -0.020  0.179 -0.045 -0.045  0.030  0.005  0.055 -0.020  0.030  0.080 -0.045 -0.020  0.030 -0.020  0.005 -0.020 -0.045  0.005 -0.045  0.005 
 0.953 -0.018 -0.018  0.031  0.006  0.031 -0.018  0.181 -0.043 -0.043  0.056  0.031 -0.043  0.006 -0.068  0.081 -0.043  0.006 -0.043 -0.018 -0.043 -0.043  0.031 -0.018 -0.018 -0.068  0.056 -0.018 -0.018 -0.068 -0.043  0.380 -0.068 -0.018  0.006  0.031  0.206  0.006  0.056  0.106 -0.043 -0.018  0.006 -0.018  0.006  0.056 -0.043  0.056 -0.043  0.031 
 0.918 -0.029  0.046 -0.004 -0.004  0.021  0.021  0.295 -0.029 -0.079  0.021  0.021 -0.054  0.021 -0.004  0.170 -0.054 -0.004 -0.054 -0.029 -0.054 -0.004  0.046 -0.054 -0.029 -0.079  0.046 -0.029 -0.004 -0.054 -0.004  0.669 -0.104 -0.004  0.021  0.046  0.295 -0.004  0.071  0.195  0.046  0.021 -0.029 -0.054 -0.004  0.096 -0.079  0.170 -0.054  0.021 
 0.886 -0.011  0.188 -0.011 -0.011  0.064  0.064  0.363 -0.011 -0.111 -0.011  0.039 -0.086 -0.011  0.039  0.288 -0.086 -0.011 -0.061 -0.061 -0.086  0.039  0.014 -0.086 -0.036 -0.086 -0.011 -0.036 -0.011  0.014 -0.011  0.786 -0.136 -0.011  0.014  0.114  0.288 -0.011  0.064  0.363  0.064  0.014 -0.011 -0.061 -0.036  0.114 -0.086  0.188 -0.086  0.014 
 0.828 -0.019  0.155  0.105 -0.069  0.080  0.105  0.529 -0.044 -0.119  0.030  0.030  0.030 -0.019  0.030  0.379 -0.069  0.030 -0.044 -0.094 -0.094  0.005  0.030 -0.044  0.030 -0.094 -0.069 -0.094  0.005  0.105 -0.019  0.828 -0.119  0.005  0.005  0.080  0.454 -0.019  0.130  0.504  0.205  0.030 -0.044 -0.019 -0.069  0.230 -0.069  0.280 -0.094  0.055 
 0.801 -0.046  0.153  0.129 -0.096  0.079  0.054  0.552 -0.021 -0.145  0.079  0.029  0.029  0.004  0.004  0.353 -0.021  0.029 -0.046 -0.121 -0.071  0.029  0.029 -0.046  0.029 -0.071 -0.021 -0.121 -0.021  0.079  0.004  0.801 -0.121 -0.021  0.004  0.054  0.527 -0.021  0.178  0.552  0.278  0.004  0.004 -0.021 -0.096  0.303 -0.096  0.328 -0.071  0.054 
 0.744 -0.053  0.146  0.171 -0.128  0.096  0.146  0.619 -0.028 -0.153  0.071  0.071  0.071  0.021 -0.028  0.320  0.021  0.021 -0.078 -0.128 -0.003  0.071 -0.003 -0.053  0.071 -0.028  0.021 -0.028 -0.028  0.121  0.046  0.719 -0.128  0.021  0.046  0.021  0.495 -0.053  0.221  0.569  0.370  0.021  0.021  0.021 -0.128  0.370 -0.103  0.420 -0.028  0.171 
 0.707 -0.065  0.159  0.184 -0.165  0.134  0.134  0.607  0.009 -0.190  0.034  0.109  0.059  0.059 -0.065  0.308 -0.015  0.059 -0.090 -0.115  0.009  0.059  0.009 -0.065  0.084 -0.040  0.059  0.009 -0.015  0.109  0.084  0.682 -0.140  0.009  0.009  0.034  0.483 -0.065  0.234  0.632  0.383  0.009  0.034  0.084 -0.140  0.433 -0.065  0.433 -0.040  0.234 
 0.669 -0.029  0.145  0.195 -0.178  0.121  0.170  0.594  0.046 -0.203  0.046  0.145  0.071  0.071 -0.079  0.270  0.021  0.046 -0.104 -0.129  0.096  0.096 -0.004 -0.079  0.096 -0.029  0.071 -0.004 -0.004  0.145  0.071  0.669 -0.153 -0.029  0.046  0.046  0.395 -0.104  0.295  0.644  0.370  0.096  0.021  0.145 -0.153  0.444  0.021  0.444 -0.004  0.345 
 0.644 -0.053  0.146  0.196 -0.178  0.146  0.171  0.569  0.046 -0.203  0.046  0.171  0.046  0.071 -0.103  0.295  0.046  0.046 -0.103 -0.103  0.096  0.121 -0.028 -0.053  0.096 -0.028  0.096 -0.028 -0.028  0.146  0.096  0.669 -0.153 -0.053  0.046  0.071  0.370 -0.103  0.295  0.644  0.320  0.096 -0.028  0.121 -0.153  0.445  0.046  0.495  0.021  0.395 
 0.611 -0.037  0.113  0.212 -0.137  0.138  0.262  0.586  0.063 -0.186  0.113  0.162  0.013  0.088 -0.112  0.262  0.113  0.088 -0.112 -0.137  0.162  0.113 -0.037 -0.012  0.088 -0.037  0.138  0.013  0.013  0.162  0.113  0.636 -0.137 -0.087  0.063  0.138  0.337 -0.112  0.287  0.611  0.312  0.162 -0.037  0.113 -0.137  0.436  0.113  0.486  0.063  0.436 
 0.581 -0.016  0.108  0.208 -0.141  0.133  0.283  0.581  0.058 -0.191  0.108  0.158  0.033  0.183 -0.116  0.283  0.158  0.033 -0.091 -0.141  0.208  0.108 -0.016  0.008  0.083 -0.016  0.158  0.083  0.008  0.208  0.133  0.631 -0.141 -0.091  0.058  0.133  0.382 -0.116  0.283  0.581  0.307  0.208 -0.041  0.133 -0.141  0.432  0.108  0.457  0.133  0.507 
 0.544 -0.029  0.095  0.220 -0.129  0.070  0.294  0.568  0.045 -0.129  0.120  0.245  0.070  0.245 -0.129  0.220  0.195  0.045 -0.104 -0.129  0.444  0.095 -0.004  0.070  0.070  0.020  0.195  0.170  0.020  0.294  0.170  0.618 -0.154 -0.104  0.045  0.120  0.419 -0.104  0.294  0.568  0.319  0.195 -0.029  0.145 -0.179  0.419  0.095  0.444  0.220  0.544 
 0.539 -0.009  0.140  0.215 -0.109  0.065  0.314  0.564  0.015 -0.134  0.140  0.240  0.090  0.265 -0.134  0.240  0.190  0.040 -0.134 -0.109  0.464  0.090 -0.009  0.090  0.065  0.065  0.190  0.215  0.015  0.314  0.165  0.613 -0.134 -0.109  0.040  0.190  0.439 -0.059  0.289  0.564  0.314  0.240 -0.034  0.215 -0.184  0.439  0.190  0.439  0.240  0.613 
 0.504 -0.019  0.130  0.180 -0.094  0.030  0.354  0.529  0.030 -0.144  0.105  0.255  0.080  0.304 -0.094  0.180  0.205  0.030 -0.144 -0.094  0.529  0.080 -0.019  0.180  0.005  0.155  0.205  0.280  0.055  0.329  0.180  0.578 -0.144 -0.094  0.130  0.230  0.404  0.005  0.255  0.529  0.329  0.255  0.005  0.230 -0.219  0.404  0.230  0.379  0.354  0.603 
 0.577 -0.020  0.104  0.204 -0.070  0.029  0.378  0.428  0.054 -0.120  0.104  0.204  0.104  0.303 -0.095  0.129  0.179  0.004 -0.070 -0.045  0.528  0.154 -0.020  0.204  0.004  0.204  0.229  0.279  0.079  0.353  0.154  0.428 -0.070 -0.145  0.129  0.204  0.303  0.004  0.179  0.528  0.279  0.279  0.004  0.179 -0.145  0.353  0.154  0.378  0.254  0.602 
 0.396  0.022  0.097  0.147 -0.027  0.097  0.371  0.396  0.097 -0.102  0.072  0.147  0.097  0.296 -0.077  0.122  0.097  0.047 -0.077 -0.077  0.421  0.197 -0.077  0.222  0.047  0.172  0.272  0.222  0.072  0.296  0.172  0.247 -0.002 -0.127  0.072  0.197  0.247 -0.027  0.122  0.521  0.197  0.321  0.022  0.097 -0.102  0.321  0.122  0.371  0.222  0.521 
 0.290  0.041  0.116  0.166 -0.008  0.116  0.340  0.365  0.066 -0.083  0.091  0.166  0.066  0.266 -0.058  0.141  0.066  0.041 -0.058 -0.058  0.390  0.216 -0.058  0.216  0.041  0.116  0.290  0.241  0.091  0.266  0.166  0.216  0.016 -0.108  0.091  0.216  0.241 -0.033  0.116  0.589  0.191  0.340  0.041  0.091 -0.083  0.290  0.141  0.365  0.216  0.540 
 0.266  0.041  0.141  0.066  0.016  0.141  0.365  0.315  0.066 -0.083  0.091  0.166  0.066  0.290 -0.058  0.141  0.016  0.016 -0.058 -0.033  0.340  0.166 -0.033  0.241  0.066  0.091  0.340  0.216  0.091  0.216  0.116  0.216 -0.008 -0.083  0.066  0.141  0.241 -0.008  0.066  0.614  0.116  0.365  0.066  0.091 -0.058  0.216  0.066  0.315  0.191  0.465 
 0.253  0.029  0.153  0.054  0.029  0.129  0.378  0.303  0.079 -0.046  0.054  0.129  0.029  0.228 -0.046  0.129 -0.046  0.029 -0.046 -0.021  0.278  0.153 -0.021  0.203  0.029  0.079  0.353  0.178  0.104  0.178  0.153  0.203 -0.021 -0.071  0.054  0.153  0.278  0.004  0.079  0.652  0.104  0.378  0.079  0.104 -0.071  0.228  0.054  0.328  0.129  0.427 
 0.143  0.019  0.168  0.019  0.044  0.143  0.318  0.293  0.094 -0.031  0.019  0.119  0.019  0.218 -0.031  0.094 -0.031  0.019 -0.056 -0.031  0.193  0.168 -0.006  0.218  0.044  0.069  0.368  0.168  0.019  0.119  0.168  0.218 -0.056 -0.056  0.019  0.143  0.293 -0.006  0.094  0.692  0.094  0.393  0.094  0.119 -0.056  0.193  0.044  0.318  0.143  0.368 
 0.127  0.002  0.152  0.027  0.027  0.127  0.326  0.277  0.052  0.002  0.002  0.077  0.027  0.202 -0.022  0.102 -0.022  0.002 -0.072 -0.072  0.127  0.152  0.002  0.202  0.052  0.077  0.326  0.152  0.027  0.077  0.202  0.202 -0.047 -0.047  0.027  0.102  0.252  0.002  0.077  0.750  0.127  0.301  0.077  0.127 -0.047  0.177  0.052  0.301  0.077  0.326 
 0.094 -0.005  0.144  0.044  0.019  0.094  0.219  0.144  0.069  0.019  0.019  0.019  0.019  0.219 -0.055  0.119 -0.030  0.019 -0.055 -0.055  0.094  0.119 -0.005  0.194  0.044  0.094  0.318  0.094  0.019  0.069  0.169  0.169 -0.030 -0.030  0.044  0.069  0.244  0.019  0.019  0.742  0.094  0.293  0.069  0.094 -0.030  0.169  0.019  0.293  0.094  0.144 
 0.057  0.007  0.107  0.057  0.007  0.082  0.181  0.107  0.032  0.007  0.007  0.007  0.032  0.107 -0.043  0.082 -0.018  0.032 -0.043 -0.043  0.057  0.032 -0.018  0.082  0.032  0.057  0.281  0.057  0.007  0.082  0.057  0.156 -0.018 -0.018  0.057  0.057  0.181 -0.018  0.007  0.829  0.057  0.181  0.032  0.057 -0.018  0.132 -0.018  0.231  0.057  0.032 
 0.024 -0.000  0.024  0.024 -0.025  0.074  0.049 -0.000 -0.025  0.024 -0.000 -0.025  0.024  0.049 -0.025 -0.000 -0.000 -0.000 -0.025 -0.025 -0.025 -0.000 -0.000  0.074 -0.025 -0.000  0.049  0.024 -0.025  0.024 -0.000  0.049 -0.025 -0.025 -0.000 -0.000  0.074 -0.025  0.049  0.971  0.049  0.074 -0.025 -0.000 -0.000 -0.000  0.024  0.099 -0.000  0.024 
 0.028 -0.022  0.003  0.003 -0.022  0.053  0.028  0.003 -0.022  0.028  0.003 -0.022  0.028  0.053 -0.022  0.003  0.003 -0.022 -0.022 -0.022 -0.022  0.003  0.003  0.053 -0.022 -0.022  0.003  0.028 -0.022  0.028 -0.022  0.053 -0.022 -0.022  0.003  0.003  0.028 -0.022  0.053  0.999  0.028  0.028 -0.022  0.003  0.003  0.003  0.028  0.028  0.003  0.028 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
 0.025 -0.024 -0.024  0.000 -0.024  0.025  0.000  0.000  0.000  0.025  0.000 -0.024  0.025  0.050 -0.024  0.000  0.000 -0.024 -0.024 -0.024 -0.024  0.000  0.000  0.050 -0.024 -0.024 -0.024  0.050 -0.024  0.025 -0.024  0.050 -0.024 -0.024  0.000 -0.024  0.000 -0.024  0.100  0.997  0.050 -0.024  0.000  0.000  0.000 -0.024  0.050  0.025  0.000  0.025 
 0.067 -0.032 -0.032 -0.007 -0.007  0.017  0.017 -0.007 -0.007  0.017  0.017 -0.007  0.042  0.117 -0.007 -0.007 -0.007 -0.032 -0.032 -0.032 -0.032 -0.007 -0.007  0.042  0.042 -0.007 -0.007  0.067 -0.032  0.042 -0.007  0.042  0.017 -0.032  0.017 -0.032  0.017 -0.032  0.092  0.989  0.067 -0.032  0.017 -0.007 -0.007 -0.007  0.042  0.042  0.017  0.042 
 0.139 -0.061 -0.036  0.039 -0.036 -0.011  0.064 -0.011  0.089  0.064 -0.011  0.064  0.089  0.188 -0.036 -0.036  0.014 -0.036 -0.061 -0.061 -0.036 -0.036  0.014  0.064  0.114  0.014  0.089  0.163 -0.036  0.064  0.039  0.039 -0.011 -0.011  0.014 -0.036  0.039 -0.061  0.114  0.961  0.114  0.014  0.039 -0.036  0.014 -0.011  0.014  0.039  0.014  0.014 
 0.245 -0.004 -0.029  0.020 -0.029 -0.054  0.170 -0.054  0.220  0.095 -0.004  0.045  0.120  0.469 -0.054 -0.079 -0.054 -0.079 -0.129 -0.104 -0.004  0.070 -0.004  0.170  0.120 -0.029  0.270  0.145 -0.054  0.070  0.045  0.020 -0.079 -0.029  0.070 -0.029 -0.004 -0.054  0.145  0.892  0.170  0.120 -0.004  0.045  0.045  0.045  0.045  0.145  0.045  0.020 
 0.403  0.004 -0.020  0.004  0.004  0.004  0.254 -0.045  0.229  0.104 -0.020  0.129  0.104  0.478 -0.095  0.004 -0.095 -0.070 -0.170 -0.120  0.054  0.029 -0.020  0.254  0.129  0.004  0.279  0.029 -0.045  0.004  0.079  0.004 -0.120 -0.070  0.054 -0.020  0.029 -0.070  0.129  0.852  0.204  0.303 -0.020  0.104  0.004  0.104  0.004  0.229  0.029  0.104 
 0.490 -0.058 -0.033 -0.058 -0.058  0.016  0.315 -0.058  0.166  0.141 -0.008  0.241  0.066  0.589 -0.108 -0.033 -0.058 -0.133 -0.233 -0.108  0.166  0.041  0.016  0.365  0.091  0.091  0.340  0.016 -0.108 -0.008  0.116 -0.058 -0.133 -0.133  0.041 -0.033  0.091 -0.033  0.066  0.789  0.216  0.365  0.041  0.216 -0.033  0.041 -0.033  0.216 -0.008  0.290 
 0.468 -0.080 -0.055 -0.055 -0.080 -0.005  0.369  0.070  0.120  0.169 -0.055  0.344  0.045  0.593 -0.105 -0.005 -0.080 -0.080 -0.229 -0.105  0.169  0.070  0.095  0.468  0.070  0.070  0.344  0.020 -0.130  0.045  0.169  0.020 -0.105 -0.130  0.045  0.020  0.095 -0.030  0.194  0.717  0.269  0.394  0.070  0.219 -0.055  0.045  0.020  0.169 -0.030  0.394 
 0.492 -0.006 -0.056  0.044 -0.106 -0.031  0.368  0.168  0.044  0.143 -0.081  0.442 -0.006  0.592 -0.131  0.119 -0.106 -0.081 -0.230 -0.131  0.268  0.119  0.119  0.467  0.044  0.119  0.318  0.019 -0.106  0.094  0.143  0.094 -0.131 -0.131  0.094  0.019  0.143  0.019  0.218  0.642  0.318  0.393  0.044  0.268 -0.131  0.143 -0.006  0.193 -0.031  0.467 
 0.501  0.027 -0.047  0.027 -0.122 -0.022  0.351  0.252  0.002  0.152 -0.097  0.476  0.002  0.575 -0.147  0.177 -0.097 -0.097 -0.247 -0.097  0.252  0.127  0.102  0.426  0.027  0.102  0.351  0.127  0.002  0.077  0.177  0.127 -0.122 -0.147  0.102  0.102  0.127  0.077  0.202  0.600  0.277  0.376  0.027  0.301 -0.122  0.202 -0.047  0.227  0.052  0.476 
 0.508  0.060 -0.065  0.085 -0.115 -0.015  0.334  0.284  0.010  0.110 -0.090  0.483  0.035  0.508 -0.140  0.184 -0.065 -0.090 -0.264 -0.140  0.384  0.135  0.085  0.409 -0.015  0.234  0.334  0.159 -0.015  0.135  0.159  0.209 -0.164 -0.164  0.110  0.184  0.159  0.110  0.209  0.583  0.259  0.359  0.035  0.309 -0.164  0.284  0.010  0.284  0.060  0.508 
 0.503  0.029 -0.070  0.079 -0.095 -0.045  0.328  0.378  0.004  0.079 -0.095  0.478  0.054  0.453 -0.145  0.179 -0.095 -0.120 -0.270 -0.070  0.478  0.104  0.079  0.403  0.004  0.303  0.328  0.179 -0.020  0.129  0.129  0.229 -0.170 -0.170  0.104  0.204  0.154  0.104  0.229  0.577  0.229  0.353  0.029  0.328 -0.170  0.279  0.029  0.279  0.129  0.503 
 0.499  0.000 -0.024  0.125 -0.099  0.000  0.324  0.374  0.000  0.075 -0.049  0.474  0.050  0.374 -0.124  0.150 -0.099 -0.124 -0.249 -0.074  0.499  0.125  0.075  0.399 -0.024  0.299  0.324  0.225  0.025  0.150  0.175  0.225 -0.124 -0.174  0.100  0.250  0.150  0.100  0.250  0.598  0.200  0.349  0.025  0.349 -0.199  0.349  0.050  0.275  0.200  0.524 
 0.493  0.020 -0.030  0.120 -0.105 -0.005  0.319  0.394  0.045  0.144 -0.030  0.443  0.020  0.369 -0.130  0.120 -0.055 -0.130 -0.204 -0.055  0.543  0.144  0.095  0.394 -0.030  0.294  0.319  0.269 -0.005  0.169  0.194  0.219 -0.130 -0.179  0.095  0.269  0.194  0.120  0.269  0.568  0.194  0.344  0.020  0.344 -0.204  0.419  0.045  0.269  0.219  0.543 
 0.487  0.014 -0.036  0.114 -0.061 -0.011  0.288  0.437  0.039  0.114 -0.036  0.413  0.039  0.338 -0.111  0.139  0.039 -0.111 -0.210 -0.061  0.537  0.163  0.089  0.363 -0.036  0.313  0.313  0.338 -0.011  0.188  0.238  0.213 -0.111 -0.160  0.089  0.263  0.188  0.139  0.263  0.562  0.163  0.338  0.039  0.338 -0.210  0.437  0.089  0.263  0.263  0.562 
 0.485 -0.013 -0.013  0.111 -0.063 -0.013  0.285  0.435  0.036  0.111 -0.038  0.385  0.036  0.335 -0.113  0.136  0.061 -0.088 -0.213 -0.063  0.560  0.161  0.086  0.335 -0.013  0.310  0.285  0.335 -0.013  0.236  0.236  0.211 -0.113 -0.163  0.086  0.261  0.261  0.136  0.261  0.560  0.161  0.335  0.036  0.335 -0.213  0.435  0.111  0.310  0.285  0.560 
 0.486 -0.012 -0.012  0.112 -0.037 -0.012  0.286  0.436  0.037  0.112 -0.037  0.311  0.037  0.361 -0.112  0.112  0.087 -0.087 -0.212 -0.062  0.585  0.162  0.062  0.336 -0.012  0.336  0.286  0.311  0.037  0.237  0.237  0.212 -0.112 -0.137  0.112  0.286  0.311  0.137  0.262  0.561  0.162  0.336  0.062  0.336 -0.212  0.436  0.162  0.311  0.311  0.561 
 0.485 -0.013 -0.013  0.112 -0.038 -0.013  0.311  0.435  0.037  0.112 -0.038  0.311  0.037  0.361 -0.138  0.112  0.087 -0.088 -0.212 -0.063  0.585  0.137  0.087  0.336 -0.013  0.336  0.286  0.311  0.037  0.236  0.236  0.211 -0.113 -0.138  0.137  0.286  0.336  0.137  0.261  0.560  0.161  0.336  0.062  0.336 -0.237  0.435  0.186  0.311  0.311  0.585 
 0.485 -0.013 -0.013  0.062 -0.038 -0.013  0.311  0.460  0.012  0.186 -0.038  0.286  0.037  0.386 -0.113  0.112  0.087 -0.088 -0.212 -0.063  0.585  0.112  0.062  0.336 -0.013  0.336  0.286  0.311  0.062  0.236  0.261  0.211 -0.113 -0.138  0.161  0.286  0.386  0.137  0.261  0.560  0.161  0.336  0.037  0.361 -0.237  0.435  0.211  0.311  0.311  0.585 
 0.483 -0.015  0.010  0.035 -0.015 -0.015  0.309  0.458  0.010  0.209 -0.015  0.284  0.035  0.384 -0.115  0.110  0.110 -0.090 -0.214 -0.065  0.583  0.110  0.035  0.309 -0.015  0.334  0.284  0.309  0.085  0.234  0.234  0.234 -0.115 -0.140  0.159  0.284  0.409  0.135  0.259  0.558  0.135  0.334  0.010  0.359 -0.214  0.433  0.209  0.309  0.309  0.583 
 0.505 -0.018  0.007  0.032  0.007  0.007  0.306  0.455  0.007  0.256 -0.018  0.281  0.032  0.430 -0.118  0.107  0.132 -0.093 -0.217 -0.068  0.580  0.107  0.032  0.306 -0.018  0.356  0.281  0.306  0.082  0.231  0.231  0.231 -0.118 -0.142  0.156  0.281  0.430  0.132  0.256  0.555  0.132  0.356  0.007  0.356 -0.242  0.406  0.206  0.331  0.306  0.555 
 0.455 -0.043  0.081  0.056 -0.018  0.081  0.305  0.430  0.056  0.156  0.006  0.156  0.056  0.355 -0.093  0.056  0.006 -0.068 -0.168 -0.043  0.555  0.131 -0.018  0.231  0.006  0.281  0.281  0.330  0.081  0.231  0.281  0.281 -0.118 -0.118  0.131  0.305  0.505  0.181  0.106  0.505  0.081  0.355  0.006  0.355 -0.193  0.405  0.206  0.281  0.281  0.579 
 0.336  0.012  0.087  0.062  0.012  0.087  0.311  0.361  0.087  0.087  0.037  0.112  0.062  0.261 -0.088  0.137 -0.088 -0.063 -0.113  0.012  0.460  0.211 -0.113  0.286  0.087  0.336  0.336  0.311  0.012  0.261  0.311  0.186 -0.088 -0.088  0.112  0.211  0.311  0.137  0.062  0.560  0.062  0.361  0.037  0.211 -0.138  0.286  0.087  0.261  0.236  0.510 
 0.287 -0.012  0.113  0.013  0.013  0.113  0.312  0.362  0.113  0.063  0.063  0.138 -0.012  0.262 -0.112  0.088 -0.112 -0.037 -0.112  0.013  0.436  0.212 -0.087  0.312  0.088  0.362  0.337  0.287  0.038  0.212  0.337  0.138 -0.062 -0.062  0.113  0.187  0.312  0.113  0.088  0.586  0.038  0.387  0.063  0.162 -0.112  0.287  0.088  0.287  0.237  0.436 
 0.187  0.013  0.138  0.038  0.038  0.138  0.287  0.337  0.113 -0.062  0.038  0.138 -0.012  0.262 -0.062  0.063 -0.112 -0.012 -0.087 -0.012  0.461  0.212 -0.062  0.362  0.113  0.362  0.362  0.237  0.063  0.187  0.262  0.113 -0.062 -0.062  0.088  0.138  0.287  0.013  0.063  0.586 -0.012  0.387  0.088  0.113 -0.087  0.262  0.063  0.312  0.212  0.337 
 0.098  0.023  0.147  0.048  0.048  0.123  0.272  0.297  0.073 -0.027  0.048  0.147  0.023  0.197 -0.052  0.048 -0.102 -0.002 -0.077 -0.052  0.496  0.222 -0.077  0.372  0.123  0.322  0.372  0.272  0.073  0.172  0.197  0.098 -0.052 -0.077  0.048  0.098  0.297  0.023  0.023  0.596 -0.027  0.397  0.073  0.123 -0.077  0.247  0.048  0.322  0.222  0.247 
 0.068  0.018  0.143  0.068  0.043  0.118  0.243  0.193  0.068 -0.006  0.043  0.118 -0.006  0.218 -0.031  0.018 -0.081  0.018 -0.056 -0.031  0.467  0.193 -0.056  0.268  0.118  0.268  0.392  0.243  0.068  0.168  0.168  0.118 -0.056 -0.081  0.068  0.093  0.268 -0.056 -0.006  0.616 -0.006  0.392  0.018  0.093 -0.056  0.218  0.043  0.292  0.218  0.193 
 0.054  0.029  0.153  0.054  0.054  0.129  0.228  0.203  0.079  0.004  0.054  0.129  0.004  0.228 -0.021  0.029 -0.071  0.029 -0.046 -0.046  0.378  0.178 -0.046  0.278  0.129  0.253  0.403  0.278  0.054  0.153  0.153  0.129 -0.046 -0.071  0.054  0.104  0.203 -0.046  0.004  0.652  0.004  0.353  0.029  0.104 -0.046  0.178  0.079  0.278  0.228  0.178 
 0.048 -0.002  0.098  0.048  0.073  0.098  0.147  0.172 -0.002  0.023  0.023  0.048 -0.002  0.247 -0.027  0.048 -0.052  0.023 -0.052 -0.027  0.322  0.073 -0.002  0.247  0.098  0.147  0.422  0.297 -0.002  0.123  0.073  0.098 -0.027 -0.052  0.048  0.073  0.197 -0.052 -0.002  0.720 -0.002  0.347  0.048  0.123 -0.027  0.073  0.048  0.098  0.123  0.048 
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 0.018 -0.031  0.018  0.018 -0.006  0.043  0.118  0.043 -0.031  0.043  0.018 -0.006  0.018  0.168 -0.031  0.018 -0.006 -0.006 -0.031 -0.031  0.118 -0.006 -0.006  0.168 -0.031  0.068  0.143  0.168 -0.031  0.043  0.018  0.043 -0.031 -0.031  0.018 -0.006  0.043 -0.031  0.018  0.940  0.018  0.218 -0.006  0.093  0.018 -0.031  0.018  0.068  0.043 -0.006 
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 0.029 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.054 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.029 -0.020  0.029 -0.020  0.054 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.054  1.001  0.029 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.029  0.004  0.004 
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 0.171 -0.028 -0.028  0.046 -0.003  0.021  0.021 -0.003 -0.003  0.021  0.021 -0.028  0.021  0.071 -0.028 -0.003 -0.003 -0.028 -0.028 -0.028 -0.028 -0.003  0.021  0.046  0.046 -0.028  0.021  0.046 -0.028  0.021 -0.028  0.046 -0.003 -0.028  0.046 -0.003 -0.003 -0.028  0.071  0.993  0.046 -0.028 -0.003 -0.003 -0.003 -0.028  0.046  0.021 -0.003  0.046 
 0.517 -0.031 -0.031  0.093  0.018 -0.006  0.043  0.093 -0.006  0.043 -0.006 -0.031  0.018  0.093 -0.031 -0.031 -0.031 -0.056 -0.056 -0.056 -0.031 -0.031  0.043  0.018  0.068 -0.031  0.168  0.093 -0.031  0.018  0.018  0.043 -0.031 -0.056  0.043 -0.031 -0.006 -0.056  0.043  0.965  0.068  0.018 -0.006  0.018 -0.031  0.018  0.018  0.043 -0.006  0.043 
 0.731 -0.041 -0.041  0.133  0.008  0.033  0.133  0.108  0.008  0.083 -0.041 -0.016  0.058  0.108 -0.041 -0.016 -0.066 -0.091 -0.091 -0.041 -0.066 -0.066  0.083  0.008  0.083 -0.016  0.208  0.058 -0.016 -0.016  0.058  0.108 -0.066 -0.066  0.033  0.033  0.008 -0.066  0.033  0.930  0.058  0.083  0.008  0.008 -0.041  0.033 -0.016  0.083 -0.041  0.058 
 0.860 -0.011 -0.011  0.088 -0.011  0.038  0.213  0.138  0.038  0.038 -0.061  0.013  0.038  0.188 -0.111  0.013 -0.136 -0.086 -0.161 -0.086  0.013 -0.086  0.063  0.188  0.138  0.038  0.412  0.088 -0.011  0.063  0.188  0.188 -0.136 -0.136  0.063  0.013  0.063 -0.036  0.063  0.860  0.188  0.263  0.038  0.113 -0.086 -0.011 -0.011  0.138  0.013  0.138 
 0.816  0.093 -0.056  0.068 -0.056  0.018  0.218  0.168  0.018  0.018 -0.081  0.068  0.043  0.317 -0.156  0.043 -0.156 -0.131 -0.206 -0.131  0.093 -0.056  0.043  0.292  0.093  0.093  0.392  0.068 -0.006  0.093  0.168  0.218 -0.131 -0.156  0.068  0.018  0.118 -0.081  0.068  0.816  0.243  0.442  0.018  0.093 -0.081 -0.031 -0.056  0.218  0.043  0.218 
 0.738  0.115 -0.034  0.115 -0.084 -0.009  0.314  0.215  0.065  0.040 -0.109  0.115  0.015  0.389 -0.184  0.115 -0.209 -0.109 -0.259 -0.134  0.190 -0.034  0.090  0.364  0.065  0.115  0.389  0.065 -0.009  0.090  0.190  0.265 -0.159 -0.159  0.065  0.090  0.140 -0.034  0.115  0.763  0.240  0.439  0.040  0.190 -0.134  0.065 -0.034  0.215  0.115  0.364 
 0.717  0.144 -0.030  0.095 -0.105 -0.030  0.294  0.294  0.045  0.045 -0.105  0.095  0.020  0.369 -0.179  0.095 -0.179 -0.105 -0.254 -0.130  0.269 -0.005  0.070  0.394  0.070  0.120  0.369  0.045 -0.005  0.070  0.169  0.244 -0.105 -0.179  0.095  0.095  0.120  0.045  0.144  0.717  0.294  0.443  0.020  0.219 -0.154  0.070 -0.005  0.194  0.120  0.443 
 0.624  0.126 -0.024  0.101 -0.124  0.001  0.325  0.350  0.001  0.076 -0.099  0.101  0.001  0.350 -0.148  0.101 -0.148 -0.148 -0.248 -0.074  0.400  0.001  0.051  0.400  0.076  0.175  0.375  0.101  0.001  0.076  0.175  0.275 -0.124 -0.173  0.101  0.175  0.101  0.026  0.200  0.624  0.225  0.400  0.026  0.225 -0.198  0.225  0.001  0.225  0.175  0.474 
 0.585  0.112 -0.038  0.087 -0.113  0.037  0.311  0.411  0.012  0.062 -0.113  0.112 -0.013  0.411 -0.138  0.161 -0.138 -0.138 -0.262 -0.038  0.386  0.037  0.037  0.361  0.037  0.211  0.361  0.161 -0.013  0.087  0.161  0.286 -0.138 -0.187  0.112  0.186  0.161  0.037  0.211  0.610  0.211  0.386  0.012  0.236 -0.212  0.261  0.037  0.236  0.186  0.510 
 0.547  0.049 -0.051  0.074 -0.076  0.024  0.298  0.423  0.024  0.099 -0.101  0.124 -0.001  0.472 -0.126  0.148 -0.126 -0.126 -0.250 -0.051  0.447  0.049  0.049  0.348  0.024  0.273  0.323  0.198 -0.026  0.124  0.148  0.273 -0.150 -0.200  0.099  0.173  0.198  0.049  0.223  0.597  0.223  0.373  0.024  0.248 -0.250  0.298  0.099  0.223  0.248  0.497 
 0.516  0.018 -0.057  0.093 -0.082  0.018  0.292  0.417  0.018  0.068 -0.107  0.118 -0.007  0.441 -0.156  0.142 -0.107 -0.082 -0.256 -0.057  0.441  0.043  0.043  0.342  0.018  0.317  0.317  0.192 -0.007  0.118  0.217  0.267 -0.156 -0.206  0.068  0.167  0.217  0.068  0.217  0.591  0.217  0.342  0.018  0.267 -0.256  0.317  0.093  0.242  0.242  0.491 
 0.487 -0.011 -0.036  0.113 -0.086  0.013  0.287  0.387  0.038  0.038 -0.061  0.163 -0.036  0.437 -0.161  0.113 -0.086 -0.036 -0.211 -0.036  0.487  0.063  0.038  0.312  0.013  0.312  0.312  0.263 -0.011  0.163  0.213  0.188 -0.111 -0.186  0.063  0.213  0.238  0.063  0.188  0.586  0.213  0.362  0.063  0.263 -0.261  0.387  0.138  0.238  0.287  0.487 
 0.459 -0.039 -0.039  0.110 -0.089  0.010  0.284  0.384  0.035  0.060 -0.064  0.160 -0.014  0.434 -0.164  0.110 -0.064 -0.039 -0.214 -0.039  0.509  0.060  0.060  0.284  0.010  0.334  0.284  0.260 -0.014  0.160  0.185  0.185 -0.114 -0.189  0.060  0.210  0.260  0.060  0.185  0.583  0.210  0.359  0.060  0.260 -0.264  0.384  0.135  0.235  0.284  0.484 
 0.454 -0.044  0.005  0.105 -0.094 -0.019  0.304  0.379  0.030  0.055 -0.044  0.180  0.005  0.429 -0.169  0.105  0.005 -0.019 -0.219 -0.044  0.603  0.080  0.055  0.280  0.030  0.329  0.280  0.304  0.030  0.205  0.205  0.180 -0.119 -0.194  0.080  0.230  0.304  0.080  0.205  0.554  0.205  0.354  0.055  0.280 -0.269  0.404  0.155  0.230  0.304  0.529 
 0.452 -0.046  0.029  0.104 -0.096 -0.021  0.303  0.378  0.029  0.054 -0.046  0.203  0.004  0.427 -0.170  0.104  0.004 -0.021 -0.220 -0.046  0.602  0.079  0.054  0.303  0.029  0.328  0.278  0.278  0.029  0.203  0.178  0.178 -0.121 -0.195  0.104  0.253  0.353  0.054  0.178  0.552  0.203  0.353  0.054  0.278 -0.270  0.403  0.178  0.228  0.303  0.552 
 0.452 -0.021  0.003  0.103 -0.096 -0.021  0.327  0.377  0.003  0.103  0.003  0.253  0.003  0.402 -0.146  0.103  0.028 -0.046 -0.221 -0.046  0.601  0.078  0.078  0.302  0.003  0.327  0.278  0.278  0.028  0.228  0.178  0.178 -0.121 -0.171  0.128  0.253  0.377  0.053  0.153  0.552  0.178  0.352  0.078  0.327 -0.271  0.402  0.178  0.278  0.302  0.552 
 0.451 -0.047  0.002  0.102 -0.097 -0.022  0.326  0.376  0.002  0.152  0.002  0.252  0.002  0.401 -0.122  0.102  0.027 -0.072 -0.222 -0.047  0.600  0.077  0.077  0.277  0.002  0.326  0.277  0.277  0.027  0.227  0.177  0.177 -0.122 -0.172  0.127  0.252  0.426  0.052  0.127  0.551  0.177  0.351  0.077  0.351 -0.272  0.401  0.227  0.301  0.326  0.551 
 0.452 -0.046  0.003  0.078 -0.096 -0.021  0.302  0.377  0.003  0.178 -0.021  0.253  0.003  0.427 -0.121  0.078  0.028 -0.071 -0.221 -0.046  0.601  0.078  0.078  0.278 -0.021  0.352  0.278  0.278  0.028  0.228  0.203  0.178 -0.121 -0.171  0.128  0.253  0.427  0.053  0.128  0.552  0.178  0.352  0.028  0.352 -0.271  0.402  0.228  0.302  0.327  0.552 
 0.390 -0.084  0.066  0.091 -0.084  0.041  0.340  0.390  0.016  0.116  0.016  0.165  0.066  0.340 -0.134  0.141 -0.034 -0.084 -0.134 -0.034  0.489  0.141  0.016  0.315  0.016  0.390  0.290  0.290  0.066  0.215  0.190  0.141 -0.084 -0.158  0.141  0.290  0.340  0.041  0.066  0.539  0.240  0.365  0.066  0.340 -0.208  0.290  0.116  0.290  0.390  0.489 
 0.360 -0.014  0.086  0.061 -0.014  0.111  0.310  0.360  0.061 -0.014  0.036  0.160  0.011  0.310 -0.089  0.136 -0.114 -0.064 -0.064 -0.014  0.410  0.185 -0.089  0.310  0.061  0.335  0.285  0.310  0.061  0.185  0.185  0.160 -0.039 -0.139  0.185  0.310  0.310  0.036  0.086  0.509  0.185  0.385  0.086  0.210 -0.114  0.185  0.086  0.260  0.210  0.434 
 0.233 -0.016  0.109  0.084  0.009  0.134  0.308  0.308  0.084  0.009  0.059  0.109  0.009  0.283 -0.066  0.158 -0.091 -0.066 -0.066 -0.016  0.408  0.183 -0.091  0.308  0.109  0.308  0.308  0.333  0.059  0.183  0.208  0.158 -0.066 -0.141  0.109  0.258  0.283  0.009  0.084  0.432  0.084  0.408  0.059  0.183 -0.091  0.208  0.109  0.258  0.233  0.333 
 0.160 -0.014  0.135  0.060  0.010  0.085  0.284  0.235  0.060 -0.064 -0.014  0.110  0.010  0.284 -0.064  0.160 -0.089 -0.039 -0.114 -0.039  0.409  0.160 -0.089  0.284  0.110  0.284  0.334  0.284  0.035  0.185  0.135  0.160 -0.089 -0.114  0.085  0.135  0.284  0.035  0.085  0.409  0.060  0.409  0.085  0.185 -0.089  0.185  0.060  0.284  0.210  0.260 
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 0.991 -0.005  0.044  0.019 -0.005 -0.005 -0.005 -0.030  0.019 -0.005 -0.005  0.069 -0.005  0.069  0.019 -0.005  0.019  0.019 -0.005 -0.005  0.069  0.019 -0.005  0.019  0.069  0.019 -0.005  0.019 -0.005 -0.005  0.019  0.019 -0.005 -0.030 -0.030  0.019 -0.005  0.019  0.019  0.044 -0.005  0.019  0.019 -0.005  0.044  0.069 -0.030 -0.005 -0.005 -0.030 
 0.995 -0.001  0.048 -0.001 -0.001 -0.001 -0.001 -0.026  0.023 -0.001 -0.001  0.073 -0.001  0.073 -0.001 -0.001  0.023  0.023 -0.001 -0.001  0.073 -0.001 -0.001 -0.001  0.073  0.023 -0.001  0.023 -0.001 -0.001  0.023 -0.001 -0.001 -0.026 -0.026  0.023 -0.001  0.023  0.023  0.048 -0.001  0.023  0.023 -0.001  0.048  0.073 -0.026 -0.001 -0.001 -0.026 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.001  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.020  0.004  0.079 -0.020  0.004 -0.020  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.029  0.079 -0.020  0.004  0.004 -0.020 
 1.000  0.004  0.029  0.004  0.004 -0.021  0.004 -0.021  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.021  0.004  0.104 -0.021  0.004 -0.021  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.021 -0.021  0.004  0.004  0.029 -0.021 -0.021 -0.021  0.029  0.029 -0.021  0.029  0.079 -0.021  0.004  0.004 -0.021 
 1.000  0.004  0.029  0.004  0.004 -0.021  0.004 -0.021  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.029  0.029 -0.021  0.004  0.079 -0.021  0.004 -0.021  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.021 -0.021  0.004  0.004  0.029 -0.021 -0.021 -0.021  0.029  0.029 -0.021  0.054  0.104 -0.021  0.004  0.004 -0.021 
 1.000  0.004  0.029  0.004  0.004 -0.021  0.004 -0.021  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.029  0.029 -0.021  0.004  0.079 -0.021  0.004 -0.021  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.021 -0.021  0.004  0.004  0.029 -0.021 -0.021 -0.021  0.029  0.029 -0.021  0.054  0.104 -0.021  0.004  0.004 -0.021 
 1.000  0.004  0.029  0.004  0.004 -0.021  0.004 -0.021  0.004  0.004  0.004  0.079  0.004  0.054  0.004  0.004  0.004  0.029 -0.021  0.004  0.079 -0.021  0.004 -0.021  0.029  0.029  0.004  0.004  0.004  0.004  0.029  0.004  0.004 -0.021 -0.021  0.004  0.004  0.029 -0.021 -0.021 -0.021  0.029  0.029 -0.021  0.029  0.104 -0.021  0.004  0.004 -0.021 
 1.000  0.003  0.028  0.003  0.003 -0.021  0.003 -0.021  0.003  0.003  0.003  0.078  0.003  0.053  0.003  0.003  0.003  0.028  0.003  0.003  0.078 -0.021  0.003 -0.021  0.028  0.053  0.003  0.003  0.003  0.003  0.028  0.003  0.003 -0.021 -0.021  0.003  0.003  0.028 -0.021 -0.021 -0.021  0.028  0.028 -0.021  0.028  0.103 -0.021  0.003  0.003 -0.021 
 0.998  0.002  0.027  0.002  0.002 -0.023  0.002 -0.023  0.002  0.002  0.002  0.077  0.002  0.052  0.002  0.002  0.027  0.027  0.002  0.002  0.102 -0.023  0.002 -0.023  0.027  0.077  0.002  0.002  0.002  0.002  0.027  0.002  0.002 -0.023 -0.023  0.002  0.002  0.027 -0.023 -0.023 -0.023  0.027  0.027 -0.023  0.052  0.127 -0.023  0.002  0.002 -0.023 
 0.996  0.000  0.025  0.025  0.000 -0.025  0.000 -0.025  0.000  0.000  0.000  0.075  0.000  0.050  0.000  0.000  0.025  0.025  0.000  0.000  0.100 -0.025  0.000 -0.025  0.025  0.174  0.000  0.000  0.000  0.000  0.025  0.000  0.025 -0.025 -0.025  0.000  0.000  0.050 -0.025 -0.025 -0.025  0.025  0.025 -0.025  0.050  0.125 -0.025  0.000  0.000 -0.025 
 0.986 -0.010  0.064  0.039 -0.010 -0.010  0.014 -0.035 -0.010 -0.010  0.014  0.114  0.014  0.039  0.014  0.014  0.014  0.039 -0.010  0.014  0.114 -0.010 -0.010 -0.035  0.039  0.488  0.014  0.014 -0.010  0.014  0.014 -0.010  0.014  0.014  0.014  0.039 -0.010  0.039  0.014 -0.035  0.014  0.039  0.014 -0.035  0.039  0.139 -0.035 -0.010 -0.010 -0.010 
 0.967 -0.004  0.045  0.070 -0.004 -0.004 -0.004 -0.054 -0.004  0.020 -0.004  0.170 -0.004  0.020 -0.004  0.045 -0.004  0.045 -0.004  0.045  0.245 -0.029 -0.029 -0.054  0.020  0.818  0.020 -0.004 -0.029  0.045 -0.004 -0.004  0.020 -0.004  0.020  0.070  0.020  0.020 -0.004 -0.054 -0.004  0.045  0.045 -0.054 -0.004  0.145 -0.029 -0.004 -0.029 -0.004 
 0.934 -0.012  0.037  0.062 -0.012 -0.012 -0.012 -0.062 -0.037 -0.012 -0.012  0.286 -0.012  0.012 -0.012  0.087  0.062  0.187 -0.012  0.087  0.536 -0.037 -0.062 -0.087  0.062  0.884  0.037  0.037 -0.062  0.037  0.012 -0.037  0.012 -0.037  0.037  0.037  0.037  0.012  0.012 -0.062 -0.012  0.037  0.012  0.037 -0.012  0.187 -0.012  0.062 -0.037 -0.037 
 0.873  0.001  0.076  0.076 -0.024 -0.024  0.051 -0.074 -0.099 -0.024 -0.024  0.549  0.001  0.051 -0.049  0.200  0.126  0.250  0.051  0.101  0.823 -0.099 -0.024 -0.148  0.150  0.873  0.126  0.026 -0.099  0.101  0.001 -0.099  0.001 -0.074  0.051  0.051  0.101 -0.024  0.051 -0.124  0.001  0.076  0.076  0.325 -0.049  0.200  0.026  0.076  0.001 -0.049 
 0.845  0.023  0.073  0.048 -0.027 -0.027  0.048 -0.077 -0.127  0.023 -0.027  0.671  0.048  0.048 -0.077  0.222  0.098  0.322  0.023  0.123  0.845 -0.102 -0.027 -0.176  0.123  0.845  0.098 -0.002 -0.102  0.073 -0.027 -0.127 -0.027 -0.077  0.048  0.023  0.123 -0.002  0.023 -0.151 -0.002  0.098  0.098  0.372 -0.052  0.222 -0.002  0.048  0.073 -0.077 
 0.808  0.010  0.035  0.010 -0.014 -0.039  0.035 -0.064 -0.164  0.085 -0.064  0.733  0.085  0.010 -0.064  0.334  0.035  0.484  0.035  0.135  0.808 -0.089 -0.039 -0.164  0.185  0.808  0.010  0.010 -0.089  0.035 -0.064 -0.139 -0.064 -0.089  0.085  0.060  0.135 -0.039 -0.014 -0.164  0.010  0.110  0.135  0.583 -0.064  0.210 -0.039  0.035  0.060 -0.089 
 0.775  0.002  0.027  0.002 -0.022 -0.047  0.027 -0.047 -0.172  0.077 -0.072  0.725  0.127  0.002 -0.072  0.351  0.027  0.551  0.027  0.127  0.800 -0.072 -0.047 -0.172  0.177  0.800  0.002  0.002 -0.097  0.027 -0.072 -0.147 -0.097 -0.097  0.102  0.052  0.152 -0.047 -0.022 -0.172  0.002  0.102  0.127  0.625 -0.097  0.202 -0.047  0.027  0.052 -0.097 
 0.733  0.036  0.061 -0.014 -0.039 -0.064  0.036 -0.014 -0.188  0.061 -0.039  0.709  0.160 -0.014 -0.089  0.410  0.036  0.684  0.036  0.111  0.758 -0.064 -0.014 -0.188  0.160  0.783 -0.014  0.036 -0.089  0.011 -0.089 -0.114 -0.114 -0.114  0.111  0.086  0.136 -0.064 -0.039 -0.163  0.011  0.111  0.111  0.709 -0.114  0.185 -0.064  0.036  0.061 -0.114 
 0.675  0.052  0.077 -0.022 -0.047 -0.072  0.027 -0.047 -0.172  0.077 -0.022  0.700  0.177 -0.022 -0.097  0.426  0.027  0.725  0.027  0.127  0.750 -0.072 -0.072 -0.197  0.177  0.775 -0.022  0.052 -0.072  0.027 -0.097 -0.097 -0.122 -0.047  0.127  0.077  0.127 -0.072 -0.047 -0.172  0.002  0.102  0.127  0.725 -0.122  0.152 -0.047  0.002  0.052 -0.122 
 0.666  0.068  0.068 -0.032 -0.057 -0.082  0.043 -0.032 -0.156  0.068 -0.007  0.666  0.167 -0.032 -0.082  0.417  0.043  0.740  0.018  0.118  0.740 -0.107 -0.107 -0.206  0.217  0.765 -0.032  0.043 -0.082  0.018 -0.082 -0.082 -0.082 -0.057  0.068  0.068  0.093 -0.082 -0.057 -0.181  0.068  0.093  0.118  0.740 -0.107  0.142 -0.057  0.018  0.068 -0.132 
 0.662  0.089  0.064 -0.036 -0.086 -0.086  0.039 -0.036 -0.160  0.064  0.014  0.662  0.188 -0.036 -0.086  0.437  0.039  0.736  0.014  0.139  0.736 -0.111 -0.111 -0.210  0.213  0.736 -0.036  0.039 -0.061  0.039 -0.086 -0.061 -0.086 -0.061  0.064  0.064  0.089 -0.086 -0.061 -0.160  0.089  0.089  0.114  0.736 -0.111  0.114 -0.061  0.014  0.064 -0.136 
 0.631  0.182  0.083 -0.042 -0.067 -0.067  0.033 -0.042 -0.166  0.083  0.008  0.681  0.207 -0.042 -0.092  0.456  0.058  0.706  0.008  0.108  0.730 -0.117 -0.117 -0.191  0.207  0.730 -0.017  0.033 -0.042  0.083 -0.067 -0.042 -0.117 -0.042  0.058  0.083  0.083 -0.092 -0.092 -0.166  0.058  0.083  0.108  0.730 -0.117  0.108 -0.067  0.008  0.033 -0.142 
 0.667  0.144  0.119 -0.080 -0.105 -0.005  0.044 -0.030 -0.130  0.044 -0.005  0.617  0.194 -0.005 -0.030  0.393  0.044  0.568  0.044  0.069  0.642 -0.130 -0.130 -0.180  0.194  0.642 -0.005  0.069 -0.030  0.094 -0.055 -0.055 -0.080 -0.030  0.019  0.069  0.094 -0.080 -0.080 -0.105  0.044  0.119  0.119  0.717 -0.130  0.069 -0.005 -0.030  0.044 -0.130 
 0.531  0.033  0.058 -0.017 -0.017 -0.017  0.033 -0.017 -0.067 -0.017  0.008  0.556  0.157  0.008  0.008  0.257  0.033  0.481  0.033  0.108  0.556 -0.092 -0.092 -0.117  0.182  0.481  0.033  0.058 -0.017  0.157 -0.067 -0.042 -0.042 -0.017 -0.017  0.058  0.058 -0.042 -0.017 -0.067  0.058  0.108  0.058  0.681 -0.092  0.108 -0.017  0.008  0.033 -0.042 
 0.388  0.064  0.064 -0.035 -0.010 -0.010  0.014  0.014 -0.060  0.014  0.014  0.488  0.089  0.014  0.014  0.164  0.039  0.338  0.039  0.014  0.264 -0.085 -0.060 -0.085  0.164  0.363 -0.010  0.014  0.014  0.114 -0.035 -0.035 -0.060  0.014 -0.010  0.039 -0.010 -0.010  0.014 -0.035  0.039  0.114  0.039  0.687 -0.060  0.139 -0.060  0.039  0.014 -0.060 
 0.262  0.037  0.087 -0.037 -0.012  0.012  0.012  0.012 -0.062  0.037  0.012  0.436  0.037  0.012 -0.012  0.112 -0.012  0.187  0.012  0.037  0.212 -0.062 -0.037 -0.062  0.137  0.286 -0.012  0.012 -0.037  0.087 -0.037 -0.037 -0.062  0.037  0.062  0.062  0.012 -0.012  0.037 -0.012  0.087  0.062  0.062  0.635 -0.062  0.162 -0.062  0.062 -0.012 -0.037 
 0.175  0.025  0.075 -0.024  0.000  0.025  0.000  0.025 -0.049  0.000  0.000  0.399  0.025 -0.024  0.000  0.050  0.000  0.150  0.000  0.000  0.125 -0.049 -0.024 -0.049  0.100  0.200 -0.049  0.000 -0.024  0.075 -0.024 -0.024 -0.049  0.025  0.025  0.050  0.025 -0.024  0.025  0.000  0.025  0.050  0.025  0.573 -0.049  0.150 -0.049  0.050 -0.024 -0.024 
 0.041  0.041  0.041 -0.034 -0.009  0.041 -0.009 -0.034 -0.034 -0.009  0.016  0.240 -0.009 -0.009 -0.009 -0.009  0.016  0.066 -0.009  0.016  0.041 -0.034 -0.009 -0.034  0.066  0.116 -0.034  0.016 -0.009  0.016 -0.034 -0.034 -0.034 -0.009  0.041  0.041  0.016 -0.009  0.041  0.016  0.041  0.041  0.041  0.439 -0.034  0.091 -0.034 -0.009 -0.009 -0.009 
 0.022  0.047  0.022 -0.027 -0.027  0.047 -0.002 -0.027 -0.027 -0.027  0.022  0.122 -0.002 -0.027 -0.027  0.022  0.022  0.072 -0.002  0.022  0.022 -0.027 -0.002 -0.027  0.047  0.097 -0.027  0.022 -0.027  0.022 -0.027 -0.027 -0.027 -0.002 -0.002 -0.002  0.022 -0.002  0.047 -0.002  0.022  0.022  0.022  0.321 -0.027  0.047 -0.027 -0.002 -0.002 -0.002 
 0.029  0.029  0.004 -0.021 -0.021  0.029  0.004 -0.021 -0.021 -0.021  0.004  0.079  0.004 -0.021 -0.021  0.029  0.029  0.029  0.004  0.029  0.004 -0.021 -0.021 -0.021  0.054  0.079 -0.021  0.029 -0.021  0.029 -0.021 -0.021 -0.021  0.004  0.029 -0.021 -0.021  0.004  0.029  0.004  0.029 -0.021 -0.021  0.129 -0.021 -0.021 -0.021 -0.021  0.004  0.004 
 0.030  0.030  0.005 -0.020 -0.020  0.030  0.005 -0.020 -0.020 -0.020  0.005  0.080  0.005 -0.020 -0.020  0.030  0.005  0.030  0.005  0.030  0.005 -0.020 -0.020 -0.020  0.055  0.080 -0.020  0.030 -0.020  0.030 -0.020 -0.020 -0.020  0.005  0.005 -0.020 -0.020  0.005  0.030  0.005  0.005 -0.020 -0.020  0.105 -0.020 -0.020 -0.020 -0.020  0.005 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.029  0.029  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.079  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054  0.004 -0.020 -0.020 -0.020  0.054  0.079 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 
 0.024  0.074 -0.000 -0.000 -0.025  0.024 -0.000 -0.025 -0.025 -0.025 -0.000  0.099  0.024 -0.025 -0.025  0.024 -0.000  0.024 -0.000  0.049 -0.000 -0.025 -0.025 -0.025  0.049  0.099 -0.025  0.024 -0.025  0.024 -0.025 -0.025 -0.025 -0.000 -0.000 -0.025 -0.025 -0.025  0.049 -0.000  0.024 -0.025 -0.025  0.049 -0.025 -0.025 -0.025 -0.025 -0.000 -0.000 
-0.004  0.096 -0.029 -0.029 -0.029  0.021 -0.029 -0.054 -0.054 -0.054  0.021  0.071  0.046 -0.004 -0.029  0.046  0.021 -0.004  0.046  0.071 -0.029 -0.054 -0.029 -0.029  0.046  0.121 -0.029  0.021 -0.029  0.046 -0.029 -0.054 -0.004 -0.004  0.046 -0.029 -0.004 -0.029  0.046 -0.004  0.145 -0.054  0.046  0.046 -0.054 -0.029 -0.029 -0.004 -0.029  0.021 
 0.032  0.107 -0.018 -0.068 -0.043  0.107 -0.043 -0.068 -0.093 -0.043  0.007  0.057  0.032 -0.018  0.007  0.057  0.007  0.032  0.032  0.032 -0.018 -0.068 -0.043 -0.018  0.007  0.132 -0.068  0.007  0.007  0.107  0.032 -0.043 -0.043 -0.043  0.057 -0.068  0.032 -0.068  0.082  0.007  0.132 -0.018  0.032  0.057 -0.093 -0.043 -0.068  0.007 -0.018  0.032 
 0.011  0.161 -0.038 -0.113 -0.038  0.161 -0.063 -0.113 -0.163 -0.113  0.036  0.111  0.036 -0.088  0.036  0.086  0.036  0.086  0.011  0.011 -0.063 -0.013 -0.063 -0.063 -0.038  0.161 -0.113  0.061 -0.013  0.061  0.061 -0.088 -0.088 -0.088  0.061 -0.063  0.061 -0.088  0.061 -0.038  0.136 -0.038 -0.013  0.036 -0.138 -0.088 -0.138  0.061 -0.063  0.036 
 0.001  0.225 -0.049 -0.099 -0.024  0.126 -0.049 -0.124 -0.148 -0.148  0.026  0.175  0.026 -0.124  0.101  0.101  0.026  0.076  0.001  0.001 -0.099 -0.049 -0.024 -0.099 -0.049  0.150 -0.148  0.076 -0.024  0.026  0.076 -0.074 -0.099 -0.124  0.051  0.026  0.051 -0.024  0.026 -0.024  0.126 -0.074 -0.049  0.126 -0.124 -0.124 -0.148  0.026 -0.074  0.051 
-0.002  0.222 -0.077 -0.127 -0.002  0.073 -0.052 -0.151 -0.102 -0.176  0.023  0.272  0.098 -0.176  0.048  0.073 -0.002  0.222 -0.027  0.023 -0.151 -0.077 -0.027 -0.151 -0.052  0.123 -0.176  0.073 -0.027  0.098  0.123 -0.151 -0.151 -0.176 -0.002 -0.002 -0.002 -0.052 -0.002 -0.002  0.048 -0.077 -0.052  0.172 -0.127 -0.151 -0.201  0.048 -0.102  0.023 
-0.014  0.235 -0.114 -0.139 -0.014  0.011 -0.089 -0.163 -0.089 -0.163  0.011  0.260  0.111 -0.188  0.061  0.036 -0.014  0.310  0.011 -0.014 -0.163 -0.089 -0.014 -0.139 -0.064  0.061 -0.163  0.061 -0.014  0.061  0.086 -0.188 -0.188 -0.188  0.011 -0.014 -0.014 -0.064  0.011  0.036  0.061 -0.089 -0.089  0.160 -0.114 -0.163 -0.188  0.036 -0.114 -0.039 
-0.032  0.217 -0.132 -0.157 -0.032 -0.032 -0.107 -0.182 -0.107 -0.182  0.017  0.217  0.192 -0.182  0.017  0.067 -0.057  0.366  0.017 -0.032 -0.157 -0.107 -0.032 -0.232 -0.107  0.067 -0.157  0.067 -0.007  0.067  0.067 -0.232 -0.207 -0.207 -0.007  0.017 -0.032 -0.082 -0.032  0.042  0.067 -0.107 -0.107  0.117 -0.132 -0.157 -0.207  0.017 -0.132 -0.057 
-0.016  0.208 -0.141 -0.165 -0.016 -0.041 -0.116 -0.190 -0.116 -0.165  0.009  0.208  0.183 -0.190  0.009  0.059 -0.066  0.383  0.009 -0.016 -0.165 -0.116 -0.016 -0.265 -0.091  0.109 -0.116  0.059 -0.016  0.059  0.059 -0.240 -0.215 -0.215 -0.016  0.009 -0.041 -0.116 -0.041  0.034  0.059 -0.091 -0.091  0.109 -0.165 -0.165 -0.215  0.009 -0.141 -0.066 
-0.024  0.175 -0.124 -0.174 -0.024 -0.074 -0.099 -0.199 -0.124 -0.149  0.000  0.200  0.150 -0.199 -0.024  0.075 -0.099  0.349  0.000 -0.024 -0.174 -0.124  0.000 -0.274 -0.099  0.150 -0.124  0.050 -0.024  0.075  0.050 -0.249 -0.224 -0.224 -0.049  0.000 -0.074 -0.124 -0.099  0.025  0.075 -0.174 -0.074  0.050 -0.124 -0.149 -0.224  0.000 -0.149 -0.074 
-0.053  0.171 -0.103 -0.177 -0.028 -0.078 -0.103 -0.227 -0.128 -0.152 -0.028  0.196  0.171 -0.202 -0.028  0.072 -0.078  0.296 -0.003 -0.028 -0.177 -0.128 -0.003 -0.277 -0.103  0.171 -0.128  0.072 -0.028  0.072  0.047 -0.252 -0.227 -0.227 -0.053 -0.003 -0.103 -0.128 -0.103 -0.003  0.072 -0.177 -0.078  0.072 -0.128 -0.128 -0.227  0.022 -0.152 -0.103 
-0.056  0.168 -0.106 -0.180 -0.031 -0.081 -0.155 -0.230 -0.131 -0.131 -0.031  0.193  0.168 -0.205 -0.031  0.143 -0.081  0.293 -0.031 -0.031 -0.180 -0.131  0.019 -0.280 -0.106  0.193 -0.106  0.069 -0.031  0.094  0.094 -0.255 -0.230 -0.230 -0.006 -0.006 -0.131 -0.106 -0.131 -0.006  0.069 -0.205 -0.106  0.069 -0.131 -0.131 -0.230  0.019 -0.131 -0.081 
-0.031  0.193 -0.106 -0.180 -0.006 -0.081 -0.155 -0.230 -0.131 -0.131 -0.056  0.193  0.168 -0.205 -0.031  0.143 -0.155  0.268 -0.006 -0.031 -0.180 -0.131 -0.006 -0.280 -0.131  0.193 -0.131  0.019 -0.006  0.069  0.044 -0.255 -0.230 -0.230 -0.031 -0.006 -0.131 -0.106 -0.106 -0.031  0.044 -0.205 -0.106  0.069 -0.131 -0.131 -0.230 -0.006 -0.205 -0.081 
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-0.109  0.240 -0.034 -0.258 -0.034 -0.084 -0.158 -0.258 -0.059 -0.084 -0.158  0.016 -0.009 -0.109  0.066  0.141 -0.134 -0.109 -0.059 -0.009 -0.183 -0.233  0.116 -0.183 -0.158  0.116 -0.084 -0.109  0.066 -0.134 -0.034 -0.183 -0.258 -0.308  0.066  0.016 -0.158 -0.158 -0.158 -0.158  0.041 -0.183 -0.134  0.041 -0.183 -0.084 -0.109 -0.034 -0.183 -0.109 
-0.135  0.239 -0.035 -0.259 -0.010 -0.085 -0.135 -0.209 -0.085 -0.085 -0.110  0.065 -0.010 -0.110  0.065  0.115 -0.135 -0.085 -0.085 -0.010 -0.184 -0.234  0.115 -0.209 -0.184  0.140 -0.085 -0.110  0.140 -0.110 -0.035 -0.209 -0.259 -0.309  0.090 -0.010 -0.159 -0.159 -0.135 -0.184  0.040 -0.184 -0.159  0.040 -0.184 -0.085 -0.085 -0.060 -0.209 -0.110 
-0.166  0.258 -0.041 -0.266 -0.016 -0.091 -0.166 -0.216 -0.091 -0.091 -0.116  0.083  0.008 -0.116  0.083  0.133 -0.091 -0.091 -0.091 -0.016 -0.191 -0.241  0.108 -0.216 -0.191  0.158 -0.116 -0.116  0.133 -0.091 -0.016 -0.216 -0.266 -0.266  0.108 -0.016 -0.141 -0.141 -0.091 -0.191  0.033 -0.191 -0.166  0.033 -0.191 -0.066 -0.066 -0.066 -0.216 -0.116 
-0.168  0.231 -0.043 -0.243 -0.018 -0.093 -0.168 -0.218 -0.093 -0.093 -0.118  0.081 -0.018 -0.118  0.081  0.131 -0.093 -0.093 -0.093 -0.018 -0.193 -0.243  0.106 -0.218 -0.193  0.181 -0.118 -0.118  0.131 -0.093 -0.018 -0.218 -0.268 -0.268  0.106 -0.018 -0.168 -0.143 -0.093 -0.193  0.031 -0.168 -0.143  0.031 -0.193 -0.068 -0.068 -0.093 -0.218 -0.118 
-0.170  0.229 -0.045 -0.245 -0.045 -0.095 -0.195 -0.245 -0.095 -0.095 -0.120  0.104 -0.020 -0.120  0.079  0.104 -0.120 -0.095 -0.095 -0.020 -0.195 -0.245  0.104 -0.220 -0.195  0.154 -0.120 -0.095  0.154 -0.095 -0.020 -0.195 -0.270 -0.270  0.104 -0.045 -0.170 -0.120 -0.070 -0.195  0.029 -0.170 -0.145  0.029 -0.195 -0.070 -0.070 -0.120 -0.195 -0.145 
-0.172  0.227 -0.047 -0.247 -0.047 -0.097 -0.197 -0.247 -0.097 -0.097 -0.122  0.077 -0.022 -0.147  0.077  0.102 -0.122 -0.097 -0.097 -0.022 -0.197 -0.247  0.127 -0.197 -0.197  0.152 -0.122 -0.097  0.152 -0.097 -0.022 -0.197 -0.272 -0.272  0.102 -0.047 -0.172 -0.122 -0.097 -0.197  0.027 -0.172 -0.147  0.027 -0.197 -0.072 -0.072 -0.147 -0.197 -0.147 
-0.174  0.275 -0.049 -0.249 -0.049 -0.099 -0.199 -0.249 -0.099 -0.099 -0.124  0.075  0.000 -0.149  0.075  0.100 -0.124 -0.099 -0.099 -0.024 -0.199 -0.249  0.125 -0.199 -0.199  0.150 -0.124 -0.099  0.150 -0.099 -0.024 -0.199 -0.274 -0.274  0.100 -0.049 -0.174 -0.124 -0.099 -0.199  0.025 -0.174 -0.149  0.025 -0.199 -0.074 -0.074 -0.149 -0.199 -0.149 
-0.175  0.298 -0.050 -0.250 -0.050 -0.100 -0.200 -0.250 -0.100 -0.100 -0.125  0.099 -0.000 -0.150  0.074  0.099 -0.125 -0.100 -0.100 -0.025 -0.200 -0.250  0.124 -0.200 -0.200  0.149 -0.125 -0.100  0.149 -0.100 -0.025 -0.200 -0.275 -0.275  0.099 -0.050 -0.175 -0.125 -0.100 -0.200  0.024 -0.175 -0.150  0.024 -0.200 -0.075 -0.075 -0.150 -0.200 -0.150 
-0.175  0.298 -0.025 -0.250 -0.050 -0.075 -0.200 -0.275 -0.100 -0.100 -0.125  0.099 -0.000 -0.125  0.074  0.124 -0.100 -0.075 -0.100 -0.025 -0.200 -0.250  0.124 -0.200 -0.200  0.124 -0.125 -0.100  0.149 -0.100 -0.025 -0.225 -0.275 -0.275  0.099 -0.050 -0.175 -0.125 -0.125 -0.200  0.024 -0.175 -0.175  0.024 -0.150 -0.075 -0.100 -0.150 -0.200 -0.150 
-0.175  0.298 -0.051 -0.250 -0.051 -0.076 -0.175 -0.250 -0.101 -0.101 -0.126  0.074 -0.001 -0.126  0.074  0.124 -0.101 -0.076 -0.101 -0.026 -0.200 -0.250  0.124 -0.200 -0.200  0.099 -0.126 -0.101  0.148 -0.101 -0.026 -0.225 -0.275 -0.250  0.099 -0.076 -0.175 -0.101 -0.126 -0.200  0.024 -0.175 -0.175  0.024 -0.150 -0.076 -0.101 -0.150 -0.200 -0.150 
-0.177  0.296 -0.052 -0.277 -0.077 -0.077 -0.177 -0.227 -0.102 -0.102 -0.127  0.097 -0.002 -0.127  0.047  0.122 -0.102 -0.077 -0.127 -0.027 -0.202 -0.252  0.122 -0.227 -0.202  0.097 -0.127 -0.102  0.147 -0.102 -0.027 -0.227 -0.277 -0.252  0.097 -0.077 -0.177 -0.102 -0.102 -0.202  0.022 -0.177 -0.202  0.047 -0.152 -0.077 -0.102 -0.152 -0.202 -0.152 
-0.176  0.297 -0.052 -0.276 -0.077 -0.077 -0.176 -0.276 -0.102 -0.127 -0.102  0.098  0.048 -0.151  0.048  0.123 -0.102 -0.077 -0.127 -0.027 -0.201 -0.251  0.098 -0.226 -0.201  0.098 -0.127 -0.151  0.123 -0.102 -0.027 -0.226 -0.301 -0.251  0.073 -0.077 -0.176 -0.127 -0.127 -0.201  0.023 -0.176 -0.201  0.048 -0.127 -0.077 -0.102 -0.151 -0.201 -0.151 
-0.180  0.293 -0.055 -0.280 -0.080 -0.055 -0.180 -0.280 -0.080 -0.130 -0.105  0.144  0.044 -0.155  0.044  0.119 -0.105 -0.080 -0.130 -0.030 -0.205 -0.255  0.094 -0.230 -0.205  0.094 -0.130 -0.155  0.094 -0.105 -0.055 -0.230 -0.304 -0.255  0.069 -0.055 -0.180 -0.130 -0.130 -0.205  0.019 -0.205 -0.205  0.044 -0.130 -0.080 -0.130 -0.155 -0.205 -0.155 

 0.991 -0.005 -0.005 -0.030 -0.030 -0.005 -0.005  0.019  0.019 -0.030  0.019 -0.030 -0.030  0.044 -0.030  0.069 -0.030  0.044 -0.005 -0.005 -0.005 -0.030  0.069  0.019  0.019 -0.030 -0.005  0.044  0.069  0.044  0.019 -0.005 -0.005 -0.005 -0.005  0.044 -0.030 -0.005 -0.005  0.019 -0.005 -0.005  0.019  0.044 -0.005 -0.030  0.019  0.019 -0.005 -0.030 
 0.996 -0.000 -0.000 -0.025 -0.025 -0.000 -0.000  0.024 -0.000 -0.025  0.024 -0.025 -0.025  0.049 -0.025  0.074 -0.025  0.049 -0.000 -0.000 -0.000 -0.025  0.049  0.024  0.024 -0.025 -0.000  0.024  0.074  0.049  0.024 -0.000 -0.000 -0.000 -0.000  0.024 -0.025 -0.000 -0.000  0.024 -0.000 -0.025 -0.000  0.049 -0.000 -0.025  0.024  0.024 -0.000 -0.025 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 1.001  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020  0.029 -0.020  0.054  0.004  0.004  0.004 -0.020  0.054  0.004  0.029 -0.020  0.004  0.029  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.029 -0.020 -0.020  0.004  0.004  0.004 -0.020  0.004  0.054  0.004 -0.020  0.029  0.029  0.004 -0.020 
 0.999  0.003  0.003 -0.022 -0.022  0.003 -0.022  0.028  0.003 -0.022  0.028 -0.022 -0.022  0.053 -0.022  0.028 -0.022  0.053  0.003  0.003  0.003 -0.022  0.103  0.003  0.028 -0.022  0.003  0.028  0.078  0.028  0.028  0.003  0.003  0.003 -0.022  0.053 -0.022 -0.022  0.003  0.003  0.003 -0.022  0.003  0.053  0.003 -0.022  0.028  0.028  0.003 -0.022 
 0.992  0.020  0.020 -0.030 -0.030  0.045 -0.030  0.020 -0.005 -0.005  0.020 -0.005 -0.030  0.045 -0.005  0.020 -0.030  0.045 -0.005 -0.005 -0.005 -0.030  0.443 -0.005  0.020 -0.030 -0.005  0.020  0.095  0.020  0.045 -0.005 -0.005 -0.005 -0.030  0.095 -0.030 -0.030 -0.005 -0.005  0.020 -0.030 -0.005  0.070 -0.005 -0.005  0.045  0.020 -0.005 -0.005 
 0.984  0.012  0.012 -0.037 -0.037  0.012 -0.037  0.012  0.012  0.012  0.037 -0.012 -0.037  0.037  0.012  0.012 -0.012  0.062 -0.012  0.012 -0.012 -0.037  0.710 -0.012  0.012 -0.037 -0.012  0.012  0.087  0.012  0.062 -0.012 -0.012  0.037 -0.037  0.137 -0.037 -0.037 -0.012 -0.012  0.012 -0.037 -0.012  0.112 -0.012  0.062  0.037  0.062  0.037 -0.012 
 0.966  0.019  0.044 -0.031  0.044  0.143 -0.056  0.044  0.019  0.019  0.069 -0.006 -0.031  0.019  0.019 -0.006 -0.006  0.044 -0.031  0.044 -0.031 -0.031  0.966 -0.031 -0.006 -0.056 -0.006  0.069  0.119  0.119  0.094 -0.031 -0.031  0.019 -0.031  0.193 -0.031 -0.006 -0.006 -0.006  0.019 -0.031 -0.031  0.143 -0.031  0.069  0.044  0.293  0.094  0.019 
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 0.658  0.309  0.384  0.210  0.210  0.509  0.334  0.260  0.260  0.160  0.359  0.060  0.110  0.434 -0.039  0.035  0.434  0.060  0.010 -0.064  0.484 -0.114  0.309 -0.039  0.509 -0.014  0.235  0.434  0.284  0.534  0.210  0.384  0.085  0.035  0.085  0.583  0.434  0.334 -0.114  0.060  0.359  0.135  0.409  0.110  0.384  0.110  0.559  0.708  0.434  0.434 
 0.659  0.310  0.360  0.186  0.211  0.485  0.360  0.335  0.236  0.136  0.360  0.111  0.111  0.435 -0.013  0.086  0.460  0.036 -0.013 -0.063  0.535 -0.063  0.285 -0.038  0.560 -0.013  0.211  0.410  0.261  0.535  0.186  0.385  0.136  0.061  0.086  0.584  0.435  0.360 -0.113  0.111  0.335  0.136  0.435  0.111  0.485  0.061  0.560  0.684  0.385  0.385 
 0.655  0.306  0.356  0.181  0.206  0.480  0.381  0.356  0.231  0.132  0.381  0.156  0.107  0.480 -0.018  0.082  0.455  0.032 -0.018 -0.068  0.555 -0.043  0.281 -0.018  0.580 -0.018  0.206  0.406  0.256  0.530  0.181  0.356  0.156  0.057  0.082  0.530  0.455  0.381 -0.118  0.107  0.331  0.082  0.406  0.107  0.480  0.032  0.530  0.680  0.356  0.406 
 0.650  0.351  0.326  0.176  0.226  0.450  0.401  0.376  0.226  0.127  0.401  0.201  0.151  0.475 -0.023  0.102  0.475  0.027 -0.023 -0.073  0.550 -0.023  0.276  0.002  0.575 -0.023  0.201  0.401  0.251  0.525  0.176  0.326  0.151  0.102  0.127  0.525  0.450  0.401 -0.098  0.102  0.326  0.077  0.376  0.102  0.525  0.002  0.525  0.675  0.351  0.401 
 0.649  0.350  0.325  0.176  0.201  0.450  0.425  0.375  0.226  0.126  0.400  0.226  0.126  0.500  0.001  0.126  0.475  0.051 -0.023 -0.073  0.550 -0.023  0.276  0.026  0.550 -0.023  0.201  0.400  0.251  0.525  0.201  0.325  0.151  0.101  0.176  0.525  0.450  0.400 -0.073  0.101  0.325  0.076  0.375  0.101  0.525  0.001  0.525  0.674  0.350  0.400 
 0.647  0.348  0.323  0.198  0.198  0.447  0.423  0.398  0.223  0.124  0.423  0.223  0.198  0.497  0.024  0.148  0.472  0.049 -0.026 -0.076  0.547 -0.001  0.248  0.049  0.572 -0.026  0.198  0.373  0.248  0.497  0.198  0.323  0.173  0.124  0.198  0.522  0.447  0.398 -0.076  0.099  0.323  0.074  0.373  0.099  0.547 -0.001  0.522  0.672  0.323  0.398 
 0.622  0.348  0.323  0.198  0.198  0.423  0.423  0.398  0.223  0.124  0.423  0.223  0.198  0.497  0.024  0.148  0.472  0.049 -0.026 -0.076  0.547 -0.001  0.248  0.049  0.572 -0.026  0.198  0.373  0.248  0.522  0.198  0.298  0.173  0.099  0.198  0.522  0.447  0.398 -0.076  0.099  0.373  0.099  0.373  0.099  0.547 -0.026  0.522  0.672  0.298  0.398 
 0.622  0.348  0.298  0.199  0.199  0.423  0.448  0.423  0.224  0.124  0.423  0.224  0.224  0.498  0.024  0.174  0.473  0.049 -0.025 -0.075  0.548  0.024  0.249  0.049  0.572 -0.025  0.199  0.373  0.249  0.523  0.199  0.298  0.174  0.099  0.174  0.548  0.498  0.398 -0.075  0.074  0.373  0.074  0.348  0.099  0.548 -0.025  0.498  0.672  0.274  0.398 
 0.561  0.312  0.312  0.187  0.262  0.362  0.461  0.461  0.237  0.162  0.362  0.187  0.162  0.461  0.038  0.162  0.412 -0.012  0.013 -0.137  0.436  0.013  0.237 -0.037  0.561 -0.062  0.138  0.412  0.262  0.511  0.187  0.337  0.162  0.088  0.063  0.486  0.486  0.337 -0.037  0.063  0.362  0.088  0.287  0.088  0.536 -0.037  0.486  0.661  0.237  0.387 
 0.529  0.230  0.330  0.106  0.180  0.405  0.380  0.429  0.280  0.180  0.305  0.131  0.106  0.405  0.006  0.106  0.280  0.031  0.031 -0.119  0.479 -0.044  0.205 -0.069  0.405  0.006  0.131  0.429  0.330  0.429  0.230  0.305  0.155  0.081  0.081  0.454  0.429  0.355 -0.069  0.006  0.230  0.106  0.330  0.106  0.454 -0.069  0.405  0.629  0.280  0.330 
 0.518  0.244  0.344  0.070  0.194  0.419  0.344  0.419  0.269  0.095  0.269  0.095  0.120  0.394  0.020  0.095  0.244 -0.005 -0.005 -0.105  0.443 -0.030  0.219 -0.030  0.344  0.020  0.120  0.443  0.344  0.419  0.194  0.219  0.169  0.045  0.045  0.419  0.443  0.369 -0.080  0.020  0.194  0.095  0.344  0.120  0.468 -0.055  0.369  0.593  0.269  0.294 
 0.545  0.121  0.345  0.021  0.196  0.420  0.345  0.370  0.196  0.046  0.196  0.121  0.146  0.395  0.021  0.021  0.146 -0.003 -0.028 -0.103  0.395 -0.003  0.246 -0.003  0.320  0.046  0.146  0.395  0.345  0.345  0.221  0.171  0.121  0.071  0.021  0.370  0.445  0.395 -0.078 -0.053  0.146  0.071  0.345  0.121  0.445 -0.078  0.395  0.520  0.271  0.246 
 0.556  0.132  0.356  0.032  0.182  0.431  0.331  0.282  0.182  0.032  0.207  0.107  0.132  0.356  0.032  0.032  0.057  0.007 -0.042 -0.092  0.381 -0.017  0.257  0.007  0.282  0.057  0.157  0.406  0.306  0.282  0.232  0.132  0.082  0.082  0.032  0.356  0.456  0.406 -0.092 -0.067  0.132  0.082  0.331  0.107  0.456 -0.067  0.406  0.481  0.232  0.232 
 0.571  0.098  0.297  0.048  0.148  0.422  0.347  0.273  0.173 -0.001  0.173  0.123  0.123  0.322 -0.001  0.023 -0.026  0.023 -0.051 -0.101  0.397 -0.001  0.248 -0.001  0.273  0.048  0.173  0.397  0.297  0.198  0.248  0.123  0.048  0.073 -0.001  0.297  0.472  0.372 -0.076 -0.051  0.073  0.023  0.297  0.098  0.397 -0.051  0.347  0.447  0.223  0.248 
 0.530  0.082  0.281  0.057  0.156  0.356  0.356  0.281  0.181  0.007  0.181  0.082  0.107  0.331 -0.018  0.032 -0.018  0.032 -0.043 -0.093  0.406  0.007  0.231  0.007  0.281  0.007  0.181  0.406  0.306  0.181  0.256  0.132  0.057  0.057 -0.043  0.281  0.455  0.331 -0.068 -0.043  0.082 -0.018  0.306  0.107  0.281 -0.043  0.356  0.430  0.206  0.256 
 0.513  0.064  0.288  0.064  0.139  0.288  0.388  0.264  0.189 -0.010  0.164  0.089  0.114  0.288 -0.060  0.039 -0.010  0.039 -0.035 -0.085  0.313  0.014  0.214  0.014  0.189 -0.010  0.189  0.388  0.338  0.189  0.239  0.139  0.064  0.064 -0.035  0.288  0.463  0.288 -0.060 -0.035  0.064 -0.010  0.313  0.089  0.214 -0.035  0.363  0.438  0.214  0.239 
 0.519  0.021  0.270  0.046  0.121  0.245  0.370  0.270  0.170 -0.004  0.145  0.096  0.121  0.295 -0.054  0.046 -0.004  0.046 -0.029 -0.079  0.270  0.021  0.220  0.021  0.145 -0.004  0.195  0.370  0.320  0.145  0.245  0.121  0.071  0.021 -0.054  0.270  0.469  0.245 -0.054 -0.029  0.046 -0.004  0.320  0.096  0.170 -0.054  0.370  0.395  0.220  0.220 
 0.481  0.007  0.257  0.007  0.107  0.182  0.406  0.232  0.182 -0.017  0.157  0.032  0.107  0.282 -0.042  0.032  0.007  0.007 -0.017 -0.067  0.157  0.032  0.232  0.032  0.032 -0.017  0.182  0.331  0.331  0.157  0.232  0.082  0.082  0.032 -0.042  0.282  0.456  0.182 -0.042 -0.017 -0.017  0.007  0.257  0.107  0.182 -0.067  0.356  0.381  0.157  0.182 
 0.438 -0.035  0.239 -0.010  0.114  0.139  0.413  0.239  0.189 -0.010  0.139  0.039  0.114  0.288 -0.035  0.039  0.014  0.014 -0.010 -0.060  0.139  0.039  0.214  0.039  0.039 -0.010  0.164  0.313  0.338  0.089  0.189  0.064  0.089  0.014 -0.035  0.288  0.463  0.139 -0.035 -0.010 -0.035  0.014  0.214  0.114  0.164 -0.060  0.288  0.363  0.164  0.164 
 0.356 -0.018  0.132  0.007  0.132  0.132  0.381  0.231  0.156 -0.018  0.082  0.007  0.057  0.281 -0.018  0.032  0.032  0.032  0.007 -0.043  0.057  0.057  0.181  0.007  0.032  0.007  0.156  0.231  0.331  0.107  0.132  0.007  0.032  0.007 -0.018  0.256  0.381  0.107 -0.018  0.007 -0.018  0.007  0.156  0.107  0.107 -0.043  0.132  0.256  0.156  0.156 
 0.242 -0.007  0.117 -0.007  0.067  0.117  0.267  0.217  0.092 -0.007  0.092 -0.032  0.067  0.217 -0.007  0.017  0.042  0.042  0.017 -0.032  0.042  0.042  0.167  0.017  0.042  0.017  0.092  0.167  0.217  0.117  0.092 -0.007  0.042  0.017 -0.032  0.192  0.341  0.092 -0.007  0.017 -0.007  0.017  0.142  0.042  0.067 -0.032  0.092  0.167  0.117  0.117 
 0.068 -0.007  0.043 -0.007  0.018 -0.007  0.118  0.043  0.068 -0.007  0.043 -0.007  0.043  0.068 -0.007 -0.007 -0.007 -0.007  0.018 -0.007  0.018  0.018  0.018 -0.007  0.018  0.018  0.043 -0.007  0.018  0.068 -0.007 -0.007 -0.007 -0.007 -0.007  0.043  0.142 -0.007 -0.007 -0.007 -0.007  0.018  0.018  0.018 -0.007 -0.007  0.018  0.043  0.018  0.018 
 0.046 -0.004  0.021 -0.004 -0.004 -0.004  0.046  0.046  0.021 -0.004 -0.004 -0.004  0.046  0.046 -0.004 -0.004 -0.004 -0.004 -0.004 -0.004  0.021 -0.004 -0.004 -0.004  0.021  0.021  0.021 -0.004  0.021  0.021 -0.004 -0.004 -0.004 -0.004 -0.004  0.021  0.071 -0.004 -0.004 -0.004 -0.004  0.021 -0.004  0.021 -0.004 -0.004 -0.004  0.021 -0.004 -0.004 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.029  0.004  0.004  0.004  0.054  0.079  0.004  0.029  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.029  0.029 -0.020  0.029 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.054 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 0.998  0.026  0.026  0.001  0.001  0.051  0.151  0.001  0.051  0.001  0.001 -0.023  0.001  0.026 -0.023  0.001  0.001 -0.023  0.001  0.026 -0.023  0.051  0.026 -0.023  0.026 -0.023 -0.023  0.001  0.001  0.001  0.026  0.101 -0.023 -0.023 -0.023  0.051  0.051 -0.023  0.001  0.001  0.001  0.051  0.026 -0.023  0.001  0.026  0.001  0.051  0.026 -0.023 
 0.991  0.019  0.094 -0.006 -0.006  0.069  0.268 -0.006  0.044  0.044  0.019 -0.031 -0.006  0.019 -0.031  0.019 -0.006 -0.031  0.019  0.019 -0.031  0.044  0.019 -0.006  0.044 -0.006 -0.031 -0.006  0.044 -0.006  0.019  0.143 -0.031 -0.006 -0.031  0.094  0.069  0.019 -0.006  0.019  0.044  0.143  0.069 -0.031 -0.006  0.044  0.019  0.069  0.019 -0.031 
 0.959  0.012  0.112  0.062  0.012  0.062  0.560  0.012  0.037  0.087  0.012 -0.063  0.037  0.062 -0.013  0.037  0.012 -0.013  0.012 -0.013 -0.013  0.012 -0.013 -0.038  0.037 -0.013 -0.038 -0.013  0.137  0.012  0.012  0.386 -0.013 -0.013 -0.063  0.112  0.137  0.161 -0.013  0.012  0.037  0.261  0.236 -0.038  0.161  0.012  0.037  0.112  0.112 -0.063 
 0.886 -0.011  0.089  0.064  0.039  0.064  0.786  0.188  0.039  0.213  0.139 -0.111  0.039  0.064 -0.011  0.064 -0.011 -0.086  0.039 -0.011  0.064  0.014  0.089 -0.011  0.089  0.014 -0.011  0.089  0.338  0.089  0.014  0.711 -0.011  0.014 -0.086  0.288  0.388  0.338 -0.036 -0.011  0.064  0.338  0.338 -0.011  0.263  0.014  0.064  0.238  0.313 -0.061 
 0.831 -0.016  0.183  0.109  0.109  0.183  0.781  0.383  0.059  0.208  0.109 -0.066  0.034  0.084 -0.041  0.059  0.059 -0.091  0.034  0.034  0.183  0.034  0.183 -0.016  0.233  0.034  0.009  0.158  0.408  0.283  0.084  0.731  0.009 -0.016 -0.066  0.457  0.482  0.482 -0.066 -0.016  0.109  0.308  0.432  0.059  0.333 -0.016  0.109  0.333  0.358  0.134 
 0.736 -0.011  0.213  0.114  0.163  0.213  0.687  0.388  0.039  0.238  0.188 -0.036  0.114  0.288 -0.061  0.064  0.188 -0.036  0.089 -0.036  0.338 -0.011  0.213 -0.061  0.462 -0.011  0.089  0.263  0.487  0.338  0.188  0.711  0.064  0.089 -0.061  0.587  0.587  0.612 -0.136  0.039  0.188  0.313  0.413  0.213  0.462 -0.036  0.313  0.512  0.413  0.238 
 0.716 -0.006  0.218  0.069  0.143  0.318  0.567  0.418  0.044  0.218  0.343  0.069  0.094  0.368 -0.081  0.094  0.268 -0.031  0.069 -0.081  0.418 -0.031  0.218 -0.056  0.492  0.069  0.119  0.268  0.492  0.368  0.218  0.667  0.044  0.143 -0.081  0.642  0.617  0.592 -0.106  0.094  0.218  0.268  0.442  0.193  0.567 -0.056  0.343  0.617  0.442  0.318 
 0.671  0.073  0.297  0.073  0.123  0.471  0.521  0.422  0.147  0.197  0.397  0.048  0.073  0.496 -0.027  0.123  0.422 -0.052  0.023 -0.077  0.521 -0.052  0.222 -0.052  0.496  0.073  0.098  0.272  0.446  0.422  0.272  0.496  0.123  0.147 -0.027  0.646  0.596  0.571 -0.102  0.147  0.297  0.272  0.422  0.172  0.571 -0.052  0.446  0.646  0.496  0.422 
 0.672  0.124  0.298  0.124  0.124  0.472  0.522  0.398  0.124  0.198  0.398  0.049  0.099  0.547 -0.051  0.099  0.423 -0.051  0.049 -0.026  0.547 -0.076  0.198 -0.051  0.497  0.099  0.099  0.323  0.423  0.447  0.298  0.398  0.173  0.148 -0.026  0.647  0.572  0.522 -0.126  0.148  0.348  0.273  0.423  0.173  0.572 -0.026  0.447  0.647  0.472  0.472 
 0.660  0.236  0.286  0.137  0.137  0.510  0.485  0.411  0.161  0.186  0.386  0.112  0.112  0.535 -0.038  0.137  0.510 -0.038  0.037 -0.038  0.535 -0.088  0.211 -0.038  0.535  0.112  0.112  0.361  0.361  0.460  0.311  0.386  0.161  0.137  0.037  0.635  0.560  0.460 -0.088  0.161  0.411  0.236  0.336  0.161  0.610 -0.038  0.485  0.685  0.460  0.510 
 0.634  0.310  0.285  0.136  0.136  0.509  0.459  0.410  0.160  0.185  0.335  0.111  0.160  0.534 -0.039  0.185  0.534 -0.039  0.036 -0.039  0.534 -0.064  0.210 -0.014  0.584  0.061  0.111  0.335  0.360  0.459  0.285  0.385  0.160  0.160  0.086  0.634  0.559  0.459 -0.089  0.160  0.434  0.210  0.335  0.160  0.609 -0.039  0.484  0.684  0.459  0.509 
 0.632  0.308  0.284  0.134  0.159  0.508  0.458  0.483  0.159  0.184  0.358  0.134  0.184  0.533 -0.040  0.234  0.558 -0.040  0.009 -0.040  0.533 -0.040  0.209 -0.015  0.607  0.034  0.109  0.333  0.358  0.483  0.308  0.383  0.159  0.159  0.109  0.632  0.558  0.433 -0.115  0.134  0.433  0.159  0.333  0.109  0.607 -0.040  0.458  0.682  0.458  0.508 
 0.604  0.305  0.280  0.155  0.205  0.479  0.454  0.479  0.155  0.180  0.405  0.155  0.230  0.529 -0.044  0.230  0.554 -0.044 -0.044 -0.044  0.529 -0.044  0.205 -0.019  0.604  0.006  0.106  0.330  0.355  0.504  0.305  0.380  0.155  0.155  0.106  0.629  0.554  0.429 -0.119  0.131  0.454  0.131  0.330  0.106  0.604 -0.044  0.454  0.679  0.454  0.504 
 0.577  0.303  0.279  0.179  0.204  0.478  0.453  0.478  0.204  0.179  0.403  0.154  0.254  0.528 -0.045  0.229  0.553 -0.045 -0.070 -0.070  0.553 -0.020  0.229 -0.020  0.602 -0.020  0.104  0.328  0.353  0.503  0.303  0.378  0.154  0.154  0.104  0.577  0.553  0.428 -0.120  0.129  0.478  0.129  0.328  0.104  0.602 -0.045  0.453  0.677  0.453  0.478 
 0.576  0.302  0.278  0.153  0.228  0.477  0.452  0.477  0.203  0.178  0.402  0.178  0.278  0.527 -0.046  0.228  0.552 -0.071 -0.071 -0.071  0.552 -0.021  0.228 -0.021  0.601 -0.021  0.103  0.327  0.352  0.552  0.302  0.377  0.153  0.128  0.078  0.552  0.527  0.427 -0.121  0.128  0.477  0.128  0.327  0.103  0.601 -0.046  0.452  0.651  0.452  0.477 
 0.551  0.327  0.277  0.152  0.227  0.476  0.451  0.501  0.227  0.177  0.402  0.177  0.277  0.526 -0.047  0.252  0.551 -0.072 -0.072 -0.072  0.551 -0.022  0.227 -0.022  0.601 -0.022  0.128  0.352  0.352  0.576  0.277  0.377  0.177  0.128  0.078  0.551  0.526  0.402 -0.122  0.128  0.476  0.128  0.327  0.103  0.601 -0.047  0.451  0.651  0.426  0.476 
 0.525  0.326  0.276  0.151  0.226  0.475  0.450  0.500  0.201  0.176  0.401  0.176  0.276  0.525 -0.048  0.251  0.550 -0.048 -0.073 -0.098  0.550 -0.023  0.226 -0.023  0.600  0.002  0.127  0.351  0.326  0.575  0.251  0.351  0.201  0.127  0.077  0.600  0.525  0.401 -0.123  0.127  0.475  0.127  0.301  0.102  0.600 -0.048  0.450  0.675  0.401  0.475 
 0.449  0.375  0.300  0.150  0.250  0.474  0.449  0.499  0.200  0.150  0.400  0.225  0.275  0.524 -0.049  0.300  0.549 -0.049 -0.074 -0.124  0.549  0.001  0.225  0.001  0.599  0.001  0.126  0.325  0.325  0.574  0.250  0.350  0.200  0.150  0.101  0.599  0.549  0.400 -0.124  0.126  0.474  0.126  0.300  0.101  0.599 -0.049  0.449  0.674  0.400  0.474 
 0.423  0.373  0.298  0.149  0.249  0.473  0.473  0.498  0.199  0.149  0.398  0.249  0.298  0.473 -0.050  0.298  0.548 -0.000 -0.075 -0.150  0.548 -0.000  0.224 -0.000  0.597 -0.000  0.124  0.348  0.274  0.572  0.224  0.348  0.174  0.124  0.149  0.597  0.548  0.398 -0.125  0.124  0.498  0.124  0.298  0.124  0.597 -0.050  0.448  0.672  0.398  0.473 
 0.397  0.347  0.297  0.172  0.247  0.496  0.471  0.471  0.197  0.147  0.397  0.297  0.297  0.471 -0.052  0.297  0.546 -0.002 -0.077 -0.151  0.571 -0.002  0.222 -0.002  0.596 -0.002  0.123  0.347  0.272  0.571  0.197  0.347  0.172  0.123  0.147  0.596  0.546  0.397 -0.127  0.123  0.496  0.123  0.297  0.123  0.596 -0.052  0.446  0.671  0.397  0.471 
 0.413  0.313  0.313  0.114  0.264  0.538  0.488  0.463  0.239  0.114  0.313  0.214  0.189  0.488 -0.010  0.264  0.563 -0.010 -0.060 -0.110  0.538 -0.060  0.239  0.014  0.538 -0.035  0.164  0.413  0.288  0.488  0.239  0.189  0.189  0.089  0.089  0.587  0.563  0.363 -0.110 -0.035  0.413  0.064  0.264  0.039  0.538 -0.085  0.413  0.687  0.363  0.513 
 0.326  0.226  0.351  0.052  0.151  0.426  0.426  0.401  0.251  0.151  0.251  0.127  0.151  0.450  0.002  0.226  0.475 -0.048 -0.048 -0.123  0.500 -0.048  0.176 -0.023  0.475  0.002  0.127  0.376  0.301  0.401  0.226  0.226  0.176  0.027  0.052  0.450  0.426  0.351 -0.098 -0.023  0.376  0.077  0.326  0.052  0.525 -0.023  0.401  0.600  0.251  0.450 
 0.321  0.221  0.371  0.022  0.171  0.421  0.445  0.396  0.246  0.097  0.221  0.097  0.146  0.421 -0.003  0.196  0.346 -0.028 -0.028 -0.103  0.445 -0.028  0.196 -0.003  0.470 -0.003  0.146  0.396  0.371  0.296  0.221  0.246  0.196  0.022  0.022  0.371  0.445  0.371 -0.078 -0.028  0.371  0.097  0.321  0.097  0.445 -0.003  0.421  0.545  0.246  0.470 
 0.291  0.117  0.366  0.017  0.192  0.416  0.441  0.366  0.217  0.067  0.167  0.092  0.142  0.441  0.017  0.017  0.291 -0.007 -0.057 -0.107  0.416 -0.007  0.217 -0.007  0.416 -0.007  0.142  0.366  0.391  0.267  0.217  0.267  0.167  0.017  0.042  0.316  0.441  0.341 -0.082 -0.032  0.341  0.117  0.341  0.117  0.416 -0.007  0.416  0.491  0.267  0.441 
 0.249  0.125  0.374  0.025  0.174  0.424  0.424  0.324  0.224  0.075  0.174  0.100  0.149  0.448  0.025  0.000  0.274  0.000 -0.050 -0.125  0.424 -0.025  0.199  0.000  0.424  0.000  0.149  0.374  0.399  0.274  0.224  0.224  0.125  0.025  0.050  0.274  0.448  0.324 -0.075 -0.050  0.299  0.125  0.349  0.125  0.374  0.000  0.424  0.473  0.249  0.448 
 0.238  0.113  0.312  0.038  0.163  0.437  0.437  0.287  0.163  0.038  0.163  0.113  0.163  0.412  0.038  0.013  0.163  0.013 -0.061 -0.111  0.437 -0.011  0.163  0.013  0.412  0.013  0.138  0.362  0.387  0.188  0.238  0.213  0.113  0.038  0.063  0.238  0.462  0.312 -0.086 -0.036  0.238  0.113  0.362  0.138  0.362 -0.036  0.337  0.437  0.213  0.437 
 0.220  0.120  0.245  0.045  0.170  0.444  0.419  0.294  0.170  0.020  0.170  0.070  0.120  0.419  0.045  0.020  0.120  0.020 -0.054 -0.104  0.419 -0.004  0.170  0.020  0.369  0.020  0.145  0.369  0.394  0.195  0.245  0.195  0.120  0.045  0.070  0.245  0.444  0.294 -0.079 -0.054  0.220  0.095  0.369  0.145  0.294 -0.029  0.344  0.469  0.170  0.444 
 0.204  0.105  0.229  0.055  0.179  0.453  0.404  0.304  0.154  0.005  0.179  0.080  0.105  0.428  0.030  0.030  0.005  0.030 -0.045 -0.095  0.354  0.005  0.179  0.030  0.354  0.030  0.154  0.354  0.404  0.204  0.254  0.154  0.080  0.055  0.030  0.179  0.453  0.304 -0.095 -0.045  0.179  0.030  0.379  0.154  0.279 -0.045  0.329  0.478  0.130  0.453 
 0.212  0.113  0.187  0.038  0.187  0.486  0.387  0.312  0.162  0.013  0.162  0.088  0.113  0.412  0.013  0.038  0.013  0.038 -0.037 -0.087  0.287 -0.012  0.138  0.063  0.312 -0.012  0.162  0.362  0.461  0.162  0.262  0.162  0.063  0.013  0.013  0.162  0.461  0.162 -0.087 -0.037  0.162 -0.037  0.362  0.162  0.287 -0.037  0.287  0.412  0.088  0.461 
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 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 

 0.991 -0.005 -0.005  0.044 -0.005 -0.005 -0.030  0.019 -0.030 -0.030 -0.005  0.069 -0.005  0.019 -0.005 -0.005 -0.030  0.019  0.094  0.019 -0.030  0.044 -0.005 -0.005  0.019 -0.005 -0.005 -0.030 -0.005 -0.005 -0.005 -0.005  0.019 -0.005 -0.005  0.019 -0.030 -0.005 -0.005  0.019  0.019 -0.030 -0.005 -0.030 -0.005  0.019 -0.030  0.019 -0.030  0.169 
 0.995 -0.001 -0.026  0.023 -0.001 -0.001 -0.026 -0.001 -0.026 -0.026 -0.001  0.048 -0.001  0.023 -0.001 -0.001 -0.026  0.023  0.073  0.023 -0.026 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.026 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.023 -0.026 -0.001 -0.001  0.023  0.023 -0.026 -0.001 -0.026 -0.026  0.023 -0.026  0.023 -0.026  0.173 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 1.001  0.004 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.054  0.004  0.004  0.004 -0.020 -0.020  0.029  0.079  0.029 -0.020 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.154 
 0.995 -0.001 -0.026  0.024 -0.026 -0.001 -0.001 -0.001 -0.026 -0.026 -0.026  0.049 -0.001 -0.001 -0.001 -0.026 -0.026  0.074  0.074  0.074 -0.026 -0.026 -0.001 -0.001 -0.001 -0.001 -0.001 -0.026 -0.001 -0.001 -0.001 -0.001 -0.001 -0.026 -0.026  0.024 -0.001 -0.026 -0.026  0.024  0.024 -0.026 -0.001 -0.026 -0.026 -0.001 -0.026 -0.001 -0.026  0.373 
 0.985 -0.012 -0.037  0.063 -0.037  0.013 -0.012  0.013 -0.012 -0.037 -0.037  0.063 -0.012 -0.012  0.013 -0.037 -0.037  0.088  0.113  0.138 -0.037 -0.037 -0.012 -0.012 -0.012 -0.012  0.038 -0.012 -0.012  0.063 -0.012  0.013  0.013 -0.037 -0.037  0.013 -0.012 -0.037 -0.037  0.013  0.013 -0.037 -0.012 -0.037 -0.037 -0.012 -0.037 -0.012 -0.037  0.760 
 0.977 -0.020 -0.045  0.055 -0.045  0.005  0.030  0.030 -0.020 -0.020 -0.020  0.055  0.005 -0.020  0.005 -0.020 -0.045  0.105  0.154  0.179 -0.045 -0.020 -0.020 -0.020  0.005  0.005  0.030 -0.020 -0.020  0.130 -0.020  0.030  0.005  0.005 -0.020  0.030 -0.020 -0.045 -0.045  0.030  0.030 -0.045 -0.020 -0.045 -0.020 -0.020 -0.020 -0.020 -0.045  0.902 
 0.960 -0.036 -0.061  0.063 -0.061  0.013  0.063  0.013 -0.011 -0.036  0.013  0.088  0.013 -0.036 -0.011 -0.036 -0.061  0.163  0.188  0.312 -0.061 -0.036 -0.036 -0.011  0.013 -0.011  0.088 -0.036  0.063  0.163 -0.036  0.013  0.063  0.013 -0.011  0.088 -0.036 -0.061 -0.036  0.013  0.038 -0.061 -0.036 -0.061 -0.036  0.013 -0.036 -0.036 -0.061  0.960 
 0.939 -0.007 -0.057  0.067 -0.057  0.017  0.067 -0.007 -0.032 -0.057  0.042  0.067 -0.007 -0.032 -0.007 -0.032 -0.057  0.316  0.391  0.416 -0.007 -0.057 -0.057 -0.007  0.042 -0.007  0.092 -0.057  0.092  0.217 -0.057 -0.007  0.217  0.017  0.017  0.067 -0.032 -0.057 -0.057  0.042  0.067 -0.057 -0.057 -0.057 -0.032 -0.007 -0.032 -0.007 -0.082  0.939 
 0.894 -0.053 -0.053  0.072 -0.078  0.022  0.097 -0.028 -0.028 -0.053 -0.003  0.072 -0.053 -0.053 -0.003 -0.053 -0.053  0.495  0.670  0.794 -0.053 -0.078 -0.028  0.097 -0.003 -0.053  0.146 -0.028  0.047  0.221 -0.103 -0.003  0.421  0.097  0.022  0.047 -0.028 -0.028 -0.103  0.097  0.122  0.072 -0.053 -0.078 -0.028 -0.003 -0.053 -0.028 -0.078  0.894 
 0.869 -0.077 -0.052  0.097 -0.102 -0.002  0.122 -0.052 -0.027 -0.027 -0.027  0.097 -0.052 -0.027  0.022 -0.052 -0.027  0.620  0.795  0.770 -0.052 -0.102  0.022  0.122 -0.002 -0.052  0.172 -0.052  0.047  0.222 -0.127 -0.027  0.521  0.147 -0.002 -0.027 -0.027 -0.027 -0.102  0.197  0.122  0.097 -0.077  0.022 -0.052  0.072 -0.052 -0.027 -0.102  0.869 
 0.831 -0.116 -0.041  0.134  0.009 -0.041  0.109 -0.016 -0.066  0.034  0.009  0.134 -0.091 -0.041  0.059 -0.041  0.034  0.756  0.831  0.781 -0.066 -0.066  0.009  0.183 -0.016 -0.016  0.233 -0.041  0.059  0.233 -0.165 -0.041  0.781  0.158  0.034 -0.091  0.009 -0.041  0.009  0.258  0.109  0.084 -0.066  0.034 -0.091  0.059 -0.016  0.009 -0.116  0.831 
 0.811 -0.136 -0.061  0.163  0.063 -0.086  0.088  0.038 -0.086  0.013 -0.011  0.163 -0.111 -0.011  0.013 -0.036  0.038  0.736  0.811  0.736 -0.086 -0.086  0.038  0.213 -0.011 -0.011  0.387 -0.061  0.163  0.213 -0.161 -0.061  0.761  0.138  0.063 -0.111  0.038 -0.011  0.038  0.287  0.063  0.063 -0.086  0.013 -0.111  0.113  0.013 -0.011 -0.136  0.811 
 0.784 -0.138 -0.013  0.161  0.137 -0.113  0.087  0.062 -0.088  0.062 -0.038  0.186 -0.113 -0.063  0.062 -0.063  0.112  0.734  0.759  0.710 -0.138 -0.113  0.037  0.361 -0.013 -0.013  0.435 -0.088  0.186  0.261 -0.113 -0.063  0.734  0.112  0.062 -0.162  0.112 -0.038  0.112  0.361  0.087  0.037 -0.088  0.012 -0.138  0.087  0.112 -0.013 -0.113  0.784 
 0.778 -0.119 -0.019  0.155  0.205 -0.119  0.106  0.056 -0.094  0.106 -0.044  0.205 -0.119 -0.069  0.056 -0.069  0.106  0.704  0.753  0.679 -0.143 -0.119  0.081  0.504 -0.019 -0.019  0.454 -0.094  0.180  0.330 -0.044 -0.069  0.728  0.131  0.081 -0.168  0.106 -0.044  0.106  0.429  0.106  0.006 -0.094  0.006 -0.143  0.031  0.106 -0.019 -0.119  0.778 
 0.738 -0.159 -0.009  0.140  0.265 -0.084  0.115  0.065 -0.109  0.115 -0.059  0.215 -0.134 -0.109  0.040 -0.059  0.090  0.688  0.713  0.663 -0.084 -0.109  0.090  0.613 -0.034 -0.059  0.514 -0.109  0.240  0.339 -0.059 -0.084  0.713  0.115  0.140 -0.184  0.090 -0.059  0.115  0.489  0.090 -0.009 -0.084  0.015 -0.159  0.015  0.165 -0.034 -0.084  0.763 
 0.710 -0.161 -0.012  0.138  0.287 -0.087  0.138  0.063 -0.112  0.162 -0.062  0.187 -0.137 -0.112  0.063 -0.037  0.088  0.586  0.710  0.661 -0.087 -0.112  0.113  0.636 -0.037 -0.112  0.511 -0.112  0.237  0.387 -0.037 -0.087  0.710  0.113  0.138 -0.186  0.088 -0.062  0.138  0.511  0.063 -0.012 -0.062  0.013 -0.137 -0.037  0.187 -0.037 -0.062  0.760 
 0.704 -0.168  0.006  0.131  0.305 -0.094  0.131  0.056 -0.094  0.180 -0.044  0.180 -0.143 -0.119  0.031 -0.044  0.106  0.529  0.704  0.629 -0.094 -0.119  0.131  0.654 -0.044 -0.094  0.504 -0.119  0.255  0.405  0.006 -0.094  0.728  0.131  0.180 -0.168  0.106 -0.069  0.131  0.554  0.056 -0.069 -0.044  0.006 -0.094 -0.044  0.205 -0.044 -0.069  0.753 
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 0.654 -0.168  0.006  0.131  0.305 -0.094  0.131  0.081 -0.094  0.180 -0.044  0.155 -0.143 -0.094 -0.044 -0.044  0.155  0.405  0.704  0.579 -0.069 -0.119  0.155  0.654  0.031 -0.044  0.504 -0.094  0.230  0.429  0.006 -0.119  0.728  0.106  0.205 -0.168  0.106 -0.069  0.131  0.579  0.081 -0.044 -0.094  0.006 -0.094 -0.044  0.230 -0.019 -0.094  0.728 
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-0.089 -0.164 -0.014  0.085 -0.014 -0.064  0.060 -0.114 -0.164 -0.214 -0.189  0.110 -0.039 -0.139 -0.139 -0.039  0.110  0.010  0.210 -0.014  0.185 -0.014 -0.014  0.085  0.010 -0.014 -0.139  0.060  0.235  0.384 -0.264  0.309  0.284 -0.164 -0.164 -0.089 -0.089 -0.139 -0.039 -0.164 -0.089 -0.089 -0.114 -0.039 -0.114 -0.089 -0.014  0.010  0.085  0.035 
-0.102 -0.176 -0.052  0.098 -0.027 -0.077  0.073 -0.127 -0.176 -0.226 -0.201  0.123 -0.077 -0.151 -0.151 -0.027  0.098 -0.002  0.197  0.048  0.172 -0.027 -0.027  0.098  0.023 -0.027 -0.151  0.048  0.272  0.397 -0.251  0.322  0.272 -0.151 -0.176 -0.102 -0.102 -0.151 -0.027 -0.176 -0.077 -0.102 -0.102 -0.052 -0.127 -0.102 -0.027 -0.002  0.073  0.023 
-0.102 -0.151 -0.077  0.098 -0.027 -0.102  0.073 -0.127 -0.176 -0.226 -0.201  0.147 -0.102 -0.127 -0.151 -0.027  0.098 -0.002  0.172  0.073  0.147 -0.027 -0.027  0.098  0.023 -0.052 -0.151  0.048  0.272  0.347 -0.251  0.347  0.247 -0.151 -0.201 -0.127 -0.127 -0.127 -0.027 -0.176 -0.077 -0.077 -0.102 -0.052 -0.127 -0.077 -0.027 -0.002  0.048  0.048 
-0.109 -0.084 -0.084  0.066 -0.034 -0.109  0.066 -0.134 -0.183 -0.233 -0.208  0.141 -0.109 -0.134 -0.158 -0.034  0.091 -0.009  0.141  0.091  0.116 -0.084  0.016  0.190  0.016 -0.059 -0.158  0.041  0.265  0.340 -0.258  0.315  0.215 -0.109 -0.183 -0.134 -0.134 -0.134 -0.034 -0.183 -0.084 -0.134 -0.109 -0.059 -0.134 -0.084 -0.009 -0.009  0.016  0.041 
-0.112 -0.087 -0.087  0.063 -0.037 -0.087  0.063 -0.137 -0.186 -0.236 -0.211  0.138 -0.112 -0.137 -0.161 -0.037  0.088 -0.012  0.138  0.113  0.113 -0.087  0.013  0.162  0.013 -0.062 -0.161  0.038  0.262  0.337 -0.261  0.337  0.212 -0.087 -0.161 -0.137 -0.137 -0.137 -0.037 -0.186 -0.062 -0.137 -0.112 -0.062 -0.137 -0.087 -0.012  0.013  0.038  0.063 
-0.137 -0.087 -0.112  0.037 -0.062 -0.062  0.012 -0.137 -0.212 -0.237 -0.212  0.062 -0.137 -0.137 -0.162 -0.012  0.112 -0.012  0.062  0.112  0.112 -0.112  0.012  0.212  0.012 -0.062 -0.212  0.012  0.262  0.286 -0.237  0.386  0.237 -0.062 -0.187 -0.162 -0.137 -0.137 -0.062 -0.187 -0.062 -0.112 -0.112 -0.087 -0.137 -0.112  0.012 -0.012  0.062  0.087 
-0.140 -0.090 -0.090  0.035 -0.040 -0.065  0.010 -0.140 -0.214 -0.239 -0.214  0.060 -0.140 -0.140 -0.164 -0.015  0.110 -0.015  0.060  0.110  0.110 -0.115  0.035  0.234  0.010 -0.065 -0.214  0.010  0.259  0.284 -0.239  0.384  0.234 -0.065 -0.189 -0.164 -0.140 -0.140 -0.065 -0.189 -0.065 -0.115 -0.115 -0.090 -0.140 -0.115  0.010 -0.015  0.060  0.085 
-0.165 -0.090 -0.065  0.034 -0.040 -0.065 -0.015 -0.140 -0.215 -0.240 -0.215  0.009 -0.140 -0.140 -0.165 -0.015  0.109 -0.015 -0.040  0.084  0.109 -0.115  0.034  0.234  0.009 -0.090 -0.215 -0.015  0.259  0.284 -0.240  0.383  0.209 -0.090 -0.215 -0.165 -0.140 -0.140 -0.065 -0.190 -0.065 -0.140 -0.115 -0.090 -0.140 -0.115  0.034 -0.065  0.034  0.084 
-0.165 -0.091 -0.066  0.059 -0.041 -0.066 -0.016 -0.141 -0.215 -0.240 -0.215  0.034 -0.141 -0.141 -0.190 -0.016  0.109 -0.016 -0.041  0.084  0.084 -0.190  0.034  0.233  0.009 -0.116 -0.215 -0.016  0.258  0.283 -0.240  0.383  0.208 -0.041 -0.215 -0.165 -0.141 -0.141 -0.091 -0.190 -0.066 -0.165 -0.141 -0.091 -0.141 -0.116  0.059 -0.066  0.034  0.084 
-0.169 -0.094 -0.069  0.055 -0.044 -0.069 -0.044 -0.169 -0.219 -0.244 -0.194  0.030 -0.144 -0.144 -0.194 -0.019  0.105 -0.019 -0.044  0.105  0.080 -0.194  0.030  0.205  0.005 -0.119 -0.219 -0.019  0.255  0.280 -0.244  0.379  0.180  0.005 -0.194 -0.169 -0.144 -0.144 -0.094 -0.194 -0.044 -0.194 -0.144 -0.094 -0.119 -0.119  0.080 -0.044  0.030  0.080 
-0.169 -0.070 -0.070  0.055 -0.045 -0.070 -0.045 -0.144 -0.219 -0.244 -0.194  0.005 -0.144 -0.144 -0.194  0.005  0.105 -0.020 -0.045  0.105  0.080 -0.194  0.030  0.179  0.030 -0.120 -0.219 -0.020  0.279  0.279 -0.244  0.379  0.179  0.005 -0.194 -0.169 -0.144 -0.144 -0.070 -0.194 -0.045 -0.194 -0.144 -0.095 -0.144 -0.120  0.080 -0.045  0.030  0.080 
-0.171 -0.071 -0.071  0.053 -0.046 -0.071 -0.046 -0.146 -0.221 -0.246 -0.196  0.003 -0.171 -0.146 -0.196  0.028  0.103 -0.046 -0.046  0.103  0.078 -0.196  0.028  0.178  0.028 -0.121 -0.221 -0.021  0.278  0.278 -0.246  0.377  0.153  0.028 -0.196 -0.146 -0.146 -0.146 -0.071 -0.196 -0.046 -0.196 -0.146 -0.096 -0.146 -0.121  0.103 -0.046  0.028  0.078 
-0.173 -0.074 -0.049  0.051 -0.049 -0.124 -0.049 -0.148 -0.223 -0.248 -0.223  0.001 -0.173 -0.148 -0.198  0.026  0.101 -0.024 -0.049  0.101  0.076 -0.198  0.001  0.175  0.026 -0.099 -0.223 -0.024  0.275  0.250 -0.248  0.400  0.150  0.026 -0.198 -0.148 -0.148 -0.148 -0.074 -0.198 -0.049 -0.198 -0.124 -0.099 -0.148 -0.124  0.076 -0.049  0.001  0.076 
-0.200 -0.076 -0.051  0.074 -0.051 -0.126 -0.051 -0.150 -0.225 -0.250 -0.225 -0.026 -0.175 -0.150 -0.200  0.049  0.074 -0.026 -0.051  0.099  0.074 -0.200 -0.001  0.198  0.024 -0.101 -0.225 -0.026  0.273  0.248 -0.250  0.398  0.173  0.024 -0.200 -0.126 -0.150 -0.150 -0.076 -0.200 -0.051 -0.200 -0.126 -0.101 -0.150 -0.126  0.074 -0.051 -0.026  0.074 

 0.991  0.019 -0.005  0.019 -0.030  0.019 -0.030 -0.005  0.044 -0.005  0.019 -0.005 -0.005 -0.005 -0.005  0.069 -0.005 -0.005 -0.005  0.019 -0.005 -0.005 -0.005  0.019  0.069 -0.030 -0.005 -0.030  0.044 -0.030 -0.005  0.019 -0.005  0.019  0.044 -0.005 -0.030 -0.030  0.119  0.019 -0.005 -0.005  0.019 -0.030  0.069 -0.030 -0.005 -0.030 -0.030  0.019 
 0.996  0.025 -0.025  0.025 -0.025  0.000 -0.025  0.000  0.050 -0.025  0.025  0.000  0.000 -0.025  0.000  0.050  0.000  0.000 -0.025  0.025 -0.025  0.000  0.000  0.025  0.075 -0.025  0.000 -0.025  0.025 -0.025 -0.025  0.025  0.000  0.025  0.050 -0.025 -0.025 -0.025  0.100  0.025 -0.025  0.000  0.000 -0.025  0.050 -0.025  0.000 -0.025 -0.025  0.025 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.001  0.029 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.004  0.054  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.054 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.029  0.004  0.004  0.054 -0.020 -0.020 -0.020  0.104  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004 
 1.000  0.029 -0.021  0.004 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.029  0.004  0.004 -0.021  0.004  0.054  0.004  0.004 -0.021  0.029 -0.021  0.004  0.004  0.029  0.054 -0.021  0.004 -0.021  0.029 -0.021 -0.021  0.029  0.004  0.004  0.054 -0.021 -0.021 -0.021  0.104  0.004 -0.021  0.004  0.004 -0.021  0.029 -0.021 -0.021 -0.021 -0.021  0.004 
 1.000  0.028 -0.021  0.003 -0.021  0.003 -0.021 -0.021  0.003 -0.021  0.028  0.003  0.003 -0.021  0.003  0.053  0.003  0.003 -0.021  0.028 -0.021  0.003  0.003  0.028  0.053 -0.021  0.003 -0.021  0.028 -0.021 -0.021  0.028  0.003  0.003  0.053 -0.021 -0.021 -0.021  0.103  0.003 -0.021  0.003  0.003 -0.021  0.028 -0.021 -0.021 -0.021 -0.021  0.003 
 1.000  0.029 -0.021  0.004 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.029  0.004  0.004 -0.021  0.004  0.079  0.004  0.004 -0.021  0.029 -0.021  0.004  0.004  0.029  0.054 -0.021  0.004 -0.021  0.029  0.004 -0.021  0.054  0.004  0.004  0.054 -0.021 -0.021 -0.021  0.104  0.004 -0.021  0.004  0.004 -0.021  0.029 -0.021 -0.021 -0.021 -0.021  0.004 
 1.000  0.029 -0.021  0.004 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.029  0.004  0.004 -0.021  0.004  0.079  0.004  0.004 -0.021  0.029 -0.021  0.004  0.004  0.029  0.054 -0.021  0.004 -0.021  0.029  0.004 -0.021  0.054  0.004  0.004  0.054 -0.021 -0.021 -0.021  0.104  0.004 -0.021  0.004  0.004 -0.021  0.029 -0.021 -0.021 -0.021 -0.021  0.004 
 1.000  0.028 -0.021  0.003 -0.021  0.003 -0.021 -0.021  0.003 -0.021  0.028  0.003  0.003 -0.021  0.003  0.078  0.003  0.003 -0.021  0.028 -0.021  0.003  0.003  0.028  0.053 -0.021  0.003 -0.021  0.028  0.003 -0.021  0.053  0.003  0.003  0.053 -0.021 -0.021 -0.021  0.128  0.003 -0.021  0.003  0.003 -0.021  0.028 -0.021 -0.021 -0.021 -0.021  0.003 
 0.997  0.025 -0.024  0.000 -0.024  0.000 -0.024 -0.024  0.000 -0.024  0.075  0.000  0.000 -0.024  0.000  0.100  0.000  0.000 -0.024  0.025  0.000  0.000  0.000  0.025  0.050 -0.024  0.000 -0.024  0.025  0.000 -0.024  0.075  0.000  0.000  0.050  0.000 -0.024 -0.024  0.225  0.000 -0.024  0.000  0.000 -0.024  0.025 -0.024  0.000 -0.024 -0.024  0.000 
 0.989  0.042 -0.008  0.017 -0.008 -0.008 -0.033 -0.008  0.017 -0.033  0.092  0.042  0.042 -0.033 -0.008  0.092 -0.008 -0.008 -0.033  0.017 -0.008 -0.008 -0.008  0.042  0.042 -0.033 -0.008 -0.008  0.017 -0.008  0.042  0.067 -0.008 -0.008  0.042 -0.008 -0.033  0.042  0.515 -0.008 -0.008  0.017 -0.008 -0.008  0.017  0.017  0.067 -0.033 -0.033  0.017 
 0.975  0.028 -0.022  0.028  0.053  0.003 -0.022 -0.022  0.028 -0.022  0.128  0.028  0.028 -0.047  0.028  0.128 -0.022 -0.022 -0.047  0.028 -0.022 -0.022 -0.022  0.053  0.028 -0.047  0.003 -0.022  0.003  0.003  0.028  0.053 -0.022 -0.022  0.028 -0.022 -0.047  0.053  0.800  0.003  0.003  0.003 -0.022  0.003  0.003  0.003  0.053 -0.047 -0.047  0.003 
 0.954  0.082 -0.043  0.032  0.057 -0.018 -0.043 -0.043 -0.018 -0.043  0.281  0.057  0.082 -0.068  0.007  0.231 -0.018 -0.018 -0.068  0.032 -0.043 -0.018 -0.043  0.107  0.032 -0.043  0.032 -0.043  0.032  0.007  0.007  0.032 -0.018 -0.043  0.057  0.007 -0.043  0.132  0.879 -0.018 -0.018  0.032 -0.043 -0.018  0.057  0.032  0.007 -0.068 -0.068  0.032 
 0.906  0.059 -0.016  0.009  0.109 -0.091  0.034 -0.016 -0.041 -0.016  0.557  0.059  0.109 -0.116  0.084  0.358  0.034 -0.066 -0.116  0.059 -0.041  0.034 -0.041  0.158  0.009  0.034  0.034 -0.041  0.059  0.009  0.059  0.009 -0.016 -0.041  0.109  0.084 -0.041  0.208  0.906 -0.041  0.034  0.009 -0.066  0.034  0.183  0.034 -0.041 -0.041 -0.091 -0.016 
 0.864  0.117 -0.007 -0.007  0.192 -0.132  0.092  0.042 -0.007 -0.057  0.765  0.042  0.117 -0.107  0.192  0.366 -0.007 -0.007 -0.132  0.092 -0.032  0.067 -0.032  0.192  0.017  0.017  0.042 -0.007  0.017  0.067  0.092 -0.007 -0.032 -0.007  0.217  0.117 -0.057  0.242  0.864 -0.057  0.017  0.092 -0.082  0.042  0.267  0.092 -0.032 -0.032 -0.082 -0.032 
 0.804  0.131  0.056 -0.043  0.405 -0.168  0.181  0.056 -0.043 -0.093  0.804 -0.018  0.106 -0.143  0.256  0.455  0.006 -0.068 -0.143  0.131 -0.018  0.181 -0.068  0.156  0.031  0.006  0.031  0.031  0.006  0.081  0.106 -0.043  0.056  0.006  0.256  0.156 -0.093  0.355  0.804  0.031  0.031  0.131 -0.068  0.056  0.430  0.031 -0.018 -0.018 -0.068 -0.093 
 0.785  0.137  0.112 -0.012  0.486 -0.187  0.262  0.037 -0.037 -0.112  0.785 -0.062  0.087 -0.112  0.286  0.411  0.087 -0.087 -0.137  0.137  0.012  0.212 -0.062  0.137  0.162  0.037  0.037  0.037 -0.037  0.112  0.162 -0.062  0.087 -0.012  0.237  0.112 -0.087  0.361  0.785  0.037  0.012  0.112 -0.037 -0.012  0.436  0.012 -0.037  0.012 -0.062 -0.087 
 0.701  0.177  0.152 -0.047  0.551 -0.196  0.426  0.053 -0.022 -0.122  0.750 -0.072  0.103 -0.072  0.302  0.377  0.152 -0.122 -0.171  0.128  0.103  0.177 -0.047  0.103  0.202  0.003  0.078  0.103 -0.047  0.152  0.227 -0.047  0.078 -0.022  0.177  0.128  0.028  0.377  0.725  0.003  0.078  0.152  0.028 -0.022  0.501  0.003 -0.047 -0.022 -0.022 -0.097 
 0.688  0.164  0.214 -0.010  0.538 -0.209  0.488  0.065  0.040 -0.085  0.712 -0.035  0.140 -0.060  0.264  0.364  0.164 -0.159 -0.184  0.140  0.090  0.164 -0.085  0.115  0.264 -0.010  0.140  0.115 -0.035  0.264  0.239 -0.060  0.065 -0.085  0.189  0.065  0.115  0.364  0.712 -0.010  0.065  0.189  0.040  0.015  0.488  0.015 -0.060 -0.035 -0.060 -0.085 
 0.670  0.172  0.272  0.122  0.546 -0.202  0.521  0.072  0.047 -0.102  0.670 -0.027  0.147 -0.002  0.247  0.321  0.097 -0.177 -0.227  0.172  0.072  0.122 -0.127  0.097  0.321 -0.027  0.197  0.147 -0.052  0.272  0.247 -0.052  0.047 -0.152  0.147  0.047  0.147  0.371  0.670 -0.027  0.047  0.197  0.022  0.022  0.471  0.022 -0.052 -0.052 -0.102 -0.102 
 0.658  0.160  0.284  0.135  0.509 -0.164  0.484  0.035  0.035 -0.114  0.658 -0.014  0.135  0.060  0.235  0.309  0.110 -0.164 -0.264  0.160  0.085  0.110 -0.139  0.110  0.309 -0.014  0.210  0.210 -0.039  0.284  0.210  0.010  0.085 -0.164  0.135  0.035  0.110  0.359  0.658 -0.039  0.035  0.235 -0.014  0.010  0.459  0.010 -0.064 -0.039 -0.139 -0.114 
 0.645  0.171  0.296  0.146  0.421 -0.152  0.470 -0.003  0.072 -0.152  0.595 -0.003  0.171  0.047  0.221  0.346  0.097 -0.177 -0.277  0.122  0.097  0.122 -0.152  0.122  0.296 -0.053  0.196  0.246 -0.028  0.271  0.171 -0.003  0.072 -0.202  0.122  0.047  0.097  0.321  0.645 -0.028 -0.028  0.296 -0.028 -0.003  0.445  0.022 -0.053  0.022 -0.177 -0.128 
 0.618  0.195  0.294  0.095  0.419 -0.154  0.469 -0.029  0.020 -0.154  0.568 -0.029  0.195  0.070  0.195  0.369  0.070 -0.154 -0.279  0.095  0.120  0.145 -0.154  0.095  0.294 -0.054  0.120  0.294 -0.004  0.245  0.170 -0.054  0.070 -0.254  0.070  0.045  0.095  0.319  0.618 -0.029 -0.079  0.319 -0.004 -0.004  0.419  0.045 -0.004  0.020 -0.179 -0.129 
 0.585  0.187  0.286  0.087  0.386 -0.162  0.386 -0.062  0.012 -0.137  0.536 -0.012  0.162  0.037  0.187  0.361  0.087 -0.187 -0.262  0.062  0.137  0.162 -0.137  0.112  0.311 -0.062  0.087  0.336  0.012  0.262  0.112 -0.062  0.037 -0.286  0.062  0.087  0.062  0.311  0.610 -0.012 -0.087  0.311  0.012  0.012  0.386  0.062  0.012  0.012 -0.187 -0.137 
 0.373  0.173  0.323  0.049  0.298 -0.150  0.173 -0.076  0.049 -0.076  0.472 -0.001  0.099 -0.001  0.173  0.248  0.074 -0.175 -0.175 -0.026  0.099  0.198 -0.076  0.049  0.273 -0.026  0.099  0.298 -0.101  0.173  0.099 -0.026 -0.026 -0.200  0.074  0.148  0.124  0.348  0.672  0.024 -0.001  0.223  0.024  0.049  0.348  0.099  0.074 -0.001 -0.175 -0.101 
 0.287  0.138  0.312  0.113  0.162 -0.112  0.138 -0.037  0.038 -0.112  0.461  0.038  0.088 -0.012  0.113  0.138  0.063 -0.112 -0.161 -0.062  0.063  0.138 -0.037  0.038  0.212  0.063  0.038  0.113 -0.087  0.138  0.063  0.013 -0.037 -0.161  0.138  0.138  0.038  0.237  0.511  0.038 -0.012  0.138  0.038  0.138  0.287  0.138  0.038 -0.037 -0.161 -0.037 
 0.284  0.110  0.334  0.135  0.135 -0.089  0.135 -0.039  0.060 -0.114  0.359  0.035  0.085 -0.014  0.135  0.060  0.060 -0.089 -0.139 -0.039  0.010  0.135 -0.014  0.035  0.160  0.060  0.035  0.085 -0.064  0.160  0.085 -0.039 -0.064 -0.139  0.185  0.110  0.035  0.185  0.309  0.060 -0.039  0.135  0.060  0.160  0.284  0.160  0.010 -0.014 -0.089 -0.039 
 0.192  0.068  0.317  0.118  0.068 -0.057  0.093 -0.032  0.068 -0.082  0.267  0.043  0.068 -0.032  0.068 -0.007  0.093 -0.057 -0.107 -0.007 -0.032  0.043 -0.007  0.043  0.043  0.093  0.018 -0.007 -0.057  0.118  0.093 -0.032 -0.057 -0.107  0.167  0.043  0.068  0.217  0.242  0.068 -0.007 -0.007  0.043  0.167  0.192  0.167  0.043 -0.007 -0.057 -0.007 
 0.131  0.081  0.305  0.106  0.081 -0.043  0.081 -0.018  0.056 -0.068  0.156  0.006  0.081 -0.043  0.056  0.006  0.106 -0.043 -0.093 -0.018 -0.043  0.006  0.006  0.031  0.006  0.081  0.031 -0.018 -0.043  0.131  0.106  0.006 -0.068 -0.093  0.131  0.006  0.081  0.231  0.131  0.081  0.006 -0.018  0.056  0.106  0.081  0.206  0.006  0.006 -0.043  0.006 
 0.050  0.075  0.274  0.125  0.050 -0.050  0.000 -0.025  0.050 -0.075  0.050 -0.025  0.025 -0.050  0.075 -0.025  0.050 -0.050 -0.075 -0.025 -0.025  0.025  0.000  0.050 -0.050  0.050  0.025 -0.075 -0.025  0.050  0.125  0.000 -0.050 -0.075  0.125 -0.025  0.075  0.199  0.050  0.100  0.000 -0.025  0.025  0.075  0.025  0.174  0.000  0.050 -0.025 -0.025 
 0.039  0.064  0.288  0.039  0.039 -0.036 -0.036 -0.011  0.014 -0.061  0.039 -0.011 -0.011 -0.036  0.064 -0.011  0.014 -0.036 -0.061 -0.036 -0.011  0.039  0.014  0.014 -0.061  0.039  0.014 -0.061 -0.011  0.014  0.089  0.014 -0.036 -0.061  0.139 -0.011  0.064  0.163  0.014  0.114 -0.011 -0.011  0.039  0.039  0.039  0.089  0.014  0.039 -0.011 -0.036 
 0.032  0.057  0.231  0.032  0.007 -0.018 -0.018  0.007  0.007 -0.043  0.007 -0.018 -0.043 -0.018  0.057 -0.018  0.007 -0.018 -0.043 -0.043  0.007  0.032 -0.018  0.032 -0.043  0.057 -0.018 -0.043  0.007  0.007  0.057 -0.018 -0.043 -0.043  0.156 -0.018  0.057  0.107  0.007  0.082 -0.043 -0.018  0.057  0.007  0.007  0.057  0.032  0.032  0.007 -0.043 
 0.041  0.041  0.216  0.016  0.016 -0.033 -0.008  0.016  0.016 -0.033  0.016 -0.008 -0.033 -0.008  0.041 -0.008  0.016 -0.033 -0.033 -0.033  0.016  0.041 -0.008  0.016 -0.033  0.041 -0.008 -0.033  0.016 -0.008  0.066 -0.008 -0.033 -0.033  0.191 -0.008  0.066  0.066 -0.008  0.091 -0.033 -0.008  0.066  0.016  0.016 -0.008  0.016  0.041  0.016 -0.033 
 0.004  0.029  0.178  0.004  0.029 -0.021  0.029  0.004  0.029 -0.021  0.004  0.004 -0.021 -0.021  0.029  0.004  0.029 -0.021 -0.021 -0.021  0.029  0.004  0.004  0.004 -0.021  0.054 -0.021 -0.021  0.029  0.004  0.054  0.004 -0.021 -0.021  0.228  0.004  0.054  0.029  0.004  0.054 -0.021  0.004  0.079  0.029  0.004  0.004  0.004  0.029  0.029 -0.021 
 0.003  0.028  0.128  0.003  0.003  0.003  0.028  0.003  0.028 -0.022  0.003  0.003 -0.022  0.003  0.028  0.003  0.028 -0.022 -0.022 -0.022  0.003  0.003 -0.022  0.003 -0.022  0.028 -0.022 -0.022  0.003  0.003  0.053  0.028 -0.022  0.003  0.227 -0.022  0.078  0.028  0.003  0.053 -0.022  0.003  0.078  0.028 -0.022  0.003  0.003  0.003  0.028 -0.022 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.021  0.029 -0.021 -0.021 -0.021 -0.021  0.004  0.029  0.004  0.004 -0.021 -0.021 -0.021  0.004  0.004 -0.021  0.004 -0.021  0.029  0.004 -0.021  0.004  0.004  0.029  0.029 -0.021  0.004  0.129 -0.021  0.054  0.004  0.004  0.054 -0.021  0.004  0.054  0.029 -0.021  0.004 -0.021  0.004  0.029 -0.021 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.021  0.029 -0.021 -0.021 -0.021 -0.021  0.004  0.029  0.004  0.004 -0.021 -0.021 -0.021  0.004  0.004 -0.021  0.004 -0.021  0.029  0.004 -0.021  0.004  0.004  0.029  0.029 -0.021  0.004  0.129 -0.021  0.054  0.004  0.004  0.054 -0.021  0.004  0.054  0.029 -0.021  0.004 -0.021  0.004  0.029 -0.021 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.029 -0.020  0.004  0.104 -0.020  0.054 -0.020  0.004  0.054 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.004  0.029 -0.020 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.029 -0.020  0.004  0.104 -0.020  0.054 -0.020  0.004  0.054 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.004  0.029 -0.020 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.029 -0.020  0.004  0.104 -0.020  0.054 -0.020  0.004  0.054 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.004  0.029 -0.020 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.029 -0.020  0.004  0.104 -0.020  0.054 -0.020  0.004  0.054 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.004  0.029 -0.020 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.029 -0.020  0.004  0.104 -0.020  0.054 -0.020  0.004  0.054 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.004  0.029 -0.020 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.029 -0.020  0.004  0.104 -0.020  0.054 -0.020  0.004  0.054 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.004  0.029 -0.020 
 0.004  0.004  0.079  0.004  0.004  0.004  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.029  0.029 -0.020  0.004  0.104 -0.020  0.054 -0.020  0.004  0.054 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.004  0.029 -0.020 
 0.022  0.022  0.147 -0.002 -0.002 -0.002  0.022 -0.002  0.022 -0.002 -0.027 -0.027 -0.027 -0.002  0.022  0.022  0.022 -0.027 -0.027 -0.027 -0.002 -0.002 -0.027 -0.002 -0.027 -0.002  0.047 -0.027 -0.027 -0.002  0.047  0.047 -0.027 -0.002  0.346 -0.027  0.097 -0.027 -0.002  0.072 -0.027 -0.002  0.047 -0.002 -0.027 -0.002 -0.027  0.022  0.022 -0.027 
 0.033  0.008  0.182 -0.017 -0.017 -0.017  0.008 -0.017  0.058  0.033  0.008 -0.042 -0.042 -0.017  0.008  0.033  0.008 -0.042 -0.017 -0.017  0.033  0.008 -0.017 -0.017 -0.017  0.108  0.058 -0.042 -0.042  0.033  0.058  0.083 -0.042  0.008  0.706 -0.017  0.108 -0.017 -0.017  0.108 -0.017 -0.017  0.083  0.033 -0.017 -0.017 -0.042  0.083  0.058 -0.042 
 0.036  0.036  0.360 -0.038 -0.038 -0.038  0.011  0.036  0.111  0.011 -0.013 -0.063 -0.013 -0.038  0.061  0.061  0.061 -0.063 -0.013 -0.038  0.036  0.086 -0.013 -0.013 -0.038  0.111  0.261 -0.063 -0.063  0.036  0.086  0.061 -0.063  0.061  0.734 -0.038  0.161 -0.038 -0.038  0.211 -0.013  0.011  0.161  0.036 -0.013  0.011 -0.063  0.086  0.036 -0.038 
 0.078  0.053  0.552 -0.021 -0.046 -0.071  0.078  0.103  0.278  0.153  0.003 -0.021  0.053 -0.096  0.103  0.028  0.103 -0.121 -0.046  0.028 -0.021  0.103  0.003 -0.021  0.003  0.228  0.626 -0.096  0.053  0.128  0.153  0.078 -0.096  0.028  0.900 -0.046  0.178 -0.046 -0.071  0.302  0.028  0.003  0.327  0.053  0.028  0.028 -0.096  0.128  0.028 -0.071 
 0.087  0.062  0.660  0.062 -0.038 -0.063  0.112  0.161  0.311  0.336  0.037  0.037  0.062 -0.088  0.062 -0.013  0.112 -0.138 -0.088  0.087 -0.063  0.087  0.037 -0.038  0.137  0.286  0.660 -0.063  0.037  0.112  0.311  0.137 -0.113  0.037  0.859 -0.063  0.112  0.062 -0.063  0.435  0.062  0.037  0.510  0.062  0.062  0.087 -0.088  0.311  0.037 -0.063 
 0.077  0.027  0.675  0.102 -0.072 -0.072  0.127  0.401  0.476  0.526  0.152  0.102  0.127 -0.122  0.027  0.002  0.277 -0.147 -0.122  0.102 -0.072  0.152 -0.022  0.052  0.202  0.401  0.800 -0.047  0.052  0.202  0.426  0.102 -0.147  0.077  0.800  0.027  0.077  0.102 -0.047  0.551  0.127  0.027  0.551  0.202  0.052  0.102 -0.022  0.426  0.002  0.002 
 0.063  0.088  0.636  0.162 -0.087 -0.087  0.138  0.511  0.561  0.536  0.237  0.088  0.187 -0.112  0.038  0.013  0.287 -0.161 -0.161  0.113 -0.062  0.138 -0.012  0.113  0.287  0.412  0.785 -0.012  0.013  0.187  0.461  0.088 -0.161  0.063  0.710 -0.012  0.088  0.162 -0.062  0.461  0.212  0.038  0.511  0.262  0.063  0.088 -0.037  0.387 -0.012 -0.012 
 0.107  0.231  0.530  0.181 -0.093 -0.093  0.181  0.530  0.680  0.605  0.430  0.132  0.281 -0.142  0.057  0.032  0.356 -0.167 -0.167  0.082 -0.043  0.132 -0.043  0.156  0.406  0.430  0.729 -0.043 -0.018  0.156  0.505  0.156 -0.192  0.107  0.655  0.007 -0.018  0.231  0.007  0.430  0.331  0.007  0.455  0.256  0.132  0.082  0.032  0.406 -0.043 -0.043 
 0.147  0.297  0.446  0.222 -0.102 -0.077  0.197  0.521  0.671  0.571  0.471  0.147  0.297 -0.127  0.048  0.023  0.372 -0.151 -0.176  0.073 -0.027  0.147 -0.077  0.147  0.422  0.422  0.720 -0.052 -0.027  0.147  0.496  0.147 -0.176  0.098  0.621  0.023 -0.027  0.222 -0.002  0.422  0.347 -0.002  0.446  0.272  0.147  0.073  0.048  0.372 -0.052 -0.052 
 0.235  0.285  0.360  0.210 -0.114 -0.089  0.210  0.509  0.659  0.559  0.584  0.210  0.335 -0.114  0.061  0.011  0.410 -0.163 -0.188  0.011 -0.039  0.136 -0.064  0.136  0.534  0.410  0.684 -0.064 -0.064  0.111  0.509  0.260 -0.188  0.086  0.534  0.086 -0.014  0.235  0.036  0.360  0.410  0.011  0.434  0.285  0.235  0.036  0.061  0.385 -0.114 -0.064 
 0.280  0.305  0.330  0.205 -0.094 -0.094  0.205  0.504  0.654  0.554  0.629  0.230  0.330 -0.119  0.081  0.006  0.405 -0.168 -0.193  0.006 -0.019  0.131 -0.069  0.131  0.554  0.405  0.679 -0.044 -0.069  0.106  0.504  0.280 -0.193  0.056  0.529  0.106  0.006  0.205  0.081  0.330  0.405 -0.019  0.429  0.280  0.305  0.056  0.056  0.330 -0.143 -0.069 
 0.390  0.340  0.266  0.216 -0.058 -0.108  0.266  0.465  0.639  0.515  0.639  0.340  0.266 -0.083  0.141 -0.033  0.365 -0.183 -0.258 -0.008 -0.008  0.166 -0.008  0.166  0.589  0.365  0.664 -0.033 -0.058  0.116  0.490  0.290 -0.233  0.016  0.490  0.116  0.016  0.141  0.166  0.315  0.440 -0.008  0.440  0.315  0.440  0.066  0.041  0.315 -0.183 -0.108 
 0.381  0.356  0.257  0.232 -0.017 -0.067  0.356  0.406  0.630  0.506  0.605  0.356  0.257 -0.042  0.257 -0.067  0.356 -0.217 -0.267 -0.017 -0.017  0.207 -0.017  0.157  0.556  0.356  0.580 -0.067 -0.067  0.082  0.481  0.306 -0.242  0.007  0.481  0.132  0.057  0.132  0.182  0.306  0.431 -0.017  0.431  0.282  0.456  0.132  0.007  0.306 -0.192 -0.117 
 0.373  0.348  0.249  0.249 -0.000 -0.075  0.448  0.398  0.622  0.498  0.572  0.373  0.224 -0.000  0.323 -0.075  0.373 -0.225 -0.275 -0.000 -0.025  0.199 -0.025  0.199  0.548  0.373  0.523 -0.025 -0.100  0.074  0.473  0.274 -0.250 -0.000  0.473  0.174  0.074  0.149  0.199  0.298  0.423  0.024  0.423  0.298  0.448  0.124 -0.000  0.298 -0.150 -0.175 
 0.366  0.366  0.242  0.267 -0.007 -0.057  0.441  0.391  0.615  0.516  0.590  0.366  0.217 -0.007  0.341 -0.007  0.366 -0.207 -0.282 -0.007 -0.032  0.192 -0.007  0.167  0.566  0.366  0.491 -0.007 -0.082  0.067  0.466  0.267 -0.257 -0.007  0.466  0.217  0.067  0.167  0.217  0.291  0.416  0.017  0.416  0.316  0.441  0.142 -0.007  0.291 -0.157 -0.182 
 0.382  0.332  0.207  0.282 -0.042 -0.067  0.456  0.382  0.581  0.506  0.581  0.357  0.257  0.058  0.357  0.008  0.357 -0.191 -0.291 -0.017 -0.017  0.207 -0.017  0.133  0.556  0.332  0.481  0.058 -0.117  0.033  0.456  0.257 -0.266 -0.042  0.456  0.282  0.058  0.157  0.232  0.282  0.382  0.033  0.382  0.307  0.431  0.232 -0.017  0.282 -0.142 -0.191 
 0.380  0.280  0.180  0.280 -0.044 -0.044  0.454  0.355  0.579  0.504  0.554  0.355  0.305  0.131  0.355  0.006  0.330 -0.193 -0.293 -0.019 -0.019  0.205 -0.044  0.131  0.554  0.330  0.479  0.081 -0.094  0.031  0.479  0.205 -0.268 -0.069  0.454  0.330  0.081  0.155  0.230  0.280  0.380  0.031  0.405  0.305  0.429  0.230 -0.019  0.255 -0.143 -0.193 
 0.350  0.275  0.200  0.225 -0.024 -0.074  0.425  0.350  0.574  0.499  0.549  0.325  0.300  0.150  0.350  0.001  0.300 -0.173 -0.298 -0.024  0.001  0.225 -0.024  0.126  0.524  0.325  0.449  0.150 -0.099  0.001  0.474  0.126 -0.273 -0.074  0.449  0.375  0.126  0.150  0.225  0.275  0.375  0.026  0.425  0.325  0.449  0.225  0.001  0.250 -0.148 -0.198 
 0.350  0.300  0.175  0.225 -0.024 -0.074  0.425  0.350  0.574  0.499  0.549  0.325  0.300  0.150  0.300  0.001  0.300 -0.173 -0.298 -0.024  0.001  0.225 -0.024  0.126  0.524  0.325  0.449  0.150 -0.099 -0.024  0.474  0.126 -0.273 -0.074  0.449  0.400  0.150  0.150  0.225  0.275  0.375  0.026  0.425  0.350  0.449  0.225  0.001  0.250 -0.148 -0.198 
 0.350  0.300  0.175  0.225 -0.024 -0.099  0.425  0.350  0.574  0.499  0.549  0.325  0.300  0.150  0.300  0.001  0.300 -0.198 -0.298 -0.024  0.001  0.225 -0.049  0.126  0.524  0.300  0.449  0.150 -0.099 -0.074  0.474  0.076 -0.273 -0.074  0.449  0.425  0.150  0.150  0.250  0.300  0.350  0.026  0.375  0.400  0.449  0.225  0.001  0.250 -0.173 -0.198 
 0.337  0.263  0.113  0.163 -0.036 -0.011  0.337  0.213  0.611  0.487  0.636  0.213  0.238  0.063  0.263 -0.036  0.287 -0.136 -0.236 -0.036  0.088  0.163  0.038  0.113  0.512  0.263  0.312  0.013 -0.036  0.013  0.462 -0.011 -0.186 -0.036  0.387  0.387  0.088  0.188  0.138  0.312  0.312  0.013  0.312  0.263  0.437  0.213 -0.011  0.287 -0.111 -0.136 
 0.262  0.212  0.038  0.113 -0.012 -0.037  0.237  0.162  0.561  0.436  0.686  0.138  0.113  0.013  0.162 -0.037  0.113 -0.087 -0.161 -0.012  0.013  0.187  0.088  0.088  0.461  0.237  0.237  0.013 -0.012  0.088  0.412  0.038 -0.112 -0.012  0.461  0.287  0.013  0.162  0.088  0.262  0.237  0.038  0.262  0.187  0.387  0.138  0.013  0.212 -0.087 -0.037 
 0.263  0.163  0.064  0.089  0.014 -0.011  0.139  0.114  0.512  0.437  0.711  0.089  0.114 -0.036  0.139 -0.011  0.114 -0.086 -0.136 -0.011  0.039  0.163  0.114  0.039  0.388  0.213  0.238  0.014 -0.011  0.114  0.388  0.064 -0.086 -0.011  0.462  0.188 -0.011  0.114  0.089  0.238  0.188  0.064  0.238  0.139  0.363  0.089  0.014  0.114 -0.086 -0.036 
 0.213  0.139  0.114  0.064  0.014 -0.061  0.089  0.089  0.512  0.437  0.736  0.039  0.139 -0.011  0.089 -0.011  0.089 -0.061 -0.111 -0.036  0.014  0.114  0.064  0.064  0.313  0.188  0.114 -0.036 -0.036  0.114  0.388  0.014 -0.061  0.014  0.487  0.188 -0.011  0.064  0.039  0.263  0.188  0.014  0.188  0.114  0.338  0.039  0.014  0.064 -0.086 -0.061 
 0.200  0.101  0.126  0.026 -0.024 -0.049  0.001  0.076  0.474  0.350  0.699  0.051  0.150  0.001  0.051 -0.024  0.101 -0.074 -0.099 -0.024  0.026  0.076  0.051  0.076  0.300  0.175  0.126 -0.024 -0.024  0.101  0.375  0.001 -0.049  0.026  0.474  0.175  0.001  0.076  0.001  0.250  0.175  0.001  0.175  0.126  0.250  0.026  0.026  0.076 -0.074 -0.049 
 0.193  0.119  0.069 -0.006 -0.031 -0.056 -0.006  0.094  0.442  0.293  0.692  0.044  0.143  0.019  0.044 -0.006  0.119 -0.056 -0.081 -0.006  0.044  0.019  0.044  0.069  0.168  0.168  0.119 -0.031 -0.031  0.044  0.368 -0.006 -0.031 -0.006  0.492  0.143  0.019  0.044  0.019  0.268  0.193  0.019  0.193  0.143  0.143  0.019  0.019  0.044 -0.056 -0.056 
 0.202  0.077  0.077  0.002  0.002 -0.047 -0.022  0.102  0.451  0.252  0.725  0.027  0.127  0.027  0.027  0.002  0.127 -0.047 -0.072 -0.022  0.052  0.027  0.052  0.077  0.102  0.127  0.127 -0.047 -0.022  0.027  0.326  0.002 -0.022  0.002  0.501  0.102  0.027  0.052  0.027  0.252  0.152  0.027  0.152  0.127  0.152  0.002 -0.022  0.052 -0.047 -0.047 
 0.148  0.048  0.098 -0.001  0.023 -0.051 -0.001  0.098  0.273  0.173  0.746  0.023  0.098 -0.001  0.023  0.023  0.073 -0.026 -0.051 -0.026  0.023  0.048 -0.001  0.073 -0.026  0.073  0.073 -0.051 -0.001 -0.001  0.273  0.023 -0.001 -0.026  0.497  0.073  0.023  0.048  0.048  0.123  0.123  0.023  0.073  0.123  0.148 -0.001 -0.026  0.073 -0.026 -0.051 
 0.154  0.055  0.105 -0.045 -0.020 -0.045  0.005  0.105  0.105  0.105  0.852  0.030  0.055  0.005  0.030  0.030  0.030 -0.020 -0.045 -0.020  0.030  0.030  0.030  0.080 -0.045  0.080  0.030 -0.020 -0.020  0.005  0.130  0.030  0.005  0.005  0.478  0.080  0.030  0.055  0.030  0.080  0.080  0.030  0.080  0.105  0.154  0.005 -0.045  0.030 -0.020 -0.045 
 0.097  0.022  0.097 -0.028 -0.003 -0.028 -0.003  0.072  0.022 -0.003  0.919  0.022 -0.003  0.022  0.022  0.047 -0.003 -0.003 -0.028 -0.003 -0.003  0.047 -0.003  0.022 -0.028  0.072 -0.003 -0.003 -0.003 -0.003  0.097  0.022 -0.003  0.022  0.246  0.072  0.047  0.072  0.047 -0.028  0.022  0.022  0.022  0.072  0.146 -0.003 -0.028  0.022 -0.028 -0.028 
 0.100  0.025  0.025 -0.025  0.000 -0.025  0.000  0.050  0.025  0.000  0.972  0.025  0.000  0.025  0.025  0.050 -0.025  0.000 -0.025  0.000  0.000  0.050  0.000  0.025 -0.025  0.075  0.000  0.000  0.000  0.000  0.050  0.025  0.000  0.025  0.125  0.075  0.000  0.075  0.025 -0.025  0.025  0.025  0.000  0.050  0.149  0.000 -0.025  0.025 -0.025 -0.025 
 0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054 -0.020  0.004  1.001  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054 -0.020  0.004  1.001  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054 -0.020  0.004  1.001  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054 -0.020  0.004  1.001  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054 -0.020  0.004  1.001  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054 -0.020  0.004  1.001  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054 -0.020  0.004  1.001  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 0.029  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054 -0.020  0.004  1.001  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
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 0.488  0.364  0.264  0.239  0.414 -0.135  0.688 -0.010  0.364 -0.110  0.712 -0.184 -0.135 -0.035  0.364  0.015 -0.184 -0.209 -0.159 -0.010  0.015  0.289  0.015 -0.010  0.414  0.339 -0.010  0.040  0.065  0.513  0.015  0.438  0.364 -0.184  0.164  0.488  0.040  0.588  0.688  0.040 -0.035  0.115 -0.060  0.090  0.688 -0.110  0.015 -0.035 -0.110  0.015 
 0.508  0.359  0.234  0.359  0.433 -0.140  0.683 -0.015  0.384 -0.115  0.708 -0.164 -0.140 -0.040  0.359  0.010 -0.140 -0.189 -0.164 -0.015  0.010  0.284 -0.015  0.010  0.409  0.334 -0.015  0.060  0.060  0.508  0.060  0.433  0.334 -0.189  0.184  0.483  0.060  0.558  0.683  0.035 -0.040  0.110 -0.040  0.135  0.658 -0.140  0.010 -0.040 -0.090  0.010 
 0.506  0.357  0.282  0.382  0.456 -0.166  0.656 -0.042  0.382 -0.117  0.681 -0.166 -0.117 -0.042  0.332  0.008 -0.142 -0.191 -0.166 -0.017  0.008  0.307 -0.067  0.008  0.407  0.282  0.008  0.058  0.108  0.506  0.108  0.431  0.357 -0.216  0.207  0.456  0.058  0.556  0.681  0.033 -0.042  0.108 -0.042  0.133  0.656 -0.142  0.008 -0.017 -0.067  0.008 
 0.502  0.377  0.302  0.477  0.477 -0.171  0.626 -0.071  0.377 -0.121  0.626 -0.171 -0.121 -0.046  0.327  0.003 -0.071 -0.196 -0.171  0.003 -0.021  0.278 -0.071  0.003  0.402  0.203  0.053  0.078  0.103  0.527  0.128  0.427  0.352 -0.221  0.203  0.452  0.078  0.552  0.676  0.028 -0.021  0.128 -0.046  0.128  0.651 -0.146  0.003 -0.021 -0.071  0.003 
 0.504  0.379  0.280  0.504  0.479 -0.119  0.628 -0.069  0.379 -0.094  0.603 -0.169 -0.119 -0.044  0.329  0.005 -0.044 -0.194 -0.169  0.030 -0.019  0.280 -0.069  0.005  0.429  0.105  0.080  0.080  0.105  0.504  0.130  0.429  0.304 -0.244  0.155  0.454  0.080  0.554  0.703  0.030  0.005  0.130 -0.044  0.130  0.653 -0.144  0.005 -0.019 -0.094  0.005 
 0.526  0.376  0.301  0.501  0.476 -0.122  0.625 -0.072  0.376 -0.097  0.575 -0.172 -0.122 -0.047  0.326  0.052 -0.022 -0.197 -0.147  0.052 -0.022  0.277 -0.072  0.002  0.426  0.102  0.077  0.077  0.102  0.501  0.127  0.426  0.301 -0.222  0.152  0.451  0.077  0.575  0.700  0.027  0.002  0.127 -0.047  0.152  0.650 -0.147  0.002 -0.022 -0.122  0.002 
 0.524  0.374  0.374  0.499  0.474 -0.124  0.623 -0.074  0.374 -0.099  0.573 -0.174 -0.124 -0.049  0.324  0.050 -0.024 -0.199 -0.149  0.025 -0.024  0.275 -0.074  0.000  0.424  0.100  0.075  0.075  0.100  0.524  0.125  0.424  0.324 -0.224  0.150  0.449  0.075  0.573  0.698  0.025  0.000  0.125 -0.049  0.150  0.648 -0.149  0.000 -0.024 -0.099  0.000 
 0.523  0.374  0.374  0.498  0.473 -0.125  0.623 -0.100  0.374 -0.100  0.523 -0.149 -0.125 -0.050  0.324  0.050 -0.025 -0.199 -0.149  0.025 -0.025  0.274 -0.075  0.000  0.424  0.100  0.075  0.075  0.075  0.523  0.125  0.424  0.324 -0.199  0.174  0.424  0.075  0.573  0.698  0.025  0.000  0.125 -0.050  0.149  0.623 -0.149  0.000 -0.025 -0.100  0.000 
 0.400  0.350  0.375  0.450  0.450 -0.148  0.500 -0.073  0.276 -0.098  0.400 -0.098 -0.048 -0.023  0.300  0.026 -0.048 -0.148 -0.123  0.051 -0.023  0.300 -0.073  0.026  0.375  0.051  0.051  0.126  0.026  0.525  0.076  0.350  0.176 -0.198  0.126  0.375  0.101  0.475  0.599  0.001  0.001  0.101 -0.048  0.101  0.550 -0.073  0.001 -0.073 -0.098  0.051 
 0.344  0.269  0.344  0.219  0.294 -0.105  0.443 -0.005  0.219 -0.080  0.369 -0.055  0.020 -0.005  0.194  0.045 -0.055 -0.105 -0.055  0.070 -0.030  0.219 -0.030  0.070  0.319 -0.005 -0.005  0.120 -0.005  0.369  0.095  0.219  0.095 -0.130  0.095  0.294  0.070  0.319  0.518  0.070 -0.005 -0.030 -0.005  0.045  0.543 -0.005  0.095 -0.055 -0.080 -0.005 
 0.270  0.170  0.345  0.220  0.220 -0.079  0.370  0.021  0.195 -0.054  0.295 -0.029  0.021 -0.004  0.145  0.046 -0.054 -0.079 -0.054  0.046 -0.004  0.121 -0.004  0.071  0.345  0.021  0.021  0.121  0.021  0.370  0.096  0.220  0.021 -0.104  0.071  0.245  0.121  0.270  0.544  0.071 -0.004 -0.079 -0.004  0.021  0.444 -0.004 -0.004 -0.029 -0.079 -0.004 
 0.161  0.061  0.211  0.036  0.161 -0.063  0.261  0.036  0.086 -0.038  0.285  0.011  0.011 -0.038  0.111  0.036 -0.013 -0.038 -0.063  0.036 -0.013  0.086  0.011  0.111  0.360  0.061  0.036  0.086  0.011  0.285  0.061  0.211 -0.013 -0.063  0.061  0.136  0.111  0.136  0.485 -0.038  0.036 -0.038 -0.013  0.036  0.385 -0.013  0.011 -0.038 -0.063 -0.013 
 0.080  0.030  0.130  0.005  0.130 -0.044  0.205  0.030  0.005 -0.019  0.280  0.030 -0.019 -0.044  0.105  0.030  0.005 -0.019 -0.044  0.030 -0.019  0.080  0.030  0.055  0.180  0.080  0.005  0.030  0.030  0.180  0.005  0.130 -0.019 -0.044  0.055  0.130  0.080  0.055  0.354 -0.044  0.030 -0.019  0.005  0.005  0.205 -0.019  0.030 -0.044 -0.044  0.005 
 0.048 -0.001  0.023 -0.001  0.073 -0.026  0.123  0.023 -0.001 -0.001  0.248  0.048 -0.001 -0.026  0.073  0.023 -0.026  0.023 -0.026  0.023 -0.001  0.023  0.023  0.048  0.098  0.098  0.023  0.023 -0.001  0.148 -0.026  0.098 -0.001 -0.026  0.048  0.098  0.023  0.073  0.248 -0.026  0.048 -0.026  0.023  0.023  0.123 -0.001  0.048 -0.026 -0.026  0.023 
 0.033  0.008  0.008  0.008  0.033 -0.017  0.058  0.033 -0.017 -0.017  0.207  0.058  0.008 -0.017  0.058  0.008 -0.017  0.033 -0.017  0.008 -0.017  0.033 -0.017  0.033  0.058  0.033  0.033  0.033  0.008  0.083 -0.017  0.058  0.008 -0.017  0.033  0.033  0.008  0.033  0.133 -0.017  0.033 -0.017  0.008  0.033  0.083 -0.017  0.058 -0.017 -0.017  0.008 
-0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.021 -0.003 -0.003 -0.003  0.046  0.021 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.021 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.021 -0.003  0.021 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.046 -0.003  0.021 -0.003 -0.003  0.021 -0.003 -0.003  0.021 -0.003 -0.003 -0.003 
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 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.054  0.029 -0.020  0.004  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.004  0.029 -0.020  0.054  0.004  0.004 -0.020  0.004  0.029  0.004  0.004  0.004  0.029  0.079  0.004  0.054  0.054 -0.020  0.029  0.029 -0.020  0.029  0.129  0.004  0.004  0.004 -0.020 -0.020 
 0.997  0.001  0.001  0.001  0.001 -0.024  0.001  0.076  0.026 -0.024  0.001  0.001  0.001  0.026  0.001  0.026  0.001 -0.024 -0.024 -0.024  0.001  0.051  0.001  0.026 -0.024  0.051  0.051  0.001 -0.024  0.026  0.026  0.026  0.026  0.001  0.026  0.076  0.001  0.051  0.051 -0.024  0.051  0.051 -0.024  0.026  0.126  0.001  0.001  0.001 -0.024 -0.024 
 0.967  0.045  0.020  0.045 -0.005 -0.055 -0.005  0.045  0.095 -0.030 -0.030  0.020 -0.030  0.095  0.070 -0.005 -0.030 -0.030 -0.055  0.020  0.194  0.169  0.020  0.045  0.045  0.244  0.045  0.020 -0.030 -0.005  0.020  0.020  0.095 -0.030  0.070  0.070  0.020  0.120  0.144 -0.055  0.070  0.045 -0.030  0.020  0.369 -0.005 -0.030 -0.030 -0.030 -0.055 
 0.934  0.037  0.037  0.037 -0.037 -0.037  0.012  0.037  0.112  0.062  0.012  0.037  0.012  0.187  0.137 -0.012 -0.037 -0.062 -0.087 -0.012  0.212  0.212  0.037  0.037  0.037  0.336  0.087 -0.012 -0.062  0.012  0.037  0.112  0.112 -0.062  0.087  0.087  0.012  0.137  0.187 -0.087  0.112  0.062 -0.037  0.037  0.561  0.012 -0.037 -0.037  0.037 -0.037 
 0.862  0.065  0.115  0.065 -0.034 -0.059  0.265  0.090  0.240  0.090 -0.034  0.015 -0.009  0.289  0.165 -0.009 -0.109 -0.034 -0.109  0.040  0.265  0.514  0.040  0.065  0.090  0.613  0.065 -0.059 -0.084  0.165  0.040  0.140  0.140 -0.109  0.240  0.339  0.065  0.289  0.314 -0.084  0.115  0.115 -0.059  0.165  0.862 -0.009  0.040 -0.034  0.040 -0.034 
 0.820  0.022  0.197  0.022 -0.002 -0.077  0.396  0.172  0.296  0.072 -0.027  0.022 -0.052  0.247  0.172 -0.002 -0.127 -0.077 -0.127  0.047  0.296  0.595  0.022  0.072  0.122  0.695  0.072 -0.027 -0.027  0.222  0.022  0.222  0.147 -0.127  0.346  0.471  0.022  0.321  0.346 -0.052  0.072  0.172 -0.002  0.197  0.820 -0.052  0.022 -0.027  0.072 -0.052 
 0.773  0.175  0.250 -0.024  0.051 -0.124  0.624  0.126  0.425  0.175 -0.024  0.001 -0.074  0.175  0.225  0.026 -0.173 -0.124 -0.124  0.026  0.300  0.624  0.001  0.076  0.225  0.748  0.026  0.076 -0.074  0.300 -0.024  0.225  0.076 -0.148  0.425  0.574  0.001  0.400  0.474 -0.074  0.026  0.250  0.026  0.275  0.773 -0.049  0.051  0.026  0.051 -0.099 
 0.757  0.284  0.309 -0.015  0.085 -0.140  0.608  0.085  0.409  0.259 -0.040  0.010 -0.065  0.159  0.284  0.010 -0.140 -0.140 -0.140  0.010  0.334  0.608 -0.015  0.060  0.259  0.732  0.010  0.110 -0.090  0.284 -0.015  0.184  0.060 -0.140  0.409  0.608 -0.015  0.433  0.483 -0.090 -0.015  0.284  0.035  0.259  0.757 -0.065  0.110  0.060  0.085 -0.115 
 0.742  0.344  0.344  0.020  0.120 -0.080  0.593  0.070  0.344  0.394 -0.055 -0.030 -0.080  0.144  0.269 -0.005 -0.130 -0.130 -0.154 -0.055  0.294  0.593 -0.030  0.045  0.344  0.693  0.020  0.120 -0.130  0.319  0.045  0.169  0.045 -0.130  0.419  0.618  0.020  0.443  0.493 -0.055 -0.030  0.319  0.070  0.269  0.693 -0.080  0.095  0.144  0.070 -0.130 
 0.736  0.363  0.338  0.014  0.114 -0.086  0.587  0.064  0.338  0.462 -0.036 -0.036 -0.086  0.139  0.263 -0.011 -0.136 -0.136 -0.160 -0.061  0.288  0.537 -0.011  0.064  0.363  0.687  0.064  0.139 -0.160  0.363  0.089  0.213  0.064 -0.160  0.413  0.587  0.039  0.487  0.512 -0.061 -0.036  0.338  0.064  0.263  0.662 -0.061  0.089  0.139  0.039 -0.136 
 0.727  0.403  0.279  0.029  0.079 -0.120  0.577  0.079  0.328  0.577  0.104 -0.070 -0.020  0.129  0.254 -0.020 -0.095 -0.170 -0.170  0.004  0.279  0.503  0.004  0.129  0.403  0.553  0.079  0.154 -0.170  0.353  0.204  0.254  0.029 -0.170  0.403  0.577  0.079  0.453  0.528 -0.070  0.054  0.353  0.079  0.254  0.627 -0.020  0.079  0.154  0.029 -0.120 
 0.722  0.473  0.249  0.074  0.099 -0.100  0.572  0.074  0.323  0.597  0.199 -0.050  0.074  0.149  0.274 -0.050 -0.075 -0.175 -0.200  0.024  0.249  0.498 -0.000  0.149  0.398  0.523  0.024  0.124 -0.175  0.323  0.249  0.249 -0.000 -0.175  0.398  0.572  0.049  0.498  0.548 -0.075  0.099  0.323  0.099  0.249  0.597 -0.025  0.074  0.149  0.024 -0.125 
 0.713  0.489  0.265  0.190  0.090 -0.084  0.588  0.065  0.314  0.638  0.240 -0.059  0.115  0.140  0.265 -0.059 -0.084 -0.184 -0.209  0.015  0.265  0.489  0.015  0.140  0.414  0.489  0.015  0.140 -0.184  0.289  0.240  0.240 -0.059 -0.184  0.414  0.588  0.065  0.489  0.539  0.015  0.090  0.314  0.165  0.265  0.588 -0.034  0.065  0.165 -0.009 -0.134 
 0.705  0.505  0.256  0.206  0.107 -0.068  0.555  0.082  0.306  0.655  0.231 -0.043  0.181  0.156  0.256 -0.068 -0.068 -0.192 -0.217  0.007  0.256  0.480 -0.018  0.132  0.406  0.480  0.007  0.132 -0.192  0.256  0.256  0.181 -0.068 -0.192  0.406  0.580  0.057  0.480  0.555  0.007  0.107  0.306  0.231  0.256  0.580 -0.043  0.057  0.156 -0.018 -0.142 
 0.677  0.528  0.254  0.229  0.104 -0.045  0.553  0.079  0.353  0.602  0.229  0.029  0.254  0.129  0.254 -0.070 -0.070 -0.170 -0.195  0.029  0.254  0.478 -0.070  0.154  0.428  0.403 -0.020  0.129 -0.195  0.229  0.279  0.204 -0.070 -0.220  0.428  0.553  0.004  0.503  0.553  0.004  0.104  0.279  0.229  0.279  0.577 -0.020  0.054  0.154 -0.045 -0.145 
 0.621  0.496  0.222  0.222  0.098 -0.027  0.571  0.073  0.397  0.596  0.247  0.023  0.247  0.123  0.247 -0.077 -0.077 -0.176 -0.226  0.023  0.247  0.471 -0.077  0.147  0.446  0.347 -0.027  0.123 -0.201  0.222  0.322  0.197 -0.102 -0.201  0.422  0.546 -0.002  0.496  0.546 -0.002  0.123  0.247  0.247  0.247  0.571  0.048  0.048  0.172 -0.052 -0.151 
 0.617  0.467  0.218  0.243  0.094 -0.031  0.567  0.069  0.418  0.592  0.243  0.044  0.243  0.119  0.268 -0.106 -0.081 -0.180 -0.230  0.019  0.218  0.467 -0.081  0.143  0.442  0.293 -0.056  0.193 -0.205  0.168  0.318  0.168 -0.131 -0.205  0.418  0.492  0.019  0.492  0.517 -0.006  0.119  0.218  0.243  0.243  0.567  0.069  0.069  0.143 -0.056 -0.155 
 0.616  0.441  0.217  0.217  0.093 -0.032  0.541  0.068  0.417  0.591  0.267  0.118  0.242  0.043  0.267 -0.132 -0.082 -0.181 -0.256  0.018  0.217  0.441 -0.082  0.118  0.441  0.267 -0.032  0.192 -0.206  0.118  0.342  0.167 -0.156 -0.206  0.417  0.417  0.043  0.491  0.516  0.043  0.118  0.217  0.242  0.242  0.566  0.118  0.068  0.142 -0.032 -0.156 
 0.613  0.439  0.240  0.215  0.065 -0.034  0.539  0.040  0.414  0.564  0.265  0.140  0.215  0.015  0.265 -0.134 -0.084 -0.184 -0.284  0.015  0.215  0.464 -0.084  0.115  0.439  0.140 -0.034  0.215 -0.184  0.115  0.339  0.140 -0.159 -0.209  0.389  0.414  0.040  0.514  0.514  0.040  0.115  0.190  0.215  0.215  0.564  0.165  0.090  0.140 -0.084 -0.184 
 0.612  0.438  0.214  0.189  0.064 -0.035  0.538  0.039  0.388  0.563  0.264  0.164  0.214  0.064  0.239 -0.110 -0.035 -0.210 -0.284 -0.010  0.214  0.438 -0.085  0.114  0.438  0.114  0.039  0.189 -0.160  0.114  0.388  0.114 -0.160 -0.185  0.363  0.438  0.039  0.513  0.513  0.039  0.114  0.164  0.214  0.214  0.563  0.164  0.089  0.139 -0.085 -0.160 
 0.607  0.408  0.233  0.183  0.059 -0.041  0.507  0.034  0.383  0.557  0.258  0.158  0.208  0.059  0.258 -0.091 -0.041 -0.215 -0.290 -0.041  0.208  0.432 -0.066  0.084  0.432  0.109  0.084  0.183 -0.141  0.084  0.383  0.084 -0.190 -0.190  0.308  0.432  0.059  0.507  0.507  0.059  0.134  0.158  0.208  0.233  0.557  0.158  0.084  0.134 -0.091 -0.165 
 0.613  0.439  0.265  0.215  0.065 -0.059  0.414 -0.034  0.314  0.514  0.165 -0.009  0.240  0.065  0.215 -0.059 -0.034 -0.184 -0.259 -0.034  0.090  0.289 -0.009  0.065  0.364  0.140 -0.009  0.165 -0.109  0.115  0.265 -0.009 -0.184 -0.184  0.314  0.339 -0.034  0.489  0.339  0.090  0.065  0.190  0.040  0.190  0.539  0.090  0.015  0.165 -0.009 -0.109 
 0.588  0.314  0.190  0.115  0.015 -0.059  0.265 -0.009  0.190  0.414  0.065 -0.034  0.115  0.015  0.165 -0.034 -0.009 -0.109 -0.159 -0.009  0.065  0.265  0.040  0.040  0.265  0.115 -0.059  0.115 -0.084  0.115  0.265 -0.034 -0.134 -0.134  0.240  0.289 -0.009  0.439  0.215  0.065  0.065  0.165  0.065  0.215  0.414  0.140  0.040  0.165  0.015 -0.059 
 0.562  0.263  0.163  0.138 -0.011 -0.036  0.163 -0.011  0.188  0.362 -0.011 -0.011  0.088  0.013  0.138 -0.011  0.013 -0.086 -0.136 -0.011  0.038  0.238 -0.011  0.038  0.188  0.138 -0.061  0.038 -0.086  0.113  0.113 -0.011 -0.111 -0.111  0.188  0.213  0.013  0.462  0.138  0.063  0.038  0.113  0.013  0.213  0.362  0.088  0.063  0.163  0.013 -0.036 
 0.517  0.218  0.118  0.093  0.018 -0.056  0.068  0.018  0.143  0.317 -0.006 -0.006  0.093  0.018  0.143 -0.006  0.018 -0.056 -0.106  0.018 -0.031  0.193 -0.006  0.068  0.118  0.143 -0.056 -0.006 -0.056  0.093  0.093 -0.031 -0.081 -0.081  0.168  0.118 -0.006  0.392  0.043  0.043  0.068  0.118  0.043  0.193  0.193  0.118  0.018  0.043  0.043 -0.056 
 0.455  0.156  0.107  0.107  0.007 -0.043  0.032  0.032  0.057  0.306  0.007 -0.018  0.107  0.007  0.107 -0.018  0.032 -0.043 -0.093  0.032 -0.018  0.156  0.007  0.082  0.032  0.132 -0.018 -0.018 -0.043  0.057  0.082 -0.043 -0.068 -0.068  0.132  0.032  0.007  0.306  0.057  0.057  0.057  0.132  0.057  0.181  0.082  0.132  0.007  0.057  0.007 -0.068 
 0.351  0.052  0.127  0.127 -0.023 -0.023 -0.023  0.052  0.052  0.251 -0.023 -0.023  0.052  0.002  0.002 -0.023  0.002 -0.023 -0.073  0.002  0.002  0.102  0.027  0.077  0.027  0.127  0.002 -0.023 -0.023  0.027  0.052 -0.048 -0.073 -0.073  0.102 -0.023 -0.023  0.201  0.027  0.077 -0.023  0.151  0.052  0.176  0.077  0.151  0.002  0.002 -0.073 -0.048 
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 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 

 0.967 -0.029 -0.004  0.045  0.070 -0.004 -0.029 -0.029  0.045 -0.029  0.020 -0.029 -0.029  0.020 -0.004  0.020  0.020 -0.004  0.045 -0.004  0.020  0.045 -0.029 -0.004  0.020 -0.029 -0.004  0.020 -0.004 -0.029  0.020 -0.004  0.020 -0.029 -0.029  0.020 -0.029 -0.029 -0.004  0.020 -0.029  0.020 -0.029 -0.004 -0.004 -0.029 -0.004 -0.029 -0.029 -0.029 
 0.996 -0.025  0.000  0.050  0.075  0.000 -0.025 -0.025  0.025 -0.025  0.000 -0.025 -0.025  0.000  0.000 -0.025  0.000  0.000  0.050  0.000  0.025  0.050 -0.025  0.000  0.025 -0.025  0.025  0.025  0.000 -0.025  0.000  0.000  0.025 -0.025  0.000  0.025 -0.025  0.000  0.000  0.025 -0.025  0.025 -0.025  0.025 -0.025 -0.025  0.000 -0.025 -0.025 -0.025 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.001 -0.020 -0.020  0.029  0.054  0.004 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.054  0.004  0.029  0.029 -0.020  0.004  0.029 -0.020  0.029  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020  0.004  0.029 -0.020  0.004  0.004  0.029 -0.020  0.029 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 
 1.000 -0.021 -0.021  0.054  0.054  0.004 -0.021 -0.021  0.029 -0.021  0.004 -0.021 -0.021  0.004  0.004 -0.021  0.004 -0.021  0.079  0.004  0.029  0.029 -0.021  0.004  0.029 -0.021  0.029  0.029  0.004 -0.021  0.004  0.004  0.029 -0.021  0.004  0.029 -0.021  0.004  0.004  0.029 -0.021  0.029 -0.021  0.029 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021 
 1.000 -0.021 -0.021  0.054  0.054  0.004 -0.021 -0.021  0.029 -0.021  0.004 -0.021 -0.021  0.004  0.004 -0.021  0.004 -0.021  0.079  0.004  0.029  0.029 -0.021  0.004  0.029 -0.021  0.029  0.029  0.004 -0.021  0.004  0.004  0.029 -0.021  0.004  0.029 -0.021  0.004  0.004  0.029 -0.021  0.029 -0.021  0.029 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021 
 1.000 -0.021 -0.021  0.053  0.053  0.003 -0.021 -0.021  0.028 -0.021  0.003 -0.021 -0.021  0.003  0.003 -0.021  0.003 -0.021  0.078  0.003  0.028  0.028 -0.021  0.003  0.028 -0.021  0.028  0.028  0.003 -0.021  0.003  0.003  0.028 -0.021  0.003  0.028 -0.021  0.003  0.003  0.028 -0.021  0.028 -0.021  0.028 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021 
 0.999 -0.022 -0.022  0.053  0.053  0.003 -0.022 -0.022  0.053 -0.022  0.003 -0.022 -0.022  0.003  0.003 -0.022  0.003 -0.022  0.078  0.003  0.028  0.028 -0.022  0.028  0.028 -0.022  0.028  0.028  0.003 -0.022  0.003  0.003  0.028 -0.022  0.003  0.028 -0.022  0.003  0.028  0.028 -0.022  0.028 -0.022  0.028 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022 
 0.995 -0.026 -0.026  0.074  0.074 -0.001 -0.026 -0.026  0.049 -0.026 -0.001 -0.026 -0.026 -0.001 -0.001 -0.026 -0.001 -0.026  0.074 -0.001  0.024  0.049 -0.026  0.024  0.024 -0.026  0.049  0.024 -0.001 -0.026 -0.001 -0.001  0.024 -0.026 -0.001  0.024 -0.026 -0.001  0.024  0.024 -0.026  0.024 -0.026  0.024 -0.026 -0.026 -0.001 -0.026 -0.026 -0.026 
 0.988 -0.034  0.016  0.091  0.066 -0.009 -0.034  0.016  0.066 -0.009 -0.009 -0.034 -0.034 -0.009  0.016 -0.009 -0.009 -0.034  0.091 -0.009  0.016  0.041 -0.034  0.016  0.016 -0.034  0.041  0.016 -0.009 -0.009 -0.009 -0.009  0.016 -0.034 -0.009  0.016 -0.034 -0.009  0.016  0.016 -0.034  0.041 -0.034  0.041 -0.034 -0.009 -0.009 -0.034 -0.034 -0.009 
 0.976 -0.020  0.029  0.129  0.104 -0.020 -0.020  0.029  0.054 -0.020 -0.020 -0.045 -0.045 -0.020  0.004  0.004  0.004 -0.045  0.079 -0.020  0.029  0.079  0.004  0.004  0.004 -0.045  0.054  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.045 -0.020  0.004 -0.020  0.004  0.029  0.004 -0.020  0.079 -0.020  0.079 -0.020  0.004  0.004 -0.045 -0.045 -0.020 
 0.945 -0.051  0.073  0.198  0.073 -0.026 -0.001  0.048  0.048 -0.001 -0.051 -0.051 -0.051 -0.026  0.023  0.023 -0.026 -0.026  0.098 -0.051  0.098  0.123 -0.001  0.023 -0.026  0.023  0.073 -0.026  0.123 -0.026 -0.051 -0.001  0.023 -0.051 -0.051 -0.001 -0.026  0.023  0.048 -0.001 -0.026  0.048 -0.051  0.098 -0.026 -0.001 -0.026 -0.051 -0.076  0.048 
 0.906 -0.041  0.034  0.308  0.059 -0.041 -0.016  0.084  0.034 -0.016 -0.091 -0.091 -0.066  0.034  0.059 -0.016  0.034 -0.016  0.109  0.009  0.084  0.183 -0.041  0.059  0.009  0.059  0.109 -0.066  0.258  0.009 -0.091 -0.041  0.109 -0.091 -0.066  0.009 -0.066 -0.016  0.059 -0.066 -0.066  0.034 -0.066  0.134  0.009  0.034 -0.066 -0.066 -0.116  0.009 
 0.848 -0.024  0.125  0.449  0.050 -0.024  0.000  0.075  0.025 -0.024 -0.124 -0.149 -0.074  0.050  0.000 -0.049  0.075  0.000  0.125  0.000  0.050  0.225 -0.049  0.075  0.000  0.100  0.100 -0.099  0.250  0.050 -0.124 -0.024  0.125 -0.124 -0.124  0.025 -0.149 -0.024  0.000 -0.024 -0.124  0.050 -0.124  0.175 -0.049  0.000 -0.049 -0.124 -0.099  0.025 
 0.825 -0.047  0.177  0.551  0.102  0.002  0.027  0.052  0.002 -0.022 -0.147 -0.147 -0.022  0.077  0.027 -0.072  0.077  0.027  0.102  0.027  0.027  0.252 -0.047  0.052 -0.022  0.127  0.077 -0.122  0.227  0.177 -0.122  0.027  0.127 -0.147 -0.147  0.027 -0.147 -0.022  0.052 -0.022 -0.147  0.027 -0.147  0.127 -0.022 -0.022 -0.022 -0.172 -0.097  0.027 
 0.761 -0.061  0.163  0.661  0.113  0.038  0.013  0.013 -0.011 -0.011 -0.186 -0.136 -0.011  0.063  0.038 -0.086  0.038 -0.011  0.088  0.013 -0.011  0.312 -0.011  0.063 -0.011  0.113  0.038 -0.161  0.163  0.188 -0.136  0.138  0.138 -0.161 -0.186 -0.011 -0.161  0.038  0.063 -0.061 -0.186  0.038 -0.186  0.113 -0.011 -0.061 -0.061 -0.161 -0.086  0.038 
 0.726 -0.071  0.153  0.626  0.153  0.028  0.028  0.003 -0.021  0.003 -0.221 -0.121  0.003  0.053  0.028 -0.096  0.028  0.053  0.078  0.028  0.003  0.302  0.003  0.028  0.028  0.128  0.028 -0.146  0.153  0.178 -0.146  0.178  0.153 -0.171 -0.196 -0.021 -0.121  0.028  0.053 -0.021 -0.196  0.028 -0.196  0.103 -0.021 -0.071 -0.046 -0.171 -0.096  0.028 
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 0.673 -0.074  0.125  0.499  0.150  0.000  0.025 -0.024 -0.024 -0.074 -0.249 -0.099  0.025  0.050  0.025 -0.124  0.050  0.100  0.075  0.000 -0.024  0.250  0.025 -0.024  0.050  0.100  0.000 -0.099  0.125  0.250 -0.124  0.324  0.175 -0.199 -0.224 -0.024 -0.099  0.000  0.050 -0.024 -0.199 -0.024 -0.149  0.025  0.000 -0.099 -0.074 -0.174 -0.074  0.050 
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 0.537 -0.160  0.089  0.163  0.064 -0.111 -0.086 -0.111 -0.136 -0.136 -0.210 -0.086  0.064 -0.061 -0.111 -0.111  0.114  0.039  0.089 -0.111  0.014  0.039  0.064 -0.061  0.064 -0.036 -0.036 -0.086  0.089  0.338 -0.136  0.263  0.263 -0.136 -0.185 -0.036 -0.061 -0.011 -0.036 -0.036 -0.185 -0.011 -0.086 -0.011 -0.061 -0.111  0.064 -0.210 -0.111  0.014 
 0.391 -0.082  0.067  0.092 -0.007 -0.082 -0.057 -0.082 -0.132 -0.057 -0.132 -0.007  0.042 -0.057 -0.082 -0.032  0.042 -0.032  0.042 -0.057  0.042  0.042  0.042 -0.007  0.042 -0.007 -0.007 -0.032  0.017  0.291 -0.107  0.192  0.167 -0.082 -0.132 -0.007 -0.007 -0.032 -0.032 -0.032 -0.107 -0.007 -0.082 -0.007  0.017 -0.132  0.017 -0.157 -0.082  0.067 
 0.263 -0.086  0.038  0.038  0.013 -0.061 -0.036 -0.061 -0.111 -0.036 -0.136  0.013  0.038 -0.036 -0.061 -0.036  0.013 -0.061  0.063 -0.061  0.063  0.038  0.063 -0.011  0.013  0.013  0.013 -0.036  0.013  0.312 -0.111  0.188  0.163 -0.111 -0.111  0.013  0.013 -0.036 -0.011 -0.011 -0.086  0.013 -0.086  0.013  0.038 -0.111  0.038 -0.136 -0.061  0.088 
 0.091 -0.059  0.016  0.066 -0.034 -0.034 -0.009 -0.034 -0.109 -0.009 -0.109  0.041  0.016 -0.009 -0.034 -0.009  0.016 -0.034  0.066 -0.059  0.066  0.016  0.016 -0.009 -0.009  0.016  0.016 -0.009  0.016  0.240 -0.109  0.215  0.041 -0.084 -0.084 -0.034  0.041 -0.009 -0.009 -0.059 -0.059 -0.059 -0.084  0.066  0.041 -0.084  0.016 -0.109 -0.034 -0.009 
 0.077 -0.047  0.027  0.102 -0.047 -0.022  0.002 -0.022 -0.097 -0.022 -0.097  0.077  0.027  0.002 -0.047 -0.022 -0.047 -0.047  0.052 -0.047  0.027  0.002  0.027 -0.022  0.002  0.027  0.052 -0.022  0.027  0.152 -0.097  0.177  0.002 -0.072 -0.047 -0.047  0.027  0.027  0.002 -0.072 -0.047 -0.072 -0.072  0.077  0.002 -0.072  0.027 -0.097 -0.022 -0.022 
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-0.060 -0.010 -0.035 -0.010 -0.060 -0.010  0.014  0.014 -0.060 -0.010 -0.060 -0.035 -0.035 -0.010  0.039 -0.010 -0.010 -0.035  0.064 -0.035 -0.010 -0.010 -0.035  0.039 -0.010  0.014  0.014 -0.060  0.089  0.039 -0.060  0.039 -0.035 -0.060 -0.035 -0.010 -0.035 -0.010  0.014 -0.060 -0.035 -0.060 -0.010  0.089  0.014 -0.060 -0.010 -0.010  0.014 -0.010 
-0.053 -0.003 -0.028 -0.003 -0.053 -0.003 -0.003  0.022 -0.053 -0.003 -0.053 -0.028 -0.028 -0.003  0.047 -0.003 -0.003 -0.028  0.072 -0.028  0.022 -0.028 -0.028  0.047 -0.003 -0.053 -0.003 -0.053  0.072  0.022 -0.053  0.022 -0.028 -0.053 -0.028 -0.003 -0.028 -0.028  0.022 -0.053 -0.028 -0.053 -0.003  0.072  0.022 -0.053 -0.028 -0.003  0.022 -0.003 
-0.027 -0.002 -0.027 -0.002 -0.027 -0.002 -0.002  0.022 -0.052 -0.002 -0.052 -0.027 -0.027 -0.002  0.047 -0.002 -0.002 -0.027  0.072 -0.027  0.022 -0.027 -0.027  0.047 -0.002 -0.052 -0.002 -0.052  0.072  0.022 -0.052  0.022 -0.027 -0.052 -0.027 -0.002 -0.027 -0.027  0.022 -0.052 -0.027 -0.052 -0.002  0.072  0.022 -0.052 -0.027 -0.002  0.022 -0.002 
-0.025 -0.000 -0.025 -0.000 -0.025 -0.000 -0.000  0.024 -0.050 -0.000 -0.050 -0.025 -0.025 -0.025  0.049 -0.000 -0.000 -0.025  0.074 -0.025  0.024 -0.050 -0.025  0.049 -0.000 -0.050 -0.000 -0.050  0.074  0.024 -0.050  0.024 -0.025 -0.050 -0.025 -0.000 -0.025 -0.025  0.024 -0.050 -0.025 -0.050 -0.000  0.074  0.024 -0.050 -0.025 -0.025 -0.000 -0.000 
-0.024  0.000 -0.024  0.000 -0.024  0.000  0.000  0.025 -0.049  0.000 -0.049 -0.024 -0.024 -0.024  0.050  0.000  0.000 -0.024  0.075 -0.024  0.025 -0.049 -0.024  0.050  0.000 -0.049  0.000 -0.049  0.075  0.025 -0.049  0.025 -0.024 -0.049 -0.024  0.000 -0.024 -0.024  0.025 -0.049 -0.024 -0.049  0.000  0.075  0.025 -0.049 -0.024 -0.024 -0.024  0.000 
-0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.029 -0.045  0.004 -0.045 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.054 -0.020  0.029 -0.045 -0.045  0.054  0.004 -0.045  0.004 -0.045  0.054  0.004 -0.045  0.029 -0.045 -0.045 -0.020  0.004 -0.020 -0.020  0.029 -0.045 -0.020 -0.045  0.004  0.054  0.029 -0.045 -0.020 -0.045 -0.020  0.004 
-0.017  0.007 -0.017  0.007 -0.017 -0.017  0.007  0.032 -0.042  0.007 -0.042 -0.017 -0.017 -0.017  0.032  0.007  0.007 -0.017  0.057 -0.017  0.032 -0.042 -0.042  0.057  0.007 -0.042  0.007 -0.042  0.032  0.007 -0.042  0.032 -0.042 -0.042 -0.017  0.007 -0.017 -0.017  0.032 -0.042 -0.017 -0.042  0.007  0.057  0.032 -0.042 -0.017 -0.042 -0.017  0.007 
-0.016  0.009 -0.016  0.009 -0.016 -0.016  0.009  0.034 -0.041  0.009 -0.041 -0.016 -0.016 -0.016  0.034  0.009  0.009 -0.016  0.059 -0.016  0.034 -0.041 -0.041  0.059  0.009 -0.041  0.009 -0.041  0.034 -0.016 -0.041  0.034 -0.041 -0.041 -0.016  0.009 -0.016 -0.016  0.009 -0.041 -0.016 -0.041  0.009  0.059  0.034 -0.041 -0.016 -0.041 -0.041  0.009 
-0.016  0.009 -0.016  0.009 -0.016 -0.016  0.009  0.034 -0.041  0.009 -0.041 -0.016 -0.016 -0.016  0.034  0.009  0.009 -0.016  0.059 -0.016  0.034 -0.041 -0.041  0.059  0.009 -0.041  0.009 -0.041  0.034 -0.016 -0.041  0.034 -0.041 -0.041 -0.016  0.009 -0.016 -0.016  0.009 -0.041 -0.016 -0.041  0.009  0.059  0.034 -0.041 -0.016 -0.041 -0.041  0.009 
-0.016  0.009 -0.016  0.009 -0.016 -0.016  0.009  0.034 -0.041  0.009 -0.041 -0.016 -0.016 -0.016  0.034  0.009  0.009 -0.016  0.059 -0.016  0.034 -0.041 -0.041  0.059  0.009 -0.041  0.009 -0.041  0.034 -0.016 -0.041  0.034 -0.041 -0.041 -0.016  0.009 -0.016 -0.016  0.009 -0.041 -0.016 -0.041  0.009  0.059  0.034 -0.041 -0.016 -0.041 -0.041  0.009 
 0.037 -0.012 -0.037  0.062 -0.037 -0.037  0.012  0.037 -0.037  0.012 -0.062 -0.037 -0.037 -0.012  0.012 -0.012  0.012  0.037  0.087 -0.012  0.037 -0.037 -0.037  0.037  0.012 -0.062 -0.012 -0.062  0.012  0.037 -0.062  0.087 -0.012 -0.037 -0.037  0.012  0.037 -0.037 -0.012 -0.037 -0.037 -0.037 -0.012  0.087  0.012 -0.062 -0.037 -0.062 -0.062  0.012 
 0.066 -0.033 -0.058  0.091 -0.058 -0.033 -0.033  0.016 -0.083 -0.033 -0.108 -0.058  0.066 -0.008  0.016 -0.083 -0.058  0.016  0.141 -0.008 -0.033  0.016 -0.033  0.016  0.041  0.041 -0.033 -0.133  0.066  0.141 -0.108  0.191  0.016 -0.083 -0.083 -0.033 -0.033 -0.083  0.041 -0.058 -0.008 -0.033 -0.083  0.166 -0.008 -0.133 -0.008 -0.108 -0.033  0.041 
 0.143 -0.031 -0.056  0.119 -0.031 -0.006 -0.031 -0.006 -0.056 -0.056 -0.155 -0.081  0.069 -0.006 -0.006 -0.106 -0.081 -0.006  0.143  0.044  0.069  0.044 -0.056 -0.031  0.069  0.069 -0.081 -0.131  0.168  0.293 -0.155  0.293  0.044 -0.131 -0.106 -0.006 -0.031 -0.056  0.019 -0.081 -0.056 -0.081 -0.131  0.094 -0.056 -0.106  0.019 -0.081 -0.056  0.044 
 0.213 -0.086 -0.086  0.089 -0.011 -0.061 -0.086  0.039 -0.086 -0.111 -0.210 -0.136  0.089 -0.061 -0.061 -0.086 -0.061 -0.036  0.114 -0.011  0.089  0.089 -0.086 -0.086  0.163  0.039 -0.111 -0.160  0.139  0.363 -0.210  0.313  0.163 -0.185 -0.185 -0.036 -0.086 -0.111 -0.011 -0.111 -0.061 -0.111 -0.086  0.064 -0.036 -0.111  0.064 -0.111 -0.011  0.089 
 0.196 -0.128 -0.103  0.071 -0.028 -0.053 -0.128  0.046 -0.053 -0.128 -0.228 -0.153  0.121 -0.078 -0.053 -0.103 -0.053  0.021  0.096  0.046  0.096  0.071 -0.103 -0.078  0.196  0.071 -0.128 -0.153  0.171  0.345 -0.228  0.320  0.196 -0.178 -0.203 -0.028 -0.103 -0.103 -0.028 -0.053 -0.078 -0.128 -0.103  0.071 -0.053 -0.128  0.046 -0.128 -0.053  0.096 
 0.247 -0.151 -0.077  0.073 -0.027 -0.077 -0.151  0.048 -0.077 -0.176 -0.226 -0.176  0.098 -0.077 -0.052 -0.127 -0.027  0.048  0.098 -0.002  0.123  0.098 -0.127 -0.052  0.247  0.048 -0.127 -0.176  0.172  0.322 -0.226  0.322  0.222 -0.176 -0.201 -0.027 -0.127 -0.127 -0.052 -0.077 -0.077 -0.102 -0.102  0.048 -0.102 -0.127  0.023 -0.127 -0.052  0.098 
 0.262 -0.137 -0.087  0.088 -0.062 -0.062 -0.137  0.038 -0.112 -0.186 -0.236 -0.186  0.088 -0.137 -0.062 -0.137 -0.012  0.038  0.088 -0.037  0.113  0.113 -0.087 -0.062  0.262  0.038 -0.137 -0.186  0.113  0.337 -0.236  0.312  0.212 -0.137 -0.211 -0.062 -0.137 -0.137 -0.037 -0.087 -0.087 -0.087 -0.112  0.038 -0.137 -0.137 -0.012 -0.137 -0.037  0.113 
 0.258 -0.116 -0.091  0.083 -0.066 -0.066 -0.166  0.033 -0.116 -0.216 -0.241 -0.191  0.008 -0.141 -0.091 -0.141  0.008  0.033  0.083 -0.041  0.108  0.108 -0.091 -0.066  0.258  0.033 -0.141 -0.191  0.083  0.307 -0.241  0.283  0.233 -0.116 -0.216 -0.091 -0.141 -0.141 -0.041 -0.091 -0.091 -0.091 -0.116  0.033 -0.141 -0.141 -0.016 -0.166 -0.041  0.108 
 0.251 -0.098 -0.098  0.077 -0.073 -0.073 -0.172  0.052 -0.123 -0.222 -0.247 -0.197  0.002 -0.147 -0.098 -0.147 -0.023  0.052  0.077 -0.048  0.102  0.102 -0.098 -0.073  0.251  0.027 -0.147 -0.197  0.077  0.301 -0.247  0.276  0.226 -0.098 -0.197 -0.098 -0.147 -0.098 -0.023 -0.098 -0.098 -0.098 -0.123  0.027 -0.147 -0.147 -0.023 -0.172 -0.048  0.127 
 0.222 -0.102 -0.127  0.122 -0.077 -0.077 -0.152  0.047 -0.127 -0.227 -0.227 -0.202 -0.027 -0.152 -0.102 -0.152 -0.027  0.097  0.047 -0.052  0.097  0.072 -0.152 -0.077  0.247  0.022 -0.152 -0.202  0.072  0.296 -0.252  0.272  0.197 -0.102 -0.202 -0.102 -0.152 -0.102 -0.052 -0.102 -0.052 -0.152 -0.102 -0.002 -0.127 -0.102 -0.027 -0.127 -0.077  0.122 
 0.220 -0.079 -0.129  0.121 -0.079 -0.054 -0.153  0.046 -0.129 -0.228 -0.228 -0.203 -0.029 -0.153 -0.129 -0.153 -0.029  0.096  0.021 -0.054  0.096  0.071 -0.153 -0.054  0.245  0.021 -0.153 -0.203  0.071  0.295 -0.253  0.270  0.245 -0.079 -0.203 -0.104 -0.153 -0.104 -0.054 -0.129 -0.029 -0.153 -0.104 -0.029 -0.129 -0.104 -0.029 -0.129 -0.104  0.121 
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 0.022 -0.103 -0.028  0.146 -0.028 -0.152 -0.053 -0.078 -0.177 -0.152 -0.177 -0.103 -0.053 -0.202 -0.152 -0.103  0.022 -0.053 -0.003 -0.028  0.047 -0.003 -0.028 -0.028  0.047 -0.128 -0.128 -0.128 -0.103  0.221 -0.227  0.321  0.171  0.047 -0.152 -0.128 -0.078 -0.053 -0.028 -0.152 -0.003 -0.103 -0.128 -0.053 -0.103 -0.103  0.146 -0.103  0.022  0.022 
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-0.053 -0.078 -0.078  0.221 -0.078  0.022 -0.053 -0.053 -0.078 -0.028 -0.078 -0.028 -0.003 -0.003 -0.028 -0.053 -0.028  0.022  0.072 -0.053 -0.003 -0.028  0.022  0.022 -0.003 -0.028 -0.028 -0.028 -0.053  0.122 -0.078  0.271 -0.003 -0.028 -0.078 -0.053  0.022  0.022 -0.003 -0.053  0.022 -0.078 -0.053  0.047 -0.003 -0.078  0.022 -0.053  0.022 -0.003 
-0.046 -0.071 -0.071  0.203 -0.071  0.003 -0.046 -0.046 -0.071 -0.021 -0.071 -0.021 -0.021  0.003 -0.021 -0.046 -0.021  0.028  0.078 -0.021  0.003  0.003  0.028  0.053 -0.046 -0.021 -0.021 -0.021 -0.046  0.103 -0.071  0.253  0.003 -0.021 -0.071 -0.046  0.028  0.003  0.003 -0.046  0.028 -0.071 -0.046  0.053  0.003 -0.071  0.028 -0.021  0.028 -0.021 
-0.043 -0.068 -0.068  0.131 -0.068  0.006 -0.043 -0.043 -0.068 -0.043 -0.068  0.006 -0.043  0.006 -0.018 -0.043  0.006  0.031  0.081 -0.018  0.006 -0.018  0.031  0.031 -0.043 -0.018  0.006 -0.043 -0.043  0.081 -0.068  0.231  0.006 -0.018 -0.043 -0.043 -0.018  0.031  0.006 -0.043  0.031 -0.068 -0.043  0.031  0.006 -0.068  0.006 -0.018  0.031 -0.018 
-0.060 -0.060 -0.060  0.090 -0.060 -0.010 -0.035 -0.035 -0.060 -0.060 -0.060  0.015 -0.010  0.015  0.015 -0.035 -0.010  0.040  0.040 -0.010  0.015  0.015  0.040  0.015 -0.035  0.040  0.015 -0.035 -0.035  0.090 -0.060  0.189 -0.035 -0.010 -0.035 -0.035 -0.035  0.015  0.015 -0.035  0.015 -0.060 -0.060  0.040  0.015 -0.060  0.015 -0.010  0.040 -0.010 
-0.055 -0.030 -0.055  0.070 -0.055 -0.005 -0.030 -0.030 -0.055 -0.055 -0.055  0.020 -0.005  0.020  0.045 -0.030 -0.005  0.020  0.020 -0.005  0.020  0.020  0.045  0.020 -0.005  0.020 -0.005 -0.030 -0.030  0.095 -0.055  0.169 -0.030 -0.005 -0.030 -0.030 -0.030  0.045  0.020 -0.030 -0.005 -0.055 -0.055  0.045  0.020 -0.055 -0.005 -0.005  0.045 -0.030 
-0.047 -0.022 -0.047  0.052 -0.047  0.002 -0.047 -0.022 -0.047 -0.047 -0.047 -0.022 -0.022  0.002  0.052 -0.022  0.002  0.027  0.027 -0.022  0.002  0.052  0.002  0.027  0.002  0.027  0.002 -0.022 -0.022  0.077 -0.047  0.102 -0.022 -0.022 -0.022 -0.022 -0.022  0.027  0.002 -0.022 -0.022 -0.047 -0.022  0.052  0.002 -0.047 -0.022  0.002  0.052 -0.022 
-0.023  0.001 -0.048  0.051 -0.048  0.001 -0.048 -0.023 -0.048 -0.048 -0.048 -0.023 -0.023  0.026  0.051 -0.023  0.001  0.026  0.026 -0.023  0.026  0.051  0.001  0.001  0.001  0.026  0.001 -0.023 -0.023  0.076 -0.048  0.101 -0.023 -0.023 -0.023 -0.023 -0.023  0.001  0.001 -0.023 -0.023 -0.048 -0.023  0.051  0.001 -0.023 -0.023  0.001  0.051 -0.023 
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-0.022  0.003 -0.047  0.028 -0.047  0.003 -0.047 -0.022 -0.047 -0.047 -0.047 -0.022 -0.022  0.028  0.053 -0.022  0.003  0.028  0.028 -0.022  0.028  0.028  0.003  0.003  0.003  0.028  0.003 -0.047 -0.022  0.053 -0.047  0.028  0.003 -0.022  0.003 -0.022 -0.022  0.003  0.003 -0.022 -0.022 -0.047 -0.022  0.053 -0.022 -0.022 -0.022  0.003  0.028 -0.022 
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 0.014 -0.010 -0.060  0.089 -0.085 -0.010 -0.060 -0.060 -0.010 -0.085 -0.085 -0.060 -0.035  0.064  0.014 -0.010 -0.010  0.064  0.014 -0.010 -0.010  0.114 -0.010 -0.035 -0.010  0.039 -0.010 -0.085 -0.035  0.139 -0.085  0.139  0.039 -0.060  0.014 -0.060 -0.060 -0.010 -0.035 -0.060 -0.035 -0.085 -0.060  0.064 -0.035 -0.060 -0.060 -0.010  0.064 -0.035 
 0.072 -0.077 -0.102  0.122 -0.152 -0.027 -0.102 -0.077 -0.077 -0.102 -0.127 -0.127 -0.002 -0.002 -0.052 -0.002 -0.002  0.047  0.022 -0.002 -0.052  0.172 -0.052 -0.027 -0.002 -0.002  0.022 -0.102 -0.052  0.296 -0.152  0.222  0.122 -0.052 -0.002 -0.102 -0.052 -0.052 -0.102 -0.102 -0.052 -0.127 -0.077  0.047 -0.077 -0.027 -0.052 -0.027  0.097 -0.052 
 0.158 -0.116 -0.066  0.083 -0.141 -0.016 -0.091 -0.066 -0.091 -0.141 -0.166 -0.141  0.008 -0.066 -0.091  0.008  0.033  0.058  0.033  0.058 -0.016  0.158 -0.066 -0.041 -0.016 -0.041  0.058 -0.141 -0.091  0.332 -0.191  0.258  0.208 -0.091 -0.041 -0.141 -0.066 -0.041 -0.091 -0.141 -0.066 -0.116 -0.066  0.033 -0.091 -0.041 -0.016 -0.016  0.083  0.008 
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 0.253 -0.121 -0.071  0.003  0.003 -0.096 -0.071 -0.046 -0.021 -0.221 -0.196 -0.121  0.103 -0.171 -0.096 -0.071  0.003  0.128  0.003  0.153  0.003  0.228  0.003 -0.046 -0.021  0.003  0.003 -0.121 -0.046  0.477 -0.271  0.228  0.302 -0.146 -0.096 -0.121 -0.071 -0.096 -0.021 -0.146 -0.071 -0.121 -0.071 -0.046 -0.121 -0.096 -0.046 -0.021  0.028  0.028 
 0.379 -0.095 -0.095  0.005  0.005 -0.095 -0.095 -0.020 -0.045 -0.219 -0.219 -0.144  0.080 -0.194 -0.095 -0.045 -0.020  0.105  0.005  0.130  0.055  0.204  0.005 -0.045  0.030 -0.020  0.030 -0.144  0.030  0.453 -0.294  0.229  0.304 -0.095 -0.095 -0.120 -0.095 -0.120 -0.020 -0.144 -0.045 -0.120 -0.095 -0.070 -0.120 -0.120 -0.020 -0.020  0.005  0.130 
 0.376 -0.098 -0.098  0.027 -0.023 -0.098 -0.098 -0.023 -0.048 -0.222 -0.222 -0.147  0.077 -0.197 -0.098 -0.073 -0.023  0.127  0.002  0.127  0.052  0.201  0.002  0.002  0.027 -0.048  0.027 -0.147  0.027  0.426 -0.297  0.251  0.301 -0.098 -0.098 -0.098 -0.098 -0.123  0.002 -0.172 -0.023 -0.123 -0.098 -0.073 -0.123 -0.123 -0.023  0.027  0.002  0.151 
 0.396 -0.103 -0.103  0.022 -0.003 -0.103 -0.152 -0.028 -0.028 -0.227 -0.227 -0.202  0.047 -0.202 -0.103 -0.078 -0.028  0.122 -0.003  0.122  0.072  0.196 -0.003 -0.003  0.072 -0.053 -0.003 -0.152  0.022  0.371 -0.302  0.246  0.296 -0.103 -0.128 -0.078 -0.103 -0.152 -0.003 -0.177 -0.028 -0.128 -0.078 -0.078 -0.128 -0.128 -0.003  0.022 -0.003  0.171 
 0.396 -0.102 -0.102  0.022 -0.027 -0.102 -0.152 -0.027 -0.027 -0.227 -0.227 -0.202  0.047 -0.202 -0.102 -0.077 -0.027  0.122 -0.002  0.122  0.072  0.172 -0.027 -0.002  0.047 -0.077 -0.002 -0.152  0.022  0.371 -0.301  0.247  0.296 -0.102 -0.127 -0.102 -0.102 -0.127 -0.002 -0.177 -0.027 -0.127 -0.077 -0.077 -0.102 -0.102 -0.002  0.022 -0.002  0.172 
 0.343 -0.081 -0.081  0.019 -0.056 -0.106 -0.155 -0.006 -0.031 -0.230 -0.230 -0.205  0.044 -0.205 -0.106 -0.081 -0.031  0.119 -0.006  0.094  0.094  0.143 -0.031 -0.031  0.044 -0.056 -0.006 -0.155  0.019  0.368 -0.305  0.268  0.243 -0.106 -0.155 -0.106 -0.106 -0.106  0.019 -0.205 -0.031 -0.131 -0.081 -0.081 -0.106 -0.106 -0.006  0.019  0.019  0.168 
 0.314 -0.084 -0.084  0.040 -0.059 -0.134 -0.159 -0.009 -0.034 -0.234 -0.234 -0.209  0.040 -0.184 -0.109 -0.059 -0.034  0.090 -0.034  0.065  0.090  0.140 -0.034 -0.034  0.040 -0.059 -0.009 -0.159  0.015  0.364 -0.308  0.339  0.240 -0.084 -0.159 -0.109 -0.109 -0.109  0.015 -0.209 -0.059 -0.159 -0.059 -0.084 -0.109 -0.109 -0.009  0.015  0.040  0.165 
 0.285 -0.089 -0.064  0.036 -0.039 -0.163 -0.114 -0.014 -0.089 -0.238 -0.238 -0.213  0.036 -0.163 -0.114 -0.064 -0.039  0.086 -0.039  0.061  0.086  0.136 -0.064 -0.064  0.036 -0.064 -0.014 -0.163 -0.014  0.360 -0.313  0.360  0.235 -0.064 -0.163 -0.089 -0.114 -0.114 -0.014 -0.213 -0.064 -0.188 -0.064 -0.064 -0.114 -0.139 -0.014  0.011  0.061  0.160 
 0.281 -0.093 -0.068  0.032 -0.043 -0.167 -0.093 -0.018 -0.093 -0.242 -0.242 -0.217  0.057 -0.142 -0.118 -0.068 -0.043  0.107 -0.043  0.007  0.082  0.132 -0.068 -0.093  0.082 -0.068 -0.018 -0.192 -0.043  0.356 -0.267  0.356  0.206 -0.043 -0.167 -0.093 -0.118 -0.118 -0.018 -0.217 -0.068 -0.192 -0.068 -0.068 -0.118 -0.142  0.057 -0.068  0.057  0.156 
 0.281 -0.093 -0.043  0.032 -0.068 -0.167 -0.093 -0.043 -0.118 -0.242 -0.242 -0.217  0.057 -0.142 -0.118 -0.068 -0.018  0.082 -0.043 -0.043  0.082  0.107 -0.093 -0.093  0.082 -0.068 -0.018 -0.192 -0.043  0.356 -0.267  0.356  0.181 -0.043 -0.167 -0.093 -0.118 -0.118 -0.043 -0.217 -0.068 -0.192 -0.068 -0.068 -0.118 -0.142  0.057 -0.068  0.032  0.156 
 0.280 -0.094 -0.019  0.030 -0.069 -0.169 -0.069 -0.044 -0.119 -0.244 -0.244 -0.219  0.055 -0.144 -0.119 -0.094 -0.019  0.080 -0.044 -0.044  0.105  0.105 -0.094 -0.094  0.105 -0.069  0.005 -0.194 -0.044  0.379 -0.269  0.354  0.205 -0.044 -0.169 -0.094 -0.119 -0.119 -0.044 -0.219 -0.069 -0.194 -0.094 -0.069 -0.094 -0.144  0.055 -0.069  0.055  0.155 
 0.278 -0.096 -0.021  0.029 -0.046 -0.170 -0.071 -0.021 -0.121 -0.245 -0.245 -0.220  0.054 -0.170 -0.121 -0.096 -0.021  0.079 -0.046 -0.046  0.104  0.054 -0.145 -0.096  0.104 -0.071  0.029 -0.195 -0.046  0.378 -0.245  0.403  0.203 -0.046 -0.170 -0.096 -0.145 -0.121 -0.071 -0.220 -0.096 -0.195 -0.096 -0.071 -0.121 -0.145  0.054 -0.046  0.054  0.153 
 0.274 -0.125 -0.025  0.025 -0.025 -0.174 -0.075 -0.025 -0.125 -0.224 -0.249 -0.224  0.075 -0.174 -0.125 -0.125  0.000  0.075 -0.025 -0.050  0.100  0.050 -0.174 -0.100  0.100 -0.075  0.025 -0.199 -0.050  0.349 -0.224  0.424  0.174  0.000 -0.174 -0.100 -0.149 -0.125 -0.075 -0.199 -0.100 -0.174 -0.100 -0.075 -0.125 -0.149  0.075 -0.050  0.025  0.125 
 0.276 -0.098 -0.023  0.027 -0.048 -0.172 -0.098 -0.048 -0.123 -0.222 -0.247 -0.222  0.077 -0.172 -0.123 -0.147  0.027  0.077 -0.023 -0.073  0.077  0.052 -0.172 -0.123  0.102 -0.073  0.027 -0.197 -0.023  0.301 -0.222  0.426  0.151  0.002 -0.172 -0.098 -0.147 -0.123 -0.048 -0.197 -0.098 -0.147 -0.098 -0.098 -0.147 -0.147  0.102 -0.048  0.027  0.027 
 0.273 -0.101 -0.026  0.049 -0.026 -0.200 -0.101 -0.051 -0.175 -0.225 -0.250 -0.225  0.074 -0.150 -0.126 -0.150  0.049  0.099 -0.051 -0.051  0.074  0.049 -0.175 -0.126  0.099 -0.076  0.024 -0.200 -0.026  0.273 -0.225  0.423  0.124 -0.001 -0.175 -0.126 -0.150 -0.126 -0.076 -0.200 -0.076 -0.150 -0.101 -0.101 -0.150 -0.150  0.099 -0.051  0.049 -0.001 
 0.248 -0.126 -0.026  0.074 -0.051 -0.200 -0.101 -0.051 -0.175 -0.225 -0.250 -0.225  0.074 -0.150 -0.126 -0.150  0.049  0.099 -0.051 -0.051  0.049  0.049 -0.175 -0.126  0.074 -0.076  0.024 -0.200 -0.076  0.248 -0.225  0.423  0.148  0.024 -0.175 -0.126 -0.150 -0.126 -0.076 -0.200 -0.076 -0.150 -0.101 -0.101 -0.150 -0.150  0.099 -0.051  0.049 -0.051 

 0.991 -0.005  0.044 -0.030  0.044 -0.005 -0.005 -0.005  0.019 -0.030 -0.005 -0.005 -0.030  0.019 -0.030  0.019  0.019 -0.005 -0.005  0.019  0.019 -0.030 -0.005 -0.030  0.019 -0.005  0.044  0.019  0.019  0.019  0.069  0.019 -0.030  0.019 -0.030 -0.030 -0.030  0.019  0.044  0.019  0.019 -0.005  0.019 -0.005 -0.005 -0.005 -0.030 -0.030 -0.005 -0.030 
 0.996 -0.000  0.024 -0.025  0.024 -0.000 -0.000 -0.000  0.024 -0.025 -0.000 -0.000 -0.025 -0.025 -0.025 -0.000  0.024 -0.000 -0.000  0.024  0.024 -0.025 -0.000 -0.025  0.024 -0.000  0.049  0.024 -0.000  0.024  0.074 -0.000 -0.025 -0.000 -0.025 -0.025 -0.025 -0.000  0.024 -0.000  0.024 -0.000 -0.000 -0.000 -0.000 -0.025 -0.025 -0.025 -0.000 -0.025 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.001 -0.020  0.004 -0.020  0.029  0.004  0.004  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004  0.004  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 
 1.000 -0.021  0.003 -0.021  0.053  0.003  0.003  0.003  0.003 -0.021  0.003  0.003 -0.021 -0.021 -0.021  0.003  0.003  0.003  0.003  0.028  0.028 -0.021  0.003 -0.021  0.028  0.003  0.028  0.028  0.003  0.028  0.078 -0.021 -0.021  0.003 -0.021 -0.021 -0.021 -0.021  0.003  0.003  0.028  0.028  0.003 -0.021  0.003 -0.021 -0.021 -0.021  0.003 -0.021 
 1.000 -0.021  0.003 -0.021  0.053  0.003  0.003  0.003  0.003 -0.021  0.003  0.003 -0.021 -0.021 -0.021  0.003  0.003  0.003  0.003  0.028  0.028 -0.021  0.003 -0.021  0.028  0.003  0.028  0.028  0.003  0.028  0.078 -0.021 -0.021  0.003 -0.021 -0.021 -0.021 -0.021  0.003  0.003  0.028  0.028  0.003 -0.021  0.003 -0.021 -0.021 -0.021  0.003 -0.021 
 1.000 -0.021  0.003 -0.021  0.053  0.003  0.003  0.003  0.003 -0.021  0.003  0.003 -0.021 -0.021 -0.021  0.003  0.003  0.003  0.003  0.028  0.028 -0.021  0.003 -0.021  0.028  0.003  0.028  0.028  0.003  0.028  0.078 -0.021 -0.021  0.003 -0.021 -0.021 -0.021 -0.021  0.003  0.003  0.028  0.028  0.003 -0.021  0.003 -0.021 -0.021 -0.021  0.003 -0.021 
 1.000 -0.021  0.004 -0.021  0.054  0.004  0.004  0.004  0.004 -0.021  0.004  0.004 -0.021 -0.021 -0.021  0.004  0.004  0.004  0.004  0.029  0.029 -0.021  0.004 -0.021  0.029  0.004  0.029  0.029  0.004  0.029  0.079 -0.021 -0.021  0.004 -0.021 -0.021 -0.021 -0.021  0.004  0.004  0.029  0.029  0.004 -0.021  0.004 -0.021 -0.021 -0.021  0.004 -0.021 
 0.999 -0.022  0.002 -0.022  0.077  0.002  0.002  0.002  0.002 -0.022  0.002  0.002 -0.022 -0.022 -0.022  0.002  0.002  0.002  0.002  0.052  0.027 -0.022  0.002 -0.022  0.027  0.002  0.027  0.052  0.002  0.052  0.077 -0.022 -0.022  0.002 -0.022 -0.022 -0.022 -0.022  0.027  0.002  0.027  0.027  0.002 -0.022  0.002 -0.022 -0.022 -0.022  0.002 -0.022 
 0.993 -0.028 -0.003 -0.028  0.146 -0.003 -0.003 -0.003  0.021 -0.028 -0.003 -0.003 -0.028 -0.028 -0.028 -0.003  0.021 -0.003 -0.003  0.046  0.021 -0.028 -0.003 -0.028  0.021 -0.003  0.021  0.071 -0.003  0.046  0.071 -0.028 -0.003  0.021 -0.028 -0.028 -0.028 -0.028  0.071  0.021  0.021  0.021 -0.003 -0.028 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 
 0.987 -0.010 -0.010 -0.035  0.115 -0.010 -0.010 -0.010  0.015 -0.035 -0.010 -0.010 -0.035  0.015 -0.010 -0.010  0.065 -0.010 -0.010  0.040  0.015 -0.035  0.015 -0.035  0.015 -0.010  0.015  0.090 -0.010  0.040  0.090 -0.035 -0.010  0.015 -0.010 -0.035 -0.035 -0.010  0.164  0.015  0.015  0.040 -0.010 -0.035 -0.010 -0.010 -0.010 -0.035 -0.010  0.040 
 0.964 -0.033 -0.033 -0.033  0.266 -0.033 -0.033 -0.008  0.067 -0.033  0.017 -0.008 -0.058  0.017 -0.033 -0.008  0.092  0.017 -0.033  0.042  0.042 -0.033 -0.008 -0.033 -0.008 -0.033 -0.008  0.191 -0.033  0.017  0.166 -0.033  0.042  0.017  0.017 -0.033 -0.033  0.067  0.540  0.017  0.042  0.067 -0.008 -0.033 -0.008  0.017 -0.033 -0.058  0.017  0.042 
 0.936 -0.035 -0.060 -0.010  0.563 -0.060 -0.010  0.039  0.089 -0.035  0.039  0.014 -0.010  0.014 -0.060 -0.010  0.114  0.089 -0.010  0.039  0.014 -0.035  0.039 -0.035  0.014 -0.010 -0.035  0.438  0.014  0.014  0.189 -0.060  0.039 -0.010  0.039 -0.060 -0.035  0.064  0.662  0.064  0.064  0.064  0.014 -0.060 -0.010  0.039 -0.060 -0.085 -0.010  0.064 
 0.895 -0.076 -0.076 -0.026  0.846 -0.076  0.023  0.048  0.098 -0.076  0.023  0.048  0.073 -0.001 -0.101 -0.001  0.123  0.148 -0.051  0.073 -0.001 -0.051  0.048 -0.026 -0.001  0.023 -0.051  0.671  0.048 -0.001  0.347 -0.026  0.048 -0.051  0.073 -0.101 -0.001  0.023  0.895  0.073  0.023  0.048  0.048 -0.076 -0.026  0.023 -0.051 -0.076 -0.001  0.098 
 0.869 -0.077 -0.052  0.022  0.845 -0.077  0.072  0.097  0.047 -0.052 -0.027  0.072  0.172 -0.027 -0.102  0.072  0.122  0.097 -0.077  0.047  0.022 -0.027  0.072 -0.002 -0.002  0.022 -0.052  0.770  0.122 -0.027  0.471 -0.027  0.072 -0.077  0.022 -0.102  0.022 -0.002  0.869  0.047  0.022  0.097  0.022 -0.077  0.022  0.072 -0.077 -0.127  0.022  0.097 
 0.831 -0.066  0.033  0.008  0.831 -0.116  0.108  0.133  0.008 -0.016 -0.066  0.083  0.183 -0.016 -0.116  0.058  0.183  0.258 -0.116  0.008  0.033 -0.066  0.058 -0.016 -0.016  0.033 -0.091  0.831  0.158  0.008  0.532  0.033  0.033 -0.091  0.033 -0.091  0.008 -0.041  0.831  0.033 -0.016  0.083  0.108 -0.091  0.008  0.108 -0.041 -0.091  0.008  0.158 
 0.811 -0.036  0.063 -0.011  0.811 -0.136  0.113  0.113  0.063  0.013 -0.086  0.113  0.163 -0.036 -0.136  0.088  0.188  0.287 -0.111 -0.036  0.013 -0.061  0.088 -0.011  0.013  0.013 -0.111  0.811  0.213 -0.011  0.537  0.013  0.063 -0.111 -0.011 -0.061  0.013 -0.061  0.811  0.038 -0.011  0.088  0.113 -0.111  0.088  0.113 -0.061 -0.086 -0.036  0.188 
 0.753 -0.069  0.155  0.030  0.778 -0.144  0.105  0.080  0.155  0.005 -0.119  0.080  0.155  0.055 -0.119  0.080  0.180  0.280 -0.094  0.005  0.005 -0.069  0.080  0.005  0.055  0.130 -0.144  0.778  0.304  0.005  0.479  0.055  0.030 -0.144 -0.044 -0.044  0.030 -0.094  0.778  0.055 -0.044  0.055  0.080 -0.094  0.130  0.180 -0.044 -0.094 -0.044  0.205 
 0.715 -0.082  0.142  0.043  0.765 -0.132  0.093  0.068  0.242 -0.007 -0.107  0.068  0.142  0.192 -0.156  0.068  0.167  0.267 -0.107 -0.007  0.018 -0.082  0.068  0.018  0.043  0.142 -0.156  0.765  0.342  0.018  0.466  0.018  0.043 -0.181 -0.032 -0.007  0.018 -0.082  0.765  0.118 -0.057  0.043  0.068 -0.107  0.142  0.217 -0.007 -0.082 -0.082  0.217 
 0.650 -0.048  0.176  0.052  0.749 -0.172  0.102  0.027  0.301  0.027 -0.123  0.052  0.102  0.176 -0.172  0.052  0.176  0.251 -0.147 -0.023  0.052 -0.098  0.077  0.002  0.077  0.176 -0.147  0.724  0.401  0.077  0.450  0.002  0.052 -0.197  0.027 -0.023  0.027 -0.023  0.700  0.102 -0.123  0.027  0.052 -0.048  0.151  0.226  0.027 -0.147 -0.098  0.201 
 0.525 -0.048  0.226  0.077  0.749 -0.172  0.102  0.002  0.301  0.027 -0.147  0.077  0.102  0.176 -0.172  0.027  0.151  0.251 -0.147 -0.048  0.027 -0.073  0.052  0.002  0.077  0.176 -0.098  0.675  0.450  0.102  0.450  0.027  0.077 -0.222  0.002 -0.048  0.027 -0.023  0.700  0.102 -0.123  0.002  0.077  0.002  0.151  0.226  0.052 -0.147 -0.123  0.201 
 0.413 -0.010  0.288  0.114  0.737 -0.160  0.114 -0.010  0.388  0.039 -0.185  0.089  0.114  0.164 -0.210  0.014  0.164  0.239 -0.160 -0.035  0.064 -0.010  0.064 -0.060  0.064  0.214 -0.110  0.662  0.488  0.164  0.438  0.064  0.064 -0.260 -0.010 -0.060  0.064 -0.010  0.687  0.089 -0.135  0.014  0.039  0.039  0.189  0.288  0.064 -0.160 -0.160  0.189 
 0.383 -0.016  0.283  0.109  0.731 -0.190  0.109 -0.016  0.383  0.059 -0.190  0.084  0.109  0.158 -0.190  0.009  0.158  0.233 -0.165 -0.066  0.059 -0.016  0.059 -0.091  0.059  0.208 -0.116  0.632  0.482  0.158  0.408  0.059  0.059 -0.265 -0.016 -0.066  0.059  0.009  0.682  0.034 -0.141 -0.016  0.034  0.034  0.208  0.308  0.059 -0.141 -0.165  0.158 
 0.301  0.027  0.276  0.102  0.625 -0.197  0.151 -0.023  0.475  0.127 -0.172  0.077  0.102  0.176 -0.197 -0.023  0.151  0.201 -0.172 -0.123  0.077 -0.023  0.077 -0.123  0.077  0.201 -0.123  0.600  0.500  0.151  0.376  0.052  0.102 -0.272  0.002 -0.048  0.052  0.002  0.675  0.027 -0.123  0.027  0.002  0.052  0.301  0.326  0.052 -0.147 -0.197  0.102 
 0.288  0.089  0.263  0.114  0.587 -0.160  0.139  0.014  0.487  0.089 -0.160  0.114  0.014  0.163 -0.160  0.014  0.064  0.213 -0.136 -0.136  0.089  0.014  0.014 -0.086  0.064  0.188 -0.086  0.487  0.413  0.089  0.263  0.039  0.064 -0.210  0.039 -0.061  0.039 -0.011  0.711  0.039 -0.086  0.039  0.014  0.064  0.188  0.288  0.014 -0.136 -0.136  0.089 
 0.157  0.057  0.257  0.107  0.456 -0.117  0.107  0.032  0.331  0.082 -0.117  0.107  0.082  0.107 -0.142  0.057  0.057  0.182 -0.092 -0.117  0.007  0.082  0.057 -0.017  0.057  0.207 -0.017  0.257  0.257  0.107  0.306  0.007  0.057 -0.117 -0.017 -0.017  0.057  0.057  0.680  0.057 -0.067 -0.017  0.057  0.032  0.182  0.182  0.032 -0.117 -0.067  0.032 
 0.097  0.072  0.246  0.072  0.470 -0.103  0.097  0.022  0.246  0.097 -0.103  0.122  0.097  0.097 -0.128  0.072  0.072  0.171 -0.078 -0.103 -0.028  0.022  0.072 -0.028  0.047  0.246 -0.028  0.171  0.246  0.122  0.271  0.022  0.047 -0.103  0.022 -0.003  0.072  0.072  0.670  0.072 -0.078 -0.028  0.072  0.022  0.196  0.146 -0.003 -0.078 -0.053  0.022 
 0.024  0.099  0.248  0.074  0.298 -0.101  0.124  0.049  0.148  0.074 -0.101  0.099  0.049  0.024 -0.101  0.124  0.099  0.124 -0.051 -0.051 -0.026  0.024  0.074 -0.001  0.024  0.223 -0.001  0.049  0.099  0.074  0.198  0.024  0.049 -0.076  0.049 -0.001  0.049  0.049  0.697  0.099 -0.076 -0.026  0.099 -0.001  0.124  0.049  0.024 -0.051 -0.051  0.049 
 0.038  0.113  0.262  0.038  0.138 -0.087  0.063  0.063  0.162  0.038 -0.087  0.063  0.038  0.013 -0.087  0.138  0.113  0.113 -0.062 -0.062 -0.012 -0.012  0.038  0.013  0.038  0.187  0.013  0.063  0.038  0.088  0.138  0.013  0.063 -0.062  0.088 -0.012  0.088  0.013  0.710  0.088 -0.062 -0.037  0.088  0.013  0.088 -0.012  0.038 -0.037 -0.062  0.063 
 0.008  0.108  0.232  0.033  0.083 -0.067  0.083  0.058  0.157  0.008 -0.067  0.058  0.008  0.008 -0.067  0.157  0.058  0.083 -0.042 -0.042 -0.017 -0.017  0.033  0.033  0.008  0.182  0.033 -0.017 -0.017  0.058  0.108  0.008  0.008 -0.042  0.083  0.008  0.083 -0.017  0.706  0.058 -0.042 -0.042  0.058  0.033  0.083 -0.042  0.033 -0.017 -0.042  0.108 
-0.002  0.097  0.172 -0.002  0.047 -0.052  0.072  0.047  0.147  0.022 -0.052  0.047 -0.002  0.022 -0.052  0.172 -0.002  0.097 -0.052 -0.027 -0.052 -0.002 -0.002  0.047  0.022  0.122  0.022 -0.027 -0.027  0.022  0.047 -0.002 -0.002 -0.027  0.072 -0.002  0.072 -0.002  0.645  0.047 -0.027 -0.052  0.047  0.047  0.047 -0.027  0.022 -0.002 -0.027  0.047 
-0.008  0.092  0.042  0.017  0.042 -0.033  0.042 -0.008  0.067 -0.008 -0.033  0.067 -0.008 -0.008 -0.033  0.092 -0.008 -0.008 -0.033 -0.008 -0.033  0.017  0.017  0.042  0.017  0.042  0.042 -0.008 -0.033  0.042  0.042 -0.008  0.017 -0.008  0.042  0.017  0.042  0.017  0.465 -0.008 -0.008 -0.033 -0.033  0.017  0.042 -0.008  0.042 -0.008 -0.008  0.042 
-0.027  0.073  0.048 -0.002  0.048 -0.027  0.023 -0.002  0.048 -0.002 -0.027  0.023 -0.027 -0.002 -0.027  0.048 -0.002 -0.002 -0.027 -0.002 -0.027  0.023 -0.002  0.023 -0.027  0.048  0.048 -0.002 -0.027  0.048  0.023 -0.002  0.023 -0.002 -0.002  0.023 -0.002  0.023  0.272 -0.002 -0.002 -0.027 -0.027 -0.002  0.048 -0.002 -0.002 -0.002 -0.027  0.048 
-0.020  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
-0.020  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
-0.020  0.054  0.004  0.004  0.029 -0.020  0.004  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020  0.054  0.029  0.004 -0.020  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.054  0.004 -0.020  0.004 -0.020  0.029 
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 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 1.001 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 -0.020  0.079 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029  0.054 -0.020  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.029 -0.020  0.004  0.004  0.029  0.079 -0.020  0.079 -0.020  0.029  0.004 
 0.999 -0.022 -0.022  0.003 -0.022  0.028  0.053 -0.022  0.003  0.003 -0.022  0.078 -0.022  0.003  0.003  0.028 -0.022 -0.022 -0.022 -0.022  0.003  0.003 -0.022  0.003 -0.022  0.003  0.003 -0.022  0.003  0.028  0.053 -0.022  0.028 -0.022 -0.022 -0.022 -0.022  0.003  0.003  0.028 -0.022  0.003  0.003  0.028  0.128 -0.022  0.103 -0.022  0.028  0.003 
 0.997 -0.024 -0.024  0.000 -0.024  0.025  0.050 -0.024  0.000  0.025 -0.024  0.100  0.000  0.000  0.000  0.025 -0.024 -0.024 -0.024 -0.024  0.000  0.000  0.000  0.000 -0.024  0.025  0.000 -0.024  0.000  0.025  0.100 -0.024  0.050 -0.024 -0.024 -0.024 -0.024  0.000  0.000  0.025  0.000  0.000  0.000  0.025  0.200 -0.024  0.125 -0.024  0.025  0.000 
 0.986 -0.035 -0.010 -0.010 -0.035  0.014  0.089 -0.035 -0.010  0.039 -0.010  0.114 -0.010 -0.010 -0.010  0.014 -0.035 -0.035 -0.035 -0.035 -0.010 -0.010  0.014 -0.010 -0.035  0.089 -0.010 -0.035  0.014  0.014  0.164 -0.010  0.139 -0.035 -0.035 -0.010 -0.035  0.014 -0.010  0.039  0.014 -0.010 -0.010  0.039  0.538 -0.035  0.139 -0.035  0.014 -0.010 
 0.966 -0.030 -0.005 -0.030  0.019 -0.005  0.119 -0.030 -0.005  0.044 -0.005  0.293 -0.030 -0.030 -0.005  0.044 -0.030 -0.055 -0.055 -0.055 -0.005 -0.005  0.044  0.019  0.019  0.244  0.019 -0.055 -0.005 -0.005  0.169 -0.030  0.144 -0.030 -0.055 -0.005 -0.005 -0.005 -0.005  0.019  0.019 -0.030 -0.030  0.044  0.916 -0.055  0.169 -0.055 -0.005 -0.005 
 0.937  0.015 -0.035 -0.060  0.065  0.015  0.164 -0.010 -0.010  0.090 -0.035  0.588 -0.060 -0.035 -0.035  0.090 -0.060 -0.085 -0.085 -0.085  0.015  0.015  0.040 -0.010  0.090  0.389  0.164 -0.035  0.015 -0.035  0.289 -0.035  0.164 -0.035 -0.035  0.115 -0.010  0.040  0.015  0.015  0.040 -0.060 -0.060  0.040  0.887 -0.035  0.115 -0.085  0.065  0.040 
 0.875  0.053  0.003 -0.047  0.128  0.028  0.402  0.053  0.128  0.277 -0.047  0.850 -0.047 -0.072 -0.072  0.202 -0.022 -0.146 -0.047 -0.122  0.003 -0.047  0.053  0.028  0.252  0.651  0.177 -0.022  0.028 -0.072  0.551  0.078  0.227  0.028 -0.047  0.327 -0.022  0.128  0.152  0.003  0.003 -0.047  0.003  0.227  0.875 -0.022  0.103 -0.072  0.103  0.053 
 0.834  0.111  0.011 -0.013  0.136  0.011  0.460  0.161  0.211  0.460 -0.038  0.809  0.011 -0.088 -0.113  0.261 -0.038 -0.138 -0.063 -0.113 -0.013 -0.013  0.161  0.011  0.236  0.684  0.385  0.036  0.086 -0.113  0.560  0.086  0.285  0.036 -0.063  0.360 -0.013  0.261  0.261 -0.013 -0.013 -0.013  0.086  0.310  0.834 -0.038  0.186  0.011  0.111  0.086 
 0.754  0.231  0.031  0.056  0.131  0.081  0.654  0.281  0.206  0.629  0.106  0.779  0.056  0.006 -0.093  0.380 -0.068 -0.043 -0.118 -0.143  0.006  0.006  0.106  0.056  0.305  0.779  0.455  0.081  0.181 -0.143  0.679  0.081  0.305  0.131 -0.093  0.455  0.056  0.405  0.330 -0.043  0.056  0.006  0.106  0.455  0.779 -0.068  0.206  0.131  0.081  0.031 
 0.737  0.288  0.039  0.089  0.114  0.114  0.637  0.264  0.288  0.662  0.214  0.762  0.164  0.014 -0.110  0.388 -0.060 -0.010 -0.085 -0.160  0.014  0.064  0.114  0.039  0.239  0.762  0.463  0.139  0.164 -0.160  0.712  0.114  0.288  0.114 -0.110  0.563  0.089  0.463  0.338 -0.060  0.139  0.014  0.114  0.488  0.737 -0.060  0.164  0.164  0.064 -0.010 
 0.718  0.370  0.096  0.170  0.096  0.096  0.594  0.295  0.320  0.669  0.345  0.743  0.320  0.046 -0.079  0.420 -0.104  0.021 -0.054 -0.203  0.021  0.046  0.096  0.046  0.195  0.743  0.569  0.220  0.170 -0.153  0.669  0.145  0.295  0.096 -0.129  0.594  0.096  0.494  0.420 -0.004  0.245  0.046  0.096  0.569  0.694 -0.079  0.145  0.220  0.046 -0.054 
 0.686  0.362  0.138  0.188  0.088  0.088  0.611  0.263  0.362  0.661  0.337  0.736  0.337  0.088 -0.061  0.487 -0.061  0.088 -0.036 -0.161  0.013  0.038  0.113  0.088  0.188  0.711  0.586  0.337  0.163 -0.161  0.636  0.138  0.287  0.088 -0.136  0.562  0.163  0.487  0.462 -0.011  0.312  0.063  0.088  0.562  0.636 -0.111  0.138  0.287  0.038 -0.061 
 0.653  0.354  0.130  0.205  0.080  0.105  0.603  0.280  0.404  0.653  0.404  0.728  0.354  0.130 -0.069  0.554 -0.094  0.155  0.005 -0.169  0.080  0.030  0.105  0.105  0.205  0.678  0.628  0.329  0.205 -0.169  0.578  0.180  0.255  0.055 -0.094  0.578  0.155  0.454  0.479  0.055  0.379  0.055  0.105  0.554  0.628 -0.094  0.130  0.329  0.030 -0.119 
 0.651  0.377  0.128  0.227  0.103  0.103  0.601  0.252  0.426  0.676  0.526  0.725  0.402  0.152 -0.047  0.551 -0.072  0.202 -0.022 -0.171  0.078  0.028  0.103  0.128  0.202  0.676  0.626  0.327  0.202 -0.146  0.501  0.177  0.227  0.003 -0.097  0.576  0.177  0.426  0.451  0.078  0.377  0.078  0.128  0.526  0.601 -0.097  0.103  0.377  0.003 -0.122 
 0.644  0.395  0.121  0.295  0.145  0.121  0.594  0.270  0.469  0.669  0.619  0.718  0.420  0.170 -0.029  0.544 -0.079  0.245 -0.029 -0.178  0.096 -0.029  0.096  0.195  0.195  0.594  0.619  0.345  0.245 -0.129  0.444  0.170  0.195 -0.079 -0.079  0.594  0.170  0.395  0.444  0.071  0.444  0.071  0.145  0.519  0.569 -0.104  0.096  0.395  0.021 -0.129 
 0.617  0.368  0.119  0.318  0.143  0.119  0.592  0.243  0.492  0.667  0.642  0.716  0.418  0.168 -0.031  0.542 -0.106  0.243 -0.006 -0.180  0.094 -0.031  0.094  0.268  0.168  0.592  0.617  0.368  0.268 -0.131  0.418  0.193  0.218 -0.081 -0.056  0.567  0.168  0.368  0.442  0.069  0.467  0.069  0.143  0.517  0.567 -0.106  0.044  0.393 -0.006 -0.131 
 0.587  0.388  0.139  0.313  0.139  0.114  0.563  0.264  0.488  0.662  0.662  0.712  0.413  0.189 -0.010  0.538 -0.160  0.288 -0.010 -0.185  0.114 -0.035  0.089  0.363  0.139  0.563  0.612  0.413  0.264 -0.110  0.338  0.189  0.189 -0.085 -0.035  0.563  0.164  0.363  0.438  0.089  0.488  0.064  0.114  0.513  0.563 -0.085  0.014  0.413 -0.010 -0.135 
 0.584  0.410  0.136  0.310  0.111  0.111  0.559  0.260  0.534  0.659  0.659  0.709  0.410  0.185  0.011  0.534 -0.163  0.310 -0.014 -0.188  0.111 -0.064  0.086  0.360  0.136  0.534  0.609  0.385  0.260 -0.114  0.335  0.210  0.185 -0.089  0.011  0.559  0.160  0.360  0.434  0.086  0.484  0.061  0.136  0.509  0.559 -0.089  0.011  0.410 -0.014 -0.139 
 0.580  0.455  0.107  0.281  0.082  0.107  0.555  0.281  0.555  0.655  0.655  0.705  0.406  0.181  0.082  0.555 -0.167  0.306  0.007 -0.192  0.132 -0.068  0.057  0.331  0.181  0.530  0.605  0.381  0.306 -0.118  0.281  0.206  0.156 -0.118  0.007  0.555  0.156  0.331  0.430  0.156  0.505  0.032  0.132  0.505  0.555 -0.093  0.032  0.381 -0.018 -0.142 
 0.582  0.458  0.109  0.284  0.084  0.109  0.558  0.284  0.558  0.657  0.632  0.707  0.408  0.184  0.084  0.483 -0.165  0.308  0.034 -0.190  0.134 -0.065  0.059  0.333  0.184  0.533  0.607  0.383  0.308 -0.115  0.234  0.209  0.159 -0.115 -0.015  0.558  0.159  0.308  0.433  0.159  0.508  0.034  0.159  0.508  0.558 -0.090  0.034  0.383 -0.015 -0.165 
 0.578  0.454  0.130  0.280  0.080  0.105  0.554  0.304  0.554  0.653  0.628  0.703  0.404  0.180  0.105  0.479 -0.169  0.304  0.030 -0.219  0.130 -0.069  0.055  0.354  0.180  0.554  0.603  0.379  0.304 -0.094  0.230  0.255  0.155 -0.119 -0.019  0.554  0.180  0.304  0.429  0.230  0.504  0.030  0.155  0.504  0.554 -0.094  0.030  0.429 -0.019 -0.169 
 0.577  0.403  0.079  0.303 -0.020  0.104  0.553  0.254  0.453  0.627  0.652  0.677  0.328  0.129  0.029  0.528 -0.145  0.328 -0.095 -0.195  0.079 -0.095  0.104  0.204  0.179  0.553  0.553  0.403  0.179 -0.070  0.154  0.254  0.154 -0.070  0.029  0.577  0.079  0.254  0.403  0.129  0.478  0.029  0.129  0.353  0.503 -0.095  0.079  0.353 -0.020 -0.095 
 0.473  0.324  0.100  0.199 -0.075  0.025  0.473  0.274  0.448  0.673  0.648  0.698  0.274  0.174  0.075  0.548 -0.075  0.299 -0.025 -0.125  0.100  0.000  0.125  0.174  0.075  0.548  0.424  0.324  0.100 -0.075  0.149  0.249  0.125 -0.050  0.025  0.523  0.000  0.125  0.174  0.100  0.424  0.050  0.149  0.324  0.523 -0.025  0.025  0.199 -0.050 -0.025 
 0.491  0.217  0.068  0.068 -0.082 -0.032  0.367  0.267  0.441  0.641  0.641  0.740  0.242  0.167  0.043  0.541 -0.057  0.267 -0.032 -0.107  0.068 -0.007  0.118  0.167  0.068  0.466  0.441  0.317  0.043 -0.057  0.093  0.267  0.142 -0.032  0.018  0.566  0.018  0.142  0.167  0.093  0.417  0.068  0.167  0.292  0.516 -0.007  0.043  0.118 -0.032 -0.007 
 0.322  0.123  0.098 -0.002 -0.077 -0.027  0.272  0.222  0.297  0.646  0.646  0.795  0.222  0.123 -0.002  0.422 -0.027  0.222 -0.052 -0.102  0.023 -0.002  0.123  0.073  0.048  0.372  0.372  0.222  0.023 -0.052  0.048  0.247  0.098 -0.002  0.023  0.546 -0.027  0.098  0.073  0.123  0.347 -0.027  0.172  0.197  0.521 -0.002  0.023  0.073 -0.027  0.023 
 0.184  0.085  0.110 -0.040 -0.065 -0.040  0.184  0.209  0.209  0.633  0.658  0.882  0.159  0.085  0.010  0.284 -0.015  0.209 -0.040 -0.090  0.035  0.010  0.135  0.085  0.010  0.359  0.309  0.184  0.010 -0.065  0.010  0.234  0.085 -0.015  0.035  0.583 -0.015  0.060  0.085  0.135  0.309 -0.015  0.184  0.184  0.483  0.010  0.035  0.085 -0.040  0.035 
 0.102  0.052  0.102 -0.047 -0.047 -0.047  0.077  0.152  0.127  0.625  0.675  0.899  0.127  0.052  0.027  0.177  0.002  0.177 -0.072 -0.072  0.027  0.027  0.127  0.002  0.002  0.252  0.227  0.127  0.027 -0.047  0.002  0.252  0.077  0.002  0.052  0.575  0.002  0.052  0.077  0.102  0.301  0.002  0.127  0.127  0.476  0.002  0.002  0.102 -0.022  0.002 
 0.108  0.033  0.058 -0.042 -0.042 -0.042  0.058  0.133  0.108  0.581  0.681  0.905  0.108  0.033  0.008  0.182 -0.017  0.157 -0.067 -0.067  0.033  0.033  0.133  0.008  0.008  0.182  0.207  0.133  0.033 -0.042 -0.017  0.232  0.083  0.008  0.058  0.531  0.008  0.058  0.083  0.083  0.307  0.008  0.108  0.108  0.431  0.008  0.008  0.108 -0.042 -0.017 
 0.091  0.016  0.016 -0.059 -0.034 -0.059  0.016  0.116  0.091  0.464  0.713  0.963  0.091  0.016 -0.009  0.141 -0.009  0.141 -0.059 -0.059  0.041  0.041  0.091 -0.009  0.016  0.066  0.165  0.066 -0.009 -0.034 -0.009  0.190  0.091 -0.009  0.066  0.539  0.016  0.041  0.066  0.066  0.290 -0.009  0.041  0.091  0.340 -0.009  0.016  0.116 -0.034 -0.034 
 0.073 -0.026  0.023 -0.051 -0.026 -0.051 -0.001  0.123  0.023  0.297  0.696  0.970  0.073  0.023 -0.001  0.123 -0.001  0.148 -0.051 -0.051  0.023  0.048  0.073 -0.001  0.023  0.023  0.123  0.073 -0.001 -0.026 -0.001  0.148  0.098 -0.001  0.073  0.472  0.023  0.048  0.073  0.048  0.273 -0.001 -0.001  0.023  0.273 -0.001 -0.001  0.123 -0.026 -0.026 
 0.078 -0.022  0.003 -0.047 -0.022 -0.047  0.003  0.103  0.028  0.103  0.825  0.975  0.053  0.003  0.003  0.078  0.003  0.128 -0.047 -0.047  0.003  0.053  0.053  0.053  0.028 -0.022  0.128  0.053 -0.022  0.003  0.003  0.078  0.078  0.003  0.053  0.426  0.053  0.053  0.053  0.053  0.227  0.003  0.003  0.028  0.177  0.003 -0.022  0.053 -0.022 -0.047 
 0.057 -0.018 -0.018 -0.043 -0.018 -0.043  0.007  0.107  0.032  0.082  0.904  0.979  0.057  0.007  0.007  0.057  0.007  0.132 -0.018 -0.043 -0.043  0.032  0.057  0.032  0.007  0.007  0.057  0.057 -0.018 -0.018  0.007  0.082  0.057  0.007  0.032  0.231  0.032  0.032  0.057  0.007  0.181  0.007  0.032  0.032  0.132  0.007 -0.018  0.032 -0.043 -0.043 
 0.059 -0.016 -0.041 -0.041 -0.016 -0.041  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.016 -0.041 -0.041  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.016 -0.016  0.009  0.059  0.034  0.009  0.034  0.134  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.016  0.009 -0.041 -0.041 
 0.059 -0.015 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.015 -0.040 -0.040  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.015 -0.015  0.009  0.059  0.034  0.009  0.009  0.109  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.015  0.009 -0.040 -0.040 
 0.059 -0.015 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.015 -0.040 -0.040  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.015 -0.015  0.009  0.059  0.034  0.009  0.009  0.109  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.015  0.009 -0.040 -0.040 
 0.059 -0.015 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.015 -0.040 -0.040  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.015 -0.015  0.009  0.059  0.034  0.009  0.009  0.109  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.015  0.009 -0.040 -0.040 
 0.059 -0.015 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.015 -0.040 -0.040  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.015 -0.015  0.009  0.059  0.034  0.009  0.009  0.109  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.015  0.009 -0.040 -0.040 
 0.059 -0.015 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.015 -0.040 -0.040  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.015 -0.015  0.009  0.059  0.034  0.009  0.009  0.109  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.015  0.009 -0.040 -0.040 
 0.059 -0.015 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.015 -0.040 -0.040  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.015 -0.015  0.009  0.059  0.034  0.009  0.009  0.109  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.015  0.009 -0.040 -0.040 
 0.059 -0.015 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.015 -0.040 -0.040  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.015 -0.015  0.009  0.059  0.034  0.009  0.009  0.109  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.015  0.009 -0.040 -0.040 
 0.059 -0.015 -0.040 -0.040 -0.015 -0.040  0.009  0.034  0.009  0.034  0.981  0.981  0.059  0.009  0.009  0.059  0.009  0.059 -0.015 -0.040 -0.040  0.009  0.059  0.084  0.009  0.009  0.059  0.009 -0.015 -0.015  0.009  0.059  0.034  0.009  0.009  0.109  0.034  0.034  0.059  0.009  0.134  0.009  0.009  0.034  0.134  0.009 -0.015  0.009 -0.040 -0.040 
 0.083  0.008 -0.066 -0.016 -0.016 -0.066 -0.016  0.083  0.133  0.033  0.955  0.955  0.108  0.058  0.033  0.108  0.083  0.108 -0.016 -0.016 -0.041  0.008  0.033  0.083  0.033  0.008  0.208  0.158 -0.041  0.008  0.033  0.208  0.233  0.033  0.008  0.307  0.033  0.083  0.058  0.008  0.332 -0.016  0.058  0.083  0.233  0.008 -0.041  0.008 -0.016 -0.066 
 0.086  0.061  0.036  0.011 -0.038 -0.088  0.036  0.161  0.310  0.186  0.883  0.883  0.236  0.011  0.036  0.360  0.086  0.261 -0.013 -0.013 -0.038 -0.013  0.086  0.136  0.036  0.086  0.435  0.435 -0.063 -0.013  0.036  0.310  0.410 -0.013  0.011  0.584  0.061  0.161  0.186  0.036  0.485 -0.038  0.211  0.111  0.410  0.011 -0.088  0.061 -0.013 -0.113 
 0.210  0.036  0.036  0.086  0.036 -0.039  0.235  0.285  0.459  0.335  0.833  0.833  0.260 -0.014  0.061  0.484  0.061  0.310 -0.039 -0.064  0.036 -0.089  0.185  0.160  0.111  0.086  0.559  0.559 -0.089 -0.064  0.086  0.360  0.459 -0.064  0.036  0.559  0.011  0.136  0.285  0.136  0.584  0.061  0.360  0.136  0.385  0.036 -0.089  0.111 -0.039 -0.114 
 0.300  0.026  0.001  0.126  0.076 -0.074  0.400  0.300  0.649  0.524  0.773  0.773  0.375  0.026  0.026  0.524  0.026  0.400 -0.024 -0.148  0.026 -0.049  0.200  0.200  0.126  0.275  0.649  0.624 -0.074 -0.074  0.250  0.524  0.400 -0.124  0.051  0.599 -0.024  0.076  0.325  0.126  0.649  0.126  0.449  0.126  0.425  0.026 -0.024  0.101 -0.049 -0.099 
 0.287  0.038  0.013  0.138  0.088 -0.087  0.387  0.312  0.636  0.561  0.760  0.760  0.387  0.038  0.013  0.486  0.063  0.387 -0.037 -0.161  0.013 -0.037  0.237  0.237  0.113  0.412  0.636  0.636 -0.062 -0.087  0.262  0.536  0.337 -0.137  0.038  0.586  0.013  0.063  0.312  0.138  0.586  0.212  0.486  0.088  0.461  0.038  0.038  0.162 -0.087 -0.112 
 0.338  0.139  0.039  0.164  0.064 -0.035  0.463  0.313  0.587  0.712  0.712  0.737  0.488  0.064  0.014  0.513  0.039  0.363 -0.060 -0.185 -0.010 -0.060  0.239  0.288  0.139  0.538  0.612  0.662 -0.085 -0.110  0.264  0.538  0.239 -0.185  0.014  0.563  0.014  0.114  0.288  0.164  0.538  0.189  0.538  0.114  0.488  0.014  0.039  0.214 -0.110 -0.060 
 0.355  0.131  0.056  0.180  0.031  0.006  0.479  0.305  0.554  0.728  0.679  0.728  0.479  0.081  0.006  0.479  0.056  0.355 -0.069 -0.193 -0.019 -0.044  0.230  0.255  0.106  0.554  0.604  0.679 -0.094 -0.119  0.230  0.504  0.230 -0.193  0.006  0.554  0.031  0.155  0.305  0.180  0.504  0.180  0.504  0.131  0.529  0.006  0.031  0.280 -0.119 -0.094 
 0.414  0.190  0.090  0.215  0.015  0.065  0.464  0.289  0.539  0.713  0.638  0.713  0.489  0.090  0.015  0.464  0.040  0.364 -0.034 -0.209 -0.034 -0.034  0.215  0.289  0.090  0.638  0.588  0.638 -0.034 -0.084  0.190  0.489  0.215 -0.184 -0.009  0.539  0.040  0.165  0.289  0.215  0.489  0.190  0.489  0.190  0.539  0.065 -0.009  0.389 -0.134 -0.109 
 0.414  0.190  0.115  0.240  0.015  0.090  0.489  0.289  0.539  0.688  0.638  0.713  0.489  0.090  0.015  0.464  0.040  0.364 -0.034 -0.209 -0.034 -0.034  0.215  0.265  0.115  0.638  0.613  0.638  0.015 -0.084  0.190  0.464  0.215 -0.184 -0.009  0.539  0.040  0.165  0.265  0.215  0.464  0.190  0.464  0.215  0.539  0.090 -0.009  0.414 -0.134 -0.109 
 0.435  0.211  0.111  0.285  0.011  0.111  0.485  0.285  0.535  0.684  0.634  0.709  0.485  0.086 -0.013  0.460  0.036  0.360 -0.088 -0.213 -0.038 -0.038  0.186  0.236  0.111  0.609  0.584  0.634  0.011 -0.063  0.211  0.460  0.186 -0.213 -0.013  0.560  0.036  0.136  0.335  0.261  0.410  0.211  0.460  0.261  0.535  0.086 -0.013  0.435 -0.088 -0.113 
 0.483  0.209  0.135  0.284  0.010  0.110  0.458  0.309  0.533  0.633  0.633  0.708  0.483  0.135 -0.040  0.458  0.035  0.334 -0.090 -0.214 -0.040 -0.040  0.184  0.209  0.110  0.608  0.583  0.633  0.010 -0.065  0.184  0.458  0.159 -0.189 -0.015  0.558  0.060  0.159  0.334  0.259  0.409  0.209  0.483  0.284  0.533  0.060 -0.015  0.433 -0.090 -0.115 
 0.502  0.228  0.153  0.302 -0.021  0.178  0.452  0.352  0.527  0.626  0.626  0.676  0.477  0.153 -0.021  0.452  0.028  0.302 -0.071 -0.221 -0.021 -0.071  0.203  0.203  0.103  0.626  0.576  0.552  0.003 -0.071  0.153  0.452  0.153 -0.171 -0.021  0.552  0.028  0.203  0.327  0.302  0.427  0.203  0.452  0.302  0.527  0.053 -0.071  0.427 -0.121 -0.146 
 0.501  0.252  0.227  0.302 -0.022  0.177  0.451  0.352  0.526  0.626  0.626  0.676  0.476  0.152 -0.022  0.451  0.003  0.302 -0.072 -0.221 -0.022 -0.072  0.202  0.202  0.103  0.601  0.576  0.501  0.003 -0.097  0.152  0.451  0.128 -0.171 -0.022  0.551  0.028  0.202  0.327  0.302  0.426  0.202  0.451  0.352  0.526  0.078 -0.072  0.426 -0.097 -0.146 
 0.524  0.250  0.225  0.299 -0.024  0.175  0.449  0.374  0.524  0.623  0.623  0.673  0.474  0.200  0.025  0.449 -0.024  0.299 -0.074 -0.224 -0.024 -0.099  0.175  0.200  0.075  0.598  0.573  0.474  0.000 -0.099  0.125  0.424  0.125 -0.174  0.000  0.549  0.050  0.250  0.324  0.299  0.449  0.200  0.424  0.374  0.499  0.075 -0.074  0.424 -0.099 -0.149 
 0.525  0.251  0.251  0.300 -0.023  0.176  0.450  0.350  0.525  0.624  0.624  0.674  0.475  0.226  0.051  0.450 -0.048  0.276 -0.048 -0.223 -0.023 -0.098  0.176  0.201  0.076  0.599  0.574  0.475 -0.023 -0.098  0.126  0.425  0.126 -0.173  0.001  0.550  0.076  0.251  0.325  0.325  0.450  0.226  0.325  0.400  0.500  0.051 -0.073  0.425 -0.098 -0.148 
 0.525  0.301  0.251  0.301 -0.023  0.176  0.475  0.351  0.525  0.625  0.625  0.675  0.475  0.226  0.052  0.426 -0.123  0.276 -0.048 -0.222 -0.023 -0.098  0.176  0.201  0.077  0.600  0.575  0.450  0.002 -0.098  0.102  0.426  0.102 -0.172  0.002  0.550  0.077  0.276  0.326  0.326  0.450  0.226  0.276  0.401  0.500  0.027 -0.073  0.426 -0.147 -0.172 
 0.522  0.298  0.298  0.323 -0.051  0.173  0.472  0.348  0.522  0.622  0.622  0.672  0.472  0.223  0.049  0.423 -0.150  0.273 -0.076 -0.225 -0.026 -0.076  0.173  0.173  0.074  0.597  0.572  0.472 -0.001 -0.101  0.074  0.423  0.099 -0.175  0.024  0.547  0.099  0.298  0.323  0.323  0.447  0.223  0.198  0.398  0.497  0.024 -0.076  0.423 -0.150 -0.175 
 0.525  0.300  0.276  0.325 -0.048  0.176  0.450  0.350  0.525  0.624  0.624  0.674  0.475  0.226  0.051  0.425 -0.148  0.251 -0.073 -0.223 -0.023 -0.073  0.176  0.176  0.076  0.599  0.574  0.475  0.001 -0.098  0.076  0.425  0.101 -0.173  0.026  0.550  0.101  0.325  0.350  0.325  0.475  0.176  0.201  0.400  0.475  0.001 -0.073  0.425 -0.173 -0.173 
 0.525  0.300  0.276  0.325 -0.048  0.151  0.450  0.350  0.525  0.624  0.624  0.674  0.450  0.226  0.026  0.425 -0.148  0.276 -0.098 -0.223 -0.023 -0.073  0.176  0.176  0.076  0.599  0.574  0.475  0.026 -0.073  0.076  0.425  0.076 -0.173  0.001  0.525  0.101  0.325  0.350  0.300  0.475  0.176  0.201  0.400  0.475 -0.023 -0.073  0.425 -0.148 -0.173 
 0.526  0.302  0.277  0.327 -0.047  0.152  0.426  0.377  0.526  0.626  0.626  0.676  0.451  0.227  0.003  0.426 -0.146  0.277 -0.097 -0.221 -0.022 -0.072  0.177  0.177  0.078  0.601  0.576  0.476  0.003 -0.072  0.078  0.426  0.078 -0.171 -0.022  0.526  0.103  0.327  0.352  0.302  0.476  0.177  0.177  0.402  0.476 -0.022 -0.072  0.426 -0.146 -0.171 
 0.554  0.280  0.230  0.280 -0.019  0.055  0.404  0.329  0.529  0.628  0.529  0.728  0.354  0.255  0.080  0.404 -0.069  0.230 -0.094 -0.194  0.005 -0.069  0.130  0.105  0.105  0.628  0.529  0.354  0.080 -0.044  0.130  0.329  0.080 -0.094  0.005  0.529  0.055  0.379  0.205  0.280  0.404  0.205  0.155  0.230  0.504 -0.019 -0.044  0.255 -0.119 -0.094 
 0.472  0.223  0.098  0.198 -0.001  0.073  0.372  0.297  0.522  0.646  0.547  0.696  0.198  0.198  0.073  0.372 -0.026  0.123 -0.051 -0.126  0.023 -0.026  0.073  0.148  0.123  0.621  0.422  0.273  0.023 -0.026  0.098  0.248  0.098 -0.076  0.023  0.571 -0.001  0.173  0.173  0.273  0.372  0.073  0.123  0.223  0.522 -0.026 -0.026  0.073 -0.076 -0.001 
 0.437  0.213  0.063  0.188  0.013  0.013  0.337  0.263  0.537  0.661  0.537  0.711  0.188  0.138  0.088  0.312 -0.011  0.138 -0.036 -0.111  0.038 -0.011  0.088  0.113  0.138  0.636  0.387  0.238 -0.011 -0.061  0.113  0.263  0.113 -0.061  0.013  0.586 -0.011  0.138  0.163  0.213  0.337  0.063  0.138  0.188  0.537 -0.011 -0.011  0.013 -0.061  0.013 
 0.288  0.213  0.089  0.114 -0.061  0.014  0.238  0.238  0.512  0.687  0.587  0.687  0.139  0.089  0.039  0.238 -0.011  0.114 -0.086 -0.111  0.039 -0.011  0.114  0.089  0.139  0.637  0.313  0.139 -0.036 -0.036  0.139  0.238  0.089 -0.061  0.014  0.612  0.014  0.039  0.089  0.188  0.263 -0.011  0.139  0.163  0.537 -0.011  0.014  0.039 -0.036  0.014 
 0.228  0.203  0.078  0.053 -0.071  0.003  0.128  0.228  0.377  0.726  0.576  0.676  0.103  0.053  0.028  0.253 -0.021  0.128 -0.071 -0.096  0.028  0.003  0.103  0.078  0.128  0.626  0.203  0.078 -0.046 -0.046  0.128  0.228  0.103 -0.046  0.028  0.626  0.053  0.028  0.103  0.178  0.278 -0.021  0.153  0.128  0.527  0.003  0.028  0.053 -0.021  0.028 
 0.141  0.041  0.091  0.016 -0.058 -0.033  0.066  0.241  0.290  0.764  0.565  0.664  0.116  0.066  0.016  0.141 -0.008  0.116 -0.058 -0.083  0.041  0.041  0.091  0.041  0.066  0.614  0.166  0.091 -0.008 -0.033  0.066  0.241  0.116 -0.033  0.041  0.639  0.091 -0.008  0.066  0.166  0.241 -0.033  0.141  0.116  0.490  0.016  0.041  0.066 -0.033  0.041 
 0.074  0.049  0.099 -0.000 -0.050 -0.050  0.024  0.199  0.274  0.797  0.498  0.548  0.124  0.074 -0.000  0.074 -0.025  0.124 -0.050 -0.075  0.049  0.049  0.049  0.024  0.074  0.597  0.149  0.074 -0.000 -0.025  0.049  0.249  0.099 -0.025  0.024  0.647  0.099 -0.000  0.074  0.099  0.249 -0.025  0.099  0.074  0.498  0.024  0.024  0.074 -0.025  0.024 
 0.084  0.009  0.109  0.009 -0.041 -0.041  0.034  0.109  0.134  0.856  0.457  0.457  0.109  0.084  0.009  0.034 -0.016  0.109 -0.066 -0.066  0.034  0.034  0.034  0.034  0.059  0.507  0.134  0.109  0.009 -0.041  0.034  0.233  0.109 -0.016  0.034  0.682  0.109  0.034  0.059  0.109  0.258 -0.016  0.059  0.084  0.457  0.034  0.009  0.084 -0.016  0.009 
 0.064 -0.010  0.114  0.014 -0.035 -0.060  0.014  0.064  0.114  0.936  0.463  0.363  0.114  0.089 -0.010 -0.010 -0.010  0.089 -0.060 -0.060  0.039  0.014  0.014  0.014  0.064  0.388  0.064  0.064 -0.010 -0.035 -0.010  0.214  0.089 -0.035  0.039  0.687  0.089  0.039  0.064  0.114  0.164 -0.010  0.039  0.089  0.413  0.039  0.014  0.089 -0.010 -0.035 
 0.076 -0.024  0.101  0.026 -0.024 -0.049 -0.024  0.051  0.076  0.973  0.400  0.175  0.076  0.076 -0.024  0.001  0.001  0.051 -0.049 -0.049  0.051  0.026  0.001  0.026  0.026  0.200  0.076  0.001  0.001 -0.024  0.001  0.175  0.101 -0.024  0.026  0.649  0.076  0.051  0.051  0.101  0.150  0.001  0.026  0.051  0.350  0.051  0.026  0.051  0.001 -0.024 
 0.081 -0.019  0.106  0.031 -0.044 -0.044 -0.019  0.056  0.056  0.978  0.255  0.131  0.031  0.056 -0.044 -0.019  0.006  0.006 -0.044 -0.044  0.031  0.031  0.006  0.031 -0.019  0.155  0.081 -0.019  0.006 -0.019  0.006  0.155  0.081 -0.044  0.031  0.654  0.056  0.056  0.006  0.031  0.106  0.006  0.006  0.056  0.305  0.031  0.031  0.056  0.006 -0.019 
-0.011 -0.011  0.038  0.038 -0.036 -0.036 -0.011  0.038  0.063  0.985  0.213  0.013 -0.011  0.038 -0.036 -0.011 -0.011  0.013 -0.036 -0.036  0.038  0.013  0.013  0.013 -0.011  0.063  0.063 -0.011 -0.011 -0.011  0.013  0.113  0.038 -0.036  0.038  0.686  0.063  0.038 -0.011  0.038  0.088 -0.011  0.013  0.063  0.038  0.013  0.013  0.063  0.013 -0.011 
-0.014 -0.014  0.035  0.035 -0.039 -0.039 -0.014  0.035  0.060  0.982  0.185  0.010 -0.014  0.035 -0.039 -0.014 -0.014  0.010 -0.039 -0.039  0.010 -0.014  0.010  0.010 -0.014  0.060  0.060  0.010 -0.014 -0.014  0.010  0.085  0.035 -0.039  0.035  0.882  0.060  0.035 -0.014  0.035  0.060 -0.014  0.010  0.060  0.010  0.010  0.010  0.060  0.035 -0.014 
-0.015 -0.015  0.034  0.034 -0.040 -0.040 -0.040  0.034  0.059  0.981  0.159  0.009 -0.015  0.034 -0.040 -0.015 -0.015  0.009 -0.040 -0.015  0.009 -0.015  0.009  0.009 -0.015  0.059  0.059  0.009 -0.015 -0.015  0.009  0.084  0.009 -0.040  0.034  0.956  0.059  0.034 -0.015  0.034  0.034 -0.015  0.009  0.059  0.009  0.009  0.009  0.059  0.034 -0.015 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.037 -0.037  0.162  0.062 -0.037 -0.012 -0.037  0.087  0.087  0.959  0.311  0.012 -0.012  0.112 -0.037 -0.037 -0.012  0.062 -0.062 -0.037  0.037 -0.012 -0.012  0.012  0.012  0.137  0.037  0.037 -0.012 -0.012 -0.012  0.187  0.037 -0.062  0.037  0.959  0.087  0.062  0.012  0.062  0.137 -0.037  0.037  0.162  0.062  0.037 -0.012  0.162  0.012 -0.037 
-0.019 -0.044  0.329  0.080 -0.044 -0.069 -0.069  0.180  0.080  0.902  0.504  0.055  0.155  0.230 -0.044 -0.019 -0.069  0.055 -0.094 -0.044  0.155 -0.019  0.030 -0.019  0.055  0.354  0.055  0.180  0.055 -0.044 -0.019  0.180  0.080 -0.119  0.030  0.902  0.080  0.105 -0.019  0.080  0.230  0.005  0.180  0.255  0.130  0.055 -0.019  0.280  0.005 -0.019 
-0.005 -0.055  0.343  0.144 -0.005 -0.030 -0.030  0.219  0.044  0.866  0.692  0.094  0.244  0.194 -0.030 -0.030 -0.105  0.119 -0.105 -0.080  0.169 -0.055 -0.030 -0.005  0.044  0.368  0.094  0.244  0.019 -0.080 -0.030  0.269  0.094 -0.155 -0.005  0.866  0.144  0.094  0.019  0.069  0.318  0.019  0.119  0.393  0.194  0.019 -0.030  0.343 -0.030 -0.055 
 0.099 -0.025  0.448  0.199 -0.050 -0.050  0.049  0.398  0.224  0.797  0.772  0.249  0.398  0.249 -0.000 -0.000 -0.100  0.149 -0.125 -0.125  0.149 -0.025 -0.025  0.049  0.124  0.597  0.149  0.398 -0.025 -0.075  0.024  0.323  0.149 -0.200 -0.025  0.772  0.274  0.199  0.049  0.149  0.473  0.074  0.174  0.548  0.298  0.049 -0.050  0.498 -0.075 -0.100 
 0.103  0.003  0.451  0.152 -0.047 -0.047  0.103  0.526  0.302  0.775  0.750  0.377  0.451  0.277  0.003  0.053 -0.097  0.202 -0.146 -0.146  0.128  0.003  0.028  0.103  0.152  0.626  0.227  0.451 -0.047 -0.072  0.003  0.377  0.128 -0.196 -0.022  0.725  0.352  0.227  0.053  0.177  0.501  0.103  0.202  0.526  0.352  0.028 -0.072  0.501 -0.122 -0.097 
 0.140  0.065  0.414  0.115 -0.034 -0.059  0.190  0.588  0.439  0.738  0.713  0.489  0.464  0.265 -0.034  0.115 -0.034  0.240 -0.159 -0.159  0.040 -0.009  0.115  0.190  0.140  0.613  0.339  0.514 -0.084 -0.084  0.065  0.414  0.140 -0.234  0.040  0.663  0.414  0.289  0.190  0.190  0.489  0.165  0.240  0.539  0.439  0.040 -0.109  0.464 -0.159 -0.109 
 0.162  0.113  0.387  0.138  0.013 -0.037  0.187  0.561  0.436  0.735  0.710  0.511  0.461  0.237 -0.062  0.162  0.013  0.287 -0.137 -0.161  0.038  0.013  0.162  0.187  0.162  0.611  0.387  0.586 -0.062 -0.087  0.038  0.461  0.113 -0.211  0.038  0.661  0.436  0.312  0.162  0.162  0.461  0.212  0.312  0.486  0.511  0.038 -0.087  0.461 -0.137 -0.137 
 0.193  0.143  0.342  0.268  0.043 -0.081  0.193  0.542  0.417  0.716  0.691  0.616  0.467  0.193 -0.006  0.193 -0.031  0.317 -0.081 -0.181  0.018 -0.006  0.168  0.243  0.168  0.591  0.467  0.616 -0.081 -0.106  0.043  0.517  0.118 -0.206  0.018  0.591  0.417  0.342  0.168  0.168  0.442  0.268  0.317  0.442  0.542  0.043 -0.106  0.442 -0.206 -0.156 
 0.212  0.137  0.336  0.262  0.062 -0.087  0.212  0.536  0.411  0.710  0.660  0.610  0.461  0.212  0.012  0.212 -0.037  0.336 -0.087 -0.212  0.012 -0.012  0.162  0.237  0.162  0.585  0.561  0.610 -0.087 -0.087  0.087  0.511  0.137 -0.212  0.012  0.585  0.436  0.336  0.162  0.162  0.436  0.262  0.311  0.411  0.536  0.087 -0.087  0.436 -0.212 -0.162 
 0.255  0.230  0.330  0.305  0.031 -0.094  0.230  0.479  0.454  0.679  0.654  0.629  0.454  0.180  0.056  0.230 -0.094  0.280 -0.069 -0.218  0.006  0.056  0.155  0.280  0.155  0.604  0.554  0.604 -0.094 -0.094  0.106  0.554  0.131 -0.218  0.006  0.554  0.429  0.280  0.155  0.155  0.429  0.255  0.280  0.405  0.529  0.081 -0.094  0.429 -0.218 -0.168 
 0.300  0.276  0.300  0.300  0.026 -0.073  0.251  0.450  0.450  0.649  0.649  0.649  0.450  0.201  0.076  0.276 -0.148  0.251 -0.073 -0.248 -0.023  0.076  0.151  0.276  0.151  0.574  0.550  0.599 -0.048 -0.098  0.126  0.550  0.076 -0.223  0.001  0.550  0.425  0.251  0.151  0.151  0.400  0.251  0.251  0.400  0.525  0.101 -0.123  0.425 -0.223 -0.173 
 0.392  0.267  0.267  0.317  0.018 -0.107  0.292  0.392  0.491  0.616  0.616  0.641  0.441  0.192  0.093  0.342 -0.156  0.217 -0.082 -0.256 -0.032  0.068  0.142  0.192  0.142  0.566  0.541  0.566 -0.032 -0.107  0.118  0.516  0.068 -0.231  0.018  0.516  0.441  0.242  0.167  0.142  0.367  0.292  0.217  0.392  0.516  0.118 -0.107  0.417 -0.231 -0.181 
 0.415  0.290  0.240  0.315  0.016 -0.109  0.340  0.365  0.464  0.614  0.614  0.639  0.439  0.190  0.091  0.390 -0.158  0.240 -0.084 -0.258 -0.034  0.066  0.141  0.165  0.141  0.564  0.539  0.564 -0.059 -0.109  0.116  0.514  0.066 -0.233  0.041  0.539  0.415  0.240  0.165  0.141  0.365  0.315  0.190  0.365  0.489  0.091 -0.109  0.415 -0.233 -0.183 
 0.460  0.261  0.236  0.335 -0.013 -0.088  0.385  0.360  0.460  0.609  0.609  0.634  0.460  0.186  0.086  0.410 -0.113  0.211 -0.088 -0.263 -0.038  0.036  0.161  0.111  0.136  0.584  0.535  0.485 -0.038 -0.113  0.061  0.510  0.111 -0.238  0.036  0.510  0.385  0.211  0.261  0.136  0.360  0.335  0.186  0.385  0.485  0.111 -0.113  0.385 -0.213 -0.188 
 0.462  0.238  0.238  0.337 -0.036 -0.086  0.387  0.337  0.462  0.611  0.611  0.636  0.462  0.188  0.088  0.387 -0.111  0.188 -0.111 -0.261 -0.036  0.013  0.163  0.113  0.113  0.586  0.537  0.487 -0.036 -0.111  0.063  0.487  0.113 -0.236  0.038  0.512  0.362  0.213  0.287  0.113  0.362  0.337  0.188  0.387  0.487  0.113 -0.111  0.387 -0.186 -0.186 
 0.460  0.236  0.236  0.335 -0.038 -0.088  0.360  0.310  0.460  0.609  0.609  0.634  0.460  0.161  0.086  0.385 -0.138  0.186 -0.113 -0.263 -0.038  0.036  0.211  0.111  0.111  0.584  0.535  0.485 -0.013 -0.113  0.036  0.485  0.111 -0.238  0.036  0.510  0.335  0.236  0.310  0.136  0.360  0.335  0.161  0.410  0.485  0.111 -0.113  0.385 -0.188 -0.188 
 0.437  0.263  0.238  0.338 -0.036 -0.111  0.363  0.288  0.462  0.612  0.612  0.637  0.462  0.163  0.089  0.388 -0.136  0.188 -0.111 -0.260 -0.011  0.039  0.238  0.114  0.089  0.587  0.537  0.487 -0.011 -0.111  0.014  0.462  0.114 -0.235  0.014  0.487  0.338  0.238  0.313  0.139  0.338  0.338  0.163  0.413  0.487  0.114 -0.111  0.388 -0.160 -0.185 
 0.457  0.258  0.233  0.332 -0.041 -0.091  0.357  0.307  0.482  0.606  0.606  0.631  0.457  0.158  0.158  0.382 -0.141  0.183 -0.116 -0.266 -0.016  0.033  0.283  0.108  0.083  0.581  0.532  0.482  0.008 -0.091  0.008  0.457  0.108 -0.241 -0.016  0.482  0.332  0.233  0.357  0.208  0.382  0.357  0.158  0.407  0.482  0.108 -0.116  0.382 -0.166 -0.191 
 0.502  0.228  0.228  0.327 -0.046 -0.071  0.352  0.302  0.477  0.601  0.601  0.626  0.452  0.153  0.153  0.377 -0.146  0.178 -0.121 -0.271 -0.021  0.028  0.302  0.103  0.078  0.576  0.527  0.477  0.003 -0.096  0.028  0.452  0.103 -0.246  0.003  0.477  0.327  0.228  0.352  0.253  0.402  0.352  0.153  0.402  0.477  0.103 -0.121  0.377 -0.171 -0.196 
 0.503  0.204  0.229  0.354 -0.070 -0.020  0.379  0.279  0.453  0.603  0.578  0.628  0.453  0.154  0.154  0.379 -0.144  0.179 -0.120 -0.269 -0.020  0.055  0.304  0.105  0.080  0.578  0.503  0.478  0.005 -0.095  0.030  0.453  0.105 -0.244  0.005  0.453  0.329  0.229  0.354  0.254  0.404  0.354  0.154  0.404  0.478  0.105 -0.095  0.379 -0.169 -0.194 
 0.538  0.164  0.214  0.288 -0.110  0.014  0.288  0.313  0.488  0.662  0.488  0.662  0.363  0.189  0.139  0.388 -0.085  0.189 -0.085 -0.210  0.014  0.064  0.214  0.064  0.164  0.513  0.438  0.413  0.014 -0.085  0.039  0.363  0.139 -0.185 -0.010  0.488  0.313  0.214  0.239  0.164  0.438  0.239  0.189  0.413  0.538  0.014 -0.060  0.363 -0.085 -0.135 
 0.457  0.158  0.109  0.208 -0.041 -0.016  0.308  0.233  0.408  0.657  0.482  0.682  0.308  0.134  0.109  0.258 -0.066  0.109 -0.091 -0.165  0.034 -0.016  0.183  0.059  0.183  0.482  0.358  0.308  0.009 -0.041  0.084  0.333  0.134 -0.091 -0.016  0.532  0.109  0.158  0.158  0.183  0.358  0.208  0.233  0.358  0.557  0.009 -0.041  0.183 -0.066 -0.041 
 0.383  0.134  0.084  0.134 -0.040 -0.015  0.308  0.234  0.383  0.682  0.433  0.682  0.259  0.159  0.109  0.234 -0.040  0.109 -0.090 -0.140  0.059 -0.015  0.209  0.084  0.134  0.408  0.358  0.284  0.034 -0.040  0.084  0.284  0.109 -0.065 -0.015  0.558  0.009  0.109  0.134  0.209  0.284  0.084  0.234  0.333  0.582 -0.015 -0.040  0.109 -0.065 -0.015 
 0.318  0.094  0.069  0.069 -0.031 -0.006  0.243  0.193  0.268  0.716  0.467  0.692  0.193  0.094  0.094  0.143 -0.031  0.143 -0.056 -0.106  0.069 -0.006  0.193  0.019  0.143  0.393  0.268  0.193 -0.006 -0.031  0.094  0.243  0.143 -0.056 -0.031  0.592  0.019  0.069  0.044  0.193  0.268  0.019  0.168  0.193  0.617 -0.006 -0.006  0.044 -0.056  0.019 
 0.231  0.107  0.082  0.057 -0.018 -0.018  0.156  0.156  0.231  0.729  0.455  0.680  0.107  0.082  0.007  0.156 -0.018  0.132 -0.068 -0.093  0.007  0.007  0.206  0.007  0.107  0.356  0.281  0.132 -0.018 -0.018  0.082  0.231  0.132 -0.043 -0.018  0.630  0.032  0.007  0.032  0.156  0.231  0.007  0.132  0.132  0.680  0.007  0.007  0.057 -0.043  0.032 
 0.151  0.026  0.101 -0.023 -0.023 -0.073  0.101  0.176  0.151  0.799  0.375  0.724  0.026  0.051 -0.023  0.101  0.001  0.051 -0.073 -0.073  0.026  0.026  0.176  0.026  0.051  0.226  0.201  0.026  0.001 -0.048  0.076  0.251  0.101 -0.023  0.026  0.649  0.076  0.051  0.026  0.076  0.226  0.001  0.101  0.151  0.699  0.026  0.001  0.076 -0.023 -0.023 
 0.156 -0.018  0.106 -0.018 -0.018 -0.068  0.081  0.181  0.156  0.804  0.305  0.704  0.031  0.056 -0.018  0.056  0.006  0.056 -0.068 -0.068  0.031  0.056  0.156  0.031  0.031  0.181  0.081  0.031  0.006 -0.043  0.056  0.256  0.106 -0.018  0.031  0.654  0.106  0.056  0.031  0.081  0.206  0.006  0.081  0.131  0.704  0.031  0.006  0.081 -0.018 -0.043 
 0.114 -0.036  0.114  0.014 -0.011 -0.061  0.014  0.089  0.139  0.886  0.213  0.687  0.014  0.039 -0.011  0.014  0.014 -0.011 -0.061 -0.061  0.039  0.064  0.139  0.039  0.039  0.089  0.089 -0.011 -0.011 -0.036  0.039  0.188  0.114 -0.036  0.039  0.662  0.089  0.064  0.039  0.014  0.163 -0.011 -0.011  0.114  0.687  0.014 -0.011  0.064 -0.011 -0.036 
 0.116 -0.034  0.066  0.016 -0.009 -0.059  0.016  0.091  0.141  0.913  0.215  0.664  0.016  0.041 -0.009  0.016  0.016 -0.009 -0.059 -0.059  0.041  0.066  0.141  0.066  0.041  0.066  0.091 -0.009 -0.009 -0.034  0.016  0.165  0.116 -0.034  0.041  0.664  0.091  0.066  0.016  0.016  0.165 -0.009 -0.009  0.116  0.639  0.016 -0.009  0.066 -0.009 -0.034 
 0.119 -0.031  0.069  0.019 -0.006 -0.056 -0.031  0.094  0.143  0.966  0.168  0.642  0.019  0.044 -0.006  0.019  0.019 -0.006 -0.056 -0.056  0.044  0.019  0.119  0.069  0.044  0.069  0.094 -0.006 -0.031 -0.031  0.019  0.143  0.094 -0.031  0.044  0.667  0.069  0.044  0.019  0.019  0.119 -0.006 -0.006  0.094  0.517  0.019 -0.006  0.069 -0.006 -0.031 
 0.095 -0.029  0.070  0.020 -0.029 -0.054 -0.029  0.095  0.145  0.967  0.170  0.643  0.020  0.045 -0.004  0.020  0.020 -0.004 -0.054 -0.054  0.045  0.020  0.070  0.070  0.045  0.070  0.095 -0.004 -0.029 -0.029  0.020  0.145  0.095 -0.029  0.045  0.693  0.070  0.045  0.020  0.020  0.120 -0.004 -0.004  0.095  0.419  0.020 -0.004  0.070 -0.004 -0.029 
 0.097 -0.027  0.047  0.022 -0.027 -0.052 -0.027  0.097  0.122  0.969  0.147  0.645  0.022  0.047 -0.002  0.022  0.022 -0.002 -0.052 -0.052  0.022 -0.002  0.047  0.047  0.022  0.047  0.097 -0.002 -0.027 -0.027 -0.002  0.122  0.022 -0.027  0.047  0.745  0.072  0.047  0.022  0.022  0.072 -0.002 -0.002  0.097  0.272  0.022 -0.002  0.072 -0.002 -0.027 
 0.096 -0.028  0.046  0.021 -0.028 -0.053 -0.028  0.096  0.121  0.968  0.146  0.644  0.021  0.046 -0.003  0.021  0.021 -0.003 -0.053 -0.053  0.021 -0.003  0.046  0.046  0.021  0.046  0.096  0.021 -0.028 -0.028 -0.003  0.121 -0.003 -0.028  0.046  0.819  0.071  0.046  0.021  0.021  0.046 -0.003 -0.003  0.096  0.246  0.021 -0.003  0.071  0.021 -0.028 
 0.074 -0.026  0.049  0.024 -0.026 -0.051 -0.026  0.099  0.074  0.971  0.148  0.547 -0.001  0.049 -0.001 -0.001  0.024 -0.001 -0.051 -0.051 -0.001 -0.026  0.024  0.024  0.024  0.049  0.074  0.024 -0.026 -0.026 -0.001  0.099 -0.001 -0.026  0.049  0.896  0.074  0.049  0.024  0.024  0.049 -0.001 -0.001  0.099  0.148  0.024 -0.001  0.074  0.024 -0.026 
 0.028 -0.022  0.028  0.028 -0.047 -0.047 -0.022  0.053  0.053  0.975  0.152  0.352 -0.022  0.053 -0.022 -0.022  0.003  0.003 -0.047 -0.047  0.003 -0.022  0.028  0.003  0.003  0.053  0.078  0.028 -0.022 -0.022  0.003  0.103  0.003 -0.047  0.028  0.925  0.078  0.053  0.003  0.028  0.053  0.003  0.003  0.078  0.103  0.028  0.003  0.103  0.028 -0.022 
 0.006 -0.018  0.031  0.031 -0.043 -0.043 -0.018  0.056  0.056  0.978  0.156  0.131 -0.018  0.031 -0.043 -0.018  0.006  0.006 -0.043 -0.018  0.006 -0.018  0.006  0.006 -0.018  0.056  0.056  0.031 -0.018 -0.018  0.006  0.081  0.006 -0.043  0.031  0.978  0.056  0.031 -0.018  0.031  0.031  0.006  0.006  0.056  0.056  0.006  0.006  0.081  0.031 -0.018 
-0.018 -0.018  0.032  0.032 -0.043 -0.043 -0.018  0.057  0.057  0.979  0.156  0.107 -0.018  0.032 -0.043 -0.018  0.007  0.007 -0.043 -0.018  0.007 -0.018  0.007  0.007 -0.018  0.057  0.057  0.032 -0.018 -0.018  0.007  0.082  0.007 -0.043  0.032  0.979  0.057  0.032 -0.018  0.032  0.032  0.007  0.007  0.057  0.032  0.007  0.007  0.082  0.032 -0.018 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.033 -0.008  0.042  0.017 -0.058 -0.008 -0.058  0.042  0.067  0.964  0.366 -0.008  0.042  0.067 -0.058 -0.008 -0.008  0.117 -0.058 -0.033  0.042 -0.033 -0.008  0.017 -0.033  0.142  0.092  0.067 -0.033 -0.033 -0.008  0.117  0.017 -0.058  0.067  0.964  0.092  0.042 -0.033  0.017  0.067 -0.008  0.017  0.042  0.067 -0.008 -0.008  0.216  0.017 -0.033 
-0.087 -0.012  0.162  0.088 -0.087  0.038 -0.062  0.138  0.038  0.910  0.785  0.013  0.063  0.088 -0.037  0.038 -0.062  0.237 -0.062 -0.062  0.088 -0.012  0.063  0.063 -0.087  0.237  0.063  0.262 -0.062 -0.037 -0.062  0.436  0.013 -0.087  0.088  0.910  0.162  0.138  0.013  0.088  0.237  0.013  0.113  0.113  0.088 -0.012 -0.012  0.536 -0.037 -0.012 
-0.085  0.115  0.264  0.040 -0.085 -0.010  0.015  0.164  0.040  0.862  0.787  0.040  0.065  0.164 -0.035  0.065 -0.110  0.214 -0.085 -0.085  0.015  0.065  0.040  0.140 -0.010  0.314  0.065  0.214 -0.060 -0.085 -0.060  0.613  0.040 -0.135  0.090  0.862  0.414  0.264 -0.035  0.115  0.339 -0.035  0.090  0.189  0.189 -0.035 -0.010  0.737 -0.060 -0.010 
-0.090  0.159  0.308  0.034 -0.090  0.009  0.059  0.308  0.134  0.807  0.807  0.184  0.159  0.134 -0.090  0.159 -0.090  0.259 -0.065 -0.015  0.009  0.134  0.034  0.159  0.084  0.408  0.159  0.458 -0.115 -0.090 -0.115  0.732  0.034 -0.140  0.059  0.807  0.582  0.308  0.059  0.234  0.533 -0.040  0.209  0.308  0.284 -0.015  0.034  0.807 -0.065 -0.015 
-0.042  0.182  0.306  0.032 -0.017  0.007  0.132  0.506  0.157  0.780  0.780  0.282  0.182  0.107 -0.067  0.182 -0.117  0.306 -0.017  0.007 -0.017  0.107  0.082  0.207  0.082  0.456  0.257  0.481 -0.117 -0.117 -0.117  0.730  0.007 -0.167  0.082  0.780  0.680  0.356  0.032  0.257  0.556 -0.067  0.232  0.381  0.257  0.007  0.032  0.780 -0.092 -0.042 
-0.046  0.178  0.302  0.028  0.028  0.003  0.128  0.527  0.278  0.751  0.726  0.552  0.278  0.078 -0.046  0.228 -0.146  0.427  0.103  0.003  0.003  0.128  0.103  0.377  0.103  0.477  0.327  0.552 -0.121 -0.071 -0.121  0.701  0.003 -0.146  0.103  0.751  0.701  0.327  0.078  0.278  0.601  0.028  0.278  0.477  0.402  0.003  0.003  0.751 -0.121 -0.121 
-0.028  0.196  0.271  0.047  0.022 -0.028  0.146  0.520  0.321  0.744  0.719  0.570  0.296  0.072 -0.003  0.221 -0.128  0.421  0.122  0.022  0.047  0.122  0.146  0.396  0.122  0.520  0.321  0.545 -0.103 -0.078 -0.128  0.695 -0.003 -0.177  0.122  0.744  0.695  0.346  0.097  0.296  0.570  0.047  0.321  0.520  0.421  0.022 -0.003  0.744 -0.152 -0.128 
 0.031  0.255  0.230  0.031  0.056 -0.044  0.230  0.529  0.429  0.704  0.679  0.704  0.355  0.131  0.106  0.280 -0.119  0.479  0.131 -0.019  0.056  0.081  0.131  0.429  0.131  0.529  0.330  0.604 -0.044 -0.094 -0.069  0.679 -0.019 -0.193  0.155  0.679  0.654  0.355  0.106  0.305  0.554  0.081  0.380  0.504  0.454  0.031 -0.019  0.704 -0.143 -0.143 
 0.031  0.255  0.230  0.031  0.056 -0.069  0.230  0.504  0.454  0.704  0.679  0.704  0.355  0.131  0.106  0.305 -0.119  0.479  0.106 -0.044  0.081  0.056  0.106  0.454  0.155  0.529  0.330  0.604  0.006 -0.094 -0.069  0.654 -0.019 -0.193  0.155  0.679  0.604  0.355  0.106  0.280  0.554  0.081  0.405  0.504  0.479  0.006 -0.019  0.679 -0.143 -0.193 
 0.056  0.256  0.156  0.056  0.056 -0.068  0.231  0.480  0.455  0.704  0.679  0.704  0.405  0.156  0.181  0.281 -0.068  0.480  0.106 -0.093  0.106  0.031  0.131  0.455  0.156  0.530  0.380  0.604  0.056 -0.143 -0.068  0.604 -0.043 -0.193  0.156  0.629  0.629  0.355  0.056  0.256  0.555  0.131  0.455  0.530  0.505  0.031 -0.018  0.654 -0.168 -0.193 
 0.153  0.228  0.128  0.053  0.053 -0.071  0.203  0.477  0.452  0.701  0.676  0.701  0.452  0.153  0.178  0.278 -0.046  0.477  0.103 -0.121  0.103  0.003  0.153  0.452  0.153  0.527  0.452  0.601  0.053 -0.146 -0.021  0.601 -0.046 -0.196  0.128  0.626  0.626  0.352  0.053  0.253  0.527  0.153  0.427  0.552  0.527  0.053 -0.021  0.651 -0.146 -0.171 
 0.220  0.245  0.121  0.071  0.046 -0.054  0.295  0.444  0.469  0.694  0.669  0.694  0.469  0.195  0.195  0.295 -0.079  0.420  0.096 -0.178  0.096 -0.004  0.145  0.444  0.170  0.494  0.469  0.594  0.071 -0.153  0.046  0.594 -0.029 -0.203  0.121  0.569  0.594  0.320  0.071  0.245  0.519  0.170  0.444  0.569  0.544  0.046 -0.054  0.594 -0.153 -0.178 
 0.266  0.241  0.117  0.092  0.017 -0.033  0.316  0.440  0.465  0.690  0.665  0.690  0.465  0.191  0.191  0.391 -0.083  0.416  0.067 -0.182  0.092 -0.008  0.142  0.465  0.166  0.490  0.490  0.615  0.042 -0.157  0.092  0.565 -0.008 -0.207  0.117  0.565  0.565  0.341  0.117  0.216  0.515  0.166  0.391  0.540  0.540  0.042 -0.033  0.590 -0.182 -0.182 
 0.382  0.282  0.108  0.108 -0.017 -0.017  0.307  0.407  0.456  0.681  0.631  0.681  0.481  0.182  0.207  0.407 -0.092  0.431  0.058 -0.191  0.058 -0.017  0.133  0.431  0.182  0.531  0.481  0.606  0.058 -0.166  0.108  0.531 -0.017 -0.191  0.108  0.556  0.531  0.407  0.182  0.207  0.531  0.182  0.332  0.531  0.556  0.083 -0.042  0.531 -0.191 -0.191 
 0.478  0.254  0.104  0.104  0.004 -0.020  0.328  0.378  0.453  0.652  0.627  0.677  0.478  0.179  0.204  0.403 -0.095  0.428  0.004 -0.195  0.029 -0.020  0.129  0.403  0.179  0.528  0.478  0.602  0.029 -0.145  0.104  0.553  0.004 -0.195  0.104  0.528  0.528  0.403  0.254  0.204  0.528  0.179  0.303  0.453  0.553  0.079 -0.045  0.503 -0.195 -0.170 
 0.522  0.273  0.099  0.173 -0.001 -0.001  0.323  0.373  0.423  0.647  0.622  0.672  0.497  0.198  0.198  0.398 -0.150  0.398 -0.001 -0.200  0.024 -0.051  0.148  0.398  0.198  0.522  0.447  0.547  0.024 -0.126  0.099  0.547 -0.001 -0.175  0.099  0.522  0.522  0.398  0.323  0.273  0.522  0.173  0.248  0.447  0.547  0.099 -0.076  0.497 -0.175 -0.175 
 0.520  0.271  0.146  0.221 -0.003 -0.003  0.296  0.371  0.421  0.645  0.620  0.670  0.495  0.246  0.196  0.396 -0.152  0.396 -0.003 -0.202  0.022 -0.053  0.146  0.396  0.221  0.495  0.445  0.520  0.047 -0.103  0.097  0.545 -0.028 -0.177  0.097  0.520  0.520  0.396  0.346  0.296  0.520  0.171  0.221  0.445  0.545  0.097 -0.078  0.495 -0.177 -0.177 
 0.516  0.291  0.142  0.242 -0.032  0.017  0.316  0.366  0.416  0.640  0.615  0.665  0.466  0.267  0.167  0.416 -0.157  0.366 -0.007 -0.207 -0.007 -0.082  0.142  0.366  0.217  0.566  0.441  0.516  0.042 -0.082  0.092  0.541 -0.032 -0.182  0.067  0.516  0.516  0.391  0.391  0.291  0.516  0.192  0.217  0.466  0.541  0.067 -0.057  0.491 -0.182 -0.182 
 0.513  0.288  0.164  0.288 -0.060  0.039  0.313  0.363  0.413  0.612  0.612  0.662  0.463  0.288  0.164  0.413 -0.160  0.338  0.014 -0.210  0.014 -0.085  0.139  0.388  0.189  0.587  0.413  0.513  0.014 -0.085  0.089  0.513 -0.035 -0.185  0.014  0.513  0.513  0.388  0.388  0.288  0.513  0.189  0.214  0.488  0.538  0.089 -0.060  0.463 -0.160 -0.185 
 0.513  0.264  0.164  0.288 -0.085  0.039  0.313  0.363  0.413  0.612  0.612  0.662  0.463  0.288  0.139  0.413 -0.160  0.288  0.039 -0.210 -0.010 -0.085  0.139  0.338  0.139  0.587  0.438  0.513 -0.010 -0.085  0.064  0.513 -0.035 -0.185  0.014  0.488  0.513  0.388  0.388  0.313  0.488  0.189  0.189  0.488  0.538  0.114 -0.035  0.463 -0.160 -0.185 
 0.501  0.252  0.127  0.202 -0.097  0.002  0.376  0.326  0.376  0.650  0.600  0.725  0.376  0.227  0.177  0.451 -0.097  0.227  0.027 -0.197  0.052 -0.097  0.052  0.376  0.202  0.551  0.301  0.401  0.027 -0.022  0.077  0.476  0.052 -0.147  0.027  0.551  0.252  0.301  0.227  0.301  0.451  0.177  0.202  0.476  0.501  0.002 -0.047  0.376 -0.097 -0.147 
 0.300  0.226  0.126  0.126 -0.073  0.001  0.300  0.276  0.325  0.699  0.599  0.699  0.375  0.201  0.076  0.450 -0.048  0.251 -0.023 -0.148  0.026 -0.023  0.076  0.176  0.176  0.400  0.276  0.375  0.051  0.001  0.026  0.325  0.101 -0.073 -0.023  0.550  0.201  0.226  0.201  0.251  0.400  0.026  0.176  0.425  0.525 -0.023  0.001  0.176 -0.048 -0.048 
 0.248  0.173  0.073  0.098 -0.051 -0.026  0.223  0.297  0.273  0.696  0.621  0.696  0.273  0.223  0.023  0.422 -0.051  0.148 -0.026 -0.126  0.023 -0.026  0.098  0.198  0.173  0.397  0.248  0.248  0.048 -0.001  0.023  0.273  0.073 -0.076 -0.001  0.547  0.098  0.223  0.173  0.248  0.422 -0.001  0.148  0.372  0.497 -0.026  0.023  0.148 -0.026 -0.026 
 0.156  0.081  0.106  0.031 -0.043 -0.043  0.056  0.231  0.156  0.729  0.629  0.729  0.181  0.156  0.031  0.281 -0.018  0.131 -0.018 -0.093  0.031  0.006  0.131  0.056  0.156  0.355  0.256  0.131 -0.018 -0.068  0.031  0.281  0.106 -0.043  0.031  0.579  0.056  0.131  0.081  0.206  0.405 -0.018  0.156  0.256  0.480  0.006  0.006  0.081 -0.043  0.031 
 0.090  0.065  0.090 -0.009 -0.059 -0.059  0.015  0.190  0.140  0.788  0.638  0.688  0.140  0.115  0.015  0.190 -0.009  0.140 -0.034 -0.084  0.040  0.015  0.115  0.040  0.140  0.314  0.190  0.190 -0.034 -0.059  0.015  0.265  0.090 -0.034  0.015  0.663  0.090  0.090  0.040  0.140  0.364 -0.009  0.140  0.215  0.489  0.015 -0.034  0.090 -0.034  0.015 
 0.079  0.004  0.104 -0.020 -0.045 -0.070  0.004  0.179  0.104  0.827  0.602  0.677  0.129  0.079  0.029  0.129  0.004  0.154 -0.045 -0.070  0.029  0.029  0.079  0.029  0.054  0.179  0.154  0.129 -0.045 -0.045  0.004  0.254  0.104 -0.020  0.029  0.677  0.079  0.054  0.054  0.104  0.303 -0.020  0.129  0.154  0.403  0.029 -0.020  0.104 -0.020 -0.020 
 0.081 -0.018  0.106  0.006 -0.043 -0.068  0.006  0.156  0.106  0.853  0.579  0.679  0.106  0.081  0.031  0.106  0.006  0.131 -0.043 -0.068  0.031  0.031  0.081  0.031  0.056  0.181  0.106  0.081 -0.043 -0.043  0.006  0.256  0.106 -0.018  0.031  0.729  0.081  0.056  0.056  0.106  0.305 -0.018  0.056  0.131  0.405  0.031 -0.018  0.106 -0.018 -0.018 
 0.063 -0.036  0.063  0.013 -0.036 -0.061 -0.011  0.113  0.063  0.910  0.512  0.661  0.038  0.088 -0.011  0.063  0.013  0.113 -0.061 -0.061  0.013  0.013  0.038 -0.011  0.038  0.088  0.063  0.088 -0.036 -0.036  0.013  0.213  0.113 -0.011  0.038  0.761  0.088  0.038  0.063  0.088  0.263 -0.011  0.038  0.113  0.238  0.038 -0.011  0.113 -0.011 -0.036 
 0.065 -0.034  0.015  0.015 -0.059 -0.059 -0.009  0.065  0.065  0.962  0.414  0.613  0.040  0.090 -0.009  0.015 -0.009  0.065 -0.059 -0.034  0.015  0.015  0.040 -0.009  0.040  0.065  0.065  0.040 -0.034 -0.034  0.015  0.190  0.115 -0.034  0.015  0.862  0.090  0.040  0.040  0.065  0.240 -0.009  0.015  0.090  0.215  0.040 -0.009  0.140 -0.009 -0.034 
 0.073 -0.027  0.023  0.023 -0.052 -0.052 -0.002  0.073  0.048  0.970  0.247  0.471 -0.002  0.048 -0.027 -0.027 -0.002 -0.002 -0.052 -0.027 -0.002 -0.002  0.048 -0.002 -0.002  0.048  0.073  0.023 -0.027 -0.027  0.023  0.123  0.048 -0.052  0.023  0.920  0.073  0.048  0.023  0.048  0.147 -0.002 -0.002  0.098  0.123  0.048 -0.002  0.098  0.023 -0.027 
 0.029 -0.020  0.029  0.029 -0.045 -0.045 -0.045  0.029  0.054  0.976  0.179  0.179 -0.020  0.029 -0.045 -0.020  0.004  0.004 -0.045 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.054  0.079  0.004 -0.020 -0.020  0.004  0.079  0.004 -0.045  0.029  0.976  0.054  0.029 -0.020  0.054  0.054 -0.020  0.004  0.104  0.054  0.029  0.004  0.079  0.029 -0.020 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.016 -0.016  0.034  0.034 -0.041 -0.041 -0.041  0.034  0.059  0.981  0.158  0.009 -0.016  0.034 -0.041 -0.016 -0.016  0.009 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.016  0.059  0.059  0.009 -0.016 -0.016  0.009  0.084  0.009 -0.041  0.034  0.981  0.059  0.034 -0.016  0.034  0.034 -0.016  0.009  0.059  0.009  0.009  0.009  0.084  0.034 -0.016 
-0.043 -0.043  0.106  0.056 -0.068 -0.018 -0.043  0.031  0.081  0.953  0.330  0.006  0.081  0.031 -0.018 -0.018 -0.043  0.006 -0.068  0.006  0.031 -0.018  0.031 -0.018  0.006  0.056  0.106  0.181 -0.018 -0.018 -0.018  0.131  0.031 -0.068  0.006  0.953  0.106  0.081 -0.043  0.006  0.081 -0.043  0.081  0.156  0.031 -0.018 -0.018  0.405  0.056 -0.043 
-0.096 -0.046  0.278  0.078 -0.121 -0.021 -0.071  0.103  0.078  0.900  0.576  0.003  0.228  0.003  0.003  0.003 -0.046  0.103 -0.046  0.028  0.003  0.003  0.028  0.053 -0.046  0.228  0.402  0.502 -0.046 -0.071  0.003  0.203  0.153 -0.121  0.028  0.900  0.203  0.153  0.003  0.128  0.153  0.103  0.153  0.327  0.053 -0.046  0.003  0.676  0.028 -0.021 
-0.095  0.055  0.304  0.055 -0.169  0.005  0.005  0.229  0.154  0.852  0.703  0.105  0.379  0.005  0.030  0.005 -0.045  0.130 -0.045 -0.020 -0.020 -0.045  0.005  0.105 -0.045  0.428  0.603  0.727 -0.070 -0.070 -0.020  0.279  0.179 -0.095  0.055  0.852  0.254  0.279 -0.020  0.130  0.229  0.055  0.204  0.478  0.030  0.030  0.030  0.802 -0.045 -0.045 
-0.102 -0.002  0.396  0.072 -0.227 -0.027  0.097  0.396  0.197  0.795  0.795  0.247  0.546  0.022  0.022  0.022 -0.102  0.197 -0.002 -0.002 -0.052  0.022  0.022  0.197  0.047  0.570  0.770  0.770 -0.052 -0.052  0.072  0.471  0.172 -0.102  0.072  0.795  0.371  0.247  0.047  0.122  0.396  0.072  0.247  0.645  0.122  0.072 -0.002  0.795 -0.102 -0.102 
-0.075 -0.000  0.398  0.049 -0.250 -0.000  0.124  0.498  0.298  0.772  0.772  0.323  0.572  0.074  0.024  0.024 -0.100  0.199  0.024 -0.000 -0.025  0.049 -0.000  0.224  0.049  0.597  0.747  0.747 -0.075 -0.075  0.049  0.572  0.149 -0.125  0.049  0.772  0.423  0.224  0.049  0.199  0.473  0.074  0.224  0.622  0.124  0.099 -0.000  0.772 -0.100 -0.075 
 0.000  0.125  0.399  0.100 -0.274 -0.025  0.125  0.523  0.399  0.747  0.747  0.498  0.573  0.125  0.000  0.100 -0.075  0.274  0.100 -0.025  0.000  0.025  0.050  0.324  0.125  0.648  0.698  0.673 -0.050 -0.075  0.000  0.673  0.125 -0.149  0.075  0.722  0.573  0.174  0.075  0.249  0.548  0.075  0.224  0.673  0.224  0.075  0.025  0.747 -0.125 -0.125 
 0.022  0.171  0.371  0.097 -0.277 -0.053  0.146  0.520  0.445  0.719  0.744  0.645  0.545  0.122  0.022  0.171 -0.078  0.296  0.122 -0.028  0.022  0.022  0.072  0.346  0.122  0.620  0.645  0.670 -0.003 -0.103 -0.028  0.670  0.072 -0.152  0.097  0.695  0.595  0.196  0.072  0.221  0.545  0.072  0.196  0.595  0.296  0.022 -0.003  0.744 -0.128 -0.128 
 0.061  0.235  0.360  0.111 -0.288 -0.014  0.235  0.509  0.434  0.709  0.709  0.659  0.559  0.185  0.111  0.260 -0.114  0.335  0.136 -0.064  0.061 -0.014  0.086  0.434  0.160  0.609  0.634  0.659  0.061 -0.114 -0.014  0.659  0.061 -0.188  0.086  0.684  0.584  0.235  0.036  0.235  0.509  0.111  0.210  0.584  0.385 -0.014 -0.014  0.709 -0.139 -0.139 
 0.106  0.256  0.355  0.131 -0.268 -0.018  0.256  0.505  0.430  0.704  0.679  0.679  0.555  0.181  0.156  0.256 -0.118  0.330  0.156 -0.068  0.081 -0.018  0.081  0.455  0.156  0.604  0.629  0.654  0.056 -0.118 -0.018  0.654  0.056 -0.193  0.106  0.679  0.579  0.231  0.031  0.256  0.505  0.106  0.206  0.629  0.405  0.006 -0.018  0.704 -0.093 -0.143 
 0.152  0.301  0.326  0.127 -0.247  0.002  0.277  0.476  0.426  0.700  0.675  0.700  0.551  0.177  0.227  0.252 -0.122  0.326  0.152 -0.122  0.077 -0.022  0.077  0.501  0.202  0.575  0.625  0.650  0.052 -0.122  0.002  0.650  0.052 -0.197  0.127  0.650  0.600  0.227  0.002  0.277  0.501  0.102  0.202  0.625  0.501  0.027 -0.022  0.625 -0.122 -0.147 
 0.197  0.297  0.322  0.123 -0.226 -0.002  0.297  0.471  0.422  0.671  0.671  0.696  0.546  0.172  0.272  0.372 -0.127  0.322  0.147 -0.127  0.073 -0.027  0.123  0.521  0.197  0.546  0.596  0.646  0.048 -0.127 -0.002  0.646  0.073 -0.201  0.123  0.646  0.621  0.222  0.048  0.247  0.496  0.098  0.197  0.621  0.521  0.023 -0.027  0.596 -0.127 -0.127 
 0.293  0.293  0.269  0.119 -0.205  0.044  0.343  0.443  0.418  0.667  0.667  0.692  0.543  0.194  0.293  0.443 -0.130  0.318  0.144 -0.130  0.094 -0.030  0.144  0.493  0.194  0.543  0.568  0.642  0.044 -0.105  0.044  0.642  0.069 -0.205  0.119  0.617  0.592  0.244  0.069  0.293  0.493  0.094  0.194  0.617  0.543 -0.005 -0.030  0.568 -0.155 -0.130 
 0.411  0.311  0.237  0.112 -0.162  0.062  0.336  0.436  0.411  0.660  0.660  0.685  0.536  0.187  0.286  0.486 -0.162  0.311  0.112 -0.137  0.087 -0.037  0.137  0.511  0.187  0.536  0.561  0.635  0.037 -0.062  0.037  0.635  0.062 -0.187  0.112  0.610  0.561  0.237  0.062  0.311  0.486  0.087  0.187  0.610  0.536 -0.012 -0.037  0.511 -0.137 -0.112 
 0.503  0.328  0.179  0.129 -0.145  0.104  0.353  0.428  0.428  0.652  0.652  0.677  0.528  0.179  0.303  0.503 -0.170  0.254  0.104 -0.145  0.079 -0.045  0.129  0.478  0.204  0.528  0.528  0.627  0.029 -0.045  0.029  0.627  0.054 -0.195  0.079  0.602  0.553  0.254  0.079  0.353  0.478  0.104  0.179  0.602  0.503 -0.020 -0.020  0.503 -0.120 -0.120 
 0.502  0.328  0.153  0.153 -0.121  0.104  0.353  0.427  0.427  0.652  0.652  0.677  0.527  0.178  0.303  0.527 -0.170  0.253  0.104 -0.145  0.079 -0.046  0.129  0.477  0.203  0.527  0.527  0.627  0.029 -0.021  0.029  0.627  0.029 -0.170  0.079  0.602  0.552  0.253  0.079  0.378  0.502  0.104  0.178  0.602  0.502 -0.021 -0.021  0.502 -0.145 -0.121 
 0.549  0.325  0.150  0.175 -0.124  0.076  0.375  0.425  0.425  0.649  0.649  0.674  0.524  0.175  0.300  0.524 -0.198  0.250  0.101 -0.173  0.101 -0.049  0.126  0.474  0.200  0.524  0.524  0.599  0.026 -0.024  0.026  0.549  0.026 -0.173  0.076  0.574  0.549  0.250  0.101  0.375  0.499  0.101  0.175  0.599  0.499 -0.024 -0.024  0.474 -0.148 -0.148 
 0.525  0.325  0.151  0.201 -0.123  0.051  0.375  0.425  0.425  0.649  0.649  0.674  0.525  0.176  0.300  0.525 -0.198  0.251  0.126 -0.173  0.101 -0.048  0.126  0.475  0.176  0.525  0.525  0.599  0.026 -0.023  0.026  0.550  0.026 -0.198  0.051  0.574  0.550  0.251  0.101  0.400  0.475  0.101  0.176  0.599  0.500 -0.023 -0.023  0.475 -0.123 -0.148 
 0.527  0.327  0.153  0.203 -0.121  0.053  0.377  0.402  0.427  0.651  0.651  0.676  0.527  0.178  0.302  0.502 -0.196  0.253  0.128 -0.171  0.103 -0.046  0.128  0.477  0.178  0.502  0.527  0.601  0.028 -0.021  0.028  0.527  0.028 -0.196  0.053  0.576  0.552  0.253  0.103  0.402  0.477  0.103  0.178  0.601  0.502 -0.021 -0.021  0.477 -0.121 -0.146 
 0.575  0.326  0.152  0.202 -0.122  0.077  0.376  0.401  0.426  0.650  0.650  0.675  0.526  0.177  0.301  0.501 -0.197  0.277  0.127 -0.172  0.102 -0.047  0.127  0.451  0.177  0.501  0.526  0.600  0.027 -0.022  0.027  0.501  0.027 -0.172  0.052  0.575  0.575  0.277  0.102  0.401  0.501  0.102  0.177  0.600  0.501 -0.022 -0.022  0.451 -0.122 -0.147 
 0.576  0.327  0.153  0.228 -0.121  0.103  0.377  0.402  0.427  0.651  0.626  0.676  0.527  0.178  0.302  0.502 -0.196  0.278  0.128 -0.171  0.103 -0.046  0.128  0.427  0.153  0.502  0.527  0.601  0.028 -0.021  0.003  0.452  0.003 -0.171  0.028  0.576  0.576  0.278  0.103  0.427  0.502  0.103  0.153  0.576  0.502 -0.021 -0.021  0.427 -0.121 -0.146 
 0.552  0.228  0.079  0.178 -0.071  0.029  0.303  0.328  0.403  0.652  0.677  0.677  0.502  0.203  0.228  0.577 -0.121  0.328  0.079 -0.170  0.129 -0.021  0.153  0.328  0.178  0.452  0.502  0.477  0.004 -0.021  0.004  0.403  0.054 -0.145  0.004  0.602  0.303  0.228  0.079  0.303  0.502  0.153  0.129  0.502  0.502 -0.021 -0.071  0.278 -0.121 -0.121 
 0.442  0.168  0.119  0.143 -0.106  0.044  0.343  0.343  0.393  0.667  0.692  0.716  0.368  0.218  0.143  0.492 -0.056  0.318  0.019 -0.131  0.044 -0.031  0.094  0.218  0.193  0.418  0.442  0.293  0.069 -0.031  0.044  0.268  0.094 -0.056  0.019  0.542  0.243  0.143  0.119  0.318  0.492  0.119  0.168  0.492  0.517 -0.031 -0.006  0.143 -0.056 -0.031 
 0.431  0.157  0.107  0.157 -0.092  0.057  0.331  0.306  0.356  0.680  0.730  0.705  0.356  0.232  0.132  0.481 -0.042  0.306  0.032 -0.142  0.032 -0.017  0.082  0.207  0.157  0.356  0.406  0.232  0.082 -0.017  0.082  0.257  0.107 -0.042  0.007  0.531  0.157  0.107  0.132  0.232  0.481  0.082  0.182  0.506  0.506 -0.017  0.007  0.132 -0.042 -0.017 
 0.293  0.069  0.094  0.044 -0.056 -0.006  0.268  0.318  0.218  0.716  0.741  0.692  0.293  0.193  0.069  0.393 -0.031  0.243 -0.006 -0.106  0.019  0.019  0.119  0.193  0.193  0.268  0.268  0.193  0.019 -0.031  0.044  0.243  0.094 -0.056  0.019  0.567  0.069  0.019  0.119  0.143  0.442  0.019  0.168  0.418  0.492 -0.006  0.019  0.094 -0.031  0.019 
 0.232  0.057  0.107  0.007 -0.042 -0.042  0.257  0.306  0.132  0.730  0.805  0.556  0.157  0.132  0.032  0.331 -0.042  0.232 -0.017 -0.092  0.032  0.032  0.132  0.182  0.132  0.257  0.232  0.057 -0.017 -0.017  0.007  0.232  0.107 -0.042  0.032  0.556  0.107  0.032  0.107  0.132  0.456 -0.017  0.182  0.356  0.506  0.007  0.032  0.057 -0.017  0.007 
 0.122  0.022  0.122 -0.052 -0.052 -0.052  0.147  0.321  0.047  0.745  0.919  0.496  0.122  0.122 -0.002  0.197 -0.027  0.197 -0.002 -0.077  0.047  0.022  0.147  0.172  0.072  0.172  0.222  0.072 -0.027 -0.027 -0.002  0.222  0.097 -0.027  0.047  0.595  0.097  0.022  0.047  0.122  0.396 -0.002  0.147  0.222  0.471  0.022 -0.027  0.072 -0.027 -0.027 
 0.130  0.005  0.105 -0.044 -0.044 -0.044  0.105  0.230  0.055  0.753  0.927  0.454  0.105  0.130 -0.044  0.130 -0.019  0.155 -0.019 -0.069  0.030  0.030  0.080  0.155  0.055  0.130  0.180  0.080 -0.044 -0.019  0.005  0.205  0.105 -0.019  0.055  0.603  0.105  0.005  0.055  0.105  0.354 -0.019  0.130  0.180  0.329  0.030 -0.019  0.080 -0.019 -0.019 
 0.062 -0.063  0.062  0.012 -0.038 -0.063  0.012  0.161  0.037  0.884  0.959  0.386  0.112  0.062 -0.038  0.087  0.012  0.137 -0.038 -0.063  0.037  0.012  0.087  0.137  0.037  0.087  0.112  0.037 -0.038 -0.013  0.012  0.161  0.112  0.012  0.062  0.610  0.112 -0.013  0.037  0.087  0.261 -0.013  0.087  0.087  0.311  0.012 -0.013  0.087 -0.013 -0.038 
 0.040 -0.060  0.065  0.015 -0.035 -0.060  0.015  0.140  0.040  0.937  0.962  0.314  0.115  0.040 -0.035  0.065  0.015  0.115 -0.035 -0.060  0.015 -0.010  0.065  0.090 -0.010  0.090  0.090  0.040 -0.035 -0.010  0.015  0.140  0.090  0.015  0.040  0.588  0.065 -0.010  0.040  0.090  0.214 -0.010  0.090  0.090  0.214  0.015 -0.010  0.065 -0.010 -0.035 
-0.000 -0.050  0.024  0.024 -0.050 -0.050 -0.025  0.024  0.024  0.971  0.971  0.049  0.049  0.049 -0.050  0.074 -0.000  0.099 -0.025 -0.050 -0.000 -0.000  0.024  0.099 -0.000  0.099  0.074 -0.000 -0.025 -0.000 -0.000  0.124  0.049 -0.000  0.049  0.572  0.074  0.024  0.024  0.074  0.124 -0.025  0.049  0.074  0.049  0.024 -0.000  0.074 -0.000 -0.025 
 0.000 -0.050  0.025  0.025 -0.050 -0.050 -0.025  0.025  0.000  0.972  0.972  0.025  0.050  0.050 -0.050  0.050  0.000  0.100 -0.025 -0.050  0.000  0.000  0.025  0.100 -0.025  0.100  0.075  0.000 -0.025  0.000  0.000  0.125  0.050 -0.025  0.050  0.573  0.075  0.025  0.000  0.075  0.125 -0.025  0.050  0.075  0.050  0.025  0.000  0.075  0.000 -0.025 
-0.022 -0.047  0.028  0.028 -0.047 -0.047 -0.022  0.028  0.003  0.975  0.975  0.003  0.053  0.053 -0.047  0.053  0.003  0.103 -0.022 -0.047 -0.022  0.003  0.028  0.103 -0.022  0.103  0.078  0.003 -0.022  0.003  0.003  0.128  0.053 -0.022  0.028  0.451  0.078  0.028  0.003  0.078  0.103 -0.022  0.053  0.078  0.028  0.028  0.003  0.053 -0.022 -0.022 
-0.018 -0.043 -0.018  0.031 -0.043 -0.043 -0.018  0.006 -0.018  0.978  0.978  0.006  0.056  0.056 -0.043  0.056 -0.018  0.081 -0.018 -0.043 -0.018  0.006  0.031  0.106 -0.018  0.106  0.031  0.006 -0.018 -0.018  0.006  0.106  0.031 -0.018  0.031  0.281  0.056  0.006  0.006  0.081  0.106 -0.018  0.031  0.031  0.031  0.031  0.006  0.056 -0.043 -0.018 
-0.016 -0.041 -0.016  0.034 -0.041 -0.041 -0.016  0.009 -0.016  0.981  0.981 -0.016  0.059  0.059 -0.041  0.059 -0.016  0.084 -0.016 -0.041 -0.016  0.009  0.034  0.109 -0.016  0.109  0.009  0.009 -0.016 -0.016  0.009  0.109  0.034 -0.016  0.009  0.158  0.059 -0.016  0.009  0.084  0.109 -0.016  0.034  0.034  0.034  0.034  0.009  0.034 -0.041 -0.016 
-0.014 -0.039 -0.014  0.035 -0.039 -0.039 -0.014  0.010 -0.014  0.982  0.982 -0.014  0.060  0.060 -0.039  0.060 -0.014  0.085 -0.014 -0.039 -0.014 -0.014  0.035  0.110 -0.014  0.110  0.010  0.010 -0.014 -0.014  0.010  0.110  0.035 -0.014  0.010  0.085  0.060 -0.014  0.010  0.035  0.110 -0.014  0.035  0.035  0.035  0.035  0.010  0.035 -0.039 -0.014 
-0.014 -0.039 -0.014  0.035 -0.039 -0.039 -0.014  0.010 -0.014  0.982  0.982 -0.014  0.060  0.060 -0.039  0.060 -0.014  0.085 -0.014 -0.039 -0.014 -0.014  0.035  0.110 -0.014  0.110  0.010  0.010 -0.014 -0.014  0.010  0.110  0.035 -0.014  0.010  0.085  0.060 -0.014  0.010  0.035  0.110 -0.014  0.035  0.035  0.035  0.035  0.010  0.035 -0.039 -0.014 
-0.014 -0.039 -0.014  0.035 -0.039 -0.039 -0.014  0.010 -0.014  0.982  0.982 -0.014  0.060  0.060 -0.039  0.060 -0.014  0.085 -0.014 -0.039 -0.014 -0.014  0.035  0.110 -0.014  0.110  0.010  0.010 -0.014 -0.014  0.010  0.110  0.035 -0.014  0.010  0.085  0.060 -0.014  0.010  0.035  0.110 -0.014  0.035  0.035  0.035  0.035  0.010  0.035 -0.039 -0.014 
-0.014 -0.039 -0.014  0.035 -0.039 -0.039 -0.014  0.010 -0.014  0.982  0.982 -0.014  0.060  0.060 -0.039  0.060 -0.014  0.085 -0.014 -0.039 -0.014 -0.014  0.035  0.110 -0.014  0.110  0.010  0.010 -0.014 -0.014  0.010  0.110  0.035 -0.014  0.010  0.085  0.060 -0.014  0.010  0.035  0.110 -0.014  0.035  0.035  0.035  0.035  0.010  0.035 -0.039 -0.014 
-0.014 -0.039 -0.014  0.035 -0.039 -0.039 -0.014  0.010 -0.014  0.982  0.982 -0.014  0.060  0.060 -0.039  0.060 -0.014  0.085 -0.014 -0.039 -0.014 -0.014  0.035  0.110 -0.014  0.110  0.010  0.010 -0.014 -0.014  0.010  0.110  0.035 -0.014  0.010  0.085  0.060 -0.014  0.010  0.035  0.110 -0.014  0.035  0.035  0.035  0.035  0.010  0.035 -0.039 -0.014 
-0.014 -0.039 -0.014  0.035 -0.039 -0.039 -0.014  0.010 -0.014  0.982  0.982 -0.014  0.060  0.060 -0.039  0.060 -0.014  0.085 -0.014 -0.039 -0.014 -0.014  0.035  0.110 -0.014  0.110  0.010  0.010 -0.014 -0.014  0.010  0.110  0.035 -0.014  0.010  0.085  0.060 -0.014  0.010  0.035  0.110 -0.014  0.035  0.035  0.035  0.035  0.010  0.035 -0.039 -0.014 
-0.033 -0.058  0.042  0.092 -0.058 -0.033 -0.033  0.042 -0.008  0.964  0.964 -0.008  0.166  0.092 -0.033  0.117 -0.008  0.166 -0.033 -0.058 -0.033 -0.008  0.042  0.092 -0.008  0.191  0.067  0.166 -0.008 -0.008 -0.008  0.166  0.042 -0.008 -0.008  0.216  0.067  0.017  0.042  0.092  0.191 -0.033  0.092  0.092  0.092  0.067  0.017  0.092 -0.033 -0.008 
-0.056 -0.081  0.093  0.043 -0.081 -0.031 -0.031  0.093 -0.031  0.915  0.915 -0.056  0.367  0.168 -0.031  0.118 -0.056  0.193  0.043 -0.056  0.093 -0.006 -0.006  0.218  0.143  0.442  0.193  0.243  0.168 -0.031  0.018  0.218  0.043 -0.056  0.043  0.517  0.093  0.018 -0.006  0.143  0.392 -0.056  0.118  0.342  0.093  0.093  0.093  0.168 -0.031 -0.031 
-0.000  0.024  0.049  0.024 -0.100 -0.050  0.024  0.124  0.049  0.871  0.871  0.024  0.423  0.174 -0.025  0.174 -0.050  0.274 -0.000 -0.050  0.074 -0.025 -0.025  0.224  0.149  0.498  0.398  0.423  0.224 -0.025  0.049  0.398  0.024 -0.050  0.024  0.622  0.049  0.074  0.049  0.149  0.498 -0.075  0.224  0.423  0.124  0.124  0.174  0.199 -0.050 -0.050 
 0.049  0.099  0.024  0.024 -0.125 -0.000  0.099  0.274  0.149  0.797  0.797  0.199  0.572  0.199  0.024  0.323 -0.075  0.348  0.124 -0.075  0.074 -0.025  0.074  0.348  0.274  0.672  0.597  0.523  0.298 -0.075  0.074  0.548  0.149 -0.075  0.024  0.747  0.099  0.074  0.124  0.199  0.647 -0.050  0.348  0.622  0.274  0.099  0.174  0.274 -0.075 -0.100 
 0.148  0.248  0.073 -0.001 -0.101  0.023  0.098  0.422  0.198  0.771  0.771  0.372  0.571  0.173  0.048  0.297 -0.101  0.322  0.123 -0.076  0.098 -0.051  0.073  0.372  0.273  0.671  0.596  0.621  0.273 -0.101  0.098  0.571  0.123 -0.101  0.023  0.721  0.198  0.048  0.098  0.273  0.621 -0.001  0.347  0.646  0.347  0.073  0.198  0.297 -0.101 -0.076 
 0.310  0.285  0.061  0.086 -0.139  0.036  0.260  0.509  0.335  0.733  0.733  0.534  0.559  0.136  0.111  0.410 -0.139  0.385  0.136 -0.139  0.111 -0.039  0.061  0.484  0.235  0.634  0.634  0.634  0.360 -0.114  0.111  0.634  0.136 -0.139  0.011  0.684  0.235  0.086  0.086  0.360  0.559  0.036  0.285  0.609  0.385  0.036  0.160  0.509 -0.114 -0.114 
 0.353  0.353  0.054  0.079 -0.170  0.029  0.353  0.502  0.328  0.726  0.702  0.602  0.527  0.129  0.153  0.403 -0.121  0.378  0.153 -0.170  0.079 -0.021  0.054  0.477  0.203  0.602  0.577  0.627  0.353 -0.121  0.129  0.602  0.153 -0.170  0.029  0.677  0.278  0.104  0.153  0.378  0.552  0.029  0.253  0.602  0.378  0.029  0.029  0.527 -0.145 -0.145 
 0.489  0.339  0.065  0.140 -0.184  0.040  0.364  0.464  0.389  0.713  0.663  0.688  0.464  0.165  0.165  0.389 -0.159  0.339  0.140 -0.209  0.040 -0.034  0.065  0.489  0.190  0.564  0.564  0.588  0.389 -0.109  0.090  0.588  0.115 -0.184  0.040  0.613  0.314  0.140  0.165  0.389  0.539  0.015  0.190  0.588  0.489 -0.109 -0.034  0.564 -0.109 -0.159 
 0.530  0.331  0.082  0.156 -0.043  0.007  0.455  0.455  0.381  0.680  0.655  0.680  0.455  0.156  0.181  0.381 -0.167  0.356  0.132 -0.217  0.032 -0.018  0.082  0.480  0.181  0.555  0.555  0.580  0.381 -0.093  0.107  0.505  0.107 -0.192  0.032  0.605  0.331  0.181  0.181  0.406  0.530  0.007  0.231  0.580  0.505 -0.118 -0.043  0.555 -0.118 -0.167 
 0.578  0.329  0.105  0.155 -0.044  0.030  0.454  0.454  0.404  0.653  0.653  0.678  0.429  0.180  0.205  0.429 -0.169  0.354  0.130 -0.219  0.055 -0.019  0.080  0.504  0.205  0.529  0.554  0.578  0.379 -0.094  0.105  0.454  0.105 -0.194  0.030  0.603  0.329  0.205  0.180  0.404  0.479  0.005  0.230  0.578  0.504 -0.119 -0.069  0.529 -0.119 -0.169 
 0.576  0.327  0.103  0.152 -0.022  0.028  0.451  0.451  0.377  0.651  0.651  0.676  0.426  0.177  0.252  0.426 -0.171  0.352  0.128 -0.221  0.053 -0.022  0.103  0.501  0.202  0.501  0.551  0.576  0.352 -0.097  0.078  0.426  0.103 -0.196  0.028  0.601  0.327  0.202  0.177  0.426  0.476  0.003  0.252  0.576  0.501 -0.122 -0.072  0.526 -0.122 -0.171 
 0.601  0.327  0.103  0.152 -0.022  0.028  0.451  0.426  0.377  0.651  0.651  0.676  0.426  0.177  0.252  0.426 -0.171  0.377  0.128 -0.221  0.053 -0.022  0.128  0.501  0.177  0.501  0.526  0.576  0.327 -0.097  0.053  0.402  0.078 -0.196  0.028  0.601  0.327  0.202  0.152  0.451  0.476  0.003  0.302  0.576  0.501 -0.097 -0.072  0.526 -0.146 -0.171 
 0.600  0.326  0.102  0.151 -0.023  0.052  0.450  0.426  0.376  0.650  0.650  0.675  0.450  0.176  0.251  0.426 -0.172  0.376  0.127 -0.222  0.052 -0.023  0.127  0.500  0.176  0.500  0.525  0.575  0.351 -0.098  0.052  0.401  0.027 -0.197  0.027  0.600  0.326  0.201  0.176  0.450  0.475  0.002  0.301  0.575  0.500 -0.098 -0.073  0.525 -0.147 -0.197 
 0.600  0.326  0.102  0.152 -0.022  0.077  0.451  0.426  0.376  0.650  0.650  0.675  0.451  0.177  0.227  0.451 -0.147  0.351  0.127 -0.222  0.077 -0.022  0.127  0.501  0.177  0.501  0.526  0.551  0.351 -0.122  0.052  0.401  0.027 -0.197  0.027  0.600  0.326  0.202  0.177  0.451  0.476  0.002  0.301  0.551  0.501 -0.097 -0.072  0.526 -0.147 -0.197 
 0.600  0.326  0.102  0.152 -0.022  0.077  0.451  0.426  0.376  0.650  0.650  0.675  0.451  0.177  0.227  0.451 -0.147  0.351  0.127 -0.222  0.077 -0.022  0.127  0.501  0.177  0.501  0.526  0.551  0.326 -0.122  0.052  0.401  0.052 -0.197  0.027  0.600  0.326  0.202  0.177  0.451  0.476  0.002  0.301  0.551  0.501 -0.097 -0.072  0.526 -0.147 -0.197 
 0.599  0.325  0.101  0.151  0.001  0.076  0.450  0.425  0.375  0.649  0.649  0.674  0.450  0.176  0.226  0.450 -0.148  0.350  0.126 -0.223  0.126 -0.023  0.126  0.500  0.176  0.500  0.525  0.525  0.325 -0.123  0.051  0.400  0.051 -0.198  0.026  0.599  0.325  0.201  0.151  0.450  0.475  0.026  0.300  0.525  0.500 -0.098 -0.073  0.525 -0.123 -0.173 
 0.599  0.325  0.101  0.150 -0.024  0.076  0.449  0.425  0.375  0.649  0.649  0.674  0.449  0.175  0.225  0.449 -0.148  0.350  0.126 -0.223  0.126 -0.024  0.126  0.499  0.175  0.499  0.524  0.524  0.350 -0.124  0.051  0.400  0.026 -0.198  0.026  0.599  0.325  0.200  0.150  0.449  0.474  0.026  0.300  0.524  0.499 -0.099 -0.074  0.524 -0.099 -0.173 
 0.600  0.326  0.102  0.152 -0.022  0.077  0.451  0.426  0.376  0.650  0.650  0.675  0.451  0.177  0.202  0.451 -0.147  0.351  0.102 -0.222  0.127 -0.022  0.102  0.501  0.177  0.501  0.526  0.526  0.351 -0.122  0.052  0.401  0.027 -0.197  0.027  0.600  0.326  0.202  0.127  0.451  0.476  0.027  0.301  0.526  0.501 -0.097 -0.072  0.501 -0.097 -0.197 
 0.599  0.325  0.101  0.151 -0.023  0.076  0.450  0.425  0.375  0.649  0.649  0.674  0.450  0.176  0.201  0.450 -0.148  0.350  0.101 -0.223  0.126 -0.023  0.101  0.500  0.176  0.500  0.525  0.525  0.350 -0.123  0.051  0.400  0.026 -0.198  0.026  0.574  0.325  0.201  0.151  0.450  0.475  0.026  0.300  0.525  0.500 -0.098 -0.073  0.450 -0.073 -0.148 
 0.601  0.352  0.103  0.152 -0.022  0.078  0.451  0.426  0.377  0.651  0.651  0.676  0.451  0.177  0.227  0.451 -0.146  0.352  0.103 -0.221  0.128 -0.022  0.128  0.501  0.177  0.501  0.526  0.501  0.327 -0.122  0.028  0.402  0.028 -0.196  0.028  0.576  0.327  0.202  0.152  0.402  0.476  0.028  0.302  0.526  0.501 -0.097 -0.097  0.451 -0.072 -0.146 

 0.991 -0.005  0.094 -0.030 -0.005 -0.030 -0.030 -0.030 -0.030  0.044  0.019 -0.005 -0.030 -0.005  0.019 -0.005 -0.030  0.019  0.019  0.044  0.019  0.044 -0.005 -0.005  0.044  0.044 -0.030  0.069 -0.005 -0.005  0.019 -0.005 -0.005 -0.030 -0.005  0.069 -0.005  0.019 -0.005 -0.005 -0.005  0.019 -0.030  0.019 -0.005 -0.005  0.019 -0.005 -0.005  0.019 
 0.997 -0.024  0.100 -0.024  0.000 -0.024 -0.024 -0.024 -0.024  0.025  0.025  0.000 -0.024 -0.024  0.025 -0.024 -0.024  0.025  0.025  0.050  0.000  0.050  0.000  0.000  0.025  0.050 -0.024  0.075  0.000 -0.024  0.000  0.000  0.000 -0.024  0.000  0.050 -0.024  0.025  0.000  0.000  0.000  0.025 -0.024  0.025  0.000  0.000  0.025  0.000  0.000  0.025 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.001 -0.020  0.104 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.029  0.029  0.054 -0.020  0.029  0.004  0.004  0.029  0.054 -0.020  0.079 -0.020 -0.020  0.004  0.004  0.004 -0.020 -0.020  0.029 -0.020  0.029  0.004  0.004 -0.020  0.029 -0.020  0.029  0.004  0.004  0.004 -0.020  0.004  0.004 
 1.000 -0.021  0.129 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021  0.029  0.029  0.004 -0.021 -0.021  0.029 -0.021 -0.021  0.029  0.029  0.054 -0.021  0.029  0.004  0.004  0.029  0.079 -0.021  0.079 -0.021 -0.021  0.004  0.004  0.004 -0.021 -0.021  0.029 -0.021  0.029  0.004  0.004 -0.021  0.029 -0.021  0.029  0.029  0.004  0.004 -0.021  0.004  0.004 
 0.998  0.002  0.151 -0.023 -0.023 -0.023 -0.023 -0.023 -0.023  0.027  0.027  0.002 -0.023 -0.023  0.027 -0.023 -0.023  0.027  0.052  0.052 -0.023  0.027  0.002  0.027  0.027  0.102 -0.023  0.077 -0.023 -0.023  0.002  0.027  0.002 -0.023 -0.023  0.052 -0.023  0.027  0.027  0.002 -0.023  0.027 -0.023  0.052  0.027  0.002  0.002 -0.023  0.002  0.002 
 0.997  0.025  0.150 -0.024 -0.024 -0.024 -0.024 -0.024 -0.024  0.075  0.025  0.000 -0.024 -0.024  0.025 -0.024 -0.024  0.050  0.025  0.050 -0.024  0.025  0.025  0.000  0.025  0.100 -0.024  0.075 -0.024 -0.024  0.000  0.100  0.000 -0.024 -0.024  0.050 -0.024  0.025  0.025  0.000 -0.024  0.025  0.000  0.025  0.025  0.000  0.025 -0.024  0.000  0.000 
 0.990  0.018  0.292 -0.032 -0.032 -0.032 -0.032  0.018 -0.032  0.118  0.018  0.068 -0.032 -0.032  0.018 -0.007 -0.032  0.068  0.018  0.043 -0.032  0.043  0.018 -0.007  0.018  0.142 -0.007  0.068 -0.032 -0.032 -0.007  0.118  0.018 -0.032 -0.032  0.142 -0.032  0.043  0.018  0.018 -0.032  0.018 -0.007  0.068  0.043 -0.007  0.018 -0.007  0.018 -0.007 
 0.964 -0.008  0.615  0.042 -0.058 -0.058 -0.033  0.067 -0.058  0.191  0.017  0.042 -0.058 -0.008 -0.008 -0.008 -0.058  0.092  0.017  0.042 -0.058  0.092  0.042  0.017  0.017  0.142  0.042  0.166 -0.008 -0.033 -0.033  0.316 -0.008 -0.058 -0.058  0.291 -0.058  0.067 -0.008  0.017  0.017  0.017 -0.008  0.266  0.017 -0.033 -0.008  0.067  0.017 -0.033 
 0.890 -0.032  0.840  0.118 -0.107 -0.057 -0.057  0.118 -0.082  0.566  0.167  0.018 -0.007 -0.032  0.068 -0.032  0.018  0.192 -0.007  0.068 -0.107  0.068  0.142  0.018 -0.007  0.217  0.068  0.317 -0.057 -0.082 -0.082  0.591 -0.007 -0.107  0.018  0.616 -0.032  0.167 -0.057  0.093  0.093  0.018  0.093  0.491 -0.007 -0.032 -0.057  0.267 -0.007 -0.057 
 0.852 -0.020  0.852  0.130 -0.144 -0.045 -0.095  0.154 -0.095  0.777  0.254  0.055  0.105 -0.020  0.105 -0.045  0.005  0.254 -0.045  0.080 -0.095  0.055  0.105  0.030  0.005  0.254  0.080  0.404 -0.045 -0.120 -0.095  0.703 -0.020 -0.120  0.055  0.727 -0.070  0.154 -0.045  0.105  0.130  0.005  0.080  0.528 -0.045  0.005 -0.095  0.379 -0.045 -0.045 
 0.806 -0.041  0.806  0.208 -0.166 -0.066 -0.141  0.233  0.008  0.806  0.507  0.108  0.158  0.033  0.158 -0.066 -0.016  0.283 -0.066  0.058 -0.091  0.083  0.058  0.108  0.033  0.283  0.108  0.507 -0.091 -0.091 -0.116  0.756 -0.066 -0.116  0.033  0.756 -0.066  0.233 -0.041  0.158  0.208  0.008  0.108  0.656 -0.041  0.058 -0.041  0.631 -0.066 -0.041 
 0.786 -0.061  0.736  0.188 -0.185 -0.086 -0.160  0.288 -0.011  0.786  0.662  0.163  0.213  0.064  0.213 -0.061 -0.036  0.313 -0.036  0.039 -0.061  0.064  0.039  0.188  0.064  0.238  0.064  0.487 -0.061 -0.111 -0.136  0.736 -0.061 -0.136  0.039  0.736 -0.011  0.263 -0.036  0.188  0.263  0.039  0.139  0.711  0.014  0.039  0.014  0.687 -0.061 -0.036 
 0.745 -0.077  0.671  0.197 -0.201 -0.102 -0.176  0.297  0.023  0.745  0.720  0.222  0.272  0.098  0.222 -0.052 -0.052  0.347 -0.052  0.023 -0.077  0.073  0.048  0.272  0.048  0.222  0.073  0.621 -0.052 -0.102 -0.102  0.720 -0.052 -0.176  0.073  0.696 -0.002  0.322  0.023  0.197  0.347  0.048  0.147  0.696  0.073  0.073  0.023  0.745 -0.077 -0.052 
 0.714 -0.083  0.614  0.191 -0.158 -0.108 -0.183  0.290  0.016  0.739  0.714  0.241  0.290  0.091  0.241 -0.033 -0.058  0.390 -0.033  0.016 -0.058  0.091  0.066  0.290  0.041  0.216  0.066  0.589 -0.058 -0.108 -0.108  0.714 -0.033 -0.183  0.116  0.689  0.016  0.340  0.041  0.216  0.365  0.091  0.191  0.689  0.166  0.066 -0.008  0.764 -0.083 -0.058 
 0.693 -0.105  0.568  0.244 -0.130 -0.105 -0.179  0.344  0.020  0.717  0.693  0.419  0.344  0.120  0.269 -0.030 -0.030  0.443 -0.005 -0.030 -0.055  0.095  0.045  0.344  0.070  0.194  0.144  0.568 -0.055 -0.105 -0.080  0.693 -0.055 -0.229  0.095  0.643  0.045  0.344  0.045  0.269  0.419  0.095  0.244  0.668  0.244  0.120 -0.030  0.717 -0.130 -0.080 
 0.660 -0.112  0.561  0.237 -0.112 -0.137 -0.187  0.336  0.037  0.710  0.685  0.461  0.361  0.112  0.262 -0.012 -0.037  0.461 -0.037 -0.037 -0.062  0.212  0.062  0.361  0.062  0.212  0.162  0.585 -0.062 -0.087 -0.012  0.660 -0.062 -0.237  0.062  0.635  0.037  0.311  0.037  0.262  0.411  0.087  0.286  0.660  0.311  0.162 -0.062  0.660 -0.137 -0.162 
 0.603 -0.095  0.404  0.254 -0.095 -0.120 -0.144  0.329  0.105  0.703  0.678  0.628  0.453  0.105  0.254  0.055 -0.020  0.453 -0.070 -0.120 -0.070  0.204  0.080  0.354  0.080  0.204  0.179  0.578 -0.070 -0.095  0.005  0.628 -0.070 -0.219  0.080  0.603  0.030  0.304  0.105  0.229  0.428  0.154  0.304  0.603  0.329  0.254 -0.095  0.628 -0.144 -0.169 
 0.600 -0.097  0.376  0.252 -0.097 -0.122 -0.147  0.326  0.102  0.700  0.675  0.625  0.451  0.077  0.277  0.077 -0.022  0.426 -0.022 -0.122 -0.097  0.202  0.077  0.351  0.102  0.177  0.177  0.551 -0.072 -0.047  0.002  0.625 -0.072 -0.222  0.027  0.575  0.027  0.301  0.102  0.301  0.426  0.177  0.301  0.625  0.326  0.326 -0.147  0.600 -0.147 -0.197 
 0.570 -0.052  0.346  0.272 -0.102 -0.102 -0.127  0.321  0.247  0.695  0.670  0.645  0.496  0.072  0.247  0.097 -0.027  0.396 -0.027 -0.127 -0.102  0.147  0.097  0.346  0.122  0.172  0.197  0.546 -0.027 -0.027 -0.002  0.595  0.022 -0.227 -0.002  0.546  0.022  0.272  0.097  0.296  0.446  0.197  0.371  0.595  0.346  0.371 -0.152  0.546 -0.102 -0.177 
 0.568 -0.054  0.344  0.270 -0.104 -0.079 -0.129  0.294  0.294  0.693  0.668  0.668  0.444  0.070  0.220  0.145 -0.054  0.369 -0.029 -0.154 -0.079  0.145  0.120  0.319  0.120  0.170  0.195  0.544 -0.029 -0.029 -0.004  0.544  0.020 -0.229 -0.054  0.519  0.020  0.195  0.145  0.294  0.469  0.220  0.394  0.568  0.344  0.369 -0.154  0.544 -0.079 -0.179 
 0.538 -0.060  0.314  0.314 -0.085 -0.085 -0.110  0.264  0.314  0.663  0.663  0.663  0.438  0.115  0.214  0.115 -0.035  0.364 -0.060 -0.184 -0.035  0.115  0.140  0.264  0.115  0.164  0.164  0.563 -0.035 -0.060  0.040  0.513  0.040 -0.234 -0.060  0.513  0.040  0.189  0.140  0.264  0.488  0.264  0.389  0.513  0.389  0.389 -0.184  0.513 -0.085 -0.184 
 0.509 -0.064  0.309  0.309 -0.089 -0.064 -0.114  0.260  0.334  0.658  0.658  0.633  0.459  0.085  0.160  0.110 -0.039  0.359 -0.089 -0.189 -0.039  0.110  0.160  0.260  0.135  0.160  0.160  0.559 -0.039 -0.064  0.035  0.509  0.035 -0.239 -0.064  0.509  0.060  0.235  0.135  0.260  0.459  0.284  0.384  0.484  0.409  0.409 -0.189  0.509 -0.114 -0.164 
 0.425 -0.048  0.325  0.300 -0.098 -0.073 -0.073  0.276  0.350  0.649  0.649  0.624  0.475  0.101  0.151  0.126 -0.048  0.350 -0.098 -0.223 -0.023  0.101  0.201  0.251  0.176  0.126  0.201  0.525 -0.048 -0.073  0.051  0.525  0.026 -0.248 -0.073  0.475  0.051  0.226  0.126  0.251  0.450  0.300  0.375  0.475  0.400  0.425 -0.173  0.500 -0.123 -0.148 
 0.390 -0.058  0.365  0.141 -0.083 -0.033 -0.033  0.141  0.216  0.565  0.540  0.639  0.465  0.091  0.166  0.066 -0.033  0.315 -0.158 -0.158 -0.058  0.041  0.091  0.166  0.066  0.141  0.091  0.415 -0.083 -0.133  0.066  0.415  0.016 -0.158 -0.058  0.490  0.091  0.216  0.116  0.216  0.415  0.191  0.241  0.415  0.340  0.415 -0.108  0.290 -0.108 -0.108 
 0.284  0.035  0.210  0.135 -0.039 -0.064 -0.064  0.110  0.210  0.484  0.484  0.384  0.284  0.035  0.160  0.010  0.010  0.235 -0.089 -0.114 -0.064  0.085  0.085  0.060  0.035  0.160  0.110  0.334 -0.114 -0.064 -0.014  0.309  0.010 -0.089 -0.089  0.509  0.035  0.210  0.010  0.135  0.210  0.185  0.185  0.309  0.309  0.260 -0.089  0.160 -0.089 -0.139 
 0.179  0.055  0.204  0.080 -0.020 -0.070 -0.070  0.105  0.179  0.404  0.528  0.304  0.179  0.055  0.179  0.030  0.055  0.254 -0.070 -0.095 -0.045  0.080  0.105  0.055 -0.020  0.154  0.130  0.229 -0.095 -0.045 -0.020  0.254  0.030 -0.070 -0.070  0.528  0.055  0.204  0.005  0.154  0.204  0.154  0.179  0.229  0.154  0.204 -0.070  0.154 -0.070 -0.120 
 0.138  0.063  0.213  0.063 -0.036 -0.061 -0.061  0.063  0.163  0.312  0.437  0.163  0.038  0.013  0.038  0.013  0.063  0.163 -0.061 -0.061 -0.036  0.063  0.038  0.038 -0.011  0.163  0.113  0.113 -0.061 -0.011 -0.061  0.213  0.013 -0.036 -0.061  0.512 -0.036  0.163  0.013  0.063  0.088  0.113  0.138  0.138  0.013  0.163 -0.061  0.063 -0.061 -0.086 
 0.126  0.051  0.175  0.051 -0.024 -0.049 -0.049  0.051  0.175  0.300  0.350  0.126  0.051  0.001  0.026  0.026  0.051  0.101 -0.049 -0.049 -0.024  0.051  0.026  0.026 -0.024  0.126  0.026  0.076 -0.049  0.001 -0.049  0.200  0.026 -0.049 -0.074  0.425 -0.024  0.150  0.026  0.051  0.101  0.101  0.051  0.126  0.001  0.101 -0.049  0.076 -0.049 -0.074 
 0.095  0.070  0.120  0.070 -0.029 -0.029 -0.029  0.020  0.120  0.220  0.270  0.095  0.020 -0.029  0.045 -0.004  0.045  0.070 -0.029 -0.029 -0.029  0.020  0.045 -0.004 -0.004  0.120  0.020  0.045 -0.054  0.020 -0.029  0.095  0.020 -0.029 -0.054  0.369 -0.029  0.095 -0.004  0.070  0.095  0.095  0.020  0.070 -0.029  0.045 -0.029 -0.004 -0.029 -0.054 
 0.087  0.062  0.062  0.087 -0.013 -0.013 -0.013 -0.013  0.037  0.137  0.186  0.062  0.012 -0.038  0.062 -0.038  0.012 -0.013  0.012 -0.038 -0.038  0.012  0.012  0.037  0.012  0.087  0.037  0.012 -0.038  0.037 -0.013  0.037  0.012 -0.038 -0.038  0.186 -0.013  0.062  0.012 -0.013  0.037  0.062 -0.038  0.062 -0.013  0.037 -0.013 -0.013 -0.038 -0.038 
 0.077  0.002  0.002  0.027 -0.023  0.002  0.002 -0.023 -0.023  0.077  0.052  0.002  0.002 -0.023  0.052 -0.023 -0.023 -0.023  0.002 -0.023 -0.023  0.027  0.002  0.052  0.002  0.077  0.002  0.002 -0.023  0.002 -0.023  0.027  0.002 -0.023 -0.023  0.052  0.002  0.052 -0.023 -0.023  0.002  0.002 -0.023  0.027  0.002 -0.023  0.002  0.002 -0.023 -0.023 
 0.053  0.003  0.003  0.028 -0.022  0.003  0.003 -0.022 -0.022  0.053  0.053  0.003  0.003 -0.022  0.053 -0.022 -0.022 -0.022  0.003 -0.022 -0.022  0.028  0.003  0.053  0.003  0.053  0.003  0.003 -0.022  0.003 -0.022  0.028  0.003 -0.022 -0.022  0.028  0.003  0.053 -0.022 -0.022  0.003  0.003 -0.022  0.028  0.003 -0.022  0.003  0.003 -0.022 -0.022 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.029 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.029  0.004 -0.020 -0.020 
 0.054  0.004  0.004  0.004  0.004  0.004  0.004 -0.021 -0.021  0.054  0.004 -0.021  0.004 -0.021  0.029 -0.021 -0.021 -0.021  0.004 -0.021 -0.021  0.029  0.004  0.029  0.004  0.079 -0.021  0.004 -0.021 -0.021 -0.021  0.004  0.004 -0.021 -0.021 -0.021  0.004  0.004 -0.021 -0.021  0.004  0.004 -0.021  0.029  0.004 -0.021  0.029  0.004 -0.021 -0.021 
 0.073 -0.002 -0.002  0.048 -0.002 -0.002 -0.002 -0.027 -0.027  0.048 -0.002 -0.027 -0.002 -0.027  0.023 -0.002 -0.027 -0.027 -0.002 -0.002 -0.027  0.048 -0.002  0.023 -0.002  0.073 -0.027 -0.002 -0.027 -0.027 -0.027  0.023 -0.002 -0.027 -0.027 -0.027 -0.002  0.023 -0.027 -0.027 -0.002 -0.002 -0.027  0.023 -0.002 -0.027  0.023 -0.002 -0.027 -0.027 
 0.078  0.003 -0.022  0.053 -0.022 -0.022  0.003 -0.047 -0.047  0.078 -0.022 -0.022 -0.022 -0.022  0.028  0.028 -0.022 -0.047 -0.022  0.003 -0.047  0.103  0.003  0.028 -0.022  0.078 -0.047  0.003 -0.047 -0.047 -0.047  0.053  0.003 -0.022 -0.047 -0.047  0.003  0.003 -0.047 -0.047 -0.022  0.003 -0.047  0.053 -0.022 -0.022  0.003  0.003 -0.047 -0.022 
 0.107 -0.018 -0.068  0.057 -0.043 -0.018 -0.018 -0.093 -0.043  0.057 -0.018  0.057 -0.018 -0.018  0.032 -0.018 -0.068 -0.018 -0.018 -0.018 -0.093  0.132 -0.018  0.057  0.007  0.107 -0.018 -0.043 -0.093 -0.043  0.007  0.082  0.032 -0.043 -0.068  0.007 -0.018  0.007 -0.068 -0.093  0.007 -0.043 -0.093  0.107 -0.018 -0.018  0.007  0.057 -0.093 -0.043 
 0.162 -0.012 -0.012  0.062 -0.037 -0.037 -0.037 -0.112 -0.062  0.112 -0.012  0.062 -0.012 -0.012  0.162 -0.062 -0.087 -0.062  0.012 -0.012 -0.137  0.087 -0.037  0.087  0.037  0.087  0.037 -0.037 -0.137  0.012  0.037  0.112  0.012 -0.062 -0.112  0.037 -0.062  0.137 -0.037 -0.137  0.012 -0.012 -0.062  0.286 -0.012  0.062 -0.012  0.062 -0.137 -0.062 
 0.120 -0.029 -0.004  0.020 -0.104 -0.079 -0.054 -0.104 -0.004  0.120  0.020  0.095 -0.029 -0.079  0.170 -0.104 -0.054 -0.029 -0.054 -0.054 -0.179  0.070  0.070  0.120  0.045  0.120  0.020 -0.079 -0.079  0.070  0.045  0.120 -0.004 -0.104 -0.154  0.045 -0.129  0.120 -0.054 -0.154 -0.004  0.045 -0.054  0.294 -0.054  0.294 -0.054  0.095 -0.154 -0.054 
 0.111 -0.063  0.011 -0.013 -0.038 -0.113 -0.088 -0.113 -0.013  0.111  0.036  0.136 -0.013 -0.113  0.111 -0.088 -0.063 -0.013 -0.038 -0.063 -0.163  0.086  0.086  0.136  0.061  0.136  0.011 -0.063 -0.088  0.036  0.011  0.136 -0.013 -0.138 -0.213  0.061 -0.138  0.111 -0.038 -0.138 -0.013  0.061 -0.013  0.285  0.011  0.310 -0.088  0.086 -0.163 -0.113 
 0.045 -0.129  0.095  0.045 -0.054 -0.154 -0.129 -0.129  0.020  0.145 -0.004  0.120  0.020 -0.129  0.070 -0.079 -0.079  0.020 -0.054 -0.079 -0.104  0.095  0.095  0.170  0.045  0.220 -0.029 -0.029 -0.054  0.020 -0.004  0.145 -0.054 -0.129 -0.279  0.020 -0.179  0.095  0.045 -0.154 -0.054  0.095  0.020  0.270 -0.004  0.344 -0.104  0.120 -0.204 -0.154 
 0.061 -0.138  0.086  0.011 -0.063 -0.163 -0.138 -0.138  0.011  0.111 -0.013  0.161  0.061 -0.063  0.061 -0.088 -0.088  0.011 -0.038 -0.113 -0.113  0.086  0.086  0.161  0.036  0.186 -0.063 -0.063 -0.038 -0.013  0.011  0.161 -0.138 -0.163 -0.287  0.061 -0.188  0.111  0.036 -0.163 -0.063  0.111 -0.038  0.285 -0.013  0.360 -0.113  0.136 -0.213 -0.163 
 0.063 -0.161  0.088 -0.011 -0.036 -0.186 -0.161 -0.111  0.013  0.113  0.038  0.163  0.038 -0.036  0.038 -0.136 -0.111  0.013 -0.061 -0.136 -0.111  0.188  0.088  0.163  0.038  0.163 -0.086 -0.011 -0.036 -0.011 -0.011  0.188 -0.161 -0.161 -0.310  0.063 -0.186  0.088  0.088 -0.136 -0.036  0.088 -0.011  0.263 -0.011  0.412 -0.136  0.138 -0.211 -0.186 
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 0.974  0.027  0.102 -0.023  0.052 -0.048 -0.048  0.002 -0.048 -0.023  0.002  0.077 -0.023  0.052 -0.023 -0.023  0.002  0.027 -0.048  0.002 -0.023 -0.048 -0.023 -0.023 -0.048 -0.023  0.002 -0.048 -0.048  0.002 -0.048  0.027 -0.023 -0.048  0.002  0.127  0.002  0.027  0.102 -0.048  0.027  0.027 -0.023  0.102  0.027  0.127  0.027  0.077  0.002 -0.048 
 0.947  0.050  0.149  0.050  0.125 -0.025 -0.050  0.000 -0.050 -0.050 -0.025  0.174 -0.025  0.025 -0.025 -0.025  0.025  0.000 -0.050  0.000 -0.025 -0.025 -0.025  0.000  0.000 -0.025  0.000 -0.075 -0.075  0.050 -0.025  0.025 -0.025 -0.075  0.050  0.149  0.025  0.000  0.125 -0.075  0.025  0.100 -0.025  0.100  0.050  0.100  0.050  0.050  0.025 -0.050 
 0.889 -0.007  0.242  0.042  0.167 -0.007 -0.082 -0.007 -0.107 -0.057 -0.032  0.391  0.042 -0.032 -0.007  0.042  0.042 -0.032 -0.032 -0.007 -0.032 -0.007 -0.032 -0.032  0.017 -0.057 -0.032 -0.132 -0.057  0.042 -0.007  0.042 -0.057 -0.107  0.042  0.167  0.042 -0.032  0.117 -0.107 -0.007  0.092 -0.032  0.267  0.142  0.167  0.017  0.017 -0.007 -0.082 
 0.840 -0.032  0.441 -0.032  0.217 -0.032 -0.032 -0.007 -0.157  0.017 -0.032  0.566  0.067 -0.032 -0.032  0.042  0.067 -0.082 -0.082 -0.057 -0.032 -0.007 -0.007 -0.082 -0.032 -0.057 -0.082 -0.132 -0.107 -0.007  0.092  0.167 -0.107 -0.107 -0.007  0.167  0.092  0.042  0.142 -0.082 -0.057  0.167 -0.057  0.366  0.142  0.142 -0.032 -0.007 -0.007 -0.107 
 0.740  0.067  0.516 -0.032  0.267 -0.057 -0.057 -0.007 -0.082  0.042 -0.032  0.590  0.117 -0.032 -0.032  0.117  0.067 -0.082 -0.082 -0.107 -0.007  0.042 -0.007 -0.082 -0.057 -0.057 -0.132 -0.132 -0.132 -0.057  0.067  0.242 -0.157 -0.107 -0.032  0.117  0.167 -0.007  0.192 -0.107 -0.082  0.192 -0.082  0.491  0.192  0.217  0.017  0.067 -0.007 -0.132 
 0.670  0.047  0.445 -0.028  0.371 -0.103 -0.078 -0.003 -0.053  0.122 -0.028  0.595  0.122 -0.053 -0.028  0.097  0.047 -0.103 -0.103 -0.103 -0.053  0.072  0.022 -0.078 -0.028 -0.028 -0.152 -0.128 -0.128 -0.078  0.047  0.246 -0.152 -0.103 -0.028  0.097  0.196 -0.028  0.196 -0.128 -0.103  0.196 -0.103  0.495  0.171  0.246  0.047  0.097 -0.003 -0.177 
 0.613 -0.009  0.489  0.065  0.364 -0.109 -0.084 -0.009 -0.034  0.165 -0.084  0.564  0.090 -0.059 -0.009  0.065  0.040 -0.159 -0.134 -0.159 -0.034  0.065  0.065 -0.109 -0.034 -0.009 -0.134 -0.134 -0.034 -0.059  0.065  0.339 -0.134 -0.159 -0.109  0.040  0.215 -0.034  0.240 -0.109 -0.134  0.140 -0.109  0.464  0.289  0.240  0.065  0.115 -0.009 -0.209 
 0.602  0.029  0.478  0.079  0.353 -0.120 -0.045 -0.020  0.004  0.179 -0.120  0.553  0.079 -0.070  0.004  0.179  0.054 -0.145 -0.120 -0.170 -0.045  0.054  0.079 -0.095 -0.020  0.004 -0.095 -0.145 -0.045 -0.045  0.054  0.353 -0.120 -0.170 -0.120  0.029  0.204 -0.045  0.254 -0.120 -0.095  0.129 -0.095  0.428  0.328  0.229  0.054  0.104 -0.020 -0.195 
 0.565  0.091  0.465  0.066  0.415 -0.108 -0.033 -0.083 -0.008  0.166 -0.083  0.440  0.091  0.041 -0.033  0.141  0.141 -0.108 -0.133 -0.208 -0.033  0.041  0.116 -0.133  0.041  0.041 -0.083 -0.133  0.041 -0.033  0.141  0.340 -0.058 -0.208 -0.183 -0.008  0.166 -0.008  0.266 -0.058 -0.058  0.141 -0.083  0.415  0.315  0.191  0.091  0.066 -0.008 -0.133 
 0.535  0.112  0.460  0.062  0.411 -0.138 -0.038 -0.113 -0.013  0.137 -0.088  0.411  0.112  0.037 -0.038  0.137  0.161 -0.113 -0.138 -0.212 -0.013  0.037  0.062 -0.088  0.037  0.037 -0.088 -0.088  0.037  0.012  0.137  0.336 -0.038 -0.212 -0.187 -0.013  0.186 -0.013  0.311 -0.038 -0.063  0.161 -0.088  0.411  0.261  0.186  0.087  0.062 -0.038 -0.113 
 0.452  0.128  0.402  0.053  0.402 -0.196 -0.021 -0.121 -0.021  0.153 -0.021  0.377  0.103  0.103 -0.071  0.128  0.153 -0.121 -0.146 -0.246 -0.021  0.103  0.103 -0.021  0.078  0.128 -0.046 -0.071  0.053  0.053  0.128  0.352 -0.046 -0.221 -0.246 -0.021  0.153 -0.071  0.377 -0.021 -0.021  0.228 -0.071  0.352  0.228  0.203  0.103  0.053 -0.046 -0.146 
 0.426  0.176  0.401  0.052  0.376 -0.197 -0.048 -0.123  0.002  0.151 -0.023  0.351  0.102  0.102 -0.048  0.127  0.151 -0.123 -0.147 -0.247 -0.048  0.102  0.102 -0.023  0.077  0.127 -0.048 -0.073  0.077  0.052  0.127  0.351 -0.023 -0.222 -0.247  0.002  0.151 -0.073  0.376 -0.023 -0.023  0.226 -0.048  0.351  0.201  0.201  0.127  0.027 -0.048 -0.147 
 0.393  0.193  0.393  0.069  0.343 -0.205 -0.056 -0.106  0.044  0.143 -0.056  0.293  0.094  0.143 -0.081  0.119  0.119 -0.056 -0.155 -0.255 -0.081  0.119  0.069 -0.031  0.094  0.119 -0.031 -0.056  0.094  0.044  0.069  0.343 -0.031 -0.230 -0.255 -0.031  0.119 -0.081  0.318 -0.031 -0.031  0.193 -0.006  0.293  0.193  0.218  0.143  0.019 -0.031 -0.131 
 0.390  0.190  0.390  0.066  0.340 -0.208 -0.059 -0.084  0.016  0.165 -0.059  0.265  0.116  0.141 -0.059  0.091  0.116 -0.009 -0.158 -0.258 -0.084  0.116  0.066 -0.009  0.066  0.141 -0.034 -0.059  0.091  0.041  0.066  0.315 -0.034 -0.233 -0.258 -0.034  0.116 -0.084  0.290 -0.034 -0.034  0.190  0.016  0.290  0.190  0.265  0.141  0.016 -0.034 -0.134 
 0.366  0.166  0.391  0.092  0.316 -0.207 -0.058 -0.083  0.017  0.166 -0.058  0.291  0.092  0.191 -0.083  0.042  0.117  0.017 -0.182 -0.232 -0.083  0.117  0.067 -0.008  0.042  0.142 -0.008 -0.033  0.092  0.017  0.042  0.291 -0.033 -0.257 -0.257 -0.033  0.117 -0.083  0.291 -0.033 -0.058  0.166  0.042  0.291  0.166  0.291  0.142  0.017 -0.083 -0.133 
 0.365  0.166  0.390  0.091  0.315 -0.208 -0.033 -0.083 -0.033  0.166 -0.058  0.290  0.091  0.191 -0.083  0.066  0.091  0.016 -0.183 -0.233 -0.083  0.091  0.066 -0.008  0.041  0.141 -0.008 -0.033  0.091  0.016  0.041  0.266 -0.058 -0.258 -0.258 -0.058  0.116 -0.083  0.290 -0.033 -0.058  0.166  0.016  0.290  0.141  0.290  0.166  0.041 -0.083 -0.133 
 0.341  0.166  0.391  0.117  0.266 -0.207 -0.033 -0.058 -0.058  0.191 -0.108  0.291  0.042  0.191 -0.108  0.067  0.092  0.092 -0.157 -0.232 -0.108  0.067  0.067 -0.008  0.017  0.142 -0.008  0.017  0.117  0.017  0.042  0.166 -0.058 -0.232 -0.257 -0.058  0.117 -0.058  0.291 -0.033 -0.083  0.166 -0.033  0.291  0.142  0.266  0.191  0.042 -0.108 -0.133 
 0.343  0.168  0.393  0.119  0.243 -0.205 -0.031 -0.056 -0.056  0.193 -0.106  0.293  0.044  0.168 -0.106  0.069  0.069  0.069 -0.155 -0.230 -0.106  0.069  0.069 -0.006 -0.006  0.143 -0.006 -0.006  0.143  0.019  0.044  0.143 -0.056 -0.230 -0.255 -0.031  0.119 -0.056  0.318 -0.056 -0.081  0.168 -0.056  0.293  0.143  0.218  0.218  0.044 -0.131 -0.131 
 0.318  0.169  0.393  0.119  0.169 -0.205 -0.030 -0.055 -0.055  0.194 -0.130  0.293  0.044  0.169 -0.130  0.069  0.069  0.094 -0.180 -0.230 -0.105  0.069  0.069 -0.005 -0.030  0.144 -0.005  0.019  0.144  0.019  0.044  0.144 -0.055 -0.205 -0.255 -0.005  0.119 -0.055  0.318 -0.055 -0.080  0.169 -0.080  0.293  0.144  0.219  0.219  0.044 -0.130 -0.130 
 0.270  0.096  0.345  0.071  0.170 -0.153 -0.054 -0.004  0.021  0.195 -0.079  0.270  0.021  0.071 -0.079  0.021  0.096  0.096 -0.129 -0.178 -0.054  0.096  0.121  0.046 -0.029  0.096 -0.004  0.046  0.096 -0.004  0.046  0.145 -0.079 -0.153 -0.203  0.021  0.096 -0.029  0.170 -0.004 -0.104  0.096 -0.004  0.220  0.145  0.245  0.096  0.046 -0.129 -0.129 
 0.229  0.104  0.328  0.104  0.054 -0.095  0.004 -0.045  0.054  0.154 -0.045  0.179  0.004  0.079  0.004  0.004  0.079  0.029 -0.120 -0.120 -0.070  0.129  0.154  0.029 -0.045  0.054  0.029  0.029  0.104 -0.020  0.079  0.154 -0.020 -0.170 -0.170  0.054 -0.045  0.004  0.129 -0.020 -0.070  0.054  0.004  0.154 -0.045  0.154  0.004  0.004 -0.045 -0.070 
 0.219  0.095  0.294  0.095 -0.005 -0.080 -0.005 -0.055  0.045  0.169 -0.030  0.169  0.020  0.095  0.020 -0.005  0.020  0.045 -0.105 -0.105 -0.055  0.095  0.169 -0.005 -0.030 -0.055  0.045  0.020  0.020 -0.005  0.095  0.120 -0.005 -0.154 -0.154  0.070 -0.080  0.020  0.095  0.020 -0.055  0.095  0.045  0.169 -0.080  0.194 -0.055  0.020 -0.030 -0.055 
 0.149  0.074  0.249  0.099 -0.050 -0.050 -0.025 -0.025 -0.025  0.199 -0.025  0.124  0.024  0.049  0.024 -0.000  0.024  0.024 -0.075 -0.100 -0.025  0.049  0.174 -0.000 -0.000 -0.050  0.049 -0.025 -0.025  0.024  0.074  0.099  0.024 -0.125 -0.125  0.074 -0.050  0.024 -0.025  0.024 -0.050  0.124  0.074  0.174 -0.050  0.149 -0.050  0.024 -0.050 -0.050 
 0.162  0.062  0.212  0.112 -0.062 -0.037 -0.012 -0.037 -0.012  0.162 -0.012  0.087  0.037  0.037  0.037 -0.012  0.037 -0.012 -0.087 -0.087 -0.012  0.012  0.087  0.012  0.012 -0.037  0.062 -0.012 -0.037  0.037  0.062  0.062 -0.012 -0.112 -0.112  0.087 -0.037  0.037 -0.037  0.037 -0.087  0.112  0.062  0.137 -0.037  0.137 -0.037  0.012 -0.062 -0.087 
 0.152  0.002  0.227  0.102 -0.047 -0.022 -0.047 -0.022  0.002  0.152 -0.047  0.052  0.027  0.052  0.027  0.002  0.052 -0.022 -0.072 -0.072  0.002  0.002  0.027  0.027  0.027 -0.022  0.077  0.002 -0.022  0.052  0.027  0.052 -0.022 -0.097 -0.097  0.102 -0.047  0.002 -0.022  0.052 -0.097  0.152  0.077  0.127 -0.022  0.152 -0.022  0.002 -0.047 -0.072 
 0.161  0.036  0.211  0.111 -0.038 -0.038 -0.038 -0.013  0.011  0.161 -0.063  0.061  0.036  0.061  0.036  0.011  0.061  0.011 -0.038 -0.088  0.011 -0.013  0.011  0.011  0.036 -0.013  0.086  0.011 -0.038 -0.013  0.036  0.061 -0.013 -0.088 -0.088  0.111 -0.038  0.011 -0.013  0.061 -0.088  0.161  0.111  0.111 -0.013  0.136 -0.013 -0.038 -0.038 -0.063 
 0.077  0.052  0.227  0.052 -0.022 -0.022 -0.047  0.002  0.027  0.127 -0.047  0.027  0.002  0.052  0.027  0.027  0.077  0.027 -0.022 -0.072 -0.022  0.002 -0.022  0.027  0.002 -0.022  0.102  0.027 -0.047  0.002 -0.022  0.027 -0.022 -0.072 -0.072  0.102 -0.047  0.002  0.002  0.077 -0.072  0.177  0.102  0.052 -0.022  0.127  0.002 -0.022 -0.047 -0.047 
 0.088  0.038  0.212  0.063 -0.012 -0.037 -0.037 -0.012  0.038  0.063 -0.037  0.013  0.013  0.013  0.038  0.013  0.088  0.038 -0.037 -0.062 -0.012  0.013 -0.012  0.038 -0.037 -0.037  0.088 -0.062 -0.037  0.013 -0.037  0.013 -0.012 -0.062 -0.062  0.113 -0.037 -0.012  0.013  0.088 -0.062  0.138  0.113  0.038 -0.012  0.113  0.013 -0.012 -0.037 -0.037 
 0.034  0.034  0.183  0.059  0.009 -0.016 -0.016  0.009  0.009  0.009 -0.041 -0.016 -0.016 -0.016 -0.016  0.034  0.109  0.034 -0.016 -0.041  0.009  0.009  0.009  0.034 -0.016 -0.041  0.034 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.041 -0.041  0.084 -0.016  0.009  0.034  0.084 -0.041  0.034  0.084  0.034  0.009  0.109  0.009  0.009 -0.016 -0.041 
 0.043  0.018  0.167 -0.007  0.018 -0.032 -0.007 -0.007  0.018  0.018 -0.032 -0.007 -0.007 -0.032 -0.007  0.043  0.093  0.018 -0.032 -0.032 -0.007 -0.032  0.018 -0.007 -0.007 -0.032  0.018 -0.032 -0.007  0.018 -0.007  0.018  0.018 -0.032 -0.032  0.068 -0.032  0.018  0.018  0.068 -0.032  0.043  0.068  0.043 -0.007  0.118 -0.007 -0.007 -0.007 -0.032 
 0.015 -0.010  0.040  0.015  0.040 -0.010 -0.010 -0.010  0.015  0.015 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010  0.040 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010  0.015  0.015  0.015  0.015 -0.010 -0.010 -0.010 -0.010 -0.010  0.015  0.065 -0.010 -0.010  0.015 -0.010  0.015  0.040 -0.010  0.015 -0.010 -0.010 
-0.005 -0.005 -0.005  0.020  0.020 -0.005 -0.005 -0.005  0.020 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005  0.020 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005 -0.005  0.045 -0.005 -0.005 -0.005 -0.005 -0.005  0.020 -0.005 -0.005 -0.005 -0.005 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 1.001  0.029  0.004  0.004  0.029 -0.020  0.004  0.004  0.104  0.004  0.004  0.054  0.029  0.029 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.004  0.004  0.004  0.004  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.079 -0.020  0.029 -0.020 -0.020  0.004 -0.020  0.029  0.054 -0.020 -0.020  0.004 
 0.998  0.026  0.001  0.001  0.051 -0.023  0.001  0.001  0.101  0.001  0.001  0.051  0.026  0.051 -0.023  0.026  0.001 -0.023 -0.023 -0.023 -0.023  0.026  0.001  0.001  0.026  0.001 -0.023  0.001  0.001  0.026  0.001  0.026  0.001  0.076  0.001 -0.023  0.001  0.001  0.101  0.001  0.026 -0.023 -0.023  0.001 -0.023  0.026  0.051 -0.023 -0.023  0.026 
 0.988  0.016 -0.008 -0.008  0.066 -0.033 -0.008 -0.008  0.091 -0.008 -0.008  0.041  0.016  0.066 -0.033  0.016  0.016 -0.033 -0.033 -0.033  0.016  0.016  0.016 -0.008  0.016 -0.008 -0.033 -0.008 -0.008  0.016 -0.008  0.016 -0.008  0.116  0.016 -0.008 -0.008  0.016  0.116 -0.008  0.016  0.016 -0.033  0.016 -0.008  0.016  0.041 -0.033 -0.033  0.041 
 0.983  0.011 -0.013  0.036  0.061 -0.038 -0.013 -0.013  0.086  0.011 -0.013  0.036  0.011  0.061 -0.013  0.036  0.036 -0.038 -0.038 -0.038  0.011  0.011  0.011 -0.013  0.011 -0.013 -0.038  0.036 -0.013  0.011  0.011  0.011  0.036  0.136  0.011 -0.013 -0.013  0.011  0.111  0.011  0.011  0.011 -0.038  0.011 -0.013  0.036  0.036 -0.038 -0.013  0.036 
 0.976  0.004 -0.021  0.029  0.104 -0.046 -0.021 -0.021  0.079  0.004 -0.021  0.029  0.004  0.079 -0.021  0.029  0.029 -0.046 -0.046 -0.046  0.004  0.004  0.029 -0.021  0.004 -0.021 -0.046  0.029 -0.021  0.004  0.029  0.004  0.054  0.253  0.004 -0.021 -0.021  0.004  0.079  0.029  0.004  0.054 -0.046  0.004  0.004  0.029  0.029 -0.046  0.004  0.029 
 0.971 -0.001 -0.026  0.024  0.148 -0.051 -0.026 -0.026  0.074 -0.001 -0.026  0.024 -0.001  0.074 -0.001  0.024  0.024 -0.051 -0.026 -0.051 -0.001 -0.001  0.024 -0.026 -0.001 -0.026 -0.051  0.024 -0.026  0.024  0.024  0.024  0.074  0.273 -0.001 -0.001 -0.026  0.024  0.124  0.049 -0.001  0.049 -0.051 -0.001 -0.001  0.024  0.024 -0.026 -0.001  0.024 
 0.942 -0.004 -0.004  0.070  0.294 -0.029  0.020 -0.004  0.145 -0.004 -0.004  0.020 -0.029  0.045  0.020  0.070  0.070 -0.029 -0.054 -0.054  0.020  0.020 -0.004 -0.054 -0.004 -0.029 -0.054  0.020 -0.029  0.070  0.170  0.020  0.120  0.568 -0.029  0.070 -0.004  0.020  0.170  0.070  0.020  0.045 -0.029 -0.029 -0.029  0.120  0.020 -0.029 -0.004 -0.004 
 0.906 -0.040  0.009  0.084  0.632 -0.065  0.059  0.009  0.159 -0.015 -0.040  0.009 -0.040  0.009  0.009  0.034  0.059 -0.040 -0.065 -0.065  0.009  0.009 -0.015 -0.065 -0.040 -0.015 -0.065  0.009  0.009  0.034  0.184  0.009  0.134  0.732 -0.040  0.109 -0.015 -0.015  0.134  0.084 -0.015  0.034 -0.040 -0.065 -0.015  0.159  0.009 -0.065 -0.015 -0.040 
 0.854 -0.043  0.007  0.082  0.754 -0.093  0.007  0.007  0.281  0.007 -0.093 -0.043 -0.068  0.007 -0.018 -0.018  0.107  0.057 -0.093 -0.043  0.057 -0.043 -0.018 -0.043  0.007  0.007 -0.068  0.132  0.082  0.032  0.206  0.032  0.156  0.854 -0.043  0.132 -0.068 -0.043  0.206  0.082 -0.068  0.082  0.032 -0.068  0.032  0.381  0.032 -0.118 -0.043 -0.043 
 0.828 -0.019  0.030  0.080  0.803 -0.119 -0.019 -0.044  0.429 -0.019 -0.094  0.005 -0.094  0.005 -0.019 -0.044  0.255  0.055 -0.119 -0.094  0.105 -0.044 -0.019 -0.069 -0.019 -0.019 -0.044  0.130  0.080  0.030  0.180  0.055  0.130  0.828 -0.044  0.180 -0.094 -0.044  0.205  0.080 -0.094  0.080  0.105 -0.069  0.005  0.578  0.030 -0.144 -0.069 -0.044 
 0.757 -0.040  0.085  0.010  0.782 -0.140  0.010 -0.090  0.633 -0.015 -0.140 -0.040 -0.115 -0.015 -0.065 -0.090  0.359  0.135 -0.164 -0.065  0.135 -0.040 -0.015 -0.015 -0.040  0.010 -0.065  0.110  0.159  0.085  0.209  0.060  0.010  0.757 -0.040  0.159 -0.065 -0.015  0.135  0.060 -0.140  0.085  0.110 -0.040  0.085  0.683 -0.015 -0.164 -0.115 -0.090 
 0.693 -0.080  0.095  0.020  0.767 -0.130 -0.005 -0.080  0.693 -0.005 -0.154  0.020 -0.055  0.020 -0.080 -0.130  0.419  0.144 -0.179 -0.030  0.144  0.020  0.070 -0.030 -0.080 -0.055 -0.105  0.070  0.120  0.070  0.244  0.070 -0.005  0.693 -0.030  0.169 -0.105 -0.055  0.219  0.045 -0.154  0.070  0.144 -0.030  0.070  0.693 -0.030 -0.179 -0.130 -0.105 
 0.642 -0.106  0.094  0.044  0.741 -0.131 -0.006 -0.081  0.692  0.019 -0.131  0.119 -0.056  0.094  0.019 -0.131  0.467  0.168 -0.180 -0.031  0.094  0.019  0.069  0.019 -0.031 -0.081 -0.056  0.019  0.119  0.143  0.218  0.193  0.019  0.567 -0.081  0.119 -0.106 -0.106  0.193  0.044 -0.155  0.119  0.168 -0.056  0.094  0.716 -0.031 -0.131 -0.180 -0.131 
 0.632 -0.090  0.134  0.134  0.682 -0.140 -0.015 -0.065  0.707  0.109 -0.140  0.134 -0.040  0.134  0.009 -0.140  0.458  0.134 -0.190 -0.065  0.084  0.009  0.084  0.009 -0.040 -0.065 -0.065  0.034  0.159  0.134  0.259  0.209  0.009  0.383 -0.140  0.109 -0.065 -0.065  0.159  0.034 -0.190  0.159  0.159 -0.065  0.084  0.682 -0.040 -0.115 -0.190 -0.140 
 0.601 -0.096  0.128  0.128  0.651 -0.121 -0.021 -0.071  0.701  0.153 -0.121  0.228 -0.046  0.203  0.028 -0.146  0.477  0.103 -0.221 -0.071  0.053  0.053  0.078 -0.021 -0.046 -0.046 -0.071  0.053  0.228  0.128  0.253  0.178 -0.021  0.278 -0.221  0.053 -0.046 -0.046  0.178  0.003 -0.171  0.178  0.178 -0.071  0.078  0.626 -0.021 -0.121 -0.196 -0.146 
 0.596 -0.076  0.123  0.148  0.646 -0.126 -0.051 -0.076  0.696  0.198 -0.151  0.223 -0.051  0.223  0.023 -0.126  0.397  0.073 -0.226 -0.076  0.048  0.073  0.123 -0.051 -0.051 -0.001 -0.076  0.098  0.198  0.148  0.248  0.198 -0.026  0.223 -0.251  0.048 -0.051 -0.051  0.148 -0.026 -0.176  0.198  0.173 -0.051  0.073  0.621  0.023 -0.101 -0.201 -0.126 
 0.586 -0.087  0.138  0.138  0.636 -0.137 -0.062 -0.112  0.686  0.237 -0.161  0.287 -0.062  0.237  0.013 -0.137  0.387  0.063 -0.236 -0.087  0.038  0.063  0.138 -0.087 -0.087 -0.012 -0.087  0.088  0.262  0.138  0.237  0.212 -0.037  0.212 -0.211  0.038 -0.012 -0.062  0.212 -0.037 -0.186  0.212  0.138  0.013  0.088  0.561  0.088 -0.112 -0.211 -0.137 
 0.580 -0.042  0.132  0.132  0.630 -0.142 -0.042 -0.117  0.680  0.257 -0.142  0.282 -0.067  0.257  0.007 -0.117  0.356  0.057 -0.242 -0.067  0.057  0.082  0.132 -0.092 -0.092  0.007 -0.067  0.082  0.282  0.132  0.182  0.207 -0.067  0.107 -0.217  0.032 -0.017 -0.067  0.232 -0.017 -0.192  0.207  0.132  0.032  0.082  0.580  0.107 -0.092 -0.217 -0.092 
 0.570 -0.028  0.146  0.122  0.545 -0.152 -0.053 -0.128  0.645  0.221 -0.128  0.346 -0.078  0.271 -0.028 -0.128  0.346  0.047 -0.227 -0.078  0.022  0.171  0.146 -0.103 -0.078  0.072 -0.078  0.072  0.296  0.146  0.122  0.171 -0.078  0.047 -0.252  0.022 -0.028 -0.028  0.221 -0.028 -0.202  0.171  0.097  0.047  0.097  0.570  0.097 -0.078 -0.202 -0.078 
 0.570 -0.028  0.146  0.122  0.470 -0.152 -0.078 -0.128  0.645  0.196 -0.103  0.346 -0.078  0.296 -0.028 -0.128  0.321  0.047 -0.227 -0.078 -0.028  0.171  0.146 -0.103 -0.053  0.072 -0.078  0.097  0.246  0.146  0.047  0.171 -0.053 -0.003 -0.252  0.022 -0.028 -0.028  0.221 -0.028 -0.177  0.171  0.072  0.072  0.097  0.570  0.097 -0.053 -0.177 -0.128 
 0.565 -0.058  0.142  0.092  0.440 -0.182 -0.108 -0.133  0.590  0.191 -0.083  0.366 -0.058  0.316 -0.058 -0.133  0.291  0.017 -0.207 -0.058 -0.033  0.191  0.216 -0.108 -0.033  0.067 -0.083  0.092  0.241  0.142  0.042  0.191 -0.033 -0.033 -0.257 -0.008 -0.058 -0.058  0.216 -0.033 -0.133  0.166  0.067  0.067  0.092  0.540  0.092 -0.083 -0.207 -0.133 
 0.490 -0.058  0.142  0.067  0.341 -0.133 -0.133 -0.083  0.540  0.142 -0.033  0.266 -0.033  0.191 -0.008 -0.108  0.216  0.017 -0.182 -0.083 -0.033  0.142  0.216 -0.058  0.017 -0.008 -0.058 -0.008  0.191  0.067  0.092  0.166 -0.008 -0.058 -0.207  0.067 -0.108 -0.083  0.191 -0.033 -0.058  0.142  0.067  0.067  0.042  0.465  0.042 -0.083 -0.133 -0.182 
 0.438 -0.010  0.064  0.064  0.139 -0.060 -0.110 -0.060  0.363  0.139 -0.060  0.239 -0.035  0.139 -0.035 -0.010  0.089  0.064 -0.135 -0.135 -0.060  0.089  0.114  0.014  0.014 -0.060  0.039 -0.010  0.089 -0.035  0.089  0.139  0.014 -0.085 -0.135  0.114 -0.085 -0.085  0.139 -0.010 -0.010  0.139  0.039  0.064 -0.010  0.388 -0.035 -0.085 -0.110 -0.110 
 0.309 -0.014  0.060  0.085  0.060 -0.039 -0.114 -0.089  0.359  0.135 -0.064  0.185 -0.064  0.110 -0.014 -0.014  0.085  0.035 -0.114 -0.114 -0.039  0.110  0.085 -0.014 -0.014 -0.039  0.060 -0.039 -0.014 -0.014  0.085  0.135  0.010 -0.139 -0.114  0.085 -0.064 -0.064  0.160  0.010 -0.014  0.160  0.060  0.035 -0.014  0.309 -0.064 -0.064 -0.089 -0.114 
 0.094 -0.006  0.069  0.094 -0.006 -0.006 -0.081 -0.056  0.193  0.119 -0.031  0.119 -0.031  0.069  0.019  0.019  0.069 -0.031 -0.081 -0.081 -0.031 -0.031 -0.006  0.019 -0.031 -0.031  0.094 -0.081 -0.056 -0.056  0.044  0.094 -0.006 -0.106 -0.106  0.094 -0.031 -0.031  0.168  0.044 -0.056  0.168  0.044  0.069  0.019  0.318 -0.081 -0.031 -0.081 -0.081 
 0.053  0.003  0.078  0.103 -0.022 -0.022 -0.072 -0.047  0.128  0.128 -0.047  0.128 -0.022  0.078  0.028  0.028  0.078 -0.022 -0.072 -0.072 -0.047 -0.047 -0.022  0.003 -0.047 -0.022  0.103 -0.072 -0.047 -0.047  0.028  0.078  0.003 -0.097 -0.097  0.103 -0.022 -0.047  0.152  0.053 -0.072  0.152  0.028  0.078  0.003  0.327 -0.072 -0.022 -0.072 -0.072 
 0.043  0.018  0.093  0.118 -0.007 -0.057 -0.057 -0.032  0.093  0.142 -0.057  0.043 -0.032  0.043  0.043  0.043  0.093 -0.007 -0.057 -0.057 -0.032 -0.057 -0.007  0.018 -0.032 -0.007  0.093 -0.057 -0.032 -0.032  0.018  0.068 -0.007 -0.082 -0.082  0.093 -0.032 -0.032  0.142  0.068 -0.057  0.142  0.043  0.068  0.018  0.292 -0.057 -0.007 -0.082 -0.057 
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 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 

 0.991  0.019 -0.005  0.019  0.019 -0.005 -0.005  0.094 -0.005 -0.005  0.019 -0.030  0.044 -0.030  0.019 -0.005  0.069  0.044  0.019 -0.030 -0.005 -0.005  0.094 -0.005 -0.005  0.019  0.044 -0.005  0.019 -0.030  0.019  0.069  0.019 -0.005  0.019  0.019 -0.005 -0.030 -0.030 -0.005  0.019 -0.030 -0.030  0.019 -0.030  0.019  0.019  0.019 -0.030 -0.005 
 0.996 -0.000 -0.000 -0.000  0.024 -0.025 -0.000  0.099 -0.000 -0.000  0.024 -0.025  0.049 -0.025  0.024 -0.000  0.074  0.049 -0.000 -0.025 -0.000 -0.000  0.074 -0.000 -0.000  0.024  0.049 -0.000  0.024 -0.025  0.024  0.049  0.024 -0.000  0.024 -0.000 -0.000 -0.025 -0.025 -0.000  0.024 -0.025 -0.025  0.024 -0.025  0.024 -0.000 -0.000 -0.025 -0.000 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 1.001  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.104  0.004  0.004  0.029 -0.020  0.029 -0.020  0.004  0.004  0.054  0.054  0.004 -0.020  0.004  0.004  0.079  0.004  0.004  0.004  0.029  0.004  0.029 -0.020  0.004  0.029  0.029  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004 -0.020  0.004 
 0.999  0.002 -0.022 -0.022  0.027 -0.022  0.002  0.102  0.002  0.002  0.027 -0.022  0.027 -0.022  0.002  0.002  0.077  0.052  0.002 -0.022  0.002  0.002  0.077  0.002  0.027  0.002  0.027  0.002  0.027 -0.022  0.002  0.052  0.027  0.002  0.027  0.002  0.002 -0.022 -0.022 -0.022  0.027 -0.022 -0.022  0.027 -0.022  0.027  0.002  0.002 -0.022  0.002 
 0.995 -0.001  0.024 -0.026  0.024 -0.026 -0.001  0.124 -0.001 -0.001  0.049 -0.026  0.024 -0.026 -0.001 -0.001  0.074  0.074 -0.001 -0.026 -0.001 -0.001  0.124 -0.001  0.024 -0.001  0.024 -0.001  0.024 -0.026 -0.001  0.074  0.024 -0.001  0.024  0.049 -0.001 -0.026 -0.026 -0.026  0.049 -0.026 -0.026  0.024 -0.026  0.024 -0.001 -0.001 -0.026 -0.001 
 0.989 -0.007  0.042 -0.032  0.017 -0.032  0.017  0.117  0.017  0.017  0.067 -0.032  0.017 -0.032 -0.007 -0.007  0.117  0.067 -0.007 -0.032 -0.007 -0.007  0.142 -0.007  0.017 -0.007  0.017  0.017  0.017 -0.032  0.017  0.092  0.017 -0.007  0.017  0.042 -0.007 -0.007 -0.032 -0.007  0.017 -0.032  0.017  0.017 -0.032  0.017  0.017 -0.007 -0.032 -0.007 
 0.959 -0.013  0.161 -0.063  0.012 -0.063  0.012  0.137  0.037  0.087  0.062 -0.063  0.012 -0.013 -0.013 -0.038  0.286  0.261 -0.013 -0.013 -0.038 -0.013  0.161  0.012 -0.013 -0.038 -0.013  0.161  0.012 -0.063 -0.013  0.186  0.012 -0.013  0.037  0.062 -0.038  0.062 -0.038 -0.038  0.037  0.037  0.012  0.012 -0.063  0.012  0.012  0.062 -0.063 -0.013 
 0.921 -0.026  0.273 -0.101 -0.026 -0.101  0.024  0.248  0.024  0.074  0.298 -0.076  0.049 -0.026 -0.051 -0.001  0.298  0.522 -0.051 -0.001 -0.051 -0.051  0.223  0.024 -0.051 -0.026  0.024  0.323 -0.026 -0.051 -0.051  0.223 -0.026 -0.051  0.074  0.173 -0.076  0.148 -0.001 -0.051  0.074  0.074  0.024  0.024 -0.101 -0.001 -0.026  0.124 -0.026 -0.051 
 0.857 -0.014  0.359 -0.114  0.035 -0.164 -0.039  0.284  0.110  0.135  0.559 -0.089  0.060 -0.039 -0.014 -0.014  0.409  0.733 -0.064 -0.014 -0.089 -0.089  0.334  0.010 -0.089  0.010 -0.014  0.384 -0.064 -0.039 -0.114  0.409  0.010 -0.064  0.010  0.359 -0.139  0.185  0.010 -0.014  0.135  0.160  0.035  0.010 -0.114  0.160 -0.039  0.135 -0.089 -0.064 
 0.816 -0.056  0.367 -0.106  0.043 -0.206 -0.031  0.268  0.068  0.143  0.691 -0.131  0.118 -0.031 -0.056  0.093  0.367  0.741 -0.006 -0.006 -0.106 -0.106  0.317  0.018 -0.106 -0.031 -0.031  0.442 -0.081 -0.056 -0.156  0.392 -0.031 -0.106 -0.006  0.342 -0.156  0.218  0.068 -0.031  0.168  0.118  0.068 -0.031 -0.106  0.292 -0.031  0.118 -0.081 -0.106 
 0.738 -0.084  0.365 -0.084  0.066 -0.233 -0.034  0.240  0.116  0.190  0.738 -0.084  0.141 -0.009 -0.059  0.141  0.315  0.664 -0.059 -0.009 -0.158 -0.084  0.315  0.016 -0.109 -0.059 -0.009  0.464 -0.134 -0.109 -0.109  0.415 -0.034 -0.158 -0.034  0.439 -0.183  0.190  0.116  0.016  0.141  0.116  0.041 -0.059 -0.134  0.415 -0.009  0.141 -0.109 -0.183 
 0.716 -0.056  0.317 -0.056  0.143 -0.181 -0.056  0.193  0.118  0.218  0.716 -0.006  0.143 -0.031  0.018  0.168  0.292  0.616 -0.081 -0.031 -0.206 -0.106  0.292  0.043 -0.106 -0.006  0.018  0.442 -0.156 -0.131 -0.081  0.492 -0.031 -0.181 -0.006  0.417 -0.206  0.168  0.093  0.018  0.093  0.118  0.043 -0.056 -0.156  0.542 -0.056  0.143 -0.106 -0.231 
 0.666 -0.081  0.218 -0.056  0.118 -0.206 -0.081  0.143  0.093  0.292  0.691  0.068  0.118  0.018  0.068  0.118  0.268  0.542 -0.156 -0.006 -0.206 -0.081  0.243  0.068 -0.056 -0.056  0.068  0.392 -0.206 -0.131 -0.081  0.467  0.018 -0.206 -0.031  0.392 -0.156  0.093  0.118 -0.006  0.118  0.093 -0.006 -0.031 -0.181  0.517 -0.081  0.168 -0.131 -0.281 
 0.582 -0.041  0.208 -0.041  0.009 -0.215 -0.066  0.109  0.084  0.283  0.657  0.059  0.084  0.034  0.084  0.134  0.208  0.532 -0.165  0.034 -0.215 -0.041  0.233  0.059 -0.091 -0.066  0.084  0.358 -0.190 -0.091 -0.116  0.432  0.009 -0.215 -0.041  0.383 -0.141  0.084  0.134  0.009  0.134  0.158 -0.016 -0.016 -0.190  0.582 -0.091  0.183 -0.141 -0.290 
 0.573 -0.049  0.150 -0.049  0.000 -0.149 -0.074  0.075  0.075  0.275  0.623  0.050  0.050  0.025  0.050  0.150  0.175  0.474 -0.174  0.050 -0.224  0.000  0.200  0.100 -0.099 -0.099  0.100  0.324 -0.199 -0.074 -0.124  0.399 -0.024 -0.224 -0.024  0.349 -0.149  0.075  0.125  0.000  0.125  0.150 -0.024  0.000 -0.174  0.573 -0.099  0.225 -0.149 -0.298 
 0.547 -0.001  0.124 -0.026 -0.026 -0.126 -0.076  0.074  0.074  0.273  0.572  0.049  0.074  0.024  0.049  0.124  0.173  0.423 -0.175 -0.001 -0.225  0.024  0.173  0.124 -0.076 -0.076  0.099  0.248 -0.175 -0.101 -0.101  0.398 -0.051 -0.225 -0.026  0.323 -0.150  0.049  0.124 -0.026  0.124  0.148 -0.026 -0.001 -0.175  0.572 -0.101  0.173 -0.175 -0.300 
 0.549 -0.024  0.101  0.001 -0.049 -0.124 -0.074  0.076  0.076  0.250  0.499  0.051  0.076  0.026  0.076  0.076  0.126  0.375 -0.198  0.001 -0.223  0.026  0.150  0.126 -0.074 -0.074  0.101  0.250 -0.173 -0.099 -0.099  0.400 -0.074 -0.248  0.001  0.325 -0.148  0.026  0.126 -0.024  0.150  0.150  0.001  0.001 -0.173  0.574 -0.099  0.175 -0.198 -0.298 
 0.475 -0.023  0.101  0.051 -0.073 -0.123 -0.073  0.051  0.101  0.251  0.425  0.076  0.101  0.001  0.101  0.051  0.101  0.350 -0.198  0.001 -0.223  0.051  0.101  0.101 -0.048 -0.073  0.076  0.251 -0.198 -0.098 -0.073  0.375 -0.098 -0.248  0.001  0.325 -0.148  0.026  0.151  0.026  0.151  0.151  0.001  0.026 -0.198  0.574 -0.098  0.176 -0.198 -0.273 
 0.449  0.000  0.075  0.075 -0.049 -0.124 -0.074  0.050  0.100  0.250  0.374  0.075  0.125  0.000  0.125  0.075  0.100  0.299 -0.174  0.000 -0.224  0.050  0.100  0.075 -0.049 -0.099  0.075  0.275 -0.199 -0.074 -0.049  0.374 -0.124 -0.249 -0.024  0.324 -0.149 -0.024  0.150  0.050  0.150  0.150  0.000  0.025 -0.199  0.549 -0.099  0.150 -0.199 -0.249 
 0.450  0.001  0.076  0.076 -0.048 -0.123 -0.073  0.076  0.101  0.251  0.375  0.076  0.101  0.001  0.126  0.051  0.101  0.300 -0.173  0.001 -0.223  0.051  0.101  0.076 -0.073 -0.098  0.076  0.276 -0.198 -0.073 -0.048  0.350 -0.123 -0.248 -0.023  0.325 -0.148 -0.023  0.151  0.051  0.126  0.151  0.001  0.026 -0.198  0.550 -0.098  0.151 -0.198 -0.248 
 0.375  0.001  0.076  0.076 -0.073 -0.123 -0.073  0.051  0.101  0.226  0.375  0.101  0.101  0.001  0.126  0.051  0.076  0.276 -0.173 -0.023 -0.223  0.051  0.126  0.076 -0.098 -0.098  0.076  0.300 -0.198 -0.073 -0.023  0.325 -0.123 -0.248 -0.048  0.325 -0.148 -0.023  0.101  0.051  0.151  0.151  0.001  0.051 -0.198  0.550 -0.098  0.151 -0.198 -0.198 
 0.371 -0.003  0.072  0.072 -0.078 -0.128 -0.078  0.022  0.097  0.221  0.346  0.097  0.122  0.022  0.122 -0.003  0.047  0.271 -0.152 -0.003 -0.227  0.072  0.122  0.072 -0.103 -0.078  0.072  0.321 -0.202 -0.078 -0.053  0.321 -0.128 -0.252 -0.053  0.321 -0.152 -0.028  0.097  0.047  0.122  0.146  0.022  0.047 -0.202  0.545 -0.103  0.171 -0.202 -0.202 
 0.367  0.018  0.093  0.068 -0.082 -0.132 -0.057  0.018  0.093  0.242  0.317  0.118  0.118  0.043  0.118 -0.007  0.018  0.267 -0.156 -0.007 -0.181  0.118  0.118  0.043 -0.107 -0.082  0.068  0.317 -0.206 -0.032 -0.032  0.317 -0.132 -0.256 -0.057  0.317 -0.156 -0.007  0.118  0.018  0.068  0.142  0.018  0.068 -0.181  0.541 -0.107  0.167 -0.206 -0.206 
 0.272  0.048  0.048  0.023 -0.052 -0.077 -0.027 -0.027  0.098  0.247  0.322  0.123  0.172  0.073  0.048  0.023  0.023  0.222 -0.102 -0.102 -0.127  0.147  0.123  0.023 -0.077 -0.052  0.073  0.297 -0.127 -0.077  0.023  0.297 -0.052 -0.176 -0.077  0.297 -0.127  0.048  0.098 -0.077  0.023  0.147  0.048  0.073 -0.127  0.397 -0.127  0.123 -0.127 -0.176 
 0.178  0.054  0.029  0.029 -0.046  0.004 -0.021 -0.021  0.129  0.253  0.253  0.029  0.054  0.054 -0.021  0.004  0.029  0.203 -0.145 -0.121 -0.096  0.104  0.054  0.054 -0.046 -0.046  0.104  0.253 -0.071 -0.021  0.029  0.228 -0.046 -0.121 -0.121  0.253 -0.096  0.054  0.104 -0.046  0.079  0.054  0.029  0.079 -0.096  0.353 -0.071  0.104 -0.046 -0.121 
 0.143  0.018  0.043  0.043 -0.081 -0.006 -0.056 -0.006  0.143  0.243  0.193  0.043  0.043  0.068 -0.006 -0.006  0.068  0.168 -0.131 -0.106 -0.081  0.093  0.018  0.043 -0.056 -0.031  0.118  0.243 -0.056 -0.006 -0.006  0.218 -0.006 -0.106 -0.156  0.268 -0.081  0.018  0.118 -0.031  0.043  0.068  0.043  0.093 -0.081  0.317 -0.081  0.068 -0.031 -0.106 
 0.119  0.044  0.094  0.094 -0.055 -0.005 -0.055  0.019  0.144  0.244  0.044  0.019  0.019  0.094 -0.030  0.019  0.094  0.119 -0.105 -0.080 -0.055  0.094 -0.005  0.019 -0.055 -0.005  0.094  0.194 -0.030 -0.030 -0.005  0.194 -0.005 -0.080 -0.130  0.219 -0.055 -0.030  0.144  0.019  0.019  0.094  0.069  0.094 -0.055  0.269 -0.055 -0.005 -0.005 -0.105 
 0.105  0.030  0.130  0.105 -0.045 -0.020 -0.045  0.030  0.179  0.229  0.005  0.030  0.030  0.105 -0.020  0.030  0.080  0.105 -0.095 -0.070 -0.045  0.080  0.005 -0.020 -0.045  0.005  0.105  0.130 -0.020 -0.045  0.005  0.179  0.005 -0.070 -0.120  0.179 -0.045 -0.045  0.154  0.030  0.030  0.080  0.055  0.105 -0.045  0.229 -0.045 -0.020 -0.045 -0.095 
 0.095  0.045  0.145  0.120 -0.029 -0.054 -0.054  0.045  0.170  0.245 -0.054  0.045  0.020  0.120 -0.004  0.045  0.095  0.120 -0.079 -0.079 -0.029  0.045  0.020 -0.004 -0.029  0.020  0.095  0.095 -0.029 -0.054  0.020  0.120 -0.029 -0.079 -0.104  0.120 -0.029 -0.029  0.170  0.020  0.045  0.020  0.095  0.145 -0.029  0.145 -0.029 -0.029 -0.054 -0.079 
 0.103  0.053  0.128  0.128 -0.021 -0.046 -0.046  0.053  0.153  0.253 -0.046  0.053  0.028  0.128  0.003  0.053  0.078  0.128 -0.071 -0.071 -0.021  0.003  0.028  0.003 -0.021  0.028  0.103  0.078 -0.021 -0.046  0.028  0.078 -0.021 -0.071 -0.096  0.028 -0.021 -0.071  0.178  0.003  0.053  0.028  0.103  0.128 -0.021  0.153 -0.046 -0.021 -0.046 -0.096 
 0.042  0.042  0.092  0.117 -0.007 -0.032 -0.032  0.017  0.092  0.267 -0.057  0.067  0.017  0.117  0.017  0.067  0.042  0.067 -0.057 -0.057 -0.007 -0.032  0.017  0.017 -0.007  0.042  0.117 -0.007 -0.007 -0.032  0.042  0.092 -0.032 -0.082 -0.082 -0.032 -0.007 -0.057  0.167  0.017  0.067  0.017  0.067  0.142 -0.007  0.142 -0.032 -0.007 -0.032 -0.082 
 0.023  0.023  0.048  0.123 -0.001 -0.026 -0.051 -0.001  0.098  0.223 -0.051  0.098  0.023  0.123  0.023  0.048  0.023  0.023 -0.051 -0.051 -0.001 -0.026 -0.001  0.023 -0.026  0.048  0.123 -0.026 -0.001 -0.026  0.048  0.073 -0.051 -0.076 -0.076 -0.026 -0.001 -0.051  0.148  0.023  0.048 -0.026  0.073  0.148 -0.001  0.048 -0.026 -0.001 -0.026 -0.076 
 0.013  0.038  0.063  0.063 -0.012 -0.012 -0.037 -0.037  0.113  0.187 -0.037  0.063  0.013  0.038  0.013  0.038  0.038 -0.012 -0.037 -0.037  0.013 -0.037  0.013  0.013 -0.062  0.063  0.038 -0.062 -0.012 -0.012  0.038  0.063 -0.037 -0.062 -0.062 -0.037 -0.012 -0.037  0.113 -0.012  0.038 -0.037  0.088  0.113 -0.012  0.013 -0.012  0.038 -0.012 -0.062 
 0.023  0.023  0.073  0.023 -0.027 -0.002 -0.027 -0.027  0.123  0.123 -0.027  0.023  0.023  0.048  0.023  0.048  0.023 -0.002 -0.027 -0.027 -0.002 -0.027 -0.002  0.023 -0.052  0.073 -0.002 -0.052 -0.002 -0.027  0.023  0.048 -0.027 -0.052 -0.052 -0.027 -0.002 -0.052  0.073 -0.002  0.023 -0.027  0.098  0.048 -0.002  0.023 -0.027 -0.002 -0.027 -0.052 
 0.033  0.033  0.033  0.008 -0.016 -0.016 -0.041 -0.041  0.083  0.083 -0.016  0.008  0.033 -0.016  0.033  0.008 -0.016 -0.041 -0.041 -0.016 -0.016 -0.016 -0.016 -0.016 -0.016  0.033 -0.016 -0.041 -0.041 -0.016  0.033  0.033 -0.016 -0.041 -0.041 -0.016  0.008 -0.041  0.058  0.008 -0.016 -0.041  0.058  0.008 -0.016 -0.016 -0.041 -0.016 -0.016 -0.041 
 0.041  0.041  0.016 -0.008 -0.008 -0.008 -0.033 -0.033  0.066  0.041 -0.033  0.016  0.016 -0.008  0.041  0.016 -0.008 -0.033 -0.033 -0.008 -0.033 -0.008 -0.008 -0.008 -0.008  0.016 -0.008 -0.033 -0.033 -0.008 -0.008  0.066 -0.008 -0.033 -0.033 -0.008 -0.008 -0.033  0.066  0.016 -0.033 -0.033  0.066  0.041 -0.033 -0.033 -0.033  0.016 -0.008 -0.033 
 0.028  0.003 -0.022  0.003 -0.022  0.003  0.003 -0.022  0.053 -0.022 -0.022  0.053  0.003 -0.022 -0.022  0.028  0.003  0.003 -0.022  0.003 -0.022  0.003  0.003 -0.022  0.003  0.003  0.003  0.003 -0.022 -0.022  0.003  0.028  0.003  0.003 -0.022 -0.022 -0.022 -0.022  0.053 -0.022 -0.022 -0.022  0.028  0.003 -0.022 -0.022 -0.022  0.003  0.003 -0.022 
 0.028  0.003 -0.021  0.003 -0.021  0.003  0.003 -0.021  0.053 -0.021 -0.021  0.053  0.003 -0.021 -0.021  0.028  0.003  0.003 -0.021  0.003 -0.021  0.003  0.003 -0.021  0.003  0.003  0.003  0.003 -0.021 -0.021  0.003  0.028  0.003  0.003 -0.021 -0.021 -0.021 -0.021  0.053 -0.021 -0.021 -0.021  0.028  0.003 -0.021 -0.021 -0.021  0.003  0.003 -0.021 
 0.029  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.029  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.029  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.029  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.029  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020  0.004  0.029  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020  0.004  0.004 -0.020 
 0.020 -0.004 -0.004 -0.004 -0.029 -0.029  0.020 -0.029  0.020 -0.029 -0.029  0.045 -0.029 -0.029 -0.029  0.020 -0.004 -0.004 -0.029 -0.004 -0.004 -0.004  0.020 -0.029 -0.004  0.020 -0.004 -0.004 -0.029 -0.029 -0.004  0.045 -0.004 -0.004 -0.029 -0.029 -0.029 -0.029  0.045 -0.004 -0.029 -0.029  0.095 -0.004 -0.029 -0.029 -0.029 -0.004 -0.004 -0.029 
 0.008  0.008 -0.042 -0.017 -0.067 -0.042 -0.017 -0.042  0.058  0.008 -0.042  0.108 -0.042 -0.042 -0.017  0.008 -0.017 -0.017  0.008 -0.042 -0.017 -0.017  0.008 -0.067  0.008  0.058 -0.042 -0.042 -0.042 -0.067 -0.042  0.083  0.008 -0.042 -0.067 -0.042 -0.017 -0.067  0.033 -0.017 -0.067 -0.042  0.108  0.033 -0.042 -0.042  0.008  0.058  0.033 -0.067 
 0.007  0.007 -0.068 -0.043 -0.118 -0.068 -0.068 -0.093  0.132  0.057 -0.068  0.082 -0.093 -0.068  0.032 -0.043 -0.018 -0.043  0.007 -0.093  0.007 -0.043 -0.068 -0.043  0.007  0.057 -0.018  0.007 -0.093 -0.068 -0.043  0.132 -0.043 -0.093 -0.068  0.007 -0.068 -0.068  0.032 -0.043 -0.093 -0.043  0.082  0.007 -0.093  0.057 -0.043  0.107  0.082 -0.068 
-0.001 -0.026 -0.076 -0.026 -0.151 -0.076 -0.126 -0.076  0.198  0.048 -0.101  0.073 -0.076 -0.101  0.123 -0.076  0.048 -0.101 -0.051 -0.101  0.048 -0.101 -0.151  0.023 -0.076 -0.001 -0.026  0.023 -0.076 -0.101 -0.101  0.048 -0.026 -0.176 -0.151  0.048 -0.076 -0.051  0.123  0.048 -0.151 -0.126  0.098 -0.001 -0.151  0.297 -0.076  0.123  0.048 -0.151 
 0.011 -0.064 -0.064  0.061 -0.163 -0.089 -0.163 -0.139  0.160  0.210 -0.064  0.036 -0.064 -0.039  0.136 -0.114  0.036 -0.139 -0.089 -0.139  0.036 -0.114 -0.064  0.011 -0.039 -0.039  0.011  0.011 -0.064 -0.139 -0.064  0.061 -0.014 -0.213 -0.163  0.036 -0.114 -0.064  0.086  0.011 -0.139 -0.139  0.111  0.036 -0.188  0.385 -0.114  0.136  0.011 -0.163 
 0.113 -0.087 -0.087  0.013 -0.112 -0.087 -0.186 -0.161  0.113  0.237 -0.062  0.038 -0.037 -0.012  0.138 -0.112  0.038 -0.161 -0.112 -0.161 -0.037 -0.087 -0.037  0.038 -0.062 -0.112 -0.037  0.038 -0.012 -0.087 -0.062  0.088 -0.062 -0.261 -0.186  0.013 -0.112 -0.062  0.138  0.013 -0.161 -0.186  0.113  0.088 -0.236  0.436 -0.137  0.162 -0.062 -0.236 
 0.127  0.002 -0.098  0.027 -0.123 -0.098 -0.147 -0.147  0.077  0.251 -0.048  0.052  0.002 -0.023  0.127 -0.073  0.002 -0.172 -0.098 -0.172 -0.073 -0.098  0.002  0.027 -0.098 -0.123 -0.048  0.027 -0.048 -0.073 -0.073  0.077 -0.073 -0.272 -0.197 -0.023 -0.123 -0.048  0.102 -0.023 -0.172 -0.197  0.102  0.102 -0.247  0.426 -0.147  0.151 -0.073 -0.222 
 0.135  0.035 -0.064  0.010 -0.089 -0.164 -0.164 -0.189 -0.014  0.210 -0.064  0.135 -0.039  0.010  0.060 -0.089 -0.014 -0.214 -0.114 -0.164 -0.114 -0.039  0.035  0.010 -0.039 -0.139 -0.039  0.060 -0.089 -0.014  0.035  0.160 -0.139 -0.288 -0.214 -0.039 -0.139 -0.039  0.085  0.110 -0.164 -0.214  0.085  0.110 -0.189  0.459 -0.164  0.160 -0.114 -0.264 
 0.110  0.060 -0.064 -0.014 -0.089 -0.164 -0.164 -0.214 -0.014  0.185 -0.064  0.160 -0.039  0.010  0.060 -0.089 -0.014 -0.214 -0.114 -0.189 -0.114 -0.014 -0.014  0.035 -0.039 -0.114 -0.064  0.060 -0.089 -0.014  0.035  0.160 -0.139 -0.288 -0.264 -0.014 -0.139 -0.014  0.085  0.085 -0.164 -0.214  0.085  0.085 -0.164  0.434 -0.189  0.160 -0.114 -0.264 
 0.080  0.105 -0.069  0.005 -0.069 -0.194 -0.144 -0.219  0.005  0.180 -0.069  0.205 -0.044  0.005  0.055 -0.094  0.005 -0.219 -0.119 -0.169 -0.144  0.005  0.005  0.030 -0.044 -0.094 -0.069  0.055 -0.094 -0.019  0.030  0.205 -0.144 -0.269 -0.269 -0.019 -0.169 -0.019  0.105  0.130 -0.169 -0.194  0.105  0.055 -0.144  0.429 -0.219  0.205 -0.119 -0.269 
 0.076  0.126 -0.073  0.001 -0.048 -0.198 -0.148 -0.173  0.001  0.176 -0.073  0.201 -0.048  0.001  0.051 -0.098  0.026 -0.198 -0.123 -0.173 -0.148  0.026  0.001  0.001 -0.048 -0.048 -0.098  0.051 -0.123 -0.048  0.026  0.201 -0.148 -0.273 -0.273 -0.023 -0.173 -0.023  0.126  0.101 -0.173 -0.198  0.101  0.051 -0.148  0.425 -0.223  0.226 -0.123 -0.273 
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 1.001  0.004 -0.020  0.054  0.004 -0.020  0.104  0.004  0.054  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
 1.001  0.004 -0.020  0.054  0.004 -0.020  0.104  0.004  0.054  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004  0.029  0.029  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.029 -0.020  0.004  0.004 -0.020  0.029  0.029 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
 0.999  0.003 -0.022  0.053  0.003 -0.022  0.177  0.003  0.053  0.003 -0.022  0.003  0.003 -0.022 -0.022  0.003  0.003  0.028  0.028  0.003 -0.022 -0.022 -0.022 -0.022 -0.022  0.003 -0.022 -0.022 -0.022 -0.022  0.003  0.003 -0.022  0.003 -0.022 -0.022  0.028 -0.022  0.003  0.003 -0.022  0.028  0.028 -0.022  0.003  0.003  0.003 -0.022  0.028  0.003 
 0.993  0.021 -0.029  0.046  0.021 -0.029  0.395 -0.004  0.170 -0.004 -0.029 -0.004 -0.004 -0.004 -0.029 -0.004 -0.004  0.021  0.021  0.046 -0.029 -0.029 -0.029 -0.029 -0.029 -0.004 -0.029 -0.029 -0.004  0.021  0.046 -0.004 -0.029  0.021 -0.029 -0.004  0.021 -0.004  0.021 -0.004 -0.029  0.021  0.071 -0.029  0.046 -0.004 -0.004 -0.004  0.021 -0.004 
 0.976  0.004  0.004  0.079  0.029 -0.020  0.602  0.004  0.577  0.054 -0.020  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.029  0.004 -0.020 -0.045 -0.020 -0.045  0.004 -0.045 -0.045 -0.020  0.054  0.079 -0.020 -0.045  0.029 -0.045  0.054  0.004 -0.020  0.004 -0.020 -0.020  0.029  0.079 -0.045  0.079 -0.020  0.004  0.004  0.004  0.004 
 0.944 -0.002  0.047  0.147  0.022 -0.052  0.944 -0.027  0.845  0.072 -0.052  0.097 -0.002 -0.052  0.022 -0.027  0.072  0.022  0.072 -0.002  0.072  0.022  0.022 -0.002 -0.077  0.022 -0.077 -0.027 -0.027  0.197  0.321  0.022 -0.002  0.047 -0.077  0.047  0.047 -0.002  0.022 -0.027  0.022  0.047  0.122 -0.077  0.072 -0.052 -0.027 -0.027  0.097 -0.002 
 0.914  0.017  0.092  0.316  0.017 -0.057  0.914 -0.007  0.815  0.192 -0.057  0.167 -0.007 -0.057  0.092 -0.032  0.067 -0.007  0.067 -0.032  0.267 -0.007  0.042  0.067 -0.082  0.017 -0.082 -0.057 -0.032  0.291  0.566  0.042 -0.032  0.042 -0.082  0.092  0.167  0.017 -0.007  0.017  0.017  0.142  0.117 -0.082  0.092 -0.082 -0.032  0.017  0.167  0.017 
 0.854 -0.018  0.156  0.406  0.007 -0.068  0.854  0.032  0.854  0.480 -0.068  0.107 -0.018 -0.068  0.231  0.007  0.132 -0.018  0.132 -0.043  0.530  0.032  0.032  0.156 -0.118  0.007 -0.093 -0.043  0.007  0.331  0.729  0.082  0.032  0.231 -0.093  0.107  0.206  0.007 -0.068  0.032  0.107  0.331  0.132 -0.018  0.206 -0.118 -0.068 -0.018  0.331  0.032 
 0.820  0.097  0.147  0.371 -0.002 -0.102  0.795  0.047  0.820  0.695 -0.052  0.097  0.047 -0.002  0.222  0.147  0.247 -0.002  0.222 -0.027  0.645  0.047  0.047  0.272 -0.077 -0.002 -0.127 -0.077  0.022  0.272  0.720  0.097  0.072  0.346 -0.052  0.072  0.222  0.072 -0.052  0.047  0.122  0.446  0.147  0.022  0.272 -0.002 -0.027  0.022  0.396  0.072 
 0.728  0.131  0.205  0.479 -0.019 -0.069  0.753  0.081  0.778  0.753  0.031  0.081  0.031  0.056  0.255  0.330  0.405  0.106  0.255 -0.069  0.728  0.081  0.031  0.380 -0.119  0.081 -0.119 -0.019  0.081  0.255  0.753  0.131  0.031  0.479 -0.019  0.031  0.305  0.106 -0.069  0.131  0.131  0.679  0.205  0.106  0.280  0.056 -0.069  0.031  0.429  0.230 
 0.691  0.143  0.193  0.467 -0.031  0.018  0.741  0.093  0.766  0.766  0.043  0.068  0.018  0.068  0.243  0.392  0.517  0.093  0.367 -0.081  0.716  0.068  0.068  0.442 -0.131  0.093 -0.056 -0.006  0.168  0.268  0.741  0.168  0.018  0.492  0.018  0.018  0.367  0.143 -0.081  0.143  0.193  0.716  0.218  0.143  0.292  0.068 -0.056  0.118  0.392  0.317 
 0.621  0.198  0.173  0.422 -0.026  0.048  0.721  0.123  0.746  0.746  0.048  0.073  0.023  0.048  0.273  0.571  0.671  0.173  0.447 -0.076  0.696  0.073  0.023  0.497 -0.151  0.148 -0.026 -0.001  0.198  0.248  0.671  0.198  0.048  0.547  0.073  0.048  0.347  0.223 -0.101  0.223  0.273  0.696  0.273  0.148  0.273  0.098 -0.076  0.148  0.347  0.472 
 0.614  0.216  0.191  0.365  0.016  0.041  0.714  0.166  0.739  0.714  0.066  0.041  0.016  0.016  0.266  0.614  0.689  0.216  0.490 -0.083  0.689  0.041  0.016  0.465 -0.183  0.191 -0.008 -0.008  0.340  0.191  0.639  0.191  0.066  0.540  0.116 -0.008  0.365  0.266 -0.133  0.266  0.290  0.689  0.266  0.141  0.266  0.116 -0.083  0.141  0.365  0.540 
 0.579  0.256  0.231  0.281  0.056  0.056  0.654  0.206  0.729  0.704  0.056  0.081  0.031  0.031  0.355  0.629  0.729  0.231  0.555 -0.093  0.679  0.031 -0.018  0.455 -0.168  0.181  0.006  0.031  0.455  0.156  0.579  0.206  0.081  0.530  0.156 -0.018  0.355  0.355 -0.118  0.380  0.305  0.679  0.281  0.206  0.256  0.056 -0.093  0.206  0.355  0.604 
 0.548  0.349  0.224  0.274  0.075  0.050  0.648  0.224  0.673  0.698  0.075  0.100  0.050  0.000  0.424  0.623  0.722  0.174  0.548 -0.075  0.648  0.000  0.000  0.424 -0.174  0.174  0.025  0.075  0.448  0.125  0.573  0.224  0.125  0.523  0.249  0.000  0.374  0.349 -0.149  0.374  0.299  0.673  0.274  0.199  0.249  0.050 -0.100  0.199  0.324  0.623 
 0.542  0.368  0.243  0.243  0.069  0.094  0.642  0.293  0.667  0.692  0.069  0.193  0.019  0.019  0.442  0.642  0.692  0.168  0.567 -0.081  0.642 -0.056  0.044  0.418 -0.205  0.193  0.019  0.069  0.467  0.119  0.542  0.218  0.143  0.542  0.243  0.019  0.318  0.418 -0.155  0.393  0.293  0.667  0.318  0.243  0.268  0.094 -0.081  0.193  0.318  0.617 
 0.514  0.365  0.240  0.240  0.066  0.091  0.639  0.340  0.639  0.689  0.066  0.215  0.016  0.016  0.439  0.639  0.689  0.190  0.564 -0.084  0.639 -0.034  0.066  0.415 -0.208  0.190  0.016  0.066  0.514  0.116  0.539  0.190  0.141  0.539  0.240  0.066  0.315  0.415 -0.158  0.390  0.290  0.664  0.340  0.215  0.265  0.091 -0.084  0.190  0.315  0.614 
 0.508  0.408  0.234  0.209  0.059  0.084  0.632  0.383  0.607  0.657  0.084  0.284  0.009  0.059  0.458  0.607  0.682  0.184  0.558 -0.115  0.632 -0.015  0.084  0.408 -0.240  0.209  0.009  0.059  0.558  0.109  0.533  0.159  0.159  0.533  0.259  0.059  0.308  0.483 -0.140  0.383  0.284  0.657  0.308  0.209  0.284  0.059 -0.090  0.184  0.308  0.607 
 0.506  0.431  0.232  0.182  0.032  0.132  0.630  0.406  0.605  0.655  0.082  0.306  0.032  0.057  0.456  0.580  0.680  0.182  0.531 -0.117  0.630  0.007  0.107  0.431 -0.192  0.232 -0.017  0.082  0.556  0.082  0.531  0.182  0.182  0.506  0.257  0.057  0.306  0.506 -0.117  0.381  0.282  0.630  0.306  0.207  0.282  0.057 -0.092  0.157  0.306  0.580 
 0.505  0.480  0.231  0.181  0.057  0.132  0.630  0.406  0.605  0.655  0.082  0.306  0.032  0.057  0.455  0.530  0.680  0.181  0.480 -0.118  0.630  0.007  0.107  0.430 -0.192  0.231 -0.018  0.082  0.555  0.082  0.530  0.181  0.181  0.480  0.281  0.057  0.306  0.505 -0.118  0.406  0.281  0.630  0.281  0.231  0.231  0.032 -0.093  0.156  0.281  0.580 
 0.453  0.478  0.229  0.179  0.055  0.154  0.628  0.404  0.603  0.653  0.080  0.304  0.055  0.055  0.453  0.528  0.678  0.179  0.503 -0.120  0.628  0.005  0.105  0.404 -0.169  0.254  0.005  0.080  0.553  0.080  0.528  0.179  0.179  0.478  0.279  0.055  0.279  0.503 -0.120  0.404  0.304  0.628  0.279  0.254  0.229  0.030 -0.095  0.154  0.254  0.603 
 0.423  0.498  0.224  0.149  0.049  0.149  0.622  0.398  0.597  0.647  0.074  0.323  0.049  0.049  0.448  0.548  0.697  0.174  0.498 -0.125  0.622 -0.000  0.149  0.398 -0.175  0.323 -0.000  0.074  0.548  0.074  0.523  0.174  0.174  0.523  0.298  0.074  0.274  0.498 -0.100  0.398  0.298  0.647  0.274  0.274  0.199  0.024 -0.100  0.174  0.249  0.597 
 0.350  0.475  0.276  0.126  0.076  0.051  0.624  0.276  0.624  0.599  0.001  0.276  0.051  0.101  0.400  0.525  0.674  0.151  0.425 -0.098  0.599  0.001  0.051  0.300 -0.148  0.276  0.001  0.026  0.450  0.101  0.450  0.051  0.051  0.500  0.176  0.076  0.300  0.375 -0.123  0.300  0.375  0.574  0.201  0.251  0.251 -0.048 -0.148  0.101  0.251  0.649 
 0.293  0.393  0.219  0.144  0.069  0.019  0.667  0.194  0.568  0.592  0.069  0.119  0.044  0.119  0.368  0.393  0.642  0.169  0.418 -0.055  0.568 -0.005 -0.030  0.169 -0.130  0.169  0.044 -0.030  0.269  0.094  0.468  0.019  0.044  0.393  0.144  0.094  0.269  0.318 -0.080  0.169  0.393  0.592  0.219  0.194  0.119 -0.030 -0.055  0.069  0.293  0.667 
 0.310  0.360  0.211  0.161  0.036 -0.013  0.734  0.136  0.584  0.634  0.061  0.036  0.061  0.136  0.360  0.410  0.535  0.111  0.310 -0.038  0.460 -0.063 -0.038  0.036 -0.113  0.111  0.061 -0.038  0.211  0.111  0.485 -0.013 -0.013  0.335  0.136  0.086  0.211  0.285 -0.088  0.111  0.385  0.609  0.236  0.136  0.061  0.011 -0.038  0.061  0.310  0.659 
 0.286  0.311  0.237  0.137 -0.012  0.037  0.710  0.062  0.585  0.660  0.062  0.012  0.062  0.112  0.336  0.486  0.461  0.012  0.286 -0.012  0.336 -0.062 -0.062 -0.037 -0.087  0.112  0.037 -0.087  0.112  0.087  0.486 -0.012 -0.037  0.212  0.062  0.087  0.212  0.237 -0.062 -0.012  0.386  0.585  0.162  0.087  0.012  0.012 -0.037  0.012  0.361  0.635 
 0.268  0.268  0.243  0.143 -0.006  0.043  0.766  0.068  0.591  0.641  0.043  0.043  0.068  0.118  0.342  0.442  0.417 -0.031  0.268 -0.006  0.317 -0.056 -0.081 -0.056 -0.081  0.093  0.043 -0.106  0.093  0.043  0.517 -0.006 -0.031  0.168  0.043  0.068  0.143  0.243 -0.056 -0.056  0.317  0.567  0.118  0.068  0.018  0.018 -0.056  0.018  0.342  0.641 
 0.232  0.207  0.257  0.132  0.007  0.032  0.780  0.057  0.556  0.755  0.032  0.032  0.057  0.107  0.331  0.381  0.381 -0.067  0.232 -0.017  0.207 -0.042 -0.067 -0.042 -0.067  0.032  0.032 -0.092  0.082 -0.017  0.506  0.007 -0.042  0.132  0.032  0.082  0.107  0.257 -0.042 -0.042  0.232  0.531  0.132  0.007 -0.017  0.007 -0.042 -0.017  0.282  0.506 
 0.235  0.160  0.210  0.111  0.011  0.011  0.808  0.061  0.584  0.783  0.011  0.036  0.061  0.061  0.335  0.310  0.360 -0.089  0.210 -0.039  0.136 -0.039 -0.064 -0.014 -0.089  0.011  0.011 -0.089  0.086 -0.014  0.534  0.011 -0.039  0.111  0.011  0.061  0.086  0.210 -0.039 -0.039  0.235  0.509  0.160  0.011 -0.014  0.011 -0.039 -0.014  0.285  0.484 
 0.217  0.142  0.167  0.117  0.017 -0.007  0.840  0.017  0.590  0.864 -0.007  0.042  0.042  0.067  0.291  0.217  0.316 -0.082  0.217 -0.032  0.117 -0.032 -0.057 -0.007 -0.082 -0.007  0.017 -0.082  0.092 -0.007  0.541  0.017 -0.057  0.092  0.017  0.067  0.092  0.192 -0.032 -0.032  0.192  0.516  0.192  0.017 -0.007  0.017 -0.007 -0.007  0.217  0.416 
 0.223  0.148  0.148  0.124 -0.001 -0.026  0.896  0.024  0.572  0.871 -0.001  0.024  0.024  0.024  0.223  0.173  0.298 -0.076  0.173 -0.026  0.074 -0.026 -0.051 -0.001 -0.076 -0.026 -0.001 -0.076  0.049 -0.001  0.497  0.024 -0.051  0.074  0.024  0.049  0.074  0.173 -0.026 -0.026  0.198  0.497  0.173 -0.001  0.024  0.024 -0.001 -0.001  0.198  0.323 
 0.185  0.061  0.061  0.136  0.011 -0.039  0.933  0.036  0.534  0.883 -0.039  0.011  0.036  0.011  0.136  0.036  0.185 -0.064  0.111 -0.039  0.061 -0.039 -0.039  0.011 -0.064 -0.014 -0.039 -0.064  0.036  0.011  0.459  0.036 -0.039  0.086 -0.014  0.011  0.086  0.061 -0.014 -0.014  0.185  0.434  0.160 -0.039  0.036  0.011  0.011  0.011  0.111  0.285 
 0.219  0.020 -0.005  0.120  0.045 -0.030  0.942  0.045  0.369  0.917 -0.030  0.020  0.020 -0.055  0.095  0.020  0.070 -0.055  0.120 -0.030  0.070 -0.055 -0.030  0.020 -0.055  0.020 -0.030 -0.030  0.020  0.020  0.369  0.045 -0.055  0.095 -0.030  0.020  0.095  0.020 -0.030 -0.005  0.194  0.369  0.144 -0.030  0.045  0.020  0.020  0.020  0.120  0.219 
 0.202  0.003 -0.022  0.078  0.053 -0.022  0.950  0.053  0.277  0.975 -0.022 -0.022  0.028 -0.047  0.028 -0.022  0.053 -0.047  0.053 -0.022  0.078 -0.047 -0.022  0.028 -0.047  0.028 -0.022 -0.022  0.028  0.028  0.252  0.003 -0.047  0.078 -0.022  0.028  0.053 -0.022 -0.047 -0.022  0.152  0.327  0.152 -0.047  0.053  0.028  0.028  0.028  0.078  0.128 
 0.131  0.006 -0.019  0.006  0.031 -0.019  0.953  0.031  0.205  0.978 -0.019 -0.019  0.006 -0.044  0.031 -0.019  0.056 -0.044  0.031 -0.019  0.081 -0.044 -0.019  0.031 -0.044  0.031 -0.019 -0.019  0.031  0.031  0.180  0.006 -0.044  0.081 -0.019  0.031  0.056 -0.019 -0.044 -0.019  0.131  0.305  0.155 -0.044  0.056  0.031  0.031  0.031  0.056  0.081 
 0.134 -0.016 -0.041 -0.041  0.034 -0.016  0.981  0.009  0.183  0.981 -0.016 -0.016  0.009 -0.041  0.034 -0.016  0.059 -0.041 -0.016 -0.016  0.059 -0.016 -0.016  0.034 -0.041  0.034 -0.016 -0.016  0.009  0.034  0.059  0.009 -0.041  0.059 -0.016  0.034  0.034 -0.016 -0.016 -0.016  0.134  0.233  0.134 -0.041  0.059  0.034  0.009  0.034  0.059  0.034 
 0.109 -0.015 -0.040 -0.040  0.034 -0.015  0.981  0.009  0.184  0.981 -0.015 -0.015  0.009 -0.040  0.034 -0.015  0.059 -0.040 -0.015 -0.015  0.059 -0.015 -0.015  0.034 -0.040  0.034 -0.015 -0.015  0.009  0.034  0.059  0.009 -0.040  0.059 -0.015  0.034  0.034 -0.015 -0.015 -0.015  0.134  0.209  0.134 -0.040  0.059  0.034  0.009  0.034  0.059  0.034 
 0.109 -0.015 -0.040 -0.040  0.034 -0.015  0.981  0.009  0.184  0.981 -0.015 -0.015  0.009 -0.040  0.034 -0.015  0.059 -0.040 -0.015 -0.015  0.059 -0.015 -0.015  0.034 -0.040  0.034 -0.015 -0.015  0.009  0.034  0.059  0.009 -0.040  0.059 -0.015  0.034  0.034 -0.015 -0.015 -0.015  0.134  0.209  0.134 -0.040  0.059  0.034  0.009  0.034  0.059  0.034 
 0.109 -0.015 -0.040 -0.040  0.034 -0.015  0.981  0.009  0.184  0.981 -0.015 -0.015  0.009 -0.040  0.034 -0.015  0.059 -0.040 -0.015 -0.015  0.059 -0.015 -0.015  0.034 -0.040  0.034 -0.015 -0.015  0.009  0.034  0.059  0.009 -0.040  0.059 -0.015  0.034  0.034 -0.015 -0.015 -0.015  0.134  0.209  0.134 -0.040  0.059  0.034  0.009  0.034  0.059  0.034 
 0.109 -0.015 -0.040 -0.040  0.034 -0.015  0.981  0.009  0.184  0.981 -0.015 -0.015  0.009 -0.040  0.034 -0.015  0.059 -0.040 -0.015 -0.015  0.059 -0.015 -0.015  0.034 -0.040  0.034 -0.015 -0.015  0.009  0.034  0.059  0.009 -0.040  0.059 -0.015  0.034  0.034 -0.015 -0.015 -0.015  0.134  0.209  0.134 -0.040  0.059  0.034  0.009  0.034  0.059  0.034 
 0.109 -0.015 -0.040 -0.040  0.034 -0.015  0.981  0.009  0.184  0.981 -0.015 -0.015  0.009 -0.040  0.034 -0.015  0.059 -0.040 -0.015 -0.015  0.059 -0.015 -0.015  0.034 -0.040  0.034 -0.015 -0.015  0.009  0.034  0.059  0.009 -0.040  0.059 -0.015  0.034  0.034 -0.015 -0.015 -0.015  0.134  0.209  0.134 -0.040  0.059  0.034  0.009  0.034  0.059  0.034 
 0.109 -0.015 -0.040 -0.040  0.034 -0.015  0.981  0.009  0.184  0.981 -0.015 -0.015  0.009 -0.040  0.034 -0.015  0.059 -0.040 -0.015 -0.015  0.059 -0.015 -0.015  0.034 -0.040  0.034 -0.015 -0.015  0.009  0.034  0.059  0.009 -0.040  0.059 -0.015  0.034  0.034 -0.015 -0.015 -0.015  0.134  0.209  0.134 -0.040  0.059  0.034  0.009  0.034  0.059  0.034 
 0.149 -0.000  0.024  0.024  0.049 -0.050  0.946 -0.000  0.572  0.946  0.049  0.024  0.024 -0.050  0.024 -0.000  0.124 -0.025 -0.000 -0.000  0.049 -0.025 -0.050  0.049 -0.075 -0.000 -0.050 -0.025 -0.000  0.074  0.249  0.024 -0.025  0.174 -0.000 -0.000  0.074 -0.025 -0.050 -0.025  0.373  0.572  0.249 -0.075  0.049 -0.000 -0.025  0.024  0.074  0.224 
 0.238 -0.011  0.113  0.138  0.038  0.013  0.885  0.063  0.786  0.885  0.113  0.013  0.113 -0.011  0.287  0.163  0.263 -0.036  0.163 -0.011  0.213 -0.011 -0.086  0.088 -0.111  0.013  0.013 -0.011  0.038  0.113  0.462 -0.011 -0.011  0.238  0.013 -0.036  0.238 -0.036 -0.111 -0.061  0.562  0.836  0.387 -0.036  0.038 -0.036 -0.011 -0.011  0.138  0.462 
 0.268  0.068  0.168  0.268  0.018 -0.006  0.841  0.093  0.766  0.841  0.143  0.068  0.093 -0.056  0.317  0.292  0.367 -0.031  0.317 -0.006  0.442 -0.031 -0.081  0.093 -0.131  0.168  0.093 -0.006  0.068  0.168  0.591  0.043  0.018  0.292  0.093  0.018  0.317  0.118 -0.131 -0.031  0.567  0.816  0.442 -0.006  0.068  0.018 -0.056  0.093  0.193  0.666 
 0.302  0.228  0.278  0.302  0.028  0.053  0.776  0.203  0.776  0.776  0.128  0.053  0.128  0.003  0.427  0.452  0.527  0.128  0.576  0.003  0.601 -0.046 -0.071  0.203 -0.171  0.203  0.078  0.028  0.128  0.128  0.601  0.028  0.003  0.427  0.078  0.028  0.352  0.178 -0.121  0.053  0.552  0.776  0.502  0.003  0.178  0.028 -0.046  0.178  0.253  0.726 
 0.331  0.282  0.282  0.232  0.032  0.057  0.730  0.257  0.755  0.755  0.132  0.107  0.107  0.032  0.431  0.506  0.531  0.207  0.580 -0.017  0.630 -0.067 -0.017  0.207 -0.192  0.232  0.032  0.057  0.157  0.082  0.630  0.107  0.057  0.481  0.132  0.057  0.406  0.207 -0.142  0.182  0.531  0.730  0.506  0.132  0.157  0.057 -0.067  0.207  0.257  0.705 
 0.333  0.358  0.283  0.208  0.009  0.059  0.682  0.333  0.657  0.731  0.158  0.183  0.084  0.059  0.482  0.557  0.582  0.208  0.557 -0.041  0.657 -0.041  0.034  0.283 -0.215  0.233  0.059  0.084  0.183  0.059  0.582  0.134  0.134  0.507  0.158  0.109  0.432  0.333 -0.141  0.283  0.482  0.707  0.507  0.233  0.208  0.059 -0.091  0.183  0.308  0.657 
 0.324  0.374  0.274  0.174  0.075  0.100  0.673  0.324  0.623  0.722  0.149  0.224  0.075  0.050  0.473  0.548  0.648  0.249  0.523 -0.050  0.648  0.000  0.050  0.274 -0.224  0.249  0.050  0.075  0.274  0.050  0.573  0.125  0.100  0.498  0.174  0.149  0.399  0.448 -0.149  0.349  0.448  0.698  0.498  0.274  0.199  0.050 -0.075  0.174  0.299  0.648 
 0.312  0.412  0.262  0.162  0.088  0.138  0.636  0.337  0.611  0.710  0.162  0.287  0.088  0.063  0.461  0.561  0.661  0.237  0.511 -0.037  0.636 -0.012  0.138  0.262 -0.236  0.262  0.063  0.063  0.362  0.038  0.536  0.113  0.162  0.486  0.237  0.187  0.387  0.486 -0.137  0.412  0.436  0.686  0.486  0.262  0.187  0.063 -0.087  0.162  0.312  0.636 
 0.309  0.484  0.235  0.160  0.085  0.185  0.608  0.334  0.608  0.708  0.160  0.309  0.085  0.085  0.459  0.559  0.658  0.235  0.509 -0.039  0.633  0.010  0.135  0.260 -0.189  0.260  0.060  0.085  0.409  0.060  0.534  0.110  0.185  0.484  0.235  0.185  0.334  0.509 -0.114  0.459  0.384  0.683  0.484  0.260  0.185  0.060 -0.114  0.160  0.334  0.633 
 0.332  0.507  0.233  0.158  0.058  0.208  0.606  0.332  0.631  0.706  0.158  0.307  0.108  0.108  0.457  0.557  0.656  0.233  0.482 -0.041  0.606  0.033  0.158  0.233 -0.191  0.283  0.033  0.083  0.407  0.058  0.532  0.108  0.208  0.482  0.283  0.183  0.283  0.507 -0.116  0.482  0.357  0.681  0.457  0.233  0.183  0.058 -0.116  0.158  0.332  0.631 
 0.305  0.505  0.231  0.156  0.056  0.206  0.629  0.330  0.629  0.704  0.156  0.305  0.106  0.106  0.455  0.555  0.654  0.231  0.480 -0.043  0.604  0.031  0.181  0.231 -0.193  0.281  0.031  0.081  0.405  0.056  0.530  0.106  0.206  0.480  0.281  0.181  0.305  0.505 -0.118  0.505  0.355  0.679  0.455  0.231  0.181  0.081 -0.093  0.156  0.355  0.629 
 0.278  0.552  0.228  0.153  0.054  0.178  0.627  0.328  0.602  0.677  0.153  0.328  0.129  0.104  0.452  0.552  0.627  0.228  0.477 -0.046  0.602  0.029  0.203  0.228 -0.195  0.278  0.029  0.079  0.378  0.054  0.527  0.104  0.253  0.477  0.303  0.178  0.303  0.527 -0.121  0.502  0.353  0.652  0.427  0.253  0.178  0.104 -0.096  0.104  0.353  0.627 
 0.277  0.551  0.227  0.152  0.053  0.202  0.601  0.327  0.601  0.676  0.152  0.302  0.152  0.103  0.451  0.551  0.626  0.227  0.476 -0.047  0.601  0.028  0.227  0.227 -0.196  0.277  0.028  0.078  0.402  0.053  0.526  0.103  0.227  0.476  0.302  0.202  0.302  0.601 -0.122  0.476  0.352  0.651  0.426  0.227  0.177  0.103 -0.122  0.103  0.352  0.626 
 0.277  0.575  0.227  0.152  0.027  0.227  0.575  0.326  0.600  0.675  0.127  0.326  0.177  0.102  0.426  0.551  0.625  0.202  0.476 -0.047  0.600  0.027  0.227  0.227 -0.172  0.301  0.027  0.077  0.401  0.052  0.526  0.102  0.227  0.476  0.301  0.202  0.277  0.625 -0.122  0.476  0.351  0.650  0.401  0.227  0.177  0.127 -0.122  0.102  0.351  0.625 
 0.273  0.596  0.223  0.148  0.023  0.248  0.571  0.322  0.621  0.671  0.123  0.347  0.173  0.098  0.447  0.547  0.621  0.198  0.472 -0.051  0.596  0.048  0.223  0.223 -0.176  0.322  0.023  0.073  0.397  0.048  0.522  0.098  0.223  0.472  0.297  0.223  0.297  0.621 -0.126  0.497  0.347  0.646  0.397  0.223  0.173  0.123 -0.126  0.098  0.347  0.621 
 0.274  0.598  0.199  0.149  0.025  0.274  0.573  0.324  0.623  0.673  0.149  0.349  0.149  0.100  0.448  0.548  0.623  0.199  0.473 -0.050  0.598  0.075  0.249  0.224 -0.174  0.349  0.025  0.075  0.374  0.050  0.523  0.050  0.249  0.473  0.299  0.224  0.299  0.623 -0.125  0.498  0.324  0.648  0.399  0.224  0.125  0.125 -0.125  0.100  0.349  0.623 
 0.273  0.596  0.198  0.148  0.023  0.273  0.571  0.322  0.621  0.671  0.148  0.322  0.148  0.098  0.447  0.571  0.621  0.198  0.472 -0.051  0.596  0.073  0.273  0.223 -0.176  0.397  0.023  0.073  0.397  0.048  0.547  0.048  0.273  0.472  0.297  0.198  0.297  0.621 -0.126  0.472  0.322  0.621  0.397  0.248  0.123  0.123 -0.126  0.098  0.347  0.621 
 0.272  0.596  0.197  0.147  0.023  0.272  0.571  0.322  0.621  0.671  0.172  0.322  0.172  0.098  0.422  0.571  0.621  0.197  0.471 -0.052  0.596  0.073  0.272  0.222 -0.176  0.422  0.023  0.073  0.397  0.048  0.546  0.023  0.297  0.471  0.297  0.197  0.297  0.621 -0.127  0.471  0.322  0.621  0.397  0.247  0.123  0.147 -0.127  0.098  0.347  0.621 
 0.272  0.595  0.172  0.147  0.047  0.272  0.570  0.321  0.620  0.670  0.197  0.321  0.147  0.097  0.421  0.546  0.620  0.222  0.471 -0.052  0.595  0.072  0.272  0.222 -0.177  0.421  0.022  0.072  0.396  0.047  0.546  0.022  0.346  0.471  0.296  0.197  0.296  0.620 -0.102  0.471  0.321  0.620  0.421  0.247  0.147  0.172 -0.127  0.097  0.346  0.620 
 0.271  0.619  0.171  0.146  0.046  0.271  0.569  0.320  0.619  0.669  0.196  0.345  0.146  0.096  0.420  0.545  0.619  0.221  0.470 -0.053  0.594  0.071  0.295  0.221 -0.178  0.420 -0.003  0.071  0.395  0.046  0.545  0.046  0.370  0.470  0.295  0.196  0.295  0.619 -0.103  0.470  0.295  0.619  0.420  0.246  0.146  0.196 -0.128  0.096  0.320  0.619 
 0.200  0.574  0.225  0.175  0.001  0.175  0.599  0.300  0.524  0.649  0.101  0.300  0.051  0.175  0.375  0.474  0.624  0.175  0.474 -0.049  0.524  0.051  0.200  0.126 -0.099  0.325  0.001  0.001  0.300  0.051  0.549 -0.049  0.325  0.499  0.126  0.076  0.250  0.649 -0.074  0.400  0.275  0.649  0.325  0.250  0.076  0.101 -0.099  0.101  0.225  0.599 
 0.188  0.487  0.238  0.138  0.013  0.088  0.562  0.213  0.487  0.661  0.063  0.213  0.013  0.138  0.387  0.462  0.537  0.088  0.487 -0.036  0.512 -0.036  0.063  0.138 -0.111  0.213  0.013 -0.086  0.188 -0.011  0.586 -0.036  0.238  0.387  0.088  0.063  0.188  0.562 -0.111  0.213  0.312  0.611  0.287  0.188  0.063  0.113 -0.061  0.088  0.238  0.562 
 0.183  0.482  0.233  0.158  0.033  0.108  0.482  0.183  0.457  0.681  0.033  0.183  0.033  0.133  0.382  0.457  0.557  0.083  0.457 -0.041  0.407 -0.041 -0.016  0.183 -0.091  0.208  0.033 -0.091  0.133 -0.016  0.557 -0.041  0.158  0.307  0.058  0.033  0.258  0.581 -0.091  0.083  0.332  0.631  0.208  0.083  0.033  0.033 -0.041  0.033  0.233  0.606 
 0.167  0.441  0.267  0.142  0.018  0.118  0.367  0.167  0.491  0.715  0.043 -0.007  0.068  0.093  0.392  0.392  0.491 -0.007  0.441 -0.032  0.267 -0.057 -0.082  0.068 -0.082  0.142  0.043 -0.107  0.018 -0.032  0.566 -0.007 -0.007  0.167  0.068  0.018  0.192  0.516 -0.057 -0.032  0.292  0.616  0.167  0.018  0.018 -0.007 -0.032  0.018  0.192  0.566 
 0.104  0.328  0.278  0.153  0.029  0.129  0.303  0.129  0.502  0.751  0.029 -0.021  0.029  0.079  0.403  0.278  0.502 -0.021  0.378 -0.021  0.129 -0.046 -0.071  0.029 -0.071  0.104  0.054 -0.096  0.029 -0.021  0.627  0.004 -0.021  0.129  0.079 -0.046  0.153  0.502 -0.046 -0.046  0.228  0.702  0.153  0.054 -0.021  0.004 -0.046 -0.021  0.203  0.477 
 0.091  0.265  0.290  0.116  0.016  0.141  0.240  0.066  0.439  0.788 -0.034 -0.034  0.016  0.066  0.340  0.240  0.489 -0.034  0.365 -0.009  0.066 -0.034 -0.059  0.041 -0.059  0.016  0.066 -0.084  0.016 -0.009  0.664  0.016 -0.034  0.066  0.066 -0.059  0.091  0.390 -0.034 -0.034  0.215  0.763  0.165  0.066 -0.009 -0.009 -0.034  0.016  0.116  0.415 
 0.098  0.222  0.197  0.147  0.023  0.123  0.247  0.023  0.397  0.795 -0.027 -0.052 -0.002  0.048  0.322  0.098  0.446 -0.027  0.347  0.023  0.048 -0.027 -0.052  0.048 -0.052 -0.027  0.073 -0.077  0.023 -0.002  0.696  0.023 -0.052  0.048  0.073 -0.052  0.098  0.322 -0.027 -0.052  0.172  0.845  0.172  0.048 -0.002 -0.002 -0.027  0.023  0.073  0.422 
 0.034  0.109  0.134  0.109  0.009  0.084  0.109  0.034  0.258  0.831 -0.016 -0.041  0.009 -0.016  0.258  0.059  0.283 -0.041  0.333  0.009  0.034 -0.016 -0.041  0.059 -0.041 -0.016  0.084 -0.066  0.034  0.009  0.731  0.034 -0.041  0.009  0.059 -0.041  0.109  0.283 -0.016 -0.041  0.158  0.881  0.134  0.059 -0.016  0.009 -0.041  0.009  0.034  0.333 
 0.016  0.091  0.091  0.091  0.016  0.016  0.116  0.016  0.215  0.838 -0.034 -0.059  0.016 -0.034  0.190  0.066  0.190 -0.034  0.240  0.016  0.041 -0.009 -0.034  0.041 -0.034 -0.009  0.091 -0.059  0.041 -0.009  0.738  0.041 -0.034  0.016  0.066 -0.034  0.116  0.290 -0.034 -0.034  0.116  0.888  0.091  0.041 -0.009  0.016 -0.034  0.016  0.016  0.190 
 0.022 -0.002  0.047  0.097 -0.002 -0.027  0.072  0.022  0.147  0.894 -0.027 -0.052 -0.002 -0.027  0.047  0.022  0.047 -0.027  0.172 -0.002  0.022 -0.002 -0.027  0.072 -0.052 -0.002  0.022 -0.052  0.047  0.022  0.795  0.022 -0.027  0.022  0.047 -0.052  0.097  0.147 -0.052 -0.027  0.097  0.944  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.022 -0.002  0.047  0.097  0.022 -0.027  0.072  0.022  0.147  0.944 -0.027 -0.052 -0.002 -0.027  0.022  0.022  0.022 -0.027  0.097 -0.002 -0.002 -0.002 -0.027  0.072 -0.052  0.022  0.022 -0.027  0.047  0.022  0.820  0.022 -0.027  0.022  0.047 -0.052  0.097  0.097 -0.052 -0.002  0.097  0.944  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.029  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054  0.020  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005 -0.005  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.072 -0.028  0.047  0.196  0.047 -0.053  0.122  0.022  0.271  0.944  0.022 -0.053 -0.003 -0.053  0.022  0.047  0.022 -0.053  0.097 -0.003  0.022 -0.028 -0.003  0.072 -0.078 -0.003  0.047 -0.028  0.097 -0.003  0.944  0.022 -0.003  0.122 -0.003 -0.053  0.072  0.022 -0.078 -0.003  0.146  0.944  0.097  0.022 -0.028 -0.003 -0.028  0.047  0.022  0.196 
 0.043  0.068  0.093  0.268 -0.006 -0.056  0.193  0.068  0.517  0.890  0.043 -0.056  0.068 -0.031  0.118  0.168  0.043  0.018  0.292 -0.031  0.193 -0.056 -0.031  0.243 -0.106 -0.006  0.093 -0.006  0.143  0.043  0.890  0.068  0.018  0.268  0.018 -0.081  0.218  0.118 -0.106  0.118  0.342  0.890  0.193  0.068 -0.056 -0.006 -0.056  0.018  0.018  0.517 
 0.068  0.118  0.218  0.367  0.018 -0.006  0.243  0.093  0.542  0.841  0.118 -0.031  0.068  0.018  0.243  0.442  0.093  0.043  0.417 -0.006  0.392 -0.081 -0.031  0.292 -0.156  0.068  0.068 -0.056  0.218  0.018  0.841  0.018  0.018  0.417  0.043 -0.081  0.268  0.168 -0.156  0.168  0.367  0.841  0.292  0.093 -0.006 -0.031 -0.056  0.118  0.093  0.691 
 0.054  0.179  0.353  0.453 -0.020  0.029  0.353  0.129  0.702  0.777  0.154 -0.095  0.079  0.054  0.378  0.528  0.303  0.104  0.553 -0.020  0.652 -0.070 -0.020  0.378 -0.195  0.054  0.079 -0.045  0.254  0.004  0.777  0.079  0.029  0.478  0.079 -0.020  0.279  0.303 -0.170  0.204  0.428  0.777  0.453  0.179  0.054  0.004 -0.095  0.129  0.204  0.727 
 0.040  0.240  0.339  0.389 -0.034  0.165  0.339  0.190  0.713  0.763  0.140 -0.084  0.115  0.065  0.464  0.539  0.339  0.115  0.588 -0.034  0.713 -0.059 -0.009  0.364 -0.184  0.040  0.040 -0.034  0.240  0.015  0.763  0.115  0.015  0.514  0.065 -0.034  0.314  0.364 -0.184  0.190  0.439  0.763  0.439  0.190  0.090  0.015 -0.109  0.140  0.240  0.713 
 0.067  0.366  0.341  0.366 -0.057  0.167  0.391  0.242  0.690  0.740  0.117 -0.032  0.142  0.092  0.466  0.516  0.441  0.142  0.566 -0.057  0.715 -0.057 -0.032  0.416 -0.207  0.092  0.017  0.017  0.242  0.017  0.715  0.142  0.017  0.541  0.067  0.042  0.291  0.466 -0.207  0.192  0.391  0.740  0.441  0.192  0.117  0.042 -0.082  0.192  0.341  0.690 
 0.084  0.383  0.333  0.333 -0.065  0.209  0.408  0.259  0.682  0.707  0.109 -0.040  0.159  0.109  0.458  0.508  0.508  0.134  0.558 -0.040  0.707 -0.040 -0.015  0.383 -0.215  0.084  0.034  0.034  0.259  0.009  0.682  0.134  0.059  0.533  0.084  0.084  0.284  0.533 -0.215  0.284  0.383  0.732  0.408  0.184  0.134  0.034 -0.090  0.184  0.333  0.682 
 0.070  0.468  0.319  0.319 -0.055  0.244  0.443  0.294  0.693  0.693  0.095 -0.055  0.144  0.120  0.468  0.493  0.593  0.120  0.518 -0.055  0.693 -0.055  0.045  0.394 -0.229  0.120  0.045  0.095  0.319  0.020  0.643  0.144  0.169  0.543  0.070  0.120  0.294  0.518 -0.204  0.394  0.369  0.693  0.369  0.194  0.169  0.045 -0.105  0.169  0.319  0.668 
 0.067  0.491  0.316  0.316 -0.007  0.242  0.416  0.316  0.690  0.690  0.117 -0.057  0.167  0.142  0.441  0.516  0.590  0.117  0.516 -0.057  0.690 -0.057  0.067  0.391 -0.232  0.117  0.067  0.117  0.316  0.017  0.615  0.142  0.192  0.541  0.117  0.142  0.316  0.566 -0.182  0.466  0.366  0.690  0.366  0.192  0.167  0.042 -0.107  0.192  0.316  0.665 
 0.059  0.533  0.284  0.308  0.009  0.259  0.408  0.284  0.682  0.682  0.109  0.009  0.159  0.134  0.408  0.508  0.632  0.109  0.533 -0.065  0.682 -0.040  0.059  0.383 -0.215  0.134  0.059  0.109  0.333  0.009  0.607  0.109  0.209  0.533  0.134  0.134  0.308  0.607 -0.165  0.558  0.358  0.682  0.358  0.209  0.159  0.034 -0.115  0.184  0.259  0.657 
 0.056  0.530  0.281  0.305  0.006  0.281  0.430  0.256  0.679  0.679  0.106  0.031  0.156  0.131  0.405  0.505  0.629  0.081  0.530 -0.068  0.679 -0.043  0.081  0.380 -0.218  0.131  0.056  0.106  0.330  0.006  0.604  0.131  0.206  0.530  0.156  0.131  0.305  0.604 -0.168  0.604  0.330  0.679  0.355  0.231  0.156  0.031 -0.118  0.181  0.256  0.654 
 0.060  0.534  0.284  0.284  0.010  0.309  0.459  0.235  0.683  0.683  0.085  0.085  0.160  0.110  0.384  0.534  0.608  0.085  0.534 -0.064  0.633  0.010  0.110  0.359 -0.214  0.160  0.035  0.085  0.334  0.010  0.608  0.135  0.210  0.534  0.210  0.110  0.309  0.658 -0.139  0.608  0.334  0.683  0.334  0.260  0.160  0.010 -0.114  0.110  0.235  0.608 
 0.082  0.531  0.257  0.282  0.032  0.306  0.456  0.207  0.680  0.680  0.082  0.107  0.157  0.082  0.381  0.531  0.605  0.107  0.531 -0.067  0.605  0.007  0.132  0.356 -0.217  0.157  0.057  0.082  0.331  0.007  0.605  0.132  0.282  0.531  0.232  0.132  0.306  0.655 -0.142  0.605  0.306  0.680  0.331  0.257  0.132  0.007 -0.117  0.107  0.232  0.605 
 0.077  0.575  0.251  0.276  0.052  0.301  0.450  0.201  0.675  0.675  0.102  0.151  0.077  0.077  0.401  0.525  0.600  0.102  0.525 -0.073  0.575  0.002  0.127  0.326 -0.222  0.226  0.052  0.077  0.426  0.002  0.600  0.127  0.326  0.525  0.251  0.127  0.301  0.650 -0.147  0.600  0.276  0.675  0.351  0.276  0.127  0.002 -0.123  0.102  0.226  0.625 
 0.074  0.572  0.249  0.274  0.049  0.323  0.448  0.199  0.672  0.672  0.099  0.149  0.074  0.074  0.373  0.523  0.597  0.099  0.523 -0.075  0.572 -0.000  0.149  0.323 -0.200  0.298  0.049  0.074  0.398 -0.000  0.572  0.149  0.348  0.523  0.249  0.149  0.298  0.647 -0.150  0.597  0.298  0.672  0.348  0.298  0.124 -0.025 -0.125  0.099  0.224  0.622 
 0.071  0.594  0.246  0.246  0.046  0.320  0.445  0.196  0.669  0.669  0.121  0.196  0.046  0.071  0.370  0.520  0.594  0.121  0.495 -0.103  0.569  0.021  0.171  0.295 -0.203  0.345  0.046  0.071  0.445 -0.003  0.569  0.146  0.370  0.520  0.246  0.171  0.295  0.644 -0.153  0.594  0.295  0.669  0.320  0.295  0.121 -0.003 -0.128  0.121  0.221  0.619 
 0.070  0.593  0.194  0.244  0.045  0.319  0.443  0.194  0.668  0.668  0.120  0.194  0.045  0.070  0.369  0.493  0.593  0.120  0.493 -0.105  0.568  0.020  0.169  0.294 -0.204  0.369  0.045  0.070  0.468 -0.005  0.568  0.144  0.369  0.518  0.244  0.194  0.294  0.643 -0.154  0.593  0.294  0.668  0.319  0.294  0.120 -0.005 -0.130  0.120  0.219  0.618 
 0.073  0.596  0.197  0.197  0.048  0.322  0.446  0.197  0.671  0.646  0.123  0.222 -0.002  0.098  0.372  0.496  0.596  0.123  0.471 -0.127  0.546  0.023  0.222  0.297 -0.201  0.397  0.048  0.073  0.496 -0.002  0.571  0.098  0.372  0.521  0.247  0.222  0.272  0.646 -0.151  0.596  0.297  0.646  0.347  0.297  0.123 -0.002 -0.151  0.123  0.222  0.621 
 0.077  0.600  0.177  0.152  0.052  0.326  0.451  0.202  0.650  0.650  0.127  0.252 -0.072  0.127  0.376  0.501  0.600  0.127  0.476 -0.122  0.551  0.052  0.227  0.277 -0.172  0.401  0.077  0.102  0.501  0.002  0.575  0.102  0.376  0.526  0.227  0.252  0.277  0.650 -0.147  0.600  0.277  0.650  0.351  0.277  0.102  0.002 -0.147  0.152  0.227  0.625 
 0.079  0.602  0.179  0.154  0.054  0.328  0.453  0.229  0.652  0.627  0.104  0.254 -0.095  0.129  0.378  0.478  0.602  0.179  0.478 -0.120  0.553  0.104  0.204  0.279 -0.170  0.378  0.079  0.104  0.503  0.004  0.577  0.054  0.378  0.528  0.229  0.279  0.303  0.627 -0.120  0.602  0.279  0.652  0.353  0.353  0.104 -0.045 -0.145  0.154  0.229  0.627 
 0.147  0.570  0.197  0.197 -0.027  0.346  0.421  0.197  0.645  0.645  0.122  0.197 -0.077  0.172  0.421  0.471  0.546  0.172  0.471 -0.127  0.595  0.097  0.147  0.222 -0.127  0.247  0.022  0.097  0.446  0.022  0.570 -0.002  0.247  0.595  0.147  0.147  0.247  0.521 -0.077  0.496  0.296  0.645  0.247  0.247  0.072 -0.027 -0.152  0.222  0.147  0.570 
 0.115  0.564  0.165  0.215  0.040  0.215  0.364  0.165  0.588  0.688  0.090 -0.009 -0.009  0.115  0.439  0.439  0.464  0.115  0.489 -0.059  0.588  0.015  0.015  0.215 -0.059  0.090 -0.009  0.040  0.289  0.015  0.564  0.015  0.140  0.464  0.140  0.065  0.165  0.389 -0.009  0.389  0.289  0.638  0.215  0.190  0.015  0.015 -0.059  0.165  0.140  0.539 
 0.135  0.558  0.184  0.209  0.035  0.159  0.259  0.159  0.608  0.683  0.035 -0.040  0.010  0.135  0.433  0.433  0.409  0.110  0.409 -0.065  0.583 -0.040 -0.015  0.159 -0.090  0.035  0.060 -0.065  0.259  0.035  0.583  0.010  0.060  0.483  0.159  0.035  0.159  0.334 -0.040  0.359  0.259  0.633  0.184  0.135 -0.015  0.035 -0.040  0.159  0.159  0.483 
 0.140  0.464  0.215  0.190  0.040  0.115  0.240  0.165  0.588  0.738  0.040  0.015 -0.009  0.090  0.414  0.339  0.414  0.040  0.389 -0.034  0.613 -0.059 -0.084  0.040 -0.084 -0.009  0.065 -0.059  0.040  0.065  0.613  0.015 -0.034  0.314  0.065 -0.009  0.140  0.265 -0.034  0.190  0.215  0.688  0.165  0.065  0.015 -0.009 -0.009  0.090  0.140  0.439 
 0.118  0.491  0.192  0.192  0.043  0.118  0.217  0.167  0.616  0.765  0.018  0.018 -0.007  0.043  0.392  0.342  0.417 -0.007  0.392 -0.057  0.591 -0.057 -0.082  0.043 -0.082 -0.032  0.068 -0.057  0.018  0.068  0.616  0.018 -0.032  0.267  0.068  0.018  0.118  0.267 -0.057  0.068  0.217  0.691  0.142  0.043 -0.032 -0.032 -0.007  0.068  0.142  0.417 
 0.107  0.431  0.157  0.207  0.057  0.157  0.232  0.182  0.630  0.805  0.007 -0.017  0.007  0.057  0.381  0.182  0.381 -0.042  0.356 -0.042  0.381 -0.042 -0.067  0.032 -0.067 -0.067  0.057 -0.067  0.007  0.032  0.630  0.007 -0.042  0.107  0.082  0.007  0.107  0.207 -0.042 -0.042  0.232  0.705  0.157  0.007 -0.017 -0.017 -0.017  0.057  0.132  0.406 
 0.086  0.410  0.186  0.186  0.036  0.136  0.236  0.186  0.634  0.809 -0.013 -0.013  0.011  0.036  0.385  0.161  0.385 -0.038  0.360 -0.038  0.211 -0.038 -0.063  0.036 -0.063 -0.063  0.061 -0.063  0.011  0.036  0.634  0.011 -0.063  0.086  0.086 -0.013  0.111  0.211 -0.038 -0.038  0.186  0.759  0.161  0.036 -0.013 -0.013 -0.013  0.061  0.136  0.385 
 0.072  0.246  0.146  0.171  0.047  0.097  0.146  0.122  0.470  0.869 -0.003 -0.053 -0.003  0.047  0.346  0.122  0.296 -0.028  0.371 -0.028  0.122 -0.028 -0.053  0.047 -0.053 -0.028  0.072 -0.078  0.022 -0.003  0.695 -0.003 -0.053  0.047  0.097 -0.028  0.122  0.221 -0.028 -0.053  0.171  0.794  0.122  0.072 -0.028 -0.003 -0.028 -0.003  0.122  0.396 
 0.076  0.226  0.151  0.176  0.051  0.101  0.151  0.076  0.400  0.898  0.001 -0.048  0.001  0.051  0.300  0.101  0.276 -0.023  0.350 -0.023  0.101 -0.023 -0.048  0.051 -0.048 -0.023  0.076 -0.073  0.026  0.001  0.699  0.001 -0.048  0.051  0.101 -0.023  0.126  0.201 -0.023 -0.048  0.151  0.824  0.151  0.076 -0.023 -0.023 -0.023  0.001  0.126  0.350 
 0.064  0.064  0.064  0.164  0.014 -0.035  0.139  0.039  0.288  0.936 -0.010 -0.060  0.014 -0.035  0.189  0.064  0.189 -0.035  0.239 -0.010  0.039 -0.010 -0.035  0.064 -0.060 -0.010  0.039 -0.060  0.014  0.014  0.737  0.014 -0.035  0.039  0.039 -0.060  0.089  0.089 -0.035 -0.035  0.139  0.911  0.089  0.064 -0.010 -0.010 -0.010  0.014  0.089  0.214 
 0.020 -0.005  0.070  0.120 -0.005 -0.030  0.070  0.020  0.194  0.942 -0.005 -0.055  0.020 -0.030  0.120  0.020  0.095 -0.030  0.194 -0.030  0.020 -0.005 -0.030  0.070 -0.055 -0.005  0.020 -0.055  0.020  0.020  0.767 -0.005 -0.030  0.020  0.045 -0.055  0.095  0.095 -0.055 -0.030  0.144  0.917  0.095  0.045 -0.005 -0.005 -0.005  0.020  0.020  0.169 
 0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.073 -0.001 -0.001 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.023  0.023  0.771  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.048 -0.001 -0.001 -0.001  0.023 -0.001  0.098 
 0.021 -0.028  0.046  0.096  0.021 -0.028  0.071  0.021  0.146  0.968 -0.028 -0.028 -0.003 -0.028  0.021  0.021 -0.003 -0.028  0.071 -0.003 -0.003 -0.003 -0.028  0.071 -0.053  0.021 -0.003 -0.028  0.046  0.021  0.868  0.021 -0.028  0.046  0.021 -0.053  0.096  0.046 -0.053 -0.003  0.096  0.968  0.096  0.046 -0.003 -0.003 -0.003  0.021 -0.003  0.096 
 0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004 -0.029  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054  0.021  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
 0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005 -0.030  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.055  0.030  0.105  0.105  0.055  0.005  0.154 -0.020  0.478  0.927 -0.020 -0.045  0.080 -0.020  0.105  0.080  0.055  0.055  0.154 -0.020 -0.020 -0.045 -0.020  0.204 -0.070 -0.020  0.105 -0.020  0.080  0.055  0.927  0.005  0.005  0.105  0.005 -0.070  0.130  0.105 -0.070  0.030  0.179  0.927  0.130  0.055 -0.045  0.005 -0.020  0.030  0.030  0.204 
 0.119  0.143  0.168  0.143  0.044 -0.006  0.318  0.094  0.692  0.866  0.044 -0.056  0.094 -0.031  0.243  0.168  0.119  0.094  0.318 -0.006  0.069 -0.106 -0.006  0.318 -0.106 -0.031  0.218 -0.056  0.119  0.069  0.866 -0.031 -0.031  0.393 -0.031 -0.131  0.293  0.168 -0.106  0.119  0.418  0.866  0.268  0.044 -0.081 -0.006 -0.031  0.069  0.094  0.542 
 0.200  0.250  0.275  0.200  0.025  0.075  0.424  0.200  0.698  0.823  0.050 -0.074  0.050  0.000  0.324  0.299  0.225  0.125  0.399  0.050  0.200 -0.149  0.050  0.299 -0.124  0.025  0.225 -0.049  0.050  0.075  0.823 -0.024  0.050  0.524  0.000 -0.099  0.324  0.250 -0.124  0.100  0.449  0.823  0.349  0.125 -0.074  0.050 -0.074  0.000  0.150  0.623 
 0.217  0.392  0.267  0.217 -0.007  0.093  0.591  0.217  0.691  0.765  0.142 -0.057  0.043  0.043  0.367  0.591  0.342  0.142  0.516 -0.007  0.491 -0.082  0.043  0.417 -0.206  0.043  0.167 -0.057  0.118  0.043  0.765 -0.007  0.118  0.641  0.018 -0.032  0.392  0.466 -0.156  0.192  0.441  0.765  0.466  0.142  0.142  0.093 -0.107  0.043  0.292  0.740 
 0.223  0.373  0.298  0.198  0.024  0.099  0.622  0.248  0.672  0.746  0.173 -0.076  0.074  0.074  0.348  0.622  0.373  0.124  0.547 -0.026  0.522 -0.101  0.049  0.423 -0.225  0.099  0.124 -0.001  0.223  0.024  0.746 -0.001  0.148  0.622  0.049 -0.001  0.373  0.547 -0.175  0.223  0.447  0.746  0.497  0.148  0.124  0.099 -0.101  0.049  0.298  0.721 
 0.204  0.478  0.304  0.154  0.055  0.105  0.653  0.229  0.653  0.727  0.179 -0.070  0.080  0.080  0.354  0.628  0.478  0.179  0.528 -0.020  0.578 -0.095  0.130  0.428 -0.194  0.105  0.105  0.055  0.279  0.005  0.703  0.005  0.204  0.603  0.105  0.030  0.354  0.603 -0.169  0.404  0.379  0.703  0.453  0.130  0.130  0.080 -0.120  0.030  0.304  0.703 
 0.197  0.521  0.297  0.147  0.048  0.172  0.646  0.247  0.646  0.720  0.147 -0.077  0.048  0.073  0.347  0.596  0.621  0.172  0.521 -0.027  0.571 -0.102  0.098  0.397 -0.201  0.098  0.073  0.073  0.297 -0.002  0.696  0.048  0.172  0.596  0.098  0.048  0.347  0.646 -0.151  0.422  0.347  0.696  0.446  0.147  0.123  0.073 -0.127  0.023  0.297  0.696 
 0.187  0.536  0.262  0.137  0.062  0.237  0.635  0.286  0.660  0.710  0.137 -0.062  0.037  0.087  0.386  0.561  0.635  0.187  0.486 -0.037  0.561 -0.087  0.087  0.361 -0.212  0.137  0.062  0.087  0.336  0.012  0.685  0.037  0.162  0.561  0.187  0.112  0.336  0.635 -0.162  0.561  0.311  0.685  0.386  0.187  0.162  0.062 -0.137  0.062  0.262  0.660 
 0.206  0.530  0.256  0.132  0.057  0.256  0.630  0.306  0.680  0.680  0.132  0.032  0.032  0.082  0.381  0.555  0.630  0.206  0.480 -0.043  0.555 -0.018  0.107  0.381 -0.217  0.132  0.057  0.082  0.331  0.007  0.630  0.132  0.181  0.555  0.231  0.132  0.331  0.630 -0.118  0.555  0.306  0.680  0.356  0.206  0.156  0.057 -0.142  0.082  0.256  0.630 
 0.204  0.503  0.254  0.130  0.055  0.254  0.603  0.304  0.678  0.678  0.179  0.055  0.005  0.080  0.404  0.553  0.628  0.204  0.478 -0.045  0.553  0.005  0.130  0.354 -0.219  0.130  0.055  0.080  0.329  0.005  0.628  0.130  0.179  0.578  0.229  0.154  0.329  0.628 -0.120  0.578  0.304  0.678  0.354  0.229  0.154  0.105 -0.144  0.080  0.229  0.603 
 0.176  0.525  0.251  0.126  0.051  0.276  0.599  0.300  0.674  0.674  0.176  0.101  0.001  0.076  0.375  0.550  0.624  0.226  0.500 -0.048  0.550  0.026  0.126  0.350 -0.223  0.151  0.051  0.076  0.350  0.001  0.649  0.151  0.176  0.574  0.226  0.151  0.325  0.624 -0.148  0.599  0.325  0.674  0.350  0.226  0.151  0.126 -0.148  0.076  0.226  0.599 
 0.177  0.526  0.252  0.127  0.052  0.301  0.600  0.277  0.675  0.675  0.202  0.102 -0.022  0.077  0.376  0.551  0.600  0.202  0.501 -0.047  0.551  0.027  0.152  0.326 -0.222  0.152  0.052  0.077  0.426  0.002  0.650  0.152  0.177  0.551  0.227  0.152  0.326  0.625 -0.147  0.600  0.326  0.675  0.351  0.227  0.152  0.127 -0.147  0.077  0.227  0.600 
 0.175  0.499  0.250  0.150  0.051  0.300  0.599  0.275  0.674  0.674  0.200  0.101 -0.024  0.076  0.375  0.549  0.599  0.200  0.499 -0.049  0.549  0.026  0.150  0.350 -0.223  0.150  0.051  0.076  0.449  0.001  0.649  0.175  0.175  0.549  0.225  0.175  0.325  0.624 -0.148  0.599  0.325  0.674  0.350  0.225  0.150  0.126 -0.124  0.076  0.225  0.599 
 0.199  0.498  0.249  0.149  0.049  0.298  0.622  0.274  0.672  0.672  0.199  0.149 -0.025  0.099  0.423  0.548  0.597  0.199  0.498 -0.050  0.548  0.024  0.174  0.323 -0.225  0.174  0.049  0.074  0.448 -0.000  0.622  0.174  0.199  0.548  0.249  0.174  0.323  0.622 -0.125  0.597  0.323  0.672  0.348  0.224  0.149  0.124 -0.125  0.099  0.224  0.597 
 0.221  0.495  0.246  0.146  0.046  0.295  0.619  0.320  0.669  0.669  0.196  0.246 -0.028  0.096  0.445  0.545  0.594  0.221  0.495 -0.053  0.520  0.021  0.196  0.295 -0.228  0.171  0.046  0.071  0.445 -0.003  0.619  0.146  0.196  0.545  0.246  0.196  0.320  0.619 -0.128  0.594  0.320  0.669  0.370  0.221  0.146  0.121 -0.128  0.096  0.221  0.594 
 0.221  0.495  0.246  0.146  0.047  0.296  0.620  0.321  0.670  0.670  0.196  0.271 -0.028  0.097  0.421  0.545  0.595  0.221  0.495 -0.053  0.520  0.022  0.196  0.271 -0.227  0.196  0.047  0.072  0.421 -0.003  0.620  0.171  0.196  0.545  0.246  0.196  0.321  0.620 -0.128  0.595  0.321  0.670  0.371  0.221  0.146  0.122 -0.128  0.122  0.221  0.595 
 0.223  0.497  0.248  0.148  0.048  0.297  0.621  0.322  0.671  0.671  0.198  0.273 -0.126  0.098  0.422  0.547  0.596  0.223  0.497 -0.051  0.522  0.023  0.198  0.248 -0.226  0.223  0.048  0.073  0.422 -0.001  0.646  0.173  0.223  0.547  0.223  0.223  0.322  0.621 -0.126  0.596  0.322  0.671  0.372  0.223  0.148  0.123 -0.126  0.123  0.223  0.571 
 0.222  0.496  0.247  0.147  0.048  0.297  0.621  0.322  0.671  0.671  0.197  0.272 -0.127  0.123  0.422  0.546  0.596  0.222  0.496 -0.052  0.521  0.023  0.197  0.247 -0.226  0.222  0.073  0.098  0.422 -0.002  0.646  0.172  0.222  0.546  0.222  0.297  0.322  0.621 -0.127  0.596  0.322  0.671  0.372  0.222  0.123  0.123 -0.127  0.147  0.222  0.571 
 0.224  0.498  0.224  0.149  0.049  0.298  0.597  0.323  0.647  0.672  0.199  0.274 -0.125  0.124  0.423  0.548  0.597  0.224  0.498 -0.050  0.523  0.024  0.199  0.249 -0.225  0.224  0.074  0.099  0.423 -0.000  0.647  0.174  0.224  0.523  0.224  0.323  0.298  0.622 -0.125  0.597  0.323  0.672  0.373  0.224  0.124  0.124 -0.125  0.149  0.224  0.572 
 0.223  0.497  0.223  0.148  0.049  0.323  0.597  0.323  0.647  0.672  0.198  0.273 -0.126  0.124  0.398  0.547  0.597  0.223  0.497 -0.051  0.522  0.049  0.198  0.248 -0.200  0.248  0.074  0.099  0.423 -0.001  0.647  0.173  0.223  0.522  0.223  0.323  0.298  0.622 -0.126  0.597  0.323  0.672  0.398  0.223  0.148  0.099 -0.126  0.148  0.223  0.572 
 0.253  0.502  0.203  0.203  0.053  0.203  0.626  0.278  0.576  0.676  0.153  0.153 -0.071  0.128  0.402  0.477  0.552  0.128  0.452 -0.171  0.502  0.053  0.103  0.253 -0.146  0.178  0.053  0.028  0.377  0.028  0.676  0.153  0.128  0.527  0.178  0.278  0.278  0.576 -0.146  0.477  0.352  0.726  0.402  0.103  0.078  0.078 -0.096  0.178  0.153  0.477 
 0.246  0.495  0.196  0.271  0.021  0.096  0.520  0.171  0.545  0.644  0.096  0.021  0.021  0.121  0.395  0.420  0.445  0.046  0.370 -0.078  0.545  0.021 -0.028  0.171 -0.128  0.071  0.046 -0.028  0.196  0.071  0.619  0.021  0.046  0.470  0.121  0.121  0.246  0.395 -0.078  0.345  0.320  0.769  0.271  0.096  0.071 -0.003 -0.053  0.121  0.171  0.445 
 0.167  0.516  0.217  0.242  0.018  0.093  0.392  0.167  0.516  0.691  0.018  0.018  0.018  0.118  0.392  0.392  0.466  0.018  0.367 -0.057  0.516 -0.032 -0.032  0.167 -0.107 -0.007  0.068 -0.032  0.093  0.043  0.616  0.018  0.068  0.367  0.068  0.093  0.217  0.342 -0.082  0.292  0.317  0.740  0.267  0.018  0.043 -0.032 -0.032  0.043  0.118  0.417 
 0.143  0.417  0.268  0.218  0.018  0.118  0.292  0.168  0.542  0.766  0.043  0.018  0.018  0.118  0.342  0.342  0.467  0.018  0.417 -0.031  0.442 -0.056 -0.081  0.018 -0.081 -0.031  0.043 -0.081  0.043  0.018  0.616  0.018 -0.006  0.317  0.093  0.018  0.168  0.367 -0.056  0.143  0.243  0.766  0.168  0.043  0.018 -0.006 -0.056  0.043  0.118  0.367 
 0.100  0.349  0.275  0.200  0.025  0.075  0.250  0.125  0.549  0.798  0.025  0.025  0.000  0.100  0.299  0.324  0.474  0.000  0.399 -0.049  0.424 -0.049 -0.074  0.000 -0.074 -0.024  0.050 -0.074  0.050  0.000  0.648  0.025  0.000  0.250  0.075  0.000  0.100  0.374 -0.049  0.025  0.250  0.773  0.150  0.050  0.000 -0.024 -0.049  0.025  0.125  0.374 
 0.088  0.287  0.287  0.212  0.038  0.063  0.212  0.088  0.536  0.810  0.013  0.013  0.013  0.063  0.262  0.212  0.486 -0.012  0.362 -0.037  0.212 -0.037 -0.062  0.013 -0.062 -0.012  0.063 -0.087  0.013 -0.012  0.661  0.013 -0.012  0.162  0.088 -0.037  0.113  0.362 -0.037 -0.037  0.212  0.810  0.138  0.063 -0.037 -0.012 -0.037  0.013  0.113  0.362 
 0.068  0.242  0.217  0.192  0.043  0.093  0.192  0.093  0.516  0.815 -0.007  0.018  0.018  0.043  0.217  0.142  0.417 -0.007  0.392 -0.032  0.142 -0.032 -0.057  0.043 -0.057 -0.032  0.068 -0.082  0.018 -0.007  0.715  0.018 -0.032  0.167  0.093 -0.057  0.118  0.317 -0.032 -0.032  0.217  0.815  0.142  0.068 -0.032 -0.007 -0.032  0.018  0.093  0.342 
 0.056  0.131  0.131  0.156  0.031  0.031  0.131  0.056  0.430  0.829 -0.018 -0.018  0.006 -0.018  0.156  0.056  0.330 -0.043  0.380 -0.018  0.056 -0.018 -0.043  0.081 -0.043 -0.018  0.081 -0.068  0.031  0.006  0.704  0.031 -0.043  0.081  0.081 -0.043  0.131  0.281 -0.018 -0.018  0.181  0.853  0.131  0.056 -0.018 -0.018 -0.043  0.006  0.081  0.305 
 0.061  0.061  0.061  0.161  0.036  0.011  0.136  0.036  0.410  0.858 -0.038 -0.013  0.011 -0.038  0.086  0.036  0.236 -0.038  0.285  0.011  0.036 -0.013 -0.038  0.061 -0.038 -0.013  0.086 -0.063  0.036  0.036  0.709  0.036 -0.038  0.086  0.061 -0.038  0.111  0.136 -0.038 -0.038  0.161  0.958  0.111  0.061 -0.013 -0.013 -0.038  0.011  0.086  0.236 
 0.043  0.018  0.043  0.118  0.018 -0.007  0.118  0.043  0.217  0.940 -0.032 -0.032  0.018 -0.032  0.068  0.018  0.167 -0.032  0.242 -0.007  0.043 -0.007 -0.032  0.068 -0.032  0.018  0.043 -0.032  0.018  0.043  0.715  0.043 -0.032  0.068  0.068 -0.057  0.118  0.142 -0.032 -0.032  0.118  0.965  0.118  0.068 -0.007 -0.007 -0.007  0.018  0.018  0.167 
 0.045 -0.005  0.045  0.120  0.020 -0.005  0.095  0.045  0.219  0.942 -0.030 -0.030  0.020 -0.030  0.045  0.020  0.120 -0.030  0.219 -0.005  0.020 -0.005 -0.030  0.070 -0.030  0.020  0.045 -0.030  0.020  0.045  0.717  0.020 -0.030  0.070  0.070 -0.055  0.120  0.144 -0.055 -0.030  0.120  0.967  0.120  0.020 -0.005 -0.005 -0.005  0.020 -0.030  0.120 
 0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.098 -0.001  0.023 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.048  0.023  0.746  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.023 -0.001 -0.001 -0.001  0.023 -0.026  0.098 
 0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.098 -0.001  0.023 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.048  0.023  0.746  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.023 -0.001 -0.001 -0.001  0.023 -0.026  0.098 
 0.022 -0.027  0.047  0.097  0.022 -0.027  0.072  0.022  0.147  0.969 -0.027 -0.027 -0.002 -0.027  0.022  0.022 -0.002 -0.027  0.072 -0.002 -0.002 -0.002 -0.027  0.072 -0.052  0.022 -0.002 -0.027  0.047  0.022  0.820  0.022 -0.027  0.047  0.022 -0.052  0.097  0.047 -0.052 -0.027  0.097  0.969  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.022 -0.028  0.047  0.097  0.022 -0.028  0.072  0.022  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.844  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.003  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.021 -0.028  0.046  0.096  0.021 -0.028  0.071  0.021  0.146  0.968 -0.028 -0.028 -0.003 -0.028  0.021  0.021 -0.003 -0.028  0.071 -0.003 -0.003 -0.003 -0.028  0.071 -0.053  0.021 -0.003 -0.028  0.046  0.021  0.868  0.021 -0.028  0.046  0.021 -0.053  0.096  0.046 -0.053 -0.003  0.096  0.968  0.096  0.046 -0.003 -0.003 -0.003  0.021 -0.003  0.096 
 0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004 -0.029  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054 -0.004  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.087 -0.012  0.087  0.162  0.037 -0.062  0.087  0.012  0.436  0.934 -0.037 -0.012  0.037 -0.012  0.062  0.062  0.187 -0.062  0.162 -0.012 -0.012 -0.037 -0.012  0.062 -0.062  0.012  0.062  0.012  0.062  0.062  0.934  0.012 -0.012  0.087  0.037 -0.062  0.137  0.162 -0.087  0.012  0.112  0.934  0.112  0.012 -0.037 -0.012 -0.037  0.037  0.012  0.187 
 0.104  0.129  0.179  0.378  0.004 -0.045  0.179  0.054  0.702  0.876  0.029 -0.045  0.054  0.004  0.129  0.079  0.303  0.029  0.478  0.004  0.204 -0.045 -0.045  0.204 -0.120  0.004  0.079  0.029  0.179  0.079  0.876  0.004 -0.020  0.229  0.029 -0.045  0.154  0.353 -0.120  0.029  0.229  0.876  0.254  0.079 -0.045 -0.045 -0.070  0.029  0.154  0.403 
 0.108  0.283  0.258  0.332  0.058 -0.016  0.233  0.083  0.781  0.831  0.083 -0.091  0.083  0.033  0.307  0.183  0.382  0.058  0.557 -0.041  0.307 -0.041 -0.016  0.332 -0.166  0.008  0.083  0.058  0.208  0.033  0.831  0.033  0.033  0.283  0.083 -0.066  0.233  0.482 -0.166  0.008  0.357  0.831  0.307  0.158 -0.091 -0.091 -0.066  0.033  0.183  0.557 
 0.067  0.391  0.291  0.366 -0.008  0.042  0.266  0.117  0.739  0.764  0.092 -0.083  0.142  0.042  0.440  0.440  0.515  0.117  0.590 -0.033  0.515 -0.008 -0.058  0.391 -0.182  0.142  0.067  0.092  0.216  0.042  0.739  0.067  0.067  0.465  0.092 -0.083  0.241  0.640 -0.182  0.142  0.416  0.764  0.391  0.191  0.042 -0.058 -0.108  0.092  0.366  0.714 
 0.049  0.498  0.274  0.323 -0.025  0.074  0.298  0.149  0.722  0.747  0.099 -0.075  0.124  0.074  0.448  0.498  0.597  0.124  0.572 -0.050  0.622 -0.000 -0.075  0.398 -0.200  0.124  0.049  0.099  0.224  0.024  0.697  0.099  0.124  0.523  0.099 -0.025  0.249  0.697 -0.175  0.149  0.398  0.747  0.423  0.224  0.099 -0.025 -0.100  0.074  0.398  0.697 
 0.034  0.532  0.308  0.283 -0.041  0.084  0.308  0.134  0.707  0.731  0.084 -0.041  0.158  0.134  0.432  0.557  0.657  0.109  0.507 -0.066  0.657 -0.016 -0.041  0.358 -0.215  0.183  0.059  0.109  0.208  0.009  0.657  0.059  0.158  0.557  0.208 -0.016  0.258  0.682 -0.190  0.283  0.383  0.707  0.408  0.258  0.134 -0.016 -0.116  0.084  0.383  0.682 
 0.050  0.524  0.299  0.275  0.050  0.125  0.349  0.125  0.698  0.723  0.150 -0.024  0.150  0.125  0.449  0.524  0.648  0.125  0.524 -0.049  0.648 -0.024  0.025  0.374 -0.199  0.175  0.050  0.100  0.200  0.000  0.623  0.050  0.250  0.573  0.175  0.000  0.250  0.673 -0.199  0.399  0.374  0.698  0.424  0.250  0.125  0.000 -0.124  0.100  0.349  0.673 
 0.070  0.544  0.270  0.245  0.095  0.220  0.419  0.145  0.693  0.718  0.145  0.070  0.120  0.120  0.444  0.544  0.643  0.145  0.519 -0.054  0.643 -0.029  0.045  0.369 -0.204  0.170  0.070  0.095  0.220  0.020  0.544  0.045  0.344  0.568  0.220  0.020  0.294  0.668 -0.154  0.469  0.369  0.693  0.419  0.319  0.145 -0.029 -0.129  0.120  0.319  0.668 
 0.092  0.541  0.267  0.267  0.092  0.267  0.441  0.142  0.690  0.715  0.142  0.117  0.117  0.117  0.391  0.541  0.640  0.142  0.516 -0.057  0.615 -0.007  0.067  0.341 -0.207  0.167  0.067  0.092  0.267  0.017  0.541  0.042  0.341  0.566  0.242  0.042  0.316  0.665 -0.132  0.491  0.366  0.690  0.416  0.341  0.142 -0.007 -0.132  0.092  0.291  0.665 
 0.084  0.533  0.234  0.259  0.084  0.308  0.433  0.134  0.682  0.707  0.159  0.159  0.109  0.109  0.383  0.533  0.632  0.184  0.508 -0.065  0.582  0.034  0.084  0.308 -0.190  0.259  0.059  0.084  0.308  0.034  0.533  0.059  0.383  0.533  0.259  0.059  0.284  0.657 -0.140  0.558  0.358  0.682  0.408  0.408  0.084  0.034 -0.140  0.084  0.284  0.632 
 0.085  0.533  0.234  0.234  0.085  0.334  0.433  0.135  0.683  0.683  0.159  0.184  0.135  0.110  0.409  0.483  0.633  0.184  0.483 -0.065  0.583  0.060  0.085  0.259 -0.189  0.259  0.060  0.085  0.359  0.035  0.533  0.060  0.384  0.508  0.259  0.085  0.284  0.658 -0.140  0.583  0.359  0.683  0.384  0.409  0.085  0.010 -0.115  0.110  0.284  0.633 
 0.082  0.531  0.207  0.232  0.082  0.331  0.456  0.157  0.680  0.680  0.157  0.207  0.132  0.082  0.406  0.481  0.630  0.182  0.481 -0.067  0.580  0.082  0.107  0.232 -0.167  0.282  0.057  0.082  0.356  0.032  0.506  0.057  0.431  0.506  0.257  0.107  0.282  0.655 -0.117  0.580  0.356  0.680  0.381  0.406  0.082 -0.017 -0.117  0.107  0.282  0.630 
 0.078  0.527  0.178  0.228  0.078  0.302  0.452  0.153  0.676  0.676  0.153  0.203  0.128  0.078  0.402  0.477  0.626  0.178  0.477 -0.071  0.601  0.128  0.128  0.228 -0.146  0.302  0.053  0.103  0.377  0.028  0.502  0.053  0.452  0.502  0.253  0.103  0.278  0.651 -0.121  0.576  0.352  0.676  0.402  0.402  0.103 -0.021 -0.121  0.103  0.278  0.626 
 0.078  0.551  0.177  0.152  0.103  0.302  0.451  0.152  0.676  0.676  0.152  0.227  0.152  0.078  0.402  0.476  0.626  0.177  0.476 -0.097  0.626  0.152  0.177  0.252 -0.146  0.327  0.053  0.103  0.402  0.028  0.501  0.028  0.451  0.476  0.252  0.128  0.302  0.651 -0.097  0.576  0.352  0.651  0.426  0.402  0.103 -0.022 -0.122  0.103  0.252  0.626 
 0.076  0.550  0.176  0.126  0.101  0.325  0.450  0.151  0.649  0.674  0.151  0.226  0.151  0.076  0.400  0.475  0.624  0.176  0.475 -0.098  0.624  0.151  0.176  0.226 -0.148  0.350  0.051  0.101  0.450  0.026  0.525  0.026  0.450  0.500  0.251  0.101  0.300  0.649 -0.098  0.574  0.350  0.649  0.425  0.425  0.101 -0.023 -0.148  0.101  0.251  0.624 
 0.076  0.549  0.150  0.126  0.076  0.325  0.449  0.150  0.624  0.649  0.150  0.225  0.150  0.101  0.400  0.449  0.624  0.175  0.474 -0.099  0.624  0.150  0.225  0.225 -0.148  0.375  0.026  0.101  0.474  0.001  0.549  0.001  0.474  0.499  0.250  0.101  0.300  0.649 -0.099  0.574  0.350  0.624  0.425  0.425  0.101 -0.024 -0.173  0.101  0.225  0.624 
 0.076  0.549  0.150  0.126  0.076  0.325  0.449  0.150  0.599  0.649  0.150  0.250  0.126  0.101  0.400  0.449  0.624  0.175  0.449 -0.124  0.624  0.126  0.225  0.250 -0.173  0.375  0.001  0.101  0.474  0.001  0.549  0.001  0.474  0.499  0.250  0.101  0.300  0.649 -0.099  0.574  0.325  0.624  0.425  0.425  0.101 -0.024 -0.198  0.101  0.250  0.624 
 0.125  0.549  0.150  0.125  0.100  0.299  0.449  0.175  0.598  0.648  0.150  0.275  0.125  0.100  0.399  0.449  0.623  0.175  0.449 -0.149  0.623  0.125  0.225  0.250 -0.174  0.374  0.025  0.100  0.474  0.000  0.549  0.000  0.474  0.499  0.250  0.100  0.299  0.648 -0.074  0.573  0.324  0.623  0.424  0.424  0.100 -0.024 -0.199  0.100  0.250  0.623 
 0.149  0.548  0.149  0.149  0.075  0.299  0.473  0.199  0.598  0.623  0.174  0.274  0.125  0.125  0.399  0.448  0.648  0.199  0.448 -0.149  0.623  0.100  0.249  0.249 -0.174  0.349  0.000  0.100  0.473  0.000  0.548  0.000  0.473  0.473  0.249  0.125  0.299  0.648 -0.075  0.573  0.324  0.623  0.399  0.424  0.100  0.000 -0.174  0.100  0.249  0.623 
 0.152  0.551  0.152  0.152  0.053  0.302  0.476  0.202  0.601  0.626  0.152  0.252  0.103  0.128  0.402  0.451  0.651  0.177  0.426 -0.146  0.626  0.103  0.252  0.252 -0.171  0.352  0.003  0.103  0.501  0.003  0.551  0.003  0.476  0.451  0.252  0.128  0.302  0.601 -0.072  0.601  0.327  0.626  0.377  0.426  0.103  0.003 -0.171  0.103  0.252  0.626 
 0.199  0.597  0.199  0.224  0.074  0.224  0.473  0.224  0.572  0.647  0.149  0.274  0.099  0.174  0.398  0.448  0.672  0.199  0.448 -0.125  0.597  0.124  0.199  0.199 -0.175  0.224 -0.000  0.049  0.398  0.024  0.523  0.024  0.423  0.498  0.224  0.124  0.274  0.548 -0.075  0.498  0.323  0.647  0.323  0.373  0.049 -0.000 -0.100  0.124  0.149  0.498 
 0.164  0.488  0.214  0.164  0.089  0.214  0.363  0.164  0.587  0.662  0.114  0.089  0.039  0.114  0.413  0.463  0.538  0.164  0.438 -0.060  0.587  0.039  0.114  0.114 -0.110  0.064  0.039 -0.035  0.288  0.039  0.563 -0.010  0.313  0.438  0.114  0.039  0.214  0.413 -0.035  0.338  0.313  0.662  0.214  0.239  0.014 -0.035 -0.085  0.064  0.164  0.488 
 0.136  0.484  0.235  0.160  0.061  0.136  0.360  0.185  0.584  0.684  0.086  0.036  0.011  0.136  0.410  0.459  0.459  0.111  0.410 -0.039  0.509 -0.064  0.086  0.086 -0.114  0.011  0.036 -0.114  0.260  0.061  0.584 -0.014  0.136  0.459  0.061  0.061  0.210  0.360 -0.039  0.285  0.335  0.659  0.185  0.185  0.011 -0.039 -0.064  0.061  0.160  0.459 
 0.160  0.459  0.235  0.160  0.010  0.110  0.309  0.160  0.583  0.708  0.085  0.010  0.010  0.110  0.409  0.409  0.459  0.085  0.384 -0.039  0.459 -0.064 -0.039  0.010 -0.089 -0.039  0.035 -0.089  0.060  0.085  0.633  0.010  0.035  0.434  0.085  0.010  0.185  0.359 -0.039  0.160  0.309  0.683  0.135  0.110 -0.014 -0.014 -0.039  0.035  0.135  0.384 
 0.168  0.442  0.268  0.168  0.019  0.119  0.318  0.168  0.542  0.716  0.044  0.019  0.019  0.069  0.418  0.318  0.467  0.019  0.418 -0.031  0.393 -0.056 -0.081  0.044 -0.081 -0.056  0.044 -0.106  0.044 -0.031  0.642 -0.006  0.019  0.343  0.069 -0.031  0.143  0.393 -0.056  0.094  0.268  0.716  0.168  0.044 -0.006 -0.006 -0.031  0.044  0.119  0.368 
 0.106  0.330  0.280  0.180  0.031  0.106  0.230  0.155  0.554  0.778  0.006  0.006  0.006  0.056  0.380  0.305  0.479  0.006  0.429 -0.019  0.180 -0.044 -0.069  0.031 -0.069 -0.044  0.056 -0.094  0.031 -0.019  0.654  0.006 -0.044  0.230  0.081 -0.044  0.131  0.380 -0.044  0.031  0.230  0.778  0.155  0.031 -0.019 -0.019 -0.044  0.031  0.131  0.380 
 0.109  0.259  0.284  0.134  0.034  0.109  0.234  0.084  0.558  0.807  0.009  0.009  0.009  0.059  0.333  0.284  0.483  0.009  0.433 -0.015  0.134 -0.040 -0.065  0.034 -0.065 -0.040  0.059 -0.090  0.009 -0.015  0.657  0.009 -0.040  0.209  0.084 -0.065  0.134  0.358 -0.040  0.009  0.234  0.782  0.159  0.034 -0.015 -0.015 -0.040  0.009  0.109  0.358 
 0.091  0.241  0.266  0.141  0.041  0.091  0.216  0.041  0.540  0.814 -0.008  0.016 -0.008  0.066  0.266  0.166  0.490 -0.008  0.390 -0.033  0.091 -0.033 -0.058  0.041 -0.058 -0.033  0.066 -0.083  0.016 -0.008  0.664  0.016 -0.033  0.166  0.066 -0.058  0.116  0.340 -0.033 -0.008  0.216  0.814  0.141  0.066 -0.033 -0.008 -0.033  0.016  0.091  0.365 
 0.073  0.198  0.223  0.148  0.048  0.098  0.173  0.048  0.547  0.821 -0.001 -0.001 -0.001 -0.001  0.198  0.073  0.472 -0.001  0.372 -0.026  0.023 -0.026 -0.051  0.048 -0.051 -0.026  0.073 -0.076  0.023 -0.001  0.721  0.023 -0.026  0.148  0.073 -0.051  0.098  0.322 -0.026 -0.026  0.198  0.796  0.098  0.048 -0.026 -0.001 -0.051 -0.001  0.073  0.223 
 0.058  0.133  0.182  0.133 -0.017  0.008  0.157  0.033  0.357  0.855 -0.017 -0.042  0.008 -0.017  0.182  0.058  0.407 -0.042  0.332  0.008  0.033 -0.017 -0.042  0.033 -0.042 -0.017  0.058 -0.067  0.008  0.033  0.730  0.033 -0.042  0.058  0.058 -0.067  0.108  0.307 -0.017 -0.042  0.133  0.880  0.108  0.058 -0.017  0.008 -0.017  0.008  0.058  0.182 
 0.061  0.086  0.161  0.136  0.011 -0.013  0.136  0.036  0.310  0.933 -0.038 -0.038 -0.013 -0.038  0.111  0.061  0.285 -0.038  0.285  0.011  0.036 -0.013 -0.038  0.061 -0.063  0.011  0.061 -0.038  0.011  0.011  0.759  0.036 -0.038  0.061  0.061 -0.063  0.086  0.261 -0.013 -0.038  0.086  0.908  0.111  0.061 -0.013 -0.013 -0.013  0.011  0.061  0.086 
 0.020 -0.004  0.070  0.095  0.020 -0.004  0.095  0.020  0.170  0.967 -0.029 -0.054 -0.004 -0.029  0.020  0.020  0.120 -0.029  0.145 -0.004  0.020 -0.004 -0.029  0.070 -0.054  0.020  0.045 -0.029  0.045  0.020  0.793  0.045 -0.029  0.045  0.070 -0.054  0.095  0.095 -0.054 -0.029  0.095  0.942  0.120  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.022 -0.028  0.047  0.097  0.022 -0.028  0.072  0.022  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022  0.022 -0.028  0.097 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.819  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.028  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.029  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054  0.020  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005 -0.005  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.014 -0.014  0.086  0.185  0.011 -0.064  0.111  0.036  0.360  0.933 -0.014 -0.014  0.036 -0.039  0.036  0.011 -0.039 -0.039  0.136 -0.014 -0.014 -0.039 -0.014  0.210 -0.064 -0.014  0.086  0.011  0.086  0.011  0.933  0.011 -0.014  0.061  0.011 -0.064  0.185  0.111 -0.089  0.036  0.210  0.933  0.111  0.036 -0.039 -0.014 -0.039  0.036 -0.014  0.136 
 0.049  0.024  0.149  0.373  0.024 -0.000  0.249  0.074  0.722  0.871  0.024 -0.000  0.024 -0.050  0.099  0.099  0.074 -0.050  0.323 -0.025  0.149 -0.050 -0.050  0.298 -0.100 -0.025  0.074 -0.000  0.099  0.024  0.871 -0.000 -0.000  0.174 -0.000 -0.125  0.298  0.274 -0.125  0.024  0.298  0.871  0.224  0.074 -0.025  0.024 -0.075 -0.000  0.024  0.498 
 0.170  0.021  0.195  0.395 -0.004  0.021  0.370  0.096  0.793  0.818  0.021 -0.029  0.096 -0.004  0.245  0.220  0.220 -0.029  0.444 -0.054  0.469 -0.029 -0.054  0.420 -0.129  0.021  0.046 -0.004  0.121  0.096  0.818 -0.029  0.121  0.170 -0.004 -0.104  0.395  0.370 -0.178  0.071  0.295  0.818  0.295  0.071  0.121 -0.029 -0.054  0.021  0.071  0.569 
 0.137  0.311  0.286  0.411 -0.038  0.137  0.460  0.087  0.759  0.759  0.037 -0.013  0.137  0.062  0.361  0.336  0.386 -0.038  0.535 -0.063  0.685 -0.063 -0.013  0.510 -0.162 -0.013  0.087  0.037  0.161  0.112  0.759  0.087  0.137  0.236  0.037 -0.063  0.411  0.610 -0.212  0.062  0.311  0.759  0.361  0.186  0.137  0.037 -0.088  0.062  0.236  0.660 
 0.146  0.296  0.296  0.371 -0.053  0.122  0.520  0.097  0.719  0.744  0.022 -0.003  0.146  0.072  0.396  0.396  0.445 -0.028  0.495 -0.078  0.695 -0.078  0.047  0.520 -0.177  0.022  0.072  0.047  0.171  0.072  0.695  0.072  0.221  0.271  0.022 -0.078  0.396  0.645 -0.227  0.047  0.296  0.744  0.346  0.196  0.171  0.047 -0.103  0.097  0.271  0.670 
 0.155  0.454  0.280  0.304 -0.069  0.205  0.529  0.180  0.703  0.703  0.030  0.030  0.155  0.105  0.404  0.454  0.554  0.005  0.529 -0.094  0.703 -0.069  0.055  0.504 -0.219  0.105  0.080  0.080  0.205  0.030  0.678  0.080  0.230  0.379  0.030 -0.019  0.404  0.678 -0.194  0.130  0.354  0.703  0.354  0.255  0.180  0.030 -0.119  0.130  0.280  0.678 
 0.150  0.474  0.275  0.300 -0.074  0.250  0.574  0.175  0.699  0.699  0.051  0.026  0.175  0.101  0.425  0.449  0.574  0.001  0.524 -0.099  0.674 -0.074  0.076  0.499 -0.223  0.101  0.076  0.076  0.250  0.026  0.674  0.076  0.250  0.400  0.076  0.026  0.350  0.674 -0.198  0.126  0.350  0.699  0.350  0.225  0.225  0.051 -0.124  0.150  0.275  0.674 
 0.118  0.517  0.268  0.292 -0.056  0.268  0.591  0.168  0.691  0.691  0.043  0.018  0.193  0.118  0.392  0.442  0.641  0.018  0.542 -0.106  0.666 -0.056  0.118  0.467 -0.231  0.093  0.068  0.068  0.292  0.018  0.666  0.093  0.268  0.417  0.143  0.043  0.317  0.666 -0.156  0.243  0.342  0.691  0.317  0.268  0.218  0.068 -0.131  0.118  0.268  0.641 
 0.163  0.512  0.213  0.287 -0.061  0.263  0.611  0.213  0.686  0.686  0.038  0.063  0.188  0.113  0.412  0.437  0.636  0.038  0.537 -0.111  0.661 -0.036  0.113  0.462 -0.211  0.113  0.063  0.063  0.362  0.013  0.661  0.088  0.287  0.412  0.188  0.088  0.312  0.661 -0.136  0.312  0.337  0.686  0.337  0.238  0.213  0.063 -0.136  0.138  0.263  0.636 
 0.182  0.506  0.182  0.282 -0.017  0.282  0.606  0.257  0.681  0.681  0.083  0.133  0.083  0.108  0.407  0.481  0.606  0.083  0.506 -0.117  0.656  0.008  0.157  0.481 -0.216  0.108  0.058  0.083  0.357  0.033  0.606  0.083  0.357  0.456  0.232  0.108  0.307  0.656 -0.117  0.431  0.307  0.681  0.307  0.282  0.182  0.033 -0.142  0.108  0.257  0.631 
 0.207  0.506  0.182  0.257  0.033  0.282  0.581  0.232  0.656  0.681  0.083  0.133  0.083  0.108  0.407  0.481  0.606  0.083  0.506 -0.117  0.631  0.008  0.157  0.481 -0.216  0.133  0.058  0.083  0.357  0.033  0.581  0.083  0.382  0.481  0.232  0.133  0.307  0.656 -0.092  0.481  0.307  0.681  0.307  0.307  0.182  0.033 -0.142  0.108  0.232  0.631 
 0.229  0.528  0.179  0.229  0.029  0.303  0.577  0.229  0.652  0.677  0.079  0.154  0.079  0.104  0.403  0.503  0.602  0.079  0.478 -0.095  0.627  0.054  0.154  0.428 -0.220  0.154  0.054  0.054  0.353  0.029  0.577  0.104  0.378  0.478  0.254  0.154  0.303  0.652 -0.095  0.503  0.279  0.677  0.303  0.328  0.179  0.029 -0.120  0.104  0.204  0.627 
 0.201  0.550  0.201  0.176  0.027  0.301  0.575  0.226  0.650  0.675  0.077  0.176  0.077  0.102  0.401  0.500  0.600  0.102  0.475 -0.098  0.625  0.052  0.176  0.401 -0.222  0.226  0.052  0.077  0.351  0.027  0.575  0.102  0.351  0.475  0.251  0.151  0.276  0.650 -0.123  0.525  0.301  0.675  0.301  0.351  0.201 -0.023 -0.123  0.102  0.201  0.625 
 0.200  0.549  0.200  0.150  0.025  0.324  0.573  0.225  0.648  0.673  0.075  0.200  0.075  0.125  0.399  0.499  0.598  0.125  0.474 -0.099  0.623  0.075  0.200  0.324 -0.199  0.275  0.025  0.075  0.349  0.000  0.573  0.075  0.349  0.474  0.250  0.175  0.299  0.648 -0.074  0.524  0.324  0.673  0.324  0.399  0.175 -0.024 -0.124  0.100  0.225  0.623 
 0.248  0.547  0.198  0.123  0.023  0.322  0.571  0.223  0.646  0.671  0.073  0.223  0.073  0.098  0.397  0.497  0.596  0.148  0.472 -0.101  0.596  0.098  0.198  0.322 -0.176  0.273  0.023  0.073  0.347 -0.001  0.571  0.073  0.372  0.472  0.248  0.173  0.322  0.646 -0.076  0.497  0.322  0.671  0.322  0.422  0.173 -0.001 -0.151  0.098  0.223  0.621 
 0.248  0.547  0.198  0.123  0.023  0.322  0.571  0.223  0.646  0.671  0.098  0.248  0.073  0.098  0.397  0.497  0.596  0.173  0.472 -0.101  0.596  0.123  0.198  0.297 -0.151  0.297  0.023  0.073  0.347 -0.001  0.547  0.073  0.372  0.472  0.248  0.198  0.322  0.646 -0.076  0.472  0.322  0.671  0.347  0.397  0.173  0.048 -0.151  0.098  0.198  0.621 
 0.247  0.521  0.197  0.147  0.022  0.321  0.570  0.222  0.645  0.670  0.097  0.272  0.047  0.097  0.421  0.496  0.595  0.172  0.471 -0.102  0.570  0.122  0.197  0.296 -0.152  0.321  0.022  0.072  0.346  0.022  0.521  0.072  0.396  0.471  0.247  0.222  0.321  0.645 -0.077  0.446  0.321  0.670  0.346  0.421  0.172  0.047 -0.127  0.097  0.222  0.595 
 0.247  0.521  0.197  0.147 -0.002  0.321  0.570  0.222  0.645  0.670  0.097  0.272  0.047  0.122  0.421  0.496  0.595  0.172  0.471 -0.102  0.570  0.122  0.197  0.296 -0.152  0.321  0.047  0.097  0.346  0.022  0.521  0.047  0.421  0.471  0.247  0.296  0.321  0.645 -0.077  0.496  0.321  0.645  0.346  0.421  0.147  0.022 -0.127  0.122  0.222  0.595 
 0.221  0.520  0.196  0.146 -0.003  0.320  0.569  0.246  0.644  0.669  0.096  0.246  0.071  0.121  0.420  0.495  0.594  0.196  0.470 -0.103  0.569  0.121  0.221  0.295 -0.153  0.345  0.046  0.096  0.395  0.021  0.520  0.071  0.420  0.470  0.246  0.295  0.295  0.644 -0.078  0.470  0.320  0.644  0.345  0.420  0.171  0.021 -0.128  0.121  0.221  0.594 
 0.220  0.519  0.195  0.145  0.021  0.320  0.569  0.245  0.644  0.669  0.096  0.245  0.071  0.121  0.420  0.494  0.594  0.195  0.469 -0.104  0.569  0.121  0.220  0.320 -0.153  0.345  0.046  0.096  0.395  0.021  0.519  0.071  0.420  0.469  0.245  0.295  0.295  0.644 -0.079  0.469  0.320  0.669  0.345  0.420  0.170  0.021 -0.129  0.121  0.220  0.594 

 0.967  0.045 -0.004  0.020 -0.004  0.045  0.020 -0.029  0.070 -0.029  0.120 -0.029 -0.029 -0.004 -0.029 -0.029 -0.004 -0.004 -0.029 -0.029  0.020 -0.029 -0.004 -0.004 -0.029 -0.029  0.045 -0.029  0.020  0.045  0.045 -0.004 -0.004 -0.029  0.020 -0.004 -0.004 -0.029  0.045 -0.004 -0.004 -0.029  0.045 -0.029 -0.004 -0.029 -0.004 -0.029 -0.004 -0.029 
 0.998  0.002 -0.023  0.027  0.002  0.027  0.027 -0.023  0.077  0.002  0.127 -0.023 -0.023  0.002 -0.023 -0.023  0.002  0.002 -0.023 -0.023  0.027 -0.023  0.002  0.002 -0.023  0.002  0.052  0.002  0.002  0.052  0.027 -0.023  0.002 -0.023  0.002  0.002  0.002 -0.023  0.027  0.002  0.002 -0.023  0.052 -0.023  0.002 -0.023  0.002 -0.023  0.002 -0.023 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.001  0.004 -0.020  0.029  0.004  0.029  0.029 -0.020  0.079  0.004  0.104 -0.020 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.054  0.004  0.004  0.054  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.029  0.004 -0.020 -0.020  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 
 1.000  0.003 -0.021  0.053  0.003  0.028  0.028 -0.021  0.103  0.003  0.128 -0.021 -0.021  0.003 -0.021 -0.021  0.003  0.028 -0.021 -0.021  0.003 -0.021  0.003  0.003 -0.021  0.003  0.053  0.003  0.003  0.053  0.028 -0.021  0.003  0.003  0.003  0.003  0.003 -0.021  0.053  0.003 -0.021 -0.021  0.053 -0.021  0.003 -0.021  0.003 -0.021  0.003 -0.021 
 0.998  0.002 -0.023  0.052  0.002  0.027  0.027 -0.023  0.151  0.027  0.127 -0.023 -0.023  0.002 -0.023 -0.023  0.002  0.027 -0.023 -0.023  0.002 -0.023  0.002  0.002 -0.023  0.027  0.052  0.002  0.002  0.102  0.027 -0.023  0.002  0.002  0.002  0.002  0.002 -0.023  0.052  0.002  0.002 -0.023  0.052 -0.023  0.002 -0.023  0.002 -0.023  0.002 -0.023 
 0.995 -0.001 -0.026  0.048 -0.001  0.023  0.048 -0.026  0.273  0.048  0.123 -0.026 -0.026 -0.001 -0.026 -0.026 -0.001  0.023 -0.026 -0.026 -0.001 -0.026 -0.001 -0.001 -0.026  0.023  0.048 -0.001 -0.001  0.148  0.023 -0.026 -0.001  0.023 -0.001 -0.001 -0.001 -0.026  0.048 -0.001 -0.001 -0.026  0.073 -0.026 -0.001 -0.026 -0.001 -0.001 -0.001 -0.026 
 0.977  0.030  0.005  0.080  0.030  0.005  0.155 -0.044  0.653  0.155  0.155 -0.019 -0.019  0.005 -0.044 -0.044  0.005  0.030 -0.019 -0.019 -0.019  0.030 -0.019  0.080 -0.019  0.055  0.055  0.080 -0.019  0.255  0.005 -0.044 -0.019  0.055 -0.019 -0.019 -0.019 -0.019  0.080 -0.019  0.030  0.005  0.230 -0.044  0.030 -0.044  0.005  0.030  0.080  0.030 
 0.950  0.152  0.028  0.152  0.003  0.028  0.377 -0.047  0.825  0.177  0.227 -0.022 -0.022  0.028 -0.022 -0.047  0.078  0.003  0.028  0.003  0.003  0.028 -0.022  0.128 -0.047  0.078  0.078  0.053 -0.022  0.476 -0.022  0.003 -0.047  0.202 -0.022  0.003 -0.022 -0.022  0.078  0.053  0.078 -0.022  0.377 -0.047  0.078 -0.047  0.003  0.028  0.128  0.028 
 0.898  0.300  0.051  0.350  0.001  0.126  0.774 -0.023  0.898  0.276  0.176  0.001 -0.023  0.101  0.001  0.001  0.126  0.101  0.051 -0.023  0.051 -0.023 -0.023  0.101 -0.073  0.076  0.076  0.026 -0.048  0.724  0.026  0.001 -0.073  0.201 -0.048  0.026  0.001 -0.023  0.051  0.101  0.126  0.026  0.749 -0.098  0.151 -0.048 -0.023  0.026  0.151  0.026 
 0.863  0.365  0.116  0.489  0.066  0.190  0.813 -0.034  0.863  0.340  0.165  0.091 -0.009  0.091 -0.009  0.041  0.240  0.116  0.091 -0.009  0.116  0.016  0.016  0.066 -0.059  0.116  0.141  0.041 -0.059  0.738  0.116 -0.034 -0.059  0.415 -0.034  0.041  0.091 -0.034  0.041  0.116  0.141  0.066  0.788 -0.109  0.265 -0.034  0.041 -0.009  0.240  0.116 
 0.800  0.501  0.227  0.626  0.028  0.202  0.775 -0.047  0.800  0.526  0.152  0.128 -0.047  0.128  0.277  0.302  0.377  0.103  0.202 -0.047  0.327  0.028  0.103  0.177 -0.072  0.128  0.128  0.053 -0.097  0.775  0.327 -0.047  0.003  0.526 -0.097  0.053  0.277  0.103  0.078  0.202  0.177  0.177  0.800 -0.097  0.402 -0.022  0.053 -0.047  0.252  0.302 
 0.757  0.508  0.209  0.633  0.085  0.159  0.757 -0.040  0.782  0.558  0.135  0.184 -0.040  0.135  0.309  0.334  0.384  0.085  0.309 -0.090  0.433  0.060  0.110  0.259  0.010  0.110  0.259  0.035 -0.065  0.757  0.359 -0.040  0.035  0.508 -0.065  0.035  0.334  0.085  0.060  0.234  0.234  0.234  0.782 -0.115  0.433 -0.040  0.035 -0.040  0.309  0.334 
 0.653  0.578  0.204  0.653  0.130  0.154  0.727 -0.045  0.752  0.678  0.130  0.204 -0.020  0.130  0.379  0.578  0.478  0.055  0.379 -0.120  0.478  0.130  0.080  0.379 -0.020  0.130  0.254  0.080  0.005  0.603  0.453 -0.020  0.080  0.553 -0.070  0.005  0.354  0.179  0.005  0.329  0.254  0.428  0.752 -0.120  0.428  0.005  0.005  0.005  0.379  0.453 
 0.619  0.569  0.221  0.619  0.121  0.146  0.719 -0.053  0.744  0.669  0.146  0.171 -0.028  0.146  0.370  0.619  0.470  0.046  0.445 -0.128  0.470  0.121  0.121  0.420 -0.028  0.196  0.271  0.121  0.071  0.594  0.470 -0.003  0.121  0.569 -0.103 -0.003  0.370  0.171 -0.003  0.345  0.295  0.445  0.744 -0.128  0.420 -0.003 -0.003 -0.003  0.370  0.495 
 0.584  0.560  0.211  0.584  0.161  0.111  0.709 -0.013  0.734  0.709  0.136  0.161  0.011  0.161  0.360  0.659  0.510  0.061  0.535 -0.113  0.535  0.111  0.111  0.460 -0.113  0.211  0.186  0.111  0.061  0.510  0.485 -0.013  0.161  0.584 -0.088 -0.013  0.385  0.211 -0.063  0.335  0.261  0.609  0.734 -0.063  0.410 -0.038 -0.013 -0.013  0.385  0.584 
 0.549  0.574  0.250  0.574  0.150  0.126  0.699 -0.024  0.723  0.699  0.126  0.150  0.001  0.150  0.375  0.649  0.574  0.126  0.524 -0.074  0.549  0.101  0.101  0.449 -0.074  0.275  0.126  0.126  0.051  0.425  0.474  0.001  0.150  0.574 -0.099  0.001  0.375  0.375 -0.074  0.325  0.275  0.649  0.723  0.001  0.400  0.001 -0.024 -0.024  0.400  0.624 
 0.523  0.548  0.298  0.548  0.149  0.124  0.672 -0.000  0.722  0.697  0.099  0.049 -0.000  0.149  0.373  0.672  0.572  0.124  0.523 -0.050  0.548  0.024  0.099  0.473 -0.125  0.323  0.124  0.099  0.024  0.348  0.473 -0.000  0.149  0.572 -0.100 -0.000  0.373  0.498 -0.100  0.323  0.298  0.647  0.697  0.024  0.423 -0.000 -0.050 -0.075  0.398  0.622 
 0.523  0.548  0.299  0.523  0.149  0.149  0.673  0.000  0.722  0.698  0.100  0.050  0.000  0.149  0.374  0.648  0.573  0.149  0.523 -0.025  0.548  0.000  0.100  0.473 -0.125  0.374  0.125  0.100  0.050  0.299  0.473  0.000  0.149  0.573 -0.100  0.000  0.374  0.473 -0.100  0.349  0.299  0.648  0.698  0.025  0.424  0.000 -0.050 -0.075  0.399  0.623 
 0.495  0.520  0.296  0.520  0.171  0.146  0.670 -0.003  0.670  0.695  0.146  0.047 -0.003  0.146  0.396  0.645  0.595  0.171  0.520 -0.028  0.545 -0.028  0.097  0.520 -0.152  0.371  0.097  0.097  0.047  0.271  0.470  0.022  0.171  0.570 -0.078  0.022  0.371  0.495 -0.103  0.346  0.296  0.645  0.695  0.022  0.421  0.047 -0.053 -0.078  0.396  0.620 
 0.516  0.516  0.292  0.516  0.167  0.142  0.666 -0.007  0.641  0.691  0.167  0.043 -0.007  0.167  0.417  0.641  0.591  0.167  0.516 -0.032  0.541 -0.032  0.118  0.566 -0.156  0.367  0.093  0.093  0.068  0.242  0.466  0.043  0.167  0.566 -0.057  0.043  0.367  0.516 -0.107  0.342  0.292  0.641  0.691  0.043  0.417  0.043 -0.057 -0.082  0.392  0.616 
 0.511  0.461  0.337  0.511  0.162  0.162  0.661  0.088  0.636  0.710  0.187  0.013 -0.012  0.162  0.412  0.636  0.611  0.162  0.511 -0.012  0.536 -0.037  0.138  0.561 -0.161  0.362  0.088  0.088  0.088  0.237  0.461  0.038  0.138  0.561 -0.037  0.088  0.337  0.511 -0.112  0.362  0.287  0.661  0.686  0.038  0.436  0.113 -0.062 -0.062  0.387  0.611 
 0.512  0.462  0.337  0.512  0.163  0.188  0.661  0.088  0.636  0.711  0.188  0.013 -0.011  0.163  0.387  0.636  0.611  0.163  0.512 -0.011  0.537 -0.036  0.138  0.562 -0.161  0.362  0.088  0.088  0.088  0.238  0.462  0.038  0.138  0.537 -0.036  0.088  0.337  0.512 -0.111  0.362  0.287  0.661  0.661  0.038  0.412  0.113 -0.061 -0.061  0.437  0.611 
 0.461  0.461  0.336  0.461  0.162  0.187  0.610  0.087  0.635  0.710  0.237 -0.012 -0.012  0.162  0.386  0.635  0.585  0.162  0.511 -0.037  0.536 -0.062  0.212  0.536 -0.162  0.361  0.087  0.087  0.162  0.237  0.461  0.037  0.137  0.536 -0.037  0.112  0.336  0.536 -0.112  0.411  0.286  0.660  0.660  0.012  0.411  0.162 -0.062 -0.037  0.436  0.610 
 0.278  0.427  0.353  0.502  0.178  0.129  0.652  0.104  0.577  0.677  0.278 -0.021 -0.021  0.203  0.353  0.652  0.627  0.104  0.502 -0.071  0.477 -0.071  0.153  0.452 -0.145  0.278  0.004  0.104  0.129  0.153  0.477  0.029  0.129  0.527  0.004  0.079  0.353  0.378 -0.096  0.278  0.303  0.677  0.552 -0.021  0.303  0.178 -0.071  0.004  0.452  0.552 
 0.222  0.322  0.322  0.372  0.123  0.048  0.671 -0.002  0.571  0.696  0.222 -0.027  0.048  0.123  0.347  0.571  0.521  0.073  0.422 -0.052  0.446 -0.052  0.073  0.272 -0.127  0.197  0.023  0.073  0.147  0.098  0.496  0.023  0.048  0.446  0.023  0.123  0.272  0.322 -0.077  0.098  0.372  0.571  0.546 -0.027  0.197  0.048 -0.052  0.023  0.322  0.546 
 0.214  0.288  0.313  0.288  0.139  0.089  0.662  0.014  0.513  0.712  0.214 -0.010  0.039  0.114  0.363  0.538  0.538  0.089  0.413 -0.035  0.388 -0.035  0.064  0.139 -0.110  0.164  0.014  0.064  0.114  0.064  0.513  0.014  0.064  0.363  0.039  0.114  0.288  0.338 -0.060  0.089  0.388  0.513  0.563 -0.035  0.139  0.014 -0.035  0.014  0.313  0.513 
 0.095  0.245  0.270  0.245  0.120  0.070  0.618  0.020  0.469  0.718  0.170 -0.004  0.045  0.120  0.294  0.544  0.469  0.020  0.394 -0.029  0.245 -0.054 -0.004  0.120 -0.079  0.095  0.045 -0.004  0.120 -0.004  0.519  0.020  0.020  0.270  0.070  0.095  0.245  0.270 -0.054  0.020  0.344  0.519  0.419 -0.004  0.045  0.020 -0.029  0.020  0.220  0.544 
 0.079  0.229  0.204  0.254  0.129  0.029  0.528  0.029  0.503  0.752  0.129  0.004  0.054  0.129  0.303  0.528  0.453 -0.045  0.353 -0.020  0.179 -0.045 -0.020  0.079 -0.070  0.079  0.029 -0.045  0.104  0.004  0.553  0.004 -0.020  0.229  0.029  0.079  0.179  0.279 -0.045 -0.020  0.303  0.528  0.353  0.004  0.004  0.029 -0.020  0.029  0.229  0.478 
 0.040  0.215  0.140  0.240  0.090 -0.009  0.489  0.015  0.539  0.788  0.065  0.015  0.065  0.065  0.289  0.489  0.439 -0.034  0.289 -0.034  0.115 -0.034 -0.059 -0.009 -0.059  0.015  0.040 -0.084  0.090 -0.009  0.613  0.015 -0.009  0.215  0.015 -0.009  0.190  0.289 -0.034 -0.009  0.240  0.514  0.215  0.015 -0.009  0.015 -0.034 -0.009  0.190  0.389 
 0.045  0.194  0.144  0.194  0.120 -0.030  0.468  0.020  0.593  0.817  0.045  0.020  0.070  0.045  0.244  0.468  0.419 -0.055  0.294 -0.030  0.095 -0.030 -0.055 -0.005 -0.055  0.020  0.045 -0.080  0.095  0.020  0.593  0.020 -0.055  0.194  0.020 -0.005  0.144  0.294 -0.030 -0.030  0.194  0.493  0.194  0.020 -0.005  0.020 -0.030 -0.005  0.194  0.369 
 0.075  0.150  0.125  0.175  0.125 -0.024  0.374  0.025  0.623  0.897 -0.024  0.025  0.050  0.025  0.200  0.349  0.374 -0.074  0.275 -0.024  0.100 -0.049 -0.049  0.000 -0.049  0.025  0.025 -0.049  0.075  0.025  0.598  0.025 -0.049  0.125  0.025 -0.024  0.125  0.299 -0.024 -0.024  0.150  0.499  0.175  0.025 -0.024  0.000  0.000  0.000  0.175  0.324 
 0.081  0.106  0.106  0.106  0.155 -0.019  0.305  0.031  0.629  0.953 -0.019  0.006  0.056  0.006  0.180  0.230  0.280 -0.069  0.255 -0.019  0.106 -0.044 -0.044  0.006 -0.044 -0.019  0.031 -0.044  0.056  0.031  0.629  0.031 -0.044  0.106  0.031 -0.044  0.155  0.205 -0.019 -0.019  0.131  0.554  0.131  0.031 -0.019  0.006  0.006  0.006  0.180  0.255 
 0.066  0.066  0.066  0.091  0.166 -0.008  0.191  0.041  0.639  0.963 -0.033 -0.008  0.016 -0.008  0.066  0.041  0.216 -0.058  0.191 -0.008  0.041 -0.033 -0.033  0.016 -0.058 -0.008  0.016 -0.033  0.016  0.041  0.664  0.041 -0.033  0.066  0.041 -0.058  0.091  0.166 -0.008 -0.008  0.116  0.565  0.116  0.016  0.016 -0.008  0.016 -0.008  0.091  0.191 
 0.070  0.070  0.020  0.070  0.170 -0.029  0.170  0.045  0.643  0.967 -0.029 -0.004  0.020 -0.004  0.070 -0.004  0.145 -0.054  0.095 -0.029  0.020 -0.029 -0.029  0.020 -0.054 -0.004 -0.029 -0.029  0.020  0.045  0.693  0.045 -0.029  0.070 -0.004 -0.054  0.070  0.070 -0.029 -0.004  0.120  0.519  0.095  0.020 -0.004 -0.004 -0.004 -0.004  0.095  0.170 
 0.072  0.072 -0.002  0.047  0.172 -0.027  0.122  0.047  0.695  0.969 -0.027 -0.002  0.022 -0.002  0.022 -0.002  0.047 -0.052  0.047 -0.052 -0.002 -0.027 -0.002  0.022 -0.052 -0.002 -0.027 -0.027  0.022  0.022  0.720  0.022 -0.027  0.072 -0.002 -0.052  0.047  0.047 -0.052 -0.002  0.122  0.521  0.072 -0.002 -0.002 -0.002 -0.002 -0.002  0.047  0.122 
 0.073  0.073 -0.027  0.048  0.172 -0.027  0.123  0.048  0.646  0.970 -0.027 -0.002  0.023 -0.002  0.023 -0.002 -0.002 -0.052  0.048 -0.052 -0.002 -0.027 -0.002  0.023 -0.052 -0.002 -0.027 -0.027  0.023  0.023  0.770  0.023 -0.027  0.073 -0.002 -0.052  0.048  0.048 -0.052 -0.002  0.123  0.496  0.073 -0.002 -0.002 -0.002 -0.002 -0.002  0.048  0.123 
 0.073  0.073 -0.026  0.048  0.173 -0.026  0.123  0.048  0.646  0.970 -0.026 -0.001  0.023 -0.001  0.023 -0.001 -0.001 -0.051  0.048 -0.051 -0.001 -0.026 -0.026  0.023 -0.051 -0.001 -0.026 -0.026  0.023  0.023  0.821  0.023 -0.026  0.073 -0.001 -0.051  0.048  0.048 -0.051 -0.001  0.123  0.422  0.073 -0.001 -0.001 -0.001 -0.001 -0.001  0.048  0.123 
 0.049  0.074 -0.026  0.049  0.173 -0.026  0.099  0.049  0.622  0.971 -0.051 -0.001 -0.001 -0.026  0.024 -0.026 -0.001 -0.051  0.049 -0.051 -0.001 -0.026 -0.026  0.024 -0.051 -0.001 -0.026 -0.026  0.024  0.024  0.871  0.024 -0.026  0.074 -0.001 -0.051  0.049  0.049 -0.051  0.024  0.124  0.373  0.074 -0.001 -0.001 -0.001 -0.001 -0.001  0.049  0.124 
 0.048  0.048 -0.026  0.048  0.173 -0.026  0.098  0.048  0.596  0.970 -0.051 -0.001 -0.001 -0.026  0.023 -0.026 -0.026 -0.051  0.048 -0.051 -0.001 -0.026 -0.001  0.023 -0.051 -0.001 -0.026 -0.026  0.023  0.023  0.970  0.023 -0.051  0.073 -0.001 -0.051  0.048  0.048 -0.051  0.048  0.123  0.322  0.073 -0.001 -0.001 -0.001 -0.001 -0.001  0.048  0.123 
 0.051  0.051 -0.024  0.051  0.126 -0.024  0.101  0.051  0.524  0.973 -0.049  0.001  0.001 -0.049  0.026 -0.024 -0.024 -0.049  0.051 -0.049  0.001 -0.024  0.001  0.026 -0.049  0.001 -0.024 -0.024  0.026  0.026  0.973  0.026 -0.049  0.076  0.001 -0.049  0.051  0.051 -0.049  0.051  0.126  0.275  0.076  0.001  0.001  0.001  0.001  0.001  0.051  0.126 
 0.031  0.031 -0.019  0.031  0.106 -0.019  0.106  0.056  0.280  0.978 -0.044 -0.044  0.006 -0.044  0.031 -0.019 -0.019 -0.044  0.056 -0.044  0.006 -0.019  0.006  0.031 -0.044  0.006 -0.019 -0.019  0.031  0.031  0.978  0.006 -0.044  0.056  0.006 -0.044  0.056  0.056 -0.044  0.031  0.131  0.280  0.081  0.006  0.006  0.006  0.006  0.006  0.031  0.131 
 0.032  0.007 -0.017  0.032  0.082 -0.017  0.107  0.032  0.207  0.979 -0.042 -0.042 -0.017 -0.042  0.032 -0.017 -0.017 -0.042  0.057 -0.042  0.007 -0.017  0.007  0.032 -0.042  0.007 -0.017 -0.017  0.032  0.007  0.979  0.007 -0.042  0.057  0.007 -0.042  0.057  0.057 -0.042  0.032  0.107  0.282  0.082  0.007  0.007  0.007  0.007  0.007  0.032  0.107 
 0.034  0.009 -0.016  0.034  0.059 -0.016  0.084  0.034  0.134  0.981 -0.041 -0.041 -0.016 -0.041  0.034 -0.016 -0.016 -0.041  0.059 -0.041  0.009 -0.016  0.009  0.034 -0.041  0.009 -0.016 -0.016  0.034  0.009  0.981  0.009 -0.041  0.034  0.009 -0.041  0.059  0.059 -0.041  0.034  0.109  0.258  0.084  0.009  0.009  0.009  0.009  0.009  0.009  0.084 
 0.075  0.000  0.000  0.125  0.125  0.000  0.149  0.050  0.374  0.947  0.000 -0.050 -0.025 -0.050  0.050 -0.025  0.075 -0.050  0.149  0.075  0.000 -0.025  0.000  0.075 -0.050  0.000  0.050 -0.050  0.100  0.000  0.947  0.050 -0.050  0.050  0.025 -0.050  0.075  0.174 -0.075  0.050  0.224  0.673  0.149  0.000  0.000  0.050 -0.025 -0.025  0.000  0.199 
 0.114  0.039  0.039  0.238  0.288 -0.011  0.139  0.064  0.736  0.886  0.039 -0.036  0.014 -0.011  0.114  0.064  0.064 -0.061  0.313  0.089  0.213 -0.036 -0.036  0.039 -0.111 -0.036  0.039 -0.061  0.139  0.039  0.886  0.064 -0.086  0.163  0.064 -0.111  0.114  0.413 -0.111  0.114  0.288  0.886  0.213  0.064 -0.011  0.064 -0.061 -0.036  0.014  0.437 
 0.119  0.069  0.119  0.293  0.318  0.094  0.268  0.119  0.766  0.841  0.044 -0.056  0.069  0.069  0.218  0.143  0.268 -0.081  0.467  0.044  0.343 -0.031 -0.081  0.094 -0.131 -0.031  0.094 -0.031  0.143  0.069  0.841  0.069 -0.056  0.268  0.094 -0.131  0.094  0.617 -0.155  0.243  0.268  0.841  0.318  0.069 -0.031  0.019 -0.081  0.019  0.069  0.542 
 0.080  0.080  0.280  0.329  0.379  0.080  0.329  0.230  0.753  0.778  0.105 -0.119  0.105  0.130  0.379  0.354  0.379 -0.044  0.578  0.005  0.504 -0.019 -0.069  0.205 -0.119  0.055  0.130  0.005  0.130  0.055  0.778  0.080  0.005  0.404  0.130 -0.144  0.180  0.753 -0.194  0.304  0.304  0.778  0.379  0.080  0.030  0.055 -0.069  0.055  0.180  0.703 
 0.012  0.112  0.436  0.336  0.336  0.087  0.411  0.212  0.735  0.760  0.112 -0.087  0.162  0.162  0.361  0.386  0.386  0.012  0.610 -0.012  0.585 -0.012 -0.087  0.286 -0.137  0.087  0.112  0.037  0.162  0.037  0.735  0.087  0.062  0.386  0.087 -0.012  0.187  0.735 -0.162  0.311  0.336  0.760  0.436  0.137  0.087  0.062 -0.087  0.062  0.212  0.685 
 0.038  0.088  0.536  0.362  0.287  0.113  0.387  0.212  0.710  0.735  0.138 -0.087  0.187  0.187  0.387  0.511  0.461  0.063  0.586 -0.037  0.586 -0.037 -0.062  0.362 -0.161  0.113  0.088  0.113  0.162  0.038  0.710  0.113  0.113  0.486  0.162 -0.037  0.237  0.710 -0.161  0.387  0.337  0.735  0.412  0.162  0.162  0.088 -0.112  0.113  0.287  0.686 
 0.030  0.105  0.578  0.329  0.280  0.130  0.379  0.230  0.703  0.728  0.130 -0.069  0.130  0.155  0.379  0.504  0.504  0.055  0.578 -0.044  0.578 -0.044 -0.094  0.379 -0.169  0.155  0.080  0.105  0.180  0.030  0.678  0.080  0.230  0.504  0.180 -0.019  0.280  0.703 -0.194  0.404  0.329  0.703  0.404  0.155  0.155  0.105 -0.119  0.130  0.304  0.678 
 0.068  0.093  0.591  0.292  0.267  0.167  0.367  0.217  0.691  0.715  0.142 -0.032  0.118  0.118  0.367  0.541  0.591  0.118  0.566 -0.057  0.591 -0.057 -0.007  0.417 -0.181  0.167  0.068  0.093  0.242  0.018  0.641  0.118  0.292  0.541  0.192 -0.032  0.267  0.691 -0.156  0.516  0.317  0.691  0.417  0.217  0.142  0.093 -0.132  0.118  0.267  0.666 
 0.091  0.091  0.589  0.290  0.265  0.240  0.365  0.215  0.689  0.713  0.141  0.066  0.116  0.116  0.365  0.539  0.564  0.141  0.539 -0.059  0.564 -0.059  0.016  0.415 -0.208  0.190  0.091  0.091  0.290 -0.009  0.564  0.116  0.340  0.539  0.215 -0.009  0.315  0.689 -0.134  0.514  0.315  0.689  0.415  0.215  0.141  0.116 -0.134  0.116  0.265  0.664 
 0.088  0.088  0.586  0.262  0.237  0.237  0.362  0.212  0.686  0.710  0.138  0.088  0.113  0.113  0.362  0.536  0.561  0.138  0.511 -0.062  0.561 -0.062  0.038  0.387 -0.211  0.212  0.088  0.088  0.287  0.013  0.561  0.088  0.387  0.536  0.237 -0.012  0.312  0.661 -0.137  0.611  0.312  0.686  0.412  0.212  0.138  0.113 -0.137  0.088  0.237  0.636 
 0.083  0.083  0.606  0.232  0.232  0.257  0.357  0.207  0.681  0.706  0.157  0.083  0.108  0.108  0.357  0.531  0.556  0.133  0.506 -0.092  0.556 -0.042  0.033  0.382 -0.216  0.207  0.083  0.083  0.357  0.008  0.556  0.108  0.407  0.531  0.232  0.008  0.307  0.656 -0.117  0.606  0.332  0.681  0.407  0.232  0.133  0.182 -0.142  0.083  0.232  0.631 
 0.081  0.081  0.604  0.231  0.231  0.281  0.380  0.206  0.679  0.679  0.156  0.156  0.106  0.106  0.355  0.530  0.555  0.156  0.505 -0.068  0.555 -0.018  0.031  0.380 -0.218  0.231  0.081  0.081  0.380  0.006  0.555  0.106  0.405  0.530  0.256  0.006  0.305  0.654 -0.118  0.604  0.330  0.679  0.380  0.256  0.131  0.181 -0.143  0.081  0.231  0.629 
 0.082  0.082  0.605  0.207  0.207  0.282  0.381  0.207  0.680  0.680  0.157  0.182  0.082  0.082  0.381  0.531  0.556  0.157  0.481 -0.067  0.580 -0.017  0.032  0.331 -0.217  0.232  0.057  0.082  0.381  0.007  0.556  0.107  0.406  0.531  0.257  0.007  0.306  0.655 -0.117  0.605  0.306  0.680  0.381  0.257  0.132  0.182 -0.142  0.107  0.232  0.630 
 0.079  0.079  0.602  0.229  0.204  0.303  0.403  0.204  0.677  0.677  0.179  0.229  0.079  0.079  0.378  0.528  0.553  0.154  0.453 -0.095  0.577 -0.020  0.054  0.328 -0.195  0.254  0.029  0.079  0.403  0.004  0.553  0.129  0.403  0.528  0.254  0.054  0.303  0.652 -0.120  0.602  0.279  0.677  0.378  0.229  0.129  0.229 -0.170  0.129  0.229  0.627 
 0.080  0.105  0.603  0.229  0.204  0.279  0.453  0.204  0.678  0.678  0.179  0.229  0.055  0.080  0.379  0.528  0.553  0.154  0.453 -0.095  0.553 -0.020  0.055  0.329 -0.219  0.229  0.030  0.080  0.428  0.005  0.553  0.130  0.404  0.528  0.254  0.055  0.304  0.653 -0.120  0.603  0.279  0.678  0.354  0.229  0.130  0.254 -0.169  0.130  0.229  0.628 
 0.076  0.126  0.599  0.201  0.176  0.276  0.450  0.201  0.674  0.674  0.176  0.251  0.051  0.076  0.375  0.525  0.574  0.151  0.450 -0.098  0.550 -0.023  0.051  0.325 -0.223  0.251  0.051  0.076  0.475  0.001  0.550  0.151  0.400  0.525  0.251  0.051  0.300  0.649 -0.123  0.599  0.276  0.674  0.350  0.226  0.126  0.251 -0.148  0.151  0.226  0.624 
 0.075  0.125  0.598  0.199  0.174  0.249  0.473  0.199  0.673  0.673  0.174  0.249  0.050  0.075  0.374  0.523  0.573  0.149  0.448 -0.100  0.548 -0.025  0.050  0.324 -0.224  0.249  0.050  0.075  0.473  0.000  0.548  0.149  0.399  0.523  0.249  0.050  0.299  0.648 -0.125  0.598  0.299  0.673  0.349  0.224  0.125  0.274 -0.149  0.149  0.224  0.623 
 0.074  0.149  0.597  0.199  0.174  0.249  0.473  0.199  0.672  0.672  0.174  0.249  0.074  0.074  0.373  0.523  0.572  0.149  0.423 -0.100  0.548 -0.025  0.049  0.323 -0.225  0.249  0.024  0.074  0.498 -0.000  0.548  0.149  0.398  0.523  0.249  0.049  0.298  0.647 -0.100  0.597  0.298  0.672  0.373  0.224  0.124  0.274 -0.175  0.149  0.224  0.622 
 0.075  0.150  0.598  0.200  0.150  0.250  0.474  0.200  0.673  0.673  0.175  0.250  0.025  0.075  0.374  0.524  0.573  0.150  0.424 -0.099  0.549 -0.024  0.050  0.299 -0.224  0.275  0.025  0.075  0.499  0.000  0.549  0.150  0.399  0.524  0.250  0.050  0.299  0.623 -0.099  0.598  0.299  0.673  0.349  0.225  0.125  0.275 -0.174  0.150  0.225  0.623 
 0.074  0.149  0.622  0.199  0.124  0.274  0.473  0.199  0.672  0.672  0.174  0.249  0.024  0.074  0.373  0.523  0.572  0.149  0.423 -0.100  0.548 -0.025  0.049  0.298 -0.200  0.298  0.024  0.074  0.498 -0.000  0.548  0.149  0.398  0.523  0.249  0.049  0.298  0.622 -0.100  0.597  0.298  0.672  0.348  0.249  0.124  0.274 -0.175  0.149  0.224  0.622 
 0.094  0.119  0.567  0.243  0.143  0.193  0.368  0.193  0.667  0.617  0.168  0.119 -0.006  0.069  0.418  0.467  0.592  0.193  0.418 -0.056  0.542 -0.031 -0.081  0.243 -0.131  0.293  0.019  0.069  0.442 -0.006  0.517  0.069  0.393  0.517  0.243 -0.006  0.218  0.592 -0.081  0.542  0.318  0.667  0.268  0.193  0.094  0.193 -0.155  0.094  0.168  0.592 
 0.114  0.139  0.487  0.213  0.188  0.064  0.338  0.139  0.612  0.687  0.139  0.089  0.014  0.139  0.437  0.413  0.487  0.163  0.437 -0.011  0.512 -0.036 -0.086  0.089 -0.086  0.238  0.014  0.039  0.313  0.014  0.537  0.014  0.263  0.462  0.188 -0.011  0.163  0.413 -0.061  0.462  0.313  0.637  0.163  0.139  0.114  0.089 -0.086  0.064  0.114  0.637 
 0.108  0.133  0.456  0.207  0.182  0.083  0.257  0.133  0.556  0.706  0.133  0.033  0.033  0.133  0.456  0.382  0.481  0.108  0.456 -0.042  0.556 -0.042 -0.067  0.058 -0.067  0.182  0.033  0.008  0.282  0.058  0.556  0.008  0.182  0.382  0.157  0.008  0.157  0.382 -0.067  0.357  0.307  0.606  0.157  0.133  0.108  0.058 -0.067  0.058  0.133  0.631 
 0.057  0.082  0.406  0.256  0.206  0.107  0.256  0.132  0.555  0.705  0.107 -0.018  0.007  0.132  0.406  0.331  0.455  0.082  0.406 -0.018  0.555 -0.068 -0.093  0.032 -0.093  0.057  0.057 -0.043  0.132  0.082  0.605  0.032  0.057  0.331  0.107  0.007  0.181  0.356 -0.043  0.231  0.306  0.555  0.132  0.057  0.057 -0.018 -0.043  0.057  0.156  0.680 
 0.042  0.092  0.341  0.242  0.217  0.117  0.267  0.142  0.590  0.765  0.042 -0.007  0.017  0.092  0.416  0.291  0.466  0.042  0.391 -0.007  0.491 -0.057 -0.082  0.042 -0.082  0.017  0.042 -0.057  0.067  0.042  0.640 -0.007  0.017  0.217  0.092 -0.007  0.167  0.291 -0.057  0.142  0.242  0.516  0.142  0.017  0.042 -0.007 -0.032  0.067  0.142  0.690 
 0.026  0.101  0.300  0.225  0.175  0.101  0.275  0.150  0.624  0.798  0.001  0.001  0.026  0.101  0.425  0.225  0.425  0.001  0.400 -0.024  0.449 -0.049 -0.074  0.026 -0.074 -0.024  0.026 -0.074  0.051  0.051  0.649  0.001  0.001  0.150  0.076  0.001  0.150  0.250 -0.049  0.076  0.225  0.499  0.126  0.001  0.026  0.001 -0.024  0.076  0.126  0.674 
 0.034  0.084  0.233  0.183  0.183  0.059  0.233  0.134  0.632  0.806 -0.016 -0.016 -0.016  0.109  0.432  0.158  0.358 -0.041  0.383 -0.016  0.432 -0.066 -0.066 -0.016 -0.066 -0.016  0.034 -0.066  0.059  0.059  0.657  0.009 -0.041  0.109  0.084 -0.016  0.084  0.258 -0.041  0.059  0.208  0.482  0.084  0.009  0.034  0.009 -0.041  0.034  0.134  0.657 
 0.021  0.096  0.170  0.121  0.170  0.021  0.195  0.121  0.619  0.818 -0.004 -0.029 -0.004  0.071  0.320  0.121  0.370 -0.079  0.370 -0.079  0.245 -0.054 -0.054 -0.004 -0.054 -0.029 -0.004 -0.079  0.046  0.021  0.669  0.021 -0.029  0.071  0.071 -0.054  0.096  0.220 -0.029 -0.029  0.195  0.519  0.096  0.021 -0.029 -0.004 -0.054 -0.004  0.096  0.669 
 0.024  0.074  0.149  0.099  0.174 -0.000  0.174  0.074  0.622  0.921 -0.025 -0.025 -0.000  0.049  0.274  0.124  0.323 -0.075  0.348 -0.075  0.174 -0.050 -0.050 -0.000 -0.050 -0.025 -0.000 -0.075  0.024  0.024  0.672  0.024 -0.050  0.074  0.049 -0.050  0.099  0.224 -0.025 -0.025  0.199  0.498  0.124  0.024 -0.025 -0.000 -0.025 -0.025  0.099  0.622 
 0.033  0.083  0.083  0.033  0.133  0.008  0.157  0.058  0.631  0.930 -0.017 -0.017  0.008  0.033  0.207  0.083  0.307 -0.067  0.307 -0.067  0.083 -0.042 -0.042  0.008 -0.042 -0.017  0.008 -0.067  0.033  0.033  0.681  0.033 -0.042  0.083  0.033 -0.067  0.083  0.182 -0.017 -0.017  0.182  0.456  0.133  0.008 -0.017 -0.017 -0.017 -0.017  0.083  0.531 
 0.042  0.092  0.067  0.042  0.142  0.017  0.117  0.067  0.615  0.964 -0.057 -0.007 -0.007 -0.007  0.142 -0.007  0.167 -0.057  0.217 -0.057  0.067 -0.032 -0.032  0.017 -0.057  0.017  0.017 -0.032  0.042  0.017  0.690  0.042 -0.032  0.067  0.042 -0.057  0.067  0.142 -0.032 -0.007  0.192  0.366  0.092  0.017 -0.007 -0.007 -0.007 -0.007  0.067  0.391 
 0.049  0.049  0.024  0.049  0.149 -0.025  0.124  0.049  0.622  0.971 -0.050 -0.000 -0.000 -0.000  0.099 -0.000  0.099 -0.050  0.099 -0.050  0.024 -0.025 -0.025  0.024 -0.050 -0.000 -0.000 -0.025 -0.000  0.024  0.722  0.049 -0.050  0.074  0.024 -0.050  0.049  0.124 -0.050 -0.000  0.149  0.298  0.074 -0.000 -0.000 -0.000 -0.000 -0.000  0.049  0.249 
 0.077  0.052  0.002  0.052  0.127 -0.023  0.151  0.052  0.625  0.974 -0.023  0.002  0.002 -0.023  0.052 -0.023  0.052 -0.048  0.077 -0.048  0.027 -0.023 -0.023  0.027 -0.048  0.002 -0.023 -0.023  0.002  0.027  0.749  0.052 -0.048  0.077  0.002 -0.048  0.052  0.077 -0.048  0.002  0.151  0.276  0.077  0.002  0.002  0.002  0.002  0.002  0.052  0.151 
 0.080  0.055 -0.020  0.055  0.130 -0.020  0.130  0.055  0.503  0.977 -0.020 -0.020  0.005 -0.020  0.030 -0.020 -0.020 -0.045  0.055 -0.045  0.005 -0.020 -0.020  0.030 -0.045  0.005 -0.020 -0.020  0.030  0.030  0.802  0.030 -0.045  0.080  0.005 -0.045  0.055  0.055 -0.045  0.005  0.130  0.279  0.080  0.005  0.005  0.005  0.005  0.005  0.055  0.130 
 0.057  0.057 -0.018  0.057  0.107 -0.018  0.107  0.057  0.381  0.979 -0.043 -0.018  0.007 -0.018  0.032 -0.018 -0.018 -0.043  0.057 -0.043  0.007 -0.018 -0.018  0.032 -0.043  0.007 -0.018 -0.018  0.032  0.007  0.829  0.032 -0.043  0.082  0.007 -0.043  0.057  0.057 -0.043  0.007  0.132  0.281  0.082  0.007  0.007  0.007  0.007  0.007  0.032  0.132 
 0.058  0.033 -0.016  0.033  0.083 -0.016  0.108  0.033  0.183  0.980 -0.041 -0.041 -0.016 -0.041  0.033 -0.016 -0.016 -0.041  0.058 -0.041  0.008 -0.016 -0.016  0.033 -0.041  0.008 -0.016 -0.016  0.033  0.008  0.955  0.008 -0.041  0.058  0.008 -0.041  0.058  0.058 -0.041  0.033  0.108  0.258  0.083  0.008  0.008  0.008  0.008  0.008  0.033  0.083 
 0.034  0.009 -0.015  0.034  0.059 -0.015  0.084  0.034  0.134  0.981 -0.040 -0.040 -0.015 -0.040  0.034 -0.015 -0.015 -0.040  0.059 -0.040  0.009 -0.015 -0.015  0.034 -0.040  0.009 -0.015 -0.015  0.034  0.009  0.956  0.009 -0.040  0.034  0.009 -0.040  0.059  0.059 -0.040  0.034  0.109  0.259  0.084  0.009  0.009  0.009  0.009  0.009  0.009  0.084 
 0.034  0.009 -0.016  0.034  0.059 -0.016  0.084  0.034  0.134  0.981 -0.041 -0.041 -0.016 -0.041  0.034 -0.016 -0.016 -0.041  0.059 -0.041  0.009 -0.016  0.009  0.034 -0.041  0.009 -0.016 -0.016  0.034  0.009  0.981  0.009 -0.041  0.034  0.009 -0.041  0.059  0.059 -0.041  0.034  0.109  0.258  0.084  0.009  0.009  0.009  0.009  0.009  0.009  0.084 
 0.034  0.009 -0.016  0.034  0.059 -0.016  0.084  0.034  0.134  0.981 -0.041 -0.041 -0.016 -0.041  0.034 -0.016 -0.016 -0.041  0.059 -0.041  0.009 -0.016  0.009  0.034 -0.041  0.009 -0.016 -0.016  0.034  0.009  0.981  0.009 -0.041  0.034  0.009 -0.041  0.059  0.059 -0.041  0.034  0.109  0.258  0.084  0.009  0.009  0.009  0.009  0.009  0.009  0.084 
 0.034  0.009 -0.016  0.034  0.059 -0.016  0.084  0.034  0.134  0.981 -0.041 -0.041 -0.016 -0.041  0.034 -0.016 -0.016 -0.041  0.059 -0.041  0.009 -0.016  0.009  0.034 -0.041  0.009 -0.016 -0.016  0.034  0.009  0.981  0.009 -0.041  0.034  0.009 -0.041  0.059  0.059 -0.041  0.034  0.109  0.258  0.084  0.009  0.009  0.009  0.009  0.009  0.009  0.084 
 0.015  0.015 -0.034  0.040  0.140 -0.009  0.115  0.065  0.240  0.962 -0.059 -0.059 -0.034 -0.059  0.065  0.015  0.040 -0.034  0.215 -0.059  0.065 -0.034 -0.009  0.065 -0.034  0.015 -0.009 -0.034  0.015  0.015  0.962  0.015 -0.009  0.065  0.015 -0.059  0.090  0.115 -0.059  0.015  0.140  0.514  0.065  0.015 -0.009  0.040 -0.009  0.015 -0.009  0.090 
 0.027  0.052  0.102  0.202  0.351 -0.072  0.177  0.152  0.551  0.899  0.002 -0.047  0.077 -0.097  0.202  0.152  0.127 -0.072  0.301 -0.022  0.227 -0.097 -0.047  0.102 -0.072  0.002  0.002 -0.047  0.077  0.027  0.899  0.002  0.027  0.102 -0.022 -0.097  0.127  0.277 -0.097  0.077  0.326  0.850  0.177  0.077 -0.047  0.052 -0.022  0.052  0.077  0.351 
 0.001  0.076  0.225  0.200  0.400  0.026  0.350  0.150  0.649  0.848  0.026 -0.049  0.150 -0.124  0.250  0.250  0.300 -0.049  0.524  0.001  0.350 -0.049 -0.074  0.275 -0.099  0.026  0.076 -0.049  0.051  0.076  0.848  0.051  0.001  0.051  0.026 -0.024  0.200  0.400 -0.148  0.051  0.325  0.823  0.275  0.076 -0.024  0.026 -0.049  0.076  0.126  0.449 
-0.025  0.124  0.473  0.274  0.448  0.049  0.473  0.174  0.722  0.772  0.049 -0.075  0.174  0.099  0.448  0.398  0.398 -0.025  0.572 -0.000  0.647 -0.050 -0.075  0.323 -0.150  0.124  0.074  0.024  0.149  0.099  0.772  0.024  0.024  0.174  0.024  0.049  0.224  0.697 -0.200  0.074  0.398  0.772  0.398  0.199  0.074 -0.000 -0.050  0.124  0.298  0.647 
-0.019  0.155  0.529  0.280  0.429  0.081  0.529  0.230  0.728  0.753  0.031 -0.094  0.205  0.131  0.479  0.429  0.454 -0.019  0.554  0.006  0.704 -0.069 -0.094  0.355 -0.168  0.131  0.031  0.081  0.155  0.081  0.753  0.006  0.031  0.205  0.056  0.081  0.280  0.679 -0.193  0.081  0.405  0.753  0.405  0.205  0.081  0.006 -0.069  0.106  0.405  0.654 
-0.041  0.233  0.557  0.283  0.408  0.084  0.532  0.283  0.707  0.731  0.034 -0.091  0.233  0.183  0.482  0.457  0.532  0.009  0.532 -0.016  0.707 -0.066 -0.141  0.408 -0.215  0.109  0.059  0.059  0.208  0.034  0.707  0.009  0.034  0.308  0.109  0.084  0.283  0.707 -0.165  0.134  0.383  0.731  0.383  0.208  0.109  0.084 -0.091  0.084  0.432  0.682 
-0.047  0.277  0.551  0.277  0.401  0.077  0.551  0.326  0.700  0.725  0.027 -0.072  0.227  0.177  0.476  0.451  0.625  0.002  0.526 -0.022  0.700 -0.047 -0.147  0.401 -0.222  0.102  0.052  0.052  0.202  0.027  0.675  0.027  0.052  0.351  0.127  0.077  0.277  0.700 -0.172  0.202  0.376  0.725  0.376  0.227  0.127  0.077 -0.097  0.077  0.426  0.675 
-0.080  0.269  0.568  0.269  0.369  0.120  0.593  0.319  0.693  0.693  0.045 -0.055  0.194  0.169  0.468  0.493  0.643  0.020  0.493 -0.030  0.693 -0.055 -0.154  0.419 -0.229  0.095  0.070  0.095  0.219  0.020  0.618  0.070  0.095  0.394  0.194  0.070  0.319  0.693 -0.154  0.269  0.369  0.693  0.344  0.219  0.169  0.070 -0.105  0.095  0.443  0.668 
-0.078  0.271  0.520  0.246  0.370  0.146  0.594  0.320  0.669  0.694  0.046 -0.003  0.196  0.146  0.445  0.520  0.644  0.021  0.495 -0.028  0.694 -0.053 -0.128  0.420 -0.228  0.121  0.071  0.096  0.271  0.021  0.594  0.071  0.096  0.395  0.196  0.071  0.320  0.694 -0.128  0.271  0.370  0.694  0.320  0.271  0.196  0.071 -0.103  0.096  0.470  0.644 
-0.061  0.263  0.512  0.213  0.362  0.188  0.586  0.337  0.661  0.686  0.063  0.038  0.163  0.113  0.437  0.562  0.636  0.088  0.512 -0.036  0.686 -0.036 -0.086  0.387 -0.211  0.113  0.038  0.088  0.387  0.013  0.562  0.088  0.138  0.462  0.213  0.088  0.337  0.661 -0.111  0.387  0.337  0.686  0.312  0.263  0.163  0.063 -0.111  0.088  0.462  0.636 
-0.017  0.257  0.506  0.207  0.356  0.207  0.580  0.356  0.655  0.680  0.082  0.082  0.132  0.107  0.431  0.556  0.630  0.132  0.506 -0.017  0.680 -0.042  0.007  0.406 -0.217  0.107  0.032  0.082  0.381  0.007  0.556  0.107  0.207  0.456  0.257  0.082  0.331  0.655 -0.117  0.431  0.356  0.680  0.306  0.257  0.157  0.032 -0.117  0.082  0.456  0.655 
 0.028  0.253  0.502  0.228  0.327  0.203  0.576  0.352  0.651  0.676  0.103  0.128  0.128  0.078  0.452  0.552  0.626  0.153  0.502 -0.046  0.626 -0.021  0.053  0.402 -0.221  0.128  0.028  0.078  0.377  0.028  0.552  0.128  0.278  0.477  0.278  0.078  0.302  0.626 -0.121  0.477  0.352  0.676  0.327  0.278  0.153  0.003 -0.121  0.103  0.452  0.651 
 0.028  0.252  0.501  0.227  0.327  0.227  0.601  0.352  0.626  0.676  0.103  0.202  0.103  0.078  0.451  0.551  0.626  0.128  0.501 -0.047  0.601 -0.022  0.078  0.426 -0.221  0.152  0.028  0.078  0.377  0.028  0.526  0.152  0.277  0.476  0.277  0.103  0.302  0.626 -0.122  0.476  0.352  0.676  0.352  0.277  0.152  0.003 -0.122  0.128  0.451  0.651 
 0.027  0.276  0.500  0.201  0.276  0.251  0.600  0.326  0.625  0.675  0.102  0.251  0.102  0.077  0.450  0.525  0.625  0.127  0.450 -0.048  0.575  0.002  0.102  0.426 -0.197  0.127  0.002  0.052  0.376  0.027  0.525  0.176  0.301  0.450  0.276  0.127  0.301  0.650 -0.123  0.500  0.326  0.650  0.376  0.276  0.151 -0.023 -0.147  0.127  0.450  0.625 
 0.026  0.276  0.500  0.176  0.251  0.276  0.624  0.325  0.649  0.674  0.101  0.251  0.076  0.101  0.450  0.525  0.599  0.126  0.450 -0.048  0.574  0.026  0.126  0.425 -0.198  0.151  0.001  0.051  0.375  0.026  0.550  0.151  0.325  0.450  0.276  0.126  0.300  0.649 -0.123  0.500  0.300  0.649  0.375  0.276  0.126 -0.023 -0.148  0.126  0.450  0.599 
 0.027  0.277  0.526  0.177  0.202  0.301  0.625  0.252  0.650  0.675  0.102  0.252  0.077  0.102  0.451  0.526  0.600  0.102  0.451 -0.047  0.575  0.077  0.127  0.376 -0.197  0.177  0.002  0.052  0.376  0.027  0.551  0.127  0.351  0.451  0.301  0.127  0.301  0.650 -0.122  0.501  0.301  0.625  0.376  0.301  0.127 -0.022 -0.147  0.102  0.426  0.600 
 0.026  0.276  0.525  0.176  0.151  0.300  0.624  0.226  0.649  0.674  0.101  0.251  0.026  0.101  0.450  0.550  0.599  0.126  0.450 -0.048  0.574  0.051  0.126  0.375 -0.198  0.176  0.001  0.051  0.375  0.026  0.525  0.151  0.375  0.475  0.325  0.151  0.300  0.649 -0.098  0.500  0.300  0.624  0.350  0.276  0.151  0.001 -0.148  0.101  0.400  0.599 
 0.026  0.276  0.525  0.176  0.151  0.300  0.624  0.226  0.649  0.674  0.101  0.251  0.001  0.101  0.450  0.550  0.599  0.126  0.450 -0.048  0.574  0.051  0.151  0.375 -0.198  0.176  0.001  0.051  0.375  0.026  0.525  0.151  0.375  0.475  0.325  0.201  0.300  0.649 -0.098  0.475  0.276  0.624  0.350  0.251  0.176  0.001 -0.148  0.101  0.400  0.624 
 0.021  0.270  0.569  0.195  0.145  0.320  0.619  0.245  0.644  0.669  0.096  0.270 -0.029  0.096  0.444  0.569  0.594  0.170  0.469 -0.079  0.569  0.046  0.170  0.345 -0.178  0.295  0.021  0.071  0.370  0.021  0.519  0.121  0.395  0.494  0.320  0.220  0.295  0.619 -0.104  0.519  0.295  0.619  0.345  0.245  0.145  0.021 -0.129  0.096  0.395  0.644 
 0.021  0.245  0.569  0.195  0.145  0.320  0.619  0.270  0.644  0.669  0.096  0.270 -0.029  0.096  0.444  0.569  0.594  0.195  0.469 -0.104  0.569  0.046  0.170  0.345 -0.178  0.320  0.021  0.071  0.420  0.021  0.519  0.096  0.345  0.494  0.320  0.245  0.295  0.619 -0.129  0.519  0.295  0.619  0.345  0.220  0.145 -0.004 -0.129  0.096  0.395  0.644 
-0.071  0.253  0.601  0.203  0.153  0.153  0.676  0.278  0.527  0.576  0.028  0.278 -0.021  0.053  0.502  0.352  0.502  0.103  0.527 -0.046  0.552  0.003  0.103  0.327 -0.121  0.178  0.003  0.078  0.302  0.078  0.502  0.103  0.278  0.352  0.352  0.253  0.253  0.552 -0.121  0.352  0.327  0.626  0.377  0.203  0.153 -0.071 -0.096  0.153  0.402  0.701 
 0.017  0.166  0.590  0.216  0.166  0.117  0.565  0.191  0.565  0.565  0.017  0.117  0.017  0.117  0.490  0.291  0.490  0.092  0.490 -0.058  0.540  0.042  0.017  0.117 -0.108  0.166  0.042 -0.033  0.191  0.117  0.540  0.042  0.191  0.291  0.216  0.216  0.166  0.440 -0.058  0.216  0.291  0.565  0.391  0.092  0.092 -0.033 -0.058  0.117  0.341  0.690 
 0.013  0.138  0.562  0.238  0.163  0.138  0.487  0.163  0.562  0.611 -0.036  0.113 -0.036  0.113  0.487  0.238  0.512  0.063  0.487 -0.061  0.462  0.063 -0.036  0.088 -0.111  0.113  0.063 -0.011  0.138  0.113  0.537  0.063  0.013  0.213  0.163  0.113  0.163  0.412 -0.061  0.163  0.263  0.537  0.312  0.088  0.063 -0.011 -0.036  0.088  0.312  0.736 
 0.017  0.142  0.516  0.267  0.192  0.142  0.341  0.167  0.590  0.590 -0.007 -0.032 -0.007  0.117  0.516  0.142  0.441  0.042  0.466 -0.032  0.341 -0.007 -0.082  0.042 -0.082  0.017  0.092 -0.057  0.042  0.092  0.590 -0.032 -0.057  0.117  0.067  0.017  0.142  0.341 -0.057  0.017  0.291  0.541  0.242  0.042  0.017 -0.032 -0.032  0.042  0.267  0.765 
 0.021  0.121  0.520  0.246  0.171  0.146  0.320  0.171  0.594  0.594 -0.003 -0.028 -0.003  0.121  0.520  0.121  0.445  0.021  0.445 -0.028  0.295 -0.028 -0.078  0.046 -0.078 -0.028  0.096 -0.053  0.046  0.071  0.594 -0.028 -0.053  0.121  0.071  0.021  0.121  0.320 -0.053 -0.003  0.295  0.545  0.221  0.046  0.021 -0.028 -0.028  0.046  0.246  0.769 
 0.034  0.109  0.482  0.208  0.158  0.134  0.208  0.158  0.607  0.632 -0.016 -0.016 -0.016  0.084  0.482  0.084  0.408  0.009  0.408 -0.041  0.208 -0.016 -0.066  0.059 -0.066 -0.016  0.084 -0.041  0.059  0.034  0.632 -0.016 -0.066  0.084  0.084  0.009  0.109  0.308 -0.041 -0.041  0.233  0.557  0.158  0.034 -0.041 -0.016 -0.041  0.059  0.183  0.756 
 0.016  0.116  0.390  0.166  0.141  0.116  0.216  0.141  0.614  0.639 -0.008 -0.008 -0.008  0.091  0.465  0.066  0.390 -0.008  0.390 -0.058  0.116 -0.033 -0.058  0.066 -0.058 -0.008  0.041 -0.083  0.041  0.016  0.664 -0.008 -0.058  0.091  0.091 -0.033  0.116  0.266 -0.033 -0.033  0.216  0.565  0.141 -0.008 -0.033 -0.008 -0.058  0.041  0.141  0.689 
 0.022  0.072  0.346  0.147  0.147  0.122  0.197  0.147  0.620  0.720 -0.002 -0.027 -0.002  0.097  0.446  0.072  0.346 -0.027  0.346 -0.052  0.072 -0.027 -0.052  0.047 -0.052 -0.027  0.047 -0.077  0.022  0.022  0.670 -0.002 -0.052  0.072  0.097 -0.027  0.097  0.222 -0.027 -0.027  0.172  0.570  0.147 -0.002 -0.027 -0.002 -0.052  0.022  0.122  0.546 
 0.025  0.075  0.249  0.149  0.149  0.100  0.199  0.149  0.648  0.822 -0.025  0.000  0.000  0.100  0.399  0.075  0.349 -0.050  0.349 -0.075  0.050 -0.050 -0.050  0.050 -0.050 -0.050  0.025 -0.075  0.000  0.025  0.673  0.025 -0.050  0.100  0.100 -0.025  0.075  0.224 -0.025 -0.025  0.174  0.548  0.149  0.000 -0.025  0.025 -0.050  0.025  0.100  0.473 
 0.029  0.079  0.153  0.129  0.153  0.079  0.153  0.104  0.702  0.851 -0.021  0.004  0.004  0.054  0.328  0.054  0.328 -0.046  0.328 -0.071  0.029 -0.046 -0.046  0.054 -0.071 -0.046  0.029 -0.071  0.004  0.029  0.677  0.029 -0.046  0.104  0.104 -0.071  0.054  0.153 -0.021 -0.021  0.178  0.627  0.129  0.004 -0.021 -0.021 -0.046 -0.021  0.079  0.403 
 0.032  0.057  0.107  0.132  0.157  0.032  0.157  0.107  0.655  0.904 -0.017 -0.017  0.007  0.032  0.257  0.057  0.306 -0.042  0.306 -0.067  0.032 -0.042 -0.042  0.057 -0.067 -0.042  0.032 -0.067  0.007  0.032  0.680  0.032 -0.042  0.082  0.082 -0.067  0.057  0.132 -0.017 -0.017  0.182  0.630  0.132  0.007 -0.017 -0.017 -0.017 -0.017  0.082  0.306 
 0.059  0.059  0.059  0.084  0.158  0.009  0.158  0.034  0.657  0.956 -0.016 -0.016  0.009 -0.016  0.183  0.059  0.258 -0.041  0.208 -0.041  0.034 -0.041 -0.041  0.034 -0.066 -0.016  0.034 -0.041  0.009  0.034  0.731  0.034 -0.041  0.059  0.059 -0.066  0.084  0.134 -0.016 -0.016  0.109  0.756  0.134  0.034 -0.016 -0.016 -0.016  0.009  0.084  0.208 
 0.061  0.061  0.011  0.061  0.161 -0.013  0.161  0.036  0.709  0.958  0.011 -0.013  0.011 -0.013  0.061  0.011  0.186 -0.038  0.136 -0.038  0.011 -0.013 -0.013  0.036 -0.063  0.011  0.011 -0.038  0.011  0.036  0.734  0.036 -0.038  0.061  0.036 -0.063  0.086  0.086 -0.038 -0.013  0.111  0.809  0.136  0.061 -0.013 -0.013 -0.013  0.011  0.086  0.136 
 0.063  0.063 -0.011  0.063  0.163 -0.036  0.138  0.038  0.711  0.960 -0.011  0.013  0.013 -0.011  0.013  0.013  0.063 -0.036  0.063 -0.036  0.013 -0.011 -0.011  0.063 -0.061  0.013 -0.011 -0.036  0.013  0.013  0.761  0.038 -0.036  0.088  0.013 -0.061  0.088  0.038 -0.061 -0.011  0.113  0.860  0.088  0.038 -0.011 -0.011 -0.011  0.013  0.038  0.113 
 0.061  0.061 -0.013  0.061  0.161 -0.038  0.136  0.036  0.759  0.958 -0.013  0.036  0.011 -0.013  0.011  0.011  0.061 -0.038  0.061 -0.013  0.011 -0.013 -0.013  0.061 -0.063  0.011 -0.013 -0.038  0.011  0.011  0.759  0.061 -0.038  0.111  0.011 -0.063  0.086  0.036 -0.063 -0.013  0.111  0.908  0.086  0.036 -0.013 -0.013 -0.013  0.011  0.036  0.111 
 0.084  0.059 -0.016  0.084  0.158 -0.041  0.109  0.034  0.881  0.956 -0.016  0.034  0.009 -0.016  0.009  0.009  0.034 -0.041  0.059 -0.016 -0.016 -0.016 -0.016  0.059 -0.066  0.009 -0.016 -0.041  0.009  0.084  0.756  0.034 -0.041  0.109  0.009 -0.066  0.084  0.034 -0.066 -0.016  0.109  0.931  0.084  0.034 -0.016 -0.016 -0.016  0.009  0.034  0.109 
 0.083  0.058 -0.016  0.083  0.158 -0.041  0.108  0.033  0.905  0.955 -0.016  0.033  0.008 -0.016  0.008  0.008  0.033 -0.041  0.058  0.008 -0.016 -0.016 -0.016  0.058 -0.066  0.008 -0.016 -0.041  0.008  0.083  0.731  0.033 -0.041  0.108  0.008 -0.066  0.083  0.033 -0.066 -0.016  0.108  0.955  0.083  0.033 -0.016 -0.016 -0.016  0.008  0.033  0.108 
 0.083  0.058 -0.016  0.083  0.158 -0.041  0.108  0.033  0.905  0.955 -0.016  0.033  0.008 -0.016  0.008  0.008  0.033 -0.041  0.058  0.008 -0.016 -0.016 -0.016  0.058 -0.066  0.008 -0.016 -0.041  0.008  0.083  0.731  0.033 -0.041  0.108  0.008 -0.066  0.083  0.008 -0.066 -0.016  0.108  0.955  0.083  0.033 -0.016 -0.016 -0.016  0.008  0.033  0.108 
 0.083  0.058 -0.016  0.083  0.158 -0.041  0.108  0.033  0.905  0.955 -0.016  0.033  0.008 -0.016  0.008  0.008  0.033 -0.041  0.058  0.008 -0.016 -0.016 -0.016  0.058 -0.066  0.008 -0.016 -0.041  0.008  0.083  0.731  0.033 -0.041  0.108  0.008 -0.066  0.083  0.008 -0.066 -0.016  0.108  0.955  0.083  0.033 -0.016 -0.016 -0.016  0.008  0.033  0.108 
 0.084  0.059 -0.016  0.084  0.158 -0.016  0.109  0.034  0.931  0.956 -0.016  0.034  0.009 -0.016  0.009  0.009  0.034 -0.041  0.059  0.009 -0.016  0.009 -0.016  0.059 -0.066  0.009 -0.016 -0.041  0.009  0.084  0.682  0.034 -0.041  0.109  0.009 -0.066  0.084  0.009 -0.066 -0.016  0.109  0.956  0.084  0.034 -0.016 -0.016 -0.016  0.009  0.034  0.109 
 0.082  0.057 -0.043  0.132  0.231  0.032  0.082  0.032  0.929  0.929 -0.018  0.007  0.007 -0.018  0.156  0.057  0.032 -0.043  0.057 -0.018 -0.043  0.032 -0.018  0.057 -0.093  0.082  0.032  0.007  0.082  0.082  0.829  0.007 -0.043  0.181  0.007 -0.068  0.057 -0.018 -0.093  0.007  0.107  0.929  0.107  0.057 -0.043 -0.043 -0.043 -0.018  0.057  0.181 
 0.028  0.078  0.028  0.202  0.402  0.053  0.177  0.053  0.875  0.875  0.028 -0.022  0.003  0.003  0.352  0.202  0.227  0.053  0.252 -0.022  0.152  0.003 -0.047  0.152 -0.146  0.053  0.078  0.028  0.028  0.103  0.875  0.003 -0.072  0.402 -0.022 -0.072  0.128  0.028 -0.122  0.103  0.177  0.875  0.152  0.128 -0.072 -0.097 -0.072 -0.022  0.252  0.476 
 0.008  0.183  0.158  0.208  0.532  0.158  0.233  0.033  0.831  0.831  0.033 -0.066  0.008  0.008  0.482  0.307  0.357  0.133  0.357  0.008  0.332 -0.041 -0.041  0.108 -0.191  0.058  0.108  0.033  0.033  0.133  0.831  0.008 -0.016  0.606 -0.041 -0.116  0.158  0.133 -0.116  0.283  0.208  0.831  0.133  0.158 -0.091 -0.091 -0.091  0.008  0.283  0.606 
 0.027  0.177  0.277  0.252  0.625  0.202  0.351  0.102  0.775  0.775  0.077 -0.072  0.002  0.102  0.600  0.501  0.426  0.127  0.451  0.052  0.501 -0.047 -0.022  0.227 -0.197  0.127  0.077  0.052  0.077  0.102  0.750  0.052  0.027  0.625 -0.022 -0.097  0.202  0.202 -0.172  0.351  0.351  0.775  0.127  0.202  0.027 -0.122 -0.097  0.052  0.326  0.700 
 0.110  0.159  0.284  0.259  0.558  0.159  0.384  0.135  0.757  0.757  0.110 -0.115  0.010  0.135  0.558  0.558  0.458  0.110  0.483  0.035  0.533 -0.065  0.035  0.259 -0.214  0.159  0.085  0.060  0.110  0.085  0.732  0.010  0.085  0.608  0.010 -0.115  0.184  0.209 -0.189  0.483  0.384  0.732  0.159  0.259  0.035 -0.140 -0.115  0.010  0.359  0.683 
 0.085  0.135  0.359  0.284  0.533  0.159  0.409  0.159  0.708  0.683  0.085 -0.115  0.060  0.159  0.458  0.533  0.558  0.135  0.483  0.010  0.583 -0.065  0.035  0.259 -0.214  0.209  0.085  0.060  0.135  0.060  0.708  0.035  0.159  0.608 -0.015 -0.115  0.234  0.259 -0.214  0.558  0.409  0.708  0.159  0.359  0.135 -0.115 -0.140 -0.015  0.384  0.658 
 0.074  0.124  0.323  0.274  0.498  0.149  0.448  0.174  0.697  0.672  0.074 -0.050  0.049  0.124  0.448  0.523  0.647  0.149  0.473 -0.000  0.597 -0.025  0.024  0.274 -0.225  0.199  0.074  0.074  0.174  0.049  0.672  0.049  0.174  0.597  0.049 -0.100  0.274  0.249 -0.200  0.572  0.398  0.697  0.149  0.398  0.149 -0.100 -0.150 -0.025  0.373  0.647 
 0.064  0.114  0.363  0.264  0.438  0.214  0.463  0.189  0.687  0.662  0.064 -0.035  0.039  0.089  0.438  0.488  0.662  0.139  0.488 -0.010  0.637  0.039  0.039  0.264 -0.210  0.189  0.064  0.089  0.264  0.039  0.662  0.064  0.164  0.563  0.089 -0.060  0.264  0.363 -0.135  0.612  0.363  0.687  0.189  0.463  0.139 -0.110 -0.185  0.039  0.338  0.637 
 0.039  0.089  0.363  0.264  0.463  0.239  0.463  0.189  0.687  0.662  0.064 -0.010  0.014  0.089  0.438  0.488  0.637  0.139  0.463 -0.035  0.612  0.039  0.039  0.264 -0.210  0.189  0.039  0.089  0.363  0.039  0.662  0.064  0.164  0.563  0.089 -0.010  0.264  0.363 -0.135  0.612  0.338  0.687  0.189  0.463  0.139 -0.110 -0.185  0.039  0.313  0.637 
 0.030  0.105  0.429  0.280  0.454  0.304  0.454  0.205  0.678  0.653  0.055  0.005  0.005  0.080  0.404  0.479  0.628  0.130  0.454 -0.044  0.628  0.055  0.055  0.255 -0.194  0.205  0.030  0.080  0.454  0.030  0.653  0.055  0.155  0.554  0.080  0.005  0.280  0.404 -0.094  0.628  0.329  0.678  0.180  0.454  0.130 -0.119 -0.194  0.055  0.304  0.603 
 0.029  0.104  0.428  0.279  0.453  0.303  0.453  0.204  0.677  0.652  0.054  0.004 -0.020  0.079  0.403  0.478  0.627  0.129  0.453 -0.045  0.627  0.054  0.054  0.279 -0.195  0.204  0.029  0.079  0.478  0.029  0.652  0.054  0.179  0.553  0.104  0.004  0.279  0.403 -0.095  0.627  0.328  0.677  0.179  0.453  0.129 -0.120 -0.195  0.054  0.303  0.602 
 0.025  0.125  0.424  0.249  0.448  0.299  0.473  0.174  0.673  0.598  0.050  0.025 -0.025  0.050  0.424  0.448  0.648  0.125  0.448 -0.075  0.648  0.075  0.050  0.274 -0.199  0.224  0.025  0.075  0.523  0.025  0.648  0.050  0.174  0.548  0.125 -0.025  0.274  0.399 -0.100  0.673  0.324  0.673  0.174  0.448  0.125 -0.149 -0.224  0.050  0.299  0.598 
 0.023  0.123  0.447  0.223  0.422  0.297  0.472  0.173  0.671  0.596  0.048  0.023 -0.026  0.023  0.397  0.472  0.646  0.123  0.447 -0.051  0.646  0.073  0.048  0.273 -0.201  0.223  0.023  0.073  0.547  0.023  0.646  0.023  0.173  0.547  0.148 -0.026  0.273  0.397 -0.101  0.671  0.322  0.671  0.173  0.447  0.123 -0.151 -0.226  0.048  0.297  0.596 
 0.024  0.124  0.448  0.224  0.398  0.298  0.473  0.174  0.672  0.597  0.049  0.049 -0.025  0.024  0.398  0.473  0.672  0.124  0.448 -0.050  0.622  0.099  0.049  0.274 -0.200  0.249  0.024  0.074  0.548  0.024  0.647  0.024  0.149  0.548  0.174 -0.000  0.249  0.373 -0.075  0.647  0.323  0.672  0.174  0.448  0.124 -0.150 -0.225  0.049  0.298  0.597 
 0.025  0.075  0.448  0.199  0.374  0.299  0.473  0.174  0.673  0.598  0.050  0.050  0.000  0.025  0.399  0.473  0.648  0.125  0.448 -0.075  0.648  0.100  0.050  0.274 -0.199  0.249  0.025  0.075  0.548  0.025  0.648  0.000  0.174  0.548  0.199  0.000  0.249  0.399 -0.125  0.648  0.324  0.648  0.174  0.448  0.125 -0.149 -0.224  0.050  0.299  0.598 
 0.024  0.049  0.472  0.198  0.373  0.298  0.472  0.173  0.672  0.597  0.049  0.049  0.024  0.024  0.423  0.447  0.622  0.124  0.447 -0.076  0.647  0.099  0.049  0.273 -0.200  0.248  0.024  0.074  0.547  0.024  0.647 -0.001  0.173  0.572  0.198 -0.001  0.273  0.423 -0.126  0.647  0.323  0.647  0.173  0.447  0.124 -0.150 -0.225  0.049  0.298  0.622 
 0.000  0.050  0.474  0.200  0.349  0.299  0.449  0.175  0.648  0.598  0.050  0.050  0.025  0.025  0.424  0.449  0.648  0.125  0.424 -0.074  0.623  0.100  0.050  0.275 -0.199  0.250  0.000  0.075  0.549  0.025  0.648  0.000  0.175  0.573  0.200  0.000  0.275  0.424 -0.124  0.648  0.324  0.648  0.175  0.449  0.125 -0.149 -0.224  0.050  0.299  0.623 
 0.001  0.076  0.474  0.150  0.325  0.300  0.449  0.175  0.649  0.599  0.051  0.101  0.026  0.026  0.449  0.425  0.649  0.126  0.400 -0.074  0.624  0.101  0.051  0.275 -0.198  0.250  0.001  0.076  0.549  0.026  0.649  0.001  0.150  0.574  0.200  0.001  0.275  0.425 -0.124  0.649  0.325  0.649  0.175  0.449  0.126 -0.148 -0.223  0.076  0.300  0.624 
 0.001  0.076  0.475  0.151  0.325  0.300  0.450  0.151  0.649  0.599  0.051  0.126  0.026  0.026  0.450  0.425  0.649  0.126  0.400 -0.073  0.624  0.126  0.051  0.276 -0.173  0.251  0.001  0.076  0.550  0.026  0.674 -0.023  0.151  0.574  0.201  0.001  0.276  0.450 -0.123  0.649  0.325  0.649  0.176  0.450  0.126 -0.148 -0.223  0.076  0.300  0.624 
 0.000  0.075  0.474  0.150  0.324  0.299  0.474  0.150  0.648  0.598  0.075  0.150  0.025  0.025  0.424  0.424  0.648  0.125  0.399 -0.074  0.598  0.125  0.075  0.275 -0.174  0.250  0.000  0.075  0.549  0.025  0.673 -0.024  0.150  0.573  0.200  0.000  0.275  0.474 -0.124  0.673  0.324  0.648  0.175  0.449  0.125 -0.149 -0.199  0.075  0.299  0.623 
 0.033  0.108  0.432  0.208  0.332  0.108  0.407  0.208  0.681  0.557  0.008  0.083 -0.016  0.058  0.382  0.457  0.557  0.183  0.482 -0.016  0.606  0.008 -0.016  0.307 -0.141  0.108  0.058  0.033  0.457  0.058  0.656  0.008  0.083  0.532  0.158 -0.041  0.283  0.382 -0.091  0.631  0.332  0.681  0.158  0.332  0.058 -0.116 -0.141  0.108  0.307  0.656 
 0.016  0.116  0.415  0.216  0.266  0.066  0.266  0.116  0.714  0.565  0.041 -0.033  0.016  0.091  0.340  0.415  0.490  0.191  0.440 -0.008  0.639 -0.008 -0.108  0.191 -0.108  0.016  0.041 -0.008  0.340  0.116  0.664  0.016 -0.033  0.490  0.091 -0.008  0.191  0.315 -0.083  0.515  0.315  0.689  0.116  0.216  0.041 -0.083 -0.083  0.091  0.266  0.689 
 0.033  0.133  0.407  0.233  0.258  0.033  0.233  0.083  0.731  0.631  0.058 -0.016 -0.016  0.108  0.307  0.357  0.432  0.233  0.382 -0.016  0.631 -0.066 -0.091  0.158 -0.091 -0.016  0.033 -0.016  0.233  0.133  0.656  0.008 -0.016  0.507  0.083 -0.016  0.158  0.307 -0.066  0.432  0.283  0.706  0.133  0.208  0.008 -0.066 -0.066  0.083  0.208  0.681 
 0.031  0.106  0.280  0.180  0.230  0.056  0.205  0.106  0.704  0.654  0.031  0.006 -0.044  0.081  0.280  0.305  0.429  0.155  0.380 -0.019  0.629 -0.069 -0.094  0.006 -0.094 -0.019  0.056 -0.069  0.106  0.155  0.679  0.031  0.006  0.479  0.056 -0.019  0.106  0.230 -0.044  0.305  0.205  0.753  0.131  0.205 -0.019 -0.044 -0.044  0.081  0.230  0.604 
 0.041  0.091  0.190  0.141  0.240  0.016  0.190  0.066  0.664  0.639  0.041  0.016 -0.034  0.016  0.215  0.290  0.415  0.116  0.340 -0.009  0.664 -0.059 -0.084 -0.034 -0.084 -0.034  0.066 -0.059  0.041  0.116  0.689  0.066  0.016  0.464  0.041 -0.009  0.116  0.215 -0.034  0.315  0.215  0.788  0.091  0.165 -0.009 -0.034 -0.034  0.041  0.240  0.539 
 0.054  0.079  0.129  0.129  0.254 -0.020  0.204  0.079  0.652  0.702  0.004  0.004 -0.020  0.029  0.204  0.129  0.378 -0.020  0.303 -0.045  0.677 -0.045 -0.070 -0.020 -0.070 -0.020  0.029 -0.045  0.004  0.129  0.702  0.079 -0.020  0.303  0.029 -0.020  0.104  0.179 -0.045  0.204  0.229  0.802  0.079  0.179  0.004 -0.020 -0.020  0.029  0.154  0.478 
 0.061  0.086  0.086  0.086  0.210 -0.014  0.210  0.086  0.634  0.758  0.011  0.011 -0.014  0.011  0.111  0.136  0.360 -0.064  0.285 -0.064  0.684 -0.039 -0.064  0.011 -0.064 -0.014  0.036 -0.064  0.011  0.111  0.709  0.086 -0.039  0.210  0.036 -0.039  0.111  0.160 -0.039  0.086  0.235  0.858  0.111  0.136  0.011 -0.039 -0.014  0.036  0.136  0.335 
 0.044  0.069  0.044  0.044  0.219 -0.005  0.219  0.044  0.642  0.817 -0.005  0.019 -0.005  0.019  0.044  0.044  0.293 -0.055  0.244 -0.055  0.692 -0.030 -0.055  0.019 -0.080 -0.005  0.019 -0.055 -0.005  0.094  0.692  0.069 -0.030  0.144  0.044 -0.055  0.094  0.119 -0.030  0.044  0.144  0.866  0.119  0.094  0.019 -0.030 -0.030  0.044  0.119  0.293 
 0.050  0.050  0.025  0.050  0.224 -0.050  0.199  0.050  0.498  0.822  0.000  0.000  0.000  0.000  0.050  0.025  0.199 -0.050  0.199 -0.025  0.698 -0.025 -0.050  0.025 -0.075  0.000 -0.025 -0.050  0.000  0.100  0.698  0.100 -0.025  0.125  0.000 -0.050  0.100  0.075 -0.025  0.050  0.149  0.922  0.100  0.100  0.025 -0.025 -0.025  0.050  0.125  0.199 
 0.031  0.056 -0.043  0.031  0.231 -0.043  0.181  0.056  0.330  0.903 -0.018  0.006  0.006 -0.043  0.031  0.031  0.081 -0.043  0.131 -0.018  0.629 -0.018 -0.043  0.056 -0.068  0.006 -0.018 -0.043  0.006  0.056  0.729  0.106 -0.018  0.106  0.006 -0.068  0.106  0.056 -0.068  0.031  0.131  0.953  0.056  0.081  0.031 -0.018 -0.018  0.031  0.106  0.106 
 0.040  0.065 -0.035  0.040  0.214 -0.035  0.140  0.065  0.264  0.937 -0.035 -0.010  0.015 -0.035  0.040  0.040  0.065 -0.035  0.115 -0.010  0.289 -0.010 -0.035  0.065 -0.060  0.040 -0.010 -0.010  0.015  0.015  0.712  0.065 -0.035  0.090  0.015 -0.060  0.115  0.065 -0.060 -0.035  0.115  0.962  0.065  0.065 -0.010 -0.010 -0.010  0.015  0.090  0.115 
 0.022  0.022 -0.027  0.047  0.097 -0.027  0.097  0.022  0.172  0.969 -0.027 -0.027 -0.002 -0.027  0.022  0.022 -0.002 -0.027  0.097 -0.002  0.072 -0.002 -0.027  0.072 -0.052  0.022 -0.002 -0.027  0.022  0.022  0.720  0.022 -0.027  0.072  0.022 -0.052  0.122  0.047 -0.052 -0.027  0.097  0.969  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.023  0.023 -0.027  0.048  0.098 -0.027  0.098  0.023  0.172  0.970 -0.027 -0.027 -0.002 -0.027  0.023  0.023 -0.002 -0.027  0.098 -0.002  0.048 -0.002 -0.027  0.073 -0.052  0.023 -0.002 -0.027  0.048  0.023  0.720  0.023 -0.027  0.073  0.023 -0.052  0.098  0.048 -0.052 -0.027  0.098  0.970  0.098  0.023 -0.002 -0.002 -0.002  0.023 -0.027  0.098 
 0.024  0.024 -0.025  0.049  0.099 -0.025  0.074  0.024  0.149  0.971 -0.025 -0.025 -0.000 -0.025  0.024  0.024 -0.000 -0.025  0.074 -0.000 -0.000 -0.000 -0.025  0.074 -0.050  0.024 -0.000 -0.025  0.049  0.024  0.722  0.024 -0.025  0.049  0.024 -0.050  0.099  0.024 -0.050 -0.025  0.099  0.971  0.099  0.024 -0.000 -0.000 -0.000  0.024 -0.025  0.099 
 0.024  0.024 -0.026  0.049  0.099 -0.026  0.074  0.024  0.148  0.971 -0.026 -0.026 -0.001 -0.026  0.024  0.024 -0.001 -0.026  0.074 -0.001 -0.001 -0.001 -0.026  0.074 -0.051  0.024 -0.001 -0.026  0.024  0.024  0.746  0.024 -0.026  0.049  0.024 -0.051  0.099  0.024 -0.051 -0.026  0.099  0.971  0.099  0.049 -0.001 -0.001 -0.001  0.024 -0.001  0.099 
 0.023  0.023 -0.026  0.048  0.098 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.073 -0.001 -0.001 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.023  0.023  0.771  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.048 -0.001 -0.001 -0.001  0.023 -0.001  0.098 
 0.022  0.022 -0.027  0.047  0.097 -0.027  0.072  0.022  0.147  0.969 -0.027 -0.027 -0.002 -0.027  0.022  0.022 -0.002 -0.027  0.072 -0.002 -0.002 -0.002 -0.027  0.072 -0.052  0.022 -0.002 -0.027  0.047  0.022  0.820  0.022 -0.027  0.047  0.022 -0.052  0.097  0.047 -0.052 -0.002  0.097  0.969  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.020  0.020 -0.029  0.045  0.095 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.029  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054  0.020  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.020  0.020 -0.030  0.045  0.095 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005 -0.030  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
 0.019  0.019 -0.030  0.044  0.094 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019 -0.005  0.019  0.119  0.094 -0.030  0.144  0.019  0.219  0.941 -0.030 -0.030 -0.005 -0.030  0.069  0.044  0.044 -0.055  0.219  0.019  0.044 -0.030 -0.030  0.094 -0.055  0.019  0.019 -0.030  0.094 -0.005  0.941  0.044 -0.030  0.094 -0.005 -0.055  0.094  0.094 -0.055  0.044  0.244  0.941  0.094  0.044 -0.005 -0.005 -0.030 -0.005  0.019  0.219 
-0.009 -0.009  0.090  0.140  0.215 -0.009  0.190  0.015  0.539  0.887  0.040 -0.034  0.040 -0.034  0.265  0.190  0.190 -0.034  0.314 -0.009  0.190 -0.059 -0.034  0.140 -0.109 -0.034  0.065  0.015  0.065  0.040  0.887  0.015  0.015  0.190  0.015 -0.059  0.090  0.165 -0.109  0.065  0.414  0.887  0.240  0.040 -0.009 -0.009 -0.059  0.015  0.065  0.439 
-0.031 -0.006  0.168  0.168  0.243  0.019  0.293  0.069  0.667  0.841  0.044 -0.031  0.094 -0.006  0.393  0.218  0.293 -0.031  0.442 -0.006  0.442 -0.081 -0.006  0.343 -0.131 -0.056  0.094  0.019  0.094  0.044  0.841  0.019  0.044  0.293  0.019 -0.006  0.168  0.343 -0.131  0.094  0.442  0.841  0.318  0.069  0.044 -0.006 -0.106  0.019  0.193  0.592 
-0.068  0.057  0.331  0.256  0.281  0.057  0.356  0.107  0.705  0.779  0.082  0.007  0.256  0.032  0.530  0.381  0.406 -0.018  0.530  0.007  0.630 -0.093  0.057  0.381 -0.192  0.057  0.082  0.032  0.132  0.007  0.754  0.007  0.032  0.430  0.082  0.007  0.206  0.530 -0.167  0.156  0.455  0.779  0.430  0.082  0.057  0.032 -0.068  0.156  0.231  0.705 
-0.035  0.114  0.413  0.239  0.264  0.064  0.438  0.189  0.687  0.762  0.114  0.014  0.264  0.064  0.488  0.463  0.388  0.114  0.513 -0.010  0.687 -0.085  0.039  0.388 -0.210  0.039  0.064  0.014  0.164  0.014  0.737 -0.010  0.089  0.513  0.089  0.014  0.214  0.538 -0.185  0.164  0.438  0.737  0.463  0.064  0.139  0.064 -0.085  0.164  0.214  0.687 
-0.037  0.087  0.461  0.286  0.286  0.062  0.461  0.162  0.660  0.735  0.112 -0.012  0.286  0.137  0.536  0.486  0.511  0.137  0.511 -0.037  0.710 -0.062  0.037  0.361 -0.212  0.112  0.062  0.037  0.212  0.037  0.685  0.062  0.112  0.561  0.112  0.037  0.212  0.610 -0.187  0.237  0.386  0.710  0.436  0.137  0.162  0.037 -0.112  0.187  0.286  0.685 
-0.070  0.105  0.478  0.329  0.254  0.080  0.478  0.154  0.653  0.727  0.105 -0.020  0.304  0.179  0.528  0.478  0.503  0.105  0.528 -0.020  0.703 -0.070  0.030  0.379 -0.194  0.154  0.055  0.055  0.204  0.030  0.653  0.080  0.229  0.578  0.105  0.030  0.229  0.653 -0.194  0.304  0.379  0.703  0.404  0.154  0.154  0.030 -0.120  0.179  0.329  0.678 
-0.031  0.094  0.517  0.318  0.268  0.094  0.517  0.193  0.667  0.692  0.119 -0.006  0.318  0.143  0.492  0.467  0.592  0.119  0.517 -0.006  0.667 -0.081  0.044  0.343 -0.205  0.168  0.044  0.094  0.193  0.019  0.617  0.069  0.318  0.542  0.168  0.019  0.243  0.667 -0.205  0.418  0.393  0.692  0.368  0.193  0.143  0.069 -0.131  0.143  0.318  0.667 
-0.038  0.112  0.535  0.311  0.236  0.112  0.560  0.137  0.660  0.685  0.112  0.012  0.311  0.137  0.485  0.485  0.585  0.112  0.510 -0.013  0.660 -0.088  0.037  0.311 -0.212  0.161  0.037  0.087  0.261  0.037  0.610  0.062  0.361  0.535  0.186  0.037  0.236  0.660 -0.187  0.485  0.386  0.685  0.361  0.211  0.137  0.037 -0.138  0.137  0.311  0.660 
 0.030  0.130  0.578  0.304  0.230  0.155  0.578  0.130  0.653  0.678  0.130  0.080  0.230  0.105  0.454  0.479  0.628  0.155  0.479 -0.019  0.628 -0.069  0.080  0.280 -0.219  0.180  0.005  0.080  0.280  0.030  0.554  0.055  0.379  0.504  0.255  0.030  0.255  0.653 -0.169  0.504  0.379  0.678  0.379  0.280  0.130  0.055 -0.169  0.130  0.280  0.653 
 0.031  0.181  0.579  0.281  0.206  0.181  0.579  0.131  0.654  0.679  0.131  0.106  0.231  0.081  0.455  0.505  0.629  0.156  0.480 -0.018  0.629 -0.043  0.106  0.256 -0.218  0.181  0.006  0.081  0.281  0.031  0.505  0.056  0.405  0.480  0.281  0.031  0.256  0.629 -0.118  0.505  0.380  0.679  0.380  0.305  0.131  0.081 -0.168  0.131  0.281  0.629 
 0.054  0.203  0.577  0.278  0.178  0.228  0.577  0.129  0.677  0.677  0.153  0.129  0.228  0.079  0.452  0.527  0.627  0.129  0.477 -0.021  0.627  0.004  0.104  0.228 -0.220  0.178  0.004  0.079  0.328  0.029  0.502  0.054  0.403  0.477  0.303  0.054  0.303  0.627 -0.096  0.527  0.378  0.677  0.403  0.303  0.129  0.079 -0.170  0.129  0.253  0.627 
 0.053  0.203  0.576  0.228  0.178  0.228  0.576  0.128  0.676  0.676  0.153  0.128  0.228  0.078  0.452  0.527  0.626  0.128  0.477 -0.021  0.626  0.028  0.103  0.228 -0.221  0.178  0.003  0.078  0.352  0.028  0.502  0.053  0.402  0.477  0.302  0.053  0.302  0.626 -0.096  0.527  0.402  0.676  0.402  0.352  0.128  0.103 -0.171  0.128  0.253  0.601 
 0.075  0.200  0.573  0.200  0.125  0.275  0.573  0.125  0.673  0.673  0.150  0.175  0.200  0.075  0.449  0.524  0.648  0.150  0.424 -0.024  0.598  0.075  0.075  0.225 -0.224  0.225  0.025  0.075  0.349  0.025  0.499  0.050  0.399  0.499  0.299  0.050  0.324  0.623 -0.074  0.549  0.399  0.673  0.399  0.424  0.125  0.150 -0.174  0.150  0.250  0.598 
 0.073  0.172  0.571  0.172  0.123  0.272  0.571  0.123  0.671  0.671  0.197  0.172  0.197  0.073  0.446  0.521  0.646  0.172  0.422 -0.027  0.621  0.123  0.073  0.222 -0.201  0.247  0.023  0.073  0.347  0.023  0.496  0.023  0.422  0.496  0.297  0.048  0.297  0.621 -0.077  0.546  0.397  0.671  0.397  0.422  0.123  0.172 -0.176  0.147  0.247  0.596 
 0.073  0.198  0.571  0.173  0.123  0.297  0.571  0.148  0.671  0.696  0.198  0.198  0.173  0.073  0.447  0.522  0.646  0.173  0.397 -0.026  0.621  0.123  0.073  0.223 -0.176  0.273  0.023  0.073  0.347  0.023  0.522  0.023  0.422  0.497  0.297  0.048  0.297  0.621 -0.076  0.547  0.397  0.671  0.422  0.422  0.123  0.198 -0.176  0.123  0.248  0.596 
 0.072  0.196  0.570  0.171  0.122  0.296  0.570  0.146  0.670  0.695  0.196  0.221  0.171  0.072  0.445  0.520  0.645  0.171  0.396 -0.028  0.620  0.122  0.072  0.221 -0.177  0.271  0.022  0.072  0.346  0.022  0.520  0.022  0.421  0.495  0.296  0.047  0.296  0.620 -0.078  0.545  0.396  0.670  0.421  0.421  0.097  0.246 -0.177  0.122  0.246  0.595 
 0.073  0.198  0.596  0.173  0.123  0.297  0.571  0.173  0.671  0.646  0.198  0.248  0.148  0.073  0.422  0.522  0.646  0.173  0.397 -0.051  0.596  0.148  0.073  0.223 -0.151  0.273  0.023  0.098  0.347  0.023  0.497  0.023  0.422  0.497  0.297  0.048  0.297  0.621 -0.076  0.571  0.372  0.671  0.397  0.422  0.073  0.248 -0.176  0.123  0.248  0.621 
 0.099  0.198  0.622  0.173  0.124  0.298  0.572  0.173  0.672  0.647  0.198  0.248  0.124  0.074  0.423  0.522  0.622  0.173  0.398 -0.076  0.597  0.148  0.074  0.223 -0.150  0.273  0.024  0.099  0.373  0.024  0.497 -0.001  0.423  0.497  0.298  0.049  0.298  0.597 -0.076  0.547  0.373  0.647  0.398  0.423  0.074  0.248 -0.175  0.099  0.248  0.622 
 0.100  0.175  0.623  0.175  0.125  0.299  0.573  0.175  0.673  0.623  0.200  0.250  0.125  0.075  0.424  0.524  0.623  0.175  0.399 -0.099  0.598  0.150  0.075  0.225 -0.149  0.275  0.025  0.100  0.399  0.025  0.499 -0.024  0.424  0.499  0.299  0.025  0.299  0.598 -0.074  0.549  0.374  0.648  0.374  0.424  0.075  0.250 -0.199  0.100  0.250  0.623 
 0.066  0.190  0.564  0.141  0.190  0.240  0.539  0.240  0.589  0.614  0.240  0.240  0.066  0.091  0.439  0.489  0.589  0.190  0.390 -0.059  0.539  0.066  0.016  0.190 -0.134  0.165  0.041  0.091  0.315  0.066  0.464  0.016  0.340  0.539  0.240  0.016  0.215  0.564 -0.084  0.439  0.439  0.639  0.365  0.340  0.066  0.315 -0.134  0.066  0.290  0.664 
 0.038  0.187  0.511  0.187  0.237  0.113  0.461  0.187  0.536  0.611  0.212  0.088  0.038  0.113  0.412  0.436  0.486  0.138  0.412 -0.037  0.536  0.013 -0.112  0.063 -0.112  0.063  0.013 -0.037  0.262  0.063  0.561 -0.012  0.187  0.511  0.212  0.038  0.162  0.436 -0.037  0.362  0.312  0.611  0.187  0.237  0.088  0.113 -0.087  0.038  0.287  0.611 
 0.065  0.165  0.414  0.215  0.215  0.065  0.389  0.165  0.564  0.638  0.140 -0.009  0.040  0.140  0.389  0.464  0.439  0.090  0.414 -0.034  0.514 -0.034 -0.084  0.015 -0.109  0.040  0.015 -0.059  0.165  0.040  0.588  0.015  0.115  0.464  0.140  0.015  0.115  0.389 -0.059  0.289  0.339  0.564  0.165  0.240  0.015  0.015 -0.059  0.065  0.240  0.588 
 0.039  0.163  0.363  0.238  0.213  0.064  0.338  0.114  0.587  0.687  0.039 -0.011  0.064  0.139  0.338  0.413  0.437  0.039  0.388 -0.011  0.512 -0.061 -0.086 -0.011 -0.086  0.039  0.014 -0.061  0.114  0.039  0.587  0.039  0.039  0.363  0.089  0.014  0.114  0.313 -0.061  0.139  0.338  0.587  0.139  0.114  0.039 -0.011 -0.036  0.064  0.188  0.562 
 0.026  0.126  0.350  0.250  0.150  0.051  0.325  0.101  0.599  0.748  0.001  0.001  0.001  0.076  0.300  0.300  0.449  0.026  0.400  0.001  0.350 -0.049 -0.074  0.001 -0.074 -0.024  0.026 -0.074  0.076  0.051  0.599  0.026  0.026  0.275  0.076  0.026  0.076  0.325 -0.049  0.076  0.300  0.549  0.126  0.076  0.026 -0.024 -0.049  0.051  0.150  0.549 
 0.018  0.118  0.267  0.192  0.142  0.043  0.217  0.093  0.641  0.815 -0.007  0.018  0.018  0.068  0.267  0.192  0.441 -0.032  0.392 -0.007  0.217 -0.032 -0.057 -0.007 -0.057 -0.057  0.018 -0.082 -0.007  0.018  0.641  0.018 -0.032  0.093  0.093 -0.007  0.093  0.267 -0.032 -0.007  0.242  0.541  0.093  0.018 -0.007 -0.007 -0.057 -0.032  0.118  0.466 
 0.050  0.100  0.149  0.149  0.149  0.050  0.199  0.075  0.648  0.847  0.000  0.025  0.025  0.075  0.249  0.149  0.399 -0.025  0.299 -0.050  0.199 -0.025 -0.050  0.000 -0.050 -0.050  0.025 -0.075  0.025  0.025  0.648  0.025 -0.050  0.100  0.050  0.000  0.100  0.199 -0.025 -0.025  0.249  0.573  0.100  0.025 -0.025  0.000 -0.050 -0.025  0.100  0.424 
 0.081  0.081  0.056  0.081  0.155  0.006  0.155  0.031  0.654  0.928 -0.019  0.006  0.006  0.031  0.205  0.056  0.280 -0.044  0.255 -0.044  0.056 -0.044 -0.044  0.031 -0.044 -0.019  0.056 -0.044  0.031  0.031  0.679  0.031 -0.044  0.106  0.056 -0.044  0.131  0.180 -0.019 -0.019  0.155  0.704  0.131  0.006 -0.019 -0.019 -0.019 -0.019  0.081  0.355 
 0.060  0.060  0.060  0.060  0.160 -0.014  0.160  0.035  0.633  0.932 -0.014 -0.014  0.010  0.010  0.135  0.010  0.235 -0.039  0.185 -0.039  0.060 -0.039 -0.039  0.035 -0.064 -0.014  0.010 -0.039  0.010  0.035  0.708  0.035 -0.039  0.085  0.035 -0.064  0.110  0.110 -0.014 -0.014  0.135  0.733  0.085  0.010 -0.014 -0.014 -0.014  0.010  0.085  0.260 
 0.064  0.064 -0.011  0.064  0.163 -0.036  0.163  0.039  0.637  0.961 -0.011 -0.011  0.014 -0.011  0.064  0.014  0.089 -0.036  0.089 -0.036  0.014 -0.011 -0.036  0.064 -0.061  0.014 -0.011 -0.036  0.014  0.014  0.736  0.039 -0.036  0.064  0.014 -0.061  0.089  0.064 -0.061 -0.011  0.114  0.861  0.089  0.039 -0.011 -0.011 -0.011  0.014  0.064  0.139 
 0.067  0.067 -0.033  0.067  0.166 -0.033  0.117  0.042  0.565  0.964 -0.008 -0.008  0.017 -0.008  0.042  0.017  0.042 -0.033  0.092 -0.033 -0.008 -0.008 -0.033  0.067 -0.058  0.017 -0.008 -0.033  0.017  0.017  0.714  0.017 -0.033  0.067  0.017 -0.058  0.092  0.067 -0.058 -0.008  0.117  0.889  0.092  0.042 -0.008 -0.008 -0.008  0.017  0.042  0.117 
 0.067  0.067 -0.033  0.067  0.166 -0.033  0.117  0.042  0.490  0.964 -0.008  0.017  0.017 -0.008  0.017  0.017 -0.008 -0.033  0.067 -0.008 -0.008 -0.008 -0.033  0.067 -0.058  0.017 -0.008 -0.033  0.017  0.042  0.739  0.042 -0.033  0.092  0.017 -0.058  0.092  0.042 -0.058 -0.008  0.117  0.964  0.092  0.042 -0.008 -0.008 -0.008  0.017  0.042  0.117 
 0.068  0.068 -0.031  0.068  0.168 -0.031  0.118  0.043  0.417  0.965 -0.006 -0.006  0.018 -0.031  0.018  0.018 -0.006 -0.031  0.068 -0.006 -0.006 -0.006 -0.031  0.068 -0.056  0.018 -0.006 -0.031  0.018  0.043  0.741  0.018 -0.031  0.068  0.018 -0.056  0.093  0.043 -0.056 -0.031  0.118  0.965  0.093  0.043 -0.006 -0.006 -0.006  0.018  0.043  0.118 
 0.022  0.022 -0.028  0.072  0.097 -0.028  0.097  0.022  0.196  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.794  0.022 -0.028  0.072  0.022 -0.053  0.097  0.047 -0.053 -0.028  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.022  0.022 -0.028  0.047  0.097 -0.028  0.097  0.022  0.171  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.819  0.022 -0.028  0.072  0.022 -0.053  0.097  0.047 -0.053 -0.028  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.022  0.022 -0.028  0.047  0.097 -0.028  0.072  0.022  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.844  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.028  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.020  0.020 -0.029  0.045  0.095 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.004  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054 -0.004  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.019  0.019 -0.030  0.044  0.094 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.039  0.114 -0.036  0.014  0.188 -0.011  0.114  0.039  0.288  0.936  0.014 -0.036  0.014 -0.061  0.114  0.089  0.139 -0.061  0.238 -0.036  0.039 -0.036 -0.036  0.114 -0.086 -0.011  0.089  0.014  0.064  0.039  0.936  0.039 -0.061  0.139  0.039 -0.061  0.064  0.114 -0.086  0.039  0.213  0.936  0.114  0.014 -0.036 -0.036 -0.036  0.014  0.039  0.288 
 0.021  0.121  0.021  0.121  0.245 -0.004  0.220  0.071  0.594  0.868  0.096 -0.054  0.071 -0.079  0.170  0.270  0.195 -0.054  0.469 -0.054  0.245 -0.079 -0.029  0.270 -0.129 -0.004  0.121 -0.029  0.096  0.021  0.868  0.021 -0.054  0.220 -0.004 -0.079  0.220  0.270 -0.104  0.071  0.420  0.868  0.220 -0.004 -0.079 -0.004 -0.054 -0.004  0.145  0.494 
-0.016  0.133  0.108  0.133  0.307  0.083  0.283  0.108  0.656  0.831  0.033 -0.016  0.058 -0.016  0.283  0.382  0.233  0.008  0.432 -0.091  0.307 -0.016 -0.066  0.332 -0.166  0.008  0.158  0.008  0.108  0.008  0.831  0.033 -0.091  0.357 -0.066 -0.091  0.283  0.507 -0.141  0.133  0.407  0.831  0.208  0.008  0.033  0.058 -0.091 -0.041  0.208  0.606 
-0.029  0.145  0.270  0.220  0.320  0.071  0.444  0.195  0.718  0.768  0.071 -0.054  0.121 -0.004  0.370  0.619  0.395  0.096  0.544 -0.029  0.519 -0.029 -0.029  0.420 -0.203  0.096  0.145 -0.029  0.145  0.021  0.768  0.046 -0.004  0.494 -0.029 -0.079  0.345  0.619 -0.178  0.195  0.370  0.768  0.345  0.096  0.071  0.071 -0.079  0.021  0.370  0.718 
-0.021  0.203  0.378  0.203  0.303  0.054  0.527  0.178  0.702  0.751  0.079 -0.071  0.153  0.004  0.378  0.652  0.427  0.054  0.552 -0.021  0.552 -0.046 -0.046  0.427 -0.195  0.104  0.129 -0.046  0.178  0.004  0.751  0.029  0.029  0.502  0.004 -0.071  0.353  0.677 -0.170  0.228  0.353  0.751  0.353  0.203  0.054  0.079 -0.096  0.004  0.427  0.702 
-0.040  0.184  0.458  0.209  0.284  0.184  0.558  0.209  0.682  0.732  0.084 -0.090  0.159  0.084  0.408  0.657  0.533  0.109  0.558 -0.040  0.657 -0.040 -0.065  0.408 -0.190  0.084  0.084  0.009  0.184  0.059  0.682  0.059  0.059  0.533 -0.015 -0.040  0.333  0.707 -0.165  0.284  0.333  0.707  0.383  0.234  0.034  0.059 -0.115  0.034  0.483  0.682 
 0.004  0.153  0.452  0.203  0.278  0.203  0.602  0.228  0.677  0.726  0.104 -0.046  0.129  0.079  0.403  0.652  0.577  0.104  0.552  0.004  0.652 -0.046  0.004  0.403 -0.195  0.079  0.079  0.004  0.203  0.054  0.602  0.054  0.153  0.527 -0.021 -0.021  0.303  0.677 -0.170  0.353  0.328  0.702  0.378  0.228  0.054  0.079 -0.121  0.029  0.477  0.677 
 0.094  0.168  0.492  0.193  0.268  0.193  0.592  0.218  0.667  0.716  0.143 -0.056  0.094  0.094  0.393  0.642  0.642  0.143  0.517 -0.006  0.667 -0.056  0.019  0.393 -0.205  0.094  0.069  0.044  0.243  0.069  0.542  0.044  0.193  0.542 -0.006  0.019  0.318  0.667 -0.155  0.492  0.318  0.692  0.418  0.243  0.069  0.069 -0.131  0.019  0.442  0.667 
 0.090  0.189  0.513  0.164  0.264  0.189  0.588  0.239  0.663  0.712  0.140 -0.035  0.115  0.090  0.389  0.638  0.638  0.164  0.513 -0.035  0.663 -0.060  0.015  0.389 -0.209  0.065  0.065  0.040  0.264  0.065  0.538 -0.010  0.214  0.538  0.065  0.040  0.289  0.663 -0.110  0.538  0.339  0.688  0.414  0.264  0.065  0.065 -0.135  0.015  0.438  0.663 
 0.087  0.187  0.511  0.162  0.286  0.187  0.561  0.262  0.660  0.710  0.137 -0.012  0.112  0.087  0.386  0.635  0.635  0.162  0.511 -0.062  0.635 -0.062  0.037  0.361 -0.212  0.087  0.062  0.037  0.262  0.062  0.536 -0.037  0.262  0.536  0.137  0.062  0.286  0.660 -0.112  0.536  0.336  0.660  0.411  0.262  0.087  0.062 -0.112  0.087  0.436  0.660 
 0.086  0.161  0.510  0.161  0.310  0.161  0.560  0.261  0.634  0.709  0.136 -0.013  0.111  0.086  0.385  0.634  0.634  0.136  0.510 -0.088  0.609 -0.063  0.036  0.360 -0.213  0.086  0.061  0.036  0.261  0.061  0.535 -0.013  0.310  0.535  0.161  0.061  0.285  0.659 -0.113  0.535  0.310  0.634  0.410  0.310  0.086  0.061 -0.113  0.061  0.435  0.659 
 0.083  0.158  0.507  0.158  0.307  0.183  0.557  0.283  0.631  0.706  0.133  0.058  0.108  0.083  0.407  0.581  0.631  0.158  0.482 -0.091  0.606 -0.066  0.033  0.357 -0.216  0.083  0.033  0.033  0.283  0.058  0.507 -0.016  0.357  0.532  0.208  0.083  0.283  0.656 -0.116  0.532  0.307  0.631  0.407  0.332  0.108  0.058 -0.141  0.058  0.432  0.631 
 0.084  0.158  0.507  0.158  0.283  0.183  0.557  0.308  0.632  0.707  0.134  0.059  0.109  0.084  0.408  0.557  0.632  0.183  0.482 -0.091  0.607 -0.066  0.034  0.333 -0.215  0.084  0.034  0.034  0.283  0.034  0.507 -0.016  0.383  0.532  0.208  0.109  0.283  0.657 -0.091  0.532  0.333  0.632  0.408  0.333  0.084  0.084 -0.141  0.059  0.432  0.632 
 0.080  0.154  0.503  0.154  0.254  0.229  0.553  0.354  0.628  0.703  0.204  0.080  0.154  0.080  0.404  0.553  0.628  0.179  0.453 -0.095  0.628 -0.070  0.055  0.329 -0.219  0.080  0.030  0.030  0.304  0.030  0.528 -0.020  0.428  0.528  0.229  0.105  0.279  0.628 -0.095  0.528  0.329  0.628  0.404  0.329  0.105  0.130 -0.144  0.055  0.428  0.628 
 0.080  0.154  0.503  0.154  0.254  0.254  0.553  0.354  0.603  0.703  0.204  0.105  0.154  0.080  0.379  0.528  0.628  0.179  0.453 -0.095  0.628  0.030  0.105  0.304 -0.219  0.080  0.030  0.030  0.304  0.030  0.503 -0.020  0.428  0.478  0.254  0.105  0.279  0.628 -0.095  0.553  0.354  0.628  0.404  0.354  0.105  0.154 -0.144  0.055  0.428  0.628 
 0.080  0.155  0.504  0.155  0.255  0.280  0.554  0.354  0.628  0.703  0.205  0.155  0.155  0.080  0.379  0.529  0.628  0.205  0.429 -0.094  0.603  0.080  0.130  0.280 -0.219  0.105  0.030  0.030  0.329  0.030  0.504 -0.019  0.429  0.454  0.255  0.130  0.304  0.628 -0.069  0.554  0.354  0.628  0.429  0.404  0.130  0.180 -0.144  0.055  0.404  0.628 
 0.077  0.151  0.500  0.151  0.251  0.276  0.550  0.351  0.625  0.675  0.201  0.151  0.151  0.077  0.376  0.525  0.625  0.226  0.426 -0.098  0.600  0.077  0.176  0.251 -0.222  0.102  0.027  0.027  0.326  0.027  0.550 -0.023  0.426  0.450  0.251  0.201  0.301  0.625 -0.073  0.550  0.351  0.625  0.426  0.426  0.127  0.176 -0.147  0.052  0.401  0.625 
 0.049  0.149  0.548  0.149  0.224  0.274  0.548  0.348  0.647  0.672  0.224  0.174  0.149  0.074  0.398  0.523  0.622  0.224  0.398 -0.100  0.597  0.099  0.199  0.224 -0.225  0.174  0.024  0.049  0.323  0.024  0.548 -0.025  0.423  0.448  0.274  0.199  0.298  0.622 -0.075  0.548  0.323  0.622  0.448  0.448  0.099  0.224 -0.150  0.074  0.373  0.597 
 0.073  0.172  0.546  0.147  0.222  0.272  0.546  0.322  0.646  0.646  0.222  0.197  0.147  0.073  0.372  0.496  0.621  0.222  0.397 -0.102  0.596  0.098  0.197  0.222 -0.226  0.172  0.023  0.048  0.372  0.023  0.546 -0.027  0.422  0.446  0.272  0.247  0.297  0.621 -0.077  0.546  0.322  0.621  0.446  0.446  0.098  0.247 -0.176  0.048  0.322  0.596 
 0.096  0.170  0.544  0.145  0.220  0.295  0.544  0.320  0.644  0.644  0.220  0.220  0.145  0.071  0.370  0.494  0.619  0.220  0.395 -0.104  0.594  0.121  0.195  0.220 -0.178  0.245  0.021  0.046  0.370  0.021  0.519 -0.004  0.420  0.444  0.270  0.245  0.295  0.619 -0.079  0.544  0.320  0.619  0.444  0.444  0.121  0.220 -0.178  0.046  0.270  0.619 

 0.991  0.019  0.094 -0.030  0.044 -0.030  0.019  0.019 -0.005 -0.005 -0.005 -0.005 -0.030 -0.030  0.044 -0.005 -0.030  0.019  0.019  0.019 -0.005 -0.030 -0.030 -0.030 -0.030 -0.005 -0.005 -0.005 -0.005 -0.030  0.019 -0.030 -0.005 -0.030 -0.005  0.019 -0.005 -0.030 -0.005 -0.030 -0.005 -0.030  0.019 -0.005 -0.005  0.044 -0.005  0.044 -0.005 -0.005 
 0.996 -0.000  0.099 -0.025  0.049 -0.025 -0.000  0.024 -0.000 -0.000 -0.000 -0.000 -0.025 -0.025  0.024 -0.000 -0.025  0.024  0.024 -0.000 -0.000 -0.025 -0.025 -0.025 -0.025 -0.000 -0.025 -0.025 -0.000 -0.025  0.024 -0.025 -0.000 -0.025 -0.000  0.024 -0.000 -0.025 -0.025 -0.025 -0.000 -0.025  0.024 -0.000 -0.000  0.049 -0.000  0.049 -0.000 -0.025 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.001  0.004  0.104 -0.020  0.054 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.029  0.004  0.054  0.004 -0.020 
 1.000  0.004  0.129 -0.021  0.054 -0.021  0.004  0.004  0.004  0.004 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.004  0.029  0.029 -0.021  0.004 -0.021 -0.021 -0.021 -0.021  0.004 -0.021 -0.021 -0.021 -0.021  0.029 -0.021  0.004 -0.021  0.004  0.004  0.004  0.004  0.004 -0.021  0.004 -0.021  0.004 -0.021  0.004  0.029  0.004  0.054  0.004 -0.021 
 0.987  0.015  0.688 -0.035  0.065 -0.035  0.065  0.015  0.015 -0.010 -0.035  0.015 -0.035 -0.010  0.040 -0.010  0.090  0.040  0.090 -0.010 -0.010 -0.035 -0.035 -0.035 -0.035 -0.010  0.065 -0.035 -0.035 -0.035  0.015 -0.035  0.015 -0.035  0.040  0.040 -0.010  0.065  0.040 -0.035 -0.010 -0.035  0.090 -0.010 -0.010  0.015  0.015  0.140  0.040 -0.035 
 0.979  0.007  0.780 -0.042  0.082 -0.042  0.082  0.007  0.007 -0.017 -0.042  0.007 -0.042 -0.017  0.032 -0.017  0.082  0.057  0.082  0.007 -0.017 -0.042 -0.042 -0.042 -0.042 -0.017  0.082 -0.042 -0.042 -0.042  0.057 -0.042  0.007 -0.042  0.057  0.032 -0.017  0.107  0.057 -0.042 -0.017 -0.017  0.082 -0.017  0.007  0.057  0.007  0.132  0.032 -0.042 
 0.958  0.011  0.958 -0.038  0.111 -0.038  0.161  0.036  0.011  0.061 -0.063 -0.038 -0.038 -0.013  0.136  0.036  0.136  0.086  0.261 -0.013  0.011 -0.063 -0.063 -0.038  0.036  0.011  0.111 -0.038 -0.038 -0.038  0.061 -0.038  0.036 -0.063  0.136  0.061  0.011  0.136  0.061 -0.063 -0.038 -0.013  0.211 -0.038 -0.013  0.036 -0.013  0.086  0.136 -0.063 
 0.922 -0.025  0.922  0.000  0.224 -0.075  0.299  0.050 -0.025  0.100 -0.075 -0.075 -0.050  0.000  0.174  0.050  0.149  0.100  0.473  0.000  0.100 -0.050 -0.075 -0.025  0.025  0.100  0.100 -0.075 -0.050 -0.025  0.100  0.000  0.000 -0.100  0.274  0.050 -0.025  0.424  0.050 -0.075 -0.075 -0.025  0.374  0.000 -0.050  0.050  0.000  0.075  0.174 -0.025 
 0.849  0.051  0.849  0.076  0.251  0.001  0.450  0.101  0.001  0.251 -0.023 -0.123 -0.098  0.026  0.425  0.101  0.450  0.126  0.774 -0.023  0.350 -0.073 -0.098  0.001  0.026  0.201  0.101  0.001 -0.023 -0.048  0.251 -0.023  0.026 -0.123  0.350  0.051  0.051  0.699 -0.023 -0.048 -0.023  0.176  0.649  0.051 -0.098  0.026  0.026  0.001  0.226  0.201 
 0.811  0.013  0.811  0.063  0.287  0.013  0.462  0.138  0.038  0.412 -0.036 -0.086 -0.086  0.038  0.537  0.138  0.512  0.088  0.786 -0.061  0.412 -0.061 -0.111 -0.011  0.038  0.188  0.063  0.013 -0.036  0.013  0.312  0.038  0.088 -0.161  0.611  0.063  0.013  0.736 -0.061 -0.086  0.013  0.312  0.711  0.138 -0.111  0.013 -0.011 -0.011  0.412  0.213 
 0.769 -0.028  0.769  0.196  0.345  0.071  0.495  0.171  0.121  0.644 -0.028 -0.078  0.021  0.196  0.569  0.196  0.669  0.071  0.769 -0.103  0.545  0.071 -0.128  0.071 -0.003  0.121  0.021  0.021  0.046  0.046  0.495  0.021  0.046 -0.128  0.719  0.071  0.046  0.744 -0.078 -0.078  0.096  0.445  0.769  0.246 -0.078  0.021 -0.028  0.121  0.395  0.395 
 0.752 -0.045  0.727  0.204  0.328  0.079  0.503  0.179  0.303  0.677 -0.020 -0.020  0.004  0.229  0.528  0.229  0.677  0.054  0.702 -0.070  0.553  0.104 -0.095  0.154 -0.020  0.104  0.029  0.029  0.054  0.054  0.503  0.054  0.029 -0.095  0.727  0.079  0.104  0.702 -0.095 -0.045  0.179  0.553  0.727  0.254 -0.045  0.004 -0.045  0.179  0.353  0.503 
 0.710 -0.037  0.710  0.212  0.312  0.113  0.436  0.187  0.387  0.735 -0.012  0.063  0.063  0.312  0.536  0.237  0.710  0.013  0.661 -0.112  0.636  0.113 -0.112  0.237 -0.012  0.063  0.063  0.063  0.038  0.038  0.486  0.038  0.013 -0.037  0.735  0.088  0.113  0.686 -0.112  0.038  0.212  0.636  0.611  0.262 -0.012 -0.012 -0.037  0.237  0.362  0.586 
 0.705 -0.042  0.705  0.257  0.306  0.132  0.431  0.232  0.456  0.730  0.057  0.057  0.082  0.331  0.531  0.257  0.705  0.007  0.630 -0.117  0.630  0.132 -0.117  0.232  0.007  0.057  0.057  0.057  0.057  0.032  0.506  0.032  0.032 -0.017  0.730  0.082  0.132  0.655 -0.092  0.057  0.232  0.630  0.605  0.282 -0.017 -0.017 -0.042  0.232  0.356  0.580 
 0.624 -0.049  0.674  0.225  0.325  0.101  0.375  0.225  0.474  0.723  0.126  0.126  0.076  0.400  0.524  0.350  0.699  0.051  0.599 -0.099  0.649  0.101 -0.124  0.250  0.001  0.051  0.076  0.076  0.126  0.026  0.499  0.026  0.126  0.076  0.699  0.101  0.150  0.624 -0.074  0.101  0.250  0.674  0.524  0.325  0.001  0.001 -0.049  0.250  0.350  0.599 
 0.624 -0.049  0.674  0.225  0.325  0.026  0.300  0.225  0.499  0.674  0.126  0.150  0.051  0.400  0.524  0.350  0.699  0.051  0.599 -0.099  0.649  0.101 -0.124  0.250 -0.024  0.051  0.101  0.076  0.200  0.026  0.499  0.026  0.150  0.101  0.699  0.101  0.175  0.624 -0.049  0.101  0.300  0.674  0.474  0.350  0.051  0.001 -0.074  0.250  0.350  0.599 
 0.621 -0.027  0.671  0.197  0.297  0.023  0.272  0.222  0.496  0.671  0.123  0.147  0.048  0.347  0.521  0.347  0.696  0.073  0.596 -0.102  0.646  0.073 -0.127  0.247 -0.027  0.048  0.123  0.073  0.197  0.023  0.471  0.048  0.247  0.147  0.696  0.073  0.197  0.621 -0.027  0.147  0.322  0.671  0.446  0.397  0.048 -0.002 -0.102  0.222  0.347  0.621 
 0.619 -0.029  0.669  0.195  0.295  0.021  0.270  0.220  0.519  0.669  0.121  0.170  0.021  0.345  0.519  0.320  0.644  0.096  0.569 -0.104  0.644  0.071 -0.129  0.245 -0.029  0.046  0.121  0.071  0.270  0.021  0.469  0.046  0.345  0.145  0.694  0.071  0.195  0.619 -0.029  0.170  0.320  0.669  0.444  0.395  0.046 -0.004 -0.104  0.195  0.345  0.619 
 0.588  0.015  0.663  0.189  0.289  0.015  0.264  0.264  0.538  0.663  0.115  0.164  0.015  0.364  0.513  0.339  0.638  0.140  0.513 -0.110  0.638  0.065 -0.085  0.239 -0.035  0.040  0.090  0.065  0.289  0.015  0.463  0.040  0.364  0.264  0.638  0.115  0.239  0.613 -0.010  0.214  0.339  0.663  0.364  0.414  0.040  0.015 -0.110  0.189  0.339  0.613 
 0.560  0.012  0.635  0.186  0.311  0.037  0.261  0.311  0.535  0.660  0.112  0.186  0.012  0.386  0.510  0.336  0.635  0.137  0.510 -0.113  0.635  0.087 -0.063  0.236 -0.038  0.037  0.087  0.062  0.286  0.012  0.460  0.037  0.411  0.286  0.585  0.161  0.261  0.610  0.037  0.211  0.336  0.660  0.361  0.435  0.012  0.037 -0.113  0.161  0.361  0.610 
 0.559  0.035  0.633  0.185  0.309  0.035  0.235  0.359  0.534  0.658  0.110  0.185  0.035  0.359  0.509  0.359  0.633  0.110  0.484 -0.114  0.633  0.135 -0.014  0.260 -0.039  0.035  0.060  0.060  0.284  0.010  0.484  0.035  0.434  0.309  0.509  0.135  0.284  0.608  0.035  0.210  0.334  0.658  0.309  0.459  0.010  0.035 -0.139  0.160  0.384  0.608 
 0.558  0.035  0.633  0.209  0.309  0.035  0.234  0.359  0.533  0.658  0.085  0.184  0.060  0.359  0.483  0.359  0.633  0.110  0.483 -0.140  0.658  0.135  0.010  0.234 -0.065  0.035  0.035  0.060  0.309 -0.015  0.483  0.035  0.433  0.334  0.483  0.135  0.284  0.608  0.035  0.234  0.334  0.658  0.259  0.458  0.035  0.035 -0.140  0.159  0.359  0.608 
 0.581  0.033  0.631  0.207  0.307  0.058  0.282  0.382  0.556  0.656  0.083  0.182  0.058  0.357  0.481  0.332  0.631  0.108  0.456 -0.142  0.656  0.157  0.058  0.232 -0.092  0.033  0.033  0.083  0.332 -0.017  0.481  0.033  0.456  0.332  0.407  0.108  0.307  0.631  0.033  0.282  0.332  0.656  0.257  0.456  0.033  0.033 -0.142  0.157  0.282  0.606 
 0.485  0.037  0.660  0.211  0.311  0.012  0.236  0.236  0.535  0.610  0.087  0.012  0.037  0.361  0.411  0.286  0.660  0.062  0.386 -0.063  0.660  0.137 -0.138  0.211 -0.063  0.037  0.012 -0.038  0.236  0.037  0.460  0.037  0.336  0.261  0.435  0.037  0.211  0.535  0.012  0.161  0.311  0.685  0.211  0.460 -0.013  0.037 -0.113  0.137  0.186  0.560 
 0.278  0.079  0.602  0.203  0.278  0.054  0.129  0.278  0.502  0.652  0.004 -0.046  0.004  0.203  0.452  0.253  0.627  0.054  0.378 -0.046  0.552 -0.021 -0.121  0.153 -0.096  0.054  0.054 -0.071  0.079  0.054  0.552 -0.021  0.178  0.203  0.228 -0.046  0.129  0.452 -0.046  0.004  0.253  0.726  0.129  0.353 -0.046  0.004 -0.121  0.079  0.153  0.577 
 0.317  0.093  0.566  0.192  0.242  0.043  0.118  0.217  0.566  0.666 -0.007 -0.032 -0.032  0.192  0.466  0.192  0.616  0.043  0.367 -0.032  0.466 -0.082 -0.107  0.068 -0.082  0.068  0.018 -0.107  0.068  0.093  0.566 -0.032  0.093  0.142  0.217 -0.032  0.093  0.441 -0.032 -0.032  0.242  0.715  0.093  0.292 -0.032  0.018 -0.107  0.068  0.167  0.516 
 0.194  0.070  0.518  0.219  0.244  0.020  0.144  0.194  0.618  0.767 -0.005 -0.030 -0.030  0.144  0.468  0.144  0.568  0.020  0.369 -0.030  0.244 -0.055 -0.080  0.020 -0.080  0.020  0.045 -0.105  0.045  0.020  0.618 -0.005  0.020  0.095  0.144 -0.005  0.095  0.369 -0.055 -0.055  0.169  0.742  0.120  0.194 -0.055 -0.005 -0.080  0.045  0.120  0.493 
 0.128  0.078  0.427  0.153  0.203  0.028  0.103  0.203  0.626  0.801 -0.021 -0.021 -0.021  0.103  0.477  0.103  0.527  0.028  0.377 -0.021  0.203 -0.046 -0.071  0.028 -0.071 -0.046  0.053 -0.096  0.028  0.028  0.651  0.003 -0.021  0.103  0.103  0.003  0.103  0.302 -0.046 -0.046  0.153  0.776  0.128  0.178 -0.046  0.003 -0.071  0.053  0.128  0.477 
 0.141  0.091  0.290  0.141  0.166  0.041  0.091  0.191  0.639  0.814 -0.008 -0.008 -0.008  0.066  0.465  0.041  0.490 -0.008  0.340 -0.033  0.066 -0.033 -0.058  0.016 -0.058 -0.033  0.066 -0.083  0.016  0.016  0.664  0.016 -0.033  0.116  0.091 -0.033  0.116  0.266 -0.033 -0.033  0.166  0.789  0.116  0.066 -0.033  0.016 -0.058  0.016  0.116  0.390 
 0.070  0.095  0.194  0.144  0.169  0.045  0.070  0.194  0.618  0.817 -0.005 -0.005 -0.005  0.070  0.394  0.045  0.468 -0.005  0.319 -0.030  0.070 -0.030 -0.055  0.020 -0.055 -0.030  0.070 -0.080  0.020  0.020  0.693  0.020 -0.030  0.120  0.070 -0.030  0.120  0.269 -0.030 -0.030  0.144  0.792  0.120  0.045 -0.030  0.020 -0.055 -0.005  0.120  0.369 
 0.031  0.081  0.081  0.106  0.155  0.056  0.056  0.180  0.629  0.853  0.006  0.006  0.006  0.006  0.230  0.056  0.355 -0.044  0.255 -0.044  0.031 -0.019 -0.044  0.031 -0.044 -0.019  0.056 -0.069  0.031  0.031  0.679  0.031 -0.044  0.106  0.056 -0.044  0.106  0.205 -0.019 -0.019  0.106  0.803  0.131  0.056 -0.019  0.006 -0.019  0.006  0.081  0.255 
 0.033  0.058  0.083  0.083  0.157  0.058  0.058  0.157  0.606  0.905  0.008 -0.017  0.008  0.008  0.207  0.058  0.282 -0.042  0.232 -0.042  0.033 -0.017 -0.042  0.033 -0.067 -0.017  0.058 -0.067  0.033  0.033  0.681  0.033 -0.042  0.083  0.058 -0.042  0.083  0.157 -0.017 -0.017  0.108  0.830  0.157  0.058 -0.017  0.008 -0.017  0.008  0.083  0.207 
 0.037  0.062  0.012  0.062  0.162  0.062 -0.012  0.137  0.610  0.934  0.012  0.012  0.012 -0.012  0.112  0.037  0.212 -0.037  0.162 -0.037  0.037 -0.012 -0.037  0.062 -0.062  0.012  0.037 -0.037  0.012  0.062  0.685  0.037 -0.037  0.087  0.062 -0.062  0.087  0.112 -0.062 -0.012  0.112  0.909  0.137  0.037 -0.012 -0.012 -0.012  0.012  0.037  0.137 
 0.039  0.064  0.014  0.064  0.164  0.064 -0.035  0.114  0.563  0.961  0.014  0.014  0.014 -0.010  0.089  0.039  0.164 -0.035  0.114 -0.010 -0.010 -0.010 -0.035  0.064 -0.060  0.014  0.014 -0.035  0.014  0.064  0.687  0.039 -0.035  0.089  0.039 -0.060  0.089  0.089 -0.060 -0.010  0.114  0.936  0.114  0.039 -0.010 -0.010 -0.010  0.014  0.039  0.114 
 0.046  0.071 -0.004  0.071  0.145  0.046 -0.029  0.096  0.295  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021  0.021 -0.029  0.071 -0.004 -0.004 -0.004 -0.029  0.071 -0.054  0.021 -0.004 -0.029  0.021  0.021  0.743  0.021 -0.029  0.071  0.021 -0.054  0.096  0.046 -0.054 -0.029  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021  0.021  0.096 
 0.022  0.047 -0.028  0.047  0.122  0.047 -0.028  0.072  0.196  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.794  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.028  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022  0.022  0.097 
 0.022  0.022 -0.027  0.047  0.097  0.022 -0.027  0.072  0.147  0.969 -0.027 -0.027 -0.002 -0.027  0.022  0.022 -0.002 -0.027  0.072 -0.002 -0.002 -0.002 -0.027  0.072 -0.052  0.022 -0.002 -0.027  0.047  0.022  0.820  0.022 -0.027  0.047  0.022 -0.052  0.097  0.047 -0.052 -0.027  0.097  0.969  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.022  0.022 -0.028  0.047  0.097  0.022 -0.028  0.072  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.844  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.003  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.020  0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.004  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054  0.020  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.020  0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005 -0.005  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.066  0.066 -0.033  0.116  0.166  0.016 -0.033  0.041  0.565  0.938 -0.058 -0.008 -0.033 -0.058  0.066  0.016  0.016 -0.058  0.166 -0.008  0.041 -0.033 -0.008  0.191 -0.083  0.016 -0.033 -0.033  0.041  0.041  0.938 -0.008 -0.033  0.066 -0.008 -0.083  0.116  0.066 -0.083  0.016  0.116  0.938  0.066  0.041 -0.033  0.016 -0.033 -0.008  0.016  0.116 
 0.055  0.055 -0.020  0.179  0.329  0.005  0.030  0.229  0.802  0.877  0.055 -0.020 -0.020 -0.070  0.105  0.154  0.229 -0.045  0.229 -0.020  0.329 -0.020 -0.045  0.304 -0.095  0.005  0.030 -0.020  0.080  0.080  0.877  0.005 -0.020  0.254  0.005 -0.120  0.279  0.154 -0.120  0.080  0.179  0.877  0.204  0.130 -0.070  0.005 -0.070  0.005  0.080  0.379 
 0.062  0.062  0.087  0.286  0.336  0.087  0.062  0.262  0.785  0.835  0.162 -0.012 -0.012  0.012  0.212  0.286  0.262  0.012  0.336 -0.012  0.511 -0.062 -0.012  0.336 -0.137  0.087  0.012  0.062  0.037  0.087  0.835  0.062 -0.037  0.336  0.037 -0.037  0.336  0.286 -0.112  0.212  0.262  0.835  0.436  0.112 -0.012  0.012 -0.062  0.087  0.187  0.585 
 0.076  0.101  0.250  0.375  0.350  0.051  0.126  0.350  0.748  0.773  0.150 -0.049  0.026  0.101  0.375  0.499  0.350  0.101  0.449 -0.049  0.699 -0.049  0.051  0.425 -0.148  0.126  0.051  0.150  0.126  0.051  0.773  0.076  0.001  0.499  0.001  0.026  0.325  0.499 -0.173  0.250  0.400  0.773  0.449  0.175  0.026  0.026 -0.099  0.126  0.175  0.699 
 0.130  0.105  0.354  0.354  0.329  0.005  0.179  0.453  0.727  0.752  0.130 -0.070  0.030  0.130  0.354  0.578  0.379  0.105  0.503 -0.045  0.678 -0.070  0.154  0.528 -0.169  0.130  0.080  0.154  0.179  0.105  0.703  0.080  0.030  0.503  0.055  0.030  0.304  0.553 -0.194  0.354  0.379  0.727  0.404  0.204  0.105  0.030 -0.120  0.154  0.279  0.703 
 0.133  0.083  0.407  0.357  0.307  0.033  0.207  0.431  0.706  0.730  0.108 -0.092  0.058  0.157  0.382  0.556  0.456  0.133  0.556 -0.042  0.681 -0.042  0.133  0.556 -0.166  0.133  0.108  0.133  0.232  0.108  0.681  0.182  0.083  0.531  0.083  0.033  0.307  0.656 -0.216  0.456  0.382  0.706  0.431  0.182  0.157  0.008 -0.117  0.157  0.307  0.681 
 0.151  0.076  0.450  0.350  0.276  0.026  0.226  0.425  0.699  0.724  0.126 -0.098  0.051  0.151  0.375  0.525  0.475  0.126  0.550 -0.048  0.674 -0.048  0.126  0.574 -0.198  0.151  0.101  0.126  0.251  0.051  0.674  0.176  0.151  0.525  0.101  0.051  0.300  0.649 -0.223  0.425  0.375  0.699  0.425  0.201  0.176  0.026 -0.123  0.151  0.300  0.674 
 0.168  0.093  0.492  0.342  0.268  0.068  0.218  0.392  0.691  0.716  0.143 -0.106  0.068  0.143  0.342  0.542  0.542  0.143  0.567 -0.056  0.616 -0.056  0.118  0.567 -0.206  0.118  0.118  0.118  0.292  0.043  0.666  0.168  0.168  0.542  0.118  0.068  0.317  0.666 -0.181  0.517  0.342  0.691  0.417  0.193  0.193  0.018 -0.131  0.093  0.268  0.666 
 0.214  0.090  0.488  0.364  0.239  0.065  0.239  0.389  0.688  0.712  0.140 -0.060  0.090  0.164  0.339  0.538  0.588  0.115  0.563 -0.060  0.613 -0.060  0.115  0.563 -0.209  0.115  0.115  0.115  0.314  0.040  0.638  0.164  0.189  0.538  0.140  0.090  0.314  0.663 -0.184  0.563  0.289  0.688  0.414  0.140  0.214  0.015 -0.135  0.140  0.264  0.663 
 0.214  0.090  0.538  0.364  0.214  0.065  0.264  0.389  0.688  0.712  0.140 -0.035  0.090  0.164  0.339  0.538  0.638  0.115  0.563 -0.060  0.563 -0.035  0.090  0.513 -0.209  0.115  0.115  0.115  0.314  0.040  0.638  0.164  0.189  0.538  0.164  0.090  0.314  0.663 -0.159  0.613  0.289  0.688  0.414  0.189  0.214  0.015 -0.135  0.140  0.264  0.638 
 0.238  0.088  0.537  0.362  0.238  0.063  0.287  0.387  0.686  0.711  0.138  0.013  0.088  0.163  0.337  0.537  0.586  0.113  0.537 -0.086  0.562 -0.061  0.088  0.512 -0.211  0.113  0.113  0.113  0.337  0.038  0.636  0.138  0.188  0.537  0.163  0.138  0.312  0.661 -0.161  0.611  0.287  0.686  0.412  0.163  0.213  0.013 -0.111  0.138  0.263  0.611 
 0.236  0.087  0.535  0.311  0.261  0.062  0.286  0.386  0.685  0.710  0.161  0.012  0.087  0.137  0.336  0.535  0.560  0.112  0.535 -0.088  0.560 -0.063  0.087  0.510 -0.212  0.112  0.112  0.112  0.336  0.037  0.635  0.112  0.211  0.535  0.161  0.137  0.311  0.660 -0.162  0.610  0.286  0.685  0.411  0.161  0.211  0.062 -0.113  0.112  0.261  0.610 
 0.237  0.088  0.536  0.337  0.262  0.063  0.287  0.387  0.686  0.686  0.138  0.013  0.088  0.162  0.362  0.536  0.586  0.113  0.511 -0.087  0.561 -0.062  0.088  0.511 -0.211  0.113  0.113  0.113  0.337  0.038  0.636  0.088  0.187  0.536  0.162  0.138  0.312  0.661 -0.161  0.611  0.287  0.686  0.387  0.162  0.237  0.013 -0.112  0.113  0.262  0.636 
 0.237  0.087  0.536  0.336  0.286  0.062  0.262  0.386  0.685  0.685  0.137  0.012  0.087  0.187  0.361  0.536  0.585  0.112  0.511 -0.087  0.561 -0.062  0.137  0.511 -0.212  0.112  0.112  0.112  0.361  0.037  0.585  0.087  0.187  0.536  0.162  0.162  0.311  0.660 -0.162  0.610  0.286  0.685  0.386  0.187  0.237  0.012 -0.112  0.112  0.262  0.635 
 0.235  0.085  0.534  0.309  0.284  0.085  0.260  0.384  0.683  0.683  0.160  0.035  0.060  0.210  0.359  0.534  0.583  0.160  0.509 -0.089  0.559 -0.064  0.160  0.484 -0.214  0.110  0.110  0.110  0.359  0.035  0.583  0.085  0.185  0.534  0.160  0.185  0.309  0.658 -0.139  0.608  0.284  0.683  0.359  0.235  0.185  0.010 -0.114  0.110  0.260  0.633 
 0.233  0.083  0.532  0.307  0.307  0.083  0.283  0.382  0.681  0.681  0.158  0.033  0.033  0.258  0.357  0.532  0.606  0.158  0.507 -0.091  0.557 -0.041  0.158  0.482 -0.216  0.108  0.108  0.108  0.382  0.033  0.581  0.108  0.183  0.532  0.133  0.208  0.307  0.656 -0.116  0.606  0.307  0.681  0.357  0.283  0.183  0.008 -0.116  0.108  0.258  0.631 
 0.256  0.082  0.530  0.306  0.281  0.082  0.281  0.381  0.680  0.680  0.132  0.032  0.057  0.256  0.356  0.530  0.605  0.206  0.505 -0.093  0.555 -0.043  0.132  0.480 -0.217  0.107  0.107  0.107  0.381  0.032  0.580  0.107  0.181  0.555  0.156  0.256  0.306  0.655 -0.118  0.605  0.306  0.680  0.356  0.256  0.181  0.007 -0.118  0.107  0.256  0.605 
 0.255  0.080  0.504  0.304  0.280  0.080  0.280  0.379  0.678  0.678  0.130  0.030  0.055  0.255  0.354  0.529  0.578  0.205  0.504 -0.094  0.554 -0.044  0.130  0.454 -0.219  0.105  0.105  0.105  0.454  0.030  0.578  0.105  0.180  0.554  0.155  0.255  0.304  0.653 -0.119  0.603  0.304  0.678  0.354  0.255  0.180  0.005 -0.119  0.105  0.255  0.603 
 0.255  0.080  0.504  0.304  0.280  0.080  0.280  0.379  0.678  0.678  0.130  0.030  0.055  0.255  0.354  0.529  0.578  0.180  0.504 -0.094  0.554 -0.069  0.130  0.479 -0.219  0.105  0.105  0.105  0.454  0.030  0.578  0.105  0.180  0.554  0.155  0.255  0.304  0.653 -0.119  0.603  0.304  0.678  0.354  0.280  0.180  0.005 -0.119  0.105  0.255  0.603 
 0.254  0.080  0.503  0.304  0.279  0.080  0.279  0.379  0.678  0.678  0.130  0.030  0.080  0.254  0.354  0.528  0.578  0.179  0.503 -0.095  0.553 -0.070  0.130  0.478 -0.219  0.105  0.105  0.105  0.478  0.030  0.553  0.105  0.179  0.553  0.154  0.279  0.304  0.653 -0.120  0.603  0.304  0.678  0.379  0.279  0.179  0.005 -0.120  0.105  0.254  0.628 
 0.227  0.078  0.451  0.227  0.327  0.053  0.202  0.377  0.626  0.651  0.177 -0.047  0.053  0.202  0.352  0.451  0.551  0.177  0.476 -0.122  0.551 -0.097  0.078  0.426 -0.171  0.103  0.053  0.053  0.377  0.053  0.526  0.053  0.128  0.576  0.103  0.327  0.227  0.501 -0.146  0.426  0.352  0.701  0.327  0.252  0.128  0.028 -0.122  0.078  0.227  0.626 
 0.146  0.146  0.470  0.221  0.295  0.046  0.121  0.295  0.569  0.644  0.121 -0.028  0.021  0.171  0.395  0.470  0.445  0.046  0.445 -0.053  0.495 -0.028  0.046  0.320 -0.103  0.021  0.071  0.021  0.295  0.046  0.569  0.021  0.096  0.445  0.096  0.096  0.221  0.370 -0.103  0.395  0.295  0.744  0.295  0.146  0.096 -0.028 -0.053  0.096  0.146  0.694 
 0.111  0.136  0.410  0.235  0.310  0.036  0.111  0.260  0.559  0.684  0.111 -0.014  0.036  0.160  0.385  0.459  0.459  0.011  0.434 -0.039  0.410 -0.014  0.011  0.285 -0.089  0.036  0.086 -0.039  0.160  0.061  0.584 -0.014  0.036  0.410  0.086  0.036  0.210  0.385 -0.089  0.335  0.260  0.808  0.260  0.086  0.011  0.011 -0.039  0.136  0.160  0.659 
 0.136  0.086  0.360  0.260  0.260  0.011  0.111  0.235  0.559  0.758  0.061  0.011  0.036  0.086  0.410  0.310  0.434 -0.014  0.410 -0.064  0.410 -0.064 -0.089  0.185 -0.089  0.011  0.061 -0.039  0.061  0.086  0.609 -0.014 -0.039  0.235  0.061  0.011  0.210  0.360 -0.064  0.061  0.235  0.858  0.136  0.061 -0.039 -0.014 -0.039  0.136  0.136  0.584 
 0.143  0.068  0.367  0.268  0.218  0.018  0.093  0.243  0.567  0.766  0.043  0.018  0.018  0.093  0.417  0.243  0.467 -0.006  0.417 -0.056  0.342 -0.056 -0.081  0.193 -0.081 -0.006  0.068 -0.056  0.043  0.068  0.616 -0.006 -0.031  0.193  0.068  0.018  0.193  0.367 -0.056  0.043  0.218  0.865  0.143  0.043 -0.031 -0.006 -0.031  0.068  0.118  0.542 
 0.133  0.058  0.332  0.258  0.208  0.033  0.108  0.208  0.606  0.806  0.008  0.008 -0.016  0.058  0.332  0.158  0.432 -0.016  0.382 -0.041  0.183 -0.041 -0.066  0.083 -0.066 -0.041  0.058 -0.091  0.008  0.033  0.631  0.008 -0.041  0.158  0.083 -0.041  0.133  0.357 -0.041 -0.041  0.208  0.880  0.133  0.058 -0.041 -0.016 -0.041  0.033  0.133  0.407 
 0.112  0.062  0.286  0.262  0.212  0.037  0.112  0.187  0.635  0.810 -0.012  0.012 -0.012  0.062  0.286  0.137  0.361 -0.037  0.386 -0.037  0.137 -0.037 -0.062  0.062 -0.062 -0.037  0.062 -0.087  0.012  0.037  0.660  0.012 -0.062  0.137  0.087 -0.037  0.112  0.311 -0.037 -0.037  0.212  0.884  0.137  0.062 -0.037 -0.012 -0.037  0.012  0.112  0.386 
 0.070  0.045  0.220  0.195  0.145  0.020  0.095  0.145  0.643  0.818 -0.004  0.020 -0.004  0.020  0.220  0.070  0.344 -0.029  0.394 -0.004  0.070 -0.029 -0.054  0.070 -0.054 -0.029  0.045 -0.079 -0.004  0.070  0.693  0.045 -0.054  0.120  0.095 -0.079  0.120  0.319 -0.029 -0.029  0.170  0.942  0.120  0.070 -0.029 -0.004 -0.054 -0.004  0.095  0.294 
 0.053  0.053  0.152  0.103  0.152  0.003  0.028  0.128  0.626  0.825 -0.022  0.028  0.003  0.003  0.152  0.053  0.352 -0.047  0.352 -0.022  0.053 -0.022 -0.047  0.078 -0.047 -0.022  0.028 -0.072  0.003  0.053  0.701  0.053 -0.047  0.128  0.103 -0.072  0.128  0.252 -0.022 -0.022  0.128  0.950  0.103  0.053 -0.022  0.003 -0.047  0.003  0.078  0.202 
 0.036  0.061 -0.013  0.061  0.161  0.011 -0.013  0.111  0.634  0.908 -0.038  0.036  0.011 -0.013  0.086  0.061  0.136 -0.038  0.186 -0.013  0.011 -0.013 -0.038  0.061 -0.038 -0.013  0.011 -0.063  0.011  0.036  0.709  0.036 -0.038  0.136  0.036 -0.063  0.111  0.111 -0.063 -0.013  0.111  0.958  0.086  0.036 -0.013 -0.013 -0.013  0.011  0.061  0.111 
 0.040  0.065 -0.035  0.065  0.164  0.015 -0.010  0.090  0.563  0.912 -0.035  0.040  0.015 -0.010  0.090  0.065  0.090 -0.035  0.140 -0.010 -0.010 -0.010 -0.035  0.065 -0.060 -0.010  0.015 -0.060  0.015  0.040  0.712  0.040 -0.035  0.115  0.040 -0.060  0.090  0.090 -0.060 -0.010  0.115  0.962  0.090  0.040 -0.010 -0.010 -0.010  0.015  0.040  0.115 
 0.043  0.068 -0.032  0.068  0.167  0.043 -0.032  0.093  0.417  0.965 -0.032  0.018  0.018 -0.032  0.018  0.018 -0.007 -0.032  0.068 -0.007 -0.007 -0.007 -0.032  0.068 -0.057  0.018 -0.007 -0.032  0.018  0.043  0.765  0.043 -0.032  0.093  0.018 -0.057  0.093  0.043 -0.057 -0.007  0.118  0.965  0.093  0.043 -0.007 -0.007 -0.007  0.018  0.043  0.118 
 0.044  0.044 -0.030  0.044  0.119  0.019 -0.030  0.094  0.318  0.966 -0.030  0.019  0.019 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.030  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.044  0.792  0.044 -0.030  0.094  0.019 -0.055  0.094  0.044 -0.055 -0.005  0.119  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.119 
 0.022  0.022 -0.028  0.047  0.097  0.022 -0.028  0.072  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.844  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.003  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.021  0.021 -0.028  0.046  0.096  0.021 -0.028  0.071  0.146  0.968 -0.028 -0.028 -0.003 -0.028  0.021  0.021 -0.003 -0.028  0.071 -0.003 -0.003 -0.003 -0.028  0.071 -0.053  0.021 -0.003 -0.028  0.046  0.021  0.868  0.021 -0.028  0.046  0.021 -0.053  0.096  0.046 -0.053 -0.003  0.096  0.968  0.096  0.046 -0.003 -0.003 -0.003  0.021 -0.003  0.096 
 0.020  0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005 -0.030  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
 0.020  0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005 -0.030  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.016  0.066 -0.008  0.066  0.216  0.016 -0.008  0.066  0.315  0.938 -0.008 -0.058 -0.008 -0.033  0.016  0.041  0.016 -0.058  0.166  0.016  0.016 -0.033  0.016  0.191 -0.083  0.016  0.041 -0.008  0.091  0.041  0.938 -0.008 -0.058  0.041 -0.008 -0.083  0.166  0.066 -0.083 -0.008  0.191  0.938  0.091  0.016 -0.008  0.016 -0.033  0.041  0.016  0.241 
 0.034  0.084  0.034  0.183  0.283 -0.016  0.084  0.134  0.582  0.881  0.034 -0.066  0.084  0.034  0.158  0.333  0.084 -0.041  0.408 -0.016  0.059 -0.016  0.009  0.358 -0.116 -0.016  0.084 -0.016  0.134  0.034  0.881 -0.041 -0.066  0.109  0.009 -0.066  0.208  0.158 -0.116  0.059  0.283  0.881  0.258  0.084 -0.066 -0.041 -0.066 -0.016  0.109  0.507 
 0.078  0.103  0.153  0.203  0.253 -0.046  0.178  0.153  0.751  0.826  0.078 -0.021  0.103  0.053  0.203  0.502  0.128 -0.071  0.527 -0.021  0.278 -0.046  0.128  0.452 -0.096  0.003  0.078  0.003  0.153  0.103  0.826  0.028  0.003  0.153  0.053 -0.046  0.377  0.402 -0.121  0.078  0.327  0.826  0.327  0.053  0.078  0.028 -0.096  0.003  0.203  0.601 
 0.121  0.096  0.245  0.245  0.295 -0.054  0.170  0.245  0.718  0.768  0.071 -0.054  0.145  0.046  0.345  0.619  0.220 -0.079  0.569 -0.029  0.420 -0.054  0.145  0.494 -0.153  0.071  0.145  0.021  0.170  0.071  0.768  0.046  0.121  0.320  0.046 -0.054  0.444  0.494 -0.178  0.096  0.370  0.768  0.370  0.145  0.096  0.046 -0.153  0.046  0.320  0.743 
 0.125  0.100  0.299  0.274  0.299 -0.075  0.199  0.324  0.698  0.747  0.075 -0.075  0.125  0.075  0.349  0.623  0.299 -0.050  0.548 -0.050  0.573 -0.050  0.174  0.573 -0.174  0.050  0.125  0.050  0.149  0.100  0.747  0.075  0.149  0.399  0.025 -0.025  0.473  0.523 -0.199  0.149  0.349  0.747  0.374  0.149  0.100  0.050 -0.125  0.025  0.399  0.722 
 0.155  0.106  0.405  0.280  0.280 -0.069  0.180  0.380  0.704  0.728  0.081 -0.069  0.155  0.131  0.380  0.629  0.330 -0.044  0.529 -0.069  0.654 -0.069  0.205  0.554 -0.193  0.081  0.081  0.081  0.155  0.106  0.679  0.081  0.230  0.454  0.006 -0.019  0.454  0.679 -0.218  0.180  0.330  0.728  0.380  0.131  0.180  0.056 -0.119  0.081  0.380  0.704 
 0.199  0.125  0.448  0.274  0.249 -0.050  0.174  0.374  0.698  0.698  0.100 -0.075  0.199  0.149  0.374  0.623  0.374  0.000  0.523 -0.075  0.648 -0.075  0.199  0.573 -0.199  0.075  0.075  0.050  0.149  0.100  0.673  0.100  0.324  0.448  0.050 -0.025  0.448  0.673 -0.224  0.199  0.324  0.698  0.349  0.125  0.199  0.075 -0.125  0.075  0.349  0.698 
 0.221  0.121  0.520  0.246  0.246 -0.078  0.196  0.370  0.694  0.669  0.121 -0.053  0.196  0.196  0.370  0.619  0.395 -0.003  0.545 -0.078  0.619 -0.078  0.221  0.569 -0.178  0.021  0.046 -0.003  0.171  0.096  0.644  0.096  0.320  0.445  0.096 -0.028  0.395  0.669 -0.178  0.271  0.271  0.694  0.345  0.121  0.196  0.096 -0.128  0.121  0.370  0.669 
 0.239  0.090  0.563  0.239  0.239 -0.060  0.189  0.339  0.688  0.663  0.140 -0.035  0.189  0.189  0.389  0.613  0.414  0.015  0.563 -0.060  0.588 -0.060  0.214  0.563 -0.184  0.015  0.065 -0.010  0.164  0.090  0.663  0.115  0.389  0.463  0.164 -0.035  0.389  0.663 -0.159  0.289  0.289  0.688  0.339  0.115  0.189  0.090 -0.135  0.140  0.364  0.663 
 0.241  0.066  0.589  0.241  0.216 -0.058  0.191  0.340  0.689  0.664  0.166 -0.008  0.166  0.216  0.415  0.614  0.440  0.041  0.565 -0.058  0.589 -0.033  0.241  0.565 -0.183  0.041  0.066 -0.008  0.191  0.091  0.639  0.116  0.390  0.465  0.216 -0.058  0.340  0.664 -0.133  0.266  0.266  0.689  0.340  0.141  0.191  0.091 -0.133  0.141  0.365  0.639 
 0.242  0.067  0.590  0.242  0.192 -0.057  0.192  0.341  0.665  0.665  0.167  0.017  0.167  0.217  0.416  0.615  0.466  0.042  0.541 -0.082  0.590 -0.032  0.242  0.541 -0.207  0.017  0.067 -0.032  0.192  0.067  0.640  0.142  0.416  0.466  0.242 -0.057  0.341  0.665 -0.107  0.242  0.267  0.690  0.341  0.117  0.192  0.117 -0.132  0.142  0.366  0.640 
 0.239  0.064  0.587  0.239  0.164 -0.035  0.189  0.338  0.662  0.662  0.189  0.089  0.164  0.239  0.463  0.587  0.538  0.064  0.513 -0.085  0.587 -0.035  0.239  0.513 -0.210  0.014  0.039 -0.035  0.189  0.014  0.587  0.139  0.438  0.463  0.264 -0.060  0.338  0.662 -0.110  0.239  0.239  0.687  0.363  0.164  0.164  0.089 -0.135  0.164  0.363  0.637 
 0.238  0.063  0.586  0.238  0.163 -0.011  0.188  0.387  0.661  0.661  0.188  0.113  0.163  0.238  0.462  0.586  0.562  0.063  0.487 -0.086  0.586 -0.036  0.238  0.512 -0.211  0.013  0.013 -0.011  0.188  0.013  0.586  0.138  0.412  0.462  0.263 -0.061  0.312  0.661 -0.111  0.287  0.238  0.686  0.362  0.163  0.163  0.088 -0.161  0.163  0.362  0.636 
 0.233  0.084  0.582  0.233  0.158  0.034  0.183  0.432  0.657  0.632  0.183  0.134  0.158  0.258  0.457  0.582  0.582  0.084  0.482 -0.116  0.582 -0.041  0.233  0.507 -0.215  0.009  0.009 -0.016  0.233  0.009  0.582  0.109  0.408  0.457  0.258 -0.041  0.308  0.657 -0.091  0.333  0.233  0.657  0.358  0.208  0.158  0.084 -0.190  0.158  0.358  0.632 
 0.233  0.108  0.581  0.233  0.158  0.033  0.183  0.457  0.656  0.631  0.233  0.133  0.183  0.258  0.457  0.581  0.581  0.083  0.482 -0.116  0.631 -0.041  0.208  0.507 -0.216  0.008  0.008  0.008  0.233  0.008  0.581  0.133  0.407  0.457  0.258 -0.041  0.307  0.656 -0.091  0.357  0.233  0.681  0.357  0.208  0.158  0.158 -0.191  0.158  0.357  0.631 
 0.227  0.128  0.626  0.252  0.152  0.028  0.177  0.451  0.626  0.626  0.252  0.177  0.177  0.277  0.451  0.576  0.576  0.078  0.476 -0.097  0.626 -0.047  0.202  0.501 -0.221  0.003  0.003  0.003  0.252  0.028  0.576  0.152  0.426  0.451  0.252 -0.022  0.302  0.651 -0.072  0.426  0.227  0.676  0.352  0.202  0.152  0.227 -0.196  0.177  0.352  0.626 
 0.225  0.150  0.624  0.225  0.150  0.026  0.150  0.449  0.599  0.649  0.250  0.200  0.175  0.250  0.449  0.524  0.574  0.076  0.474 -0.124  0.624 -0.074  0.200  0.499 -0.223  0.001  0.001  0.001  0.250  0.051  0.574  0.150  0.425  0.425  0.250 -0.024  0.300  0.649 -0.074  0.449  0.225  0.649  0.350  0.225  0.150  0.225 -0.173  0.150  0.325  0.649 
 0.225  0.150  0.623  0.225  0.150  0.050  0.175  0.449  0.598  0.673  0.250  0.225  0.175  0.250  0.449  0.524  0.573  0.100  0.474 -0.124  0.623 -0.074  0.175  0.449 -0.224  0.050  0.000  0.025  0.275  0.050  0.549  0.150  0.424  0.424  0.250  0.000  0.299  0.648 -0.074  0.499  0.225  0.648  0.349  0.225  0.150  0.250 -0.174  0.125  0.299  0.623 
 0.226  0.151  0.624  0.226  0.151  0.051  0.201  0.450  0.599  0.649  0.251  0.276  0.151  0.251  0.450  0.525  0.574  0.126  0.450 -0.123  0.624 -0.073  0.176  0.450 -0.223  0.076  0.001  0.026  0.276  0.051  0.500  0.126  0.425  0.425  0.251  0.001  0.300  0.649 -0.073  0.500  0.226  0.649  0.350  0.226  0.151  0.251 -0.198  0.126  0.300  0.599 
 0.227  0.152  0.626  0.227  0.152  0.053  0.202  0.451  0.601  0.651  0.252  0.277  0.152  0.252  0.451  0.526  0.576  0.128  0.451 -0.122  0.626 -0.072  0.152  0.426 -0.221  0.103  0.003  0.053  0.327  0.053  0.476  0.128  0.426  0.377  0.252  0.028  0.302  0.651 -0.072  0.476  0.227  0.651  0.352  0.252  0.128  0.252 -0.196  0.128  0.302  0.601 
 0.231  0.181  0.505  0.206  0.206  0.032  0.181  0.430  0.530  0.630  0.231  0.181  0.107  0.156  0.455  0.455  0.605  0.132  0.381 -0.093  0.680 -0.018  0.107  0.356 -0.167  0.057  0.032 -0.018  0.356  0.057  0.530  0.132  0.381  0.356  0.256  0.057  0.306  0.555 -0.118  0.331  0.256  0.655  0.281  0.156  0.156  0.181 -0.142  0.156  0.156  0.580 
 0.169  0.194  0.468  0.219  0.269  0.069  0.119  0.368  0.518  0.667  0.194  0.044  0.044  0.144  0.468  0.368  0.543  0.069  0.393 -0.080  0.568 -0.055 -0.105  0.219 -0.105  0.069  0.044 -0.030  0.293 -0.005  0.568  0.069  0.244  0.244  0.144 -0.005  0.194  0.418 -0.105  0.244  0.293  0.742  0.219  0.119  0.069  0.044 -0.080  0.169  0.144  0.543 
 0.187  0.162  0.461  0.237  0.287  0.063  0.138  0.337  0.536  0.686  0.162  0.013  0.038  0.138  0.436  0.362  0.461 -0.012  0.412 -0.062  0.561 -0.037 -0.087  0.187 -0.087  0.063  0.063 -0.012  0.212  0.013  0.561  0.063  0.187  0.187  0.138 -0.012  0.187  0.412 -0.087  0.138  0.287  0.735  0.212  0.038  0.063  0.013 -0.062  0.113  0.113  0.511 
 0.165  0.091  0.464  0.265  0.215  0.016  0.116  0.290  0.539  0.713  0.041 -0.034  0.041  0.165  0.439  0.315  0.439 -0.034  0.415 -0.034  0.390 -0.059 -0.084  0.091 -0.084 -0.009  0.066 -0.084  0.141  0.016  0.614 -0.009  0.016  0.066  0.116  0.016  0.141  0.390 -0.059  0.041  0.265  0.763  0.165  0.066 -0.009 -0.009 -0.059  0.066  0.116  0.489 
 0.174  0.100  0.424  0.274  0.199  0.025  0.125  0.274  0.548  0.747  0.000 -0.025  0.025  0.125  0.448  0.299  0.448 -0.025  0.424 -0.025  0.199 -0.050 -0.075  0.050 -0.075 -0.025  0.050 -0.075  0.075  0.000  0.623  0.000 -0.025  0.075  0.125  0.025  0.149  0.374 -0.050  0.025  0.249  0.772  0.149  0.075 -0.025  0.000 -0.050  0.025  0.125  0.448 
 0.160  0.086  0.335  0.285  0.185  0.036  0.111  0.210  0.509  0.808 -0.014 -0.064  0.011  0.111  0.410  0.210  0.459 -0.039  0.385 -0.039  0.136 -0.039 -0.064  0.036 -0.064 -0.014  0.061 -0.089  0.011 -0.014  0.659 -0.014 -0.039  0.036  0.086 -0.014  0.111  0.385 -0.039 -0.064  0.185  0.783  0.136  0.061 -0.039  0.011 -0.039  0.036  0.136  0.434 
 0.092  0.092  0.316  0.216  0.166  0.042  0.117  0.191  0.465  0.814 -0.008 -0.058 -0.008  0.067  0.341  0.166  0.440 -0.033  0.391 -0.033  0.067 -0.033 -0.058  0.067 -0.058 -0.008  0.067 -0.083  0.017 -0.008  0.690 -0.008 -0.033  0.042  0.092 -0.033  0.117  0.391 -0.033 -0.058  0.166  0.814  0.142  0.067 -0.033  0.017 -0.058  0.017  0.117  0.391 
 0.076  0.076  0.201  0.176  0.151  0.001  0.126  0.151  0.350  0.824 -0.023 -0.073  0.001 -0.023  0.251  0.076  0.400 -0.023  0.375 -0.023  0.051 -0.023 -0.048  0.076 -0.048 -0.023  0.051 -0.073  0.001  0.026  0.699  0.001 -0.048  0.051  0.076 -0.073  0.126  0.325 -0.023 -0.048  0.176  0.898  0.101  0.051 -0.023  0.001 -0.048  0.001  0.076  0.325 
 0.058  0.033  0.133  0.133  0.108  0.008  0.033  0.083  0.258  0.831 -0.016 -0.066  0.008 -0.016  0.208  0.083  0.307 -0.041  0.382 -0.041  0.033 -0.016 -0.041  0.083 -0.041 -0.016  0.033 -0.066  0.008  0.033  0.731  0.008 -0.041  0.033  0.083 -0.066  0.108  0.283 -0.016 -0.041  0.183  0.905  0.108  0.058 -0.016  0.008 -0.041  0.008  0.033  0.307 
 0.016  0.016  0.066  0.041  0.091 -0.009  0.016  0.091  0.190  0.888 -0.034 -0.059  0.016 -0.034  0.091  0.041  0.215 -0.034  0.315 -0.009  0.041 -0.009 -0.034  0.066 -0.034 -0.009  0.041 -0.059  0.016  0.016  0.738  0.041 -0.034  0.041  0.066 -0.059  0.116  0.215 -0.009 -0.034  0.165  0.938  0.091  0.066 -0.009 -0.009 -0.034  0.016  0.016  0.265 
 0.021  0.021 -0.003  0.046  0.096  0.021 -0.003  0.071  0.146  0.918 -0.028 -0.053 -0.003 -0.028  0.096  0.046  0.096 -0.028  0.221 -0.003  0.021 -0.003 -0.028  0.071 -0.028  0.021  0.021 -0.028  0.021  0.021  0.744  0.021 -0.028  0.021  0.046 -0.053  0.121  0.146 -0.028 -0.028  0.096  0.943  0.096  0.046 -0.003 -0.003 -0.028  0.021 -0.003  0.121 
 0.023  0.023 -0.027  0.048  0.098  0.023 -0.027  0.073  0.147  0.970 -0.027 -0.027 -0.002 -0.027  0.023  0.023 -0.002 -0.027  0.073 -0.002 -0.002 -0.002 -0.027  0.073 -0.052  0.023 -0.002 -0.027  0.048  0.023  0.795  0.023 -0.027  0.048  0.023 -0.052  0.098  0.048 -0.052 -0.027  0.098  0.970  0.098  0.048 -0.002 -0.002 -0.002  0.023 -0.002  0.098 
 0.022  0.022 -0.028  0.047  0.097  0.022 -0.028  0.072  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.844  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.003  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
 0.021  0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004 -0.004  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054 -0.004  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
 0.020  0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.004  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054 -0.004  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.060  0.010 -0.014  0.060  0.210  0.035 -0.039  0.135  0.260  0.932  0.035 -0.064  0.010 -0.039  0.060  0.085  0.010  0.010  0.185 -0.039 -0.014 -0.039 -0.039  0.160 -0.064 -0.014  0.085  0.010  0.135  0.010  0.932 -0.014 -0.064  0.060  0.035 -0.064  0.185  0.210 -0.089 -0.014  0.210  0.932  0.185  0.035 -0.039  0.035  0.010  0.035  0.010  0.135 
 0.025  0.000  0.125  0.150  0.225  0.025 -0.049  0.275  0.598  0.872  0.050 -0.074  0.000  0.000  0.175  0.200  0.225 -0.024  0.424 -0.024  0.125  0.000 -0.024  0.250 -0.099 -0.049  0.075  0.000  0.250  0.000  0.872  0.000  0.000  0.125  0.075 -0.074  0.275  0.349 -0.099 -0.024  0.349  0.872  0.299  0.100 -0.024  0.025 -0.024  0.050  0.000  0.349 
 0.175  0.050  0.250  0.175  0.324  0.050 -0.049  0.299  0.648  0.823  0.125 -0.024  0.000  0.000  0.299  0.424  0.299 -0.024  0.499  0.000  0.349 -0.024 -0.024  0.299 -0.149 -0.024  0.075 -0.024  0.275  0.000  0.823  0.075  0.025  0.299  0.100  0.000  0.324  0.399 -0.124  0.000  0.324  0.823  0.349  0.100  0.075  0.050 -0.074  0.150  0.100  0.524 
 0.170  0.096  0.420  0.320  0.320  0.021  0.046  0.345  0.694  0.768  0.145 -0.029  0.046  0.071  0.420  0.544  0.469  0.021  0.594 -0.029  0.494 -0.054 -0.029  0.370 -0.203  0.071  0.121 -0.004  0.220 -0.004  0.768  0.096  0.046  0.370  0.071  0.021  0.370  0.594 -0.153  0.071  0.395  0.743  0.469  0.121  0.121  0.046 -0.079  0.170  0.245  0.694 
 0.225  0.100  0.524  0.299  0.299  0.050  0.075  0.349  0.673  0.748  0.175  0.000  0.075  0.075  0.399  0.573  0.573  0.075  0.573 -0.049  0.573 -0.074 -0.024  0.374 -0.199  0.075  0.100  0.050  0.175  0.000  0.748  0.100  0.225  0.399  0.100  0.000  0.324  0.723 -0.174  0.150  0.349  0.723  0.449  0.125  0.125  0.075 -0.099  0.175  0.275  0.673 
 0.233  0.084  0.532  0.333  0.308  0.059  0.109  0.358  0.707  0.731  0.158 -0.016  0.109  0.134  0.408  0.607  0.632  0.109  0.532 -0.066  0.607 -0.041 -0.066  0.408 -0.215  0.109  0.109  0.109  0.208  0.034  0.657  0.109  0.233  0.482  0.134  0.059  0.308  0.707 -0.190  0.233  0.333  0.707  0.432  0.183  0.158  0.059 -0.091  0.183  0.308  0.657 
 0.274  0.100  0.548  0.299  0.274  0.050  0.100  0.349  0.698  0.698  0.149  0.075  0.100  0.125  0.424  0.648  0.648  0.125  0.548 -0.075  0.598 -0.025 -0.025  0.424 -0.224  0.100  0.100  0.125  0.274  0.050  0.648  0.100  0.274  0.473  0.174  0.025  0.299  0.698 -0.174  0.299  0.324  0.698  0.399  0.249  0.174  0.050 -0.125  0.199  0.324  0.648 
 0.261  0.087  0.560  0.286  0.261  0.062  0.137  0.336  0.685  0.685  0.137  0.087  0.112  0.137  0.411  0.635  0.635  0.137  0.535 -0.088  0.585 -0.038  0.012  0.411 -0.212  0.137  0.087  0.112  0.261  0.037  0.635  0.137  0.361  0.485  0.211  0.037  0.286  0.660 -0.113  0.386  0.361  0.685  0.386  0.336  0.161  0.037 -0.138  0.186  0.336  0.635 
 0.210  0.085  0.583  0.284  0.284  0.060  0.135  0.359  0.683  0.683  0.135  0.110  0.110  0.135  0.409  0.633  0.633  0.135  0.534 -0.089  0.583 -0.039  0.010  0.384 -0.214  0.135  0.085  0.110  0.260  0.035  0.559  0.135  0.384  0.509  0.235  0.085  0.284  0.658 -0.114  0.384  0.359  0.683  0.384  0.309  0.135  0.010 -0.114  0.185  0.309  0.658 
 0.205  0.081  0.579  0.280  0.280  0.056  0.205  0.429  0.679  0.679  0.131  0.155  0.106  0.131  0.405  0.579  0.629  0.131  0.529 -0.094  0.579 -0.019  0.081  0.355 -0.218  0.155  0.081  0.106  0.305  0.006  0.529  0.155  0.380  0.529  0.255  0.131  0.305  0.654 -0.143  0.454  0.355  0.679  0.380  0.305  0.131  0.006 -0.119  0.180  0.305  0.654 
 0.178  0.078  0.576  0.278  0.278  0.078  0.203  0.427  0.676  0.676  0.128  0.153  0.103  0.128  0.402  0.576  0.626  0.153  0.502 -0.096  0.576 -0.021  0.078  0.352 -0.221  0.153  0.103  0.103  0.302  0.028  0.502  0.128  0.377  0.527  0.253  0.128  0.302  0.651 -0.146  0.502  0.352  0.676  0.377  0.302  0.128  0.003 -0.121  0.178  0.302  0.651 
 0.178  0.079  0.577  0.228  0.278  0.079  0.228  0.427  0.677  0.677  0.129  0.203  0.129  0.079  0.403  0.552  0.627  0.178  0.502 -0.096  0.577 -0.021  0.129  0.328 -0.220  0.228  0.054  0.079  0.303  0.029  0.502  0.104  0.378  0.527  0.253  0.129  0.303  0.652 -0.145  0.527  0.353  0.677  0.378  0.278  0.104  0.029 -0.121  0.153  0.278  0.627 
 0.205  0.081  0.579  0.230  0.280  0.081  0.230  0.429  0.679  0.679  0.131  0.205  0.131  0.081  0.380  0.554  0.629  0.180  0.504 -0.094  0.579 -0.019  0.131  0.305 -0.218  0.230  0.056  0.081  0.305  0.006  0.504  0.081  0.380  0.529  0.255  0.131  0.305  0.654 -0.143  0.554  0.355  0.679  0.380  0.280  0.106  0.031 -0.119  0.155  0.255  0.629 
 0.204  0.079  0.577  0.204  0.279  0.079  0.279  0.453  0.677  0.677  0.129  0.179  0.129  0.079  0.378  0.553  0.602  0.179  0.503 -0.120  0.553  0.029  0.129  0.303 -0.195  0.303  0.054  0.079  0.353  0.004  0.503  0.029  0.403  0.528  0.254  0.129  0.303  0.652 -0.120  0.553  0.353  0.652  0.378  0.328  0.104  0.054 -0.120  0.129  0.229  0.627 
 0.176  0.101  0.574  0.201  0.276  0.076  0.325  0.475  0.674  0.674  0.126  0.176  0.126  0.076  0.375  0.525  0.599  0.176  0.500 -0.123  0.550  0.051  0.151  0.276 -0.198  0.400  0.051  0.076  0.350  0.001  0.525  0.001  0.400  0.525  0.251  0.126  0.300  0.649 -0.123  0.550  0.350  0.649  0.375  0.325  0.076  0.076 -0.123  0.126  0.226  0.624 
 0.151  0.102  0.600  0.176  0.276  0.077  0.326  0.475  0.675  0.675  0.151  0.176  0.102  0.077  0.376  0.525  0.625  0.176  0.500 -0.123  0.550  0.077  0.151  0.276 -0.197  0.401  0.052  0.077  0.351  0.002  0.525  0.002  0.401  0.525  0.251  0.102  0.301  0.650 -0.098  0.550  0.326  0.650  0.376  0.401  0.077  0.127 -0.123  0.127  0.226  0.625 
 0.150  0.125  0.598  0.175  0.275  0.075  0.324  0.474  0.673  0.673  0.175  0.175  0.075  0.075  0.374  0.499  0.623  0.175  0.499 -0.124  0.573  0.075  0.200  0.275 -0.199  0.399  0.050  0.075  0.349  0.000  0.549  0.000  0.399  0.524  0.250  0.100  0.324  0.648 -0.074  0.549  0.324  0.648  0.349  0.374  0.100  0.150 -0.124  0.100  0.225  0.623 
 0.150  0.125  0.598  0.175  0.225  0.075  0.324  0.474  0.673  0.673  0.200  0.175  0.100  0.075  0.399  0.499  0.598  0.175  0.399 -0.124  0.598  0.075  0.200  0.275 -0.199  0.399  0.025  0.075  0.349  0.025  0.524  0.000  0.399  0.524  0.250  0.100  0.324  0.648 -0.074  0.549  0.324  0.648  0.349  0.399  0.125  0.200 -0.149  0.100  0.250  0.623 
 0.172  0.098  0.621  0.172  0.197  0.073  0.322  0.471  0.671  0.671  0.222  0.172  0.098  0.073  0.422  0.496  0.596  0.172  0.422 -0.127  0.621  0.073  0.197  0.272 -0.201  0.397  0.023  0.073  0.347  0.023  0.521 -0.002  0.422  0.521  0.247  0.073  0.322  0.646 -0.102  0.571  0.322  0.621  0.347  0.397  0.123  0.222 -0.176  0.098  0.247  0.621 
 0.173  0.098  0.621  0.173  0.148  0.073  0.322  0.472  0.671  0.671  0.223  0.173  0.098  0.073  0.422  0.497  0.596  0.173  0.422 -0.126  0.621  0.073  0.223  0.273 -0.201  0.397  0.023  0.073  0.347  0.023  0.522 -0.001  0.422  0.497  0.248  0.073  0.322  0.646 -0.101  0.571  0.322  0.621  0.347  0.397  0.123  0.248 -0.176  0.098  0.248  0.621 
 0.181  0.106  0.579  0.181  0.231  0.031  0.231  0.355  0.629  0.654  0.131  0.106  0.106  0.081  0.380  0.505  0.555  0.206  0.380 -0.118  0.679  0.031 -0.043  0.206 -0.193  0.256  0.056  0.056  0.330  0.056  0.530 -0.018  0.305  0.455  0.206 -0.018  0.305  0.530 -0.043  0.505  0.330  0.629  0.231  0.330  0.106  0.231 -0.168  0.081  0.256  0.654 
 0.170  0.170  0.519  0.170  0.220  0.045  0.095  0.319  0.544  0.693  0.145 -0.004  0.020  0.095  0.419  0.469  0.494  0.145  0.394 -0.029  0.544 -0.029 -0.079  0.095 -0.129  0.195  0.020 -0.004  0.270  0.045  0.593 -0.004  0.120  0.444  0.145 -0.004  0.195  0.494 -0.054  0.369  0.344  0.593  0.170  0.195  0.095  0.095 -0.079  0.070  0.195  0.618 
 0.192  0.142  0.491  0.217  0.242  0.042  0.142  0.316  0.541  0.690  0.117 -0.032  0.017  0.067  0.441  0.341  0.441  0.092  0.391 -0.007  0.516 -0.082 -0.107 -0.007 -0.107  0.067 -0.007 -0.057  0.217  0.042  0.615 -0.007  0.092  0.366  0.067 -0.007  0.142  0.491 -0.057  0.242  0.316  0.590  0.117  0.142  0.067  0.067 -0.057  0.092  0.142  0.665 
 0.165  0.115  0.414  0.265  0.215  0.015  0.140  0.289  0.464  0.713  0.040 -0.009  0.015  0.090  0.414  0.339  0.464  0.015  0.414 -0.009  0.464 -0.059 -0.084 -0.009 -0.084  0.040  0.015 -0.059  0.090  0.040  0.613  0.015 -0.034  0.215  0.090 -0.009  0.090  0.414 -0.059  0.065  0.314  0.588  0.090  0.090 -0.009 -0.009 -0.059  0.065  0.165  0.713 
 0.099  0.124  0.348  0.274  0.199  0.024  0.124  0.274  0.473  0.722  0.049 -0.025 -0.000  0.099  0.423  0.274  0.448  0.024  0.398 -0.000  0.323 -0.050 -0.075 -0.000 -0.075 -0.000  0.024 -0.075  0.074  0.024  0.622 -0.000 -0.050  0.199  0.099 -0.025  0.074  0.423 -0.050 -0.025  0.298  0.548  0.099  0.074 -0.000 -0.000 -0.050  0.024  0.149  0.722 
 0.090  0.090  0.264  0.289  0.189  0.040  0.115  0.214  0.488  0.812 -0.010 -0.010 -0.010  0.090  0.364  0.164  0.438 -0.035  0.414 -0.010  0.140 -0.035 -0.060  0.015 -0.060 -0.010  0.040 -0.085  0.065 -0.010  0.638  0.015 -0.060  0.090  0.090 -0.010  0.090  0.364 -0.035 -0.035  0.214  0.588  0.090  0.015 -0.010 -0.010 -0.035 -0.010  0.140  0.663 
 0.093  0.068  0.168  0.243  0.193  0.018  0.043  0.168  0.567  0.816 -0.031 -0.006 -0.006  0.093  0.367  0.093  0.367 -0.056  0.367 -0.031  0.143 -0.056 -0.056 -0.006 -0.056 -0.031  0.043 -0.081  0.043  0.018  0.666  0.018 -0.056  0.093  0.068 -0.031  0.093  0.317 -0.031 -0.031  0.218  0.616  0.093  0.018 -0.031 -0.006 -0.056 -0.006  0.143  0.666 
 0.052  0.077  0.077  0.176  0.151  0.002  0.052  0.127  0.525  0.824 -0.048 -0.023  0.002  0.077  0.351  0.077  0.326 -0.073  0.301 -0.023  0.052 -0.048 -0.048  0.027 -0.048 -0.023  0.052 -0.073  0.027  0.027  0.675  0.027 -0.048  0.077  0.027 -0.048  0.102  0.251 -0.023 -0.023  0.201  0.650  0.127  0.002 -0.023 -0.023 -0.048 -0.023  0.077  0.650 
 0.030  0.080  0.080  0.105  0.154  0.005  0.055  0.130  0.478  0.877 -0.045 -0.020  0.005  0.055  0.304  0.080  0.304 -0.045  0.279 -0.020  0.055 -0.045 -0.045  0.030 -0.070 -0.020  0.055 -0.070  0.030  0.030  0.678  0.030 -0.045  0.080  0.055 -0.045  0.080  0.179 -0.020 -0.020  0.154  0.703  0.154  0.005 -0.020 -0.020 -0.020 -0.020  0.080  0.603 
 0.039  0.089  0.014  0.089  0.139  0.014  0.039  0.114  0.338  0.936 -0.061 -0.061  0.014  0.039  0.238  0.089  0.188 -0.036  0.213 -0.036  0.039 -0.036 -0.036  0.039 -0.061 -0.036  0.039 -0.061  0.014 -0.011  0.711  0.014 -0.036  0.064  0.064 -0.061  0.089  0.139 -0.061 -0.036  0.163  0.736  0.139 -0.036 -0.011 -0.011 -0.011  0.014 -0.011  0.462 
 0.020  0.045 -0.029  0.070  0.095 -0.004 -0.004  0.095  0.220  0.942 -0.054 -0.054  0.020  0.020  0.170  0.095  0.095 -0.029  0.170 -0.029  0.045 -0.029 -0.029  0.045 -0.054 -0.029 -0.004 -0.054  0.020 -0.004  0.668  0.020 -0.029  0.045  0.020 -0.054  0.095  0.095 -0.054 -0.029  0.170  0.743  0.120 -0.029 -0.004 -0.004 -0.004  0.020 -0.029  0.369 
 0.027  0.027 -0.023  0.052  0.102  0.027  0.002  0.052  0.176  0.974 -0.048 -0.048  0.027 -0.023  0.077  0.052  0.002 -0.023  0.102  0.002  0.002 -0.023 -0.023  0.077 -0.048  0.027  0.002 -0.023  0.027  0.002  0.625  0.027 -0.023  0.027  0.027 -0.048  0.102  0.027 -0.048 -0.023  0.127  0.849  0.102  0.002  0.002  0.002  0.002  0.027 -0.023  0.176 
 0.025  0.025 -0.024  0.050  0.100  0.025  0.000  0.050  0.150  0.972 -0.024 -0.024  0.000 -0.024  0.025  0.025  0.000 -0.024  0.075  0.000  0.000  0.000 -0.024  0.075 -0.049  0.025  0.000 -0.024  0.025  0.025  0.673  0.025 -0.024  0.050  0.025 -0.049  0.100  0.025 -0.049 -0.024  0.100  0.947  0.100  0.025  0.000  0.000  0.000  0.025 -0.024  0.125 
 0.025  0.025 -0.024  0.050  0.100  0.025 -0.024  0.050  0.150  0.972 -0.024 -0.024  0.000 -0.024  0.025  0.025  0.000 -0.024  0.075  0.000  0.000  0.000 -0.024  0.075 -0.049  0.025  0.000 -0.024  0.025  0.025  0.673  0.025 -0.024  0.050  0.025 -0.049  0.100  0.025 -0.049 -0.024  0.100  0.972  0.100  0.025  0.000  0.000  0.000  0.025 -0.024  0.100 
 0.025  0.025 -0.024  0.050  0.100  0.025 -0.024  0.050  0.150  0.972 -0.024 -0.024  0.000 -0.024  0.025  0.025  0.000 -0.024  0.075  0.000  0.000  0.000 -0.024  0.075 -0.049  0.025  0.000 -0.024  0.025  0.025  0.673  0.025 -0.024  0.050  0.025 -0.049  0.100  0.025 -0.049 -0.024  0.100  0.972  0.100  0.025  0.000  0.000  0.000  0.025 -0.024  0.100 
 0.026  0.026 -0.024  0.051  0.101  0.026 -0.024  0.051  0.150  0.973 -0.024 -0.024  0.001 -0.024  0.026  0.026  0.001 -0.024  0.076  0.001  0.001  0.001 -0.024  0.076 -0.049  0.026  0.001 -0.024  0.026  0.026  0.649  0.026 -0.024  0.051  0.026 -0.049  0.101  0.026 -0.049 -0.024  0.101  0.973  0.101  0.026  0.001  0.001  0.001  0.026 -0.024  0.101 
 0.026  0.026 -0.024  0.051  0.101  0.026 -0.024  0.051  0.150  0.973 -0.024 -0.024  0.001 -0.024  0.026  0.026  0.001 -0.024  0.076  0.001  0.001  0.001 -0.024  0.076 -0.049  0.026  0.001 -0.024  0.026  0.026  0.649  0.026 -0.024  0.051  0.026 -0.049  0.101  0.026 -0.049 -0.024  0.101  0.973  0.101  0.026  0.001  0.001  0.001  0.026 -0.024  0.101 
 0.026  0.026 -0.024  0.051  0.101  0.026 -0.024  0.051  0.150  0.973 -0.024 -0.024  0.001 -0.024  0.026  0.026  0.001 -0.024  0.076  0.001  0.001  0.001 -0.024  0.076 -0.049  0.026  0.001 -0.024  0.026  0.026  0.649  0.026 -0.024  0.051  0.026 -0.049  0.101  0.026 -0.049 -0.024  0.101  0.973  0.101  0.026  0.001  0.001  0.001  0.026 -0.024  0.101 
 0.025  0.025 -0.024  0.050  0.100  0.025 -0.024  0.075  0.150  0.972 -0.024 -0.024  0.000 -0.024  0.025  0.025  0.000 -0.024  0.075  0.000  0.000  0.000 -0.024  0.075 -0.049  0.025  0.000 -0.024  0.025  0.025  0.673  0.025 -0.024  0.050  0.025 -0.049  0.100  0.025 -0.049 -0.024  0.100  0.972  0.100  0.025  0.000  0.000  0.000  0.025 -0.024  0.100 
 0.024  0.024 -0.025  0.049  0.099  0.024 -0.025  0.074  0.149  0.971 -0.025 -0.025 -0.000 -0.025  0.024  0.024 -0.000 -0.025  0.074 -0.000 -0.000 -0.000 -0.025  0.074 -0.050  0.024 -0.000 -0.025  0.024  0.024  0.722  0.024 -0.025  0.049  0.024 -0.050  0.099  0.024 -0.050 -0.025  0.099  0.971  0.099  0.024 -0.000 -0.000 -0.000  0.024 -0.025  0.099 
 0.021 -0.003 -0.028  0.146  0.146 -0.003 -0.028  0.121  0.221  0.943 -0.028 -0.053  0.046 -0.053  0.046  0.071 -0.003 -0.028  0.246 -0.028  0.021 -0.028 -0.028  0.121 -0.053 -0.003 -0.028 -0.053  0.021  0.021  0.868 -0.003 -0.003  0.071  0.046 -0.078  0.146  0.071 -0.078 -0.003  0.196  0.943  0.096  0.021 -0.028 -0.003 -0.003 -0.003 -0.028  0.121 
 0.053  0.003  0.128  0.252  0.302  0.053  0.053  0.152  0.526  0.875  0.028 -0.072  0.103  0.053  0.177  0.277  0.152  0.078  0.327 -0.022  0.152 -0.072 -0.022  0.252 -0.122 -0.022  0.103 -0.047 -0.022  0.003  0.875 -0.022 -0.047  0.152  0.078 -0.072  0.377  0.426 -0.097 -0.022  0.302  0.875  0.227  0.103 -0.072 -0.047 -0.072 -0.047  0.128  0.426 
 0.087  0.037  0.161  0.286  0.336  0.112  0.087  0.137  0.660  0.834  0.037 -0.063  0.087  0.062  0.211  0.485  0.386  0.037  0.435 -0.013  0.311 -0.088 -0.013  0.286 -0.113  0.112  0.137  0.062 -0.013  0.037  0.834 -0.013  0.062  0.186  0.062 -0.063  0.460  0.485 -0.138  0.087  0.286  0.834  0.236  0.112 -0.063 -0.038 -0.063 -0.063  0.137  0.510 
 0.171  0.072  0.196  0.296  0.396  0.072  0.072  0.246  0.744  0.769  0.047 -0.053  0.072  0.072  0.346  0.645  0.520  0.022  0.520 -0.053  0.495 -0.028 -0.028  0.421 -0.177  0.171  0.122  0.072 -0.003  0.047  0.769  0.022  0.022  0.396  0.022 -0.103  0.620  0.719 -0.128  0.146  0.321  0.769  0.271  0.146 -0.003 -0.003 -0.078 -0.028  0.246  0.695 
 0.200  0.050  0.225  0.324  0.374  0.100  0.100  0.299  0.723  0.723  0.050 -0.074  0.075  0.075  0.374  0.673  0.499  0.000  0.524 -0.049  0.499 -0.024  0.000  0.524 -0.174  0.225  0.075  0.075  0.025  0.075  0.748  0.075  0.000  0.449  0.025 -0.099  0.598  0.748 -0.149  0.225  0.299  0.723  0.225  0.150  0.100  0.050 -0.099 -0.049  0.349  0.698 
 0.232  0.033  0.307  0.307  0.307  0.083  0.133  0.307  0.706  0.681  0.033 -0.092  0.058  0.083  0.407  0.681  0.581 -0.017  0.556 -0.067  0.556  0.008  0.008  0.556 -0.166  0.232  0.083  0.108  0.033  0.108  0.706  0.133  0.033  0.506  0.058 -0.117  0.556  0.730 -0.166  0.307  0.282  0.706  0.232  0.232  0.182  0.058 -0.117 -0.017  0.332  0.681 
 0.277  0.053  0.352  0.302  0.302  0.078  0.152  0.302  0.701  0.676  0.028 -0.097  0.053  0.078  0.402  0.676  0.576  0.028  0.551 -0.072  0.601  0.003  0.003  0.526 -0.171  0.252  0.078  0.103  0.028  0.128  0.676  0.152  0.078  0.501  0.078 -0.122  0.551  0.725 -0.146  0.352  0.277  0.701  0.227  0.252  0.202  0.053 -0.122  0.003  0.327  0.676 
 0.297  0.048  0.422  0.297  0.272  0.073  0.147  0.322  0.696  0.671  0.023 -0.102  0.048  0.098  0.397  0.621  0.596  0.048  0.546 -0.052  0.621 -0.002  0.023  0.521 -0.201  0.272  0.073  0.098  0.048  0.098  0.671  0.147  0.123  0.521  0.073 -0.151  0.521  0.696 -0.151  0.397  0.297  0.696  0.222  0.297  0.197  0.048 -0.151 -0.002  0.347  0.671 
 0.292  0.018  0.517  0.292  0.243  0.043  0.168  0.292  0.691  0.666  0.043 -0.081  0.043  0.118  0.392  0.616  0.616  0.043  0.542 -0.056  0.641 -0.006  0.068  0.517 -0.206  0.268  0.068  0.093  0.018  0.093  0.616  0.143  0.168  0.542  0.093 -0.156  0.417  0.666 -0.081  0.442  0.292  0.691  0.243  0.317  0.193  0.068 -0.131  0.018  0.342  0.666 
 0.284  0.010  0.534  0.284  0.235  0.060  0.210  0.284  0.683  0.658  0.085 -0.064  0.035  0.110  0.359  0.608  0.608  0.085  0.534 -0.064  0.608 -0.014  0.110  0.534 -0.189  0.334  0.110  0.085  0.160  0.085  0.608  0.135  0.210  0.534  0.110 -0.164  0.384  0.658 -0.089  0.534  0.309  0.683  0.235  0.309  0.185  0.060 -0.164  0.035  0.334  0.658 
 0.286  0.012  0.536  0.286  0.212  0.062  0.212  0.286  0.685  0.685  0.087 -0.087  0.037  0.137  0.411  0.585  0.610  0.087  0.486 -0.062  0.610 -0.012  0.137  0.536 -0.187  0.336  0.112  0.087  0.162  0.087  0.585  0.112  0.187  0.536  0.137 -0.162  0.336  0.660 -0.087  0.536  0.311  0.685  0.237  0.311  0.187  0.062 -0.137  0.062  0.336  0.660 
 0.284  0.035  0.583  0.259  0.135  0.060  0.209  0.309  0.683  0.683  0.135  0.010  0.035  0.184  0.409  0.583  0.608  0.135  0.458 -0.065  0.583  0.035  0.159  0.533 -0.189  0.409  0.110  0.085  0.184  0.085  0.558  0.085  0.184  0.533  0.159 -0.140  0.334  0.658 -0.090  0.533  0.309  0.683  0.259  0.359  0.184  0.135 -0.140  0.060  0.334  0.658 
 0.257  0.032  0.605  0.257  0.132  0.057  0.207  0.331  0.680  0.680  0.132  0.032  0.057  0.182  0.406  0.556  0.605  0.132  0.456 -0.092  0.580  0.032  0.157  0.531 -0.192  0.406  0.107  0.082  0.182  0.057  0.556  0.057  0.207  0.531  0.207 -0.142  0.331  0.655 -0.092  0.556  0.306  0.655  0.257  0.356  0.182  0.132 -0.142  0.057  0.331  0.655 
 0.256  0.056  0.604  0.231  0.131  0.056  0.231  0.355  0.679  0.654  0.131  0.131  0.031  0.181  0.405  0.555  0.604  0.131  0.455 -0.093  0.579  0.081  0.156  0.530 -0.193  0.405  0.106  0.081  0.231  0.056  0.505  0.056  0.256  0.530  0.231 -0.118  0.330  0.654 -0.093  0.579  0.305  0.654  0.281  0.355  0.181  0.131 -0.168  0.081  0.281  0.654 
 0.229  0.055  0.603  0.229  0.130  0.055  0.254  0.379  0.678  0.653  0.130  0.204  0.030  0.179  0.428  0.553  0.603  0.130  0.453 -0.120  0.578  0.105  0.130  0.503 -0.169  0.404  0.105  0.080  0.229  0.055  0.503  0.055  0.279  0.528  0.229 -0.120  0.329  0.653 -0.095  0.578  0.304  0.653  0.279  0.354  0.179  0.130 -0.169  0.105  0.279  0.653 
 0.227  0.078  0.601  0.202  0.128  0.053  0.252  0.426  0.651  0.676  0.128  0.227  0.028  0.202  0.451  0.551  0.601  0.152  0.451 -0.122  0.576  0.103  0.103  0.451 -0.171  0.402  0.103  0.078  0.227  0.053  0.501  0.053  0.302  0.526  0.252 -0.097  0.327  0.651 -0.072  0.576  0.327  0.651  0.302  0.352  0.177  0.202 -0.146  0.103  0.277  0.651 
 0.227  0.077  0.600  0.202  0.127  0.052  0.252  0.426  0.650  0.650  0.127  0.252  0.052  0.202  0.451  0.551  0.600  0.152  0.451 -0.122  0.575  0.102  0.102  0.401 -0.147  0.401  0.102  0.077  0.252  0.052  0.501  0.077  0.301  0.526  0.252 -0.072  0.326  0.650 -0.072  0.551  0.326  0.650  0.301  0.376  0.177  0.152 -0.172  0.127  0.252  0.650 
 0.221  0.121  0.594  0.196  0.121  0.046  0.271  0.470  0.644  0.644  0.146  0.246  0.046  0.196  0.420  0.545  0.594  0.146  0.445 -0.128  0.569  0.121  0.096  0.370 -0.128  0.395  0.121  0.071  0.345  0.021  0.495  0.071  0.370  0.520  0.246 -0.003  0.320  0.644 -0.053  0.545  0.320  0.644  0.295  0.420  0.171  0.196 -0.178  0.121  0.246  0.619 
 0.220  0.145  0.594  0.195  0.121  0.046  0.295  0.469  0.644  0.644  0.145  0.270  0.046  0.195  0.420  0.544  0.594  0.145  0.444 -0.129  0.569  0.121  0.096  0.370 -0.129  0.395  0.096  0.071  0.345  0.021  0.494  0.071  0.395  0.519  0.245 -0.004  0.320  0.644 -0.054  0.544  0.320  0.644  0.270  0.420  0.170  0.195 -0.178  0.121  0.245  0.644 
 0.273  0.148  0.597  0.173  0.124  0.049  0.298  0.472  0.647  0.647  0.148  0.298  0.024  0.148  0.398  0.547  0.597  0.148  0.447 -0.126  0.547  0.124  0.099  0.348 -0.126  0.398  0.099  0.074  0.323  0.024  0.497  0.049  0.398  0.522  0.248  0.024  0.298  0.647 -0.051  0.547  0.323  0.622  0.273  0.423  0.148  0.223 -0.175  0.124  0.248  0.647 
 0.294  0.095  0.618  0.220  0.170 -0.029  0.220  0.494  0.593  0.593  0.120  0.220  0.045  0.170  0.444  0.494  0.544  0.195  0.394 -0.104  0.568  0.070 -0.004  0.270 -0.104  0.270 -0.004 -0.029  0.319  0.070  0.544  0.070  0.369  0.444  0.220  0.020  0.294  0.494 -0.029  0.519  0.294  0.544  0.245  0.319  0.170  0.170 -0.154  0.120  0.294  0.643 
 0.186  0.161  0.485  0.211  0.211  0.037  0.112  0.386  0.510  0.635  0.137  0.112 -0.038  0.112  0.435  0.411  0.460  0.161  0.485 -0.038  0.585  0.037 -0.088  0.137 -0.088  0.137  0.012 -0.063  0.261  0.062  0.560  0.012  0.236  0.460  0.186  0.012  0.161  0.435 -0.063  0.386  0.311  0.610  0.211  0.311  0.087  0.112 -0.088  0.037  0.236  0.660 
 0.158  0.158  0.407  0.258  0.208  0.033  0.108  0.382  0.557  0.631  0.108 -0.016 -0.016  0.108  0.407  0.382  0.457  0.083  0.507 -0.016  0.557 -0.041 -0.116  0.083 -0.066  0.058  0.008 -0.091  0.133  0.058  0.581  0.033  0.158  0.407  0.108  0.008  0.133  0.382 -0.066  0.332  0.307  0.606  0.133  0.233  0.058  0.033 -0.066  0.033  0.233  0.656 
 0.134  0.134  0.358  0.259  0.209  0.034  0.109  0.308  0.558  0.657  0.059 -0.015  0.009  0.059  0.383  0.358  0.433  0.034  0.433 -0.015  0.582 -0.065 -0.090  0.034 -0.065  0.009  0.034 -0.065  0.084  0.034  0.582  0.034  0.034  0.333  0.059  0.009  0.159  0.308 -0.065  0.184  0.308  0.707  0.159  0.159  0.009 -0.040 -0.040  0.059  0.159  0.632 
 0.121  0.121  0.295  0.245  0.195  0.046  0.121  0.270  0.519  0.694  0.021 -0.004 -0.029  0.071  0.370  0.245  0.444  0.046  0.420 -0.004  0.469 -0.054 -0.079  0.021 -0.079 -0.054  0.046 -0.079  0.071  0.021  0.594 -0.004  0.021  0.295  0.071 -0.004  0.121  0.295 -0.054  0.096  0.270  0.694  0.170  0.145  0.021 -0.029 -0.054  0.021  0.121  0.669 
 0.088  0.113  0.238  0.188  0.213  0.038  0.113  0.213  0.487  0.786  0.013 -0.011 -0.011  0.063  0.287  0.138  0.412 -0.011  0.387 -0.011  0.337 -0.036 -0.061  0.063 -0.061 -0.061  0.063 -0.086  0.013 -0.011  0.636  0.013 -0.036  0.113  0.063 -0.011  0.138  0.263 -0.036 -0.011  0.263  0.736  0.113  0.063 -0.011 -0.011 -0.036 -0.011  0.113  0.611 
 0.071  0.071  0.195  0.170  0.170  0.046  0.071  0.195  0.494  0.818  0.021 -0.004 -0.004  0.071  0.295  0.121  0.370 -0.004  0.345 -0.004  0.245 -0.029 -0.054  0.021 -0.054 -0.029  0.071 -0.079  0.021 -0.004  0.669  0.021 -0.029  0.096  0.071 -0.029  0.121  0.270 -0.029 -0.029  0.245  0.768  0.121  0.096 -0.029 -0.004 -0.054 -0.004  0.096  0.494 
 0.056  0.081  0.106  0.081  0.155  0.031  0.031  0.131  0.405  0.828 -0.019 -0.044  0.006  0.056  0.230  0.081  0.280 -0.044  0.330 -0.044  0.106 -0.019 -0.044  0.056 -0.044 -0.019  0.056 -0.069  0.031  0.006  0.679  0.006 -0.044  0.056  0.056 -0.019  0.131  0.230 -0.019 -0.044  0.180  0.853  0.131  0.056 -0.019  0.006 -0.044  0.006  0.081  0.429 
 0.010  0.010  0.035  0.060  0.110 -0.015  0.035  0.110  0.284  0.857 -0.015 -0.015  0.010 -0.015  0.234  0.085  0.259 -0.040  0.309 -0.015  0.060 -0.015 -0.040  0.060 -0.040 -0.015  0.035 -0.065  0.010  0.035  0.683  0.035 -0.040  0.060  0.060 -0.065  0.135  0.184 -0.040 -0.040  0.159  0.957  0.110  0.060 -0.015 -0.015 -0.040  0.010  0.060  0.359 
 0.020  0.020 -0.004  0.045  0.095 -0.004 -0.004  0.095  0.145  0.942 -0.029 -0.029 -0.004 -0.029  0.120  0.070  0.120 -0.029  0.220 -0.004  0.020 -0.004 -0.029  0.070 -0.054 -0.004  0.045 -0.054  0.020  0.020  0.718  0.020 -0.029  0.045  0.070 -0.054  0.095  0.120 -0.054 -0.029  0.095  0.967  0.120  0.045 -0.004 -0.004 -0.004  0.020  0.020  0.120 
 0.022  0.022 -0.028  0.047  0.097  0.022 -0.003  0.097  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.072  0.047  0.022 -0.028  0.146 -0.003  0.022 -0.003 -0.028  0.072 -0.053  0.022  0.022 -0.028  0.022  0.022  0.719  0.022 -0.028  0.047  0.047 -0.053  0.097  0.072 -0.053 -0.028  0.097  0.969  0.122  0.047 -0.003 -0.003 -0.003  0.022  0.022  0.122 
 0.023  0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.073 -0.001 -0.001 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.023  0.023  0.771  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.048 -0.001 -0.001 -0.001  0.023 -0.001  0.098 
 0.022  0.022 -0.027  0.047  0.097  0.022 -0.027  0.072  0.147  0.969 -0.027 -0.027 -0.002 -0.027  0.022  0.022 -0.002 -0.027  0.072 -0.002 -0.002 -0.002 -0.027  0.072 -0.052  0.022 -0.002 -0.027  0.047  0.022  0.820  0.022 -0.027  0.047  0.022 -0.052  0.097  0.047 -0.052 -0.027  0.097  0.969  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
 0.021  0.021 -0.028  0.046  0.096  0.021 -0.028  0.071  0.146  0.968 -0.028 -0.028 -0.003 -0.028  0.021  0.021 -0.003 -0.028  0.071 -0.003 -0.003 -0.003 -0.028  0.071 -0.053  0.021 -0.003 -0.028  0.046  0.021  0.868  0.021 -0.028  0.046  0.021 -0.053  0.096  0.046 -0.053 -0.003  0.096  0.968  0.096  0.046 -0.003 -0.003 -0.003  0.021 -0.003  0.096 
 0.020  0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004 -0.004  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054 -0.004  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.019  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.070  0.045 -0.005  0.070  0.120  0.020 -0.030  0.070  0.269  0.942 -0.055 -0.030 -0.005 -0.055 -0.005  0.045 -0.005 -0.055  0.095 -0.005 -0.005 -0.030 -0.030  0.070 -0.080  0.020 -0.005 -0.055  0.045 -0.005  0.942  0.020  0.020  0.219  0.020 -0.080  0.070  0.045 -0.055  0.120  0.194  0.942  0.095  0.120  0.020 -0.030 -0.005 -0.005  0.020  0.219 
 0.037  0.062  0.012  0.137  0.261  0.012 -0.038  0.161  0.610  0.884  0.062 -0.038  0.012 -0.038  0.062  0.112  0.012 -0.038  0.211 -0.013  0.211 -0.063 -0.063  0.112 -0.138 -0.038  0.037 -0.013  0.161  0.012  0.884  0.062  0.062  0.261 -0.013 -0.113  0.062  0.062 -0.113  0.186  0.311  0.884  0.087  0.161  0.012 -0.013 -0.063  0.037  0.087  0.336 
 0.090  0.065  0.165  0.190  0.289 -0.009  0.040  0.215  0.713  0.838  0.065 -0.009 -0.009 -0.034  0.190  0.140  0.165  0.090  0.389 -0.009  0.514 -0.059 -0.109  0.115 -0.159 -0.084 -0.009 -0.009  0.115  0.040  0.838  0.115  0.065  0.439  0.040 -0.084  0.115  0.165 -0.159  0.265  0.314  0.838  0.165  0.215  0.065 -0.059 -0.059  0.115  0.140  0.514 
 0.227  0.103  0.377  0.277  0.402  0.003  0.078  0.327  0.725  0.775  0.128 -0.022  0.028  0.053  0.352  0.302  0.277  0.177  0.526  0.003  0.576 -0.097 -0.097  0.152 -0.171 -0.072  0.003 -0.047  0.152  0.053  0.775  0.078  0.128  0.576  0.053 -0.097  0.227  0.277 -0.171  0.277  0.426  0.775  0.302  0.277  0.128  0.003 -0.122  0.128  0.302  0.701 
 0.210  0.085  0.484  0.284  0.359 -0.039  0.085  0.359  0.708  0.733  0.135 -0.039  0.035  0.085  0.409  0.309  0.359  0.185  0.509  0.010  0.683 -0.089 -0.089  0.235 -0.189 -0.064  0.010 -0.014  0.185  0.060  0.733  0.060  0.135  0.583  0.035 -0.014  0.210  0.309 -0.189  0.309  0.409  0.733  0.409  0.309  0.110 -0.014 -0.139  0.135  0.284  0.708 
 0.156  0.132  0.530  0.306  0.331 -0.043  0.181  0.430  0.680  0.705  0.156 -0.043  0.107  0.132  0.430  0.406  0.455  0.181  0.530  0.007  0.680 -0.068 -0.093  0.231 -0.192  0.007  0.007  0.007  0.256  0.057  0.680  0.082  0.206  0.555  0.057  0.032  0.181  0.381 -0.118  0.455  0.381  0.705  0.455  0.331  0.156 -0.018 -0.167  0.156  0.331  0.680 
 0.167  0.118  0.541  0.292  0.317  0.018  0.167  0.417  0.666  0.691  0.142 -0.082  0.068  0.118  0.417  0.417  0.591  0.167  0.516 -0.007  0.666 -0.057 -0.057  0.217 -0.206 -0.007 -0.007  0.018  0.292  0.043  0.666  0.118  0.242  0.566  0.118  0.043  0.167  0.367 -0.132  0.541  0.367  0.691  0.441  0.342  0.142 -0.007 -0.181  0.142  0.342  0.666 
 0.159  0.110  0.533  0.259  0.284  0.035  0.184  0.409  0.658  0.708  0.135 -0.065  0.110  0.085  0.409  0.433  0.633  0.159  0.508 -0.015  0.658 -0.015 -0.065  0.209 -0.214  0.010  0.010  0.035  0.334  0.035  0.633  0.110  0.234  0.558  0.184  0.060  0.135  0.359 -0.140  0.583  0.384  0.683  0.433  0.409  0.135 -0.015 -0.189  0.135  0.359  0.658 
 0.155  0.080  0.529  0.280  0.255  0.055  0.180  0.404  0.653  0.678  0.130  0.005  0.105  0.105  0.429  0.429  0.653  0.155  0.504 -0.019  0.653  0.005 -0.069  0.205 -0.219 -0.019  0.030  0.005  0.354  0.030  0.628  0.105  0.230  0.554  0.180  0.055  0.130  0.404 -0.169  0.603  0.379  0.678  0.429  0.404  0.130 -0.019 -0.194  0.180  0.354  0.653 
 0.155  0.080  0.529  0.280  0.230  0.055  0.180  0.429  0.653  0.653  0.130  0.080  0.080  0.105  0.429  0.429  0.653  0.155  0.504 -0.044  0.628  0.005 -0.044  0.205 -0.219 -0.019  0.030  0.005  0.404  0.030  0.628  0.080  0.280  0.554  0.205  0.055  0.155  0.429 -0.169  0.603  0.379  0.678  0.429  0.429  0.130 -0.044 -0.219  0.180  0.354  0.628 
 0.151  0.076  0.525  0.276  0.226  0.051  0.201  0.425  0.649  0.624  0.126  0.101  0.051  0.101  0.425  0.425  0.649  0.151  0.500 -0.048  0.599  0.051  0.026  0.226 -0.223 -0.023  0.026  0.001  0.400  0.026  0.624  0.101  0.325  0.550  0.226  0.051  0.226  0.450 -0.148  0.599  0.350  0.674  0.425  0.450  0.126 -0.048 -0.223  0.176  0.325  0.624 
 0.151  0.026  0.525  0.276  0.176  0.051  0.251  0.425  0.649  0.599  0.126  0.126  0.026  0.101  0.425  0.400  0.649  0.151  0.475 -0.073  0.574  0.101  0.051  0.226 -0.223 -0.048  0.026  0.001  0.425  0.026  0.649  0.076  0.350  0.550  0.226  0.026  0.226  0.550 -0.148  0.599  0.350  0.649  0.375  0.450  0.101 -0.048 -0.198  0.176  0.325  0.649 
 0.150  0.025  0.524  0.275  0.200  0.050  0.250  0.449  0.648  0.573  0.150  0.125 -0.024  0.100  0.424  0.399  0.648  0.150  0.474 -0.074  0.573  0.100  0.075  0.225 -0.224 -0.049  0.025  0.000  0.424  0.025  0.673  0.075  0.349  0.549  0.225  0.025  0.250  0.598 -0.124  0.598  0.324  0.648  0.374  0.449  0.100 -0.074 -0.199  0.175  0.299  0.623 
 0.148  0.023  0.522  0.248  0.198  0.023  0.273  0.447  0.646  0.571  0.148  0.123 -0.051  0.098  0.422  0.397  0.646  0.148  0.472 -0.101  0.547  0.123  0.123  0.273 -0.226 -0.051  0.023 -0.001  0.447  0.023  0.671  0.048  0.347  0.547  0.223  0.023  0.273  0.596 -0.126  0.596  0.322  0.646  0.347  0.447  0.098 -0.076 -0.201  0.173  0.297  0.621 
 0.147  0.023  0.496  0.247  0.172 -0.002  0.272  0.446  0.646  0.571  0.147  0.123 -0.077  0.098  0.422  0.397  0.646  0.147  0.446 -0.102  0.546  0.123  0.123  0.272 -0.226 -0.052 -0.002 -0.002  0.496  0.023  0.671  0.048  0.347  0.546  0.222  0.023  0.272  0.596 -0.127  0.596  0.372  0.646  0.322  0.446  0.098 -0.077 -0.226  0.147  0.297  0.621 
 0.145  0.045  0.494  0.245  0.145 -0.029  0.270  0.444  0.643  0.568  0.120  0.120 -0.104  0.120  0.444  0.394  0.643  0.120  0.444 -0.104  0.544  0.070  0.145  0.270 -0.229 -0.054 -0.004 -0.004  0.519  0.020  0.668  0.020  0.344  0.544  0.195  0.045  0.270  0.593 -0.104  0.593  0.369  0.643  0.270  0.444  0.095 -0.079 -0.229  0.145  0.294  0.643 
 0.145  0.045  0.494  0.220  0.145 -0.029  0.270  0.444  0.643  0.568  0.120  0.120 -0.104  0.120  0.444  0.394  0.643  0.120  0.444 -0.104  0.544  0.095  0.145  0.270 -0.229 -0.054 -0.004 -0.004  0.519  0.045  0.668  0.020  0.369  0.544  0.195  0.045  0.270  0.593 -0.079  0.593  0.369  0.643  0.270  0.444  0.095 -0.054 -0.229  0.145  0.270  0.643 
 0.144  0.045  0.493  0.219  0.144 -0.030  0.269  0.443  0.643  0.568  0.144  0.120 -0.080  0.095  0.443  0.394  0.643  0.095  0.443 -0.105  0.543  0.095  0.120  0.269 -0.229 -0.055 -0.005 -0.005  0.518  0.045  0.668  0.020  0.369  0.543  0.194  0.020  0.269  0.593 -0.080  0.593  0.369  0.643  0.269  0.443  0.095 -0.030 -0.229  0.144  0.269  0.643 
 0.145  0.071  0.494  0.220  0.145 -0.029  0.270  0.444  0.644  0.569  0.170  0.121 -0.054  0.096  0.444  0.395  0.644  0.096  0.444 -0.104  0.544  0.071  0.121  0.270 -0.228 -0.054 -0.004 -0.004  0.519  0.021  0.669  0.021  0.370  0.544  0.220  0.021  0.270  0.594 -0.079  0.594  0.370  0.644  0.270  0.444  0.096 -0.004 -0.228  0.145  0.270  0.644 
 0.145  0.095  0.494  0.220  0.145 -0.029  0.270  0.469  0.643  0.568  0.170  0.120 -0.054  0.095  0.444  0.394  0.643  0.095  0.444 -0.104  0.544  0.070  0.095  0.270 -0.229 -0.054 -0.004 -0.004  0.519  0.020  0.668  0.020  0.369  0.544  0.220  0.020  0.270  0.593 -0.079  0.593  0.369  0.643  0.270  0.444  0.095  0.020 -0.229  0.145  0.270  0.643 

 0.967  0.020 -0.004 -0.004 -0.029 -0.029 -0.029 -0.004  0.020  0.045 -0.029 -0.029  0.020 -0.029 -0.004 -0.004 -0.029 -0.004 -0.029 -0.004 -0.029  0.045  0.020 -0.029 -0.004  0.045 -0.029 -0.004 -0.004 -0.029 -0.029  0.045  0.020  0.045  0.095  0.045 -0.004  0.020 -0.004 -0.004 -0.029 -0.004 -0.004  0.020 -0.029  0.045 -0.029  0.045 -0.029 -0.029 
 0.997  0.025  0.000 -0.024 -0.024 -0.024 -0.024  0.000  0.025  0.050 -0.024 -0.024  0.025 -0.024  0.000  0.000 -0.024  0.000 -0.024 -0.024 -0.024  0.050  0.025 -0.024  0.000  0.050 -0.024 -0.024  0.000 -0.024 -0.024  0.025  0.025  0.050  0.075  0.050  0.025  0.025  0.000  0.000 -0.024  0.000  0.000  0.025  0.000  0.050 -0.024  0.050 -0.024 -0.024 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004  0.054 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004  0.054 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.029  0.054  0.079  0.029  0.029  0.004  0.004  0.004 -0.020  0.004  0.004  0.029  0.004  0.054 -0.020  0.054 -0.020 -0.020 
 1.000  0.003 -0.021 -0.021 -0.021 -0.021 -0.021  0.003  0.003  0.053 -0.021 -0.021  0.003 -0.021  0.003  0.003 -0.021  0.003 -0.021 -0.021 -0.021  0.028  0.028 -0.021  0.003  0.053 -0.021 -0.021  0.003 -0.021 -0.021  0.028  0.028  0.078  0.103  0.028  0.028  0.003  0.003  0.003 -0.021  0.003  0.003  0.028  0.003  0.078 -0.021  0.053 -0.021 -0.021 
 0.999  0.002  0.002 -0.022 -0.022 -0.022 -0.022  0.002  0.002  0.052 -0.022 -0.022  0.002 -0.022  0.002  0.002 -0.022  0.002 -0.022 -0.022 -0.022  0.027  0.027 -0.022  0.002  0.077 -0.022 -0.022  0.002 -0.022 -0.022  0.027  0.027  0.077  0.152  0.027  0.027  0.002  0.002  0.002 -0.022  0.002  0.002  0.027  0.002  0.077 -0.022  0.052 -0.022 -0.022 
 0.997  0.000  0.000 -0.024 -0.024 -0.024 -0.024  0.000  0.000  0.050 -0.024 -0.024  0.000 -0.024  0.000  0.000 -0.024  0.025 -0.024 -0.024 -0.024  0.075  0.025 -0.024  0.000  0.075 -0.024 -0.024  0.000 -0.024 -0.024  0.050  0.025  0.050  0.250  0.025  0.025  0.000  0.000  0.000 -0.024  0.000  0.000  0.025  0.000  0.050 -0.024  0.050 -0.024 -0.024 
 0.986  0.014  0.089 -0.036 -0.011 -0.011 -0.036 -0.011  0.014  0.039 -0.011 -0.011 -0.011 -0.036  0.014 -0.011 -0.011  0.089  0.114 -0.036 -0.036  0.089  0.014 -0.036  0.014  0.064 -0.011 -0.036 -0.011 -0.036 -0.036  0.039  0.014  0.039  0.637  0.064  0.039  0.014  0.014  0.014 -0.036  0.014  0.064  0.039  0.014  0.039 -0.036  0.064 -0.011 -0.036 
 0.968  0.021  0.246 -0.053 -0.003 -0.003 -0.028 -0.028 -0.003  0.021 -0.003 -0.028  0.021 -0.028  0.021  0.046 -0.028  0.146  0.096 -0.028 -0.028  0.071  0.021 -0.053 -0.003  0.096 -0.028 -0.053 -0.028 -0.053 -0.053  0.021 -0.003  0.021  0.794  0.121  0.021 -0.003  0.021  0.021 -0.053 -0.003  0.096  0.021  0.021  0.021 -0.028  0.071 -0.003 -0.053 
 0.938  0.041  0.639 -0.083  0.016 -0.008 -0.008 -0.008  0.041  0.016 -0.033 -0.033 -0.008  0.016  0.066  0.091  0.091  0.191  0.166 -0.033 -0.058  0.066  0.016 -0.083 -0.008  0.191 -0.033 -0.033  0.016 -0.058 -0.033 -0.008  0.041  0.041  0.938  0.141  0.016  0.091  0.066  0.016 -0.058 -0.033  0.141  0.016  0.016  0.041 -0.008  0.141 -0.008 -0.058 
 0.911  0.064  0.737 -0.060 -0.010 -0.010 -0.010 -0.010  0.139  0.014 -0.060 -0.060 -0.035  0.189  0.114  0.114  0.139  0.388  0.239 -0.035 -0.085  0.039  0.014 -0.035 -0.035  0.264 -0.010 -0.010  0.039 -0.085 -0.035 -0.010  0.089  0.089  0.911  0.239 -0.010  0.114  0.039 -0.010 -0.085 -0.010  0.239 -0.010  0.014  0.064 -0.010  0.214 -0.035 -0.060 
 0.857  0.085  0.857 -0.039  0.010 -0.014  0.010 -0.039  0.334  0.060  0.010 -0.089 -0.039  0.334  0.160  0.160  0.185  0.559  0.409 -0.064 -0.089  0.010  0.035  0.010 -0.014  0.409  0.010 -0.039  0.160 -0.114 -0.064 -0.064  0.160  0.060  0.857  0.309  0.010  0.185  0.085  0.010 -0.039  0.010  0.359 -0.014  0.060  0.135 -0.064  0.409 -0.064 -0.039 
 0.825  0.127  0.825 -0.022  0.002  0.002  0.052 -0.072  0.426  0.127  0.052 -0.072 -0.072  0.451  0.202  0.277  0.227  0.526  0.551 -0.047 -0.072 -0.022  0.077  0.002  0.002  0.526  0.002  0.027  0.376 -0.097 -0.072 -0.097  0.177  0.102  0.825  0.326 -0.022  0.152  0.102  0.002 -0.022 -0.022  0.426 -0.047  0.027  0.152 -0.072  0.476 -0.072 -0.047 
 0.758  0.185  0.758 -0.039  0.035  0.060  0.185 -0.089  0.583  0.110  0.060 -0.014 -0.089  0.434  0.260  0.309  0.235  0.484  0.683 -0.089 -0.064 -0.014  0.135  0.085  0.035  0.608  0.060  0.160  0.409 -0.064 -0.089 -0.114  0.260  0.085  0.783  0.459 -0.014  0.160  0.085 -0.014 -0.014 -0.039  0.509 -0.089  0.060  0.135 -0.089  0.509 -0.064 -0.014 
 0.744  0.221  0.744  0.022  0.022  0.122  0.196 -0.078  0.595  0.196  0.146 -0.003 -0.078  0.445  0.396  0.296  0.221  0.445  0.670 -0.103 -0.078 -0.028  0.122  0.122  0.022  0.620  0.122  0.146  0.396 -0.003 -0.078 -0.128  0.296  0.072  0.744  0.520 -0.003  0.146  0.072 -0.028  0.047 -0.053  0.470 -0.128  0.022  0.171 -0.103  0.495 -0.078  0.072 
 0.722  0.249  0.697 -0.000  0.024  0.199  0.199 -0.050  0.597  0.249  0.174  0.049 -0.075  0.448  0.423  0.323  0.249  0.398  0.647 -0.125 -0.100 -0.025  0.124  0.149  0.049  0.597  0.224  0.224  0.423  0.024 -0.050 -0.150  0.298  0.099  0.722  0.548 -0.025  0.124  0.074 -0.025  0.024 -0.000  0.473 -0.150  0.099  0.249 -0.100  0.473 -0.075  0.274 
 0.710  0.237  0.685  0.037  0.012  0.286  0.311 -0.062  0.585  0.237  0.187  0.062 -0.087  0.436  0.461  0.311  0.237  0.336  0.635 -0.137 -0.112 -0.012  0.112  0.162  0.062  0.610  0.336  0.212  0.461  0.012 -0.062 -0.162  0.286  0.062  0.710  0.536 -0.012  0.112  0.087 -0.012  0.012  0.012  0.511 -0.162  0.087  0.311 -0.087  0.436 -0.087  0.311 
 0.649  0.201  0.624  0.101  0.001  0.325  0.350 -0.098  0.550  0.226  0.201  0.051 -0.073  0.450  0.450  0.325  0.201  0.300  0.599 -0.148 -0.123 -0.048  0.101  0.201  0.101  0.574  0.450  0.226  0.525  0.051  0.001 -0.173  0.251  0.076  0.724  0.500 -0.023  0.151  0.076 -0.023  0.026  0.026  0.500 -0.148  0.101  0.325 -0.048  0.350 -0.123  0.350 
 0.616  0.218  0.616  0.168 -0.006  0.342  0.367 -0.081  0.517  0.218  0.243  0.043 -0.081  0.442  0.417  0.367  0.243  0.292  0.591 -0.156 -0.156 -0.031  0.118  0.193  0.093  0.567  0.492  0.193  0.517  0.018  0.043 -0.181  0.243  0.068  0.716  0.492 -0.006  0.143  0.043 -0.031  0.168  0.068  0.492 -0.131  0.118  0.367 -0.056  0.243 -0.106  0.392 
 0.513  0.214  0.612  0.264 -0.010  0.338  0.388 -0.085  0.488  0.214  0.239  0.039 -0.085  0.463  0.388  0.413  0.239  0.264  0.587 -0.185 -0.160 -0.035  0.114  0.214  0.089  0.538  0.538  0.214  0.513  0.064  0.064 -0.185  0.239  0.064  0.712  0.463 -0.060  0.164  0.039 -0.010  0.214  0.064  0.488 -0.135  0.089  0.388 -0.060  0.214 -0.110  0.413 
 0.488  0.214  0.613  0.289 -0.035  0.339  0.364 -0.085  0.438  0.239  0.264  0.040 -0.085  0.463  0.389  0.414  0.239  0.239  0.588 -0.184 -0.184 -0.060  0.090  0.239  0.090  0.538  0.563  0.214  0.513  0.065  0.090 -0.184  0.239  0.065  0.688  0.488 -0.060  0.189  0.040 -0.010  0.239  0.090  0.488 -0.135  0.065  0.414 -0.035  0.214 -0.110  0.414 
 0.413  0.189  0.612  0.313 -0.035  0.363  0.363 -0.035  0.438  0.189  0.264  0.114 -0.110  0.463  0.388  0.413  0.239  0.214  0.587 -0.185 -0.185 -0.060  0.089  0.288  0.089  0.513  0.563  0.189  0.513  0.039  0.139 -0.210  0.214  0.039  0.587  0.538 -0.060  0.189  0.014 -0.060  0.239  0.064  0.513 -0.185  0.089  0.413 -0.010  0.239 -0.110  0.413 
 0.411  0.187  0.610  0.311 -0.037  0.361  0.361 -0.012  0.436  0.187  0.262  0.187 -0.112  0.486  0.386  0.411  0.262  0.162  0.585 -0.187 -0.162 -0.062  0.062  0.311  0.112  0.461  0.561  0.212  0.486  0.062  0.137 -0.212  0.187  0.037  0.585  0.536 -0.062  0.187  0.012 -0.087  0.212  0.062  0.561 -0.187  0.112  0.436  0.037  0.237 -0.137  0.411 
 0.408  0.158  0.607  0.333 -0.041  0.408  0.333  0.034  0.432  0.183  0.283  0.233 -0.116  0.482  0.408  0.408  0.233  0.134  0.582 -0.190 -0.165 -0.041  0.059  0.308  0.134  0.432  0.557  0.233  0.482  0.084  0.084 -0.215  0.208  0.034  0.557  0.532 -0.066  0.183  0.109 -0.116  0.208  0.059  0.557 -0.190  0.158  0.432  0.109  0.233 -0.116  0.383 
 0.360  0.136  0.609  0.186 -0.013  0.285  0.310  0.036  0.435  0.136  0.285  0.211 -0.088  0.410  0.385  0.385  0.211  0.161  0.560 -0.138 -0.163 -0.113 -0.088  0.136  0.111  0.385  0.485  0.161  0.385 -0.013 -0.013 -0.213  0.236  0.011  0.435  0.485 -0.063  0.161  0.011 -0.088  0.111  0.136  0.584 -0.113  0.111  0.435  0.036  0.211 -0.088  0.310 
 0.257  0.082  0.531  0.082  0.007  0.182  0.232  0.057  0.381  0.132  0.207  0.107  0.007  0.282  0.331  0.331  0.082  0.157  0.456 -0.092 -0.067 -0.042 -0.042  0.132  0.082  0.331  0.381  0.132  0.207 -0.017  0.007 -0.142  0.082 -0.017  0.381  0.481 -0.067  0.107 -0.017 -0.092  0.082  0.182  0.556 -0.042  0.107  0.431  0.057  0.107 -0.042  0.207 
 0.229  0.104  0.553  0.054  0.004  0.054  0.204  0.054  0.328  0.104  0.229  0.029  0.029  0.254  0.204  0.303  0.079  0.129  0.303 -0.045 -0.095 -0.045 -0.020  0.129  0.104  0.328  0.353  0.104  0.179 -0.020 -0.020 -0.120 -0.020  0.004  0.378  0.453 -0.070  0.079  0.004 -0.095  0.104  0.154  0.528 -0.020  0.104  0.378  0.079  0.129 -0.020  0.154 
 0.234  0.034  0.582  0.059 -0.015  0.034  0.134  0.034  0.284 -0.040  0.159 -0.065  0.034  0.209  0.059  0.259  0.009  0.084  0.209  0.009 -0.065 -0.015  0.009  0.109  0.034  0.234  0.333  0.084  0.084 -0.040  0.009 -0.090 -0.015 -0.015  0.358  0.358 -0.040  0.034 -0.015 -0.065  0.034  0.109  0.483  0.009  0.084  0.308  0.084  0.134  0.009  0.009 
 0.248  0.048  0.547  0.023 -0.001  0.023  0.148  0.048  0.198 -0.051  0.148 -0.051  0.023  0.148  0.098  0.173  0.023  0.098  0.273 -0.001 -0.051 -0.026  0.023  0.123 -0.001  0.123  0.322  0.048  0.073 -0.026  0.023 -0.076 -0.001 -0.026  0.347  0.347 -0.026 -0.001 -0.026 -0.051 -0.001  0.098  0.472  0.023  0.073  0.273  0.073  0.148 -0.001  0.023 
 0.144  0.070  0.518 -0.005  0.020 -0.005  0.070  0.020  0.120 -0.030  0.095 -0.055 -0.005  0.070  0.070  0.120  0.020  0.095  0.294  0.020 -0.030 -0.030  0.020  0.120 -0.005  0.045  0.219  0.045 -0.030 -0.030 -0.005 -0.055 -0.005 -0.030  0.269  0.244 -0.005  0.020 -0.030 -0.030  0.020  0.070  0.369 -0.005  0.070  0.144  0.070  0.095 -0.005 -0.030 
 0.154  0.055  0.478  0.005 -0.020  0.005  0.080  0.005  0.055 -0.045  0.030 -0.045  0.005  0.030  0.005  0.105  0.005  0.105  0.229  0.005 -0.020 -0.020  0.030  0.105 -0.020  0.055  0.154  0.005 -0.020 -0.020  0.005 -0.045  0.005 -0.020  0.254  0.130  0.005  0.005 -0.020 -0.020  0.005  0.055  0.304 -0.020  0.055  0.105  0.055  0.055 -0.020 -0.020 
 0.119  0.044  0.343 -0.005 -0.030 -0.005  0.044  0.019  0.019 -0.030 -0.030 -0.030 -0.005 -0.005 -0.005  0.069  0.019  0.094  0.194 -0.030 -0.005 -0.005  0.019  0.044 -0.005  0.019  0.069 -0.005 -0.030 -0.030 -0.030 -0.030  0.019 -0.005  0.244 -0.005 -0.005  0.019 -0.005  0.019 -0.030  0.019  0.244 -0.005  0.019  0.019  0.044  0.069 -0.005 -0.030 
 0.076  0.026  0.275  0.001 -0.024 -0.024  0.051  0.026  0.026 -0.024 -0.024 -0.024 -0.024  0.001  0.001  0.026  0.026  0.076  0.175 -0.024  0.001 -0.024  0.001  0.001 -0.024 -0.024  0.051 -0.024 -0.024 -0.024 -0.024 -0.024  0.026  0.001  0.175  0.001  0.001  0.026  0.001  0.026 -0.024  0.026  0.225  0.001  0.026  0.026  0.051  0.076  0.001 -0.024 
 0.042  0.017  0.092  0.017 -0.008 -0.008 -0.008  0.017  0.017 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008  0.017 -0.008  0.042  0.042 -0.008 -0.008 -0.008  0.017  0.017 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008  0.017 -0.008  0.067 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008  0.017  0.117 -0.008 -0.008  0.017  0.042  0.042 -0.008 -0.008 
 0.022  0.022  0.022 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003  0.022 -0.003 -0.003 -0.003 -0.003  0.022 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003  0.022  0.047 -0.003 -0.003  0.022  0.022 -0.003 -0.003 -0.003 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 1.001  0.004 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020  0.054 -0.020 -0.020 -0.020 -0.020  0.029 -0.020  0.004  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.004  0.029 -0.020  0.079  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004  0.054 
 0.999  0.002 -0.022  0.002 -0.022 -0.022 -0.022  0.002 -0.022  0.002  0.002 -0.022  0.002  0.027 -0.022  0.077 -0.022 -0.022 -0.022 -0.022  0.027 -0.022  0.002  0.002  0.002  0.002 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022  0.002 -0.022  0.002  0.002  0.027 -0.022  0.102  0.002  0.002 -0.022  0.002 -0.022 -0.022 -0.022  0.002  0.052 
 0.995 -0.001 -0.026 -0.001 -0.026 -0.026 -0.026 -0.001 -0.001 -0.001 -0.001 -0.026  0.048  0.023 -0.026  0.073 -0.026 -0.026 -0.001 -0.026  0.023 -0.026 -0.001 -0.001 -0.001 -0.001 -0.026 -0.026 -0.026 -0.026 -0.026 -0.026 -0.026 -0.026  0.023 -0.026 -0.001 -0.001  0.023 -0.026  0.098 -0.001 -0.001 -0.026 -0.001 -0.026 -0.026 -0.026 -0.001  0.048 
 0.985 -0.011 -0.036  0.013 -0.036  0.013 -0.036 -0.011 -0.011 -0.011 -0.011 -0.036  0.063  0.038 -0.011  0.063 -0.036 -0.011 -0.011 -0.011  0.013 -0.011 -0.011 -0.011 -0.011 -0.011 -0.036 -0.036 -0.036 -0.011 -0.036 -0.011  0.063 -0.011  0.088 -0.036  0.013 -0.011  0.013 -0.036  0.063 -0.011 -0.011 -0.011 -0.011 -0.036 -0.011 -0.011  0.038  0.038 
 0.978 -0.018 -0.043  0.006 -0.043  0.006 -0.043 -0.018 -0.018 -0.018 -0.018  0.006  0.056  0.031 -0.018  0.056 -0.043  0.006  0.006 -0.018  0.006 -0.018  0.006 -0.018  0.006 -0.018 -0.043  0.006 -0.018  0.006 -0.043 -0.018  0.056  0.006  0.106 -0.043  0.006 -0.018  0.031 -0.043  0.106 -0.018  0.006  0.006 -0.018 -0.043 -0.018  0.031  0.056  0.056 
 0.966 -0.031 -0.031 -0.006 -0.056 -0.006 -0.056 -0.006 -0.031 -0.006  0.019 -0.006  0.069  0.019 -0.006  0.044 -0.056  0.019  0.044 -0.006  0.019  0.019  0.044 -0.031  0.069 -0.031 -0.056  0.044 -0.031 -0.006 -0.031 -0.031  0.119  0.044  0.119 -0.031  0.019 -0.031  0.019 -0.056  0.293 -0.006  0.044  0.019 -0.006 -0.056 -0.006  0.019  0.069  0.094 
 0.940 -0.057 -0.057  0.068 -0.082 -0.032  0.018  0.043  0.018  0.043  0.093  0.018  0.068 -0.007  0.018  0.093 -0.007  0.018  0.167 -0.032  0.068  0.043  0.068 -0.007  0.093  0.093 -0.032  0.068 -0.057 -0.007 -0.082 -0.007  0.167  0.018  0.142 -0.057 -0.007  0.043 -0.007 -0.082  0.691 -0.057  0.093 -0.007  0.018 -0.057 -0.032  0.018  0.192  0.093 
 0.893 -0.079 -0.104  0.096 -0.104 -0.054  0.046  0.021  0.071  0.046  0.295  0.046  0.046  0.021  0.096  0.295  0.021  0.071  0.270 -0.029  0.096  0.021  0.170  0.046  0.046  0.121 -0.004  0.145 -0.079 -0.054 -0.129 -0.029  0.270  0.021  0.121 -0.054 -0.004  0.021 -0.054 -0.104  0.818  0.071  0.170 -0.004  0.021 -0.029 -0.029  0.021  0.270  0.245 
 0.853 -0.118 -0.118  0.056 -0.143 -0.018  0.156  0.006  0.031  0.031  0.355  0.056  0.031  0.006  0.181  0.405  0.031  0.081  0.305  0.006  0.256 -0.018  0.231  0.056  0.031  0.131  0.031  0.131 -0.118  0.031 -0.143 -0.068  0.355  0.031  0.081 -0.043 -0.018  0.056 -0.093 -0.118  0.804  0.156  0.156  0.006  0.081 -0.043 -0.068  0.006  0.405  0.455 
 0.801 -0.121 -0.121  0.079 -0.195 -0.071  0.228  0.004 -0.021 -0.021  0.403  0.104  0.079  0.029  0.353  0.702  0.029  0.054  0.303  0.004  0.203 -0.046  0.353  0.153  0.054  0.203  0.054  0.129 -0.121  0.054 -0.145 -0.121  0.378  0.178  0.054 -0.021  0.029  0.054 -0.145 -0.145  0.776  0.203  0.203 -0.046  0.178  0.004 -0.071 -0.046  0.477  0.627 
 0.782 -0.140 -0.115  0.085 -0.214 -0.115  0.209 -0.015 -0.040 -0.040  0.409  0.135  0.159  0.060  0.458  0.732  0.085  0.060  0.284 -0.015  0.159 -0.115  0.309  0.209  0.035  0.259  0.110  0.159 -0.140  0.085 -0.140 -0.189  0.359  0.259  0.035 -0.040  0.035  0.060 -0.164 -0.140  0.732  0.184  0.209 -0.040  0.184  0.110 -0.065 -0.040  0.458  0.658 
 0.739 -0.133 -0.133  0.117 -0.232 -0.108  0.216  0.042 -0.033 -0.033  0.366  0.142  0.142  0.092  0.490  0.714  0.092  0.067  0.241 -0.008  0.117 -0.133  0.316  0.316  0.042  0.391  0.117  0.216 -0.157  0.142 -0.182 -0.207  0.391  0.291 -0.008 -0.033  0.017  0.067 -0.157 -0.157  0.665  0.166  0.166 -0.058  0.291  0.117 -0.108 -0.033  0.490  0.665 
 0.726 -0.096 -0.145  0.129 -0.245 -0.121  0.203  0.029 -0.021  0.004  0.353  0.129  0.178  0.129  0.502  0.652  0.079  0.054  0.253 -0.021  0.104 -0.121  0.328  0.452  0.029  0.427  0.153  0.253 -0.170  0.129 -0.170 -0.220  0.378  0.278  0.004 -0.021  0.054  0.079 -0.170 -0.170  0.627  0.203  0.153 -0.071  0.303  0.104 -0.071 -0.071  0.477  0.677 
 0.691 -0.082 -0.156  0.217 -0.206 -0.132  0.142  0.018 -0.032  0.018  0.367  0.068  0.192  0.093  0.541  0.616  0.068 -0.007  0.217 -0.057  0.093 -0.132  0.317  0.491  0.068  0.566  0.142  0.317 -0.132  0.167 -0.181 -0.206  0.342  0.267 -0.007 -0.032  0.093  0.093 -0.181 -0.231  0.641  0.267  0.142 -0.082  0.292  0.093 -0.032 -0.057  0.466  0.666 
 0.685 -0.088 -0.162  0.211 -0.212 -0.113  0.137  0.012 -0.038  0.062  0.361  0.062  0.161  0.161  0.585  0.635  0.062 -0.013  0.211 -0.063  0.087 -0.138  0.311  0.510  0.062  0.610  0.137  0.311 -0.113  0.161 -0.138 -0.212  0.311  0.261  0.012 -0.013  0.087  0.037 -0.187 -0.237  0.635  0.261  0.161 -0.063  0.286  0.112 -0.013 -0.063  0.460  0.660 
 0.680 -0.117 -0.192  0.207 -0.217 -0.117  0.082 -0.017 -0.017  0.057  0.356  0.032  0.157  0.132  0.605  0.630  0.032 -0.042  0.207 -0.092  0.057 -0.142  0.331  0.556  0.082  0.605  0.182  0.306 -0.042  0.157 -0.117 -0.217  0.232  0.232  0.032  0.007  0.082  0.032 -0.192 -0.242  0.630  0.282  0.182 -0.067  0.232  0.107 -0.042 -0.067  0.431  0.605 
 0.678 -0.120 -0.219  0.204 -0.219 -0.120  0.055 -0.020 -0.020  0.055  0.304  0.005  0.130  0.154  0.603  0.628  0.005 -0.070  0.204 -0.120  0.030 -0.144  0.354  0.578  0.105  0.603  0.204  0.354 -0.020  0.154 -0.120 -0.219  0.179  0.229  0.055  0.080  0.080  0.005 -0.194 -0.244  0.628  0.279  0.204 -0.095  0.229  0.080 -0.020  0.030  0.428  0.578 
 0.678 -0.120 -0.219  0.204 -0.219 -0.095  0.080 -0.020 -0.045  0.055  0.304  0.005  0.154  0.130  0.603  0.628 -0.045 -0.095  0.204 -0.120  0.030 -0.144  0.379  0.578  0.154  0.603  0.204  0.354 -0.020  0.130 -0.095 -0.219  0.154  0.204  0.030  0.080  0.130  0.005 -0.169 -0.244  0.628  0.254  0.204 -0.095  0.229  0.080 -0.020  0.030  0.404  0.578 
 0.675 -0.123 -0.222  0.201 -0.222 -0.098  0.077  0.002 -0.073  0.027  0.301  0.002  0.151  0.151  0.600  0.600 -0.073 -0.098  0.226 -0.123  0.027 -0.147  0.376  0.575  0.176  0.600  0.226  0.351 -0.023  0.127 -0.098 -0.222  0.127  0.201  0.027  0.102  0.151  0.027 -0.147 -0.247  0.625  0.226  0.201 -0.098  0.226  0.077 -0.023  0.027  0.401  0.575 
 0.670 -0.127 -0.202  0.197 -0.202 -0.102  0.072  0.047 -0.052  0.022  0.296 -0.002  0.122  0.147  0.595  0.595 -0.077 -0.077  0.247 -0.127  0.022 -0.127  0.396  0.595  0.222  0.570  0.222  0.346 -0.027  0.122 -0.077 -0.202  0.097  0.197  0.022  0.147  0.147  0.047 -0.152 -0.252  0.620  0.222  0.197 -0.102  0.222  0.072 -0.002  0.022  0.396  0.570 
 0.380 -0.068 -0.143  0.206 -0.168 -0.018  0.081  0.081 -0.093  0.081  0.330  0.006  0.056  0.106  0.455  0.555 -0.043 -0.043  0.256 -0.118  0.006 -0.093  0.281  0.654  0.181  0.455  0.206  0.181 -0.018  0.031 -0.143 -0.168  0.131  0.231 -0.093  0.056  0.106  0.081 -0.118 -0.168  0.480  0.181  0.206 -0.068  0.156  0.106 -0.018 -0.018  0.305  0.430 
 0.212 -0.012 -0.137  0.212 -0.112  0.038  0.113 -0.062 -0.087  0.063  0.287  0.038  0.038  0.088  0.387  0.511 -0.012 -0.012  0.312 -0.062 -0.062 -0.062  0.138  0.536  0.088  0.387  0.262  0.138  0.013  0.063 -0.112 -0.112  0.063  0.162 -0.037  0.038  0.013  0.088 -0.062 -0.087  0.337  0.138  0.187 -0.012  0.138  0.088 -0.012 -0.062  0.237  0.412 
 0.206 -0.018 -0.118  0.206 -0.118  0.056  0.131 -0.068 -0.093  0.056  0.281  0.056  0.031  0.031  0.330  0.405 -0.018  0.006  0.330 -0.043 -0.068 -0.043  0.156  0.555  0.031  0.281  0.231  0.106  0.031  0.006 -0.093 -0.093  0.081  0.131 -0.043 -0.043  0.006  0.081 -0.043 -0.068  0.281  0.131  0.206 -0.018  0.156  0.081 -0.068 -0.068  0.131  0.430 
 0.138  0.013 -0.087  0.138 -0.087  0.063  0.113 -0.062 -0.062  0.088  0.237  0.038 -0.037 -0.012  0.212  0.237  0.013  0.013  0.287 -0.062 -0.062 -0.062  0.063  0.561 -0.037  0.287  0.212  0.113  0.013 -0.012 -0.062 -0.062  0.013  0.088 -0.062 -0.087  0.038  0.088 -0.037 -0.037  0.162  0.162  0.162 -0.037  0.162  0.038 -0.037 -0.037  0.013  0.287 
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 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 

 0.991  0.044 -0.005 -0.030 -0.030 -0.030 -0.005  0.019 -0.030 -0.005 -0.030 -0.005 -0.030 -0.005 -0.005 -0.005 -0.030 -0.030 -0.005 -0.030 -0.030 -0.005 -0.005 -0.030  0.019 -0.030 -0.005 -0.005 -0.005 -0.030  0.019  0.019 -0.030 -0.030 -0.005 -0.005 -0.030 -0.005 -0.005  0.044 -0.030  0.019 -0.005 -0.005  0.044  0.019 -0.005 -0.030 -0.005  0.019 
 0.995  0.024 -0.001 -0.026 -0.026 -0.026 -0.001 -0.001 -0.026 -0.001 -0.026 -0.001 -0.026 -0.026 -0.026 -0.001 -0.026 -0.026 -0.001 -0.026 -0.026 -0.001 -0.001 -0.026  0.024 -0.026 -0.001 -0.001 -0.001 -0.026  0.024  0.024 -0.026 -0.026 -0.026 -0.001 -0.026 -0.001 -0.001  0.024 -0.026  0.024 -0.001 -0.001  0.049  0.024 -0.001 -0.026 -0.026  0.024 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.001  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020  0.029  0.004  0.004  0.029  0.004  0.004 -0.020 -0.020  0.004 
 1.000  0.004  0.004 -0.021 -0.021 -0.021 -0.021  0.004 -0.021  0.004 -0.021  0.004 -0.021 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.004  0.004 -0.021 -0.021 -0.021  0.029 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021  0.004  0.004 -0.021  0.029  0.004  0.004  0.029  0.004  0.004 -0.021 -0.021  0.004 
 0.999  0.003  0.003 -0.022 -0.022 -0.022 -0.022  0.003 -0.022  0.003 -0.022  0.003 -0.022 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022  0.003  0.003 -0.022 -0.022 -0.022  0.028 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022  0.003  0.003 -0.022  0.028  0.003  0.003  0.028  0.003  0.003 -0.022 -0.022  0.003 
 0.999  0.003  0.003 -0.022 -0.022 -0.022 -0.022  0.003 -0.022  0.003 -0.022  0.003 -0.022 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022  0.003  0.003 -0.022 -0.022 -0.022  0.028 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022  0.003  0.003 -0.022  0.028  0.003  0.003  0.028  0.003  0.003 -0.022 -0.022  0.003 
 0.999  0.003  0.003 -0.022 -0.022 -0.022 -0.022  0.003 -0.022  0.003 -0.022  0.003 -0.022 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022 -0.022  0.003 -0.022  0.003  0.003 -0.022 -0.022 -0.022  0.028 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022  0.003  0.003 -0.022  0.028  0.003  0.003  0.028  0.003  0.003 -0.022 -0.022  0.003 
 0.996  0.000  0.025 -0.025 -0.025 -0.025 -0.025  0.000 -0.025  0.000  0.000  0.000 -0.025 -0.025 -0.025  0.000 -0.025 -0.025  0.000 -0.025 -0.025  0.000 -0.025 -0.025  0.000 -0.025  0.025  0.000 -0.025 -0.025 -0.025  0.025 -0.025 -0.025 -0.025  0.000 -0.025 -0.025  0.000  0.000 -0.025  0.025  0.075  0.000  0.050  0.000  0.025  0.000 -0.025  0.000 
 0.982 -0.014  0.085  0.035 -0.039  0.010 -0.014 -0.014 -0.039 -0.014 -0.014 -0.014 -0.039 -0.039 -0.014 -0.014 -0.039 -0.039 -0.014 -0.014 -0.039 -0.014 -0.039 -0.039 -0.014 -0.039  0.010  0.010 -0.014 -0.014 -0.039  0.060 -0.014 -0.039 -0.014  0.010 -0.039 -0.014  0.010  0.010 -0.039  0.010  0.185  0.010  0.035 -0.014  0.010  0.010  0.010 -0.014 
 0.956 -0.016  0.134  0.084 -0.041  0.109 -0.016  0.009 -0.066 -0.041 -0.041  0.034 -0.016 -0.041 -0.016  0.034 -0.041 -0.041 -0.016 -0.041 -0.066 -0.016 -0.041 -0.066 -0.041 -0.066 -0.016  0.034  0.009 -0.041 -0.041  0.034  0.034 -0.066  0.009  0.059 -0.016  0.009  0.034  0.009 -0.041  0.009  0.383  0.009  0.084 -0.016  0.009 -0.016 -0.016 -0.041 
 0.906  0.009  0.209  0.209 -0.040  0.234  0.034  0.034 -0.040 -0.065 -0.065  0.134 -0.040 -0.040 -0.040  0.059 -0.015  0.034  0.009  0.059 -0.115  0.034 -0.040 -0.015 -0.040 -0.090  0.034  0.034 -0.015 -0.065 -0.065  0.059  0.009 -0.040  0.059  0.034  0.084  0.059 -0.015  0.034 -0.015  0.009  0.732 -0.040  0.059 -0.040 -0.015  0.034 -0.065 -0.040 
 0.874  0.102  0.277  0.277 -0.047  0.227  0.052  0.052  0.027 -0.047 -0.072  0.177 -0.047 -0.072 -0.072  0.052 -0.022  0.027  0.027  0.202 -0.147  0.052 -0.047 -0.022 -0.047 -0.122  0.002  0.027  0.002 -0.097  0.052  0.027  0.002 -0.047  0.052  0.027  0.202  0.052 -0.022  0.027 -0.022  0.002  0.775 -0.047  0.052 -0.022  0.102  0.002 -0.097 -0.072 
 0.819  0.196  0.296  0.371 -0.078  0.346  0.072  0.122 -0.028 -0.103 -0.053  0.371 -0.078 -0.053 -0.028  0.047  0.097  0.072  0.072  0.346 -0.152  0.122 -0.053  0.146  0.097 -0.128  0.097  0.097 -0.003 -0.128  0.072 -0.028  0.047 -0.103  0.097  0.022  0.246  0.146  0.022 -0.028 -0.003 -0.003  0.819 -0.103  0.072  0.122  0.246  0.022 -0.152 -0.053 
 0.800  0.252  0.326  0.401 -0.097  0.351  0.077  0.127 -0.047 -0.122 -0.072  0.451 -0.097 -0.097 -0.047  0.052  0.077  0.077  0.102  0.401 -0.147  0.102 -0.072  0.177  0.127 -0.147  0.102  0.077  0.027 -0.147  0.077 -0.047  0.027 -0.122  0.102  0.052  0.252  0.127  0.027 -0.022  0.002 -0.022  0.800 -0.097  0.052  0.102  0.252  0.002 -0.172 -0.022 
 0.697  0.323  0.323  0.448 -0.125  0.323  0.074  0.149 -0.050 -0.150 -0.100  0.572 -0.050 -0.075 -0.050  0.174  0.149  0.049  0.074  0.548 -0.150  0.124 -0.050  0.174  0.174 -0.125  0.074  0.099 -0.000 -0.150  0.049 -0.075  0.049 -0.075  0.124  0.049  0.224  0.149  0.024 -0.075 -0.025 -0.050  0.772 -0.125  0.049  0.249  0.348 -0.025 -0.200  0.024 
 0.659  0.335  0.310  0.434 -0.163  0.310  0.160  0.160 -0.064 -0.163 -0.089  0.584 -0.039 -0.064 -0.039  0.210  0.185  0.036  0.111  0.559 -0.139  0.136 -0.014  0.185  0.185 -0.089  0.061  0.086 -0.014 -0.163  0.011 -0.064  0.011 -0.089  0.111  0.086  0.210  0.136  0.011 -0.064 -0.039 -0.064  0.758 -0.139  0.061  0.335  0.509 -0.014 -0.213  0.036 
 0.596  0.422  0.297  0.422 -0.151  0.297  0.172  0.172 -0.077 -0.151 -0.052  0.571 -0.027 -0.052 -0.052  0.197  0.172  0.023  0.098  0.596 -0.151  0.147 -0.027  0.172  0.247 -0.102  0.073  0.098 -0.027 -0.151  0.023 -0.077 -0.002 -0.102  0.098  0.147  0.222  0.247 -0.027 -0.052 -0.052 -0.077  0.720 -0.151  0.048  0.347  0.571 -0.002 -0.226  0.048 
 0.541  0.416  0.291  0.441 -0.157  0.291  0.267  0.167 -0.082 -0.182 -0.057  0.566 -0.032 -0.057 -0.057  0.192  0.167  0.017  0.117  0.566 -0.157  0.117  0.017  0.167  0.242 -0.082  0.117  0.092 -0.057 -0.157  0.042 -0.082 -0.007 -0.082  0.092  0.167  0.217  0.242 -0.032 -0.032 -0.032 -0.057  0.715 -0.157  0.042  0.341  0.590 -0.007 -0.232  0.092 
 0.511  0.436  0.286  0.461 -0.162  0.286  0.262  0.162 -0.087 -0.187 -0.062  0.561 -0.037 -0.062 -0.062  0.187  0.162 -0.012  0.137  0.536 -0.137  0.112  0.012  0.162  0.262 -0.062  0.112  0.112 -0.037 -0.162  0.062 -0.112 -0.012 -0.087  0.087  0.162  0.212  0.286 -0.037 -0.037 -0.037 -0.062  0.710 -0.162  0.037  0.361  0.585 -0.037 -0.237  0.087 
 0.510  0.410  0.261  0.460 -0.163  0.285  0.261  0.186 -0.088 -0.188 -0.063  0.560 -0.013 -0.088 -0.063  0.186  0.161 -0.013  0.136  0.510 -0.138  0.111  0.011  0.161  0.261 -0.063  0.136  0.111 -0.038 -0.163  0.061 -0.113 -0.013 -0.088  0.061  0.161  0.211  0.285 -0.013 -0.038 -0.063 -0.063  0.709 -0.138  0.061  0.385  0.584 -0.038 -0.213  0.111 
 0.505  0.405  0.281  0.430 -0.168  0.281  0.305  0.231 -0.093 -0.193 -0.068  0.555 -0.043 -0.018 -0.068  0.206  0.181 -0.018  0.131  0.505 -0.143  0.106  0.006  0.181  0.281 -0.068  0.131  0.106 -0.043 -0.168  0.031 -0.118 -0.018 -0.093  0.056  0.156  0.231  0.355  0.006 -0.068 -0.068 -0.093  0.704 -0.143  0.081  0.455  0.579 -0.043 -0.218  0.131 
 0.482  0.383  0.283  0.457 -0.165  0.283  0.308  0.233 -0.091 -0.190 -0.066  0.557 -0.041 -0.016 -0.041  0.183  0.183 -0.016  0.109  0.507 -0.165  0.109  0.009  0.208  0.283 -0.066  0.158  0.084 -0.041 -0.165  0.059 -0.116  0.009 -0.091  0.059  0.183  0.208  0.333  0.034 -0.091 -0.066 -0.116  0.707 -0.165  0.084  0.482  0.557 -0.041 -0.215  0.084 
 0.452  0.353  0.228  0.452 -0.195  0.278  0.303  0.228 -0.071 -0.195 -0.071  0.552 -0.046  0.004 -0.021  0.178  0.203 -0.021  0.079  0.502 -0.170  0.104  0.029  0.253  0.303 -0.071  0.253  0.104 -0.046 -0.145  0.029 -0.121  0.004 -0.096  0.054  0.228  0.178  0.353  0.004 -0.071 -0.071 -0.121  0.726 -0.170  0.079  0.527  0.552 -0.021 -0.195  0.054 
 0.374  0.249  0.299  0.399 -0.199  0.199  0.174  0.224 -0.025 -0.125  0.000  0.548 -0.025  0.000 -0.100  0.100  0.224  0.050  0.075  0.548 -0.125  0.149  0.025  0.299  0.299 -0.075  0.249  0.125 -0.075 -0.100  0.000 -0.125  0.000 -0.050  0.075  0.199  0.149  0.349  0.000 -0.025 -0.050 -0.100  0.747 -0.174  0.050  0.374  0.498 -0.050 -0.149 -0.025 
 0.280  0.280  0.230  0.379 -0.119  0.205  0.080  0.130  0.030 -0.044  0.005  0.479 -0.044 -0.019 -0.044  0.130  0.255  0.080  0.005  0.529 -0.119  0.130  0.055  0.255  0.180 -0.044  0.205  0.080 -0.019 -0.044 -0.019 -0.094  0.030 -0.044  0.080  0.055  0.155  0.230 -0.069 -0.094 -0.044 -0.044  0.828 -0.094  0.080  0.304  0.304  0.005 -0.094 -0.044 
 0.207  0.307  0.207  0.357 -0.092  0.232  0.058  0.157  0.033 -0.017  0.033  0.431 -0.017 -0.042 -0.042  0.108  0.232  0.108  0.008  0.506 -0.092  0.108  0.083  0.207  0.108 -0.017  0.108  0.108 -0.017 -0.017  0.008 -0.067  0.033 -0.067  0.083  0.058  0.182  0.232 -0.067 -0.067 -0.042 -0.017  0.855 -0.067  0.108  0.232  0.207 -0.017 -0.067 -0.042 
 0.188  0.238  0.213  0.313 -0.061  0.163  0.039  0.114  0.064 -0.036  0.014  0.288  0.014 -0.011 -0.011  0.139  0.213  0.139 -0.011  0.462 -0.061  0.089  0.039  0.188  0.014 -0.036  0.064  0.039  0.014 -0.036  0.039 -0.061  0.014 -0.086  0.114  0.089  0.163  0.213 -0.061 -0.061 -0.036  0.014  0.911 -0.061  0.114  0.139  0.139 -0.011 -0.036 -0.036 
 0.105  0.130  0.229  0.329 -0.045  0.154  0.055  0.105  0.080 -0.020  0.030  0.204  0.030 -0.020  0.005  0.130  0.130  0.130  0.005  0.428 -0.045  0.080  0.005  0.154 -0.020 -0.045  0.055  0.055  0.005 -0.020  0.055 -0.045  0.030 -0.070  0.105  0.055  0.179  0.229 -0.045 -0.045 -0.045  0.030  0.927 -0.020  0.055  0.055  0.105  0.005 -0.020 -0.020 
 0.029  0.079  0.179  0.204 -0.020  0.079  0.029  0.054  0.029 -0.020  0.029  0.129  0.029  0.004  0.029  0.104  0.079  0.129  0.029  0.453 -0.020  0.029  0.004  0.079 -0.020 -0.020  0.054  0.029 -0.020  0.004  0.079 -0.020  0.029 -0.045  0.104  0.054  0.129  0.229 -0.020 -0.020 -0.020  0.029  0.976  0.004 -0.020 -0.045  0.054  0.029  0.004 -0.020 
 0.016  0.041  0.141  0.041 -0.009  0.066  0.016  0.066  0.041 -0.009  0.041  0.091  0.016  0.016  0.016  0.016  0.016  0.091  0.041  0.340 -0.009 -0.009  0.016  0.066 -0.009 -0.034  0.066  0.016 -0.009  0.016  0.041 -0.009 -0.009 -0.034  0.091  0.066  0.141  0.116 -0.009 -0.009 -0.009  0.041  0.988  0.016 -0.009 -0.034  0.041  0.041 -0.009 -0.009 
 0.003  0.028  0.053 -0.022 -0.022  0.053  0.028  0.078  0.003  0.003  0.053  0.078  0.028  0.003  0.028 -0.022 -0.022  0.053  0.053  0.128  0.003  0.003  0.028  0.053 -0.022 -0.022  0.028  0.028  0.003  0.028  0.028 -0.022  0.003 -0.022  0.053  0.078  0.028  0.003 -0.022  0.003  0.003  0.028  0.999 -0.022 -0.022 -0.022  0.028  0.028 -0.022  0.003 
 0.004  0.029  0.054 -0.021 -0.021  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.029  0.004  0.029 -0.021 -0.021  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.021 -0.021  0.029  0.029  0.004  0.029  0.029 -0.021  0.004 -0.021  0.054  0.079  0.029  0.004 -0.021  0.004  0.004  0.029  1.000 -0.021 -0.021 -0.021  0.029  0.029 -0.021  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.004  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029  1.001 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.019  0.019  0.119 -0.005 -0.030  0.069  0.044  0.094 -0.005  0.044  0.094  0.069  0.019 -0.005  0.019 -0.030 -0.030  0.044  0.044  0.244 -0.005 -0.005  0.019  0.069 -0.005 -0.030  0.144  0.044  0.044  0.019  0.019 -0.030 -0.005 -0.030  0.069  0.094  0.069  0.069 -0.005 -0.005 -0.005  0.069  0.991 -0.005 -0.005 -0.030  0.019  0.044 -0.005 -0.005 
 0.009  0.034  0.283  0.009 -0.041  0.183  0.084  0.283  0.034  0.109  0.109  0.059 -0.016 -0.041  0.034 -0.066  0.059  0.034  0.034  0.582 -0.016 -0.041 -0.016  0.084 -0.041 -0.041  0.283  0.059  0.009  0.158  0.109 -0.066 -0.041 -0.066  0.134  0.158  0.158  0.134 -0.041  0.009 -0.016  0.134  0.956 -0.041  0.059 -0.016  0.059  0.059  0.009  0.034 
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-0.014  0.061  0.758  0.185  0.036  0.335  0.434  0.559  0.136  0.160  0.310  0.086  0.011 -0.014  0.011  0.210  0.260  0.160 -0.039  0.808  0.061  0.061  0.111  0.410  0.011 -0.014  0.509  0.160 -0.064  0.185  0.086 -0.064  0.011 -0.139  0.260  0.335  0.310  0.310 -0.064 -0.064 -0.014  0.185  0.833 -0.114  0.160 -0.089  0.061  0.086  0.011  0.185 
 0.026  0.051  0.748  0.275  0.051  0.325  0.425  0.599  0.200  0.150  0.375  0.150  0.001 -0.024  0.026  0.250  0.350  0.150  0.001  0.773  0.126  0.101  0.175  0.474  0.001 -0.049  0.549  0.126 -0.049  0.300  0.101 -0.074 -0.024 -0.099  0.350  0.400  0.275  0.300 -0.049 -0.074 -0.024  0.150  0.798 -0.099  0.225 -0.049  0.150  0.076  0.026  0.200 
-0.007  0.093  0.691  0.466  0.068  0.367  0.392  0.616  0.242  0.217  0.441  0.167  0.043  0.043  0.118  0.342  0.491  0.167  0.018  0.740  0.142  0.142  0.192  0.466 -0.007 -0.032  0.541  0.093 -0.082  0.367  0.217 -0.082  0.043 -0.057  0.392  0.417  0.292  0.317 -0.057 -0.107 -0.007  0.267  0.765 -0.107  0.317  0.093  0.142  0.043  0.068  0.292 
-0.017  0.083  0.656  0.531  0.058  0.407  0.357  0.606  0.257  0.257  0.456  0.157  0.083  0.083  0.133  0.357  0.531  0.157  0.008  0.730  0.133  0.133  0.207  0.481  0.008 -0.017  0.407  0.083 -0.067  0.357  0.257 -0.092  0.058 -0.042  0.431  0.382  0.332  0.357 -0.042 -0.117  0.058  0.282  0.755 -0.092  0.357  0.157  0.157  0.058  0.083  0.332 
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 1.001 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.054  0.004 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029 -0.020  0.004  0.054  0.029  0.004 
 1.001 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.054  0.004 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029 -0.020  0.004  0.054  0.029  0.004 
 1.001 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.054  0.004 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029 -0.020  0.004  0.054  0.029  0.004 
 1.001 -0.020 -0.020 -0.020  0.054  0.004 -0.020  0.054  0.004 -0.020  0.004  0.004 -0.020  0.029  0.004 -0.020  0.004  0.029  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.004 -0.020  0.029  0.004  0.054  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029 -0.020  0.004  0.054  0.029  0.004 
 0.997 -0.024 -0.024 -0.024  0.051  0.001 -0.024  0.076  0.001 -0.024  0.026  0.001 -0.024  0.026  0.001 -0.024  0.026  0.026  0.001  0.051 -0.024  0.001 -0.024  0.001 -0.024  0.001 -0.024  0.001 -0.024  0.026  0.001  0.051  0.001  0.001 -0.024  0.001  0.026 -0.024 -0.024  0.051  0.026  0.026  0.001  0.026  0.026  0.001  0.001  0.051  0.076  0.026 
 0.981 -0.015  0.034 -0.040  0.134  0.059 -0.015  0.109  0.034  0.034  0.009 -0.015 -0.040  0.034  0.009 -0.015  0.009  0.059 -0.015  0.084 -0.040 -0.015 -0.040 -0.015  0.009  0.009 -0.040  0.009 -0.040  0.109  0.034  0.059 -0.015 -0.015 -0.040  0.009  0.009 -0.040 -0.015  0.059  0.034  0.009  0.034  0.084  0.034 -0.015 -0.015  0.084  0.383  0.009 
 0.964 -0.008  0.067 -0.033  0.142  0.067 -0.033  0.092  0.042  0.092  0.092 -0.033 -0.058  0.042 -0.008 -0.008 -0.008  0.067 -0.008  0.191 -0.058 -0.033 -0.058  0.017  0.017 -0.008 -0.033 -0.008 -0.033  0.142  0.017  0.067 -0.033 -0.033 -0.058 -0.008 -0.008 -0.033 -0.008  0.042  0.117  0.042  0.067  0.142  0.017 -0.008 -0.008  0.067  0.565  0.042 
 0.906  0.009  0.184 -0.040  0.308  0.059  0.009  0.209  0.134  0.234  0.358 -0.040 -0.090  0.034 -0.040  0.034 -0.015  0.259 -0.040  0.458 -0.090  0.009 -0.090  0.034  0.009  0.009 -0.065 -0.040 -0.065  0.209  0.184  0.084 -0.015  0.059 -0.040 -0.040  0.059  0.059  0.009  0.109  0.159  0.009  0.084  0.308 -0.040 -0.065 -0.040  0.109  0.881  0.284 
 0.859  0.087  0.386 -0.013  0.336  0.037  0.062  0.286  0.211  0.311  0.510 -0.088 -0.088  0.012 -0.088  0.087 -0.038  0.435  0.037  0.710 -0.113  0.112 -0.113 -0.013  0.062  0.012 -0.038 -0.063 -0.063  0.186  0.361  0.062 -0.013  0.062 -0.038 -0.088  0.062  0.137  0.062  0.137  0.236  0.087  0.112  0.386 -0.088 -0.113 -0.038  0.137  0.834  0.460 
 0.791  0.119  0.442  0.094  0.467  0.044  0.044  0.343  0.218  0.692  0.766 -0.081 -0.106 -0.031 -0.056  0.243 -0.081  0.642  0.119  0.741 -0.106  0.094 -0.131  0.143 -0.006  0.019  0.019  0.019 -0.106  0.119  0.467  0.069  0.069  0.168 -0.006 -0.131  0.044  0.193 -0.006  0.143  0.368  0.318  0.193  0.492 -0.131 -0.155 -0.006  0.119  0.741  0.642 
 0.769  0.171  0.495  0.121  0.545  0.071  0.096  0.395  0.221  0.719  0.744 -0.053 -0.103 -0.053  0.021  0.320 -0.078  0.694  0.121  0.719 -0.153  0.046 -0.103  0.171 -0.053  0.046  0.071  0.046 -0.053  0.121  0.520  0.071  0.121  0.171 -0.003 -0.128  0.021  0.196  0.046  0.096  0.420  0.395  0.196  0.520 -0.128 -0.153 -0.028  0.146  0.719  0.644 
 0.721  0.198  0.597  0.173  0.522  0.049  0.124  0.398  0.248  0.746  0.697 -0.051 -0.126 -0.026  0.049  0.398 -0.051  0.746  0.173  0.672 -0.175 -0.001 -0.101  0.223 -0.126  0.049  0.024  0.074 -0.051  0.074  0.522  0.024  0.198  0.198  0.049 -0.150  0.049  0.248  0.049  0.099  0.398  0.547  0.198  0.522 -0.126 -0.175 -0.026  0.198  0.697  0.647 
 0.712  0.189  0.612  0.139  0.513  0.014  0.139  0.413  0.338  0.737  0.687 -0.035 -0.110 -0.035  0.139  0.438 -0.035  0.737  0.164  0.637 -0.160 -0.035 -0.085  0.239 -0.135  0.039  0.064  0.114 -0.060  0.064  0.513  0.014  0.214  0.239  0.064 -0.085  0.039  0.264  0.014  0.164  0.388  0.563  0.189  0.488 -0.085 -0.160 -0.060  0.239  0.662  0.637 
 0.705  0.157  0.630  0.157  0.456 -0.017  0.157  0.456  0.331  0.730  0.655 -0.017 -0.117 -0.042  0.157  0.456  0.057  0.730  0.157  0.556 -0.117 -0.067 -0.092  0.207 -0.142  0.057  0.007  0.082 -0.017  0.082  0.531  0.007  0.207  0.257  0.082 -0.092  0.007  0.282  0.007  0.207  0.406  0.605  0.182  0.481 -0.042 -0.117 -0.117  0.257  0.655  0.605 
 0.698  0.149  0.648  0.199  0.448  0.025  0.174  0.473  0.399  0.722  0.648 -0.025 -0.100 -0.025  0.174  0.424  0.100  0.722  0.174  0.523 -0.149 -0.050 -0.100  0.199 -0.149  0.050  0.025  0.075  0.050  0.075  0.573  0.000  0.199  0.249  0.100 -0.050  0.000  0.324 -0.025  0.249  0.399  0.598  0.174  0.473  0.000 -0.100 -0.125  0.224  0.573  0.598 
 0.660  0.162  0.660  0.237  0.436  0.062  0.237  0.511  0.411  0.710  0.635  0.012 -0.112 -0.087  0.187  0.411  0.112  0.710  0.187  0.511 -0.137 -0.062 -0.037  0.187 -0.187  0.062  0.037  0.062  0.237  0.062  0.610  0.037  0.187  0.262  0.112  0.037 -0.012  0.411 -0.062  0.286  0.336  0.585  0.212  0.461  0.062 -0.087 -0.162  0.212  0.511  0.585 
 0.654  0.155  0.704  0.205  0.429  0.106  0.230  0.554  0.429  0.704  0.629  0.031 -0.094 -0.094  0.180  0.405  0.106  0.704  0.180  0.504 -0.143 -0.069 -0.044  0.180 -0.193  0.056  0.031  0.106  0.280  0.081  0.604  0.031  0.230  0.305  0.106  0.031 -0.019  0.405 -0.069  0.355  0.330  0.579  0.230  0.454  0.056 -0.094 -0.168  0.205  0.479  0.579 
 0.646  0.148  0.646  0.223  0.447  0.098  0.297  0.547  0.472  0.696  0.621  0.023 -0.101 -0.126  0.198  0.397  0.123  0.696  0.173  0.472 -0.126 -0.026 -0.026  0.173 -0.176  0.073  0.023  0.123  0.322  0.073  0.621  0.023  0.248  0.372  0.123  0.073 -0.026  0.447 -0.076  0.447  0.322  0.571  0.248  0.447  0.048 -0.101 -0.176  0.198  0.422  0.571 
 0.643  0.170  0.593  0.220  0.469  0.095  0.294  0.568  0.469  0.693  0.618  0.020 -0.079 -0.129  0.220  0.394  0.170  0.693  0.170  0.469 -0.129 -0.029 -0.004  0.170 -0.179  0.095  0.020  0.120  0.344  0.070  0.618  0.020  0.245  0.369  0.120  0.095 -0.029  0.469 -0.079  0.469  0.319  0.568  0.220  0.444  0.095 -0.104 -0.179  0.195  0.419  0.568 
 0.644  0.170  0.569  0.220  0.494  0.071  0.295  0.569  0.469  0.644  0.619  0.021 -0.029 -0.129  0.270  0.420  0.195  0.694  0.170  0.444 -0.129 -0.004 -0.029  0.170 -0.178  0.096  0.021  0.121  0.420  0.046  0.619  0.021  0.220  0.370  0.121  0.145 -0.029  0.469 -0.079  0.494  0.270  0.569  0.195  0.420  0.121 -0.129 -0.178  0.195  0.395  0.569 
 0.617  0.169  0.543  0.219  0.493  0.069  0.293  0.543  0.468  0.642  0.617  0.019 -0.030 -0.130  0.269  0.418  0.194  0.692  0.169  0.443 -0.130  0.019 -0.030  0.169 -0.180  0.094  0.019  0.119  0.468  0.019  0.617  0.019  0.244  0.368  0.119  0.169 -0.030  0.468 -0.080  0.543  0.269  0.568  0.169  0.443  0.119 -0.130 -0.180  0.169  0.393  0.568 
 0.614  0.165  0.514  0.240  0.539 -0.009  0.290  0.514  0.464  0.614  0.614  0.016  0.041 -0.134  0.315  0.439  0.190  0.689  0.165  0.439 -0.134  0.016 -0.009  0.165 -0.183  0.066 -0.009  0.116  0.514  0.016  0.614  0.016  0.290  0.365  0.141  0.165  0.016  0.464 -0.059  0.539  0.265  0.539  0.165  0.439  0.116 -0.134 -0.183  0.190  0.340  0.564 
 0.611  0.162  0.511  0.237  0.561 -0.012  0.337  0.511  0.461  0.611  0.611  0.013  0.088 -0.137  0.337  0.436  0.187  0.686  0.162  0.436 -0.137  0.063  0.038  0.138 -0.186  0.063 -0.012  0.138  0.511  0.013  0.611  0.013  0.312  0.362  0.187  0.187  0.088  0.486 -0.062  0.536  0.262  0.561  0.162  0.436  0.113 -0.137 -0.186  0.187  0.287  0.561 
 0.609  0.161  0.535  0.236  0.584 -0.013  0.335  0.510  0.460  0.609  0.609  0.086  0.086 -0.138  0.360  0.435  0.211  0.684  0.161  0.435 -0.138  0.086  0.086  0.111 -0.188  0.086 -0.013  0.136  0.510  0.011  0.609 -0.013  0.335  0.385  0.211  0.211  0.136  0.510 -0.038  0.535  0.261  0.535  0.161  0.435  0.111 -0.088 -0.188  0.161  0.261  0.560 
 0.641  0.192  0.491  0.242  0.516  0.018  0.267  0.466  0.317  0.566  0.666  0.043  0.093 -0.107  0.292  0.466  0.242  0.691  0.167  0.441 -0.107  0.043 -0.032  0.118 -0.132 -0.007 -0.007  0.118  0.541 -0.007  0.566 -0.007  0.317  0.317  0.192  0.192  0.093  0.441 -0.032  0.466  0.267  0.591  0.192  0.417  0.093 -0.082 -0.107  0.242  0.118  0.491 
 0.669  0.145  0.494  0.245  0.295  0.021  0.145  0.395  0.220  0.494  0.644  0.021 -0.029 -0.029  0.170  0.420  0.295  0.718  0.170  0.444 -0.054  0.021 -0.104  0.071 -0.129  0.071  0.046  0.021  0.370  0.021  0.594  0.046  0.145  0.320  0.170  0.096  0.071  0.370 -0.104  0.295  0.245  0.569  0.145  0.295  0.046 -0.079 -0.079  0.145  0.145  0.420 
 0.665  0.117  0.490  0.216  0.291  0.042  0.142  0.316  0.241  0.490  0.590  0.017 -0.033 -0.058  0.166  0.440  0.216  0.764  0.142  0.465 -0.033  0.017 -0.108 -0.008 -0.108  0.042  0.017 -0.008  0.241  0.017  0.590  0.092  0.117  0.316  0.166 -0.008  0.042  0.341 -0.083  0.166  0.241  0.565  0.092  0.316  0.042 -0.058 -0.058  0.166  0.166  0.416 
 0.688  0.090  0.414  0.239  0.264  0.065  0.090  0.214  0.189  0.538  0.638 -0.010 -0.035 -0.035  0.140  0.414  0.164  0.787  0.065  0.389 -0.035 -0.035 -0.085 -0.060 -0.085 -0.010  0.015 -0.085  0.065  0.015  0.588  0.065 -0.035  0.164  0.115 -0.010  0.090  0.339 -0.060  0.065  0.214  0.638  0.065  0.264 -0.010 -0.010 -0.035  0.115  0.140  0.414 
 0.593  0.070  0.319  0.244  0.269  0.070  0.070  0.219  0.169  0.543  0.717 -0.005 -0.030 -0.030  0.120  0.443  0.120  0.767 -0.030  0.394 -0.055 -0.030 -0.080 -0.030 -0.080 -0.005  0.045 -0.080  0.020 -0.005  0.568  0.070 -0.030  0.144  0.095 -0.005  0.095  0.319 -0.055  0.020  0.219  0.668  0.095  0.194 -0.030 -0.005 -0.030  0.070  0.144  0.443 
 0.428  0.080  0.279  0.179  0.229  0.080  0.080  0.179  0.130  0.453  0.802  0.005 -0.045 -0.020  0.105  0.453  0.105  0.802 -0.020  0.379 -0.045 -0.020 -0.070 -0.020 -0.070 -0.020  0.055 -0.045  0.005 -0.020  0.578  0.055 -0.020  0.080  0.080  0.005  0.105  0.304 -0.045 -0.045  0.179  0.727  0.080  0.154 -0.020  0.005 -0.070 -0.020  0.130  0.428 
 0.359  0.085  0.259  0.159  0.209  0.060  0.085  0.135  0.135  0.384  0.807 -0.015 -0.065 -0.015  0.085  0.433  0.110  0.807 -0.015  0.359 -0.040 -0.015 -0.065 -0.015 -0.065 -0.015  0.060 -0.040  0.010 -0.015  0.583  0.035 -0.015  0.060  0.085 -0.015  0.110  0.284 -0.040 -0.065  0.184  0.732  0.085  0.159 -0.065 -0.015 -0.065 -0.015  0.135  0.433 
 0.245  0.045  0.170  0.120  0.145  0.020  0.070  0.120  0.120  0.270  0.818 -0.004 -0.079 -0.004  0.095  0.319  0.070  0.867 -0.029  0.294 -0.029 -0.004 -0.054  0.020 -0.054 -0.004  0.070 -0.054  0.020 -0.004  0.593  0.020 -0.004  0.045  0.070 -0.029  0.120  0.245 -0.029 -0.054  0.170  0.793  0.120  0.120 -0.054 -0.004 -0.054 -0.004  0.070  0.369 
 0.099  0.024  0.149  0.074  0.074  0.024  0.074  0.124 -0.000  0.224  0.847 -0.025 -0.075 -0.000  0.049  0.274  0.049  0.946 -0.025  0.298 -0.025 -0.000 -0.050  0.024 -0.050 -0.000  0.074 -0.050  0.024 -0.000  0.597  0.024 -0.025  0.049  0.074 -0.050  0.124  0.249 -0.000 -0.025  0.149  0.797  0.124  0.099 -0.025 -0.000 -0.050  0.024  0.049  0.348 
 0.079  0.029  0.079  0.079  0.079  0.004  0.004  0.129  0.004  0.204  0.901 -0.020 -0.070  0.004  0.004  0.179  0.054  0.951 -0.020  0.279 -0.045  0.004 -0.045  0.054 -0.045  0.004  0.029 -0.045  0.004  0.029  0.602  0.029 -0.020  0.054  0.054 -0.070  0.129  0.204  0.004 -0.020  0.129  0.852  0.129  0.079 -0.020 -0.020 -0.045  0.029  0.004  0.204 
 0.081  0.031  0.081  0.056  0.081  0.006  0.006  0.131  0.006  0.181  0.928 -0.018 -0.068 -0.018 -0.018  0.131  0.056  0.953 -0.018  0.256 -0.043  0.006 -0.043  0.056 -0.043  0.006  0.031 -0.043  0.006  0.031  0.579  0.031 -0.018  0.056  0.056 -0.068  0.131  0.206  0.006 -0.018  0.081  0.853  0.131  0.081 -0.018 -0.018 -0.018  0.031  0.006  0.131 
 0.059  0.034  0.059  0.034  0.084  0.034  0.009  0.109  0.009  0.183  0.956 -0.016 -0.066 -0.016 -0.016  0.084  0.034  0.956 -0.016  0.183 -0.016 -0.016 -0.041  0.059 -0.066  0.034  0.034 -0.016  0.009  0.034  0.532  0.059 -0.016  0.059  0.059 -0.066  0.084  0.158 -0.016 -0.016  0.084  0.906  0.134  0.059 -0.016 -0.016 -0.016  0.034 -0.041  0.109 
 0.038  0.013  0.063 -0.012  0.063  0.013  0.013  0.113  0.013  0.187  0.960 -0.012 -0.037 -0.012 -0.012  0.088  0.038  0.960 -0.012  0.138 -0.012 -0.012 -0.037  0.063 -0.062  0.038  0.038 -0.012  0.013  0.038  0.312  0.063 -0.012  0.063  0.063 -0.062  0.088  0.162 -0.012 -0.012  0.088  0.935  0.113  0.038 -0.012 -0.012 -0.012  0.038 -0.037  0.063 
 0.017  0.017  0.067 -0.007  0.042 -0.007  0.017  0.067  0.017  0.167  0.964 -0.007 -0.032 -0.007 -0.007  0.092  0.042  0.964 -0.007  0.117 -0.007 -0.007 -0.032  0.067 -0.057  0.042  0.042 -0.007 -0.007  0.017  0.117  0.067 -0.007  0.067  0.042 -0.057  0.067  0.117 -0.007 -0.007  0.092  0.939  0.117  0.042 -0.032 -0.007 -0.007  0.042 -0.032  0.067 
 0.017  0.017  0.067 -0.007  0.042 -0.007  0.017  0.042 -0.007  0.167  0.964 -0.007 -0.032 -0.007 -0.007  0.092  0.042  0.964 -0.007  0.117 -0.007 -0.007 -0.032  0.067 -0.057  0.042  0.042 -0.007 -0.007  0.017  0.092  0.067 -0.007  0.067  0.042 -0.057  0.067  0.117 -0.007 -0.007  0.092  0.964  0.092  0.042 -0.032 -0.007 -0.007  0.042 -0.032  0.067 
 0.019  0.019  0.044 -0.005  0.019 -0.005  0.019  0.044 -0.030  0.169  0.966 -0.005 -0.030 -0.005 -0.005  0.094  0.044  0.966 -0.005  0.094 -0.005 -0.005 -0.030  0.069 -0.055  0.044  0.044 -0.005 -0.005  0.019 -0.005  0.044 -0.005  0.069  0.044 -0.055  0.044  0.094 -0.005 -0.005  0.094  0.966  0.094  0.044 -0.030 -0.005 -0.030  0.044 -0.030  0.069 
 0.019  0.019  0.044 -0.005  0.019 -0.005  0.019  0.044 -0.030  0.169  0.966 -0.005 -0.030 -0.005 -0.005  0.094  0.044  0.966 -0.005  0.094 -0.005 -0.005 -0.030  0.069 -0.055  0.044  0.044 -0.005 -0.005  0.019 -0.005  0.044 -0.005  0.069  0.044 -0.055  0.044  0.094 -0.005 -0.005  0.094  0.966  0.094  0.044 -0.030 -0.005 -0.030  0.044 -0.030  0.069 
 0.019  0.019  0.044 -0.005  0.019 -0.005  0.019  0.044 -0.030  0.169  0.966 -0.005 -0.030 -0.005 -0.005  0.094  0.044  0.966 -0.005  0.094 -0.005 -0.005 -0.030  0.069 -0.055  0.044  0.044 -0.005 -0.005  0.019 -0.005  0.044 -0.005  0.069  0.044 -0.055  0.044  0.094 -0.005 -0.005  0.094  0.966  0.094  0.044 -0.030 -0.005 -0.030  0.044 -0.030  0.069 
 0.019  0.019  0.044 -0.005  0.019 -0.005  0.019  0.044 -0.030  0.169  0.966 -0.005 -0.030 -0.005 -0.005  0.094  0.044  0.966 -0.005  0.094 -0.005 -0.005 -0.030  0.069 -0.055  0.044  0.044 -0.005 -0.005  0.019 -0.005  0.044 -0.005  0.069  0.044 -0.055  0.044  0.094 -0.005 -0.005  0.094  0.966  0.094  0.044 -0.030 -0.005 -0.030  0.044 -0.030  0.069 
 0.019  0.019  0.044 -0.005  0.019 -0.005  0.019  0.044 -0.030  0.169  0.966 -0.005 -0.030 -0.005 -0.005  0.094  0.044  0.966 -0.005  0.094 -0.005 -0.005 -0.030  0.069 -0.055  0.044  0.044 -0.005 -0.005  0.019 -0.005  0.044 -0.005  0.069  0.044 -0.055  0.044  0.094 -0.005 -0.005  0.094  0.966  0.094  0.044 -0.030 -0.005 -0.030  0.044 -0.030  0.069 
 0.019  0.019  0.119  0.019  0.119 -0.031 -0.006  0.069  0.019  0.368  0.941 -0.006 -0.031 -0.006 -0.031  0.268  0.044  0.941 -0.031  0.119  0.019 -0.006 -0.031  0.044 -0.081  0.019  0.044 -0.006  0.019  0.019  0.119  0.019 -0.031  0.119  0.094 -0.081  0.094  0.168 -0.031 -0.031  0.243  0.941  0.094  0.069 -0.056 -0.031 -0.031  0.069 -0.031  0.143 
 0.132  0.032  0.281  0.281  0.181 -0.018  0.032  0.132  0.082  0.630  0.879  0.007 -0.018 -0.043  0.107  0.430  0.082  0.879  0.007  0.306 -0.018 -0.018 -0.093  0.107 -0.142  0.057  0.107  0.007  0.007  0.032  0.406  0.057 -0.043  0.156  0.082 -0.118  0.132  0.331 -0.043 -0.043  0.331  0.879  0.132  0.181 -0.093 -0.068 -0.093  0.132 -0.018  0.381 
 0.219  0.045  0.394  0.344  0.319 -0.005  0.070  0.169  0.144  0.717  0.842  0.020  0.020 -0.055  0.169  0.493  0.095  0.842  0.045  0.419 -0.005 -0.030 -0.105  0.120 -0.154  0.120  0.120  0.020  0.020  0.095  0.419  0.070 -0.030  0.144  0.095 -0.130  0.144  0.493 -0.030 -0.080  0.419  0.842  0.144  0.194 -0.130 -0.055 -0.080  0.169  0.070  0.443 
 0.559  0.010  0.633  0.359  0.384 -0.014  0.135  0.235  0.210  0.758  0.783 -0.014  0.035 -0.064  0.260  0.583  0.210  0.783  0.060  0.534 -0.064  0.010 -0.139  0.235 -0.214  0.135  0.160  0.085  0.010  0.035  0.534  0.110 -0.064  0.110  0.210 -0.064  0.160  0.608 -0.064 -0.039  0.559  0.783  0.185  0.260 -0.089 -0.089 -0.064  0.235  0.110  0.633 
 0.643  0.020  0.618  0.319  0.394 -0.004  0.145  0.270  0.195  0.743  0.768 -0.004 -0.004 -0.054  0.270  0.593  0.245  0.768  0.095  0.519 -0.079 -0.004 -0.154  0.245 -0.204  0.120  0.145  0.120  0.020  0.070  0.544  0.120 -0.054  0.095  0.245 -0.079  0.145  0.643 -0.079 -0.029  0.544  0.768  0.245  0.319 -0.079 -0.104 -0.079  0.220  0.145  0.618 
 0.718  0.070  0.693  0.319  0.344 -0.029  0.145  0.394  0.195  0.718  0.718  0.020 -0.004  0.020  0.419  0.593  0.270  0.743  0.070  0.544 -0.054 -0.004 -0.154  0.270 -0.204  0.120  0.145  0.120  0.020  0.070  0.519  0.120 -0.029  0.120  0.294 -0.029  0.120  0.693 -0.079  0.020  0.469  0.743  0.220  0.444 -0.029 -0.079 -0.104  0.195  0.245  0.668 
 0.688  0.065  0.713  0.339  0.364 -0.034  0.140  0.464  0.140  0.713  0.713  0.015 -0.034  0.040  0.539  0.588  0.289  0.713  0.065  0.539 -0.059  0.015 -0.159  0.265 -0.209  0.115  0.140  0.115  0.040  0.090  0.514  0.115 -0.034  0.090  0.314 -0.009  0.115  0.663 -0.109  0.065  0.464  0.713  0.215  0.464  0.015 -0.059 -0.109  0.190  0.240  0.663 
 0.680  0.057  0.705  0.356  0.356 -0.043  0.132  0.530  0.156  0.655  0.705  0.032  0.007  0.082  0.555  0.555  0.281  0.705  0.082  0.530 -0.068  0.007 -0.142  0.281 -0.217  0.107  0.107  0.132  0.107  0.082  0.480  0.107 -0.018  0.156  0.306  0.032  0.132  0.655 -0.118  0.107  0.455  0.680  0.306  0.455  0.007 -0.043 -0.118  0.181  0.231  0.680 
 0.674  0.051  0.699  0.350  0.350 -0.048  0.126  0.550  0.126  0.624  0.699  0.026  0.001  0.151  0.550  0.550  0.276  0.699  0.076  0.525 -0.073  0.001 -0.148  0.276 -0.223  0.076  0.101  0.126  0.151  0.076  0.475  0.101 -0.023  0.176  0.300  0.026  0.151  0.699 -0.123  0.126  0.450  0.674  0.300  0.450  0.026 -0.048 -0.123  0.176  0.226  0.674 
 0.669  0.046  0.694  0.345  0.345 -0.028  0.121  0.545  0.121  0.594  0.694  0.021  0.021  0.146  0.594  0.520  0.295  0.694  0.071  0.520 -0.103 -0.028 -0.153  0.271 -0.228  0.071  0.096  0.121  0.146  0.071  0.495  0.121 -0.028  0.246  0.295  0.021  0.221  0.694 -0.128  0.221  0.420  0.669  0.295  0.445  0.071 -0.053 -0.128  0.171  0.246  0.669 
 0.671  0.023  0.696  0.347  0.347 -0.027  0.098  0.546  0.123  0.596  0.696  0.048  0.023  0.147  0.571  0.521  0.297  0.696  0.073  0.521 -0.102 -0.027 -0.151  0.247 -0.226  0.073  0.098  0.123  0.123  0.073  0.496  0.147 -0.027  0.247  0.297  0.023  0.222  0.696 -0.127  0.222  0.422  0.671  0.322  0.446  0.073 -0.052 -0.127  0.172  0.247  0.671 
 0.668  0.045  0.693  0.344  0.344 -0.029  0.095  0.568  0.120  0.593  0.693  0.045  0.020  0.170  0.568  0.519  0.294  0.693  0.070  0.519 -0.104 -0.029 -0.154  0.245 -0.229  0.070  0.095  0.095  0.120  0.070  0.519  0.145 -0.029  0.294  0.294  0.020  0.195  0.668 -0.129  0.245  0.419  0.668  0.369  0.444  0.070 -0.054 -0.129  0.170  0.270  0.668 
 0.694  0.071  0.694  0.345  0.320 -0.028  0.096  0.569  0.121  0.594  0.694  0.046  0.021  0.171  0.569  0.520  0.295  0.694  0.071  0.520 -0.103 -0.028 -0.153  0.221 -0.228  0.071  0.071  0.096  0.121  0.071  0.495  0.146 -0.028  0.295  0.295  0.021  0.221  0.669 -0.128  0.246  0.420  0.669  0.370  0.445  0.071 -0.053 -0.128  0.146  0.246  0.669 
 0.669  0.071  0.694  0.345  0.320 -0.028  0.096  0.594  0.121  0.594  0.694  0.046  0.046  0.171  0.569  0.520  0.320  0.694  0.071  0.520 -0.103 -0.028 -0.153  0.221 -0.228  0.071  0.071  0.096  0.121  0.071  0.495  0.146 -0.028  0.320  0.320  0.021  0.221  0.669 -0.128  0.246  0.420  0.694  0.370  0.445  0.071 -0.053 -0.128  0.146  0.246  0.669 
 0.672  0.099  0.697  0.348  0.323 -0.025  0.099  0.572  0.124  0.597  0.697  0.049  0.049  0.199  0.548  0.523  0.373  0.697  0.074  0.498 -0.100 -0.025 -0.150  0.224 -0.225  0.099  0.049  0.099  0.124  0.074  0.498  0.124 -0.025  0.323  0.323  0.024  0.224  0.647 -0.125  0.224  0.423  0.697  0.373  0.448  0.099 -0.075 -0.150  0.149  0.249  0.672 
 0.645  0.122  0.695  0.346  0.321 -0.028  0.097  0.595  0.122  0.595  0.695  0.047  0.047  0.221  0.545  0.520  0.371  0.695  0.072  0.495 -0.103 -0.028 -0.152  0.221 -0.202  0.097  0.047  0.097  0.122  0.072  0.495  0.122 -0.028  0.346  0.321  0.047  0.196  0.645 -0.128  0.221  0.421  0.695  0.396  0.445  0.122 -0.053 -0.152  0.146  0.246  0.670 
 0.644  0.171  0.694  0.345  0.320 -0.028  0.096  0.644  0.121  0.594  0.694  0.046  0.046  0.196  0.545  0.520  0.370  0.669  0.071  0.470 -0.103 -0.028 -0.153  0.221 -0.228  0.096  0.046  0.096  0.121  0.071  0.520  0.096 -0.028  0.370  0.345  0.046  0.221  0.644 -0.128  0.221  0.395  0.694  0.395  0.445  0.121 -0.028 -0.153  0.146  0.246  0.669 
 0.645  0.171  0.695  0.346  0.346 -0.028  0.097  0.645  0.122  0.595  0.695  0.047  0.047  0.196  0.545  0.520  0.371  0.670  0.072  0.495 -0.103 -0.028 -0.152  0.221 -0.227  0.097  0.072  0.097  0.097  0.072  0.520  0.097 -0.028  0.371  0.346  0.047  0.221  0.620 -0.128  0.221  0.396  0.695  0.396  0.445  0.122 -0.028 -0.128  0.146  0.246  0.670 
 0.646  0.198  0.696  0.347  0.347 -0.051  0.123  0.646  0.123  0.596  0.696  0.048  0.048  0.198  0.571  0.522  0.372  0.696  0.048  0.497 -0.101 -0.051 -0.151  0.223 -0.226  0.098  0.073  0.098  0.123  0.073  0.497  0.098 -0.026  0.372  0.347  0.048  0.223  0.621 -0.126  0.198  0.397  0.696  0.397  0.422  0.098 -0.026 -0.126  0.148  0.248  0.671 
 0.646  0.197  0.696  0.347  0.347 -0.052  0.123  0.646  0.123  0.596  0.696  0.048  0.048  0.197  0.571  0.521  0.372  0.696  0.048  0.521 -0.102 -0.052 -0.151  0.197 -0.226  0.098  0.073  0.098  0.123  0.073  0.496  0.123 -0.027  0.372  0.347  0.048  0.222  0.621 -0.127  0.197  0.397  0.696  0.397  0.422  0.098 -0.002 -0.127  0.147  0.222  0.646 
 0.647  0.198  0.622  0.373  0.273 -0.051  0.124  0.547  0.148  0.572  0.697 -0.026 -0.001  0.124  0.348  0.547  0.373  0.622  0.049  0.522 -0.076 -0.076 -0.076  0.173 -0.150  0.099  0.049  0.074  0.074  0.074  0.522  0.148 -0.001  0.248  0.248  0.074  0.173  0.522 -0.101  0.148  0.323  0.597  0.323  0.348 -0.001 -0.001 -0.076  0.099  0.223  0.672 
 0.581  0.158  0.557  0.258  0.208 -0.016  0.108  0.507  0.133  0.532  0.706 -0.041 -0.041  0.033  0.233  0.507  0.258  0.532  0.058  0.482 -0.041 -0.041 -0.116  0.083 -0.116  0.058  0.033 -0.041  0.058  0.058  0.557  0.008 -0.016  0.133  0.133  0.033  0.108  0.432 -0.091  0.058  0.307  0.656  0.208  0.208  0.008 -0.016 -0.041  0.108  0.208  0.706 
 0.520  0.146  0.470  0.246  0.246 -0.003  0.097  0.445  0.122  0.545  0.744 -0.028 -0.028 -0.003  0.171  0.495  0.171  0.495  0.022  0.421 -0.028 -0.028 -0.103 -0.003 -0.103  0.022  0.022 -0.053  0.047 -0.003  0.570 -0.003 -0.028  0.146  0.122  0.022  0.097  0.445 -0.078 -0.028  0.271  0.670  0.146  0.196  0.022 -0.003 -0.078  0.097  0.221  0.695 
 0.364  0.115  0.438  0.239  0.239  0.015  0.090  0.339  0.140  0.488  0.812 -0.010 -0.060 -0.010  0.090  0.488  0.140  0.463  0.015  0.389 -0.010 -0.035 -0.085  0.015 -0.085  0.040  0.040 -0.060  0.040 -0.010  0.613 -0.010 -0.035  0.090  0.065 -0.010  0.115  0.438 -0.060 -0.060  0.264  0.737  0.164  0.090 -0.010  0.015 -0.060  0.090  0.214  0.688 
 0.200  0.126  0.375  0.250  0.200  0.026  0.076  0.250  0.150  0.449  0.823 -0.024 -0.074 -0.024  0.101  0.474  0.150  0.449  0.001  0.350  0.001 -0.049 -0.074  0.001 -0.074  0.051  0.051 -0.074  0.026  0.001  0.624 -0.024 -0.049  0.051  0.076 -0.024  0.101  0.425 -0.049 -0.074  0.225  0.773  0.126  0.101 -0.024  0.001 -0.074  0.051  0.225  0.649 
 0.068  0.118  0.317  0.192  0.167  0.018  0.093  0.167  0.093  0.417  0.840 -0.032 -0.057 -0.007  0.043  0.367  0.118  0.417 -0.032  0.367 -0.032 -0.032 -0.057  0.018 -0.057  0.018  0.068 -0.082  0.043 -0.007  0.641 -0.007 -0.057  0.043  0.093 -0.032  0.118  0.367 -0.032 -0.057  0.192  0.790  0.142  0.068 -0.032 -0.007 -0.057  0.018  0.167  0.516 
 0.074  0.124  0.198  0.198  0.173  0.024  0.074  0.124  0.074  0.373  0.821 -0.026 -0.051 -0.001  0.049  0.323  0.099  0.398 -0.051  0.348 -0.026 -0.026 -0.051  0.024 -0.051 -0.026  0.074 -0.076  0.024 -0.001  0.672 -0.001 -0.051  0.024  0.074 -0.026  0.124  0.323 -0.026 -0.051  0.198  0.821  0.124  0.074 -0.026 -0.001 -0.051 -0.001  0.124  0.447 
 0.034  0.059  0.158  0.109  0.109 -0.016  0.034  0.084  0.059  0.208  0.856 -0.016 -0.066  0.009 -0.016  0.258  0.084  0.283 -0.041  0.333 -0.016 -0.016 -0.041  0.059 -0.041 -0.016  0.059 -0.066  0.009  0.034  0.707  0.009 -0.041  0.034  0.084 -0.066  0.109  0.258 -0.016 -0.041  0.183  0.906  0.134  0.059 -0.016  0.009 -0.016  0.009  0.009  0.383 
 0.038  0.063  0.088  0.088  0.113  0.013  0.038  0.088  0.063  0.187  0.910 -0.012 -0.062  0.013 -0.037  0.212  0.038  0.162 -0.037  0.287  0.013 -0.012 -0.037  0.063 -0.037  0.013  0.063 -0.037  0.013  0.013  0.710  0.038 -0.037  0.013  0.063 -0.062  0.113  0.237 -0.037 -0.037  0.187  0.935  0.088  0.013 -0.012  0.013 -0.012  0.013 -0.037  0.287 
-0.004  0.021 -0.004  0.046  0.096  0.021  0.021  0.071  0.021  0.170  0.943 -0.029 -0.054  0.021 -0.029  0.071  0.046  0.071 -0.029  0.195 -0.004 -0.004 -0.029  0.071 -0.029  0.021  0.046 -0.029  0.046  0.021  0.768  0.021 -0.029  0.021  0.071 -0.054  0.121  0.145 -0.054 -0.029  0.121  0.943  0.096  0.021 -0.004 -0.004 -0.004  0.021 -0.029  0.145 
-0.003  0.022 -0.003  0.047  0.097  0.022 -0.003  0.072  0.022  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022  0.022 -0.028  0.097 -0.003 -0.003 -0.028  0.072 -0.053  0.022  0.022 -0.028  0.047  0.022  0.794  0.022 -0.028  0.047  0.047 -0.053  0.097  0.072 -0.053 -0.028  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.122 
-0.003  0.022 -0.028  0.047  0.097  0.022 -0.028  0.072  0.022  0.146  0.969 -0.028 -0.028 -0.003 -0.028  0.022  0.022 -0.003 -0.028  0.072 -0.003 -0.003 -0.028  0.072 -0.053  0.022 -0.003 -0.028  0.047  0.022  0.844  0.022 -0.028  0.047  0.022 -0.053  0.097  0.047 -0.053 -0.028  0.097  0.969  0.097  0.047 -0.003 -0.003 -0.003  0.022 -0.003  0.097 
-0.003  0.021 -0.028  0.046  0.096  0.021 -0.028  0.071  0.021  0.146  0.968 -0.028 -0.028 -0.003 -0.028  0.021  0.021 -0.003 -0.028  0.071 -0.003 -0.003 -0.028  0.071 -0.053  0.021 -0.003 -0.028  0.046  0.021  0.868  0.021 -0.028  0.046  0.021 -0.053  0.096  0.046 -0.053 -0.003  0.096  0.968  0.096  0.046 -0.003 -0.003 -0.003  0.021 -0.003  0.096 
-0.005  0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
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-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.031  0.006  0.031  0.056  0.156 -0.018  0.031  0.156  0.056  0.281  0.928  0.006 -0.043  0.031 -0.018  0.031  0.106  0.056  0.006  0.305  0.006 -0.018 -0.043  0.131 -0.093  0.031  0.031 -0.018  0.081  0.006  0.928  0.031 -0.043  0.131  0.031 -0.093  0.106  0.081 -0.093  0.031  0.281  0.928  0.231  0.131 -0.043 -0.043 -0.018  0.056 -0.018  0.281 
 0.167  0.043  0.192  0.192  0.242 -0.032  0.043  0.167  0.043  0.466  0.865 -0.007 -0.032  0.167 -0.082  0.167  0.342  0.217  0.018  0.616  0.018 -0.057 -0.032  0.167 -0.132  0.018  0.142 -0.007  0.093 -0.032  0.865  0.043 -0.007  0.242  0.093 -0.057  0.217  0.392 -0.107  0.018  0.441  0.865  0.367  0.167 -0.032 -0.057 -0.032  0.043  0.093  0.441 
 0.372  0.073  0.272  0.272  0.222 -0.052  0.073  0.123  0.147  0.496  0.820  0.048 -0.027  0.247 -0.027  0.297  0.446  0.272  0.023  0.671 -0.027 -0.027 -0.027  0.197 -0.127  0.048  0.073  0.048  0.073 -0.002  0.820  0.123  0.098  0.322  0.172 -0.077  0.322  0.546 -0.151  0.147  0.446  0.820  0.446  0.247 -0.027 -0.027 -0.077  0.123  0.098  0.596 
 0.539  0.116  0.415  0.315  0.215 -0.034  0.091  0.290  0.215  0.664  0.763  0.066 -0.034  0.290  0.041  0.439  0.564  0.439  0.041  0.639 -0.009 -0.034 -0.009  0.265 -0.158  0.066  0.091  0.066  0.141  0.016  0.738  0.116  0.116  0.340  0.190 -0.034  0.390  0.713 -0.183  0.165  0.464  0.763  0.439  0.215  0.016 -0.009 -0.084  0.141  0.190  0.664 
 0.568  0.120  0.568  0.294  0.195 -0.004  0.145  0.294  0.245  0.643  0.718  0.070 -0.004  0.270  0.095  0.444  0.568  0.494  0.045  0.593 -0.029 -0.029  0.070  0.294 -0.179  0.070  0.070  0.045  0.195  0.020  0.718  0.095  0.195  0.369  0.220 -0.054  0.394  0.693 -0.129  0.195  0.444  0.718  0.444  0.245  0.045  0.020 -0.104  0.145  0.195  0.668 
 0.549  0.125  0.573  0.299  0.175 -0.049  0.175  0.349  0.225  0.648  0.673  0.100  0.025  0.250  0.125  0.449  0.598  0.524  0.050  0.573 -0.049 -0.049  0.100  0.349 -0.199  0.100  0.050  0.100  0.225  0.000  0.698  0.125  0.225  0.449  0.250 -0.049  0.374  0.723 -0.124  0.299  0.399  0.698  0.374  0.275  0.100  0.075 -0.124  0.125  0.225  0.673 
 0.546  0.122  0.595  0.296  0.172 -0.052  0.172  0.371  0.197  0.670  0.670  0.097  0.097  0.222  0.122  0.471  0.570  0.570  0.072  0.570 -0.052 -0.077  0.097  0.371 -0.202  0.097  0.047  0.097  0.247 -0.002  0.670  0.147  0.272  0.496  0.272 -0.052  0.346  0.695 -0.127  0.321  0.396  0.695  0.346  0.272  0.047  0.047 -0.127  0.122  0.247  0.670 
 0.562  0.188  0.587  0.288  0.163 -0.011  0.139  0.388  0.188  0.662  0.662  0.114  0.163  0.213  0.139  0.487  0.562  0.612  0.139  0.537 -0.061 -0.061  0.114  0.363 -0.210  0.188  0.039  0.089  0.313 -0.011  0.662  0.139  0.338  0.537  0.288 -0.036  0.338  0.662 -0.111  0.388  0.388  0.687  0.338  0.263  0.039  0.014 -0.136  0.114  0.238  0.637 
 0.557  0.183  0.581  0.283  0.158  0.008  0.158  0.407  0.183  0.656  0.681  0.108  0.208  0.183  0.133  0.482  0.557  0.581  0.158  0.532 -0.041 -0.066  0.108  0.357 -0.216  0.208  0.033  0.083  0.307  0.008  0.656  0.183  0.357  0.507  0.283 -0.016  0.332  0.656 -0.116  0.457  0.382  0.681  0.332  0.258  0.083  0.033 -0.141  0.133  0.233  0.631 
 0.553  0.179  0.577  0.279  0.154  0.054  0.179  0.428  0.179  0.652  0.677  0.129  0.229  0.179  0.104  0.453  0.528  0.577  0.179  0.528 -0.045 -0.070  0.104  0.328 -0.220  0.229  0.029  0.079  0.353  0.029  0.652  0.204  0.378  0.503  0.279  0.004  0.328  0.652 -0.120  0.478  0.378  0.677  0.353  0.254  0.104  0.029 -0.145  0.129  0.254  0.627 
 0.551  0.177  0.575  0.277  0.127  0.052  0.202  0.426  0.177  0.675  0.675  0.127  0.227  0.177  0.102  0.451  0.526  0.575  0.177  0.476 -0.047 -0.047  0.127  0.326 -0.222  0.252  0.002  0.077  0.351  0.027  0.675  0.202  0.376  0.501  0.277  0.027  0.326  0.650 -0.122  0.476  0.376  0.675  0.351  0.252  0.127  0.027 -0.172  0.127  0.252  0.625 
 0.547  0.148  0.572  0.273  0.124  0.049  0.223  0.447  0.173  0.672  0.647  0.148  0.223  0.148  0.099  0.398  0.522  0.597  0.173  0.472 -0.051 -0.026  0.148  0.298 -0.225  0.273 -0.001  0.074  0.373  0.024  0.672  0.198  0.398  0.522  0.248  0.024  0.298  0.647 -0.101  0.547  0.348  0.672  0.348  0.248  0.124  0.049 -0.200  0.124  0.248  0.622 
 0.551  0.177  0.575  0.227  0.127  0.052  0.227  0.476  0.177  0.675  0.650  0.152  0.227  0.127  0.077  0.401  0.526  0.600  0.177  0.451 -0.047 -0.022  0.152  0.277 -0.222  0.277  0.002  0.077  0.401  0.027  0.650  0.127  0.401  0.526  0.252  0.027  0.301  0.650 -0.097  0.526  0.351  0.675  0.351  0.252  0.127  0.077 -0.197  0.127  0.252  0.625 
 0.551  0.152  0.575  0.202  0.127  0.052  0.227  0.476  0.177  0.675  0.675  0.202  0.227  0.127  0.102  0.401  0.526  0.600  0.177  0.451 -0.072 -0.022  0.227  0.252 -0.222  0.301  0.002  0.077  0.426  0.027  0.650  0.077  0.401  0.501  0.252  0.052  0.301  0.650 -0.097  0.575  0.351  0.675  0.351  0.252  0.127  0.127 -0.172  0.127  0.252  0.625 
 0.550  0.127  0.575  0.201  0.127  0.077  0.251  0.475  0.201  0.675  0.675  0.201  0.226  0.102  0.102  0.376  0.525  0.625  0.176  0.426 -0.073  0.002  0.226  0.251 -0.197  0.326  0.027  0.077  0.426  0.002  0.625  0.052  0.401  0.500  0.251  0.077  0.301  0.650 -0.123  0.600  0.301  0.675  0.376  0.251  0.127  0.176 -0.172  0.127  0.226  0.625 
 0.551  0.103  0.601  0.202  0.128  0.078  0.302  0.476  0.202  0.676  0.651  0.202  0.202  0.103  0.103  0.377  0.501  0.601  0.152  0.426 -0.097  0.028  0.252  0.252 -0.196  0.377  0.003  0.078  0.426  0.003  0.626  0.003  0.402  0.501  0.252  0.103  0.302  0.651 -0.122  0.601  0.252  0.651  0.402  0.252  0.128  0.202 -0.196  0.103  0.227  0.626 
 0.574  0.101  0.599  0.201  0.126  0.076  0.300  0.475  0.176  0.674  0.624  0.201  0.201  0.126  0.101  0.375  0.500  0.599  0.151  0.425 -0.098  0.051  0.251  0.251 -0.198  0.375  0.001  0.076  0.425  0.001  0.674  0.001  0.400  0.500  0.251  0.101  0.325  0.649 -0.098  0.599  0.251  0.649  0.400  0.276  0.126  0.201 -0.198  0.101  0.226  0.624 
 0.596  0.123  0.596  0.198  0.123  0.073  0.297  0.472  0.173  0.671  0.621  0.223  0.248  0.123  0.098  0.372  0.497  0.596  0.148  0.422 -0.101  0.073  0.248  0.248 -0.201  0.397 -0.001  0.073  0.397 -0.001  0.671 -0.001  0.422  0.497  0.248  0.098  0.322  0.646 -0.101  0.596  0.248  0.646  0.397  0.322  0.123  0.248 -0.201  0.098  0.223  0.621 
 0.596  0.123  0.621  0.222  0.123  0.048  0.297  0.471  0.172  0.671  0.621  0.222  0.272  0.098  0.123  0.372  0.521  0.596  0.147  0.422 -0.102  0.073  0.247  0.247 -0.201  0.397 -0.027  0.073  0.397 -0.002  0.646 -0.002  0.422  0.496  0.247  0.098  0.322  0.621 -0.102  0.596  0.247  0.646  0.397  0.322  0.123  0.247 -0.201  0.098  0.222  0.621 
 0.617  0.119  0.617  0.218  0.119  0.044  0.293  0.467  0.218  0.667  0.617  0.218  0.343  0.094  0.119  0.368  0.517  0.592  0.143  0.418 -0.106  0.119  0.243  0.243 -0.180  0.393 -0.031  0.069  0.418 -0.006  0.642  0.019  0.418  0.492  0.243  0.094  0.318  0.617 -0.106  0.592  0.243  0.642  0.418  0.318  0.119  0.243 -0.205  0.119  0.218  0.617 
 0.521  0.122  0.595  0.272  0.172  0.047  0.296  0.371  0.222  0.546  0.595  0.272  0.222  0.022  0.122  0.371  0.496  0.645  0.147  0.396 -0.127  0.122  0.172  0.222 -0.127  0.272 -0.052  0.047  0.296  0.022  0.645 -0.027  0.421  0.521  0.197 -0.027  0.296  0.496 -0.102  0.496  0.321  0.595  0.321  0.346  0.097  0.172 -0.152  0.072  0.222  0.645 
 0.562  0.139  0.512  0.213  0.213  0.089  0.163  0.363  0.163  0.512  0.662  0.163  0.114  0.014  0.114  0.437  0.462  0.537  0.163  0.437 -0.036 -0.011  0.114  0.188 -0.111  0.139 -0.011 -0.036  0.163  0.014  0.612 -0.011  0.288  0.437  0.139 -0.011  0.263  0.363 -0.061  0.263  0.338  0.662  0.213  0.188  0.039 -0.011 -0.086  0.064  0.163  0.687 
 0.530  0.132  0.505  0.231  0.206  0.057  0.181  0.306  0.132  0.505  0.680  0.107  0.032  0.007  0.132  0.430  0.455  0.530  0.132  0.455 -0.043 -0.018  0.082  0.181 -0.093  0.057  0.032 -0.093  0.181  0.032  0.605 -0.043  0.132  0.406  0.107 -0.018  0.231  0.331 -0.043  0.181  0.331  0.705  0.181  0.181  0.007 -0.018 -0.068  0.057  0.181  0.705 
 0.407  0.083  0.407  0.258  0.208  0.008  0.108  0.283  0.108  0.457  0.731  0.083  0.008  0.033  0.133  0.457  0.432  0.457  0.058  0.407 -0.016 -0.066 -0.066  0.083 -0.091  0.033  0.033 -0.116  0.108  0.008  0.631 -0.016  0.033  0.332  0.058  0.008  0.208  0.357 -0.041  0.058  0.357  0.756  0.158  0.133 -0.016 -0.016 -0.066  0.058  0.183  0.681 
 0.318  0.069  0.293  0.268  0.193  0.019  0.119  0.293  0.044  0.442  0.741  0.094 -0.006  0.019  0.119  0.393  0.418  0.442  0.019  0.418 -0.006 -0.056 -0.056  0.069 -0.081  0.044  0.044 -0.106  0.094 -0.006  0.642 -0.006 -0.031  0.243  0.069 -0.006  0.193  0.343 -0.031  0.044  0.368  0.741  0.143  0.094 -0.006 -0.006 -0.056 -0.006  0.193  0.692 
 0.158  0.083  0.233  0.283  0.158  0.008  0.108  0.208  0.033  0.382  0.781  0.008  0.008  0.008  0.083  0.332  0.357  0.407 -0.066  0.407 -0.016 -0.041 -0.066  0.058 -0.066  0.033  0.058 -0.091  0.033 -0.016  0.656  0.008 -0.041  0.133  0.058  0.008  0.158  0.332 -0.041 -0.016  0.283  0.781  0.133  0.058 -0.016 -0.016 -0.041  0.008  0.183  0.681 
 0.116  0.091  0.215  0.265  0.165  0.016  0.091  0.190  0.016  0.340  0.788 -0.009 -0.059  0.016  0.066  0.315  0.265  0.390 -0.059  0.365 -0.034 -0.034 -0.059  0.066 -0.059  0.041  0.066 -0.084  0.041 -0.009  0.664 -0.009 -0.059  0.091  0.066 -0.009  0.141  0.340 -0.034 -0.059  0.215  0.813  0.141  0.066 -0.034 -0.009 -0.034  0.016  0.141  0.689 
 0.075  0.050  0.075  0.249  0.100  0.025  0.075  0.149  0.000  0.249  0.822 -0.025 -0.075  0.000  0.050  0.324  0.125  0.299 -0.050  0.349 -0.050 -0.025 -0.050  0.100 -0.050  0.025  0.050 -0.075  0.050  0.000  0.698  0.000 -0.050  0.025  0.050 -0.025  0.125  0.324 -0.025 -0.050  0.199  0.847  0.125  0.075 -0.025  0.000 -0.025  0.000  0.100  0.673 
 0.075  0.050  0.075  0.224  0.100  0.025  0.075  0.125  0.000  0.249  0.872 -0.025 -0.075  0.000  0.050  0.324  0.125  0.274 -0.050  0.349 -0.050 -0.025 -0.050  0.100 -0.050  0.025  0.050 -0.075  0.050  0.000  0.698  0.000 -0.050  0.025  0.050 -0.025  0.125  0.299 -0.025 -0.050  0.174  0.872  0.125  0.075 -0.025  0.000  0.000  0.000  0.100  0.673 
 0.008  0.033 -0.017  0.133  0.083 -0.017  0.058  0.058  0.008  0.157  0.930 -0.042 -0.067  0.008  0.033  0.257  0.083  0.133 -0.042  0.332 -0.017 -0.017 -0.042  0.108 -0.042  0.008  0.033 -0.067  0.033  0.008  0.730  0.008 -0.042  0.008  0.058 -0.067  0.133  0.232 -0.067 -0.042  0.182  0.930  0.133  0.033 -0.017 -0.017 -0.017  0.008 -0.017  0.581 
-0.011  0.014 -0.011  0.089  0.089  0.014  0.039  0.064  0.014  0.163  0.961 -0.036 -0.061  0.014 -0.011  0.238  0.089  0.139 -0.036  0.238 -0.011 -0.011 -0.036  0.064 -0.036  0.014  0.039 -0.036  0.014  0.014  0.711  0.014 -0.036  0.014  0.064 -0.061  0.114  0.163 -0.061 -0.036  0.188  0.936  0.114  0.014 -0.011 -0.011 -0.011  0.014 -0.036  0.413 
-0.004  0.021 -0.029  0.046  0.096  0.021  0.021  0.071  0.021  0.170  0.968 -0.029 -0.054  0.021 -0.029  0.071  0.021  0.021 -0.029  0.121 -0.004 -0.004 -0.029  0.071 -0.054  0.021  0.021 -0.029  0.021  0.021  0.743  0.021 -0.029  0.021  0.046 -0.054  0.096  0.071 -0.054 -0.029  0.170  0.943  0.121  0.021 -0.004 -0.004 -0.004  0.021 -0.029  0.245 
-0.002  0.023 -0.027  0.048  0.098  0.023  0.023  0.073  0.023  0.172  0.970 -0.027 -0.027  0.023 -0.027  0.023  0.023  0.023 -0.027  0.098 -0.002 -0.002 -0.027  0.073 -0.052  0.023  0.023 -0.027  0.023  0.023  0.720  0.023 -0.027  0.048  0.048 -0.052  0.098  0.073 -0.052 -0.027  0.123  0.970  0.123  0.023 -0.002 -0.002 -0.002  0.023 -0.027  0.147 
-0.002  0.023 -0.027  0.048  0.098  0.023 -0.027  0.073  0.023  0.147  0.970 -0.027 -0.027 -0.002 -0.027  0.023  0.023 -0.002 -0.027  0.073 -0.002 -0.002 -0.027  0.073 -0.052  0.023 -0.002 -0.027  0.048  0.023  0.795  0.023 -0.027  0.048  0.023 -0.052  0.098  0.048 -0.052 -0.027  0.098  0.970  0.098  0.048 -0.002 -0.002 -0.002  0.023 -0.002  0.098 
-0.003  0.021 -0.028  0.046  0.096  0.021 -0.028  0.071  0.021  0.146  0.968 -0.028 -0.028 -0.003 -0.028  0.021  0.021 -0.003 -0.028  0.071 -0.003 -0.003 -0.028  0.071 -0.053  0.021 -0.003 -0.028  0.046  0.021  0.868  0.021 -0.028  0.046  0.021 -0.053  0.096  0.046 -0.053  0.021  0.096  0.968  0.096  0.046 -0.003 -0.003 -0.003  0.021 -0.003  0.096 
-0.004  0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.029  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054  0.020  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
-0.005  0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.030  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055  0.020  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.045 -0.030  0.144  0.120  0.020 -0.030  0.095  0.045  0.219  0.942 -0.005 -0.055  0.020 -0.030  0.045  0.045 -0.030 -0.030  0.070 -0.030 -0.030 -0.005  0.169 -0.080 -0.005  0.045 -0.005  0.045 -0.005  0.942 -0.005 -0.055  0.045  0.020 -0.080  0.120  0.070 -0.080  0.020  0.219  0.942  0.120  0.045 -0.030  0.045 -0.005 -0.005  0.020  0.095 
 0.139  0.064  0.014  0.139  0.238  0.039  0.064  0.238  0.089  0.537  0.886  0.114 -0.061  0.014 -0.061  0.188  0.163  0.139  0.039  0.213 -0.011 -0.061 -0.036  0.238 -0.111 -0.011  0.139  0.039  0.064  0.014  0.886 -0.011  0.014  0.163  0.014 -0.086  0.238  0.163 -0.111  0.014  0.313  0.886  0.313  0.089 -0.011 -0.011 -0.011  0.014  0.039  0.313 
 0.261  0.137  0.161  0.137  0.261  0.012  0.112  0.485  0.087  0.635  0.834  0.112 -0.038  0.037  0.012  0.236  0.411  0.261  0.037  0.386  0.037 -0.063 -0.038  0.211 -0.162 -0.013  0.161 -0.013  0.186 -0.013  0.834  0.037  0.012  0.236  0.112 -0.038  0.311  0.236 -0.138  0.012  0.386  0.834  0.361  0.137  0.062 -0.038 -0.013  0.112  0.186  0.535 
 0.477  0.128  0.302  0.203  0.302  0.053  0.128  0.527  0.203  0.726  0.776  0.128 -0.021  0.078  0.053  0.377  0.502  0.377  0.003  0.452 -0.021 -0.096  0.028  0.352 -0.221  0.053  0.153 -0.021  0.228  0.053  0.726  0.003  0.053  0.327  0.053 -0.021  0.352  0.402 -0.196  0.053  0.402  0.776  0.477  0.228  0.128  0.028 -0.096  0.153  0.278  0.701 
 0.460  0.161  0.460  0.186  0.286  0.037  0.211  0.535  0.236  0.710  0.759  0.137  0.062  0.062  0.087  0.411  0.485  0.435  0.012  0.435 -0.038 -0.113  0.087  0.336 -0.212  0.037  0.062  0.012  0.236  0.037  0.685  0.012  0.161  0.336  0.087 -0.013  0.336  0.535 -0.162  0.062  0.386  0.734  0.485  0.261  0.137  0.112 -0.113  0.186  0.286  0.685 
 0.533  0.134  0.533  0.184  0.284  0.059  0.234  0.582  0.308  0.707  0.732  0.159  0.084  0.034  0.084  0.408  0.483  0.558  0.034  0.508 -0.065 -0.040  0.109  0.433 -0.215  0.059  0.059  0.059  0.234  0.009  0.632  0.059  0.358  0.433  0.059  0.084  0.333  0.582 -0.115  0.134  0.333  0.707  0.458  0.308  0.184  0.109 -0.115  0.159  0.284  0.657 
 0.543  0.144  0.543  0.169  0.294  0.045  0.244  0.568  0.319  0.693  0.717  0.144  0.120  0.045  0.070  0.394  0.468  0.618  0.045  0.493 -0.080 -0.005  0.144  0.394 -0.229  0.095  0.045  0.045  0.269 -0.005  0.618  0.045  0.369  0.443  0.144  0.144  0.319  0.618 -0.105  0.194  0.319  0.693  0.443  0.319  0.169  0.120 -0.105  0.144  0.269  0.668 
 0.533  0.135  0.558  0.184  0.284  0.035  0.234  0.558  0.309  0.683  0.708  0.159  0.159  0.060  0.085  0.384  0.483  0.633  0.060  0.483 -0.115  0.035  0.135  0.384 -0.239  0.110  0.010  0.035  0.259 -0.015  0.533  0.035  0.409  0.458  0.234  0.135  0.334  0.633 -0.065  0.234  0.284  0.683  0.433  0.433  0.159  0.159 -0.115  0.135  0.309  0.658 
 0.531  0.132  0.531  0.182  0.282  0.032  0.282  0.556  0.306  0.680  0.705  0.157  0.182  0.082  0.082  0.381  0.456  0.630  0.057  0.506 -0.092  0.082  0.157  0.331 -0.217  0.157  0.032  0.057  0.282 -0.017  0.531  0.032  0.406  0.431  0.232  0.132  0.306  0.655 -0.067  0.331  0.306  0.680  0.431  0.456  0.157  0.157 -0.117  0.132  0.331  0.655 
 0.554  0.130  0.554  0.155  0.280  0.030  0.280  0.554  0.329  0.653  0.653  0.205  0.205  0.130  0.080  0.404  0.479  0.628  0.130  0.454 -0.119  0.080  0.130  0.329 -0.219  0.205  0.005  0.055  0.304  0.005  0.479  0.005  0.429  0.429  0.280  0.130  0.304  0.653 -0.069  0.404  0.304  0.653  0.404  0.454  0.155  0.230 -0.144  0.130  0.354  0.653 
 0.574  0.151  0.574  0.151  0.276  0.026  0.276  0.574  0.325  0.674  0.674  0.201  0.251  0.126  0.076  0.400  0.475  0.624  0.151  0.450 -0.123  0.076  0.126  0.300 -0.223  0.201  0.001  0.051  0.300  0.026  0.475  0.001  0.425  0.425  0.276  0.126  0.300  0.624 -0.073  0.425  0.300  0.649  0.400  0.450  0.126  0.251 -0.148  0.126  0.300  0.649 
 0.598  0.175  0.573  0.150  0.225  0.025  0.299  0.573  0.324  0.673  0.673  0.200  0.250  0.150  0.100  0.399  0.499  0.623  0.175  0.399 -0.124  0.075  0.125  0.250 -0.199  0.250  0.000  0.050  0.324  0.025  0.474  0.000  0.424  0.424  0.275  0.125  0.299  0.623 -0.074  0.449  0.349  0.648  0.399  0.449  0.125  0.250 -0.149  0.100  0.275  0.623 
 0.597  0.174  0.572  0.149  0.199  0.024  0.298  0.548  0.323  0.672  0.672  0.199  0.249  0.149  0.074  0.398  0.498  0.622  0.174  0.398 -0.125  0.074  0.149  0.224 -0.200  0.249 -0.000  0.049  0.323  0.024  0.473 -0.000  0.423  0.423  0.274  0.149  0.298  0.622 -0.075  0.473  0.348  0.647  0.398  0.448  0.149  0.249 -0.150  0.099  0.298  0.622 
 0.597  0.174  0.572  0.149  0.149  0.049  0.298  0.548  0.323  0.647  0.622  0.199  0.298  0.149  0.074  0.423  0.498  0.622  0.174  0.398 -0.125  0.099  0.149  0.224 -0.175  0.249 -0.000  0.049  0.323  0.024  0.473 -0.000  0.423  0.423  0.274  0.124  0.298  0.622 -0.075  0.498  0.348  0.622  0.398  0.448  0.149  0.249 -0.200  0.074  0.298  0.622 
 0.596  0.172  0.571  0.123  0.123  0.048  0.297  0.546  0.347  0.621  0.621  0.197  0.322  0.147  0.073  0.422  0.496  0.621  0.197  0.397 -0.102  0.147  0.147  0.222 -0.151  0.247 -0.002  0.048  0.322 -0.002  0.471 -0.002  0.422  0.446  0.272  0.123  0.297  0.621 -0.077  0.496  0.347  0.621  0.422  0.446  0.147  0.247 -0.201  0.073  0.297  0.621 
 0.599  0.176  0.574  0.126  0.126  0.051  0.300  0.550  0.350  0.624  0.624  0.201  0.325  0.151  0.076  0.425  0.500  0.624  0.201  0.400 -0.098  0.151  0.151  0.226 -0.148  0.251  0.001  0.051  0.325  0.001  0.475  0.001  0.425  0.425  0.276  0.126  0.300  0.624 -0.073  0.450  0.350  0.624  0.425  0.450  0.126  0.226 -0.198  0.076  0.276  0.624 
 0.600  0.176  0.575  0.127  0.127  0.052  0.301  0.550  0.351  0.625  0.625  0.201  0.326  0.151  0.077  0.426  0.500  0.625  0.201  0.401 -0.123  0.151  0.151  0.226 -0.147  0.251  0.002  0.052  0.326  0.002  0.475 -0.023  0.426  0.450  0.276  0.127  0.301  0.625 -0.073  0.450  0.351  0.625  0.426  0.450  0.127  0.226 -0.197  0.077  0.276  0.625 
 0.602  0.179  0.577  0.129  0.129  0.054  0.303  0.553  0.353  0.602  0.627  0.204  0.328  0.154  0.079  0.403  0.503  0.627  0.204  0.403 -0.145  0.129  0.154  0.229 -0.145  0.254 -0.020  0.054  0.328  0.004  0.478 -0.020  0.428  0.453  0.279  0.129  0.303  0.627 -0.070  0.478  0.303  0.652  0.403  0.453  0.154  0.229 -0.195  0.104  0.254  0.627 
 0.600  0.176  0.575  0.127  0.127  0.077  0.301  0.550  0.351  0.600  0.625  0.201  0.326  0.176  0.077  0.401  0.500  0.625  0.201  0.401 -0.147  0.151  0.201  0.226 -0.147  0.276  0.002  0.052  0.326  0.002  0.500 -0.023  0.426  0.450  0.276  0.127  0.301  0.625 -0.073  0.475  0.326  0.650  0.426  0.450  0.127  0.226 -0.197  0.102  0.226  0.625 
 0.621  0.172  0.596  0.147  0.123  0.073  0.297  0.546  0.347  0.596  0.621  0.197  0.372  0.172  0.098  0.372  0.496  0.621  0.197  0.397 -0.127  0.147  0.222  0.222 -0.151  0.322 -0.002  0.073  0.322 -0.027  0.496 -0.027  0.446  0.446  0.272  0.123  0.297  0.621 -0.077  0.446  0.347  0.646  0.422  0.446  0.123  0.222 -0.201  0.098  0.197  0.646 
 0.602  0.178  0.627  0.178  0.129  0.054  0.203  0.502  0.253  0.552  0.627  0.153  0.228  0.178  0.079  0.378  0.477  0.602  0.203  0.427 -0.096  0.079  0.079  0.253 -0.145  0.228  0.004  0.054  0.203  0.029  0.502 -0.021  0.278  0.477  0.228  0.029  0.228  0.602 -0.071  0.303  0.403  0.652  0.427  0.403  0.054  0.079 -0.145  0.004  0.253  0.627 
 0.567  0.168  0.542  0.243  0.168  0.069  0.168  0.318  0.218  0.492  0.667  0.168  0.069  0.019  0.143  0.442  0.393  0.567  0.143  0.442 -0.056  0.044 -0.006  0.193 -0.131  0.094  0.019 -0.056  0.168  0.019  0.517 -0.031  0.218  0.343  0.119 -0.031  0.218  0.442 -0.006  0.168  0.343  0.667  0.218  0.243  0.019  0.044 -0.081  0.044  0.168  0.642 
 0.539  0.190  0.514  0.240  0.140  0.040  0.140  0.339  0.165  0.489  0.688  0.090  0.065  0.015  0.090  0.439  0.389  0.489  0.090  0.389 -0.034 -0.034 -0.059  0.190 -0.109  0.015  0.065 -0.059  0.140  0.040  0.539 -0.009  0.090  0.314  0.090 -0.009  0.190  0.339 -0.009  0.090  0.314  0.688  0.190  0.215  0.015 -0.009 -0.059  0.065  0.140  0.613 
 0.412  0.113  0.436  0.237  0.162  0.013  0.138  0.287  0.162  0.486  0.760  0.063  0.013  0.038  0.088  0.461  0.362  0.461  0.038  0.387 -0.012 -0.062 -0.087  0.088 -0.087  0.038  0.038 -0.112  0.088 -0.012  0.561 -0.012  0.013  0.237  0.063  0.013  0.187  0.312 -0.062  0.013  0.312  0.735  0.162  0.138 -0.012 -0.012 -0.062  0.038  0.138  0.636 
 0.319  0.120  0.369  0.244  0.194  0.020  0.144  0.244  0.169  0.468  0.792  0.045  0.020  0.045  0.095  0.468  0.294  0.468  0.020  0.394 -0.055 -0.055 -0.080  0.095 -0.080  0.020  0.045 -0.105  0.095 -0.030  0.618 -0.005 -0.005  0.194  0.070  0.020  0.194  0.269 -0.055  0.020  0.294  0.792  0.169  0.095 -0.055 -0.005 -0.055  0.045  0.120  0.568 
 0.184  0.084  0.333  0.209  0.184  0.034  0.134  0.209  0.134  0.483  0.807  0.009  0.009 -0.015  0.084  0.408  0.209  0.408 -0.040  0.383 -0.040 -0.040 -0.065  0.084 -0.065 -0.015  0.059 -0.090  0.059 -0.015  0.657  0.009 -0.015  0.084  0.084  0.034  0.134  0.234 -0.040 -0.015  0.209  0.807  0.134  0.059 -0.040 -0.015 -0.040  0.059  0.134  0.533 
 0.142  0.092  0.316  0.166  0.191  0.017  0.142  0.191  0.117  0.416  0.814 -0.033 -0.008 -0.008  0.092  0.341  0.166  0.416 -0.033  0.391 -0.033 -0.033 -0.058  0.042 -0.058 -0.033  0.067 -0.083  0.042 -0.008  0.665  0.017 -0.033  0.067  0.092  0.017  0.117  0.241 -0.033 -0.008  0.166  0.814  0.142  0.067 -0.033 -0.008 -0.058  0.067  0.142  0.465 
 0.053  0.053  0.228  0.078  0.128  0.003  0.103  0.153  0.103  0.327  0.826 -0.021 -0.046  0.003  0.028  0.302  0.103  0.327 -0.046  0.377 -0.021 -0.021 -0.046  0.053 -0.046 -0.021  0.078 -0.071  0.028  0.003  0.676  0.003 -0.046  0.053  0.103 -0.046  0.128  0.228 -0.021 -0.046  0.178  0.826  0.128  0.053 -0.021  0.003 -0.046  0.003  0.078  0.427 
 0.032  0.007  0.156  0.057  0.082  0.007  0.082  0.156  0.082  0.231  0.904 -0.018 -0.043  0.007  0.007  0.306  0.057  0.306 -0.043  0.331  0.007 -0.018 -0.043  0.057 -0.043 -0.018  0.082 -0.068  0.032  0.007  0.680  0.032 -0.043  0.057  0.082 -0.043  0.107  0.206 -0.018 -0.043  0.181  0.879  0.156  0.057 -0.018  0.007 -0.043  0.007  0.057  0.381 
 0.015  0.015  0.065  0.065  0.090  0.015  0.040  0.090  0.040  0.164  0.962 -0.010 -0.035 -0.010 -0.035  0.189  0.040  0.239 -0.035  0.189 -0.010 -0.010 -0.035  0.065 -0.060  0.015  0.040 -0.035  0.015  0.015  0.737  0.040 -0.035  0.065  0.065 -0.060  0.090  0.140 -0.035 -0.035  0.115  0.962  0.115  0.065 -0.010 -0.010 -0.010  0.015  0.015  0.239 
-0.007  0.017  0.042  0.067  0.092  0.017 -0.007  0.067  0.017  0.167  0.964 -0.007 -0.032 -0.007 -0.032  0.167  0.042  0.167 -0.032  0.142 -0.007 -0.007 -0.032  0.067 -0.057  0.017  0.017 -0.032  0.042  0.017  0.790  0.017 -0.032  0.067  0.042 -0.057  0.092  0.092 -0.032 -0.032  0.092  0.964  0.092  0.067 -0.007 -0.007 -0.007  0.017  0.017  0.167 
-0.002  0.023 -0.027  0.048  0.098  0.023 -0.027  0.073  0.023  0.147  0.970 -0.027 -0.027 -0.002 -0.027  0.023  0.023 -0.002 -0.027  0.073 -0.002 -0.002 -0.027  0.073 -0.052  0.023 -0.002 -0.027  0.048  0.023  0.795  0.023 -0.027  0.048  0.023 -0.052  0.098  0.048 -0.052 -0.027  0.098  0.970  0.098  0.048 -0.002 -0.002 -0.002  0.023 -0.002  0.098 
-0.004  0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054 -0.029  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
-0.004  0.021 -0.029  0.046  0.096  0.021 -0.029  0.071  0.021  0.145  0.968 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.029  0.071 -0.004 -0.004 -0.004  0.071 -0.054  0.021 -0.004 -0.029  0.046  0.021  0.893  0.021 -0.029  0.046  0.021 -0.054  0.096  0.046 -0.054 -0.029  0.096  0.968  0.096  0.046 -0.004 -0.004 -0.004  0.021 -0.004  0.096 
-0.005  0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055 -0.005  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.016  0.116  0.066  0.091  0.216  0.041 -0.008  0.141  0.016  0.490  0.938  0.016 -0.058 -0.008 -0.033  0.041  0.016  0.016 -0.033  0.166 -0.033 -0.033 -0.033  0.091 -0.083 -0.008 -0.008  0.016  0.016  0.066  0.938  0.016 -0.058  0.066 -0.008 -0.058  0.091  0.116 -0.058 -0.008  0.191  0.938  0.166  0.066 -0.033  0.016  0.016  0.066  0.066  0.216 
 0.176  0.051  0.251  0.276  0.375  0.076  0.051  0.201  0.076  0.799  0.873  0.001 -0.023 -0.048 -0.023  0.251  0.151  0.226 -0.023  0.325 -0.023 -0.073 -0.073  0.176 -0.148  0.051  0.026  0.001  0.051  0.076  0.873 -0.023 -0.023  0.226  0.026 -0.098  0.151  0.325 -0.123 -0.048  0.300  0.873  0.251  0.076 -0.073 -0.023 -0.023  0.026  0.151  0.425 
 0.356  0.057  0.306  0.331  0.331  0.032  0.057  0.331  0.132  0.804  0.829  0.007 -0.018  0.007 -0.068  0.381  0.256  0.356 -0.043  0.480 -0.068 -0.018 -0.093  0.256 -0.192  0.057  0.082  0.032  0.032  0.107  0.829 -0.068 -0.018  0.256  0.007 -0.068  0.156  0.580 -0.142  0.032  0.306  0.829  0.356  0.132 -0.043 -0.043 -0.018  0.032  0.356  0.555 
 0.568  0.045  0.468  0.319  0.394  0.070  0.095  0.319  0.244  0.767  0.767  0.070 -0.080  0.020  0.070  0.468  0.394  0.493  0.020  0.543 -0.030 -0.005 -0.105  0.369 -0.179  0.095  0.070  0.070  0.045  0.070  0.742  0.045  0.020  0.344  0.070 -0.030  0.244  0.668 -0.179  0.144  0.369  0.767  0.394  0.194 -0.055 -0.030 -0.080  0.070  0.468  0.693 
 0.555  0.056  0.505  0.305  0.330  0.006  0.081  0.330  0.330  0.729  0.754  0.031 -0.093  0.056  0.106  0.455  0.430  0.604  0.006  0.530 -0.043  0.006 -0.118  0.380 -0.193  0.131  0.056  0.081  0.056  0.031  0.729  0.056  0.056  0.355  0.081 -0.018  0.256  0.679 -0.193  0.181  0.355  0.729  0.380  0.256 -0.018  0.006 -0.093  0.081  0.530  0.704 
 0.637  0.039  0.538  0.338  0.313 -0.010  0.114  0.313  0.338  0.712  0.737  0.064 -0.085  0.114  0.139  0.438  0.513  0.662  0.039  0.513 -0.060  0.014 -0.110  0.413 -0.210  0.164  0.064  0.114  0.064  0.014  0.587  0.064  0.089  0.463  0.114 -0.035  0.239  0.687 -0.135  0.264  0.363  0.712  0.388  0.313  0.014  0.014 -0.110  0.089  0.612  0.687 
 0.656  0.033  0.556  0.332  0.307 -0.017  0.133  0.307  0.332  0.706  0.706  0.083 -0.092  0.108  0.157  0.431  0.531  0.656  0.033  0.506 -0.067  0.008 -0.117  0.407 -0.216  0.182  0.083  0.108  0.033  0.008  0.581  0.083  0.133  0.506  0.157 -0.042  0.257  0.656 -0.117  0.282  0.357  0.706  0.382  0.357  0.008  0.008 -0.117  0.083  0.606  0.681 
 0.674  0.026  0.574  0.325  0.300  0.026  0.126  0.300  0.300  0.699  0.699  0.101 -0.099  0.126  0.150  0.449  0.599  0.649  0.051  0.524 -0.049  0.001 -0.099  0.449 -0.198  0.200  0.076  0.101  0.026  0.001  0.549  0.101  0.150  0.524  0.200 -0.074  0.250  0.649 -0.124  0.400  0.350  0.699  0.375  0.375  0.001  0.051 -0.124  0.076  0.599  0.674 
 0.671  0.023  0.547  0.322  0.297  0.023  0.073  0.297  0.297  0.671  0.696  0.098 -0.101  0.123  0.148  0.447  0.671  0.646  0.048  0.522 -0.051 -0.026 -0.076  0.447 -0.201  0.223  0.073  0.098  0.073  0.023  0.547  0.098  0.148  0.497  0.198 -0.076  0.248  0.671 -0.126  0.422  0.347  0.696  0.372  0.397  0.023  0.048 -0.126  0.073  0.571  0.671 
 0.646  0.048  0.547  0.322  0.273  0.048  0.073  0.322  0.297  0.621  0.696  0.123 -0.051  0.123  0.148  0.447  0.671  0.646  0.048  0.522 -0.051 -0.026 -0.076  0.447 -0.201  0.223  0.048  0.098  0.073  0.023  0.547  0.098  0.173  0.522  0.223 -0.076  0.297  0.671 -0.101  0.422  0.347  0.696  0.372  0.422  0.048  0.048 -0.126  0.073  0.571  0.671 
 0.619  0.021  0.569  0.320  0.271  0.046  0.071  0.295  0.295  0.619  0.694  0.121  0.046  0.121  0.146  0.445  0.669  0.644  0.046  0.520 -0.053 -0.028 -0.078  0.445 -0.203  0.246  0.046  0.096  0.071  0.021  0.545  0.096  0.196  0.545  0.246 -0.078  0.295  0.644 -0.103  0.420  0.345  0.694  0.370  0.445  0.046  0.071 -0.128  0.096  0.569  0.669 
 0.615  0.017  0.565  0.316  0.266  0.042  0.067  0.291  0.291  0.590  0.690  0.142  0.067  0.117  0.142  0.465  0.640  0.640  0.067  0.515 -0.058 -0.033 -0.083  0.440 -0.207  0.241  0.042  0.092  0.067  0.017  0.540  0.117  0.266  0.540  0.241 -0.083  0.291  0.640 -0.108  0.440  0.366  0.690  0.366  0.440  0.042  0.092 -0.133  0.117  0.590  0.665 
 0.611  0.013  0.562  0.312  0.263  0.063  0.063  0.263  0.287  0.586  0.686  0.163  0.088  0.113  0.163  0.487  0.636  0.636  0.113  0.512 -0.061 -0.036 -0.086  0.437 -0.211  0.238  0.038  0.088  0.063  0.038  0.537  0.113  0.312  0.537  0.238 -0.111  0.287  0.636 -0.111  0.487  0.362  0.686  0.362  0.437  0.038  0.088 -0.136  0.113  0.586  0.661 
 0.607  0.034  0.557  0.333  0.258  0.059  0.059  0.308  0.283  0.582  0.682  0.158  0.109  0.109  0.258  0.457  0.607  0.632  0.109  0.507 -0.066 -0.041 -0.041  0.432 -0.215  0.233  0.059  0.084  0.084  0.009  0.532  0.109  0.358  0.507  0.258 -0.141  0.283  0.632 -0.091  0.507  0.358  0.682  0.333  0.432  0.034  0.109 -0.141  0.109  0.582  0.657 
 0.605  0.032  0.555  0.331  0.256  0.057  0.057  0.331  0.256  0.580  0.680  0.156  0.132  0.107  0.256  0.455  0.605  0.630  0.107  0.505 -0.068 -0.018 -0.018  0.430 -0.217  0.231  0.057  0.082  0.107  0.007  0.530  0.107  0.356  0.505  0.306 -0.118  0.281  0.630 -0.093  0.530  0.356  0.680  0.356  0.430  0.032  0.107 -0.142  0.107  0.580  0.655 
 0.603  0.030  0.578  0.354  0.255  0.030  0.055  0.304  0.255  0.578  0.678  0.130  0.155  0.105  0.255  0.454  0.578  0.628  0.080  0.504 -0.069 -0.019 -0.019  0.404 -0.219  0.205  0.055  0.080  0.155  0.005  0.529  0.105  0.379  0.529  0.304 -0.119  0.280  0.628 -0.094  0.529  0.354  0.678  0.329  0.429  0.030  0.105 -0.144  0.105  0.554  0.653 
 0.603  0.030  0.578  0.329  0.254  0.030  0.105  0.304  0.254  0.578  0.678  0.154  0.154  0.105  0.254  0.453  0.578  0.628  0.080  0.503 -0.070 -0.020  0.005  0.379 -0.219  0.204  0.055  0.080  0.179  0.005  0.528  0.080  0.478  0.528  0.279 -0.120  0.279  0.628 -0.095  0.528  0.354  0.678  0.329  0.428  0.055  0.105 -0.144  0.105  0.553  0.653 
 0.602  0.029  0.627  0.303  0.228  0.029  0.104  0.303  0.228  0.577  0.677  0.153  0.153  0.104  0.253  0.452  0.602  0.627  0.079  0.452 -0.071 -0.021  0.004  0.328 -0.220  0.203  0.004  0.079  0.203  0.004  0.527  0.029  0.502  0.527  0.278 -0.096  0.278  0.627 -0.096  0.527  0.353  0.677  0.328  0.427  0.054  0.104 -0.170  0.104  0.552  0.627 
 0.602  0.029  0.627  0.303  0.229  0.029  0.079  0.303  0.229  0.577  0.677  0.154  0.154  0.104  0.254  0.428  0.602  0.627  0.104  0.453 -0.095  0.004  0.004  0.328 -0.220  0.204  0.004  0.079  0.229  0.004  0.528 -0.020  0.503  0.528  0.254 -0.095  0.279  0.627 -0.095  0.528  0.353  0.652  0.328  0.428  0.054  0.104 -0.170  0.104  0.553  0.627 
 0.600  0.052  0.625  0.301  0.226  0.027  0.077  0.326  0.226  0.575  0.650  0.151  0.176  0.102  0.251  0.426  0.600  0.625  0.127  0.450 -0.098  0.002  0.027  0.301 -0.222  0.251  0.002  0.102  0.276  0.002  0.525 -0.023  0.500  0.525  0.276 -0.098  0.301  0.625 -0.098  0.550  0.351  0.650  0.326  0.426  0.052  0.151 -0.197  0.102  0.550  0.625 
 0.577  0.054  0.552  0.253  0.253  0.104  0.129  0.253  0.153  0.502  0.652  0.153  0.004  0.054  0.203  0.477  0.552  0.527  0.129  0.427 -0.071  0.029  0.029  0.278 -0.170  0.228  0.054  0.104  0.153  0.004  0.527 -0.046  0.452  0.427  0.303 -0.071  0.228  0.602 -0.121  0.403  0.303  0.652  0.253  0.353  0.054  0.079 -0.170 -0.021  0.452  0.677 
 0.490  0.142  0.490  0.241  0.191  0.042  0.067  0.266  0.142  0.490  0.640  0.191 -0.008  0.042  0.166  0.465  0.440  0.490  0.117  0.465 -0.033 -0.008 -0.083  0.191 -0.108  0.092  0.067 -0.008  0.092  0.017  0.540 -0.008  0.266  0.416  0.216 -0.033  0.191  0.565 -0.058  0.291  0.266  0.640  0.166  0.191  0.092  0.042 -0.083  0.067  0.316  0.739 
 0.484  0.135  0.509  0.235  0.185  0.010  0.085  0.235  0.135  0.484  0.683  0.085 -0.014  0.060  0.110  0.484  0.409  0.459  0.085  0.434 -0.039 -0.064 -0.089  0.135 -0.089  0.085  0.035 -0.014  0.085  0.035  0.559 -0.014  0.210  0.334  0.185 -0.014  0.185  0.559 -0.064  0.235  0.260  0.658  0.135  0.210  0.010  0.035 -0.064  0.085  0.260  0.733 
 0.434  0.061  0.360  0.260  0.160  0.011  0.111  0.260  0.136  0.434  0.709  0.011 -0.014  0.061  0.086  0.484  0.335  0.459  0.036  0.434 -0.014 -0.039 -0.089  0.061 -0.064  0.036  0.061 -0.064  0.061  0.036  0.584  0.011  0.036  0.260  0.061  0.011  0.160  0.534 -0.064  0.061  0.260  0.684  0.111  0.185 -0.014  0.011 -0.039  0.061  0.235  0.733 
 0.345  0.046  0.345  0.246  0.071 -0.028  0.121  0.246  0.146  0.370  0.744 -0.028 -0.028  0.021  0.071  0.495  0.246  0.470  0.021  0.420 -0.003 -0.028 -0.078  0.046 -0.078  0.021  0.071 -0.053  0.046  0.021  0.594  0.021 -0.028  0.096  0.071 -0.028  0.171  0.520 -0.053  0.021  0.246  0.694  0.121  0.146 -0.003  0.021 -0.053  0.046  0.146  0.769 
 0.157  0.057  0.207  0.232  0.057 -0.017  0.107  0.157  0.057  0.356  0.805 -0.017 -0.017 -0.017  0.082  0.456  0.182  0.456  0.007  0.331 -0.017 -0.042 -0.067  0.057 -0.067  0.032  0.082 -0.092  0.057 -0.017  0.605  0.007 -0.017  0.107  0.032 -0.042  0.157  0.531 -0.042 -0.042  0.182  0.805  0.107  0.107 -0.042  0.032 -0.042  0.007  0.107  0.755 
 0.139  0.039  0.188  0.213  0.039 -0.011  0.064  0.114  0.014  0.263  0.811 -0.036 -0.061 -0.011  0.089  0.388  0.163  0.437 -0.011  0.313 -0.036 -0.036 -0.061  0.064 -0.061  0.039  0.089 -0.086  0.039 -0.011  0.587 -0.011 -0.036  0.039  0.039 -0.036  0.163  0.537 -0.036 -0.061  0.188  0.836  0.114  0.064 -0.036  0.039 -0.061 -0.011  0.114  0.711 
 0.097  0.047  0.097  0.221  0.047 -0.003  0.047  0.122 -0.003  0.196  0.819 -0.028 -0.078  0.022  0.047  0.321  0.097  0.421 -0.053  0.321 -0.028 -0.028 -0.053  0.072 -0.053  0.022  0.072 -0.078  0.047 -0.003  0.595 -0.003 -0.028  0.022  0.047 -0.028  0.171  0.520 -0.028 -0.053  0.171  0.844  0.122  0.047 -0.028  0.022 -0.053 -0.003  0.022  0.695 
 0.026  0.026  0.101  0.201  0.076  0.001  0.026  0.051  0.001  0.201  0.849 -0.023 -0.073  0.026  0.026  0.276  0.101  0.300 -0.048  0.325  0.001 -0.023 -0.048  0.076 -0.048  0.026  0.076 -0.073  0.051  0.001  0.649  0.026 -0.048  0.026  0.051 -0.048  0.151  0.450 -0.023 -0.048  0.176  0.873  0.126  0.051 -0.023  0.026 -0.048  0.001  0.001  0.649 
 0.034  0.034  0.034  0.109  0.084  0.009  0.034  0.059  0.009  0.158  0.906 -0.041 -0.066  0.009  0.009  0.233  0.084  0.208 -0.041  0.308 -0.016 -0.016 -0.041  0.084 -0.041  0.009  0.059 -0.066  0.059  0.009  0.632  0.034 -0.041  0.034  0.059 -0.041  0.134  0.333 -0.041 -0.041  0.183  0.931  0.134  0.009 -0.016  0.034 -0.041  0.009 -0.041  0.532 
-0.012  0.012  0.037  0.112  0.087  0.037  0.037  0.037  0.012  0.162  0.959 -0.037 -0.062  0.012  0.012  0.212  0.062  0.112 -0.037  0.262 -0.012 -0.012 -0.037  0.062 -0.037  0.012  0.062 -0.037  0.037  0.012  0.660  0.012 -0.037  0.037  0.062 -0.037  0.112  0.311 -0.037 -0.037  0.187  0.934  0.137  0.012 -0.012  0.012 -0.012  0.012 -0.037  0.411 
-0.004  0.021 -0.004  0.046  0.096  0.021 -0.004  0.046  0.021  0.170  0.968 -0.029 -0.054  0.021 -0.029  0.071  0.046  0.071 -0.029  0.170 -0.004 -0.004 -0.029  0.071 -0.054  0.021  0.046 -0.029  0.021  0.021  0.694  0.021 -0.029  0.021  0.071 -0.054  0.096  0.170 -0.054 -0.029  0.145  0.943  0.121  0.021 -0.004 -0.004 -0.004  0.021 -0.029  0.220 
-0.002  0.023 -0.002  0.048  0.098  0.023 -0.027  0.073  0.023  0.147  0.970 -0.027 -0.052 -0.002 -0.027  0.048  0.023  0.023 -0.027  0.123 -0.002 -0.002 -0.027  0.073 -0.052  0.023  0.023 -0.027  0.048  0.023  0.745  0.023 -0.027  0.023  0.048 -0.052  0.098  0.098 -0.052 -0.027  0.098  0.945  0.098  0.023 -0.002 -0.002 -0.002  0.023 -0.027  0.123 
-0.001  0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.073 -0.001 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.048  0.023  0.771  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.023 -0.001 -0.001 -0.001  0.023 -0.026  0.098 
-0.001  0.023 -0.026  0.048  0.098  0.023 -0.026  0.073  0.023  0.148  0.970 -0.026 -0.026 -0.001 -0.026  0.023  0.023 -0.001 -0.026  0.073 -0.001 -0.001 -0.026  0.073 -0.051  0.023 -0.001 -0.026  0.048  0.023  0.771  0.023 -0.026  0.048  0.023 -0.051  0.098  0.048 -0.051 -0.026  0.098  0.970  0.098  0.023 -0.001 -0.001 -0.001  0.023 -0.026  0.098 
-0.002  0.022 -0.027  0.047  0.097  0.022 -0.027  0.072  0.022  0.147  0.969 -0.027 -0.027 -0.002 -0.027  0.022  0.022 -0.002 -0.027  0.072 -0.002 -0.002 -0.027  0.072 -0.052  0.022 -0.002 -0.027  0.047  0.022  0.820  0.022 -0.027  0.047  0.022 -0.052  0.097  0.047 -0.052 -0.027  0.097  0.969  0.097  0.047 -0.002 -0.002 -0.002  0.022 -0.002  0.097 
-0.003  0.021 -0.028  0.046  0.096  0.021 -0.028  0.071  0.021  0.146  0.968 -0.028 -0.028 -0.003 -0.028  0.021  0.021 -0.003 -0.028  0.071 -0.003 -0.003 -0.028  0.071 -0.053  0.021 -0.003 -0.028  0.046  0.021  0.868  0.021 -0.028  0.046  0.021 -0.053  0.096  0.046 -0.053 -0.028  0.096  0.968  0.096  0.046 -0.003 -0.003 -0.003  0.021 -0.003  0.096 
-0.004  0.020 -0.029  0.045  0.095  0.020 -0.029  0.070  0.020  0.145  0.967 -0.029 -0.029 -0.004 -0.029  0.020  0.020 -0.004 -0.029  0.070 -0.004 -0.004 -0.004  0.070 -0.054  0.020 -0.004 -0.029  0.045  0.020  0.917  0.020 -0.029  0.045  0.020 -0.054  0.095  0.045 -0.054 -0.029  0.095  0.967  0.095  0.045 -0.004 -0.004 -0.004  0.020 -0.004  0.095 
-0.005  0.020 -0.030  0.045  0.095  0.020 -0.030  0.070  0.020  0.144  0.967 -0.030 -0.030 -0.005 -0.030  0.020  0.020 -0.005 -0.030  0.070 -0.005 -0.005 -0.005  0.070 -0.055  0.020 -0.005 -0.030  0.045  0.020  0.942  0.020 -0.030  0.045  0.020 -0.055  0.095  0.045 -0.055 -0.005  0.095  0.967  0.095  0.045 -0.005 -0.005 -0.005  0.020 -0.005  0.095 
-0.005  0.019 -0.030  0.044  0.094  0.019 -0.030  0.069  0.019  0.144  0.966 -0.030 -0.030 -0.005 -0.030  0.019  0.019 -0.005 -0.030  0.069 -0.005 -0.005 -0.005  0.069 -0.055  0.019 -0.005 -0.030  0.044  0.019  0.966  0.019 -0.030  0.044  0.019 -0.055  0.094  0.044 -0.055  0.019  0.094  0.966  0.094  0.044 -0.005 -0.005 -0.005  0.019 -0.005  0.094 
 0.045  0.070 -0.054  0.045  0.270  0.045 -0.029  0.070  0.020  0.369  0.942  0.020 -0.029 -0.029 -0.029  0.020 -0.004 -0.004 -0.029  0.145 -0.029 -0.029 -0.029  0.120 -0.079 -0.004 -0.029 -0.004  0.045 -0.004  0.942  0.045 -0.029  0.070  0.020 -0.079  0.095  0.095 -0.079  0.020  0.145  0.942  0.095  0.020 -0.029 -0.004 -0.029  0.020  0.020  0.145 
 0.209  0.084  0.084  0.159  0.408  0.009 -0.040  0.134  0.159  0.682  0.881  0.009 -0.065  0.009 -0.065  0.059  0.059  0.034 -0.040  0.234 -0.015 -0.065 -0.065  0.184 -0.115  0.009  0.009 -0.040  0.034  0.059  0.881  0.009  0.009  0.159 -0.040 -0.090  0.159  0.184 -0.090  0.059  0.308  0.881  0.084  0.134 -0.065  0.009 -0.065  0.034  0.159  0.333 
 0.388  0.064  0.139  0.114  0.537 -0.036 -0.011  0.188  0.263  0.736  0.836  0.039 -0.086 -0.011 -0.061  0.089  0.188  0.139  0.039  0.363 -0.061 -0.061 -0.036  0.263 -0.136 -0.011 -0.011 -0.036  0.089  0.114  0.836  0.039  0.064  0.288 -0.011 -0.086  0.163  0.238 -0.111  0.089  0.338  0.836  0.114  0.163  0.014  0.064 -0.086  0.064  0.263  0.487 
 0.596  0.123  0.247  0.197  0.596 -0.052  0.073  0.297  0.347  0.745  0.770  0.073 -0.102  0.048 -0.052  0.297  0.372  0.372  0.123  0.422 -0.052 -0.052 -0.052  0.322 -0.201  0.023 -0.027 -0.002  0.197  0.073  0.770  0.048  0.098  0.397 -0.002 -0.102  0.222  0.347 -0.176  0.172  0.422  0.770  0.272  0.272  0.123 -0.002 -0.127  0.098  0.347  0.646 
 0.630  0.082  0.281  0.231  0.480 -0.018  0.032  0.331  0.381  0.705  0.705  0.107 -0.093  0.032  0.007  0.406  0.455  0.505  0.181  0.430 -0.043 -0.018 -0.018  0.356 -0.217  0.007 -0.018 -0.018  0.181  0.032  0.729  0.007  0.206  0.455 -0.018 -0.118  0.231  0.406 -0.192  0.181  0.430  0.754  0.256  0.306  0.107  0.032 -0.118  0.107  0.406  0.655 
 0.647  0.049  0.423  0.224  0.448  0.024  0.074  0.348  0.448  0.672  0.672  0.099 -0.050  0.024  0.049  0.398  0.498  0.597  0.199  0.448 -0.050 -0.050 -0.000  0.348 -0.250  0.024 -0.025 -0.000  0.224  0.024  0.647 -0.000  0.224  0.523 -0.025 -0.075  0.274  0.448 -0.175  0.249  0.398  0.697  0.249  0.423  0.124 -0.000 -0.150  0.099  0.498  0.672 
 0.639  0.091  0.464  0.215  0.439 -0.009  0.066  0.390  0.439  0.664  0.614  0.141 -0.034  0.016  0.041  0.390  0.489  0.589  0.190  0.439 -0.059 -0.034 -0.034  0.340 -0.233 -0.009 -0.009 -0.009  0.265  0.016  0.639 -0.009  0.265  0.514  0.016 -0.059  0.240  0.489 -0.158  0.340  0.390  0.689  0.290  0.415  0.116  0.016 -0.183  0.066  0.489  0.664 
 0.630  0.082  0.481  0.232  0.406  0.007  0.057  0.406  0.481  0.630  0.605  0.132 -0.042  0.032  0.057  0.381  0.481  0.630  0.182  0.431 -0.092 -0.067 -0.042  0.331 -0.242 -0.017 -0.017 -0.017  0.306  0.007  0.630 -0.067  0.331  0.531  0.007 -0.017  0.232  0.580 -0.117  0.381  0.381  0.655  0.282  0.406  0.132  0.057 -0.192  0.057  0.481  0.655 
 0.598  0.100  0.473  0.224  0.399  0.000  0.075  0.448  0.473  0.623  0.598  0.125 -0.025  0.000  0.075  0.374  0.498  0.623  0.174  0.448 -0.100 -0.050 -0.050  0.324 -0.224 -0.025 -0.025 -0.025  0.349  0.000  0.623 -0.075  0.349  0.548  0.025  0.025  0.224  0.598 -0.100  0.448  0.374  0.648  0.274  0.399  0.125  0.075 -0.199  0.050  0.473  0.648 
 0.592  0.094  0.492  0.218  0.343 -0.006  0.094  0.442  0.492  0.642  0.592  0.143  0.019 -0.056  0.119  0.368  0.492  0.617  0.168  0.442 -0.106 -0.031 -0.056  0.318 -0.230 -0.031 -0.006 -0.006  0.442  0.019  0.592 -0.081  0.343  0.567  0.044  0.044  0.218  0.592 -0.106  0.492  0.343  0.642  0.293  0.418  0.143  0.119 -0.205  0.044  0.467  0.642 
 0.593  0.120  0.493  0.219  0.344 -0.005  0.095  0.443  0.493  0.643  0.593  0.144  0.045 -0.055  0.120  0.369  0.493  0.618  0.169  0.443 -0.105 -0.030 -0.055  0.319 -0.229 -0.030 -0.005 -0.005  0.443  0.020  0.593 -0.080  0.369  0.543  0.070  0.045  0.219  0.593 -0.105  0.543  0.344  0.643  0.294  0.419  0.144  0.120 -0.204  0.045  0.419  0.643 
 0.568  0.119  0.493  0.219  0.269 -0.005  0.094  0.443  0.518  0.642  0.592  0.144  0.069 -0.080  0.119  0.368  0.468  0.617  0.144  0.418 -0.105  0.019 -0.055  0.293 -0.230 -0.005 -0.005 -0.005  0.518  0.019  0.592 -0.055  0.393  0.543  0.119  0.044  0.244  0.592 -0.080  0.592  0.343  0.642  0.293  0.443  0.144  0.119 -0.205  0.019  0.368  0.617 
 0.542  0.118  0.492  0.193  0.268 -0.006  0.093  0.442  0.517  0.641  0.591  0.168  0.093 -0.056  0.118  0.392  0.467  0.616  0.143  0.417 -0.106  0.043 -0.031  0.292 -0.231 -0.006 -0.006 -0.006  0.517  0.018  0.591 -0.056  0.367  0.567  0.193  0.043  0.243  0.591 -0.081  0.591  0.342  0.641  0.292  0.442  0.143  0.143 -0.206  0.043  0.342  0.616 
 0.540  0.116  0.490  0.191  0.241 -0.033  0.166  0.440  0.515  0.639  0.589  0.166  0.091 -0.083  0.116  0.365  0.465  0.614  0.141  0.415 -0.108  0.066 -0.008  0.290 -0.233 -0.008 -0.008 -0.008  0.540  0.016  0.614 -0.033  0.440  0.565  0.216  0.016  0.266  0.589 -0.083  0.589  0.340  0.639  0.266  0.440  0.141  0.141 -0.233  0.041  0.340  0.614 
 0.542  0.118  0.467  0.143  0.218 -0.031  0.268  0.442  0.517  0.616  0.591  0.168  0.093 -0.081  0.043  0.367  0.467  0.616  0.118  0.392 -0.106  0.068  0.043  0.292 -0.231 -0.006 -0.006 -0.006  0.542  0.018  0.591 -0.031  0.467  0.567  0.218 -0.006  0.292  0.567 -0.081  0.591  0.342  0.641  0.243  0.442  0.143  0.143 -0.231  0.043  0.342  0.616 
 0.542  0.118  0.467  0.118  0.193 -0.031  0.268  0.467  0.517  0.616  0.591  0.193  0.093 -0.031  0.043  0.367  0.467  0.616  0.118  0.392 -0.106  0.068  0.093  0.292 -0.231 -0.006 -0.006 -0.006  0.542  0.018  0.616 -0.031  0.492  0.542  0.218  0.018  0.292  0.567 -0.081  0.591  0.342  0.641  0.243  0.442  0.143  0.118 -0.231  0.043  0.342  0.616 
 0.542  0.118  0.467  0.118  0.168 -0.031  0.268  0.467  0.517  0.616  0.567  0.193  0.093 -0.031  0.043  0.367  0.417  0.616  0.143  0.392 -0.106  0.068  0.093  0.292 -0.231 -0.006 -0.006  0.018  0.542  0.018  0.616 -0.031  0.492  0.542  0.218  0.018  0.292  0.542 -0.081  0.591  0.367  0.641  0.243  0.442  0.143  0.093 -0.231  0.043  0.342  0.616 
 0.544  0.096  0.469  0.121  0.145 -0.029  0.270  0.469  0.519  0.619  0.569  0.195  0.096 -0.104  0.046  0.370  0.345  0.619  0.145  0.395 -0.104  0.071  0.121  0.270 -0.228 -0.029 -0.004  0.021  0.544  0.021  0.669 -0.029  0.494  0.544  0.220  0.046  0.295  0.544 -0.079  0.594  0.370  0.619  0.245  0.444  0.121  0.071 -0.228  0.021  0.345  0.619 
 0.543  0.094  0.468  0.119  0.144 -0.030  0.269  0.468  0.518  0.617  0.568  0.194  0.094 -0.105  0.044  0.368  0.343  0.642  0.144  0.393 -0.105  0.069  0.144  0.269 -0.230 -0.030 -0.005  0.019  0.543  0.019  0.667 -0.030  0.493  0.518  0.219  0.044  0.293  0.543 -0.080  0.592  0.368  0.617  0.244  0.443  0.119  0.069 -0.230  0.044  0.343  0.617 
 0.542  0.094  0.467  0.119  0.143 -0.031  0.268  0.467  0.517  0.617  0.567  0.193  0.094 -0.106  0.044  0.368  0.343  0.642  0.143  0.393 -0.106  0.069  0.143  0.268 -0.230 -0.031 -0.006  0.019  0.542  0.019  0.667 -0.031  0.467  0.517  0.218  0.044  0.293  0.542 -0.081  0.592  0.368  0.617  0.243  0.442  0.119  0.069 -0.230  0.044  0.343  0.617 

 0.991  0.019  0.044 -0.030 -0.030  0.069  0.019  0.069 -0.005 -0.005  0.044  0.069 -0.005 -0.005  0.019 -0.030 -0.030  0.019  0.044  0.094  0.019 -0.005 -0.005  0.019  0.044 -0.030 -0.030  0.019  0.019  0.019  0.019  0.019 -0.030 -0.005 -0.030  0.044  0.069  0.019 -0.005 -0.030 -0.005 -0.005  0.044 -0.030 -0.005 -0.030  0.019  0.019 -0.030 -0.005 
 0.998  0.026  0.051 -0.023 -0.023  0.051  0.026  0.076  0.001  0.001  0.051  0.076  0.001  0.001  0.026 -0.023 -0.023  0.026  0.051  0.101  0.001  0.001  0.001  0.026  0.051 -0.023 -0.023  0.026  0.026  0.001  0.026  0.026 -0.023  0.001 -0.023  0.026  0.076  0.026  0.001 -0.023  0.001  0.001  0.026 -0.023 -0.023 -0.023  0.026  0.026 -0.023  0.001 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 1.001  0.029  0.054 -0.020 -0.020  0.054  0.029  0.079  0.004  0.004  0.054  0.079  0.004  0.004  0.029 -0.020 -0.020  0.029  0.054  0.104  0.004  0.004  0.004  0.029  0.054 -0.020 -0.020  0.029  0.029  0.004  0.029  0.029 -0.020  0.004 -0.020  0.029  0.079  0.029  0.004 -0.020  0.004  0.004  0.029 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 
 0.987  0.015  0.214 -0.035 -0.010  0.090  0.040  0.090  0.015 -0.010  0.040  0.065 -0.010 -0.010  0.065 -0.035 -0.035  0.040  0.065  0.314  0.065  0.015 -0.010  0.015  0.040 -0.035 -0.035  0.164  0.090  0.015  0.015  0.040 -0.035 -0.010 -0.035  0.090  0.189  0.040  0.040 -0.010 -0.010 -0.010  0.015 -0.010 -0.010 -0.035  0.090  0.040 -0.010 -0.010 
 0.940  0.018  0.317 -0.032 -0.007  0.118  0.093  0.118  0.018 -0.057  0.043  0.018 -0.032 -0.032  0.018 -0.007 -0.082  0.018  0.043  0.691  0.093  0.018 -0.057 -0.007  0.192 -0.032 -0.082  0.616  0.093 -0.007 -0.007  0.043 -0.057 -0.007 -0.082  0.118  0.217  0.068  0.142 -0.057  0.018 -0.007  0.018 -0.057 -0.007 -0.057  0.317  0.018 -0.032  0.043 
 0.898  0.026  0.350  0.001 -0.024  0.250  0.200  0.101  0.001 -0.099  0.001  0.026 -0.024 -0.049 -0.024  0.026 -0.024  0.051  0.001  0.773  0.175  0.026  0.001 -0.024  0.275  0.026 -0.124  0.798  0.126 -0.049  0.001  0.026 -0.049 -0.049 -0.124  0.101  0.275  0.076  0.250 -0.024  0.001 -0.049  0.051 -0.074 -0.024 -0.024  0.524 -0.024 -0.049  0.001 
 0.842 -0.005  0.543  0.144 -0.030  0.269  0.293  0.044 -0.005 -0.155 -0.030  0.094 -0.030 -0.080 -0.030  0.069  0.094  0.044 -0.005  0.817  0.194 -0.030  0.044 -0.005  0.468  0.144 -0.105  0.842  0.119 -0.080 -0.055  0.044 -0.030  0.069 -0.180  0.144  0.318  0.194  0.318 -0.005  0.019 -0.105  0.044 -0.130 -0.005  0.094  0.692 -0.055 -0.055 -0.005 
 0.810  0.012  0.610  0.212 -0.062  0.361  0.361  0.062 -0.037 -0.137 -0.012  0.237 -0.062 -0.112 -0.037  0.087  0.162  0.037 -0.037  0.785  0.361 -0.012  0.087  0.012  0.511  0.187 -0.112  0.785  0.112 -0.087 -0.087  0.062 -0.012  0.062 -0.212  0.137  0.262  0.237  0.311  0.087  0.012 -0.137  0.087 -0.137  0.037  0.112  0.685 -0.037 -0.112 -0.062 
 0.769  0.071  0.594  0.271 -0.078  0.345  0.420  0.096  0.021 -0.178 -0.028  0.246 -0.078 -0.153 -0.028  0.146  0.171  0.021 -0.053  0.744  0.370 -0.028  0.171  0.021  0.569  0.221 -0.128  0.744  0.121 -0.103 -0.128  0.121 -0.053  0.046 -0.203  0.121  0.295  0.271  0.320  0.121  0.021 -0.128  0.046 -0.128  0.071  0.196  0.669 -0.053 -0.153 -0.028 
 0.755  0.132  0.556  0.257 -0.167  0.306  0.431  0.132  0.032 -0.192 -0.042  0.331 -0.092 -0.142 -0.042  0.182  0.157  0.007 -0.067  0.705  0.406 -0.067  0.157  0.107  0.556  0.257 -0.142  0.705  0.082 -0.117 -0.092  0.132 -0.067  0.032 -0.192  0.107  0.257  0.306  0.356  0.132  0.007 -0.167  0.032 -0.142  0.057  0.356  0.680 -0.092 -0.192 -0.017 
 0.737  0.139  0.538  0.338 -0.185  0.288  0.438  0.164  0.039 -0.210 -0.060  0.388 -0.060 -0.160 -0.010  0.214  0.139 -0.010 -0.060  0.662  0.413 -0.110  0.114  0.114  0.488  0.239 -0.110  0.687  0.064 -0.110 -0.110  0.089 -0.085  0.039 -0.160  0.064  0.313  0.288  0.413  0.164 -0.035 -0.160 -0.010 -0.160  0.039  0.463  0.662 -0.110 -0.210 -0.010 
 0.735  0.212  0.536  0.362 -0.211  0.287  0.436  0.212  0.013 -0.211 -0.062  0.387 -0.062 -0.161 -0.012  0.212  0.162 -0.012 -0.062  0.636  0.387 -0.137  0.113  0.138  0.436  0.262 -0.087  0.686  0.063 -0.112 -0.112  0.063 -0.087  0.088 -0.161  0.088  0.337  0.237  0.412  0.162 -0.037 -0.161 -0.012 -0.161  0.038  0.486  0.636 -0.137 -0.236 -0.012 
 0.728  0.255  0.529  0.354 -0.219  0.280  0.379  0.205  0.005 -0.169 -0.044  0.429 -0.069 -0.069 -0.044  0.230  0.155 -0.019 -0.044  0.603  0.379 -0.144  0.080  0.130  0.429  0.304 -0.094  0.653  0.105 -0.094 -0.069  0.055 -0.069  0.105 -0.169  0.055  0.379  0.230  0.429  0.180 -0.044 -0.119 -0.019 -0.169  0.080  0.529  0.578 -0.119 -0.244 -0.019 
 0.724  0.251  0.525  0.325 -0.223  0.300  0.325  0.226  0.026 -0.173  0.001  0.500 -0.073 -0.073 -0.048  0.226  0.176 -0.023 -0.023  0.599  0.350 -0.123  0.076  0.101  0.425  0.325 -0.098  0.624  0.101 -0.123 -0.073  0.001 -0.073  0.126 -0.173  0.051  0.375  0.226  0.425  0.226 -0.073 -0.123  0.001 -0.148  0.076  0.525  0.574 -0.123 -0.198 -0.048 
 0.719  0.296  0.520  0.321 -0.252  0.296  0.321  0.221  0.047 -0.177 -0.003  0.520 -0.053 -0.028 -0.028  0.196  0.196 -0.028  0.022  0.495  0.346 -0.152  0.097  0.097  0.421  0.321 -0.103  0.620  0.097 -0.128 -0.078 -0.003 -0.103  0.146 -0.202  0.072  0.371  0.221  0.421  0.221 -0.152 -0.152 -0.003 -0.128  0.146  0.545  0.520 -0.128 -0.202 -0.028 
 0.715  0.342  0.491  0.317 -0.256  0.317  0.317  0.217  0.043 -0.181 -0.007  0.516 -0.032 -0.032 -0.057  0.167  0.217 -0.032  0.043  0.466  0.367 -0.181  0.118  0.068  0.417  0.317 -0.107  0.616  0.093 -0.132 -0.082 -0.007 -0.107  0.142 -0.181  0.043  0.392  0.217  0.392  0.217 -0.181 -0.156 -0.007 -0.132  0.167  0.541  0.516 -0.132 -0.206 -0.057 
 0.711  0.338  0.487  0.313 -0.260  0.338  0.313  0.213  0.039 -0.160 -0.011  0.537 -0.036 -0.011 -0.036  0.163  0.238 -0.036  0.039  0.462  0.363 -0.185  0.114  0.064  0.437  0.263 -0.111  0.587  0.089 -0.136 -0.036 -0.036 -0.111  0.188 -0.160  0.039  0.388  0.163  0.388  0.213 -0.210 -0.160 -0.011 -0.160  0.163  0.537  0.512 -0.136 -0.185 -0.061 
 0.701  0.327  0.477  0.352 -0.246  0.352  0.302  0.203  0.028 -0.171  0.028  0.601 -0.046  0.003  0.003  0.153  0.253 -0.046  0.028  0.452  0.327 -0.196  0.128  0.078  0.452  0.253 -0.046  0.576  0.153 -0.121 -0.046 -0.046 -0.146  0.178 -0.171  0.028  0.377  0.153  0.377  0.203 -0.221 -0.146  0.003 -0.171  0.153  0.552  0.502 -0.146 -0.196 -0.046 
 0.674  0.325  0.474  0.400 -0.248  0.400  0.225  0.225  0.001 -0.173  0.026  0.599 -0.024  0.001 -0.024  0.150  0.250 -0.049  0.001  0.449  0.275 -0.223  0.126  0.051  0.449  0.275 -0.024  0.574  0.150 -0.124 -0.049 -0.049 -0.148  0.150 -0.173  0.076  0.375  0.126  0.350  0.225 -0.248 -0.099  0.001 -0.198  0.150  0.524  0.474 -0.148 -0.198 -0.099 
 0.672  0.323  0.447  0.398 -0.225  0.398  0.223  0.223 -0.001 -0.175 -0.001  0.572 -0.001 -0.026  0.024  0.148  0.248 -0.051 -0.001  0.398  0.223 -0.250  0.124  0.024  0.423  0.273 -0.001  0.547  0.148 -0.101 -0.051 -0.026 -0.150  0.099 -0.150  0.074  0.398  0.124  0.348  0.223 -0.250 -0.101 -0.001 -0.200  0.124  0.522  0.472 -0.150 -0.200 -0.150 
 0.644  0.295  0.420  0.345 -0.228  0.395  0.221  0.221 -0.003 -0.178 -0.003  0.569  0.071 -0.028  0.046  0.121  0.271 -0.053 -0.003  0.395  0.196 -0.253  0.096  0.021  0.395  0.295 -0.003  0.545  0.146 -0.078 -0.028 -0.003 -0.153  0.046 -0.153  0.096  0.395  0.046  0.345  0.221 -0.253 -0.103 -0.028 -0.178  0.121  0.520  0.470 -0.153 -0.203 -0.203 
 0.643  0.294  0.419  0.344 -0.229  0.394  0.169  0.194 -0.005 -0.179 -0.005  0.593  0.095 -0.005  0.070  0.120  0.269 -0.055 -0.005  0.394  0.194 -0.254  0.095 -0.005  0.394  0.319 -0.005  0.543  0.144 -0.080 -0.030 -0.005 -0.179  0.070 -0.154  0.095  0.369  0.070  0.344  0.269 -0.254 -0.105 -0.030 -0.179  0.144  0.518  0.468 -0.130 -0.204 -0.229 
 0.619  0.271  0.395  0.320 -0.228  0.395  0.071  0.171 -0.003 -0.178 -0.028  0.594  0.096 -0.003  0.046  0.096  0.271 -0.078 -0.028  0.395  0.171 -0.253  0.096 -0.003  0.395  0.295 -0.003  0.520  0.171 -0.053 -0.053 -0.003 -0.178  0.071 -0.128  0.096  0.345  0.071  0.345  0.271 -0.253 -0.103 -0.028 -0.153  0.121  0.520  0.470 -0.103 -0.178 -0.228 
 0.570  0.271  0.371  0.221 -0.177  0.321  0.022  0.146  0.047 -0.128 -0.003  0.520  0.122  0.072  0.072 -0.003  0.271 -0.028  0.022  0.346  0.196 -0.202  0.022 -0.053  0.346  0.246  0.072  0.495  0.022 -0.003 -0.053 -0.028 -0.128  0.022 -0.103  0.171  0.346  0.097  0.371  0.196 -0.177 -0.028 -0.053 -0.103  0.122  0.520  0.470 -0.078 -0.152 -0.227 
 0.535  0.186  0.236  0.186 -0.138  0.285  0.036  0.161  0.011 -0.063  0.011  0.261  0.161  0.061  0.061  0.011  0.211  0.011  0.036  0.285  0.086 -0.138  0.011 -0.013  0.285  0.161  0.136  0.385  0.036 -0.013  0.011 -0.088 -0.163  0.061 -0.113  0.161  0.310  0.086  0.310  0.011 -0.138 -0.038 -0.038 -0.088  0.136  0.385  0.360 -0.013 -0.088 -0.163 
 0.502  0.203  0.253  0.178 -0.146  0.253  0.028  0.153  0.028 -0.046  0.028  0.153  0.153  0.028  0.028  0.028  0.228  0.028  0.053  0.278  0.028 -0.121 -0.021 -0.021  0.228  0.078  0.128  0.402  0.003  0.003  0.003 -0.096 -0.146  0.053 -0.096  0.178  0.253  0.078  0.228 -0.046 -0.121 -0.046 -0.021 -0.071  0.128  0.352  0.302  0.003 -0.071 -0.146 
 0.480  0.156  0.206  0.107 -0.118  0.132  0.007  0.107  0.057 -0.043  0.057  0.057  0.107  0.057  0.032  0.057  0.156  0.007  0.082  0.256  0.007 -0.093 -0.043 -0.018  0.206  0.057  0.107  0.356  0.007  0.007  0.032 -0.118 -0.118  0.057 -0.043  0.181  0.231  0.007  0.132 -0.068 -0.093 -0.018 -0.018 -0.043  0.132  0.331  0.156  0.032 -0.068 -0.118 
 0.490  0.166  0.216  0.042 -0.108  0.117  0.017  0.067  0.042 -0.033  0.067  0.067  0.092  0.042  0.042  0.067  0.166 -0.008  0.092  0.241  0.017 -0.083 -0.033 -0.008  0.191  0.042  0.092  0.341  0.017 -0.008  0.042 -0.108 -0.108  0.092 -0.033  0.191  0.166 -0.033  0.067 -0.083 -0.083 -0.008 -0.008 -0.033  0.142  0.316  0.117  0.042 -0.058 -0.108 
 0.485  0.161  0.211 -0.013 -0.088  0.011  0.036  0.061 -0.038 -0.038  0.061 -0.063  0.111  0.061 -0.013  0.036  0.161 -0.013  0.086  0.211  0.036 -0.063 -0.013  0.011  0.186  0.036  0.086  0.285  0.036 -0.038  0.036 -0.063 -0.088  0.011 -0.013  0.211  0.086 -0.013  0.011 -0.063 -0.063 -0.013  0.036 -0.013  0.111  0.236  0.036  0.061 -0.038 -0.088 
 0.444  0.121  0.170 -0.029 -0.079 -0.029 -0.029  0.046 -0.029 -0.029  0.046 -0.079  0.121  0.046 -0.029  0.046  0.145 -0.004  0.096  0.245  0.021 -0.054 -0.004  0.021  0.170  0.021  0.071  0.270  0.021 -0.029 -0.004 -0.054 -0.079 -0.004 -0.004  0.170  0.046 -0.029  0.021 -0.054 -0.054 -0.004  0.046 -0.004  0.096  0.220  0.046  0.021 -0.029 -0.079 
 0.338  0.039  0.114 -0.010 -0.060 -0.010 -0.010  0.014 -0.035 -0.060 -0.010 -0.060  0.114  0.039 -0.035  0.064  0.114  0.014  0.114  0.214  0.039 -0.035  0.014 -0.010  0.114  0.014  0.064  0.214  0.014 -0.060 -0.035 -0.035 -0.060 -0.035 -0.010  0.189 -0.010 -0.010  0.014 -0.035 -0.035 -0.010  0.039 -0.035  0.089  0.114  0.064  0.014 -0.035 -0.060 
 0.225  0.051  0.051  0.001 -0.049  0.001  0.026  0.001 -0.049 -0.049  0.001 -0.049  0.101  0.001 -0.024  0.051  0.101  0.026  0.101  0.175  0.026 -0.024  0.026  0.001  0.101  0.026  0.026  0.200  0.026 -0.049 -0.024 -0.024 -0.049 -0.024  0.001  0.150  0.001  0.001  0.026 -0.049 -0.024  0.001  0.051 -0.049  0.076  0.101  0.051 -0.024 -0.049 -0.024 
 0.163  0.063  0.063 -0.011 -0.036  0.013 -0.011 -0.011 -0.036 -0.036 -0.011 -0.036  0.113  0.013 -0.036  0.013  0.088 -0.011  0.113  0.088  0.013 -0.011  0.038  0.013  0.038  0.013  0.013  0.113  0.038 -0.011 -0.036  0.013 -0.036 -0.011 -0.011  0.113 -0.036  0.013 -0.011 -0.036  0.013 -0.011  0.038 -0.036  0.038  0.013  0.038 -0.011 -0.036  0.013 
 0.141  0.066  0.041 -0.008 -0.033 -0.008 -0.008 -0.008 -0.033 -0.033 -0.008 -0.033  0.116  0.016 -0.033 -0.008  0.091 -0.033  0.066  0.066  0.016 -0.008  0.041  0.016  0.016 -0.008  0.016  0.041 -0.008 -0.008 -0.033  0.016 -0.033  0.016 -0.008  0.066 -0.033  0.016 -0.033 -0.008  0.016 -0.008  0.041 -0.033  0.041  0.016  0.016 -0.008 -0.033  0.016 
 0.120  0.045  0.045 -0.004 -0.029 -0.004 -0.004 -0.004 -0.029 -0.029 -0.029 -0.029  0.120 -0.004 -0.029 -0.004  0.070 -0.029  0.070  0.070  0.020 -0.004  0.045  0.020  0.020 -0.004 -0.004 -0.004 -0.029 -0.004 -0.029  0.020 -0.029  0.020 -0.004  0.045 -0.029  0.020 -0.029 -0.004  0.020 -0.029  0.045 -0.029  0.020  0.020  0.020 -0.004 -0.029  0.020 
 0.123  0.048  0.048 -0.001 -0.026 -0.001 -0.001 -0.001 -0.026 -0.026 -0.026 -0.026  0.123 -0.001 -0.026 -0.001  0.073 -0.026  0.073  0.073  0.023 -0.001  0.023  0.023  0.023 -0.001 -0.001 -0.001 -0.026 -0.001 -0.026  0.023 -0.026  0.023 -0.001  0.023 -0.026  0.023 -0.026 -0.001  0.023 -0.026  0.048 -0.026  0.023  0.023  0.023 -0.001 -0.026 -0.001 
 0.079  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.079  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.079  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.079  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.079  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.079  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.079  0.029  0.054  0.004 -0.020  0.004  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.079  0.004 -0.020  0.004  0.029 -0.020 -0.020  0.054  0.004  0.004  0.004  0.029  0.029  0.004  0.004  0.004 -0.020  0.004 -0.020  0.029 -0.020  0.029 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.004 -0.020  0.029 -0.020  0.004  0.004  0.029  0.004 -0.020  0.004 
 0.076  0.051  0.051  0.001 -0.024  0.001  0.026  0.026 -0.024 -0.024 -0.024 -0.024  0.101  0.001 -0.024  0.001  0.076 -0.024 -0.024  0.101  0.001  0.001  0.001  0.026  0.101  0.001  0.001  0.001 -0.024  0.001 -0.024  0.026 -0.024  0.026 -0.024  0.001 -0.024  0.001 -0.024  0.001  0.001 -0.024  0.051 -0.024  0.001  0.026  0.026  0.001 -0.024  0.026 
 0.161  0.037  0.087  0.012 -0.038  0.012  0.037  0.037 -0.013 -0.038 -0.013 -0.038  0.137 -0.013 -0.013 -0.013  0.062 -0.038 -0.013  0.211 -0.013  0.012  0.012  0.037  0.435  0.012 -0.013  0.037  0.012 -0.013 -0.038  0.012 -0.038  0.112 -0.013  0.037 -0.038 -0.013 -0.038 -0.013 -0.013  0.012  0.087 -0.038  0.012  0.012  0.037 -0.013 -0.038  0.037 
 0.494  0.046  0.245  0.021 -0.054 -0.004  0.170  0.096 -0.004 -0.054 -0.029 -0.004  0.145 -0.029  0.021 -0.054  0.096  0.046 -0.029  0.594 -0.029  0.046 -0.029  0.046  0.619  0.046  0.046  0.220  0.021 -0.029 -0.004  0.046 -0.029  0.195 -0.054  0.096  0.121  0.021  0.096 -0.029 -0.029 -0.004  0.046 -0.079 -0.029  0.021  0.096 -0.004 -0.029  0.046 
 0.814  0.067  0.416  0.042 -0.058  0.092  0.216  0.067  0.042 -0.083  0.067  0.067  0.117 -0.033  0.017 -0.033  0.191  0.017 -0.008  0.839 -0.033 -0.008  0.017  0.017  0.864  0.067  0.042  0.440  0.117 -0.108 -0.008  0.042 -0.058  0.191 -0.108  0.216  0.142  0.142  0.241 -0.008 -0.058 -0.033  0.067 -0.108  0.191  0.067  0.191  0.042 -0.033  0.092 
 0.807  0.085  0.433 -0.015 -0.065  0.159  0.234  0.010  0.085 -0.115  0.110  0.060  0.159 -0.040 -0.015 -0.065  0.209  0.010 -0.015  0.832 -0.065 -0.040 -0.015 -0.015  0.832  0.110  0.135  0.633  0.135 -0.090 -0.015  0.110 -0.090  0.110 -0.090  0.209  0.184  0.184  0.259  0.010 -0.015 -0.065  0.060 -0.115  0.184  0.060  0.209  0.010 -0.065  0.085 
 0.752  0.030  0.528  0.080 -0.120  0.254  0.279 -0.020  0.080 -0.120  0.130  0.080  0.105 -0.020  0.055 -0.045  0.279  0.005 -0.045  0.752 -0.120 -0.045 -0.045 -0.070  0.752  0.130  0.179  0.727  0.229 -0.095  0.055  0.105 -0.095  0.030 -0.070  0.204  0.154  0.154  0.404  0.030 -0.045 -0.095  0.030 -0.120  0.204  0.179  0.254  0.005 -0.144  0.055 
 0.730  0.007  0.531  0.107 -0.142  0.257  0.331  0.007  0.082 -0.117  0.132  0.082  0.082  0.007  0.082 -0.042  0.306  0.007 -0.067  0.680 -0.117 -0.092  0.007 -0.017  0.730  0.207  0.207  0.680  0.207 -0.067  0.057  0.107 -0.142  0.057 -0.117  0.182  0.207  0.182  0.381  0.082 -0.092 -0.117  0.057 -0.117  0.182  0.207  0.232 -0.017 -0.167  0.057 
 0.676  0.028  0.477  0.128 -0.171  0.327  0.327  0.078  0.103 -0.146  0.103  0.028  0.078  0.053  0.053 -0.046  0.302 -0.021 -0.046  0.626 -0.146 -0.121  0.053 -0.021  0.626  0.203  0.203  0.651  0.153 -0.046  0.028  0.103 -0.171  0.028 -0.171  0.178  0.228  0.203  0.402  0.078 -0.146 -0.071  0.028 -0.146  0.153  0.228  0.203 -0.071 -0.196  0.028 
 0.640  0.042  0.465  0.142 -0.207  0.341  0.316  0.092  0.092 -0.157  0.067  0.017  0.092  0.042  0.042 -0.008  0.316 -0.033 -0.058  0.540 -0.133 -0.182  0.042 -0.008  0.590  0.216  0.191  0.640  0.142 -0.033  0.017  0.117 -0.182  0.067 -0.182  0.166  0.241  0.166  0.416  0.117 -0.157 -0.108  0.017 -0.157  0.117  0.216  0.216 -0.083 -0.157  0.017 
 0.581  0.058  0.456  0.133 -0.216  0.332  0.307  0.133  0.133 -0.166  0.058 -0.017  0.083  0.033  0.008 -0.042  0.207 -0.042 -0.017  0.506 -0.117 -0.191  0.058 -0.017  0.531  0.207  0.182  0.631  0.108 -0.017 -0.017  0.083 -0.191  0.058 -0.216  0.157  0.282  0.083  0.407  0.108 -0.166 -0.117 -0.017 -0.166  0.083  0.257  0.207 -0.092 -0.117  0.008 
 0.507  0.058  0.457  0.133 -0.216  0.332  0.283  0.133  0.158 -0.191  0.033  0.008  0.083  0.033 -0.041 -0.066  0.183 -0.066 -0.016  0.482 -0.116 -0.216  0.058 -0.041  0.507  0.208  0.183  0.631  0.083  0.058 -0.041  0.083 -0.191  0.058 -0.216  0.158  0.283  0.083  0.407  0.108 -0.191 -0.091 -0.016 -0.191  0.083  0.258  0.208 -0.066 -0.116 -0.016 
 0.479  0.155  0.454  0.081 -0.218  0.330  0.280  0.180  0.155 -0.193  0.031 -0.019  0.081  0.006 -0.044 -0.069  0.131 -0.094 -0.019  0.479 -0.119 -0.243 -0.019 -0.044  0.454  0.205  0.155  0.629  0.056  0.056 -0.094  0.031 -0.168  0.056 -0.218  0.180  0.280  0.081  0.405  0.106 -0.168 -0.094 -0.019 -0.193  0.056  0.280  0.180 -0.069 -0.094  0.006 
 0.456  0.157  0.456  0.057 -0.217  0.331  0.282  0.182  0.157 -0.192  0.032 -0.017  0.082 -0.017 -0.042 -0.067  0.107 -0.092 -0.017  0.481 -0.117 -0.242 -0.017 -0.042  0.456  0.232  0.157  0.630  0.057  0.032 -0.092  0.007 -0.167  0.057 -0.217  0.182  0.282  0.082  0.406  0.107 -0.192 -0.092 -0.017 -0.192  0.057  0.282  0.157 -0.067 -0.092  0.007 
 0.430  0.181  0.430  0.056 -0.218  0.330  0.256  0.206  0.181 -0.193  0.031  0.006  0.081 -0.018 -0.043 -0.068  0.081 -0.093 -0.018  0.430 -0.118 -0.268  0.031 -0.043  0.430  0.281  0.181  0.579  0.031  0.031 -0.093 -0.018 -0.168  0.056 -0.218  0.181  0.256  0.081  0.405  0.106 -0.218 -0.093 -0.018 -0.218  0.006  0.281  0.231 -0.068 -0.043  0.031 
 0.405  0.181  0.405  0.006 -0.218  0.305  0.206  0.206  0.181 -0.193  0.006 -0.043  0.081 -0.018 -0.043 -0.093  0.081 -0.118 -0.043  0.430 -0.068 -0.268  0.031 -0.043  0.430  0.281  0.181  0.555  0.031  0.006 -0.093 -0.018 -0.143  0.056 -0.218  0.156  0.281  0.081  0.355  0.131 -0.218 -0.093 -0.043 -0.218  0.006  0.256  0.231 -0.068 -0.018  0.006 
 0.378  0.178  0.328 -0.021 -0.195  0.303  0.228  0.178  0.178 -0.195  0.004 -0.071  0.104 -0.021 -0.071 -0.096  0.104 -0.071 -0.046  0.378 -0.046 -0.270  0.029 -0.071  0.353  0.278  0.203  0.552 -0.021 -0.021 -0.096 -0.071 -0.145  0.054 -0.195  0.129  0.378  0.054  0.278  0.129 -0.220 -0.096 -0.071 -0.220 -0.021  0.278  0.303 -0.021 -0.021  0.029 
 0.376  0.177  0.277 -0.047 -0.197  0.252  0.127  0.177  0.177 -0.197 -0.022 -0.047  0.102  0.002 -0.072 -0.122  0.102 -0.072  0.027  0.401 -0.072 -0.272  0.027 -0.022  0.376  0.277  0.202  0.526 -0.022 -0.022 -0.097 -0.072 -0.147  0.077 -0.172  0.127  0.376  0.052  0.277  0.152 -0.222 -0.097 -0.072 -0.222  0.002  0.252  0.301 -0.022 -0.022  0.002 
 0.372  0.173  0.273 -0.076 -0.201  0.248  0.098  0.173  0.173 -0.201 -0.026 -0.026  0.098  0.023 -0.076 -0.101  0.073 -0.051  0.023  0.372  0.023 -0.276  0.048 -0.026  0.372  0.248  0.173  0.522 -0.001 -0.026 -0.101 -0.101 -0.126  0.073 -0.176  0.123  0.397  0.023  0.273  0.148 -0.226 -0.101 -0.076 -0.201 -0.001  0.273  0.297 -0.001 -0.026 -0.001 
 0.374  0.175  0.275 -0.074 -0.199  0.250  0.100  0.175  0.150 -0.199 -0.024 -0.049  0.125  0.075 -0.074 -0.099  0.075 -0.074 -0.024  0.374  0.025 -0.274  0.025 -0.024  0.374  0.275  0.175  0.499  0.000 -0.024 -0.099 -0.099 -0.099  0.075 -0.199  0.125  0.399  0.025  0.250  0.125 -0.224 -0.099 -0.074 -0.224  0.000  0.275  0.275  0.025 -0.024  0.000 
 0.349  0.175  0.225 -0.074 -0.224  0.275  0.100  0.150  0.100 -0.199 -0.024 -0.074  0.125  0.075 -0.074 -0.099  0.050 -0.074  0.000  0.324  0.025 -0.274  0.025 -0.074  0.349  0.275  0.175  0.499  0.000 -0.049 -0.099 -0.174 -0.074  0.050 -0.199  0.125  0.374  0.000  0.250  0.150 -0.224 -0.099 -0.074 -0.224 -0.024  0.299  0.250  0.025 -0.049  0.000 
 0.347  0.147  0.123 -0.027 -0.151  0.247 -0.002  0.172  0.048 -0.127  0.048 -0.052  0.073  0.098 -0.077 -0.027  0.023 -0.102 -0.052  0.297 -0.052 -0.201 -0.002 -0.052  0.272  0.297  0.147  0.471  0.048 -0.077 -0.027 -0.127 -0.176  0.048 -0.176  0.098  0.272  0.023  0.222  0.098 -0.176 -0.052 -0.077 -0.151  0.023  0.322  0.197 -0.027 -0.052 -0.077 
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 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 

 0.991 -0.005  0.019 -0.030 -0.005 -0.030 -0.005 -0.005  0.019 -0.030  0.044  0.044  0.044 -0.005  0.019 -0.005  0.044 -0.005  0.019 -0.030  0.019 -0.030 -0.030 -0.005 -0.005  0.044 -0.005 -0.005 -0.030 -0.005 -0.030 -0.005 -0.030  0.019  0.019 -0.030 -0.005 -0.030  0.044  0.044 -0.005 -0.030  0.019 -0.030 -0.030  0.069 -0.005 -0.030 -0.005 -0.030 
 0.998  0.001  0.026 -0.023 -0.023 -0.023  0.001  0.001  0.026 -0.023  0.026  0.051  0.051 -0.023  0.001  0.001  0.051  0.001  0.001 -0.023  0.001 -0.023 -0.023  0.001  0.001  0.026  0.001  0.001 -0.023  0.001 -0.023 -0.023 -0.023  0.026  0.026 -0.023  0.001 -0.023  0.051  0.026  0.001 -0.023  0.001 -0.023 -0.023  0.051  0.001 -0.023  0.001 -0.023 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.001  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004  0.029 -0.020  0.029  0.054  0.054 -0.020  0.004  0.004  0.054 -0.020  0.004 -0.020  0.004 -0.020 -0.020  0.004  0.004  0.029  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.029  0.029 -0.020  0.004 -0.020  0.054  0.029 -0.020 -0.020  0.004 -0.020 -0.020  0.054  0.004 -0.020 -0.020 -0.020 
 1.000  0.004  0.029 -0.021 -0.021 -0.021 -0.021  0.004  0.029 -0.021  0.029  0.054  0.079 -0.021  0.004  0.004  0.054 -0.021  0.004 -0.021  0.004 -0.021 -0.021  0.004  0.004  0.029  0.004  0.004 -0.021  0.004 -0.021 -0.021 -0.021  0.029  0.029  0.004  0.004 -0.021  0.054  0.029 -0.021 -0.021  0.004 -0.021 -0.021  0.054  0.004 -0.021 -0.021 -0.021 
 0.998  0.001  0.026  0.001 -0.023 -0.023 -0.023  0.001  0.026 -0.023  0.026  0.051  0.076 -0.023  0.001  0.001  0.076 -0.023  0.001 -0.023  0.001 -0.023 -0.023  0.001  0.001  0.026  0.026  0.001 -0.023  0.001 -0.023 -0.023 -0.023  0.026  0.051  0.001  0.001 -0.023  0.076  0.026 -0.023 -0.023  0.001 -0.023 -0.023  0.051  0.001 -0.023 -0.023 -0.023 
 0.985  0.013  0.038 -0.012 -0.037  0.013 -0.037 -0.012  0.038 -0.037  0.038  0.088  0.063 -0.037  0.013 -0.012  0.088 -0.012  0.013 -0.037 -0.012 -0.037 -0.037 -0.012 -0.012  0.013  0.013  0.013 -0.012 -0.012 -0.037 -0.037 -0.037  0.038  0.113 -0.012 -0.012 -0.037  0.088  0.063 -0.037 -0.037 -0.012 -0.037 -0.037  0.088  0.038 -0.037 -0.037 -0.037 
 0.950  0.028  0.003  0.078 -0.071  0.028 -0.071 -0.046  0.003 -0.046  0.028  0.078  0.078 -0.021  0.028  0.003  0.128 -0.046  0.028 -0.021  0.028 -0.071 -0.021 -0.046  0.003  0.028  0.028  0.053 -0.021 -0.021 -0.071 -0.071 -0.071  0.003  0.078  0.053  0.003 -0.071  0.078  0.053 -0.071 -0.046 -0.021 -0.021 -0.046  0.153  0.028  0.003  0.003 -0.046 
 0.884  0.062  0.012  0.037 -0.063  0.037 -0.013 -0.063  0.012 -0.063  0.012  0.062  0.087  0.037  0.062 -0.013  0.137 -0.063  0.062 -0.038 -0.038 -0.138 -0.038 -0.088  0.012 -0.013  0.137 -0.013 -0.013 -0.038 -0.038 -0.063 -0.088  0.062  0.012  0.012  0.112 -0.113  0.087 -0.013 -0.113 -0.088  0.062  0.012 -0.088  0.112 -0.013 -0.038 -0.038 -0.063 
 0.843  0.070 -0.004  0.070 -0.054  0.045 -0.054 -0.029  0.045 -0.104 -0.004  0.045  0.070 -0.004  0.020 -0.004  0.095 -0.079  0.070 -0.029 -0.079 -0.104 -0.029 -0.104  0.070  0.045  0.120 -0.004 -0.029 -0.054 -0.029 -0.104 -0.104  0.070 -0.029  0.020  0.120 -0.129  0.095 -0.029 -0.154 -0.104  0.045  0.020 -0.129  0.120  0.020 -0.079 -0.004 -0.104 
 0.782  0.109 -0.015  0.034 -0.115 -0.015 -0.090  0.009  0.084 -0.165 -0.015  0.009  0.009  0.009 -0.015 -0.065  0.084 -0.165  0.059  0.009 -0.040 -0.140  0.009 -0.115  0.159  0.034  0.109  0.059 -0.015 -0.065 -0.065 -0.165 -0.190  0.084 -0.090 -0.015  0.259 -0.115  0.034 -0.090 -0.140 -0.115 -0.040  0.084 -0.140  0.059  0.034 -0.090 -0.040 -0.165 
 0.712  0.115 -0.010  0.040 -0.135 -0.010 -0.135  0.015  0.140 -0.209 -0.035  0.040  0.015 -0.035 -0.085 -0.135  0.065 -0.184 -0.010  0.065 -0.060 -0.159  0.015 -0.135  0.214  0.040  0.140  0.090  0.015 -0.060 -0.085 -0.184 -0.209  0.040 -0.085  0.015  0.289 -0.110  0.015 -0.060 -0.159 -0.135 -0.085  0.065 -0.110  0.040  0.090 -0.060 -0.010 -0.209 
 0.654  0.155  0.006 -0.019 -0.193  0.006 -0.119  0.056  0.081 -0.243 -0.044  0.056 -0.019  0.031 -0.094 -0.168  0.056 -0.168  0.031  0.155 -0.044 -0.193  0.031 -0.143  0.255  0.006  0.106  0.205 -0.019 -0.094 -0.069 -0.218 -0.218  0.006 -0.143  0.006  0.305 -0.094  0.031 -0.044 -0.218 -0.143 -0.119  0.180 -0.119  0.006  0.155 -0.044  0.031 -0.218 
 0.618  0.170 -0.004 -0.004 -0.204 -0.004 -0.129  0.120  0.020 -0.254 -0.054  0.095 -0.054  0.045 -0.104 -0.129  0.045 -0.154  0.020  0.170  0.045 -0.204  0.045 -0.129  0.245  0.045  0.070  0.245 -0.004 -0.104 -0.079 -0.254 -0.179 -0.004 -0.154 -0.004  0.294 -0.104  0.070 -0.004 -0.229 -0.154 -0.104  0.220 -0.129  0.020  0.220 -0.029  0.020 -0.229 
 0.583  0.209  0.035 -0.015 -0.214  0.060 -0.115  0.159  0.010 -0.239 -0.015  0.110 -0.040  0.035 -0.090 -0.140  0.035 -0.140  0.010  0.209  0.060 -0.264  0.035 -0.115  0.259  0.060  0.060  0.309  0.010 -0.090 -0.090 -0.264 -0.164 -0.015 -0.164  0.010  0.359 -0.140  0.060  0.060 -0.214 -0.115 -0.090  0.334 -0.164 -0.015  0.259  0.010  0.010 -0.239 
 0.582  0.234  0.034 -0.065 -0.215  0.059 -0.090  0.159  0.034 -0.240 -0.015  0.034 -0.040  0.034 -0.090 -0.140  0.034 -0.115 -0.015  0.234  0.084 -0.265  0.034 -0.115  0.284  0.084  0.059  0.333  0.059 -0.090 -0.090 -0.265 -0.165 -0.040 -0.190  0.009  0.358 -0.115  0.084  0.034 -0.215 -0.115 -0.090  0.383 -0.190 -0.015  0.259  0.009  0.009 -0.240 
 0.475  0.276  0.027 -0.073 -0.247  0.127 -0.073  0.176  0.052 -0.247 -0.023  0.002 -0.023  0.052 -0.073 -0.147  0.002 -0.147 -0.023  0.276  0.102 -0.272  0.002 -0.073  0.326  0.127  0.077  0.401  0.027 -0.073 -0.123 -0.247 -0.147 -0.073 -0.172 -0.023  0.401 -0.123  0.052  0.002 -0.197 -0.147 -0.073  0.401 -0.197 -0.048  0.251  0.002  0.002 -0.247 
 0.401  0.277  0.002 -0.072 -0.222  0.177 -0.072  0.177  0.052 -0.222 -0.022  0.002 -0.022  0.052 -0.047 -0.147 -0.047 -0.147 -0.022  0.301  0.102 -0.272  0.027 -0.072  0.326  0.152  0.052  0.426  0.002 -0.072 -0.097 -0.197 -0.122 -0.097 -0.147 -0.047  0.401 -0.097  0.077  0.002 -0.222 -0.147 -0.072  0.401 -0.197 -0.047  0.252  0.027 -0.022 -0.222 
 0.373  0.273 -0.001 -0.051 -0.250  0.173 -0.076  0.198  0.074 -0.225 -0.026 -0.001 -0.026  0.049 -0.051 -0.150 -0.051 -0.150 -0.001  0.298  0.099 -0.275  0.024 -0.051  0.323  0.198  0.074  0.423 -0.001 -0.076 -0.076 -0.200 -0.076 -0.101 -0.150 -0.026  0.423 -0.076  0.099 -0.001 -0.225 -0.150 -0.076  0.373 -0.200 -0.026  0.248  0.024 -0.026 -0.200 
 0.298  0.274 -0.000 -0.050 -0.275  0.174 -0.075  0.199  0.074 -0.225 -0.025 -0.025 -0.000  0.049 -0.050 -0.150 -0.050 -0.125 -0.000  0.298  0.074 -0.250 -0.025 -0.025  0.323  0.174  0.074  0.423 -0.000 -0.075 -0.075 -0.200 -0.000 -0.075 -0.150 -0.025  0.398 -0.050  0.099 -0.000 -0.225 -0.125 -0.075  0.373 -0.175 -0.025  0.224  0.049 -0.025 -0.200 
 0.274  0.249  0.000 -0.050 -0.299  0.174 -0.075  0.174  0.075 -0.224 -0.025  0.000  0.025  0.050 -0.050 -0.149 -0.050 -0.125  0.000  0.299  0.075 -0.249 -0.025  0.000  0.299  0.174  0.075  0.473  0.000 -0.075 -0.075 -0.224  0.050 -0.050 -0.174  0.000  0.374 -0.050  0.100 -0.025 -0.224 -0.125 -0.075  0.349 -0.174 -0.025  0.224  0.050 -0.025 -0.199 
 0.298  0.274 -0.000 -0.050 -0.299  0.174 -0.075  0.199  0.074 -0.225 -0.025  0.049  0.024  0.024 -0.075 -0.150 -0.050 -0.125 -0.000  0.298  0.074 -0.225 -0.025 -0.025  0.298  0.199  0.074  0.498 -0.000 -0.075 -0.075 -0.225  0.049 -0.050 -0.150 -0.000  0.323 -0.050  0.099 -0.025 -0.225 -0.125 -0.075  0.348 -0.175 -0.025  0.224  0.049 -0.050 -0.200 
 0.298  0.273  0.049 -0.051 -0.300  0.173 -0.076  0.198  0.099 -0.225 -0.026  0.074  0.024  0.024 -0.076 -0.150 -0.026 -0.101  0.024  0.298  0.074 -0.225 -0.026 -0.026  0.298  0.173  0.074  0.497 -0.001 -0.051 -0.076 -0.225  0.049 -0.051 -0.126 -0.001  0.323 -0.051  0.099 -0.001 -0.200 -0.101 -0.076  0.348 -0.175 -0.026  0.223  0.049 -0.051 -0.225 
 0.271  0.196 -0.003 -0.103 -0.253  0.146 -0.053  0.221  0.096 -0.153 -0.003  0.021  0.046  0.046 -0.053 -0.153 -0.028 -0.128  0.021  0.146  0.096 -0.203 -0.028 -0.028  0.320  0.096  0.071  0.420  0.046 -0.028 -0.028 -0.153 -0.003  0.021 -0.053 -0.003  0.295 -0.078 -0.053 -0.028 -0.203 -0.078 -0.053  0.320 -0.153  0.021  0.196  0.071 -0.078 -0.153 
 0.257  0.157 -0.017 -0.092 -0.166  0.133 -0.042  0.232  0.058 -0.092  0.033 -0.017  0.058  0.058 -0.017 -0.067  0.008 -0.092 -0.017  0.133 -0.042 -0.117  0.008 -0.017  0.257  0.133  0.108  0.332  0.058 -0.017  0.033 -0.117 -0.042  0.033 -0.117  0.033  0.232 -0.067 -0.092 -0.092 -0.142 -0.042 -0.067  0.332 -0.092  0.083  0.083  0.058 -0.067 -0.166 
 0.199  0.149 -0.025 -0.075 -0.150  0.124 -0.025  0.149  0.049 -0.075  0.049 -0.025  0.074  0.024 -0.025 -0.050  0.024 -0.075 -0.025  0.124 -0.075 -0.100 -0.000 -0.025  0.224  0.124  0.124  0.298  0.074 -0.000  0.024 -0.075 -0.075  0.049 -0.100 -0.000  0.199 -0.050 -0.075 -0.100 -0.125 -0.050 -0.025  0.348 -0.075  0.099  0.049  0.049 -0.050 -0.150 
 0.145  0.145 -0.004 -0.054 -0.129  0.045 -0.004  0.145  0.020 -0.054  0.070 -0.029  0.095  0.045 -0.029 -0.054 -0.004 -0.054 -0.004  0.070 -0.129 -0.104 -0.029 -0.029  0.170  0.095  0.145  0.270  0.070  0.020 -0.004 -0.054 -0.104  0.070 -0.079 -0.004  0.145 -0.029 -0.054 -0.079 -0.129 -0.054 -0.054  0.270 -0.054  0.095  0.070  0.070 -0.029 -0.129 
 0.127  0.151  0.002 -0.048 -0.123  0.002 -0.023  0.151  0.002 -0.048  0.077 -0.073  0.127  0.027 -0.023 -0.073  0.002 -0.073  0.002  0.077 -0.123 -0.098 -0.023 -0.023  0.176  0.077  0.151  0.251  0.077  0.027  0.002 -0.048 -0.098  0.052 -0.073 -0.023  0.102 -0.048 -0.048 -0.073 -0.123 -0.048 -0.048  0.226 -0.048  0.102  0.077  0.077 -0.023 -0.123 
 0.115  0.140  0.015 -0.034 -0.109 -0.009 -0.034  0.190 -0.009 -0.034  0.065 -0.059  0.115  0.040 -0.009 -0.059 -0.009 -0.084  0.015  0.040 -0.109 -0.084 -0.009 -0.034  0.165  0.065  0.090  0.165  0.065  0.015  0.015 -0.059 -0.084  0.040 -0.059 -0.034  0.065 -0.059 -0.084 -0.059 -0.109 -0.034 -0.059  0.190 -0.034  0.115  0.065  0.090 -0.009 -0.109 
 0.145  0.095  0.020 -0.029 -0.104 -0.004 -0.029  0.195 -0.029 -0.054  0.020 -0.054  0.095  0.045 -0.004 -0.054 -0.004 -0.079  0.020 -0.004 -0.104 -0.079 -0.029 -0.029  0.145  0.045  0.095  0.170  0.070  0.020  0.020 -0.054 -0.079  0.045 -0.054 -0.029  0.070 -0.054 -0.079 -0.054 -0.104 -0.029 -0.079  0.095 -0.029  0.120  0.070  0.095 -0.004 -0.104 
 0.156  0.106  0.006 -0.018 -0.093  0.006 -0.018  0.081 -0.018 -0.043  0.031 -0.043  0.056  0.056 -0.018 -0.043  0.031 -0.093  0.006 -0.018 -0.093 -0.093 -0.043 -0.068  0.156  0.006  0.081  0.081  0.031  0.031  0.006 -0.043 -0.068  0.056 -0.043 -0.018  0.031 -0.043 -0.068 -0.068 -0.093 -0.043 -0.068  0.031 -0.018  0.131  0.056  0.056  0.006 -0.093 
 0.168  0.068  0.018 -0.006 -0.081 -0.006 -0.006 -0.006 -0.006 -0.031  0.018 -0.031  0.068 -0.006 -0.006 -0.081  0.043 -0.081 -0.031 -0.006 -0.081 -0.081 -0.031 -0.081  0.118  0.018  0.093  0.093  0.043  0.043  0.018 -0.031 -0.056  0.068 -0.031 -0.006  0.043 -0.031 -0.056 -0.081 -0.081 -0.056 -0.056 -0.006 -0.006  0.143  0.018  0.068 -0.031 -0.081 
 0.130  0.030 -0.020 -0.020 -0.070  0.005  0.005 -0.045  0.005 -0.020  0.030 -0.020  0.080  0.005 -0.020 -0.070  0.030 -0.070 -0.045  0.005 -0.070 -0.070 -0.045 -0.070  0.055  0.030  0.055  0.055  0.030  0.030  0.030 -0.045 -0.045  0.055 -0.020  0.005  0.055 -0.045 -0.070 -0.070 -0.070 -0.045 -0.045 -0.020 -0.020  0.130 -0.020  0.055 -0.020 -0.070 
 0.109  0.009 -0.016 -0.016 -0.066  0.009  0.009 -0.041  0.009  0.009  0.009 -0.016  0.084 -0.016 -0.016 -0.066 -0.016 -0.066 -0.041  0.009 -0.066 -0.066 -0.041 -0.066  0.034  0.034  0.034  0.034  0.034  0.009  0.034 -0.041 -0.041  0.034 -0.041  0.009  0.059 -0.041 -0.066 -0.066 -0.066 -0.066 -0.041 -0.041 -0.016  0.109 -0.016  0.059 -0.041 -0.041 
 0.099 -0.000 -0.000 -0.000 -0.050 -0.025 -0.025 -0.050  0.024 -0.000 -0.000 -0.050  0.099 -0.000 -0.000 -0.050 -0.000 -0.050 -0.025 -0.000 -0.050 -0.050 -0.025 -0.050 -0.025 -0.025  0.024 -0.000 -0.000 -0.050  0.024 -0.025 -0.025 -0.000 -0.025 -0.000 -0.000 -0.025 -0.050 -0.050 -0.050 -0.050 -0.025 -0.025 -0.025  0.074 -0.000  0.049 -0.025 -0.025 
 0.087  0.012 -0.038  0.012 -0.038 -0.013 -0.038 -0.038  0.037  0.012 -0.013 -0.038  0.112  0.012 -0.013 -0.038 -0.013 -0.038 -0.013 -0.038 -0.038 -0.038 -0.013 -0.038 -0.013 -0.013  0.012  0.012 -0.013 -0.038  0.012 -0.013 -0.013  0.012 -0.013  0.012 -0.013 -0.013 -0.038 -0.038 -0.038 -0.038 -0.013 -0.038 -0.013  0.087  0.012  0.012 -0.013 -0.013 
 0.102  0.052 -0.022  0.002 -0.022  0.002 -0.022  0.002  0.027  0.027 -0.022 -0.022  0.027  0.027 -0.022 -0.022  0.002 -0.022  0.002 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022 -0.022  0.027  0.002 -0.022 -0.022 -0.022  0.002  0.002  0.002  0.002 -0.022  0.002 -0.022 -0.022 -0.022 -0.022 -0.022  0.002 -0.022  0.002  0.077 -0.022  0.002  0.002  0.002 
 0.104  0.054 -0.020 -0.020 -0.020  0.004 -0.020  0.004  0.029  0.029 -0.020 -0.020  0.029  0.004 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020 -0.020 -0.020  0.004 -0.020  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.004 
 0.104  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.004 
 0.104  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.004 
 0.104  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.004 
 0.104  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.004 
 0.104  0.054  0.004 -0.020 -0.020  0.004  0.004  0.004  0.029  0.029  0.004 -0.020  0.029 -0.020  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020 -0.020  0.029  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.004  0.004 -0.020  0.004 -0.020  0.004  0.079 -0.020 -0.020 -0.020  0.004 
 0.122  0.097 -0.003 -0.028 -0.003 -0.003 -0.003 -0.003  0.022  0.022 -0.003 -0.028  0.022 -0.028  0.022 -0.028 -0.028 -0.003 -0.003 -0.028 -0.028 -0.028 -0.028 -0.028 -0.003 -0.003  0.022 -0.003 -0.028 -0.003 -0.028 -0.003 -0.003 -0.003 -0.003 -0.003  0.022 -0.028  0.047 -0.003  0.022 -0.028 -0.003 -0.028 -0.003  0.072 -0.028 -0.028 -0.028 -0.003 
 0.343  0.119 -0.005 -0.030 -0.005 -0.005 -0.005 -0.005  0.119 -0.005  0.044 -0.055  0.044 -0.055  0.019 -0.055 -0.055 -0.030 -0.005 -0.030 -0.055 -0.030 -0.055 -0.055  0.019 -0.030  0.019 -0.030 -0.030 -0.030 -0.030 -0.005 -0.005  0.044 -0.005 -0.030  0.069 -0.055  0.019 -0.005 -0.005 -0.030  0.044 -0.055 -0.005  0.119 -0.055 -0.030 -0.055 -0.030 
 0.609  0.136 -0.039 -0.039  0.036 -0.039 -0.014 -0.014  0.111 -0.014  0.061 -0.064  0.061  0.011  0.036 -0.089 -0.089 -0.039 -0.014 -0.064 -0.064 -0.064 -0.064 -0.064 -0.014 -0.039  0.061 -0.014 -0.014 -0.014 -0.014 -0.014 -0.039  0.036 -0.039  0.011  0.086 -0.089  0.036  0.036 -0.039 -0.064  0.011 -0.089 -0.014  0.086 -0.064 -0.014 -0.039 -0.039 
 0.850  0.177  0.003 -0.097  0.028 -0.097  0.028  0.003  0.103 -0.072  0.028  0.003  0.003  0.028  0.053 -0.097  0.028  0.028 -0.047 -0.072 -0.097 -0.097 -0.122 -0.022  0.028  0.028  0.103  0.028  0.053 -0.072 -0.022 -0.072 -0.097  0.028 -0.072  0.103  0.252 -0.122  0.028  0.028 -0.072 -0.122 -0.047 -0.146 -0.022  0.078 -0.097  0.003  0.003 -0.097 
 0.841  0.168 -0.006 -0.106 -0.006 -0.081  0.019 -0.031  0.069 -0.106  0.044 -0.006 -0.031  0.019  0.044 -0.106  0.019  0.019 -0.056 -0.081 -0.131 -0.081 -0.155 -0.056  0.044  0.019  0.143  0.044  0.119 -0.056 -0.031 -0.056 -0.081  0.019 -0.081  0.143  0.318 -0.106  0.069 -0.006 -0.106 -0.081 -0.081 -0.180 -0.031  0.094 -0.106 -0.031 -0.006 -0.106 
 0.709  0.086 -0.014 -0.139 -0.039 -0.064  0.036  0.086  0.086 -0.139  0.086  0.011 -0.014  0.086  0.111 -0.064  0.011  0.036 -0.089 -0.014 -0.139 -0.089 -0.089 -0.089  0.061  0.036  0.185  0.036  0.111 -0.014 -0.089 -0.064 -0.114  0.036 -0.139  0.111  0.310 -0.114  0.036 -0.014 -0.213 -0.064 -0.014 -0.139 -0.039  0.061 -0.114 -0.014 -0.014 -0.114 
 0.643  0.045 -0.030 -0.130 -0.080 -0.080  0.045  0.120  0.070 -0.179  0.070 -0.030 -0.005  0.120  0.120 -0.080 -0.005  0.095 -0.080  0.070 -0.154 -0.130 -0.030 -0.130  0.045  0.045  0.144  0.020  0.120  0.020 -0.055 -0.030 -0.030 -0.005 -0.154  0.144  0.344 -0.105  0.045  0.070 -0.229 -0.080 -0.055 -0.105 -0.005  0.095 -0.105 -0.005 -0.005 -0.130 
 0.586  0.038  0.038 -0.136 -0.136 -0.036 -0.011  0.188  0.113 -0.211  0.038 -0.061  0.013  0.188  0.063 -0.136 -0.036  0.113 -0.061  0.138 -0.161 -0.186 -0.036 -0.111  0.088  0.063  0.163  0.088  0.088  0.088 -0.061 -0.036 -0.061 -0.036 -0.186  0.138  0.337 -0.111  0.063  0.063 -0.261 -0.086 -0.061 -0.011  0.013  0.063 -0.036  0.063  0.038 -0.161 
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 0.309  0.110 -0.039 -0.164 -0.164  0.135 -0.064  0.185  0.085 -0.189  0.010 -0.114  0.060  0.135  0.010 -0.114 -0.064 -0.064 -0.089  0.210 -0.114 -0.139 -0.014 -0.139  0.160  0.035  0.160  0.284  0.060  0.035  0.010 -0.164 -0.039 -0.064 -0.189  0.135  0.334 -0.114  0.010 -0.014 -0.288 -0.089  0.060  0.185 -0.039  0.035  0.035  0.085  0.085 -0.189 
 0.234  0.110 -0.040 -0.164 -0.164  0.135 -0.015  0.184  0.085 -0.189  0.010 -0.115  0.060  0.110  0.010 -0.115 -0.040 -0.115 -0.065  0.184 -0.140 -0.164 -0.065 -0.140  0.184  0.035  0.135  0.284  0.060  0.010  0.035 -0.164 -0.015 -0.065 -0.189  0.110  0.334 -0.115  0.010 -0.015 -0.264 -0.065  0.035  0.209 -0.090  0.035  0.060  0.085  0.085 -0.164 
 0.229  0.104 -0.045 -0.145 -0.170  0.154 -0.045  0.179  0.079 -0.195  0.004 -0.120  0.054  0.104 -0.020 -0.120  0.004 -0.145 -0.070  0.204 -0.120 -0.145 -0.070 -0.095  0.204  0.004  0.129  0.303  0.054  0.004  0.054 -0.170 -0.020 -0.095 -0.170  0.104  0.328 -0.070  0.029 -0.020 -0.270 -0.045  0.029  0.204 -0.095  0.029  0.054  0.079  0.079 -0.145 
 0.253  0.129 -0.071 -0.145 -0.195  0.129 -0.021  0.178  0.079 -0.195  0.004 -0.121  0.054  0.104 -0.046 -0.145  0.004 -0.195 -0.046  0.228 -0.071 -0.145 -0.071 -0.096  0.228  0.029  0.129  0.278  0.004  0.004  0.054 -0.170  0.004 -0.096 -0.170  0.054  0.328 -0.046  0.004 -0.046 -0.195 -0.046  0.029  0.228 -0.096  0.029  0.054  0.054  0.079 -0.121 
 0.252  0.177 -0.072 -0.122 -0.221  0.078  0.003  0.177  0.078 -0.196  0.003 -0.122  0.053  0.103 -0.047 -0.146  0.003 -0.196 -0.047  0.227 -0.047 -0.146 -0.072 -0.097  0.252  0.028  0.128  0.327  0.003 -0.022  0.078 -0.171  0.003 -0.097 -0.171  0.053  0.302 -0.047  0.003 -0.022 -0.196 -0.047  0.028  0.227 -0.097  0.028  0.053  0.053  0.078 -0.097 
 0.254  0.179 -0.070 -0.120 -0.220  0.104 -0.020  0.179  0.079 -0.195  0.004 -0.145  0.029  0.104 -0.045 -0.145  0.004 -0.195 -0.045  0.229 -0.045 -0.145 -0.070 -0.095  0.254  0.029  0.129  0.353  0.004 -0.045  0.079 -0.170  0.004 -0.095 -0.170  0.054  0.303 -0.045  0.004 -0.020 -0.195 -0.070  0.004  0.229 -0.095  0.029  0.054  0.054  0.079 -0.120 
 0.254  0.204 -0.045 -0.120 -0.219  0.105 -0.020  0.179  0.080 -0.194  0.005 -0.144  0.030  0.105 -0.070 -0.144 -0.020 -0.169 -0.045  0.254 -0.045 -0.144 -0.070 -0.095  0.254  0.030  0.130  0.354  0.005 -0.095  0.080 -0.194  0.005 -0.095 -0.169  0.030  0.304 -0.045  0.005 -0.020 -0.194 -0.070  0.005  0.229 -0.095  0.030  0.055  0.055  0.080 -0.120 
 0.253  0.178 -0.021 -0.121 -0.221  0.103 -0.021  0.178  0.078 -0.196  0.003 -0.146  0.028  0.103 -0.071 -0.146 -0.021 -0.146 -0.046  0.278 -0.046 -0.121 -0.071 -0.096  0.253  0.028  0.128  0.402  0.003 -0.096  0.078 -0.196  0.003 -0.096 -0.171  0.053  0.302 -0.046  0.028 -0.021 -0.196 -0.071  0.003  0.228 -0.121  0.028  0.053  0.053  0.078 -0.121 
 0.252  0.177 -0.022 -0.122 -0.196  0.103  0.028  0.177  0.078 -0.196  0.003 -0.146  0.028  0.103 -0.072 -0.146 -0.047 -0.146 -0.047  0.277 -0.047 -0.122 -0.072 -0.097  0.252  0.028  0.128  0.402  0.003 -0.097  0.053 -0.196  0.003 -0.072 -0.171  0.053  0.277 -0.072  0.028 -0.022 -0.196 -0.072 -0.022  0.227 -0.122  0.028  0.053  0.053  0.028 -0.097 
 0.273  0.198 -0.001 -0.126 -0.150  0.049  0.024  0.124  0.074 -0.175  0.049 -0.126  0.099  0.074 -0.026 -0.101 -0.051 -0.101 -0.101  0.223 -0.126 -0.076 -0.076 -0.101  0.198  0.074  0.124  0.273  0.049 -0.026  0.049 -0.150 -0.051 -0.026 -0.126 -0.001  0.223 -0.026 -0.001 -0.101 -0.150 -0.051 -0.001  0.273 -0.101  0.024  0.049  0.049  0.074 -0.150 
 0.186  0.136 -0.038 -0.113 -0.113  0.011 -0.038  0.136  0.111 -0.088  0.061 -0.038  0.086  0.011 -0.038 -0.063 -0.013 -0.088 -0.038  0.111 -0.163 -0.113 -0.038 -0.038  0.136  0.086  0.136  0.236  0.111  0.011 -0.013 -0.088 -0.063  0.036 -0.088  0.036  0.261 -0.063 -0.088 -0.113 -0.163 -0.063 -0.063  0.261 -0.088  0.036  0.036  0.036 -0.013 -0.163 
 0.149  0.125  0.000 -0.100 -0.149 -0.025 -0.025  0.149  0.125 -0.075  0.050 -0.050  0.100  0.000 -0.050 -0.050  0.000 -0.075 -0.025  0.075 -0.149 -0.100 -0.025 -0.050  0.125  0.075  0.125  0.224  0.100  0.025  0.000 -0.075 -0.075  0.000 -0.100  0.050  0.249 -0.050 -0.100 -0.100 -0.149 -0.050 -0.050  0.249 -0.075  0.050  0.050  0.075 -0.025 -0.149 
 0.119  0.094  0.019 -0.080 -0.130 -0.030 -0.030  0.194  0.069 -0.055  0.069 -0.030  0.069  0.019 -0.030 -0.055 -0.005 -0.055 -0.030  0.069 -0.130 -0.105  0.019 -0.030  0.144  0.044  0.119  0.244  0.044  0.019 -0.005 -0.080 -0.080  0.019 -0.080  0.019  0.219 -0.055 -0.080 -0.080 -0.130 -0.030 -0.080  0.219 -0.055  0.044  0.069  0.094 -0.030 -0.130 
 0.125  0.125  0.025 -0.075 -0.125 -0.025 -0.025  0.249 -0.025 -0.050  0.075 -0.025  0.075  0.025 -0.025 -0.050  0.000 -0.050 -0.025  0.075 -0.125 -0.100  0.025 -0.025  0.149  0.050  0.125  0.224  0.050  0.025  0.000 -0.075 -0.100  0.025 -0.075  0.025  0.149 -0.050 -0.075 -0.075 -0.125 -0.025 -0.075  0.224 -0.050  0.025  0.050  0.100  0.000 -0.125 
 0.137  0.137  0.012 -0.062 -0.112 -0.012 -0.037  0.237 -0.087 -0.037  0.062 -0.037  0.087  0.037 -0.012 -0.037  0.012 -0.062 -0.012  0.037 -0.112 -0.087  0.012 -0.037  0.137  0.037  0.112  0.212  0.062  0.037  0.012 -0.062 -0.087  0.037 -0.062 -0.012  0.112 -0.037 -0.087 -0.062 -0.112 -0.037 -0.062  0.187 -0.037  0.037  0.062  0.087  0.012 -0.112 
 0.143  0.118  0.018 -0.056 -0.106 -0.031 -0.031  0.243 -0.081 -0.056  0.018 -0.031  0.093  0.043 -0.006 -0.031 -0.006 -0.056 -0.006 -0.006 -0.106 -0.081  0.018 -0.031  0.093  0.043  0.143  0.143  0.043  0.043  0.018 -0.056 -0.081  0.043 -0.056 -0.006  0.093 -0.031 -0.081 -0.056 -0.106 -0.031 -0.081  0.118 -0.031  0.043  0.068  0.093  0.018 -0.106 
 0.128  0.128  0.003 -0.022 -0.097 -0.022 -0.022  0.202 -0.072 -0.047  0.028 -0.047  0.078  0.028 -0.047 -0.047  0.003 -0.097  0.003 -0.022 -0.097 -0.097  0.028 -0.022  0.053  0.028  0.128  0.103  0.053  0.028  0.003 -0.047 -0.072  0.028 -0.047 -0.022  0.053 -0.047 -0.072 -0.047 -0.097  0.003 -0.072  0.103 -0.022  0.053  0.028  0.078  0.028 -0.097 
 0.136  0.061 -0.038 -0.013 -0.088 -0.013 -0.038  0.136 -0.063 -0.038  0.036 -0.063  0.086  0.011 -0.038 -0.038 -0.013 -0.088 -0.013 -0.013 -0.088 -0.088 -0.013 -0.013  0.061  0.036  0.086  0.086  0.061  0.036  0.011 -0.038 -0.088  0.036 -0.038 -0.013  0.061 -0.038 -0.088 -0.063 -0.088 -0.013 -0.063  0.061 -0.013  0.036 -0.038  0.036  0.036 -0.088 
 0.101  0.051 -0.049 -0.024 -0.049 -0.024 -0.049  0.076 -0.049 -0.024  0.001 -0.074  0.076  0.001 -0.049 -0.049  0.001 -0.074 -0.024 -0.024 -0.074 -0.074  0.001  0.001 -0.024  0.026  0.026  0.101  0.026  0.051  0.001  0.001 -0.074  0.051 -0.049  0.001  0.076 -0.024 -0.074 -0.074 -0.074 -0.024 -0.074  0.051  0.001  0.026 -0.024  0.001  0.001 -0.049 
 0.082  0.032 -0.043 -0.018 -0.043 -0.018 -0.043  0.032 -0.043 -0.018  0.007 -0.068  0.082  0.007 -0.043 -0.043  0.007 -0.068 -0.043 -0.018 -0.068 -0.068  0.007  0.007 -0.018  0.032  0.032  0.057  0.032  0.032  0.007  0.007 -0.068  0.057 -0.043  0.007  0.057 -0.043 -0.068 -0.068 -0.068 -0.043 -0.068  0.032  0.007  0.032 -0.018  0.007  0.007 -0.043 
 0.068  0.018 -0.056 -0.006 -0.031 -0.031 -0.031  0.018 -0.031 -0.031  0.018 -0.056  0.068 -0.031 -0.031 -0.031  0.018 -0.056 -0.056 -0.006 -0.056 -0.056  0.018 -0.006 -0.031  0.018 -0.006  0.043  0.018  0.018 -0.006  0.018 -0.056  0.068 -0.031 -0.031  0.068 -0.031 -0.056 -0.056 -0.056 -0.031 -0.056  0.043 -0.006  0.043 -0.006 -0.006 -0.006 -0.031 
 0.033  0.033 -0.042  0.008 -0.017 -0.017 -0.042  0.008 -0.042 -0.017  0.008 -0.042  0.033 -0.017 -0.017 -0.017  0.008 -0.042 -0.042  0.008 -0.042 -0.042 -0.017 -0.042 -0.017  0.008  0.008  0.033  0.033  0.008  0.008  0.008 -0.042  0.033 -0.017 -0.042  0.008 -0.017 -0.042 -0.042 -0.042 -0.017 -0.042  0.008 -0.042  0.058 -0.017  0.008  0.008 -0.017 
 0.054  0.029 -0.021  0.004 -0.021 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.029  0.004 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021 -0.021  0.004  0.004  0.029  0.029 -0.021  0.004  0.004 -0.021 -0.021  0.004 -0.021  0.004 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021  0.029 -0.021  0.054  0.004  0.004  0.004 -0.021 
 0.015  0.015 -0.010  0.015 -0.010 -0.010 -0.010  0.015 -0.010 -0.010 -0.010 -0.010  0.015  0.015 -0.010 -0.010  0.015 -0.010 -0.010  0.015 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010  0.015 -0.010 -0.010  0.015 -0.010 -0.010  0.015 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 -0.010  0.015 -0.010  0.015 -0.010  0.015  0.015 -0.010 
 0.024 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001  0.024 -0.001 -0.001 -0.001 -0.001 
 0.024 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000  0.024 -0.000 -0.000 -0.000 -0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
 0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000  0.000 
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 1.001 -0.020  0.029  0.004  0.029  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.079 -0.020  0.054  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 
 1.001 -0.020  0.029  0.004  0.029  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.079 -0.020  0.054  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 
 1.001 -0.020  0.029  0.004  0.029  0.004 -0.020  0.004  0.004 -0.020  0.004  0.029 -0.020 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.029  0.004  0.004  0.029  0.004 -0.020  0.079 -0.020  0.054  0.029 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.029  0.004  0.004  0.079  0.004 -0.020 -0.020  0.029 -0.020 -0.020  0.004  0.004 -0.020 -0.020 
 1.000 -0.021  0.054  0.004  0.029  0.004 -0.021  0.004  0.004 -0.021  0.004  0.029 -0.021 -0.021 -0.021 -0.021  0.004 -0.021 -0.021  0.029  0.004  0.004  0.029  0.004 -0.021  0.079 -0.021  0.054  0.029 -0.021  0.004  0.004 -0.021 -0.021 -0.021 -0.021  0.029  0.004  0.004  0.104  0.004 -0.021 -0.021  0.029 -0.021 -0.021  0.004  0.004 -0.021 -0.021 
 0.997 -0.024  0.050  0.000  0.025  0.000 -0.024  0.000  0.000 -0.024  0.000  0.025 -0.024 -0.024 -0.024 -0.024  0.000 -0.024 -0.024  0.050  0.000  0.000  0.050  0.000 -0.024  0.100 -0.024  0.100  0.025 -0.024  0.000  0.000 -0.024 -0.024 -0.024 -0.024  0.025  0.000  0.000  0.100  0.000 -0.024 -0.024  0.050 -0.024 -0.024  0.000  0.000 -0.024 -0.024 
 0.984 -0.013  0.062 -0.013  0.062 -0.013 -0.013  0.037  0.012 -0.038 -0.013  0.037  0.012 -0.038  0.012 -0.013 -0.013 -0.013 -0.013  0.037  0.037  0.037  0.062 -0.013 -0.013  0.087 -0.038  0.211  0.062 -0.038  0.012 -0.013 -0.013 -0.038 -0.038  0.012  0.037  0.012  0.012  0.112 -0.013 -0.038 -0.013  0.062 -0.038 -0.013  0.037  0.037 -0.038 -0.038 
 0.941 -0.055  0.144 -0.030  0.119 -0.055  0.044  0.069 -0.005 -0.080 -0.030 -0.005 -0.005 -0.005  0.019 -0.030 -0.055 -0.005 -0.055  0.144  0.094  0.019  0.069 -0.055  0.044  0.119 -0.030  0.568  0.169 -0.080  0.019 -0.055  0.019 -0.055 -0.080  0.019  0.094 -0.005  0.094  0.144 -0.055 -0.030 -0.005  0.169 -0.055  0.044  0.069  0.044 -0.030 -0.055 
 0.899 -0.047  0.177  0.027  0.152 -0.072  0.027  0.127  0.077 -0.122 -0.047 -0.047 -0.022  0.002  0.052 -0.022 -0.047 -0.047 -0.072  0.177  0.102 -0.022  0.127 -0.072  0.052  0.177 -0.022  0.725  0.177 -0.097  0.002 -0.022  0.002 -0.097 -0.097  0.027  0.102 -0.047  0.152  0.152 -0.097 -0.047  0.002  0.277 -0.072  0.052  0.301  0.052  0.002 -0.072 
 0.824 -0.023  0.151  0.101  0.151  0.026  0.101  0.076  0.076 -0.198 -0.073 -0.048  0.001  0.051  0.001 -0.073 -0.048 -0.073 -0.098  0.201  0.101 -0.023  0.151 -0.023  0.101  0.201  0.026  0.799  0.226 -0.148 -0.073 -0.023  0.026 -0.098 -0.173  0.026  0.226 -0.048  0.176  0.176 -0.148 -0.023 -0.048  0.400  0.001  0.051  0.450  0.001  0.001 -0.123 
 0.687 -0.036  0.213  0.139  0.114  0.089  0.139  0.114  0.114 -0.210 -0.036 -0.061  0.039 -0.011 -0.011 -0.036  0.014 -0.086 -0.036  0.188  0.139 -0.061  0.139 -0.086  0.114  0.188  0.064  0.736  0.338 -0.136 -0.086 -0.036  0.014 -0.011 -0.185  0.039  0.263 -0.036  0.188  0.188 -0.160 -0.036 -0.061  0.462 -0.011  0.039  0.437 -0.036 -0.036 -0.136 
 0.609  0.011  0.260  0.111  0.036  0.185  0.160  0.086  0.136 -0.213 -0.039 -0.064  0.086  0.086  0.036 -0.089  0.086 -0.039 -0.014  0.260  0.136 -0.089  0.111 -0.089  0.210  0.260  0.160  0.634  0.410 -0.114 -0.014 -0.064  0.036 -0.064 -0.188  0.061  0.285 -0.039  0.285  0.210 -0.163 -0.039 -0.114  0.459 -0.064  0.111  0.484 -0.039 -0.139 -0.188 
 0.598  0.125  0.299  0.125 -0.025  0.224  0.174  0.125  0.125 -0.224 -0.050 -0.025  0.075  0.050  0.000 -0.125  0.075 -0.075  0.050  0.249  0.149 -0.125  0.125 -0.100  0.249  0.224  0.174  0.623  0.349 -0.125 -0.050 -0.100  0.000 -0.075 -0.199  0.075  0.274  0.025  0.274  0.174 -0.174 -0.075 -0.125  0.448 -0.075  0.125  0.448 -0.050 -0.125 -0.199 
 0.509  0.160  0.285  0.111 -0.039  0.210  0.160  0.136  0.136 -0.213 -0.039 -0.014  0.061  0.036 -0.014 -0.114  0.111 -0.064  0.061  0.285  0.210 -0.163  0.185 -0.114  0.235  0.160  0.160  0.534  0.285 -0.139 -0.039 -0.114 -0.014 -0.064 -0.188  0.061  0.285  0.011  0.285  0.111 -0.213 -0.114 -0.139  0.459 -0.089  0.111  0.360 -0.064 -0.139 -0.213 
 0.505  0.206  0.256  0.107 -0.093  0.206  0.107  0.132  0.132 -0.217 -0.043 -0.018  0.057  0.007 -0.018 -0.093  0.107 -0.043  0.032  0.306  0.206 -0.242  0.181 -0.118  0.231  0.156  0.132  0.480  0.281 -0.142 -0.043 -0.118 -0.018 -0.043 -0.217  0.057  0.281  0.057  0.281  0.107 -0.217 -0.093 -0.142  0.455 -0.118  0.107  0.331 -0.068 -0.142 -0.217 
 0.478  0.229  0.204  0.105 -0.120  0.179  0.080  0.130  0.154 -0.219 -0.020 -0.070  0.055 -0.020 -0.020 -0.095  0.130 -0.070  0.030  0.379  0.179 -0.244  0.179 -0.070  0.304  0.154  0.130  0.453  0.254 -0.169  0.005 -0.120  0.005 -0.045 -0.219  0.030  0.229  0.055  0.254  0.080 -0.244 -0.095 -0.144  0.453 -0.120  0.055  0.279 -0.095 -0.095 -0.244 
 0.480  0.231  0.181  0.107 -0.142  0.181  0.057  0.132  0.132 -0.217 -0.043 -0.068  0.082 -0.018 -0.043 -0.093  0.132 -0.068  0.032  0.381  0.156 -0.242  0.156 -0.068  0.331  0.156  0.132  0.430  0.256 -0.167  0.007 -0.093  0.032 -0.043 -0.167  0.032  0.231  0.057  0.256  0.082 -0.242 -0.093 -0.118  0.455 -0.142  0.082  0.281 -0.093 -0.093 -0.242 
 0.456  0.282  0.108  0.108 -0.191  0.182  0.008  0.108  0.083 -0.216 -0.042 -0.067  0.083  0.008 -0.042 -0.092  0.133 -0.067  0.033  0.382  0.157 -0.241  0.133 -0.042  0.332  0.157  0.133  0.431  0.232 -0.142  0.008 -0.166  0.033 -0.042 -0.117  0.033  0.232  0.033  0.257  0.058 -0.216 -0.092 -0.117  0.382 -0.142  0.108  0.282 -0.067 -0.092 -0.266 
 0.454  0.280  0.080  0.105 -0.244  0.180  0.005  0.105  0.080 -0.219 -0.044 -0.044  0.105  0.030 -0.044 -0.119  0.130 -0.044  0.030  0.379  0.155 -0.244  0.080 -0.044  0.329  0.155  0.155  0.429  0.155 -0.119 -0.019 -0.169  0.080 -0.044 -0.119  0.055  0.230  0.030  0.230  0.055 -0.219 -0.094 -0.119  0.429 -0.144  0.105  0.255 -0.019 -0.069 -0.244 
 0.355  0.256  0.081  0.106 -0.243  0.181  0.006  0.106  0.081 -0.218 -0.043 -0.043  0.106  0.031 -0.043 -0.118  0.131 -0.043  0.031  0.355  0.156 -0.243  0.081 -0.043  0.330  0.181  0.156  0.430  0.131 -0.118 -0.043 -0.218  0.056 -0.043 -0.118  0.081  0.231  0.031  0.231  0.056 -0.218 -0.093 -0.118  0.430 -0.143  0.081  0.256  0.006 -0.068 -0.243 
 0.351  0.276  0.077  0.102 -0.247  0.176  0.002  0.102  0.077 -0.222 -0.048 -0.048  0.102  0.027 -0.048 -0.123  0.127 -0.048  0.027  0.376  0.151 -0.247  0.077 -0.048  0.326  0.226  0.151  0.426  0.102 -0.123 -0.048 -0.172  0.052 -0.048 -0.123  0.102  0.226  0.002  0.226  0.052 -0.222 -0.098 -0.123  0.426 -0.147  0.102  0.251 -0.023 -0.073 -0.247 
 0.327  0.278  0.078  0.078 -0.271  0.153  0.003  0.103  0.078 -0.221 -0.046 -0.046  0.103  0.053 -0.046 -0.121  0.103 -0.046  0.028  0.377  0.153 -0.221  0.078 -0.046  0.327  0.253  0.153  0.377  0.053 -0.121 -0.046 -0.171  0.028 -0.021 -0.121  0.103  0.203  0.003  0.228  0.053 -0.221 -0.096 -0.121  0.402 -0.146  0.078  0.253 -0.021 -0.071 -0.246 
 0.327  0.277  0.078  0.078 -0.271  0.152  0.003  0.103  0.078 -0.221 -0.047 -0.072  0.103  0.053 -0.047 -0.122  0.103 -0.022  0.028  0.377  0.152 -0.221  0.078 -0.047  0.327  0.252  0.152  0.377  0.053 -0.122 -0.047 -0.171  0.028 -0.022 -0.122  0.103  0.202  0.003  0.227  0.053 -0.221 -0.097 -0.122  0.377 -0.146  0.053  0.252  0.003 -0.072 -0.246 
 0.331  0.282  0.082  0.082 -0.242  0.107  0.007  0.107  0.082 -0.217 -0.042 -0.092  0.107  0.057 -0.042 -0.117  0.082 -0.017  0.007  0.381  0.107 -0.217  0.082 -0.042  0.331  0.282  0.182  0.381  0.032 -0.092 -0.042 -0.167  0.032 -0.042 -0.117  0.107  0.207  0.007  0.232  0.057 -0.217 -0.092 -0.117  0.306 -0.142  0.032  0.257  0.007 -0.067 -0.192 
 0.275  0.125  0.050  0.050 -0.199  0.100 -0.024  0.125  0.025 -0.149  0.000 -0.074  0.075  0.100 -0.074 -0.074  0.050 -0.049 -0.049  0.374  0.000 -0.149  0.000 -0.074  0.225  0.324  0.150  0.349  0.075 -0.074  0.000 -0.124 -0.024  0.025 -0.149  0.100  0.125  0.000  0.200 -0.024 -0.174 -0.099 -0.124  0.324 -0.099  0.025  0.250  0.050 -0.099 -0.224 
 0.203  0.128  0.028 -0.021 -0.171  0.028 -0.021  0.078  0.053 -0.096  0.028 -0.071  0.078  0.053 -0.021 -0.021  0.028 -0.021 -0.096  0.327  0.003 -0.096  0.003 -0.071  0.153  0.153  0.078  0.352  0.053 -0.046  0.003 -0.121 -0.096  0.028 -0.121  0.128  0.178 -0.046  0.103 -0.046 -0.146 -0.071 -0.046  0.278 -0.046  0.078  0.153  0.078 -0.046 -0.171 
 0.121  0.121  0.021 -0.028 -0.153  0.046 -0.053  0.096  0.046 -0.078  0.021 -0.103  0.071  0.071 -0.003 -0.103 -0.003 -0.028 -0.078  0.271 -0.028 -0.078 -0.028 -0.103  0.121  0.121  0.021  0.345  0.046 -0.028  0.021 -0.103 -0.078  0.046 -0.103  0.121  0.146 -0.053  0.046 -0.078 -0.128 -0.053 -0.053  0.246 -0.053  0.071  0.096  0.071 -0.053 -0.153 
 0.068  0.118  0.018 -0.082 -0.132  0.018 -0.032  0.018 -0.007 -0.057  0.043 -0.082  0.068  0.093 -0.007 -0.107 -0.007 -0.057 -0.057  0.217 -0.082 -0.107 -0.007 -0.107  0.093  0.142  0.018  0.292  0.068 -0.007  0.018 -0.057 -0.107  0.068 -0.082  0.093  0.118 -0.082 -0.057 -0.082 -0.107 -0.057 -0.032  0.217 -0.082  0.043  0.043  0.068 -0.032 -0.132 
 0.053  0.128  0.003 -0.072 -0.122 -0.022 -0.022 -0.047 -0.022 -0.047  0.028 -0.047  0.053  0.103 -0.047 -0.097  0.003 -0.072 -0.047  0.202 -0.072 -0.097  0.003 -0.072  0.078  0.152  0.028  0.277  0.053  0.003  0.028 -0.047 -0.097  0.053 -0.072  0.053  0.053 -0.072 -0.072 -0.072 -0.097 -0.047 -0.022  0.177 -0.072  0.028  0.053  0.028 -0.047 -0.122 
 0.040  0.090 -0.034 -0.059 -0.109 -0.034 -0.009 -0.034 -0.059 -0.034  0.040 -0.009  0.040  0.040 -0.034 -0.084 -0.009 -0.059 -0.034  0.165 -0.084 -0.084  0.015 -0.084  0.065  0.190 -0.009  0.289  0.090  0.015  0.040 -0.034 -0.084  0.040 -0.059  0.040  0.015 -0.059 -0.059 -0.059 -0.084 -0.034 -0.009  0.090 -0.034  0.015  0.065  0.015 -0.059 -0.109 
 0.046  0.096 -0.028 -0.053 -0.103 -0.028 -0.003 -0.028 -0.078 -0.028  0.046 -0.053  0.021  0.046 -0.028 -0.078 -0.003 -0.053 -0.028  0.171 -0.103 -0.078 -0.003 -0.103  0.046  0.096 -0.028  0.295  0.071  0.021  0.021 -0.028 -0.078  0.046 -0.053  0.046  0.021 -0.053 -0.078 -0.053 -0.078 -0.028 -0.003  0.096 -0.028  0.021  0.071  0.021 -0.053 -0.103 
 0.055  0.055 -0.044 -0.044 -0.094 -0.019  0.005 -0.044 -0.094 -0.044  0.030 -0.044  0.030  0.030 -0.044 -0.069  0.005 -0.044 -0.019  0.155 -0.094 -0.069  0.005 -0.094  0.055  0.055 -0.019  0.280  0.055  0.030  0.005 -0.044 -0.069  0.030 -0.044  0.030  0.030 -0.044 -0.069 -0.094 -0.094 -0.044 -0.044  0.080 -0.044  0.005  0.080  0.030 -0.019 -0.094 
 0.064  0.039 -0.035 -0.035 -0.085 -0.010 -0.010 -0.035 -0.085 -0.035  0.014 -0.035  0.039  0.039 -0.035 -0.060  0.014 -0.060 -0.010  0.064 -0.085 -0.060  0.014 -0.085  0.039 -0.010 -0.010  0.264  0.064  0.039  0.014 -0.035 -0.060  0.014 -0.035 -0.010  0.014 -0.035 -0.085 -0.085 -0.085 -0.035 -0.035  0.039 -0.035  0.014  0.089  0.039 -0.010 -0.085 
 0.120  0.045 -0.029 -0.029 -0.079 -0.004 -0.004 -0.054 -0.079 -0.029  0.020 -0.029  0.045  0.020 -0.029 -0.054 -0.004 -0.079 -0.004  0.045 -0.079 -0.079  0.045 -0.079  0.045 -0.029 -0.029  0.270  0.020  0.020  0.020 -0.054 -0.054  0.020 -0.054 -0.004  0.045 -0.054 -0.079 -0.079 -0.079 -0.029 -0.054  0.045 -0.029  0.020  0.070  0.045 -0.004 -0.079 
 0.127  0.027 -0.023 -0.023 -0.073  0.002  0.002 -0.048 -0.073 -0.023  0.002 -0.048  0.052  0.027 -0.023 -0.048  0.002 -0.073  0.002  0.052 -0.073 -0.073  0.052 -0.073  0.027 -0.048 -0.023  0.251  0.027 -0.048  0.027 -0.048 -0.048  0.027 -0.048  0.002  0.052 -0.048 -0.073 -0.073 -0.073 -0.023 -0.073  0.027 -0.023  0.027  0.077  0.052  0.002 -0.073 
 0.112  0.037 -0.012 -0.012 -0.062  0.012 -0.012 -0.037 -0.062 -0.012  0.012 -0.037  0.062  0.037 -0.012 -0.037  0.012 -0.062  0.012  0.012 -0.062 -0.062  0.037 -0.062  0.012 -0.037 -0.012  0.212  0.012 -0.062  0.037 -0.037 -0.037 -0.012 -0.037 -0.012  0.037 -0.062 -0.062 -0.062 -0.062 -0.012 -0.062  0.012 -0.037  0.037  0.087  0.037  0.012 -0.062 
 0.100  0.025  0.000  0.000 -0.049  0.025  0.000 -0.024 -0.049 -0.024 -0.024 -0.024  0.025  0.025  0.000 -0.024  0.025 -0.049 -0.049 -0.049 -0.049 -0.049  0.050 -0.049  0.000 -0.024  0.000  0.100 -0.024 -0.049  0.025 -0.024 -0.024 -0.024 -0.024  0.000  0.050 -0.049 -0.049 -0.049 -0.049  0.000 -0.049 -0.049 -0.049  0.025  0.100  0.025  0.025 -0.049 
 0.067 -0.008  0.017 -0.008 -0.033  0.042 -0.008 -0.008 -0.033 -0.008 -0.008 -0.008 -0.008  0.017  0.017 -0.033  0.017 -0.008 -0.033 -0.033 -0.033 -0.008  0.017 -0.033 -0.008 -0.033 -0.008 -0.008 -0.033 -0.033  0.042 -0.008 -0.008 -0.008 -0.008 -0.008  0.042 -0.033 -0.033 -0.033 -0.033 -0.033 -0.033 -0.033 -0.033  0.017  0.067  0.042  0.017 -0.033 
 0.076  0.001  0.026 -0.024 -0.024  0.026  0.001  0.001 -0.024  0.001  0.001  0.001  0.001  0.001  0.001 -0.024  0.001  0.001 -0.024 -0.024 -0.024  0.001  0.026 -0.024 -0.024 -0.024 -0.024 -0.024 -0.024 -0.024  0.026  0.001  0.001  0.001  0.001  0.001  0.026 -0.024 -0.024 -0.024 -0.024 -0.024 -0.024 -0.024 -0.024  0.026  0.051  0.026  0.001 -0.024 
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 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.001 -0.020  0.079  0.004  0.004 -0.020 -0.020  0.004  0.054  0.029  0.029  0.004  0.054 -0.020  0.029  0.029 -0.020  0.004 -0.020 -0.020 -0.020  0.054 -0.020 -0.020 -0.020 -0.020 -0.020  0.004  0.054  0.079  0.029 -0.020  0.004 -0.020  0.029  0.004  0.004 -0.020 -0.020  0.004  0.029 -0.020  0.004  0.029 -0.020 -0.020 -0.020  0.004 -0.020  0.004 
 1.000 -0.021  0.078  0.003  0.003 -0.021 -0.021  0.003  0.053  0.028  0.053  0.003  0.078 -0.021  0.028  0.028 -0.021  0.003 -0.021 -0.021 -0.021  0.053 -0.021 -0.021 -0.021 -0.021 -0.021  0.003  0.053  0.078  0.028 -0.021  0.003 -0.021  0.028  0.003  0.003 -0.021 -0.021  0.003  0.028 -0.021  0.028  0.028 -0.021 -0.021 -0.021  0.003 -0.021  0.003 
 0.999 -0.022  0.077  0.002  0.002 -0.022 -0.022  0.002  0.052  0.027  0.052  0.002  0.077 -0.022  0.027  0.027 -0.022  0.002 -0.022 -0.022 -0.022  0.052 -0.022  0.002 -0.022 -0.022 -0.022  0.002  0.052  0.077  0.027 -0.022  0.002 -0.022  0.027  0.027  0.002 -0.022 -0.022  0.002  0.027 -0.022  0.027  0.027 -0.022 -0.022 -0.022  0.002 -0.022  0.002 
 0.995 -0.026  0.073 -0.001 -0.001 -0.026 -0.026 -0.001  0.048  0.023  0.048  0.023  0.123 -0.026  0.023  0.023 -0.026 -0.001 -0.026 -0.026 -0.026  0.048 -0.026 -0.001 -0.026 -0.001 -0.026 -0.001  0.073  0.073  0.023 -0.026 -0.001 -0.026  0.048  0.073 -0.001 -0.026 -0.026 -0.001  0.048 -0.026  0.048  0.023 -0.001 -0.026 -0.026 -0.001 -0.026  0.023 
 0.985 -0.037  0.088 -0.012 -0.012 -0.037 -0.012 -0.012  0.038  0.013  0.038  0.013  0.113 -0.037  0.013  0.013 -0.037 -0.012 -0.037 -0.012 -0.037  0.063 -0.012  0.013 -0.037  0.013 -0.037 -0.012  0.088  0.063  0.038 -0.037 -0.012 -0.037  0.038  0.063 -0.012 -0.037 -0.037  0.038  0.063 -0.012  0.038  0.013  0.013 -0.012 -0.037 -0.012  0.013  0.013 
 0.965 -0.057  0.093 -0.032 -0.032 -0.057 -0.032 -0.032  0.018  0.018  0.043 -0.007  0.093 -0.057 -0.007 -0.007 -0.032  0.043 -0.032 -0.032 -0.057  0.093 -0.032 -0.007 -0.057 -0.007 -0.057 -0.032  0.142  0.043  0.043 -0.057 -0.032 -0.057  0.043  0.068 -0.032 -0.057 -0.057  0.018  0.043 -0.007  0.043 -0.007  0.043 -0.007 -0.057 -0.032  0.018 -0.007 
 0.926 -0.095  0.104  0.004 -0.070 -0.045 -0.020 -0.070  0.004  0.079  0.104 -0.020  0.104 -0.020  0.004 -0.045 -0.045  0.054 -0.020 -0.020 -0.095  0.129  0.004  0.029 -0.070  0.004 -0.070 -0.070  0.129  0.029  0.029 -0.045 -0.045 -0.070  0.029  0.079 -0.070 -0.070 -0.095 -0.020  0.029  0.004  0.054  0.004  0.129  0.004 -0.095 -0.045  0.029 -0.045 
 0.892 -0.129  0.145 -0.004 -0.004 -0.054  0.095 -0.104 -0.029  0.070  0.095 -0.029  0.095 -0.029  0.045 -0.079 -0.079  0.095 -0.054 -0.029 -0.079  0.095  0.070  0.095 -0.104 -0.004 -0.104 -0.104  0.145 -0.004  0.020 -0.079 -0.054 -0.079  0.020  0.045 -0.054  0.020 -0.129 -0.029  0.045 -0.004  0.070  0.070  0.120 -0.029 -0.104 -0.029 -0.004 -0.079 
 0.839 -0.157  0.191  0.017  0.017 -0.083  0.166 -0.108 -0.033  0.067  0.042 -0.083  0.117 -0.058 -0.008 -0.058 -0.108  0.142 -0.108 -0.033 -0.008  0.067  0.092  0.092 -0.133 -0.058 -0.108 -0.058  0.166 -0.058  0.042 -0.133 -0.108 -0.083  0.042 -0.008 -0.083 -0.033 -0.133 -0.008  0.067 -0.008  0.017  0.042  0.216 -0.033 -0.108 -0.058  0.042 -0.133 
 0.816 -0.155  0.193  0.019 -0.006 -0.106  0.193 -0.131 -0.056  0.044  0.019 -0.081  0.119 -0.056 -0.006 -0.056 -0.131  0.143 -0.081 -0.031 -0.006  0.044  0.119  0.094 -0.131 -0.006 -0.131 -0.081  0.168 -0.081  0.044 -0.155 -0.131 -0.106  0.044 -0.031 -0.106 -0.031 -0.106 -0.006  0.094 -0.031 -0.006  0.069  0.268 -0.031 -0.131 -0.056  0.019 -0.155 
 0.760 -0.187  0.187  0.012 -0.012 -0.087  0.237 -0.162 -0.087  0.012 -0.037 -0.087  0.187 -0.062 -0.037 -0.087 -0.137  0.112 -0.087  0.037 -0.037  0.037  0.162  0.112 -0.162  0.012 -0.112 -0.112  0.162 -0.162  0.037 -0.187 -0.137 -0.137  0.037  0.037 -0.112 -0.012 -0.112  0.012  0.062 -0.037 -0.062  0.037  0.336  0.012 -0.112 -0.062  0.037 -0.162 
 0.676 -0.146  0.153  0.053 -0.021 -0.071  0.178 -0.171 -0.121 -0.046 -0.046 -0.096  0.178 -0.071 -0.071 -0.121 -0.146  0.103 -0.121  0.028 -0.071  0.028  0.178  0.078 -0.171  0.003 -0.046 -0.121  0.153 -0.196  0.028 -0.196 -0.146 -0.171  0.003  0.053 -0.096 -0.021 -0.096  0.028  0.028 -0.046 -0.046  0.053  0.402  0.003 -0.121 -0.071  0.028 -0.171 
 0.627 -0.170  0.129  0.079 -0.021 -0.071  0.153 -0.195 -0.121 -0.046 -0.046 -0.121  0.253 -0.071 -0.071 -0.145 -0.145  0.079 -0.145  0.054 -0.046  0.004  0.203  0.178 -0.170  0.004 -0.046 -0.096  0.129 -0.245 -0.021 -0.220 -0.170 -0.195 -0.021  0.054 -0.096  0.029 -0.096  0.004 -0.046 -0.021 -0.046  0.029  0.452 -0.021 -0.121 -0.096  0.054 -0.121 
 0.517 -0.155  0.069  0.119 -0.031 -0.081  0.143 -0.230 -0.106 -0.056 -0.056 -0.131  0.243 -0.031 -0.081 -0.155 -0.155  0.069 -0.180  0.044 -0.031 -0.031  0.193  0.193 -0.180 -0.006 -0.031 -0.106  0.119 -0.255 -0.006 -0.230 -0.180 -0.180 -0.056  0.044 -0.081  0.019 -0.106 -0.006 -0.081 -0.031 -0.056 -0.006  0.418 -0.031 -0.106 -0.106  0.044 -0.131 
 0.464 -0.158  0.016  0.141 -0.034 -0.109  0.091 -0.233 -0.134 -0.059 -0.084 -0.134  0.240 -0.034 -0.084 -0.158 -0.158  0.066 -0.158  0.041  0.016 -0.059  0.215  0.165 -0.183 -0.009 -0.034 -0.109  0.091 -0.258  0.016 -0.233 -0.183 -0.183 -0.034  0.016 -0.084 -0.009 -0.084 -0.009 -0.109 -0.084 -0.059  0.016  0.415 -0.059 -0.134 -0.134  0.041 -0.134 
 0.310 -0.163  0.011  0.136  0.011 -0.113  0.086 -0.238 -0.163 -0.063 -0.088 -0.138  0.186 -0.013 -0.113 -0.188 -0.163  0.061 -0.113  0.036  0.036 -0.063  0.236  0.161 -0.188 -0.013 -0.038 -0.113  0.111 -0.263  0.061 -0.238 -0.188 -0.188 -0.038  0.061 -0.063 -0.013 -0.088 -0.013 -0.113 -0.088 -0.063  0.011  0.435 -0.063 -0.138 -0.138  0.036 -0.113 
 0.279 -0.169  0.005  0.154  0.005 -0.120  0.105 -0.244 -0.194 -0.070 -0.070 -0.144  0.154 -0.020 -0.095 -0.169 -0.169  0.055 -0.095  0.030  0.030 -0.070  0.229  0.130 -0.169 -0.020 -0.045 -0.120  0.130 -0.244  0.055 -0.244 -0.194 -0.219 -0.070  0.105 -0.045 -0.020 -0.095 -0.045 -0.120 -0.095 -0.045  0.055  0.453 -0.095 -0.144 -0.095  0.055 -0.120 
 0.278 -0.171 -0.021  0.103  0.003 -0.121  0.078 -0.246 -0.221 -0.071 -0.096 -0.146  0.128 -0.021 -0.096 -0.171 -0.171  0.053 -0.071  0.028  0.028 -0.071  0.228  0.103 -0.171  0.003 -0.096 -0.121  0.103 -0.246  0.053 -0.271 -0.196 -0.246 -0.071  0.103 -0.021 -0.046 -0.096 -0.046 -0.121 -0.146 -0.121  0.053  0.427 -0.096 -0.146 -0.096  0.078 -0.146 
 0.297 -0.151 -0.027  0.098 -0.052 -0.176  0.098 -0.251 -0.251 -0.127 -0.102 -0.151  0.098 -0.002 -0.102 -0.151 -0.176  0.023 -0.077  0.023  0.048 -0.077  0.222  0.073 -0.176 -0.027 -0.127 -0.176  0.048 -0.251  0.048 -0.251 -0.176 -0.251 -0.102  0.147 -0.027 -0.052 -0.077 -0.052 -0.127 -0.151 -0.151  0.073  0.422 -0.102 -0.176 -0.102  0.073 -0.151 
 0.289 -0.159 -0.035  0.090 -0.060 -0.209  0.090 -0.259 -0.259 -0.135 -0.110 -0.135  0.115 -0.010 -0.110 -0.135 -0.184  0.015 -0.060  0.015  0.090 -0.085  0.214  0.065 -0.184 -0.035 -0.135 -0.184  0.040 -0.259  0.040 -0.259 -0.184 -0.234 -0.110  0.189 -0.035 -0.060 -0.085 -0.060 -0.135 -0.159 -0.135  0.065  0.414 -0.110 -0.159 -0.110  0.065 -0.135 
 0.235 -0.139 -0.039  0.060 -0.089 -0.214  0.060 -0.264 -0.239 -0.139 -0.114 -0.114  0.110 -0.014 -0.139 -0.139 -0.164  0.010 -0.064 -0.014  0.085 -0.114  0.185  0.060 -0.189  0.010 -0.164 -0.164  0.035 -0.264  0.010 -0.264 -0.189 -0.239 -0.139  0.185 -0.064 -0.064 -0.089 -0.089 -0.164 -0.189 -0.139  0.060  0.359 -0.114 -0.164 -0.114  0.035 -0.139 
 0.136 -0.089  0.011  0.011 -0.114 -0.163  0.086 -0.188 -0.163 -0.139 -0.139 -0.114  0.111  0.011 -0.139 -0.139 -0.114  0.011 -0.139  0.011  0.036 -0.114  0.136  0.086 -0.139 -0.039 -0.139 -0.114 -0.014 -0.213 -0.014 -0.213 -0.114 -0.188 -0.114  0.011  0.011 -0.039 -0.089 -0.039 -0.089 -0.139 -0.139  0.136  0.235 -0.089 -0.114 -0.064 -0.014 -0.163 
 0.122 -0.077  0.022  0.072 -0.027 -0.102  0.047 -0.152 -0.127 -0.077 -0.102 -0.077  0.022 -0.077 -0.127 -0.102 -0.102 -0.002 -0.102  0.072  0.022 -0.052  0.147  0.097 -0.052 -0.002 -0.127 -0.052 -0.002 -0.127 -0.002 -0.127 -0.077 -0.102 -0.052 -0.052  0.022 -0.002 -0.077 -0.002 -0.052 -0.052 -0.077  0.197  0.122 -0.027 -0.077 -0.027  0.022 -0.127 
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 0.104 -0.021  0.004  0.004 -0.021  0.004  0.004 -0.021 -0.021 -0.021 -0.021  0.004  0.004 -0.021 -0.021 -0.021  0.004 -0.021 -0.021  0.004 -0.021  0.029  0.004  0.029 -0.021  0.029 -0.021 -0.021  0.029 -0.021  0.004 -0.021 -0.021 -0.021 -0.021  0.029 -0.021 -0.021 -0.021  0.029  0.029  0.004 -0.021 -0.021  0.004  0.004 -0.021 -0.021  0.004  0.004 
 0.104 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020  0.029 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
 0.104 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020  0.029 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
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 0.104 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020  0.029 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
 0.104 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020  0.029 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
 0.104 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020  0.029 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
 0.104 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020  0.029 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
 0.104 -0.020  0.004  0.004 -0.020  0.004  0.004 -0.020 -0.020 -0.020 -0.020  0.004  0.004 -0.020 -0.020 -0.020  0.004 -0.020 -0.020  0.004 -0.020  0.029  0.004  0.029 -0.020  0.029 -0.020 -0.020  0.029 -0.020  0.004 -0.020 -0.020 -0.020 -0.020  0.029 -0.020 -0.020 -0.020  0.029  0.029  0.004 -0.020 -0.020  0.004  0.004 -0.020 -0.020  0.004  0.004 
 0.126 -0.024  0.001  0.001 -0.024  0.001  0.001 -0.024 -0.024 -0.024 -0.024  0.001  0.001 -0.024 -0.024 -0.024  0.001 -0.024 -0.024  0.001 -0.024  0.051  0.001  0.051 -0.024  0.051 -0.024 -0.024  0.026 -0.024  0.026 -0.024 -0.024 -0.024 -0.024  0.076 -0.024 -0.024 -0.024  0.026  0.026  0.026 -0.024 -0.024  0.001  0.026 -0.024 -0.024  0.001  0.001 
 0.238 -0.011 -0.011 -0.011 -0.036 -0.011 -0.011 -0.011 -0.011 -0.011 -0.011 -0.011 -0.011 -0.036 -0.036 -0.036 -0.011  0.014 -0.011 -0.011 -0.036  0.064 -0.011  0.039 -0.036  0.064 -0.036 -0.036  0.039 -0.036  0.014 -0.011 -0.036 -0.036 -0.036  0.064 -0.036 -0.036 -0.036  0.014  0.039  0.014 -0.011 -0.011 -0.011  0.014 -0.036 -0.036 -0.011 -0.011 
 0.553 -0.020  0.004 -0.020 -0.020  0.004 -0.020 -0.070 -0.045  0.079  0.004 -0.045  0.029 -0.020  0.004 -0.070 -0.020 -0.020 -0.045  0.004  0.004  0.054 -0.045  0.004 -0.070  0.029 -0.045 -0.045  0.104 -0.020  0.054 -0.045 -0.070 -0.020  0.029  0.079 -0.020 -0.070 -0.070  0.004  0.129 -0.045  0.029  0.029  0.029  0.004 -0.045 -0.070  0.004 -0.020 
 0.768 -0.079  0.020 -0.029  0.020  0.020 -0.029 -0.129 -0.029  0.195 -0.029 -0.029  0.095 -0.054 -0.004 -0.054 -0.029 -0.004 -0.029 -0.029 -0.004  0.070 -0.004  0.045 -0.104  0.070 -0.054 -0.079  0.095  0.020  0.095 -0.079 -0.079 -0.079  0.070  0.095 -0.029 -0.129 -0.129 -0.029  0.120 -0.004 -0.004 -0.004  0.070  0.020 -0.054 -0.079 -0.004 -0.079 
 0.813 -0.084  0.065 -0.034  0.015  0.015 -0.059 -0.134 -0.009  0.165 -0.034 -0.034  0.090  0.015 -0.034 -0.084  0.040 -0.009 -0.009 -0.084 -0.034  0.040  0.065  0.065 -0.084  0.040 -0.059 -0.084  0.090 -0.009  0.040 -0.084 -0.109 -0.084  0.140  0.140 -0.059 -0.109 -0.159 -0.009  0.115  0.015 -0.009 -0.034  0.165  0.015 -0.059 -0.109  0.040 -0.109 
 0.817 -0.105  0.144  0.019 -0.005  0.044 -0.005 -0.180 -0.030  0.144 -0.055 -0.005  0.144  0.094 -0.030 -0.080  0.044 -0.030  0.069 -0.105 -0.055 -0.005  0.119  0.119 -0.105 -0.005  0.019 -0.130  0.119 -0.030  0.069 -0.130 -0.105 -0.130  0.269  0.194 -0.055 -0.105 -0.180 -0.030  0.119  0.019 -0.030  0.019  0.169  0.094 -0.105 -0.105  0.019 -0.105 
 0.799 -0.098  0.126  0.026 -0.023  0.026  0.051 -0.198 -0.023  0.126 -0.073  0.001  0.151  0.101 -0.023 -0.073  0.026 -0.023  0.051 -0.073 -0.073 -0.023  0.126  0.126 -0.123 -0.048  0.051 -0.123  0.101 -0.048  0.026 -0.148 -0.123 -0.148  0.226  0.176 -0.073 -0.123 -0.148 -0.048  0.151  0.026 -0.048  0.026  0.126  0.076 -0.123 -0.123 -0.023 -0.098 
 0.771 -0.076  0.123  0.023 -0.051 -0.026  0.148 -0.226 -0.001  0.048 -0.026  0.023  0.173  0.098 -0.051 -0.076 -0.026 -0.026  0.023 -0.101 -0.051 -0.051  0.123  0.098 -0.151 -0.051  0.148 -0.126  0.198 -0.101 -0.001 -0.151 -0.151 -0.176  0.223  0.123 -0.101 -0.151 -0.151 -0.051  0.073 -0.001 -0.026  0.023  0.098  0.073 -0.151 -0.126 -0.051 -0.076 
 0.741 -0.056  0.094 -0.006 -0.056 -0.031  0.143 -0.255 -0.006  0.044 -0.031  0.044  0.193  0.143 -0.056 -0.106 -0.031 -0.081  0.019 -0.106 -0.056 -0.056  0.094  0.094 -0.155 -0.056  0.168 -0.131  0.193 -0.106 -0.006 -0.180 -0.155 -0.180  0.218  0.143 -0.106 -0.131 -0.131 -0.056  0.044  0.019 -0.031  0.019  0.069  0.069 -0.155 -0.131 -0.081 -0.106 
 0.729 -0.043  0.082  0.032 -0.068 -0.043  0.132 -0.242 -0.018  0.057 -0.043  0.057  0.206  0.132 -0.068 -0.118 -0.093 -0.068 -0.018 -0.093  0.007 -0.068  0.132  0.082 -0.167 -0.043  0.181 -0.118  0.206 -0.093 -0.018 -0.192 -0.167 -0.192  0.231  0.132 -0.118 -0.118 -0.118 -0.068  0.007 -0.018 -0.043  0.007  0.057  0.007 -0.142 -0.167 -0.018 -0.142 
 0.725 -0.047  0.078  0.028 -0.047 -0.047  0.128 -0.246 -0.022  0.053 -0.047  0.053  0.227  0.128 -0.072 -0.122 -0.122 -0.072 -0.047 -0.097  0.028 -0.072  0.152  0.078 -0.171 -0.047  0.152 -0.122  0.227 -0.097  0.003 -0.196 -0.171 -0.196  0.202  0.128 -0.122 -0.122 -0.146 -0.072 -0.022 -0.047 -0.047  0.003  0.028  0.003 -0.146 -0.171  0.003 -0.122 
 0.645 -0.052  0.022  0.072 -0.052 -0.052  0.072 -0.252 -0.077  0.047 -0.077  0.022  0.197  0.122 -0.077 -0.102 -0.127 -0.052 -0.052 -0.102  0.022 -0.077  0.197  0.072 -0.202 -0.027  0.122 -0.127  0.222 -0.127 -0.002 -0.202 -0.127 -0.202  0.172  0.097 -0.077 -0.127 -0.127 -0.077 -0.027 -0.027 -0.077 -0.002  0.022 -0.002 -0.127 -0.177  0.022 -0.127 
 0.590 -0.058 -0.008  0.142 -0.058 -0.058  0.067 -0.257 -0.083  0.042 -0.083  0.017  0.191  0.117 -0.033 -0.108 -0.133 -0.058 -0.058 -0.108  0.017 -0.083  0.191  0.067 -0.207 -0.058  0.117 -0.133  0.142 -0.133 -0.033 -0.182 -0.133 -0.207  0.191  0.092 -0.083 -0.133 -0.133 -0.083 -0.058 -0.033 -0.083 -0.008  0.017 -0.008 -0.133 -0.157  0.092 -0.133 
 0.510 -0.063 -0.038  0.137 -0.063 -0.063  0.062 -0.262 -0.113 -0.038 -0.088  0.012  0.112  0.087 -0.013 -0.088 -0.138 -0.088 -0.063 -0.088  0.012 -0.088  0.236  0.062 -0.212 -0.063  0.112 -0.113  0.137 -0.162 -0.013 -0.187 -0.138 -0.212  0.062  0.112 -0.038 -0.138 -0.138 -0.088 -0.088 -0.088 -0.063 -0.013 -0.013 -0.038 -0.113 -0.162  0.112 -0.113 
 0.438 -0.060 -0.035  0.140 -0.060 -0.085  0.065 -0.259 -0.135 -0.035 -0.085 -0.010  0.115  0.090 -0.035 -0.085 -0.135 -0.110 -0.135 -0.085  0.040 -0.135  0.239  0.090 -0.209 -0.060  0.090 -0.135  0.140 -0.159 -0.010 -0.184 -0.135 -0.209 -0.010  0.115 -0.060 -0.110 -0.110 -0.110 -0.110 -0.085 -0.060 -0.035  0.015 -0.060 -0.110 -0.159  0.115 -0.110 
 0.383 -0.041 -0.041  0.158 -0.066 -0.116  0.034 -0.265 -0.091 -0.091 -0.066 -0.041  0.109  0.084 -0.041 -0.091 -0.141 -0.141 -0.141 -0.066  0.034 -0.141  0.233  0.084 -0.190 -0.041  0.084 -0.165  0.109 -0.190 -0.016 -0.165 -0.141 -0.215 -0.016  0.109 -0.066 -0.116 -0.116 -0.116 -0.141 -0.091 -0.066 -0.016  0.009 -0.066 -0.116 -0.165  0.109 -0.116 
 0.383 -0.041 -0.041  0.158 -0.066 -0.116  0.009 -0.265 -0.066 -0.091 -0.066 -0.091  0.109  0.059 -0.041 -0.091 -0.165 -0.141 -0.141 -0.066  0.059 -0.141  0.233  0.059 -0.190 -0.041  0.084 -0.165  0.109 -0.165 -0.016 -0.141 -0.141 -0.215 -0.041  0.109 -0.066 -0.116 -0.116 -0.116 -0.141 -0.091 -0.066 -0.016  0.009 -0.091 -0.116 -0.165  0.084 -0.116 
 0.333 -0.040 -0.065  0.159 -0.090 -0.115  0.009 -0.240 -0.065 -0.090 -0.065 -0.115  0.109  0.034 -0.040 -0.090 -0.190 -0.140 -0.140 -0.065  0.059 -0.165  0.234  0.059 -0.190 -0.040  0.059 -0.190  0.084 -0.165 -0.040 -0.140 -0.140 -0.215 -0.040  0.109 -0.040 -0.115 -0.115 -0.115 -0.165 -0.090 -0.065 -0.015  0.009 -0.140 -0.090 -0.165  0.084 -0.115 
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 0.182 -0.042  0.033  0.008 -0.042 -0.017  0.008 -0.067 -0.067 -0.017 -0.042 -0.017  0.033 -0.042 -0.017 -0.042 -0.017 -0.042 -0.042  0.058  0.058  0.008  0.008  0.058 -0.067  0.033 -0.067 -0.067  0.033 -0.042 -0.017 -0.067 -0.017 -0.017 -0.042  0.033  0.033 -0.042 -0.067  0.008  0.008 -0.017 -0.042  0.157 -0.017  0.008 -0.017 -0.017  0.008 -0.042 
 0.163 -0.036  0.039  0.014 -0.036 -0.011  0.014 -0.061 -0.061 -0.011 -0.036 -0.011  0.014 -0.036 -0.011 -0.036 -0.011 -0.036 -0.036  0.064  0.064  0.014  0.014  0.039 -0.061  0.014 -0.061 -0.061  0.039 -0.036 -0.011 -0.061 -0.036 -0.011 -0.036  0.014  0.039 -0.036 -0.061  0.014  0.014 -0.036 -0.036  0.163 -0.011  0.014 -0.011 -0.011  0.014 -0.036 
 0.145 -0.054  0.046  0.021 -0.029 -0.004 -0.004 -0.054 -0.054 -0.004 -0.029 -0.004  0.021 -0.029 -0.004 -0.029 -0.004 -0.029 -0.029  0.046  0.046  0.021  0.021  0.046 -0.054  0.021 -0.054 -0.054  0.046 -0.029 -0.004 -0.054 -0.029 -0.029 -0.029  0.021  0.046 -0.029 -0.054  0.021  0.021 -0.029 -0.029  0.170 -0.004  0.021 -0.004 -0.004  0.021 -0.029 
 0.147 -0.052  0.047  0.022 -0.027 -0.002 -0.002 -0.052 -0.052 -0.002 -0.027 -0.002  0.022 -0.027 -0.002 -0.027 -0.002 -0.027 -0.027  0.047  0.047  0.022  0.022  0.022 -0.052  0.022 -0.052 -0.052  0.047 -0.027 -0.002 -0.052 -0.027 -0.027 -0.027 -0.002  0.047 -0.027 -0.052  0.022  0.022 -0.027 -0.027  0.172 -0.002  0.022 -0.002 -0.027  0.022 -0.027 
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 0.157 -0.017  0.033  0.033 -0.017  0.008 -0.017 -0.042 -0.042  0.008 -0.017 -0.017  0.008 -0.042  0.008 -0.042  0.008 -0.017 -0.017 -0.017  0.058  0.033  0.033  0.058 -0.042  0.033 -0.042 -0.042  0.033 -0.042 -0.017 -0.042 -0.017 -0.017 -0.017  0.008  0.008 -0.042 -0.042  0.008  0.008  0.008 -0.017  0.083 -0.017  0.008 -0.017 -0.017  0.008 -0.017 
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 0.136 -0.013 -0.013  0.011 -0.013  0.011  0.011 -0.038 -0.038  0.011 -0.013 -0.013  0.011 -0.038 -0.013 -0.038  0.011  0.011 -0.013 -0.013  0.011  0.036  0.036  0.061 -0.038  0.036 -0.038 -0.038  0.011 -0.038 -0.013 -0.013 -0.038 -0.013 -0.013  0.011 -0.038 -0.038 -0.038  0.011  0.011  0.011 -0.013  0.011  0.011  0.011 -0.013 -0.038 -0.013 -0.013 
 0.136 -0.013 -0.013  0.011 -0.013  0.011  0.011 -0.038 -0.038  0.011 -0.013 -0.013  0.011 -0.038 -0.013 -0.038  0.011  0.011 -0.013 -0.013  0.011  0.036  0.036  0.061 -0.038  0.036 -0.038 -0.038  0.011 -0.038 -0.013 -0.013 -0.038 -0.013 -0.013  0.011 -0.038 -0.038 -0.038  0.011  0.011  0.011 -0.013  0.011  0.011  0.011 -0.013 -0.038 -0.013 -0.013 
 0.136 -0.013 -0.013  0.011 -0.013  0.011  0.011 -0.038 -0.038  0.011 -0.013 -0.013  0.011 -0.038 -0.013 -0.038  0.011  0.011 -0.013 -0.013  0.011  0.036  0.036  0.061 -0.038  0.036 -0.038 -0.038  0.011 -0.038 -0.013 -0.013 -0.038 -0.013 -0.013  0.011 -0.038 -0.038 -0.038  0.011  0.011  0.011 -0.013  0.011  0.011  0.011 -0.013 -0.038 -0.013 -0.013 
 0.136 -0.013 -0.013  0.011 -0.013  0.011  0.011 -0.038 -0.038  0.011 -0.013 -0.013  0.011 -0.038 -0.013 -0.038  0.011  0.011 -0.013 -0.013  0.011  0.036  0.036  0.061 -0.038  0.036 -0.038 -0.038  0.011 -0.038 -0.013 -0.013 -0.038 -0.013 -0.013  0.011 -0.038 -0.038 -0.038  0.011  0.011  0.011 -0.013  0.011  0.011  0.011 -0.013 -0.038 -0.013 -0.013 
 0.136 -0.013 -0.013  0.011 -0.013  0.011  0.011 -0.038 -0.038  0.011 -0.013 -0.013  0.011 -0.038 -0.013 -0.038  0.011  0.011 -0.013 -0.013  0.011  0.036  0.036  0.061 -0.038  0.036 -0.038 -0.038  0.011 -0.038 -0.013 -0.013 -0.038 -0.013 -0.013  0.011 -0.038 -0.038 -0.038  0.011  0.011  0.011 -0.013  0.011  0.011  0.011 -0.013 -0.038 -0.013 -0.013 
 0.136 -0.013 -0.013  0.011 -0.013  0.011  0.011 -0.038 -0.038  0.011 -0.013 -0.013  0.011 -0.038 -0.013 -0.038  0.011  0.011 -0.013 -0.013  0.011  0.036  0.036  0.061 -0.038  0.036 -0.038 -0.038  0.011 -0.038 -0.013 -0.013 -0.038 -0.013 -0.013  0.011 -0.038 -0.038 -0.038  0.011  0.011  0.011 -0.013  0.011  0.011  0.011 -0.013 -0.038 -0.013 -0.013 
 0.136 -0.013 -0.013  0.011 -0.013  0.011  0.011 -0.038 -0.038  0.011 -0.013 -0.013  0.011 -0.038 -0.013 -0.038  0.011  0.011 -0.013 -0.013  0.011  0.036  0.036  0.061 -0.038  0.036 -0.038 -0.038  0.011 -0.038 -0.013 -0.013 -0.038 -0.013 -0.013  0.011 -0.038 -0.038 -0.038  0.011  0.011  0.011 -0.013  0.011  0.011  0.011 -0.013 -0.038 -0.013 -0.013 
 0.239  0.015 -0.035 -0.010 -0.010  0.015  0.065 -0.060 -0.035  0.015 -0.035 -0.010 -0.010 -0.010 -0.035 -0.060  0.015 -0.010 -0.035 -0.035 -0.010  0.015  0.065  0.115 -0.060  0.040 -0.035 -0.035  0.015 -0.060 -0.010 -0.035 -0.035 -0.010 -0.010  0.015 -0.035 -0.060 -0.060 -0.010  0.040  0.040 -0.035  0.040  0.040  0.040 -0.010 -0.035 -0.035 -0.035 
 0.308  0.009 -0.066 -0.016  0.034  0.009  0.183 -0.116 -0.066  0.084 -0.016  0.059 -0.041 -0.016 -0.066 -0.091  0.034 -0.016 -0.066  0.009 -0.016 -0.041  0.183  0.109 -0.091  0.009 -0.091 -0.091  0.009 -0.091  0.034 -0.041 -0.066 -0.041  0.059  0.034 -0.066 -0.091 -0.116 -0.016  0.084  0.034 -0.041  0.009  0.059  0.084 -0.041 -0.066 -0.091 -0.091 
 0.364 -0.035 -0.035  0.040  0.065  0.015  0.164 -0.159 -0.085  0.090 -0.035  0.065 -0.060  0.065 -0.085 -0.135  0.015  0.040 -0.010  0.040 -0.010 -0.035  0.289  0.115 -0.085 -0.010 -0.085 -0.110  0.065 -0.110 -0.010 -0.085 -0.110 -0.085  0.115 -0.035 -0.060 -0.110 -0.110 -0.035  0.090  0.090 -0.060  0.040  0.115  0.040 -0.085 -0.110 -0.035 -0.135 
 0.330 -0.093 -0.018  0.031  0.006 -0.018  0.106 -0.218 -0.118  0.056 -0.093 -0.018 -0.068  0.181 -0.143 -0.168  0.056  0.081  0.006  0.006  0.006 -0.093  0.281  0.131 -0.118 -0.018 -0.068 -0.143  0.131 -0.168  0.006 -0.118 -0.143 -0.143  0.156  0.006 -0.118 -0.043 -0.068 -0.068  0.031  0.106 -0.068  0.006  0.106 -0.018 -0.118 -0.118 -0.018 -0.143 
 0.312 -0.061 -0.036  0.063 -0.011 -0.011  0.063 -0.236 -0.161  0.038 -0.086 -0.011 -0.086  0.188 -0.136 -0.111  0.013  0.063  0.013  0.013  0.013 -0.111  0.263  0.113 -0.136 -0.011 -0.061 -0.136  0.138 -0.186  0.038 -0.136 -0.111 -0.161  0.138  0.013 -0.111 -0.061 -0.036 -0.061  0.013  0.088 -0.086  0.013  0.113 -0.036 -0.136 -0.136 -0.011 -0.161 
 0.271 -0.028 -0.053  0.096 -0.003 -0.028  0.046 -0.228 -0.178 -0.003 -0.128 -0.028 -0.078  0.196 -0.153 -0.128 -0.003  0.046 -0.003 -0.003  0.071 -0.128  0.221  0.071 -0.128  0.021 -0.003 -0.153  0.171 -0.228  0.096 -0.153 -0.128 -0.178  0.046 -0.003 -0.078 -0.028 -0.053 -0.003 -0.053  0.021 -0.103  0.046  0.096 -0.028 -0.153 -0.103  0.046 -0.153 
 0.267 -0.032 -0.057  0.092  0.017 -0.032  0.017 -0.232 -0.157 -0.007 -0.132 -0.032 -0.082  0.167 -0.157 -0.132 -0.007  0.042 -0.032 -0.007  0.067 -0.132  0.217  0.067 -0.132  0.017 -0.007 -0.157  0.167 -0.207  0.117 -0.157 -0.132 -0.182  0.042 -0.032 -0.082 -0.032 -0.057 -0.007 -0.057  0.017 -0.107  0.042  0.092 -0.007 -0.132 -0.107  0.067 -0.157 
 0.199 -0.025 -0.050  0.075  0.050 -0.050  0.000 -0.249 -0.174 -0.025 -0.125 -0.025 -0.050  0.174 -0.174 -0.174 -0.050  0.025 -0.050 -0.025  0.050 -0.149  0.199  0.050 -0.149  0.000  0.075 -0.149  0.199 -0.224  0.100 -0.199 -0.149 -0.199  0.025 -0.050 -0.050 -0.050 -0.050 -0.025 -0.100  0.000 -0.125  0.050  0.100 -0.025 -0.125 -0.100  0.075 -0.174 
 0.192 -0.032 -0.057  0.092  0.042 -0.057 -0.007 -0.257 -0.157 -0.032 -0.132 -0.032 -0.032  0.142 -0.157 -0.157 -0.057  0.042 -0.057 -0.032  0.042 -0.157  0.217  0.017 -0.157  0.017  0.092 -0.157  0.192 -0.232  0.092 -0.207 -0.157 -0.232  0.017 -0.032 -0.057 -0.082 -0.057 -0.032 -0.107 -0.032 -0.132  0.042  0.092 -0.032 -0.132 -0.082  0.117 -0.182 
 0.111  0.011 -0.063  0.111  0.036 -0.063 -0.013 -0.263 -0.188 -0.038 -0.163 -0.088 -0.038  0.086 -0.163 -0.138 -0.038  0.036 -0.113 -0.013  0.036 -0.213  0.236  0.011 -0.138  0.011  0.111 -0.163  0.186 -0.238  0.061 -0.213 -0.163 -0.238 -0.013 -0.013 -0.038 -0.088 -0.038 -0.063 -0.138 -0.063 -0.138  0.011  0.036 -0.063 -0.138 -0.063  0.111 -0.188 
 0.133  0.033 -0.067  0.108  0.033 -0.067 -0.042 -0.266 -0.191 -0.042 -0.191 -0.092 -0.042  0.033 -0.142 -0.117 -0.042  0.033 -0.092 -0.017  0.083 -0.216  0.257 -0.017 -0.142  0.008  0.083 -0.166  0.207 -0.241  0.033 -0.216 -0.166 -0.241 -0.042  0.033 -0.067 -0.092 -0.017 -0.067 -0.142 -0.117 -0.166  0.008  0.008 -0.042 -0.117 -0.067  0.108 -0.216 
 0.106  0.031 -0.069  0.180 -0.019 -0.094 -0.019 -0.293 -0.168 -0.044 -0.193 -0.119 -0.044  0.031 -0.119 -0.069 -0.094  0.006 -0.094 -0.019  0.081 -0.193  0.255 -0.019 -0.193  0.031  0.081 -0.168  0.205 -0.268  0.006 -0.218 -0.168 -0.243 -0.069  0.056 -0.069 -0.094 -0.019 -0.069 -0.143 -0.119 -0.193  0.006 -0.019 -0.044 -0.119 -0.069  0.056 -0.193 
 0.102 -0.022 -0.047  0.202 -0.047 -0.097 -0.022 -0.296 -0.147 -0.047 -0.172 -0.097 -0.022  0.052 -0.122 -0.072 -0.097  0.002 -0.097 -0.022  0.127 -0.197  0.227 -0.022 -0.197  0.027  0.127 -0.172  0.202 -0.272  0.002 -0.247 -0.172 -0.247 -0.072  0.077 -0.072 -0.097 -0.022 -0.097 -0.147 -0.122 -0.197  0.002  0.002 -0.047 -0.122 -0.047  0.077 -0.172 
 0.096 -0.028 -0.053  0.221 -0.053 -0.103 -0.003 -0.302 -0.128 -0.053 -0.178 -0.078 -0.028  0.071 -0.103 -0.078 -0.103 -0.003 -0.103 -0.028  0.146 -0.203  0.221 -0.028 -0.203  0.021  0.096 -0.178  0.221 -0.278  0.021 -0.253 -0.178 -0.253 -0.078  0.096 -0.078 -0.103 -0.028 -0.103 -0.153 -0.178 -0.228  0.021 -0.003 -0.053 -0.128 -0.078  0.071 -0.153 
 0.096 -0.029 -0.054  0.220 -0.054 -0.129 -0.004 -0.303 -0.129 -0.054 -0.129 -0.079 -0.029  0.096 -0.079 -0.079 -0.153 -0.029 -0.153 -0.029  0.170 -0.203  0.220 -0.054 -0.228  0.021  0.046 -0.178  0.220 -0.278  0.021 -0.253 -0.178 -0.253 -0.129  0.096 -0.079 -0.129  0.021 -0.104 -0.153 -0.153 -0.203  0.021  0.021 -0.054 -0.129 -0.029  0.021 -0.203 
 0.096 -0.028 -0.053  0.221 -0.053 -0.128  0.046 -0.302 -0.128 -0.078 -0.128 -0.003 -0.028  0.096 -0.053 -0.103 -0.178 -0.053 -0.128 -0.053  0.171 -0.178  0.221 -0.053 -0.253  0.046  0.021 -0.203  0.146 -0.278  0.046 -0.228 -0.178 -0.228 -0.128  0.071 -0.078 -0.128  0.021 -0.103 -0.178 -0.153 -0.203  0.071  0.021 -0.103 -0.128 -0.028 -0.003 -0.203 
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 0.172 -0.052  0.022  0.072 -0.052 -0.077  0.022 -0.102 -0.102 -0.052 -0.077 -0.052 -0.027 -0.052 -0.077 -0.077 -0.102 -0.027 -0.077  0.147  0.022 -0.077 -0.027  0.047 -0.077 -0.002 -0.077 -0.052  0.047 -0.077 -0.027 -0.077 -0.052 -0.052 -0.052 -0.002  0.047 -0.027 -0.027 -0.052 -0.027 -0.027 -0.077  0.122 -0.027 -0.002 -0.052 -0.027  0.022 -0.077 
 0.184 -0.065  0.009  0.084 -0.040 -0.065 -0.015 -0.090 -0.090 -0.040 -0.065 -0.040 -0.040 -0.065 -0.065 -0.065 -0.065 -0.015 -0.065  0.109  0.034 -0.065 -0.015  0.059 -0.065  0.009 -0.090 -0.065  0.034 -0.065 -0.015 -0.065 -0.040 -0.040 -0.065  0.009  0.059 -0.040 -0.015 -0.040 -0.015 -0.040 -0.065  0.134 -0.015  0.034 -0.040 -0.040  0.009 -0.065 
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 0.177 -0.047  0.027  0.102 -0.047 -0.047  0.002 -0.072 -0.072 -0.022 -0.047 -0.022  0.027 -0.047 -0.047 -0.047 -0.022 -0.022 -0.047  0.077  0.052  0.002  0.002  0.027 -0.047  0.027 -0.072 -0.072  0.027 -0.047 -0.022 -0.072 -0.022 -0.022 -0.047  0.052  0.027 -0.022  0.002  0.002  0.002 -0.047 -0.047  0.152 -0.022  0.027 -0.022 -0.022  0.002 -0.047 
 0.182 -0.042  0.032  0.032 -0.042 -0.042  0.007 -0.067 -0.067 -0.017 -0.042 -0.017  0.032 -0.042 -0.042 -0.042 -0.017 -0.042 -0.042  0.057  0.057  0.007  0.007  0.032 -0.042  0.032 -0.067 -0.067  0.032 -0.042 -0.017 -0.067 -0.017 -0.017 -0.017  0.032  0.032 -0.017 -0.042  0.007  0.007 -0.042 -0.042  0.157 -0.017  0.032 -0.017 -0.017  0.007 -0.042 
 0.158 -0.041  0.034  0.034 -0.041 -0.041  0.009 -0.066 -0.066 -0.016 -0.041 -0.016  0.009 -0.041 -0.041 -0.041 -0.016 -0.041 -0.041  0.059  0.059  0.009  0.009  0.034 -0.041  0.034 -0.066 -0.066  0.034 -0.041 -0.016 -0.066 -0.016 -0.016 -0.016  0.009  0.059 -0.041 -0.066  0.009  0.009 -0.041 -0.041  0.158 -0.016  0.034 -0.016 -0.016  0.009 -0.041 
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 0.134 -0.041  0.034  0.009 -0.041 -0.016  0.009 -0.066 -0.066 -0.016 -0.041 -0.016  0.009 -0.041 -0.016 -0.041 -0.016 -0.041 -0.041  0.059  0.059  0.009  0.009  0.034 -0.066  0.034 -0.041 -0.066  0.034 -0.041  0.009 -0.066 -0.016 -0.016 -0.016 -0.016  0.059 -0.041 -0.016  0.009  0.009 -0.041 -0.041  0.158 -0.016  0.009 -0.016 -0.016  0.009 -0.016 
 0.113 -0.037 -0.012  0.013 -0.037 -0.012  0.013 -0.062 -0.062 -0.012 -0.037 -0.012 -0.012 -0.037 -0.012 -0.037 -0.012 -0.037 -0.037  0.013  0.063  0.013  0.013  0.013 -0.062  0.038 -0.037 -0.062  0.013 -0.037  0.038 -0.062 -0.012 -0.012 -0.012 -0.012  0.038 -0.062 -0.012 -0.012  0.013 -0.037 -0.037  0.088 -0.037  0.013 -0.012 -0.037 -0.012 -0.012 
 0.117 -0.032 -0.032  0.017 -0.032 -0.007  0.017 -0.057 -0.057 -0.007 -0.032 -0.007 -0.007 -0.032 -0.032 -0.032 -0.007 -0.032 -0.032  0.017  0.067  0.017  0.017  0.017 -0.057  0.042 -0.032 -0.057  0.017 -0.032  0.042 -0.057 -0.032 -0.007 -0.007 -0.007 -0.007 -0.057 -0.007 -0.007 -0.007 -0.032 -0.032  0.042 -0.032  0.017 -0.007 -0.032 -0.007 -0.007 
 0.123 -0.026 -0.026 -0.001 -0.051 -0.001  0.023 -0.051 -0.051 -0.001 -0.026 -0.001 -0.026 -0.026 -0.026 -0.026 -0.001 -0.026 -0.026  0.023  0.048  0.023  0.023  0.023 -0.051  0.048 -0.026 -0.051 -0.001 -0.051  0.023 -0.051 -0.026 -0.001 -0.026 -0.001 -0.001 -0.051 -0.001 -0.001 -0.001 -0.026 -0.051  0.023 -0.026  0.023 -0.001 -0.026 -0.026 -0.001 
 0.124 -0.026 -0.026 -0.001 -0.051 -0.026  0.024 -0.051 -0.051 -0.001 -0.026 -0.001 -0.026 -0.026 -0.051 -0.026 -0.001 -0.026 -0.026  0.024  0.049  0.024  0.024  0.024 -0.051  0.049 -0.026 -0.051 -0.001 -0.051  0.024 -0.051 -0.026 -0.001 -0.026 -0.001 -0.001 -0.051 -0.001 -0.001 -0.001 -0.026 -0.051  0.024 -0.026  0.024 -0.001 -0.026 -0.026 -0.001 
 0.126 -0.023 -0.023  0.001 -0.048 -0.023  0.026 -0.048 -0.048 -0.023 -0.023  0.001 -0.023 -0.023 -0.048 -0.023 -0.023 -0.023 -0.023  0.026  0.026  0.026  0.026  0.026 -0.048  0.051 -0.023 -0.048  0.001 -0.048  0.026 -0.048 -0.023  0.001 -0.023  0.001  0.001 -0.048  0.001  0.001  0.001 -0.023 -0.048  0.026 -0.023  0.001 -0.023 -0.023 -0.023  0.001 
 0.106 -0.018 -0.018  0.006 -0.043 -0.018  0.031 -0.043 -0.043 -0.043 -0.043  0.006 -0.018 -0.018 -0.043 -0.018 -0.018 -0.043 -0.018  0.031  0.006  0.031  0.006  0.031 -0.043  0.031 -0.018 -0.043  0.006 -0.043  0.031 -0.043 -0.018  0.006 -0.018  0.006  0.006 -0.043  0.006  0.006  0.006 -0.018 -0.043 -0.018 -0.018  0.006 -0.018 -0.018 -0.018  0.006 
 0.084 -0.016 -0.016 -0.016 -0.041 -0.016  0.034 -0.041 -0.041 -0.041 -0.041  0.009 -0.016 -0.016 -0.041 -0.016 -0.016 -0.041 -0.016  0.034 -0.016  0.009  0.009  0.034 -0.041  0.034 -0.016 -0.041  0.009 -0.041  0.034 -0.041 -0.016  0.009 -0.016  0.009  0.009 -0.041  0.009  0.009  0.009 -0.016 -0.041 -0.016 -0.016  0.009 -0.016 -0.016 -0.016  0.009 
 0.084 -0.015 -0.015 -0.015 -0.040 -0.015  0.034 -0.040 -0.040 -0.040 -0.040  0.009 -0.015 -0.015 -0.040 -0.015 -0.015 -0.040 -0.015  0.034 -0.015  0.009  0.009  0.034 -0.040  0.034 -0.015 -0.040  0.009 -0.040  0.034 -0.040 -0.015  0.009 -0.015  0.009  0.009 -0.040  0.009  0.009  0.009 -0.015 -0.040 -0.015 -0.015  0.009 -0.015 -0.015 -0.015  0.009 
 0.085 -0.014 -0.014 -0.014 -0.039 -0.014  0.035 -0.039 -0.039 -0.039 -0.039  0.010 -0.014 -0.014 -0.039 -0.014 -0.014 -0.039 -0.039  0.035 -0.014  0.010 -0.014  0.035 -0.039  0.035 -0.014 -0.039  0.010 -0.039  0.035 -0.039 -0.014  0.010 -0.014  0.010  0.010 -0.039  0.010  0.010  0.010 -0.014 -0.039 -0.014 -0.014  0.010 -0.014 -0.014 -0.014  0.010 
 0.221 -0.028 -0.028 -0.028  0.022 -0.028  0.047 -0.053 -0.053 -0.053 -0.053  0.047 -0.028 -0.028 -0.053 -0.028 -0.028 -0.053 -0.053  0.047  0.022 -0.003 -0.028  0.047 -0.053  0.022 -0.003 -0.053  0.022 -0.053  0.022 -0.028 -0.028 -0.003 -0.028 -0.003 -0.003 -0.053 -0.003 -0.003  0.047 -0.028 -0.028 -0.028 -0.028 -0.003 -0.028 -0.028 -0.028 -0.003 
 0.328 -0.045 -0.070 -0.020 -0.020 -0.020  0.079 -0.095 -0.095 -0.045 -0.045  0.029  0.004  0.004 -0.095 -0.045 -0.070 -0.045 -0.120  0.079 -0.045 -0.020  0.029  0.229 -0.095  0.054  0.079 -0.120  0.029 -0.120  0.004 -0.070 -0.045 -0.045 -0.045  0.054  0.004 -0.120  0.054 -0.045  0.004 -0.020 -0.070 -0.045 -0.070  0.004 -0.070 -0.070 -0.070 -0.045 
 0.412 -0.037 -0.062  0.013 -0.062 -0.062  0.212 -0.137 -0.112 -0.062 -0.062 -0.012  0.013 -0.037 -0.137 -0.062 -0.112 -0.012 -0.112  0.063 -0.037 -0.012  0.088  0.287 -0.112  0.038  0.113 -0.161  0.013 -0.161  0.038 -0.112 -0.087 -0.087 -0.087  0.063 -0.012 -0.137  0.038 -0.087 -0.012  0.013 -0.087  0.013  0.013  0.013 -0.112 -0.087 -0.062 -0.062 
 0.394 -0.054  0.020  0.045 -0.054 -0.029  0.170 -0.204 -0.179 -0.029 -0.054 -0.054  0.095 -0.054 -0.129 -0.029 -0.179 -0.004 -0.129  0.045  0.020 -0.029  0.145  0.294 -0.179 -0.029  0.120 -0.204  0.095 -0.204  0.045 -0.179 -0.129 -0.154 -0.079  0.095 -0.029 -0.104  0.045 -0.129 -0.029  0.070 -0.104  0.045  0.045 -0.029 -0.129 -0.154 -0.104 -0.129 
 0.423 -0.075 -0.000  0.074 -0.050 -0.025  0.124 -0.225 -0.200 -0.050 -0.025 -0.075  0.124 -0.025 -0.150 -0.050 -0.200 -0.025 -0.150  0.024 -0.000 -0.050  0.149  0.274 -0.200 -0.050  0.099 -0.175  0.074 -0.200  0.074 -0.200 -0.125 -0.175 -0.100  0.074 -0.025 -0.075  0.024 -0.100 -0.050  0.049 -0.025  0.049  0.099 -0.075 -0.150 -0.175 -0.075 -0.075 
 0.339 -0.060 -0.035  0.140 -0.035 -0.060  0.090 -0.259 -0.234 -0.010 -0.060 -0.085  0.115 -0.010 -0.184 -0.085 -0.209 -0.035 -0.184 -0.010 -0.010 -0.110  0.189  0.214 -0.184 -0.085  0.115 -0.159  0.065 -0.234  0.140 -0.209 -0.135 -0.209 -0.085  0.040 -0.060 -0.110 -0.010 -0.110 -0.135  0.015 -0.035  0.040  0.164 -0.085 -0.159 -0.209 -0.010 -0.110 
 0.308 -0.066 -0.041  0.158 -0.066 -0.066  0.059 -0.290 -0.215 -0.016 -0.066 -0.066  0.109 -0.041 -0.190 -0.091 -0.215 -0.041 -0.190 -0.016  0.009 -0.116  0.134  0.208 -0.141 -0.066  0.134 -0.141  0.034 -0.240  0.158 -0.215 -0.141 -0.215 -0.091  0.009 -0.066 -0.116 -0.041 -0.116 -0.141 -0.016  0.009  0.059  0.158 -0.091 -0.165 -0.215  0.009 -0.116 
 0.176 -0.073 -0.048  0.201 -0.073 -0.098  0.026 -0.297 -0.248 -0.048 -0.098 -0.098  0.051 -0.048 -0.173 -0.123 -0.173 -0.098 -0.198 -0.023  0.026 -0.098  0.126  0.151 -0.173 -0.073  0.176 -0.148  0.001 -0.248  0.151 -0.223 -0.148 -0.248 -0.073  0.026 -0.048 -0.123 -0.023 -0.123 -0.148 -0.048  0.001  0.076  0.176 -0.148 -0.148 -0.223  0.076 -0.098 
 0.125 -0.074 -0.049  0.200 -0.074 -0.124  0.025 -0.274 -0.249 -0.049 -0.099 -0.099  0.050 -0.049 -0.174 -0.124 -0.174 -0.074 -0.199 -0.024  0.050 -0.099  0.150  0.150 -0.174 -0.074  0.175 -0.199  0.025 -0.274  0.100 -0.224 -0.149 -0.249 -0.049  0.025 -0.049 -0.124 -0.024 -0.124 -0.149 -0.074  0.000  0.075  0.175 -0.149 -0.149 -0.224  0.125 -0.099 
 0.095 -0.105 -0.030  0.244 -0.105 -0.130 -0.005 -0.279 -0.204 -0.055 -0.105 -0.105  0.045 -0.030 -0.154 -0.130 -0.179 -0.080 -0.204 -0.030  0.070 -0.130  0.144  0.144 -0.179 -0.080  0.169 -0.204  0.020 -0.279  0.070 -0.179 -0.154 -0.254 -0.055  0.045 -0.055 -0.130 -0.005 -0.130 -0.179 -0.055 -0.030  0.070  0.169 -0.154 -0.130 -0.229  0.144 -0.105 
 0.094 -0.105 -0.030  0.244 -0.080 -0.130 -0.005 -0.280 -0.205 -0.055 -0.105 -0.105  0.044 -0.030 -0.155 -0.155 -0.180 -0.080 -0.205 -0.030  0.094 -0.130  0.144  0.144 -0.180 -0.080  0.169 -0.205  0.019 -0.280  0.044 -0.180 -0.155 -0.255 -0.055  0.019 -0.055 -0.130 -0.005 -0.130 -0.180 -0.055 -0.030  0.069  0.169 -0.155 -0.105 -0.230  0.144 -0.105 
 0.092 -0.108 -0.033  0.241 -0.083 -0.157 -0.008 -0.282 -0.133 -0.058 -0.108 -0.108  0.042 -0.033 -0.157 -0.157 -0.182 -0.083 -0.232 -0.033  0.142 -0.133  0.142  0.142 -0.182 -0.083  0.166 -0.207  0.017 -0.282  0.042 -0.182 -0.157 -0.257 -0.083  0.017 -0.058 -0.133 -0.008 -0.133 -0.182 -0.058 -0.033  0.067  0.142 -0.157 -0.108 -0.232  0.142 -0.133 
 0.090 -0.110 -0.035  0.239 -0.085 -0.159  0.015 -0.284 -0.135 -0.060 -0.110 -0.110  0.040 -0.035 -0.159 -0.159 -0.184 -0.085 -0.234 -0.035  0.140 -0.135  0.140  0.164 -0.184 -0.060  0.164 -0.209  0.015 -0.284  0.040 -0.184 -0.159 -0.259 -0.085  0.015 -0.060 -0.135 -0.010 -0.135 -0.184 -0.060 -0.035  0.065  0.140 -0.159 -0.110 -0.234  0.140 -0.135 
 0.062 -0.113 -0.038  0.236 -0.088 -0.187  0.012 -0.287 -0.088 -0.063 -0.113 -0.138  0.037 -0.038 -0.162 -0.187 -0.187 -0.088 -0.237 -0.038  0.161 -0.162  0.137  0.161 -0.187 -0.063  0.137 -0.212 -0.038 -0.287  0.037 -0.187 -0.162 -0.262 -0.138 -0.013 -0.063 -0.138 -0.013 -0.138 -0.187 -0.038 -0.038  0.062  0.137 -0.162 -0.113 -0.212  0.161 -0.162 
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 0.037 -0.113 -0.038  0.186 -0.088 -0.237 -0.038 -0.312 -0.063 -0.038 -0.113 -0.113  0.062 -0.038 -0.212 -0.187 -0.187 -0.088 -0.237 -0.063  0.161 -0.187  0.161  0.137 -0.187 -0.063  0.087 -0.212 -0.013 -0.287  0.037 -0.187 -0.162 -0.262 -0.088 -0.013 -0.063 -0.138 -0.038 -0.138 -0.187 -0.038 -0.038  0.037  0.161 -0.138 -0.113 -0.212  0.087 -0.212 
 0.037 -0.088 -0.038  0.161 -0.088 -0.237 -0.038 -0.312 -0.063 -0.038 -0.138 -0.113  0.062 -0.038 -0.212 -0.187 -0.212 -0.088 -0.237 -0.063  0.186 -0.162  0.161  0.137 -0.187 -0.063  0.012 -0.212 -0.038 -0.287  0.037 -0.187 -0.162 -0.262 -0.088  0.012 -0.063 -0.138 -0.063 -0.138 -0.187 -0.038 -0.088  0.037  0.137 -0.113 -0.113 -0.212  0.087 -0.212 
 0.035 -0.090 -0.040  0.159 -0.090 -0.239 -0.040 -0.314 -0.040 -0.040 -0.140 -0.115  0.060 -0.040 -0.214 -0.189 -0.214 -0.090 -0.214 -0.065  0.184 -0.164  0.159  0.135 -0.189 -0.040  0.010 -0.189 -0.065 -0.289  0.035 -0.189 -0.164 -0.264 -0.090  0.010 -0.065 -0.140 -0.065 -0.140 -0.189 -0.040 -0.090  0.035  0.135 -0.115 -0.115 -0.189  0.085 -0.214 
 0.033 -0.092 -0.042  0.157 -0.092 -0.241 -0.042 -0.316 -0.042 -0.042 -0.142 -0.117  0.058 -0.042 -0.216 -0.191 -0.216 -0.067 -0.191 -0.067  0.182 -0.166  0.157  0.157 -0.191 -0.042  0.008 -0.166 -0.067 -0.291  0.033 -0.191 -0.166 -0.241 -0.067  0.008 -0.067 -0.142 -0.067 -0.142 -0.191 -0.042 -0.092  0.033  0.133 -0.117 -0.117 -0.191  0.083 -0.216 
 0.029 -0.096 -0.046  0.129 -0.096 -0.245 -0.046 -0.320 -0.021 -0.046 -0.170 -0.096  0.054 -0.046 -0.220 -0.195 -0.220 -0.071 -0.195 -0.071  0.178 -0.170  0.153  0.153 -0.195 -0.046 -0.046 -0.170 -0.096 -0.295  0.029 -0.195 -0.170 -0.245 -0.071  0.004 -0.071 -0.145 -0.071 -0.096 -0.195 -0.096 -0.121  0.029  0.129 -0.121 -0.121 -0.195  0.079 -0.220 
 0.110 -0.015  0.010  0.110 -0.040 -0.164 -0.015 -0.239 -0.065 -0.040 -0.140 -0.115  0.085 -0.065 -0.189 -0.140 -0.214 -0.090 -0.164 -0.015  0.110 -0.140  0.060  0.135 -0.140 -0.065 -0.040 -0.115 -0.090 -0.214 -0.040 -0.189 -0.115 -0.189 -0.065 -0.040 -0.015 -0.115 -0.040 -0.040 -0.115 -0.065 -0.115  0.035  0.085 -0.115 -0.090 -0.115  0.060 -0.214 
 0.125 -0.025  0.025  0.174 -0.050 -0.075  0.025 -0.149 -0.100 -0.050 -0.125 -0.125  0.050 -0.100 -0.125 -0.100 -0.125 -0.075 -0.125  0.050  0.100 -0.100  0.025  0.050 -0.075 -0.050 -0.075 -0.100 -0.050 -0.125 -0.025 -0.125 -0.100 -0.100  0.000 -0.050 -0.025 -0.075 -0.075 -0.050 -0.050 -0.050 -0.100  0.075 -0.050 -0.025 -0.100 -0.100  0.000 -0.125 
 0.141 -0.033  0.041  0.191 -0.033 -0.058  0.041 -0.133 -0.108 -0.033 -0.108 -0.108  0.066 -0.083 -0.108 -0.108 -0.108 -0.058 -0.108  0.066  0.091 -0.083  0.016  0.041 -0.058 -0.033 -0.108 -0.108 -0.033 -0.108 -0.008 -0.108 -0.083 -0.083  0.016 -0.033 -0.008 -0.058 -0.058 -0.033 -0.033 -0.083 -0.083  0.091 -0.033 -0.008 -0.083 -0.083  0.016 -0.108 
 0.169 -0.005  0.020  0.194 -0.005 -0.030  0.070 -0.105 -0.105 -0.005 -0.080 -0.080  0.020 -0.080 -0.080 -0.080 -0.080 -0.030 -0.080  0.070  0.070 -0.080  0.020  0.045 -0.080 -0.005 -0.105 -0.105  0.020 -0.080  0.020 -0.080 -0.055 -0.055  0.020 -0.030 -0.005 -0.030 -0.030 -0.005 -0.030 -0.055 -0.030  0.120 -0.030  0.020 -0.055 -0.055 -0.005 -0.080 
 0.181  0.007  0.032  0.181  0.007 -0.043  0.032 -0.093 -0.093  0.007 -0.068 -0.068  0.032 -0.068 -0.068 -0.068 -0.068 -0.018 -0.068  0.082  0.082 -0.068  0.007  0.057 -0.068  0.007 -0.093 -0.093  0.007 -0.068  0.032 -0.068 -0.043 -0.043 -0.018 -0.018  0.007 -0.018 -0.018  0.007 -0.018 -0.043 -0.018  0.156 -0.018  0.032 -0.043 -0.043  0.007 -0.068 
 0.216 -0.058  0.016  0.116 -0.008 -0.033  0.016 -0.083 -0.083  0.041 -0.033 -0.058 -0.008 -0.058 -0.033 -0.058 -0.058 -0.008 -0.058  0.116  0.091 -0.058  0.016  0.066 -0.058  0.016 -0.083 -0.083 -0.008 -0.058  0.066 -0.058 -0.033 -0.033 -0.008 -0.008  0.016 -0.058 -0.033  0.016 -0.008 -0.033 -0.033  0.141 -0.008 -0.008 -0.033 -0.033  0.016 -0.058 
 0.220 -0.054  0.020  0.095 -0.004 -0.029 -0.004 -0.079 -0.079  0.020 -0.029 -0.054 -0.004 -0.054 -0.029 -0.054 -0.054 -0.004 -0.054  0.095  0.095 -0.054 -0.004  0.070 -0.054  0.020 -0.079 -0.079 -0.004 -0.054  0.070 -0.054 -0.029 -0.029 -0.004 -0.004  0.020 -0.054 -0.029 -0.004 -0.004 -0.029 -0.029  0.145 -0.004 -0.004 -0.029 -0.029  0.020 -0.054 
 0.203 -0.046  0.029  0.054 -0.046 -0.021  0.004 -0.071 -0.071  0.004 -0.021 -0.046  0.029 -0.046 -0.021 -0.046 -0.046 -0.021 -0.046  0.054  0.104 -0.046  0.004  0.054 -0.046  0.004 -0.071 -0.071 -0.021 -0.046  0.054 -0.046 -0.021 -0.021  0.004  0.004  0.029 -0.046 -0.046  0.004  0.004 -0.021 -0.046  0.153  0.004  0.004 -0.021 -0.021  0.029 -0.046 
 0.206 -0.043  0.032  0.032 -0.043 -0.018  0.007 -0.068 -0.068  0.007 -0.018 -0.043  0.032 -0.043 -0.018 -0.043 -0.043 -0.043 -0.043  0.057  0.057 -0.043  0.007  0.082 -0.043  0.007 -0.068 -0.068  0.007 -0.043  0.057 -0.043 -0.018  0.007 -0.018  0.007  0.032 -0.043 -0.068  0.007  0.007 -0.018 -0.043  0.156  0.007  0.007 -0.018 -0.018  0.032 -0.043 
 0.185 -0.039  0.010  0.035 -0.039 -0.014  0.010 -0.064 -0.064  0.010 -0.014 -0.039  0.010 -0.039 -0.014 -0.039 -0.039 -0.039 -0.039  0.035  0.060 -0.039  0.010  0.085 -0.039  0.010 -0.039 -0.064  0.010 -0.039  0.060 -0.039 -0.014  0.010 -0.014 -0.014  0.060 -0.039 -0.039 -0.014  0.010 -0.014 -0.039  0.160 -0.039  0.010 -0.014 -0.014 -0.014 -0.039 
 0.163 -0.011  0.013 -0.011 -0.036 -0.011  0.013 -0.061 -0.061  0.013 -0.011 -0.036  0.013 -0.036 -0.011 -0.036 -0.036 -0.036 -0.036  0.013  0.038 -0.036  0.013  0.088 -0.061  0.013 -0.036 -0.061  0.013 -0.036  0.038 -0.011 -0.036  0.013 -0.011 -0.036  0.063 -0.036 -0.036 -0.011  0.013 -0.011 -0.036  0.113 -0.036 -0.011 -0.011 -0.011 -0.036 -0.036 
 0.144 -0.005  0.019 -0.005 -0.030 -0.005  0.019 -0.055 -0.055 -0.005 -0.030 -0.030  0.019 -0.030 -0.005 -0.030 -0.030 -0.030 -0.030  0.019  0.019 -0.030  0.019  0.094 -0.055  0.019 -0.030 -0.055 -0.030 -0.055  0.019 -0.030 -0.030  0.019 -0.005 -0.030  0.044 -0.055 -0.005 -0.005 -0.030 -0.005 -0.030  0.094 -0.030 -0.005 -0.005 -0.005 -0.030 -0.005 
 0.121 -0.004 -0.029 -0.004 -0.029 -0.004  0.021 -0.054 -0.054 -0.004 -0.029 -0.029 -0.004 -0.029 -0.029 -0.029 -0.029 -0.004 -0.029  0.021  0.021 -0.004 -0.004  0.071 -0.054  0.021 -0.029 -0.054 -0.029 -0.054  0.021 -0.029 -0.029  0.021 -0.004 -0.029 -0.004 -0.054 -0.004 -0.004 -0.004 -0.004 -0.029  0.021 -0.004  0.021 -0.004 -0.029 -0.029 -0.004 
 0.120 -0.005 -0.030 -0.005 -0.030 -0.005  0.045 -0.055 -0.055 -0.005 -0.030 -0.030 -0.005 -0.030 -0.030 -0.030 -0.030 -0.005 -0.030  0.020  0.020  0.020 -0.005  0.070 -0.055  0.020 -0.030 -0.055 -0.030 -0.055  0.020 -0.030 -0.030  0.020 -0.005 -0.005 -0.005 -0.055 -0.005 -0.005 -0.005 -0.005 -0.030  0.020 -0.005  0.020 -0.005 -0.030 -0.030 -0.005 
 0.119 -0.005 -0.030 -0.005 -0.030 -0.005  0.044 -0.055 -0.055 -0.005 -0.030 -0.030 -0.005 -0.030 -0.030 -0.030 -0.030 -0.005 -0.030  0.019  0.019  0.019  0.019  0.069 -0.055  0.019 -0.030 -0.055 -0.030 -0.055  0.019 -0.030 -0.030  0.019 -0.005 -0.005 -0.005 -0.055 -0.005 -0.005 -0.005 -0.005 -0.030  0.019 -0.005  0.019 -0.005 -0.030 -0.030 -0.005 
 0.117 -0.007 -0.032 -0.007 -0.032 -0.007  0.042 -0.057 -0.057 -0.007 -0.032 -0.007 -0.007 -0.032 -0.032 -0.032 -0.007 -0.007 -0.032  0.017  0.017  0.017  0.017  0.067 -0.057  0.042 -0.032 -0.057 -0.007 -0.057  0.017 -0.032 -0.032  0.017 -0.007 -0.007 -0.007 -0.057 -0.007 -0.007 -0.007 -0.007 -0.032  0.017 -0.007  0.017 -0.007 -0.032 -0.032 -0.007 
 0.117 -0.007 -0.032 -0.007 -0.032 -0.007  0.042 -0.057 -0.057 -0.007 -0.032 -0.007 -0.007 -0.032 -0.032 -0.032 -0.007 -0.007 -0.032  0.017  0.017  0.017  0.017  0.067 -0.057  0.042 -0.032 -0.057 -0.007 -0.057  0.017 -0.032 -0.032  0.017 -0.007 -0.007 -0.007 -0.057 -0.007 -0.007 -0.007 -0.007 -0.032  0.017 -0.007  0.017 -0.007 -0.032 -0.032 -0.007 
 0.117 -0.007 -0.032 -0.007 -0.032 -0.007  0.042 -0.057 -0.057 -0.007 -0.032 -0.007 -0.007 -0.032 -0.032 -0.032 -0.007 -0.007 -0.032  0.017  0.017  0.017  0.017  0.067 -0.057  0.042 -0.032 -0.057 -0.007 -0.057  0.017 -0.032 -0.032  0.017 -0.007 -0.007 -0.007 -0.057 -0.007 -0.007 -0.007 -0.007 -0.032  0.017 -0.007  0.017 -0.007 -0.032 -0.032 -0.007 
 0.117 -0.007 -0.032 -0.007 -0.032 -0.007  0.042 -0.057 -0.057 -0.007 -0.032 -0.007 -0.007 -0.032 -0.032 -0.032 -0.007 -0.007 -0.032  0.017  0.017  0.017  0.017  0.067 -0.057  0.042 -0.032 -0.057 -0.007 -0.057  0.017 -0.032 -0.032  0.017 -0.007 -0.007 -0.007 -0.057 -0.007 -0.007 -0.007 -0.007 -0.032  0.017 -0.007  0.017 -0.007 -0.032 -0.032 -0.007 
 0.117 -0.007 -0.032 -0.007 -0.032 -0.007  0.042 -0.057 -0.057 -0.007 -0.032 -0.007 -0.007 -0.032 -0.032 -0.032 -0.007 -0.007 -0.032  0.017  0.017  0.017  0.017  0.067 -0.057  0.042 -0.032 -0.057 -0.007 -0.057  0.017 -0.032 -0.032  0.017 -0.007 -0.007 -0.007 -0.057 -0.007 -0.007 -0.007 -0.007 -0.032  0.017 -0.007  0.017 -0.007 -0.032 -0.032 -0.007 
 0.230 -0.019 -0.069  0.006 -0.044 -0.019  0.106 -0.069 -0.094 -0.019 -0.044 -0.044 -0.019  0.031 -0.069 -0.044 -0.044  0.006 -0.044 -0.019  0.006 -0.019  0.031  0.106 -0.069  0.056 -0.069 -0.094 -0.019 -0.094  0.031 -0.044 -0.069 -0.019 -0.044  0.056 -0.044 -0.069  0.006 -0.044  0.006  0.056 -0.044  0.006  0.006  0.031 -0.019 -0.069 -0.019 -0.044 
 0.285  0.011 -0.063  0.011 -0.063 -0.038  0.161 -0.138 -0.088  0.061 -0.063 -0.038 -0.038  0.061 -0.088 -0.013 -0.088  0.061 -0.063  0.011  0.086 -0.038  0.086  0.111 -0.138  0.036 -0.088 -0.163 -0.038 -0.163  0.036 -0.113 -0.088 -0.063 -0.063  0.136 -0.088 -0.138 -0.013 -0.063 -0.038  0.061 -0.088 -0.013  0.036  0.061 -0.063 -0.138 -0.088 -0.113 
 0.303  0.004 -0.020  0.054 -0.095 -0.045  0.179 -0.145 -0.045  0.054 -0.020 -0.070  0.029  0.079 -0.120 -0.045 -0.120  0.054 -0.095  0.004  0.104 -0.070  0.129  0.129 -0.170  0.054  0.004 -0.145 -0.020 -0.195  0.054 -0.145 -0.070 -0.120 -0.070  0.154 -0.095 -0.145 -0.045 -0.095  0.004  0.129 -0.070  0.004  0.079  0.029 -0.070 -0.145 -0.095 -0.145 
 0.251 -0.023  0.026  0.076 -0.048 -0.073  0.101 -0.198 -0.048  0.051 -0.073 -0.148  0.126  0.076 -0.173 -0.098 -0.173  0.051 -0.098  0.001  0.126 -0.098  0.276  0.151 -0.198  0.126  0.026 -0.148  0.076 -0.248  0.076 -0.198 -0.123 -0.173 -0.073  0.201 -0.073 -0.173 -0.123 -0.098 -0.048  0.126 -0.123  0.001  0.101  0.001 -0.073 -0.173 -0.048 -0.223 
 0.235 -0.064  0.060  0.085 -0.064 -0.064  0.060 -0.214 -0.064  0.060 -0.064 -0.164  0.160  0.060 -0.114 -0.114 -0.189  0.010 -0.064 -0.014  0.110 -0.039  0.260  0.160 -0.214  0.135  0.010 -0.139  0.085 -0.264  0.110 -0.214 -0.139 -0.189 -0.039  0.284 -0.039 -0.164 -0.139 -0.064 -0.039  0.085 -0.089  0.060  0.135 -0.039 -0.089 -0.189  0.035 -0.239 
 0.184 -0.090  0.009  0.134 -0.065 -0.090 -0.015 -0.265 -0.115  0.034 -0.115 -0.165  0.134  0.034 -0.140 -0.140 -0.190 -0.040 -0.090 -0.040  0.084 -0.065  0.284  0.109 -0.190  0.159 -0.015 -0.165  0.034 -0.265  0.184 -0.265 -0.165 -0.215  0.034  0.259 -0.040 -0.165 -0.140 -0.065 -0.115  0.034 -0.115  0.034  0.209 -0.065 -0.115 -0.215  0.059 -0.240 
 0.148 -0.101 -0.001  0.148 -0.076 -0.101 -0.026 -0.276 -0.101  0.023 -0.126 -0.176  0.123  0.023 -0.126 -0.151 -0.201 -0.051 -0.101 -0.051  0.123 -0.101  0.273  0.073 -0.176  0.148 -0.026 -0.176  0.023 -0.276  0.198 -0.276 -0.151 -0.251  0.023  0.248 -0.051 -0.126 -0.101 -0.076 -0.151  0.023 -0.076  0.073  0.173 -0.101 -0.126 -0.226  0.073 -0.251 
 0.144 -0.130 -0.005  0.169 -0.080 -0.130 -0.030 -0.280 -0.105 -0.055 -0.130 -0.155  0.119  0.019 -0.155 -0.155 -0.205 -0.055 -0.105 -0.055  0.169 -0.130  0.269  0.019 -0.180  0.144 -0.080 -0.180 -0.030 -0.280  0.119 -0.255 -0.155 -0.255 -0.005  0.244 -0.055 -0.130 -0.105 -0.105 -0.180 -0.030 -0.080  0.069  0.194 -0.130 -0.130 -0.230  0.094 -0.255 
 0.142 -0.132 -0.007  0.167 -0.082 -0.156 -0.032 -0.281 -0.107 -0.057 -0.132 -0.132  0.118 -0.007 -0.156 -0.156 -0.206 -0.057 -0.082 -0.057  0.167 -0.132  0.292  0.018 -0.181  0.142 -0.082 -0.181 -0.032 -0.281  0.118 -0.231 -0.156 -0.256 -0.007  0.242 -0.057 -0.132 -0.107 -0.132 -0.181 -0.032 -0.082  0.068  0.242 -0.132 -0.132 -0.206  0.093 -0.256 
 0.141 -0.133 -0.033  0.141 -0.083 -0.183 -0.033 -0.283 -0.033 -0.058 -0.133 -0.133  0.091 -0.008 -0.183 -0.158 -0.208 -0.083 -0.108 -0.058  0.191 -0.133  0.290  0.041 -0.183  0.191 -0.108 -0.183 -0.083 -0.283  0.066 -0.233 -0.133 -0.258 -0.033  0.241 -0.033 -0.133 -0.083 -0.133 -0.183 -0.058 -0.083  0.066  0.266 -0.133 -0.133 -0.183  0.116 -0.258 
 0.142 -0.133 -0.033  0.142 -0.083 -0.182 -0.008 -0.282 -0.033 -0.058 -0.133 -0.157  0.092 -0.008 -0.182 -0.133 -0.207 -0.083 -0.108 -0.058  0.216 -0.133  0.316  0.017 -0.182  0.191 -0.133 -0.182 -0.083 -0.282  0.042 -0.232 -0.108 -0.257 -0.033  0.266 -0.033 -0.133 -0.058 -0.133 -0.182 -0.083 -0.083  0.067  0.266 -0.133 -0.133 -0.182  0.092 -0.232 
 0.112 -0.137 -0.037  0.087 -0.112 -0.212 -0.012 -0.286 -0.062 -0.062 -0.162 -0.137  0.062 -0.012 -0.212 -0.137 -0.212 -0.062 -0.112 -0.062  0.286 -0.137  0.286 -0.012 -0.187  0.187 -0.137 -0.162 -0.112 -0.286  0.037 -0.237 -0.112 -0.262 -0.037  0.262 -0.037 -0.137 -0.062 -0.137 -0.187 -0.112 -0.112  0.062  0.286 -0.137 -0.062 -0.112  0.087 -0.187 
 0.132 -0.142 -0.017  0.082 -0.117 -0.217  0.007 -0.316 -0.042 -0.092 -0.167 -0.117  0.057 -0.017 -0.217 -0.142 -0.217 -0.067 -0.117 -0.067  0.282 -0.142  0.257 -0.017 -0.192  0.207 -0.142 -0.167 -0.117 -0.291  0.032 -0.217 -0.142 -0.267 -0.042  0.232 -0.042 -0.142 -0.067 -0.092 -0.192 -0.117 -0.117  0.057  0.282 -0.142 -0.067 -0.092  0.057 -0.192 
 0.131 -0.168  0.006  0.081 -0.119 -0.218  0.031 -0.318  0.031 -0.143 -0.143 -0.119  0.056 -0.019 -0.218 -0.143 -0.218 -0.069 -0.119 -0.044  0.280 -0.168  0.255 -0.019 -0.193  0.205 -0.143 -0.168 -0.119 -0.293  0.006 -0.218 -0.143 -0.268 -0.069  0.280 -0.069 -0.143 -0.069 -0.094 -0.193 -0.119 -0.119  0.056  0.280 -0.143 -0.069 -0.094  0.031 -0.193 
 0.155 -0.169  0.005  0.080 -0.119 -0.219  0.030 -0.318  0.055 -0.194 -0.144 -0.094  0.055 -0.019 -0.219 -0.144 -0.219 -0.119 -0.119 -0.044  0.280 -0.169  0.280  0.005 -0.194  0.230 -0.144 -0.169 -0.119 -0.293  0.005 -0.244 -0.119 -0.269 -0.069  0.304 -0.069 -0.144 -0.069 -0.094 -0.194 -0.119 -0.119  0.055  0.255 -0.119 -0.069 -0.094  0.030 -0.194 
 0.152 -0.171  0.003  0.078 -0.122 -0.221  0.053 -0.321  0.053 -0.196 -0.122 -0.097  0.053 -0.047 -0.221 -0.146 -0.221 -0.146 -0.122 -0.047  0.277 -0.171  0.277  0.003 -0.196  0.227 -0.146 -0.171 -0.122 -0.296  0.003 -0.246 -0.122 -0.246 -0.097  0.302 -0.072 -0.146 -0.072 -0.097 -0.196 -0.122 -0.122  0.053  0.252 -0.122 -0.072 -0.097  0.028 -0.196 
 0.128 -0.171  0.003  0.078 -0.122 -0.221  0.028 -0.321  0.028 -0.196 -0.122 -0.097  0.053 -0.047 -0.221 -0.146 -0.221 -0.146 -0.122 -0.047  0.252 -0.171  0.277  0.003 -0.196  0.227 -0.146 -0.171 -0.122 -0.296  0.003 -0.246 -0.122 -0.246 -0.122  0.302 -0.072 -0.146 -0.072 -0.097 -0.196 -0.122 -0.122  0.053  0.252 -0.122 -0.097 -0.097  0.028 -0.196 
 0.126 -0.173  0.001  0.076 -0.124 -0.223  0.026 -0.323  0.026 -0.198 -0.099 -0.099  0.051 -0.049 -0.223 -0.148 -0.198 -0.148 -0.148 -0.049  0.225 -0.173  0.275  0.001 -0.198  0.225 -0.148 -0.173 -0.124 -0.298  0.001 -0.248 -0.124 -0.248 -0.124  0.325 -0.074 -0.148 -0.074 -0.099 -0.198 -0.124 -0.124  0.051  0.225 -0.124 -0.074 -0.099  0.026 -0.223 
 0.125 -0.199  0.000  0.075 -0.125 -0.224  0.025 -0.324  0.025 -0.199 -0.100 -0.100  0.050 -0.050 -0.224 -0.149 -0.199 -0.149 -0.149 -0.050  0.224 -0.174  0.274  0.025 -0.199  0.224 -0.149 -0.174 -0.125 -0.299  0.025 -0.249 -0.125 -0.249 -0.125  0.324 -0.075 -0.149 -0.075 -0.100 -0.199 -0.125 -0.125  0.050  0.199 -0.125 -0.075 -0.100  0.025 -0.224 
 0.122 -0.202 -0.003  0.072 -0.128 -0.227  0.022 -0.327  0.022 -0.202 -0.078 -0.103  0.047 -0.053 -0.227 -0.152 -0.177 -0.152 -0.128 -0.053  0.271 -0.177  0.271  0.022 -0.202  0.221 -0.152 -0.177 -0.128 -0.302  0.047 -0.252 -0.128 -0.252 -0.128  0.321 -0.078 -0.152 -0.078 -0.103 -0.202 -0.128 -0.128  0.047  0.221 -0.128 -0.053 -0.103  0.022 -0.202 
 0.128 -0.121  0.053  0.103 -0.096 -0.146  0.078 -0.246  0.003 -0.171 -0.146 -0.221  0.028  0.003 -0.146 -0.121 -0.146 -0.096 -0.046  0.028  0.178 -0.146  0.203  0.003 -0.171  0.078 -0.096 -0.096 -0.071 -0.221  0.028 -0.196 -0.096 -0.196 -0.096  0.302 -0.021 -0.096 -0.021 -0.071 -0.146 -0.121 -0.096  0.053  0.178 -0.071 -0.121 -0.146  0.053 -0.146 
 0.149 -0.050  0.074  0.074 -0.075 -0.050  0.049 -0.150 -0.075 -0.075 -0.125 -0.125 -0.000 -0.000 -0.075 -0.100 -0.125 -0.000 -0.100  0.074  0.099 -0.075  0.124 -0.000 -0.125 -0.000 -0.100 -0.075 -0.000 -0.125  0.049 -0.125 -0.025 -0.100 -0.075  0.124  0.049 -0.075 -0.025 -0.075 -0.075 -0.050 -0.125  0.099  0.024 -0.000 -0.050 -0.100 -0.000 -0.125 
 0.174 -0.050  0.074  0.049 -0.075 -0.075  0.049 -0.125 -0.050 -0.050 -0.100 -0.100 -0.025 -0.000 -0.075 -0.075 -0.100  0.024 -0.100  0.099  0.099 -0.050  0.049  0.024 -0.100 -0.000 -0.075 -0.050 -0.000 -0.100  0.049 -0.100 -0.025 -0.075 -0.100  0.124  0.074 -0.050 -0.000 -0.050 -0.050 -0.050 -0.100  0.099 -0.000 -0.000 -0.050 -0.075 -0.000 -0.100 
 0.180 -0.019  0.006  0.056 -0.044 -0.069  0.056 -0.094 -0.069 -0.019 -0.069 -0.069 -0.019 -0.069 -0.069 -0.069 -0.069 -0.019 -0.069  0.155  0.106 -0.069  0.031  0.056 -0.069 -0.019 -0.094 -0.069 -0.019 -0.069 -0.044 -0.069 -0.044 -0.044 -0.069  0.031  0.056 -0.044  0.006 -0.044 -0.019 -0.044 -0.069  0.131 -0.019 -0.019 -0.044 -0.044  0.031 -0.069 
 0.189 -0.035  0.014  0.064 -0.035 -0.060  0.014 -0.085 -0.085 -0.010 -0.060 -0.060 -0.010 -0.060 -0.060 -0.060 -0.060 -0.010 -0.060  0.114  0.114 -0.060  0.014  0.064 -0.060 -0.010 -0.085 -0.060 -0.010 -0.060 -0.060 -0.060 -0.035 -0.035 -0.060  0.014  0.064 -0.035  0.014 -0.035 -0.010 -0.035 -0.060  0.139 -0.010 -0.010 -0.035 -0.035 -0.010 -0.060 
 0.198 -0.051  0.024  0.049 -0.026 -0.051 -0.001 -0.076 -0.076 -0.026 -0.051 -0.051 -0.001 -0.051 -0.051 -0.051 -0.051 -0.026 -0.051  0.074  0.074 -0.051 -0.001  0.074 -0.051 -0.026 -0.051 -0.076 -0.001 -0.051 -0.051 -0.051 -0.026 -0.026 -0.026  0.024  0.049 -0.026 -0.001 -0.026 -0.001 -0.026 -0.026  0.148 -0.026 -0.001 -0.026 -0.026 -0.001 -0.051 
 0.204 -0.045  0.030  0.055 -0.020 -0.045  0.005 -0.070 -0.070 -0.020 -0.045 -0.045 -0.020 -0.045 -0.045 -0.045 -0.045 -0.020 -0.045  0.055  0.055 -0.045  0.005  0.055 -0.045 -0.020 -0.045 -0.070  0.005 -0.045 -0.045 -0.045 -0.020 -0.020 -0.020  0.005  0.055 -0.045 -0.020 -0.020  0.005 -0.020 -0.020  0.154 -0.020  0.005 -0.020 -0.020  0.005 -0.045 
 0.210 -0.039  0.035  0.010 -0.039 -0.039  0.010 -0.064 -0.064 -0.014 -0.039 -0.039 -0.014 -0.039 -0.039 -0.039 -0.039 -0.039 -0.039  0.060  0.060 -0.039 -0.014  0.060 -0.064 -0.014 -0.039 -0.064 -0.014 -0.039 -0.014 -0.039 -0.014 -0.014 -0.014  0.010  0.060 -0.039 -0.014 -0.014  0.010 -0.014 -0.014  0.160 -0.014 -0.014 -0.014 -0.014  0.010 -0.014 
 0.140 -0.034  0.040 -0.009 -0.034 -0.059  0.015 -0.059 -0.059 -0.009 -0.034 -0.009 -0.009 -0.034 -0.034 -0.034 -0.034 -0.034 -0.034  0.065  0.090 -0.034 -0.009  0.065 -0.059 -0.009 -0.034 -0.059 -0.009 -0.034 -0.009 -0.059 -0.009 -0.009 -0.009  0.015  0.065 -0.034 -0.009 -0.034 -0.009 -0.009 -0.009  0.165 -0.009 -0.009 -0.009 -0.009  0.015 -0.009 
 0.119 -0.031  0.044 -0.006 -0.031 -0.031  0.019 -0.056 -0.056 -0.006 -0.031 -0.006 -0.006 -0.031 -0.006 -0.031 -0.031 -0.031 -0.031  0.044  0.094 -0.031  0.019  0.069 -0.056 -0.006 -0.031 -0.056 -0.006 -0.031  0.019 -0.056 -0.006 -0.006 -0.006 -0.006  0.069 -0.031 -0.006 -0.031 -0.031 -0.006 -0.031  0.143 -0.031 -0.006 -0.006 -0.006  0.019 -0.031 
 0.070 -0.030  0.020 -0.005 -0.030 -0.030  0.020 -0.055 -0.055 -0.005 -0.030 -0.005 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.030  0.045  0.095 -0.030  0.020  0.095 -0.055 -0.005 -0.030 -0.055 -0.005 -0.030  0.020 -0.055 -0.005  0.020 -0.005 -0.005  0.070 -0.030 -0.005 -0.030 -0.030 -0.005 -0.030  0.144 -0.030 -0.005 -0.005 -0.005  0.020 -0.030 
 0.069 -0.030  0.019 -0.005 -0.030 -0.030 -0.005 -0.055 -0.055 -0.005 -0.030 -0.005 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.030  0.044  0.094 -0.030  0.019  0.094 -0.055 -0.005 -0.030 -0.055 -0.030 -0.030  0.019 -0.055 -0.005  0.019 -0.005 -0.005  0.069 -0.030 -0.005 -0.030 -0.030 -0.005 -0.030  0.144 -0.030 -0.005 -0.005 -0.005  0.019 -0.030 
 0.069 -0.030  0.019 -0.005 -0.030 -0.030 -0.005 -0.055 -0.055 -0.005 -0.030 -0.005 -0.005 -0.030 -0.005 -0.030 -0.030 -0.030 -0.030  0.044  0.094 -0.030  0.019  0.094 -0.055 -0.005 -0.030 -0.055 -0.030 -0.030  0.019 -0.055 -0.005  0.019 -0.005 -0.005  0.069 -0.030 -0.005 -0.030 -0.030 -0.005 -0.030  0.144 -0.030 -0.005 -0.005 -0.005  0.019 -0.030 
 0.066 -0.009  0.016 -0.009 -0.034 -0.034 -0.009 -0.059 -0.059 -0.009 -0.034 -0.009 -0.009 -0.034 -0.009 -0.009 -0.009 -0.009 -0.034  0.066  0.091 -0.034  0.016  0.091 -0.059 -0.009 -0.034 -0.059 -0.034 -0.034  0.016 -0.059 -0.009  0.016 -0.009 -0.009  0.066 -0.034 -0.009 -0.034 -0.034 -0.009 -0.034  0.165 -0.034 -0.009 -0.009 -0.009  0.016 -0.034 
 0.065 -0.010  0.015 -0.010 -0.010 -0.035 -0.010 -0.060 -0.060 -0.010 -0.035 -0.010 -0.010 -0.035 -0.010 -0.010 -0.010 -0.010 -0.035  0.065  0.090 -0.035  0.015  0.090 -0.060 -0.010 -0.035 -0.060 -0.035 -0.035  0.015 -0.035 -0.010  0.015 -0.010 -0.010  0.065 -0.035 -0.010 -0.035 -0.035 -0.010 -0.035  0.164 -0.035 -0.010 -0.010 -0.010  0.015 -0.035 
 0.064 -0.010  0.014 -0.010 -0.010 -0.035  0.014 -0.060 -0.060 -0.010 -0.035 -0.010 -0.010 -0.035 -0.010 -0.010 -0.010  0.014 -0.035  0.039  0.089 -0.035  0.014  0.089 -0.060 -0.010 -0.035 -0.060 -0.035 -0.035  0.014 -0.035 -0.010  0.014 -0.010 -0.010  0.064 -0.035 -0.010 -0.035 -0.035 -0.010 -0.035  0.139 -0.010 -0.010 -0.010 -0.010  0.014 -0.035 
 0.064 -0.010  0.014 -0.010 -0.010 -0.035  0.014 -0.060 -0.060 -0.010 -0.035 -0.010 -0.010 -0.035 -0.010 -0.010 -0.010  0.014 -0.035  0.039  0.089 -0.035  0.014  0.089 -0.060 -0.010 -0.035 -0.060 -0.035 -0.035  0.014 -0.035 -0.010  0.014 -0.010 -0.010  0.064 -0.035 -0.010 -0.035 -0.035 -0.010 -0.035  0.139 -0.010 -0.010 -0.010 -0.010  0.014 -0.035 
 0.065 -0.010  0.015 -0.010 -0.010 -0.035  0.015 -0.060 -0.060 -0.010 -0.035 -0.010 -0.010 -0.035 -0.010 -0.035 -0.035 -0.010 -0.035  0.040  0.090 -0.035  0.015  0.090 -0.060 -0.010 -0.035 -0.060 -0.035 -0.035  0.015 -0.035 -0.010  0.015 -0.010 -0.010  0.065 -0.035 -0.010 -0.035 -0.035 -0.010 -0.035  0.140 -0.010 -0.010 -0.010 -0.010  0.015 -0.035 
 0.064 -0.010  0.014 -0.010 -0.010 -0.035  0.014 -0.060 -0.060 -0.010 -0.035 -0.010 -0.010 -0.035 -0.010 -0.010 -0.010  0.014 -0.035  0.039  0.089 -0.035  0.014  0.089 -0.060 -0.010 -0.035 -0.060 -0.035 -0.035  0.014 -0.035 -0.010  0.014 -0.010 -0.010  0.064 -0.035 -0.010 -0.035 -0.035 -0.010 -0.035  0.139 -0.010 -0.010 -0.010 -0.010  0.014 -0.035 
 0.064 -0.010  0.014 -0.010 -0.010 -0.035  0.014 -0.060 -0.060 -0.010 -0.035 -0.010 -0.010 -0.035 -0.010 -0.010 -0.010  0.014 -0.035  0.039  0.089 -0.035  0.014  0.089 -0.060 -0.010 -0.035 -0.060 -0.035 -0.035  0.014 -0.035 -0.010  0.014 -0.010 -0.010  0.064 -0.035 -0.010 -0.035 -0.035 -0.010 -0.035  0.139 -0.010 -0.010 -0.010 -0.010  0.014 -0.035 
 0.107 -0.042  0.032  0.007 -0.017 -0.042  0.082 -0.092 -0.067 -0.017 -0.042 -0.017 -0.017 -0.042 -0.042 -0.042 -0.042 -0.017 -0.017  0.132  0.107 -0.067  0.032  0.132 -0.067  0.007 -0.067 -0.092 -0.042 -0.067  0.032 -0.067 -0.017 -0.017 -0.042  0.007  0.057 -0.067  0.007 -0.042 -0.017 -0.017 -0.067  0.207 -0.017 -0.017 -0.017 -0.042  0.032 -0.067 
 0.161 -0.113  0.012  0.062 -0.038 -0.063  0.186 -0.138 -0.013 -0.063 -0.063 -0.038  0.012  0.012 -0.113 -0.088 -0.063  0.012 -0.088  0.161  0.087 -0.088 -0.013  0.186 -0.038  0.087 -0.113 -0.138 -0.063 -0.138  0.112 -0.138 -0.063 -0.088 -0.063  0.037  0.012 -0.063  0.012 -0.088  0.037 -0.038 -0.113  0.211 -0.038 -0.013 -0.063 -0.113  0.012 -0.088 
 0.166 -0.108  0.017  0.191 -0.033 -0.108  0.142 -0.182 -0.058 -0.058 -0.083 -0.033  0.042  0.042 -0.133 -0.108 -0.058 -0.008 -0.133  0.117  0.142 -0.133  0.042  0.166 -0.083  0.042 -0.033 -0.182 -0.083 -0.157  0.092 -0.182 -0.108 -0.133 -0.083  0.067  0.017 -0.083  0.067 -0.108 -0.008 -0.058 -0.058  0.241 -0.033 -0.033 -0.058 -0.157 -0.008 -0.108 
 0.237 -0.087  0.013  0.162 -0.062 -0.112  0.088 -0.236 -0.037 -0.087 -0.112 -0.037  0.063  0.063 -0.161 -0.112 -0.112 -0.012 -0.137  0.063  0.162 -0.062  0.038  0.162 -0.137  0.038 -0.062 -0.186 -0.112 -0.186  0.138 -0.211 -0.112 -0.186 -0.137  0.187 -0.012 -0.112  0.038 -0.112 -0.037 -0.087 -0.087  0.212 -0.012 -0.062 -0.087 -0.211 -0.012 -0.137 
 0.228 -0.096  0.029  0.178 -0.096 -0.121  0.079 -0.245 -0.046 -0.096 -0.121 -0.046  0.054  0.054 -0.170 -0.121 -0.121 -0.021 -0.121  0.029  0.129 -0.071  0.054  0.104 -0.145  0.004 -0.096 -0.145 -0.121 -0.195  0.104 -0.220 -0.121 -0.220 -0.145  0.228 -0.021 -0.096  0.029 -0.121 -0.071 -0.096 -0.096  0.203 -0.046 -0.071 -0.096 -0.195 -0.021 -0.145 
 0.212 -0.087  0.037  0.212 -0.112 -0.137  0.062 -0.262 -0.037 -0.137 -0.137 -0.012  0.012  0.012 -0.162 -0.112 -0.112 -0.087 -0.137  0.012  0.137 -0.112  0.062  0.062 -0.162  0.012 -0.087 -0.112 -0.112 -0.212  0.112 -0.212 -0.137 -0.212 -0.112  0.262 -0.012 -0.137  0.012 -0.137 -0.087 -0.137 -0.112  0.162 -0.112 -0.087 -0.062 -0.187  0.012 -0.137 
 0.179 -0.095  0.029  0.204 -0.120 -0.145  0.054 -0.270 -0.045 -0.170 -0.120 -0.020  0.004  0.004 -0.170 -0.095 -0.095 -0.095 -0.145  0.004  0.154 -0.145  0.054  0.054 -0.170  0.029 -0.070 -0.120 -0.120 -0.220  0.104 -0.220 -0.145 -0.220 -0.120  0.254 -0.020 -0.145  0.004 -0.145 -0.120 -0.145 -0.095  0.154 -0.120 -0.095 -0.045 -0.195  0.004 -0.145 
 0.171 -0.078  0.022  0.196 -0.152 -0.152  0.047 -0.277 -0.053 -0.177 -0.053 -0.028 -0.028 -0.003 -0.177 -0.128 -0.128 -0.128 -0.152 -0.003  0.146 -0.152  0.047  0.022 -0.177  0.047 -0.078 -0.103 -0.128 -0.227  0.097 -0.227 -0.152 -0.227 -0.128  0.271 -0.053 -0.177 -0.003 -0.152 -0.177 -0.177 -0.103  0.146 -0.128 -0.128 -0.003 -0.177  0.022 -0.177 
 0.149 -0.075  0.024  0.124 -0.175 -0.150  0.074 -0.299 -0.050 -0.175 -0.050 -0.025 -0.025 -0.000 -0.200 -0.150 -0.100 -0.125 -0.100 -0.000  0.149 -0.150  0.049  0.049 -0.150  0.049 -0.075 -0.125 -0.125 -0.250  0.049 -0.225 -0.150 -0.225 -0.125  0.274 -0.050 -0.150 -0.025 -0.150 -0.175 -0.175 -0.100  0.149 -0.150 -0.125 -0.000 -0.150 -0.000 -0.200 
 0.118 -0.082  0.018  0.118 -0.181 -0.156  0.068 -0.306 -0.057 -0.181 -0.032 -0.007 -0.032 -0.007 -0.206 -0.156 -0.082 -0.132 -0.107 -0.007  0.118 -0.156  0.018  0.068 -0.156  0.043 -0.082 -0.132 -0.156 -0.256  0.043 -0.231 -0.156 -0.231 -0.132  0.267 -0.057 -0.156 -0.007 -0.156 -0.181 -0.181 -0.107  0.142 -0.156 -0.132 -0.007 -0.132 -0.007 -0.206 
 0.117 -0.083  0.017  0.117 -0.182 -0.157  0.092 -0.307 -0.058 -0.182 -0.033  0.042 -0.033 -0.008 -0.207 -0.157 -0.108 -0.133 -0.108 -0.008  0.117 -0.157 -0.008  0.067 -0.157  0.017 -0.083 -0.108 -0.157 -0.257  0.042 -0.232 -0.157 -0.232 -0.133  0.266 -0.058 -0.157 -0.008 -0.157 -0.182 -0.182 -0.108  0.142 -0.157 -0.133 -0.033 -0.133 -0.008 -0.207 
 0.136 -0.089  0.011  0.111 -0.188 -0.163  0.086 -0.313 -0.039 -0.188 -0.039  0.036 -0.039  0.011 -0.213 -0.163 -0.089 -0.139 -0.114  0.036  0.160 -0.163  0.011  0.086 -0.114  0.061 -0.089 -0.114 -0.139 -0.288  0.036 -0.238 -0.163 -0.238 -0.139  0.260 -0.064 -0.163 -0.014 -0.139 -0.188 -0.188 -0.089  0.136 -0.163 -0.139 -0.039 -0.114 -0.014 -0.213 
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================================================
FILE: hippocampus/out/oscillation/baseline_params.txt
================================================
seed            = 97065491

T_sim           = 120
T_rec           = -2
update_type     = 1

N               = 2048
p               = 3
s               = 50
gamma           = 0.050000
beta            = 100.000000
field           = 0.000000

theta_type      = 2
theta_start     = 0.600000
theta_end       = 0.200000
T_theta         = 20
theta_file      = 
cycle_theta     = 0

X_dir           = out/pathways/N2048-p3-s512-a02-2
n_cue           = 30
incomp          = 0.000000
inacc           = 0.010000
record_type     = 0


================================================
FILE: hippocampus/out/oscillation/baseline_qcue.txt
================================================
2 9 11 15 16 20 25 48 49 54 57 60 78 82 85 86 87 88 92 100 104 107 111 112 119 120 142 145 146 147 

================================================
FILE: hippocampus/out/oscillation/baseline_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/oscillation/baseline_qnu.txt
================================================
18 25 41 44 54 66 69 78 93 96 97 100 116 124 158 167 170 183 194 197 210 237 252 284 289 291 304 327 328 335 343 351 363 375 384 390 391 394 422 442 445 447 450 454 460 465 475 482 491 499 

================================================
FILE: hippocampus/out/oscillation/baseline_theta.txt
================================================
0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.600000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 0.200000 

================================================
FILE: hippocampus/out/oscillation/baseline_wsample.txt
================================================
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================================================
FILE: hippocampus/out/pathways/AE.pt
================================================
[File too large to display: 17.0 MB]

================================================
FILE: hippocampus/out/pathways/FF.pt
================================================
[File too large to display: 48.1 MB]

================================================
FILE: hippocampus/out/sweep/bc-s001_a.txt
================================================
2.23e-01 3.36e-01 
2.18e-01 3.40e-01 
2.21e-01 2.19e-01 
2.25e-01 3.39e-01 
2.22e-01 3.35e-01 
2.25e-01 2.16e-01 
2.23e-01 3.39e-01 
2.22e-01 3.41e-01 
2.23e-01 2.41e-01 
2.24e-01 3.37e-01 
2.22e-01 3.40e-01 
2.21e-01 2.33e-01 
2.24e-01 3.38e-01 
2.19e-01 3.37e-01 
2.20e-01 2.17e-01 
2.20e-01 3.39e-01 
2.21e-01 3.40e-01 
2.22e-01 2.17e-01 
2.23e-01 3.41e-01 
2.20e-01 3.41e-01 
2.20e-01 2.16e-01 
2.24e-01 3.43e-01 
2.21e-01 3.39e-01 
2.21e-01 2.17e-01 
2.24e-01 3.46e-01 
2.21e-01 3.42e-01 
2.22e-01 2.17e-01 
2.23e-01 3.40e-01 
2.21e-01 3.39e-01 
2.22e-01 2.17e-01 


================================================
FILE: hippocampus/out/sweep/bc-s001_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bc-s001
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 1 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.90 s
Mean overlap 0.113 --> 0.117

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bc-s001_mclassic.txt
================================================
-0.007 -0.038 
 0.082  0.096 
 0.227  0.248 
-0.015 -0.045 
 0.089  0.088 
 0.244  0.245 
-0.001 -0.046 
 0.092  0.093 
 0.246  0.129 
-0.017 -0.046 
 0.095  0.087 
 0.242  0.065 
-0.008 -0.054 
 0.084  0.082 
 0.237  0.247 
-0.006 -0.046 
 0.087  0.093 
 0.232  0.245 
-0.013 -0.048 
 0.082  0.090 
 0.240  0.245 
-0.020 -0.044 
 0.084  0.085 
 0.248  0.244 
-0.020 -0.051 
 0.084  0.095 
 0.238  0.245 
-0.013 -0.040 
 0.090  0.095 
 0.235  0.245 


================================================
FILE: hippocampus/out/sweep/bc-s001_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/bc-s001_params.txt
================================================
seed             = 44729462

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 1
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bc-s001_qcue.txt
================================================
0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 

================================================
FILE: hippocampus/out/sweep/bc-s001_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bc-s001_qnu.txt
================================================
0 

================================================
FILE: hippocampus/out/sweep/bc-s001_wsample.txt
================================================
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-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 0.000000e+00 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 0.000000e+00 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 0.000000e+00 -1.595703e-06 
-4.238279e-07 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 2.603516e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 1.431641e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 4.458985e-06 2.565039e-05 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -3.451172e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.712305e-05 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -1.595703e-06 2.379492e-05 -1.595703e-06 -1.595703e-06 1.431641e-06 1.431641e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/bc-s003_a.txt
================================================
2.23e-01 2.55e-01 
2.21e-01 2.91e-01 
2.22e-01 4.13e-01 
2.21e-01 2.43e-01 
2.24e-01 2.92e-01 
2.23e-01 2.75e-01 
2.22e-01 3.67e-01 
2.18e-01 2.91e-01 
2.23e-01 2.51e-01 
2.21e-01 2.59e-01 
2.21e-01 2.90e-01 
2.19e-01 4.20e-01 
2.22e-01 7.41e-01 
2.21e-01 2.88e-01 
2.25e-01 6.95e-01 
2.19e-01 3.77e-01 
2.19e-01 2.91e-01 
2.20e-01 2.94e-01 
2.22e-01 2.54e-01 
2.22e-01 2.74e-01 
2.19e-01 4.26e-01 
2.26e-01 7.44e-01 
2.23e-01 2.94e-01 
2.23e-01 4.12e-01 
2.21e-01 3.61e-01 
2.23e-01 2.91e-01 
2.22e-01 2.91e-01 
2.23e-01 2.64e-01 
2.23e-01 2.89e-01 
2.24e-01 4.22e-01 


================================================
FILE: hippocampus/out/sweep/bc-s003_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bc-s003
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 3 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.92 s
Mean overlap 0.181 --> 0.113

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bc-s003_mclassic.txt
================================================
-0.016 -0.014 
 0.090  0.100 
 0.247  0.292 
 0.392  0.053 
 0.239  0.193 
 0.240  0.078 
 0.092 -0.037 
 0.234  0.198 
 0.173  0.015 
-0.010 -0.024 
 0.087  0.098 
 0.242  0.277 
 0.378  0.032 
 0.237  0.180 
 0.235 -0.011 
 0.086 -0.038 
 0.233  0.182 
 0.173  0.035 
-0.015 -0.003 
 0.086  0.099 
 0.242  0.286 
 0.380  0.053 
 0.234  0.176 
 0.244  0.264 
 0.090 -0.033 
 0.222  0.192 
 0.165  0.036 
-0.016 -0.034 
 0.100  0.093 
 0.239  0.266 


================================================
FILE: hippocampus/out/sweep/bc-s003_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/bc-s003_params.txt
================================================
seed             = 44769654

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 3
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bc-s003_qcue.txt
================================================
0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 

================================================
FILE: hippocampus/out/sweep/bc-s003_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bc-s003_qnu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bc-s003_wsample.txt
================================================
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-2.931641e-06 -2.931641e-06 7.517579e-06 7.792967e-07 2.634765e-06 5.662109e-06 3.806641e-06 2.634765e-06 3.806641e-06 4.490234e-06 4.490234e-06 1.951172e-06 7.792967e-07 2.634765e-06 7.792967e-07 2.634765e-06 7.792967e-07 7.792967e-07 7.792967e-07 7.792967e-07 -1.076172e-06 4.490234e-06 -1.076172e-06 4.490234e-06 4.490234e-06 3.806641e-06 7.792967e-07 2.634765e-06 -1.406445e-05 2.634765e-06 2.634765e-06 7.517579e-06 -1.591992e-05 2.634765e-06 2.919727e-05 4.490234e-06 -1.777539e-05 4.490234e-06 7.792967e-07 2.634765e-06 2.634765e-06 3.806641e-06 -1.076172e-06 2.634765e-06 7.792967e-07 -1.076172e-06 2.634765e-06 2.634765e-06 2.634765e-06 2.634765e-06 1.951172e-06 2.634765e-06 7.792967e-07 2.634765e-06 2.634765e-06 -4.787110e-06 -1.591992e-05 4.490234e-06 7.517579e-06 7.792967e-07 2.634765e-06 -1.963086e-05 2.634765e-06 2.634765e-06 1.951172e-06 2.616992e-05 4.490234e-06 2.634765e-06 -1.591992e-05 4.490234e-06 -1.076172e-06 -1.406445e-05 -1.474805e-05 4.490234e-06 2.634765e-06 7.517579e-06 -2.931641e-06 7.517579e-06 4.490234e-06 2.634765e-06 4.490234e-06 5.662109e-06 -3.615235e-06 9.570294e-08 2.634765e-06 -2.773633e-05 -1.220898e-05 2.634765e-06 2.634765e-06 1.951172e-06 -1.963086e-05 4.490234e-06 -1.076172e-06 5.662109e-06 7.792967e-07 2.634765e-06 -1.076172e-06 2.634765e-06 0.000000e+00 1.951172e-06 
-3.615234e-06 1.267578e-06 1.951172e-06 9.570317e-08 1.951172e-06 4.978516e-06 3.123047e-06 -2.931641e-06 3.123047e-06 -1.076172e-06 -1.076172e-06 1.267578e-06 4.978516e-06 -2.931641e-06 -4.787110e-06 1.951172e-06 -4.787110e-06 -4.787110e-06 9.570317e-08 -4.787110e-06 3.123047e-06 -1.076172e-06 -1.759766e-06 -1.076172e-06 -1.076172e-06 8.005860e-06 -4.787110e-06 -2.931641e-06 -1.474805e-05 1.951172e-06 -2.931641e-06 1.951172e-06 2.734180e-05 -2.931641e-06 2.851367e-05 -1.076172e-06 -1.845898e-05 -1.076172e-06 -4.787110e-06 -2.931641e-06 -2.931641e-06 3.123047e-06 3.123047e-06 -2.931641e-06 -4.787110e-06 3.123047e-06 -2.931641e-06 -2.931641e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 -2.931641e-06 4.978516e-06 -2.931641e-06 -2.931641e-06 -5.878903e-07 2.245899e-05 -1.076172e-06 1.951172e-06 4.978516e-06 -2.931641e-06 -2.031445e-05 -2.931641e-06 -2.931641e-06 6.150391e-06 2.548633e-05 -1.076172e-06 -2.931641e-06 -1.660352e-05 -1.076172e-06 -1.759766e-06 -1.963086e-05 -1.543164e-05 -1.076172e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 1.951172e-06 -1.076172e-06 1.951172e-06 -1.076172e-06 9.570317e-08 -4.298828e-06 -5.878904e-07 -2.931641e-06 1.064258e-05 -1.777539e-05 1.951172e-06 1.951172e-06 1.267578e-06 -1.543164e-05 -1.076172e-06 -1.759766e-06 4.978516e-06 -4.787110e-06 -2.931641e-06 -1.759766e-06 -2.931641e-06 1.951172e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/bc-s010_a.txt
================================================
2.20e-01 3.23e-01 
2.23e-01 3.42e-01 
2.20e-01 3.49e-01 
2.23e-01 3.10e-01 
2.23e-01 3.31e-01 
2.22e-01 3.49e-01 
2.18e-01 3.15e-01 
2.19e-01 4.97e-01 
2.19e-01 3.37e-01 
2.25e-01 3.40e-01 
2.21e-01 3.39e-01 
2.20e-01 3.26e-01 
2.25e-01 2.99e-01 
2.22e-01 3.77e-01 
2.18e-01 3.41e-01 
2.24e-01 3.32e-01 
2.24e-01 3.32e-01 
2.20e-01 3.55e-01 
2.23e-01 3.46e-01 
2.23e-01 3.47e-01 
2.21e-01 3.34e-01 
2.23e-01 3.29e-01 
2.21e-01 3.15e-01 
2.21e-01 3.26e-01 
2.22e-01 3.31e-01 
2.19e-01 3.50e-01 
2.16e-01 3.57e-01 
2.18e-01 3.55e-01 
2.24e-01 3.34e-01 
2.19e-01 3.48e-01 


================================================
FILE: hippocampus/out/sweep/bc-s010_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bc-s010
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 10 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.91 s
Mean overlap 0.182 --> 0.140

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bc-s010_mclassic.txt
================================================
-0.009  0.024 
 0.088 -0.049 
 0.237  0.198 
 0.368  0.126 
 0.237  0.108 
 0.233  0.180 
 0.099  0.063 
 0.218  0.255 
 0.165  0.107 
 0.027  0.066 
 0.170  0.003 
 0.222  0.170 
 0.060  0.078 
 0.217  0.273 
 0.213  0.181 
 0.071  0.110 
 0.251  0.192 
 0.177  0.148 
 0.213  0.093 
 0.115  0.158 
 0.234  0.211 
 0.164  0.126 
 0.258  0.158 
 0.154  0.148 
 0.284  0.069 
 0.263  0.212 
 0.225  0.201 
-0.026  0.038 
 0.242  0.198 
 0.212  0.251 


================================================
FILE: hippocampus/out/sweep/bc-s010_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/bc-s010_params.txt
================================================
seed             = 44781398

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 10
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bc-s010_qcue.txt
================================================
0 10 20 1 11 21 2 12 22 3 13 23 4 14 24 5 15 25 6 16 26 7 17 27 8 18 28 9 19 29 

================================================
FILE: hippocampus/out/sweep/bc-s010_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bc-s010_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 

================================================
FILE: hippocampus/out/sweep/bc-s010_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/bc-s030_a.txt
================================================
2.25e-01 5.23e-01 
2.22e-01 5.35e-01 
2.22e-01 4.62e-01 
2.23e-01 4.21e-01 
2.22e-01 5.20e-01 
2.23e-01 4.33e-01 
2.21e-01 5.46e-01 
2.20e-01 5.15e-01 
2.21e-01 4.56e-01 
2.25e-01 5.45e-01 
2.19e-01 4.50e-01 
2.23e-01 4.52e-01 
2.23e-01 4.80e-01 
2.20e-01 4.41e-01 
2.19e-01 4.29e-01 
2.22e-01 4.73e-01 
2.21e-01 4.56e-01 
2.22e-01 4.22e-01 
2.22e-01 4.34e-01 
2.21e-01 5.35e-01 
2.23e-01 4.50e-01 
2.22e-01 4.29e-01 
2.22e-01 4.70e-01 
2.25e-01 4.17e-01 
2.25e-01 4.20e-01 
2.23e-01 5.05e-01 
2.20e-01 4.57e-01 
2.22e-01 5.19e-01 
2.24e-01 5.38e-01 
2.25e-01 4.48e-01 


================================================
FILE: hippocampus/out/sweep/bc-s030_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bc-s030
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 30 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.92 s
Mean overlap 0.182 --> 0.237

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bc-s030_mclassic.txt
================================================
-0.009 -0.206 
 0.080  0.100 
 0.247  0.307 
 0.386  0.276 
 0.239  0.211 
 0.234  0.265 
 0.090 -0.140 
 0.223  0.238 
 0.166  0.315 
 0.031 -0.291 
 0.166  0.185 
 0.231  0.332 
 0.069  0.078 
 0.210  0.227 
 0.218  0.199 
 0.071  0.193 
 0.246  0.281 
 0.178  0.223 
 0.214  0.251 
 0.106  0.103 
 0.216  0.331 
 0.159  0.278 
 0.262  0.264 
 0.156  0.308 
 0.259  0.333 
 0.264  0.233 
 0.238  0.320 
-0.015 -0.224 
 0.251  0.125 
 0.226  0.264 


================================================
FILE: hippocampus/out/sweep/bc-s030_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/bc-s030_params.txt
================================================
seed             = 44925462

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 30
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bc-s030_qcue.txt
================================================
0 30 60 1 31 61 2 32 62 3 33 63 4 34 64 5 35 65 6 36 66 7 37 67 8 38 68 9 39 69 

================================================
FILE: hippocampus/out/sweep/bc-s030_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bc-s030_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 

================================================
FILE: hippocampus/out/sweep/bc-s030_wsample.txt
================================================
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-1.769531e-05 2.195312e-05 1.130860e-05 3.347656e-05 -1.046874e-05 9.941414e-06 4.949220e-05 -5.666017e-05 -9.296866e-06 -7.570315e-05 -1.691406e-05 1.542976e-06 3.787109e-05 -1.134765e-05 -3.810548e-05 7.597664e-06 1.257812e-05 -1.466797e-05 -6.074212e-06 -1.271483e-05 -2.167963e-06 -1.164062e-05 1.560547e-05 -2.628906e-05 -1.271486e-05 -4.552735e-05 -4.416014e-05 1.482423e-05 -1.720702e-05 -2.833983e-05 -6.291016e-05 1.072267e-05 -4.201171e-05 2.302735e-05 2.283203e-05 -3.185546e-05 -5.158204e-05 -1.330078e-05 -3.458983e-05 -4.826173e-05 7.597657e-06 3.175585e-04 -2.443358e-05 -2.375000e-05 -9.589843e-06 -3.925779e-06 3.064453e-05 6.328126e-06 -5.060546e-05 -6.339845e-05 7.742186e-05 5.652344e-05 3.591795e-05 1.023438e-05 3.738282e-05 -3.742187e-05 -3.205077e-05 -3.124967e-07 6.160157e-05 -3.371094e-05 4.783202e-05 2.078126e-05 2.507813e-05 1.267579e-05 3.477343e-04 -4.923827e-05 -2.248049e-05 -3.339845e-06 -1.466796e-05 -9.960941e-07 -9.785151e-06 -4.757813e-05 -5.382812e-05 3.308594e-05 4.177734e-05 1.335938e-05 6.707032e-05 -3.878905e-05 1.082032e-05 -1.828128e-05 1.941407e-05 1.082031e-05 -2.462890e-05 -1.837891e-05 -5.714844e-05 -4.855467e-05 -2.833983e-05 2.156250e-05 -9.492202e-06 -3.576173e-05 2.742188e-05 1.013672e-05 -3.136718e-05 -1.701171e-05 1.542974e-06 -3.124933e-07 1.179688e-05 0.000000e+00 -1.906250e-05 5.546881e-06 
4.001953e-05 5.037109e-05 -9.101560e-06 5.212891e-05 -4.552734e-05 4.324217e-05 4.667971e-06 8.406250e-05 -3.947265e-05 -2.775391e-05 -3.244141e-05 -4.218747e-06 -2.160156e-05 -6.105469e-05 -4.875001e-05 -3.046873e-06 -6.154297e-05 8.867190e-06 2.234375e-05 -6.730467e-05 2.625000e-05 -4.669921e-05 1.960937e-05 -3.693360e-05 -8.710929e-06 5.613281e-05 5.750001e-05 -1.046875e-05 -1.808593e-05 -4.874999e-05 -6.378906e-05 4.402343e-05 -7.707031e-05 -4.621093e-05 -7.343753e-06 -4.249999e-05 -3.632817e-06 -2.882812e-05 -2.570311e-05 3.951952e-04 -1.769531e-05 -8.371093e-05 -5.781241e-06 1.443360e-05 -5.585935e-06 -3.410155e-05 1.511718e-05 5.449216e-06 -6.613281e-05 8.964840e-06 -3.576173e-05 -1.759765e-05 2.039063e-05 3.865235e-05 3.650391e-05 -1.876952e-05 -5.246094e-05 -2.072265e-05 -3.693359e-05 -3.458983e-05 3.230469e-05 -4.357424e-05 1.931639e-05 2.031256e-06 3.273241e-04 7.683594e-05 3.965624e-04 -9.101559e-06 -2.531250e-05 3.007817e-06 8.867190e-06 2.478515e-05 4.783204e-05 4.685546e-05 -1.281249e-05 1.248048e-05 1.248046e-05 2.869139e-05 -9.589843e-06 3.568163e-04 -5.878901e-06 1.757835e-07 1.843751e-05 1.003907e-05 -2.384765e-05 4.277363e-06 9.843763e-06 1.152352e-06 -6.054652e-07 -1.222658e-05 7.011724e-06 -1.515625e-05 4.587891e-05 3.093749e-05 -4.218749e-06 -1.583984e-05 3.044922e-05 -1.906250e-05 0.000000e+00 -2.148413e-07 
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================================================
FILE: hippocampus/out/sweep/bc-s100_a.txt
================================================
2.23e-01 5.43e-01 
2.23e-01 5.33e-01 
2.19e-01 5.27e-01 
2.21e-01 4.13e-01 
2.25e-01 4.78e-01 
2.24e-01 5.30e-01 
2.20e-01 4.18e-01 
2.17e-01 4.70e-01 
2.22e-01 5.31e-01 
2.22e-01 5.46e-01 
2.14e-01 4.28e-01 
2.21e-01 5.31e-01 
2.21e-01 4.23e-01 
2.23e-01 4.29e-01 
2.22e-01 4.15e-01 
2.17e-01 4.25e-01 
2.22e-01 4.34e-01 
2.22e-01 4.71e-01 
2.25e-01 4.09e-01 
2.22e-01 5.34e-01 
2.25e-01 5.24e-01 
2.21e-01 4.10e-01 
2.24e-01 4.68e-01 
2.23e-01 5.33e-01 
2.20e-01 4.17e-01 
2.21e-01 4.80e-01 
2.22e-01 5.34e-01 
2.20e-01 5.24e-01 
2.24e-01 4.75e-01 
2.21e-01 4.26e-01 


================================================
FILE: hippocampus/out/sweep/bc-s100_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bc-s100
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 100 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.77 s
Mean overlap 0.184 --> 0.314

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bc-s100_mclassic.txt
================================================
-0.007 -0.490 
 0.091  0.079 
 0.236  0.235 
 0.377  0.512 
 0.238  0.382 
 0.233  0.237 
 0.088  0.505 
 0.233  0.356 
 0.183  0.224 
 0.043 -0.490 
 0.172  0.167 
 0.230  0.219 
 0.081  0.475 
 0.228  0.172 
 0.205 -0.002 
 0.077  0.473 
 0.254  0.181 
 0.187  0.333 
 0.220  0.502 
 0.101  0.077 
 0.223  0.245 
 0.151  0.513 
 0.257  0.361 
 0.179  0.215 
 0.256  0.505 
 0.264  0.374 
 0.229  0.223 
-0.019 -0.402 
 0.251  0.377 
 0.215  0.087 


================================================
FILE: hippocampus/out/sweep/bc-s100_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/bc-s100_params.txt
================================================
seed             = 44710710

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 100
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bc-s100_qcue.txt
================================================
0 100 200 1 101 201 2 102 202 3 103 203 4 104 204 5 105 205 6 106 206 7 107 207 8 108 208 9 109 209 

================================================
FILE: hippocampus/out/sweep/bc-s100_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bc-s100_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 

================================================
FILE: hippocampus/out/sweep/bc-s100_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/bs-s001_a.txt
================================================
2.21e-01 2.00e-02 
2.25e-01 2.00e-02 
2.18e-01 2.00e-02 
2.20e-01 2.00e-02 
2.21e-01 2.00e-02 
2.23e-01 2.00e-02 
2.24e-01 2.00e-02 
2.25e-01 2.00e-02 
2.23e-01 2.00e-02 
2.23e-01 2.00e-02 
2.23e-01 2.00e-02 
2.20e-01 2.00e-02 
2.23e-01 2.00e-02 
2.22e-01 2.00e-02 
2.23e-01 2.00e-02 
2.22e-01 2.00e-02 
2.24e-01 2.00e-02 
2.22e-01 2.00e-02 
2.22e-01 2.00e-02 
2.24e-01 2.00e-02 
2.21e-01 2.00e-02 
2.19e-01 2.00e-02 
2.23e-01 2.00e-02 
2.23e-01 2.00e-02 
2.23e-01 2.00e-02 
2.21e-01 2.00e-02 
2.24e-01 2.00e-02 
2.20e-01 2.00e-02 
2.22e-01 2.00e-02 
2.21e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/bs-s001_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bs-s001
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 1 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.94 s
Mean overlap 0.788 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bs-s001_mclassic.txt
================================================
 0.796  1.001 
 0.792  1.001 
 0.774  1.001 
 0.797  1.001 
 0.796  1.001 
 0.794  1.001 
 0.793  1.001 
 0.792  1.001 
 0.794  1.001 
 0.794  1.001 
 0.794  1.001 
 0.797  1.001 
 0.769  1.001 
 0.745  1.001 
 0.794  1.001 
 0.795  1.001 
 0.793  1.001 
 0.795  1.001 
 0.795  1.001 
 0.793  1.001 
 0.796  1.001 
 0.773  1.001 
 0.769  1.001 
 0.794  1.001 
 0.794  1.001 
 0.771  1.001 
 0.793  1.001 
 0.797  1.001 
 0.770  1.001 
 0.796  1.001 


================================================
FILE: hippocampus/out/sweep/bs-s001_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/bs-s001_params.txt
================================================
seed             = 45341814

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 1
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bs-s001_qcue.txt
================================================
0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 

================================================
FILE: hippocampus/out/sweep/bs-s001_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bs-s001_qnu.txt
================================================
0 

================================================
FILE: hippocampus/out/sweep/bs-s001_wsample.txt
================================================
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-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 0.000000e+00 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 0.000000e+00 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 0.000000e+00 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 0.000000e+00 -1.595703e-06 
-4.238279e-07 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 2.603516e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 1.431641e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 4.458985e-06 2.565039e-05 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -3.451172e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.712305e-05 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -1.595703e-06 2.379492e-05 -1.595703e-06 -1.595703e-06 1.431641e-06 1.431641e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/bs-s003_a.txt
================================================
2.22e-01 2.00e-02 
2.24e-01 2.00e-02 
2.24e-01 2.00e-02 
2.19e-01 2.00e-02 
2.21e-01 2.00e-02 
2.24e-01 2.00e-02 
2.20e-01 2.00e-02 
2.19e-01 2.00e-02 
2.19e-01 2.00e-02 
2.23e-01 2.00e-02 
2.24e-01 2.00e-02 
2.22e-01 2.00e-02 
2.24e-01 2.00e-02 
2.23e-01 2.00e-02 
2.21e-01 2.00e-02 
2.18e-01 2.00e-02 
2.19e-01 2.00e-02 
2.18e-01 2.00e-02 
2.22e-01 2.00e-02 
2.19e-01 2.00e-02 
2.23e-01 2.00e-02 
2.20e-01 2.00e-02 
2.20e-01 2.00e-02 
2.22e-01 2.00e-02 
2.21e-01 2.00e-02 
2.20e-01 2.00e-02 
2.19e-01 2.00e-02 
2.25e-01 2.00e-02 
2.24e-01 2.00e-02 
2.24e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/bs-s003_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bs-s003
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 3 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.94 s
Mean overlap 0.784 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bs-s003_mclassic.txt
================================================
 0.795  1.001 
 0.768  1.001 
 0.793  1.001 
 0.798  1.001 
 0.796  1.001 
 0.793  1.001 
 0.747  1.001 
 0.773  1.001 
 0.798  1.001 
 0.794  1.001 
 0.793  1.001 
 0.795  1.001 
 0.768  1.001 
 0.794  1.001 
 0.746  1.001 
 0.799  1.001 
 0.798  1.001 
 0.799  1.001 
 0.795  1.001 
 0.773  1.001 
 0.794  1.001 
 0.772  1.001 
 0.797  1.001 
 0.795  1.001 
 0.771  1.001 
 0.747  1.001 
 0.798  1.001 
 0.792  1.001 
 0.793  1.001 
 0.743  1.001 


================================================
FILE: hippocampus/out/sweep/bs-s003_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/bs-s003_params.txt
================================================
seed             = 45382006

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 3
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bs-s003_qcue.txt
================================================
0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 

================================================
FILE: hippocampus/out/sweep/bs-s003_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bs-s003_qnu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bs-s003_wsample.txt
================================================
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-2.931641e-06 -2.931641e-06 7.517579e-06 7.792967e-07 2.634765e-06 5.662109e-06 3.806641e-06 2.634765e-06 3.806641e-06 4.490234e-06 4.490234e-06 1.951172e-06 7.792967e-07 2.634765e-06 7.792967e-07 2.634765e-06 7.792967e-07 7.792967e-07 7.792967e-07 7.792967e-07 -1.076172e-06 4.490234e-06 -1.076172e-06 4.490234e-06 4.490234e-06 3.806641e-06 7.792967e-07 2.634765e-06 -1.406445e-05 2.634765e-06 2.634765e-06 7.517579e-06 -1.591992e-05 2.634765e-06 2.919727e-05 4.490234e-06 -1.777539e-05 4.490234e-06 7.792967e-07 2.634765e-06 2.634765e-06 3.806641e-06 -1.076172e-06 2.634765e-06 7.792967e-07 -1.076172e-06 2.634765e-06 2.634765e-06 2.634765e-06 2.634765e-06 1.951172e-06 2.634765e-06 7.792967e-07 2.634765e-06 2.634765e-06 -4.787110e-06 -1.591992e-05 4.490234e-06 7.517579e-06 7.792967e-07 2.634765e-06 -1.963086e-05 2.634765e-06 2.634765e-06 1.951172e-06 2.616992e-05 4.490234e-06 2.634765e-06 -1.591992e-05 4.490234e-06 -1.076172e-06 -1.406445e-05 -1.474805e-05 4.490234e-06 2.634765e-06 7.517579e-06 -2.931641e-06 7.517579e-06 4.490234e-06 2.634765e-06 4.490234e-06 5.662109e-06 -3.615235e-06 9.570294e-08 2.634765e-06 -2.773633e-05 -1.220898e-05 2.634765e-06 2.634765e-06 1.951172e-06 -1.963086e-05 4.490234e-06 -1.076172e-06 5.662109e-06 7.792967e-07 2.634765e-06 -1.076172e-06 2.634765e-06 0.000000e+00 1.951172e-06 
-3.615234e-06 1.267578e-06 1.951172e-06 9.570317e-08 1.951172e-06 4.978516e-06 3.123047e-06 -2.931641e-06 3.123047e-06 -1.076172e-06 -1.076172e-06 1.267578e-06 4.978516e-06 -2.931641e-06 -4.787110e-06 1.951172e-06 -4.787110e-06 -4.787110e-06 9.570317e-08 -4.787110e-06 3.123047e-06 -1.076172e-06 -1.759766e-06 -1.076172e-06 -1.076172e-06 8.005860e-06 -4.787110e-06 -2.931641e-06 -1.474805e-05 1.951172e-06 -2.931641e-06 1.951172e-06 2.734180e-05 -2.931641e-06 2.851367e-05 -1.076172e-06 -1.845898e-05 -1.076172e-06 -4.787110e-06 -2.931641e-06 -2.931641e-06 3.123047e-06 3.123047e-06 -2.931641e-06 -4.787110e-06 3.123047e-06 -2.931641e-06 -2.931641e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 -2.931641e-06 4.978516e-06 -2.931641e-06 -2.931641e-06 -5.878903e-07 2.245899e-05 -1.076172e-06 1.951172e-06 4.978516e-06 -2.931641e-06 -2.031445e-05 -2.931641e-06 -2.931641e-06 6.150391e-06 2.548633e-05 -1.076172e-06 -2.931641e-06 -1.660352e-05 -1.076172e-06 -1.759766e-06 -1.963086e-05 -1.543164e-05 -1.076172e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 1.951172e-06 -1.076172e-06 1.951172e-06 -1.076172e-06 9.570317e-08 -4.298828e-06 -5.878904e-07 -2.931641e-06 1.064258e-05 -1.777539e-05 1.951172e-06 1.951172e-06 1.267578e-06 -1.543164e-05 -1.076172e-06 -1.759766e-06 4.978516e-06 -4.787110e-06 -2.931641e-06 -1.759766e-06 -2.931641e-06 1.951172e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/bs-s010_a.txt
================================================
2.22e-01 2.00e-02 
2.20e-01 2.00e-02 
2.26e-01 2.00e-02 
2.22e-01 2.00e-02 
2.22e-01 2.00e-02 
2.19e-01 2.00e-02 
2.21e-01 2.00e-02 
2.21e-01 3.71e-02 
2.19e-01 2.00e-02 
2.22e-01 2.00e-02 
2.20e-01 2.00e-02 
2.24e-01 2.00e-02 
2.21e-01 2.00e-02 
2.24e-01 2.00e-02 
2.21e-01 2.00e-02 
2.22e-01 2.00e-02 
2.21e-01 2.00e-02 
2.23e-01 2.00e-02 
2.19e-01 2.00e-02 
2.19e-01 2.00e-02 
2.21e-01 2.00e-02 
2.21e-01 2.00e-02 
2.24e-01 2.00e-02 
2.25e-01 2.00e-02 
2.21e-01 2.00e-02 
2.20e-01 2.00e-02 
2.20e-01 2.00e-02 
2.20e-01 2.00e-02 
2.22e-01 2.00e-02 
2.23e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/bs-s010_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bs-s010
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 10 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.91 s
Mean overlap 0.791 --> 1.000

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bs-s010_mclassic.txt
================================================
 0.795  1.001 
 0.797  1.001 
 0.791  1.001 
 0.795  1.001 
 0.795  1.001 
 0.773  1.001 
 0.796  1.001 
 0.796  0.984 
 0.798  1.001 
 0.770  1.001 
 0.772  1.001 
 0.793  1.001 
 0.796  1.001 
 0.793  1.001 
 0.796  1.001 
 0.795  1.001 
 0.771  1.001 
 0.794  1.001 
 0.773  1.001 
 0.798  1.001 
 0.796  1.001 
 0.796  1.001 
 0.793  1.001 
 0.767  1.001 
 0.796  1.001 
 0.797  1.001 
 0.797  1.001 
 0.797  1.001 
 0.795  1.001 
 0.794  1.001 


================================================
FILE: hippocampus/out/sweep/bs-s010_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.146 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/bs-s010_params.txt
================================================
seed             = 45393750

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 10
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bs-s010_qcue.txt
================================================
0 10 20 1 11 21 2 12 22 3 13 23 4 14 24 5 15 25 6 16 26 7 17 27 8 18 28 9 19 29 

================================================
FILE: hippocampus/out/sweep/bs-s010_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bs-s010_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 

================================================
FILE: hippocampus/out/sweep/bs-s010_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/bs-s030_a.txt
================================================
2.24e-01 2.00e-02 
2.24e-01 2.00e-02 
2.23e-01 2.00e-02 
2.21e-01 2.00e-02 
2.21e-01 2.00e-02 
2.26e-01 2.00e-02 
2.20e-01 2.00e-02 
2.19e-01 2.00e-02 
2.21e-01 2.00e-02 
2.21e-01 2.00e-02 
2.15e-01 2.00e-02 
2.23e-01 2.00e-02 
2.21e-01 2.00e-02 
2.22e-01 2.00e-02 
2.20e-01 2.00e-02 
2.22e-01 2.00e-02 
2.22e-01 3.71e-02 
2.24e-01 3.86e-02 
2.21e-01 2.00e-02 
2.21e-01 2.00e-02 
2.22e-01 2.00e-02 
2.21e-01 2.00e-02 
2.21e-01 2.00e-02 
2.23e-01 2.00e-02 
2.20e-01 2.00e-02 
2.22e-01 2.00e-02 
2.21e-01 2.00e-02 
2.21e-01 2.00e-02 
2.21e-01 2.00e-02 
2.22e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/bs-s030_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bs-s030
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 30 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.91 s
Mean overlap 0.788 --> 1.000

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bs-s030_mclassic.txt
================================================
 0.793  1.001 
 0.793  1.001 
 0.794  1.001 
 0.796  1.001 
 0.796  1.001 
 0.791  1.001 
 0.797  1.001 
 0.773  1.001 
 0.796  1.001 
 0.771  1.001 
 0.802  1.001 
 0.794  1.001 
 0.796  1.001 
 0.795  1.001 
 0.772  1.001 
 0.795  1.001 
 0.770  0.984 
 0.793  0.982 
 0.771  1.001 
 0.796  1.001 
 0.770  1.001 
 0.796  1.001 
 0.796  1.001 
 0.794  1.001 
 0.797  1.001 
 0.795  1.001 
 0.771  1.001 
 0.771  1.001 
 0.771  1.001 
 0.795  1.001 


================================================
FILE: hippocampus/out/sweep/bs-s030_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.146 
 0.000  0.073 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/bs-s030_params.txt
================================================
seed             = 45537814

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 30
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bs-s030_qcue.txt
================================================
0 30 60 1 31 61 2 32 62 3 33 63 4 34 64 5 35 65 6 36 66 7 37 67 8 38 68 9 39 69 

================================================
FILE: hippocampus/out/sweep/bs-s030_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bs-s030_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 

================================================
FILE: hippocampus/out/sweep/bs-s030_wsample.txt
================================================
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-1.769531e-05 2.195312e-05 1.130860e-05 3.347656e-05 -1.046874e-05 9.941414e-06 4.949220e-05 -5.666017e-05 -9.296866e-06 -7.570315e-05 -1.691406e-05 1.542976e-06 3.787109e-05 -1.134765e-05 -3.810548e-05 7.597664e-06 1.257812e-05 -1.466797e-05 -6.074212e-06 -1.271483e-05 -2.167963e-06 -1.164062e-05 1.560547e-05 -2.628906e-05 -1.271486e-05 -4.552735e-05 -4.416014e-05 1.482423e-05 -1.720702e-05 -2.833983e-05 -6.291016e-05 1.072267e-05 -4.201171e-05 2.302735e-05 2.283203e-05 -3.185546e-05 -5.158204e-05 -1.330078e-05 -3.458983e-05 -4.826173e-05 7.597657e-06 3.175585e-04 -2.443358e-05 -2.375000e-05 -9.589843e-06 -3.925779e-06 3.064453e-05 6.328126e-06 -5.060546e-05 -6.339845e-05 7.742186e-05 5.652344e-05 3.591795e-05 1.023438e-05 3.738282e-05 -3.742187e-05 -3.205077e-05 -3.124967e-07 6.160157e-05 -3.371094e-05 4.783202e-05 2.078126e-05 2.507813e-05 1.267579e-05 3.477343e-04 -4.923827e-05 -2.248049e-05 -3.339845e-06 -1.466796e-05 -9.960941e-07 -9.785151e-06 -4.757813e-05 -5.382812e-05 3.308594e-05 4.177734e-05 1.335938e-05 6.707032e-05 -3.878905e-05 1.082032e-05 -1.828128e-05 1.941407e-05 1.082031e-05 -2.462890e-05 -1.837891e-05 -5.714844e-05 -4.855467e-05 -2.833983e-05 2.156250e-05 -9.492202e-06 -3.576173e-05 2.742188e-05 1.013672e-05 -3.136718e-05 -1.701171e-05 1.542974e-06 -3.124933e-07 1.179688e-05 0.000000e+00 -1.906250e-05 5.546881e-06 
4.001953e-05 5.037109e-05 -9.101560e-06 5.212891e-05 -4.552734e-05 4.324217e-05 4.667971e-06 8.406250e-05 -3.947265e-05 -2.775391e-05 -3.244141e-05 -4.218747e-06 -2.160156e-05 -6.105469e-05 -4.875001e-05 -3.046873e-06 -6.154297e-05 8.867190e-06 2.234375e-05 -6.730467e-05 2.625000e-05 -4.669921e-05 1.960937e-05 -3.693360e-05 -8.710929e-06 5.613281e-05 5.750001e-05 -1.046875e-05 -1.808593e-05 -4.874999e-05 -6.378906e-05 4.402343e-05 -7.707031e-05 -4.621093e-05 -7.343753e-06 -4.249999e-05 -3.632817e-06 -2.882812e-05 -2.570311e-05 3.951952e-04 -1.769531e-05 -8.371093e-05 -5.781241e-06 1.443360e-05 -5.585935e-06 -3.410155e-05 1.511718e-05 5.449216e-06 -6.613281e-05 8.964840e-06 -3.576173e-05 -1.759765e-05 2.039063e-05 3.865235e-05 3.650391e-05 -1.876952e-05 -5.246094e-05 -2.072265e-05 -3.693359e-05 -3.458983e-05 3.230469e-05 -4.357424e-05 1.931639e-05 2.031256e-06 3.273241e-04 7.683594e-05 3.965624e-04 -9.101559e-06 -2.531250e-05 3.007817e-06 8.867190e-06 2.478515e-05 4.783204e-05 4.685546e-05 -1.281249e-05 1.248048e-05 1.248046e-05 2.869139e-05 -9.589843e-06 3.568163e-04 -5.878901e-06 1.757835e-07 1.843751e-05 1.003907e-05 -2.384765e-05 4.277363e-06 9.843763e-06 1.152352e-06 -6.054652e-07 -1.222658e-05 7.011724e-06 -1.515625e-05 4.587891e-05 3.093749e-05 -4.218749e-06 -1.583984e-05 3.044922e-05 -1.906250e-05 0.000000e+00 -2.148413e-07 
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================================================
FILE: hippocampus/out/sweep/bs-s100_a.txt
================================================
2.25e-01 2.00e-02 
2.25e-01 2.00e-02 
2.21e-01 2.00e-02 
2.25e-01 2.62e-01 
2.20e-01 2.75e-01 
2.25e-01 2.00e-02 
2.21e-01 2.00e-02 
2.22e-01 2.73e-01 
2.23e-01 2.00e-02 
2.25e-01 2.00e-02 
2.19e-01 2.66e-01 
2.21e-01 2.53e-01 
2.24e-01 2.00e-02 
2.21e-01 2.68e-01 
2.19e-01 2.49e-01 
2.20e-01 2.00e-02 
2.20e-01 2.74e-01 
2.23e-01 2.50e-01 
2.24e-01 2.61e-01 
2.21e-01 2.00e-02 
2.23e-01 2.63e-01 
2.21e-01 2.57e-01 
2.22e-01 2.71e-01 
2.24e-01 2.00e-02 
2.22e-01 2.60e-01 
2.22e-01 2.76e-01 
2.24e-01 2.66e-01 
2.23e-01 2.00e-02 
2.19e-01 2.00e-02 
2.25e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/bs-s100_log.txt
================================================

STARTING SIMULATION FOR out/sweep/bs-s100
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 100 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.92 s
Mean overlap 0.786 --> 0.583

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/bs-s100_mclassic.txt
================================================
 0.792  1.001 
 0.767  1.001 
 0.796  1.001 
 0.792  0.380 
 0.747 -0.057 
 0.792  1.001 
 0.796  1.001 
 0.770  0.020 
 0.794  1.001 
 0.792  1.001 
 0.798  0.202 
 0.796  0.389 
 0.768  1.001 
 0.796  0.125 
 0.773 -0.004 
 0.772  1.001 
 0.797  0.343 
 0.794  0.193 
 0.793  0.356 
 0.796  1.001 
 0.794  0.230 
 0.796  0.136 
 0.770  0.097 
 0.793  1.001 
 0.770  0.432 
 0.795  0.142 
 0.793  0.377 
 0.794  1.001 
 0.773  1.001 
 0.792  1.001 


================================================
FILE: hippocampus/out/sweep/bs-s100_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/bs-s100_params.txt
================================================
seed             = 45323062

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 100
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 3
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/bs-s100_qcue.txt
================================================
0 100 200 1 101 201 2 102 202 3 103 203 4 104 204 5 105 205 6 106 206 7 107 207 8 108 208 9 109 209 

================================================
FILE: hippocampus/out/sweep/bs-s100_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/bs-s100_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 

================================================
FILE: hippocampus/out/sweep/bs-s100_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/dc-s001_a.txt
================================================
2.03e-01 3.38e-01 
2.06e-01 3.37e-01 
2.04e-01 2.71e-01 
2.08e-01 3.41e-01 
2.09e-01 3.39e-01 
2.07e-01 2.16e-01 
2.08e-01 3.42e-01 
2.02e-01 3.40e-01 
2.09e-01 2.30e-01 
2.06e-01 3.38e-01 
2.04e-01 3.42e-01 
2.07e-01 2.17e-01 
2.03e-01 3.38e-01 
2.07e-01 3.33e-01 
2.07e-01 2.93e-01 
2.03e-01 3.41e-01 
2.07e-01 3.35e-01 
2.03e-01 3.66e-01 
2.07e-01 3.39e-01 
2.07e-01 3.35e-01 
2.07e-01 2.18e-01 
2.06e-01 3.40e-01 
2.07e-01 3.40e-01 
2.09e-01 3.65e-01 
2.06e-01 3.36e-01 
2.09e-01 3.33e-01 
2.09e-01 2.52e-01 
2.06e-01 3.39e-01 
2.06e-01 3.40e-01 
2.08e-01 2.17e-01 


================================================
FILE: hippocampus/out/sweep/dc-s001_log.txt
================================================

STARTING SIMULATION FOR out/sweep/dc-s001
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 1 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.91 s
Mean overlap 0.123 --> 0.111

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/dc-s001_mclassic.txt
================================================
-0.013 -0.054 
 0.093  0.088 
 0.255  0.062 
-0.025 -0.048 
 0.102  0.095 
 0.254  0.245 
-0.019 -0.046 
 0.089  0.078 
 0.255  0.237 
-0.029 -0.045 
 0.099  0.085 
 0.248  0.244 
-0.010 -0.060 
 0.095  0.081 
 0.254  0.217 
-0.019 -0.045 
 0.095  0.091 
 0.250  0.187 
-0.009 -0.049 
 0.101  0.088 
 0.242  0.243 
-0.023 -0.046 
 0.095  0.090 
 0.255  0.191 
-0.016 -0.054 
 0.093  0.084 
 0.255  0.087 
-0.023 -0.052 
 0.118  0.081 
 0.247  0.244 


================================================
FILE: hippocampus/out/sweep/dc-s001_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/dc-s001_params.txt
================================================
seed             = 44736310

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 1
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/dc-s001_qcue.txt
================================================
0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 

================================================
FILE: hippocampus/out/sweep/dc-s001_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/dc-s001_qnu.txt
================================================
0 

================================================
FILE: hippocampus/out/sweep/dc-s001_wsample.txt
================================================
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-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 0.000000e+00 2.115234e-06 2.115234e-06 -1.595703e-06 
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-4.238279e-07 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 2.603516e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 1.431641e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 4.458985e-06 2.565039e-05 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -3.451172e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.712305e-05 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -1.595703e-06 2.379492e-05 -1.595703e-06 -1.595703e-06 1.431641e-06 1.431641e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/dc-s003_a.txt
================================================
2.06e-01 2.50e-01 
2.08e-01 2.92e-01 
2.07e-01 2.98e-01 
2.06e-01 2.84e-01 
2.00e-01 2.94e-01 
2.08e-01 4.02e-01 
2.07e-01 2.45e-01 
2.05e-01 2.92e-01 
2.08e-01 2.94e-01 
2.08e-01 2.62e-01 
2.06e-01 2.88e-01 
2.05e-01 4.21e-01 
2.04e-01 7.33e-01 
2.05e-01 2.91e-01 
2.02e-01 4.21e-01 
2.02e-01 3.68e-01 
2.08e-01 3.74e-01 
2.09e-01 2.59e-01 
2.07e-01 2.46e-01 
2.08e-01 2.90e-01 
2.05e-01 2.97e-01 
2.05e-01 2.46e-01 
2.04e-01 2.62e-01 
2.07e-01 2.72e-01 
2.05e-01 3.62e-01 
2.05e-01 3.74e-01 
2.02e-01 2.64e-01 
2.03e-01 2.54e-01 
2.07e-01 2.77e-01 
2.06e-01 4.23e-01 


================================================
FILE: hippocampus/out/sweep/dc-s003_log.txt
================================================

STARTING SIMULATION FOR out/sweep/dc-s003
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 3 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.91 s
Mean overlap 0.186 --> 0.110

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/dc-s003_mclassic.txt
================================================
-0.020 -0.010 
 0.091  0.110 
 0.254  0.235 
 0.402  0.109 
 0.247  0.193 
 0.231  0.105 
 0.098  0.054 
 0.223  0.193 
 0.167  0.029 
-0.022 -0.013 
 0.099  0.095 
 0.247  0.255 
 0.395  0.027 
 0.244  0.198 
 0.233  0.135 
 0.095 -0.033 
 0.231  0.225 
 0.166 -0.022 
-0.021 -0.023 
 0.100  0.108 
 0.259  0.236 
 0.397  0.052 
 0.245  0.128 
 0.233  0.081 
 0.101 -0.038 
 0.217  0.219 
 0.178 -0.037 
-0.022 -0.019 
 0.107 -0.032 
 0.246  0.286 


================================================
FILE: hippocampus/out/sweep/dc-s003_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.024  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.020  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.020  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/dc-s003_params.txt
================================================
seed             = 44776502

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 3
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/dc-s003_qcue.txt
================================================
0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 

================================================
FILE: hippocampus/out/sweep/dc-s003_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/dc-s003_qnu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/dc-s003_wsample.txt
================================================
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-2.931641e-06 -2.931641e-06 7.517579e-06 7.792967e-07 2.634765e-06 5.662109e-06 3.806641e-06 2.634765e-06 3.806641e-06 4.490234e-06 4.490234e-06 1.951172e-06 7.792967e-07 2.634765e-06 7.792967e-07 2.634765e-06 7.792967e-07 7.792967e-07 7.792967e-07 7.792967e-07 -1.076172e-06 4.490234e-06 -1.076172e-06 4.490234e-06 4.490234e-06 3.806641e-06 7.792967e-07 2.634765e-06 -1.406445e-05 2.634765e-06 2.634765e-06 7.517579e-06 -1.591992e-05 2.634765e-06 2.919727e-05 4.490234e-06 -1.777539e-05 4.490234e-06 7.792967e-07 2.634765e-06 2.634765e-06 3.806641e-06 -1.076172e-06 2.634765e-06 7.792967e-07 -1.076172e-06 2.634765e-06 2.634765e-06 2.634765e-06 2.634765e-06 1.951172e-06 2.634765e-06 7.792967e-07 2.634765e-06 2.634765e-06 -4.787110e-06 -1.591992e-05 4.490234e-06 7.517579e-06 7.792967e-07 2.634765e-06 -1.963086e-05 2.634765e-06 2.634765e-06 1.951172e-06 2.616992e-05 4.490234e-06 2.634765e-06 -1.591992e-05 4.490234e-06 -1.076172e-06 -1.406445e-05 -1.474805e-05 4.490234e-06 2.634765e-06 7.517579e-06 -2.931641e-06 7.517579e-06 4.490234e-06 2.634765e-06 4.490234e-06 5.662109e-06 -3.615235e-06 9.570294e-08 2.634765e-06 -2.773633e-05 -1.220898e-05 2.634765e-06 2.634765e-06 1.951172e-06 -1.963086e-05 4.490234e-06 -1.076172e-06 5.662109e-06 7.792967e-07 2.634765e-06 -1.076172e-06 2.634765e-06 0.000000e+00 1.951172e-06 
-3.615234e-06 1.267578e-06 1.951172e-06 9.570317e-08 1.951172e-06 4.978516e-06 3.123047e-06 -2.931641e-06 3.123047e-06 -1.076172e-06 -1.076172e-06 1.267578e-06 4.978516e-06 -2.931641e-06 -4.787110e-06 1.951172e-06 -4.787110e-06 -4.787110e-06 9.570317e-08 -4.787110e-06 3.123047e-06 -1.076172e-06 -1.759766e-06 -1.076172e-06 -1.076172e-06 8.005860e-06 -4.787110e-06 -2.931641e-06 -1.474805e-05 1.951172e-06 -2.931641e-06 1.951172e-06 2.734180e-05 -2.931641e-06 2.851367e-05 -1.076172e-06 -1.845898e-05 -1.076172e-06 -4.787110e-06 -2.931641e-06 -2.931641e-06 3.123047e-06 3.123047e-06 -2.931641e-06 -4.787110e-06 3.123047e-06 -2.931641e-06 -2.931641e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 -2.931641e-06 4.978516e-06 -2.931641e-06 -2.931641e-06 -5.878903e-07 2.245899e-05 -1.076172e-06 1.951172e-06 4.978516e-06 -2.931641e-06 -2.031445e-05 -2.931641e-06 -2.931641e-06 6.150391e-06 2.548633e-05 -1.076172e-06 -2.931641e-06 -1.660352e-05 -1.076172e-06 -1.759766e-06 -1.963086e-05 -1.543164e-05 -1.076172e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 1.951172e-06 -1.076172e-06 1.951172e-06 -1.076172e-06 9.570317e-08 -4.298828e-06 -5.878904e-07 -2.931641e-06 1.064258e-05 -1.777539e-05 1.951172e-06 1.951172e-06 1.267578e-06 -1.543164e-05 -1.076172e-06 -1.759766e-06 4.978516e-06 -4.787110e-06 -2.931641e-06 -1.759766e-06 -2.931641e-06 1.951172e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/dc-s010_a.txt
================================================
2.04e-01 3.20e-01 
2.10e-01 3.15e-01 
2.09e-01 3.50e-01 
2.06e-01 3.42e-01 
2.04e-01 3.29e-01 
2.06e-01 3.34e-01 
2.06e-01 3.25e-01 
2.05e-01 3.40e-01 
2.08e-01 3.26e-01 
2.06e-01 3.33e-01 
2.03e-01 3.44e-01 
2.09e-01 3.52e-01 
2.06e-01 3.19e-01 
2.10e-01 3.12e-01 
2.06e-01 3.54e-01 
2.09e-01 3.34e-01 
2.02e-01 3.49e-01 
2.05e-01 3.43e-01 
2.09e-01 3.50e-01 
2.06e-01 3.36e-01 
2.03e-01 3.46e-01 
2.07e-01 3.14e-01 
2.06e-01 3.11e-01 
2.04e-01 6.43e-01 
2.06e-01 3.42e-01 
2.07e-01 3.65e-01 
2.03e-01 3.45e-01 
2.08e-01 3.43e-01 
2.07e-01 3.17e-01 
2.01e-01 3.48e-01 


================================================
FILE: hippocampus/out/sweep/dc-s010_log.txt
================================================

STARTING SIMULATION FOR out/sweep/dc-s010
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 10 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.92 s
Mean overlap 0.186 --> 0.123

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/dc-s010_mclassic.txt
================================================
-0.011 -0.007 
 0.104  0.012 
 0.245  0.209 
 0.392  0.094 
 0.251  0.160 
 0.225  0.150 
 0.096  0.088 
 0.229  0.252 
 0.182  0.127 
 0.026  0.051 
 0.170 -0.021 
 0.233  0.174 
 0.066  0.080 
 0.217  0.108 
 0.209  0.165 
 0.074  0.089 
 0.260  0.168 
 0.189  0.145 
 0.227  0.067 
 0.109  0.187 
 0.234  0.261 
 0.150  0.141 
 0.246  0.112 
 0.178 -0.004 
 0.258  0.088 
 0.281  0.169 
 0.222  0.240 
-0.016  0.016 
 0.254  0.064 
 0.215  0.245 


================================================
FILE: hippocampus/out/sweep/dc-s010_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.010  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/dc-s010_params.txt
================================================
seed             = 44788246

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 10
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/dc-s010_qcue.txt
================================================
0 10 20 1 11 21 2 12 22 3 13 23 4 14 24 5 15 25 6 16 26 7 17 27 8 18 28 9 19 29 

================================================
FILE: hippocampus/out/sweep/dc-s010_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/dc-s010_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 

================================================
FILE: hippocampus/out/sweep/dc-s010_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/dc-s030_a.txt
================================================
2.07e-01 5.28e-01 
2.05e-01 5.27e-01 
2.07e-01 4.58e-01 
2.07e-01 4.14e-01 
2.09e-01 5.14e-01 
2.06e-01 4.55e-01 
2.08e-01 5.45e-01 
2.05e-01 5.25e-01 
2.05e-01 4.55e-01 
2.08e-01 5.46e-01 
2.07e-01 4.25e-01 
2.06e-01 4.39e-01 
2.10e-01 5.42e-01 
2.07e-01 4.30e-01 
2.07e-01 4.22e-01 
2.03e-01 4.51e-01 
2.08e-01 4.69e-01 
2.04e-01 4.30e-01 
2.08e-01 4.18e-01 
2.05e-01 5.32e-01 
2.06e-01 4.44e-01 
2.05e-01 4.24e-01 
2.05e-01 4.51e-01 
2.08e-01 5.46e-01 
2.07e-01 4.22e-01 
2.04e-01 5.24e-01 
2.07e-01 4.52e-01 
2.01e-01 5.13e-01 
2.06e-01 5.30e-01 
2.03e-01 4.60e-01 


================================================
FILE: hippocampus/out/sweep/dc-s030_log.txt
================================================

STARTING SIMULATION FOR out/sweep/dc-s030
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 30 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.90 s
Mean overlap 0.187 --> 0.242

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/dc-s030_mclassic.txt
================================================
-0.027 -0.236 
 0.104  0.089 
 0.248  0.310 
 0.394  0.328 
 0.245  0.252 
 0.225  0.276 
 0.100 -0.163 
 0.223  0.198 
 0.171  0.314 
 0.033 -0.276 
 0.178  0.228 
 0.234  0.355 
 0.076 -0.140 
 0.217  0.182 
 0.214  0.229 
 0.082  0.129 
 0.271  0.308 
 0.190  0.231 
 0.219  0.322 
 0.098  0.172 
 0.237  0.361 
 0.153  0.263 
 0.262  0.251 
 0.167  0.120 
 0.266  0.339 
 0.270  0.214 
 0.236  0.314 
-0.016 -0.204 
 0.255  0.140 
 0.213  0.306 


================================================
FILE: hippocampus/out/sweep/dc-s030_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.010  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/dc-s030_params.txt
================================================
seed             = 44932310

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 30
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/dc-s030_qcue.txt
================================================
0 30 60 1 31 61 2 32 62 3 33 63 4 34 64 5 35 65 6 36 66 7 37 67 8 38 68 9 39 69 

================================================
FILE: hippocampus/out/sweep/dc-s030_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/dc-s030_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 

================================================
FILE: hippocampus/out/sweep/dc-s030_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/dc-s100_a.txt
================================================
2.07e-01 5.42e-01 
2.08e-01 5.36e-01 
2.04e-01 5.29e-01 
2.07e-01 4.11e-01 
2.06e-01 4.36e-01 
2.08e-01 5.26e-01 
2.05e-01 4.12e-01 
2.07e-01 4.78e-01 
2.06e-01 5.33e-01 
2.05e-01 5.35e-01 
2.03e-01 4.25e-01 
2.07e-01 5.31e-01 
2.06e-01 4.26e-01 
2.09e-01 4.26e-01 
2.04e-01 4.03e-01 
2.06e-01 4.24e-01 
2.07e-01 4.29e-01 
2.07e-01 4.64e-01 
2.07e-01 4.10e-01 
2.05e-01 4.87e-01 
2.06e-01 5.28e-01 
2.03e-01 4.08e-01 
2.08e-01 4.30e-01 
2.02e-01 5.29e-01 
2.05e-01 4.15e-01 
2.06e-01 4.68e-01 
2.03e-01 5.29e-01 
2.06e-01 5.42e-01 
2.08e-01 4.79e-01 
2.05e-01 4.09e-01 


================================================
FILE: hippocampus/out/sweep/dc-s100_log.txt
================================================

STARTING SIMULATION FOR out/sweep/dc-s100
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 100 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.91 s
Mean overlap 0.186 --> 0.312

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/dc-s100_mclassic.txt
================================================
-0.024 -0.494 
 0.103  0.072 
 0.245  0.239 
 0.394  0.515 
 0.246  0.219 
 0.219  0.243 
 0.101  0.505 
 0.226  0.374 
 0.167  0.219 
 0.021 -0.477 
 0.182  0.149 
 0.226  0.224 
 0.081  0.478 
 0.221  0.148 
 0.206 -0.055 
 0.084  0.480 
 0.269  0.168 
 0.196  0.323 
 0.223  0.510 
 0.098  0.361 
 0.234  0.231 
 0.161  0.512 
 0.250  0.171 
 0.172  0.212 
 0.269  0.501 
 0.267  0.367 
 0.234  0.226 
-0.016 -0.485 
 0.250  0.371 
 0.208  0.029 


================================================
FILE: hippocampus/out/sweep/dc-s100_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.010  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/dc-s100_params.txt
================================================
seed             = 44717558

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 100
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/dc-s100_qcue.txt
================================================
0 100 200 1 101 201 2 102 202 3 103 203 4 104 204 5 105 205 6 106 206 7 107 207 8 108 208 9 109 209 

================================================
FILE: hippocampus/out/sweep/dc-s100_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/dc-s100_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 

================================================
FILE: hippocampus/out/sweep/dc-s100_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/ds-s001_a.txt
================================================
2.08e-01 2.00e-02 
2.08e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.03e-01 2.00e-02 
2.04e-01 2.00e-02 
2.09e-01 2.00e-02 
2.05e-01 2.00e-02 
2.05e-01 2.00e-02 
2.03e-01 2.00e-02 
2.05e-01 2.00e-02 
2.04e-01 2.00e-02 
2.08e-01 2.00e-02 
2.08e-01 2.00e-02 
2.06e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.08e-01 2.00e-02 
2.05e-01 2.00e-02 
2.03e-01 2.00e-02 
2.08e-01 2.00e-02 
2.06e-01 2.00e-02 
2.06e-01 2.00e-02 
2.06e-01 2.00e-02 
2.08e-01 2.00e-02 
2.05e-01 2.00e-02 
2.04e-01 2.00e-02 
2.05e-01 2.00e-02 
2.06e-01 2.00e-02 
2.06e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ds-s001_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ds-s001
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 1 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.80 s
Mean overlap 0.020 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ds-s001_mclassic.txt
================================================
 0.012  1.001 
 0.062  1.001 
-0.037  1.001 
 0.013  1.001 
 0.017  1.001 
-0.009  1.001 
 0.011  1.001 
 0.040  1.001 
 0.015  1.001 
 0.017  1.001 
-0.010  1.001 
-0.009  1.001 
 0.012  1.001 
 0.012  1.001 
-0.036  1.001 
 0.013  1.001 
 0.013  1.001 
-0.013  1.001 
 0.015  1.001 
 0.017  1.001 
-0.013  1.001 
 0.014  1.001 
 0.039  1.001 
-0.011  1.001 
 0.037  1.001 
 0.040  1.001 
 0.016  1.001 
 0.015  1.001 
 0.014  1.001 
-0.011  1.001 


================================================
FILE: hippocampus/out/sweep/ds-s001_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/ds-s001_params.txt
================================================
seed             = 45348662

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 1
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ds-s001_qcue.txt
================================================
0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 

================================================
FILE: hippocampus/out/sweep/ds-s001_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ds-s001_qnu.txt
================================================
0 

================================================
FILE: hippocampus/out/sweep/ds-s001_wsample.txt
================================================
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-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 0.000000e+00 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 0.000000e+00 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 0.000000e+00 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 0.000000e+00 -1.595703e-06 
-4.238279e-07 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 2.603516e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 1.431641e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 4.458985e-06 2.565039e-05 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -3.451172e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.712305e-05 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -1.595703e-06 2.379492e-05 -1.595703e-06 -1.595703e-06 1.431641e-06 1.431641e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/ds-s003_a.txt
================================================
2.08e-01 2.00e-02 
2.06e-01 2.00e-02 
2.07e-01 2.00e-02 
2.08e-01 2.00e-02 
2.03e-01 2.00e-02 
2.06e-01 2.00e-02 
2.08e-01 2.00e-02 
2.05e-01 2.00e-02 
2.04e-01 2.00e-02 
2.08e-01 2.00e-02 
2.06e-01 2.00e-02 
2.03e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.08e-01 2.00e-02 
2.06e-01 2.00e-02 
2.07e-01 2.00e-02 
2.03e-01 2.00e-02 
2.06e-01 2.00e-02 
2.02e-01 2.00e-02 
2.09e-01 2.00e-02 
2.05e-01 2.00e-02 
2.06e-01 2.00e-02 
2.07e-01 2.00e-02 
2.06e-01 2.00e-02 
2.03e-01 2.00e-02 
2.08e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ds-s003_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ds-s003
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 3 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.82 s
Mean overlap 0.042 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ds-s003_mclassic.txt
================================================
 0.012  1.001 
 0.014  1.001 
-0.012  1.001 
-0.013  1.001 
-0.008  1.001 
-0.061  1.001 
 0.087  1.001 
 0.115  1.001 
-0.009  1.001 
 0.037  1.001 
 0.014  1.001 
-0.033  1.001 
-0.012  1.001 
 0.013  1.001 
-0.088  1.001 
 0.089  1.001 
 0.113  1.001 
-0.008  1.001 
 0.039  1.001 
 0.018  1.001 
-0.014  1.001 
-0.010  1.001 
 0.014  1.001 
-0.087  1.001 
 0.114  1.001 
 0.117  1.001 
 0.037  1.001 
 0.063  1.001 
 0.013  1.001 
-0.012  1.001 


================================================
FILE: hippocampus/out/sweep/ds-s003_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/ds-s003_params.txt
================================================
seed             = 45388854

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 3
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ds-s003_qcue.txt
================================================
0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 

================================================
FILE: hippocampus/out/sweep/ds-s003_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ds-s003_qnu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ds-s003_wsample.txt
================================================
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-2.931641e-06 -2.931641e-06 7.517579e-06 7.792967e-07 2.634765e-06 5.662109e-06 3.806641e-06 2.634765e-06 3.806641e-06 4.490234e-06 4.490234e-06 1.951172e-06 7.792967e-07 2.634765e-06 7.792967e-07 2.634765e-06 7.792967e-07 7.792967e-07 7.792967e-07 7.792967e-07 -1.076172e-06 4.490234e-06 -1.076172e-06 4.490234e-06 4.490234e-06 3.806641e-06 7.792967e-07 2.634765e-06 -1.406445e-05 2.634765e-06 2.634765e-06 7.517579e-06 -1.591992e-05 2.634765e-06 2.919727e-05 4.490234e-06 -1.777539e-05 4.490234e-06 7.792967e-07 2.634765e-06 2.634765e-06 3.806641e-06 -1.076172e-06 2.634765e-06 7.792967e-07 -1.076172e-06 2.634765e-06 2.634765e-06 2.634765e-06 2.634765e-06 1.951172e-06 2.634765e-06 7.792967e-07 2.634765e-06 2.634765e-06 -4.787110e-06 -1.591992e-05 4.490234e-06 7.517579e-06 7.792967e-07 2.634765e-06 -1.963086e-05 2.634765e-06 2.634765e-06 1.951172e-06 2.616992e-05 4.490234e-06 2.634765e-06 -1.591992e-05 4.490234e-06 -1.076172e-06 -1.406445e-05 -1.474805e-05 4.490234e-06 2.634765e-06 7.517579e-06 -2.931641e-06 7.517579e-06 4.490234e-06 2.634765e-06 4.490234e-06 5.662109e-06 -3.615235e-06 9.570294e-08 2.634765e-06 -2.773633e-05 -1.220898e-05 2.634765e-06 2.634765e-06 1.951172e-06 -1.963086e-05 4.490234e-06 -1.076172e-06 5.662109e-06 7.792967e-07 2.634765e-06 -1.076172e-06 2.634765e-06 0.000000e+00 1.951172e-06 
-3.615234e-06 1.267578e-06 1.951172e-06 9.570317e-08 1.951172e-06 4.978516e-06 3.123047e-06 -2.931641e-06 3.123047e-06 -1.076172e-06 -1.076172e-06 1.267578e-06 4.978516e-06 -2.931641e-06 -4.787110e-06 1.951172e-06 -4.787110e-06 -4.787110e-06 9.570317e-08 -4.787110e-06 3.123047e-06 -1.076172e-06 -1.759766e-06 -1.076172e-06 -1.076172e-06 8.005860e-06 -4.787110e-06 -2.931641e-06 -1.474805e-05 1.951172e-06 -2.931641e-06 1.951172e-06 2.734180e-05 -2.931641e-06 2.851367e-05 -1.076172e-06 -1.845898e-05 -1.076172e-06 -4.787110e-06 -2.931641e-06 -2.931641e-06 3.123047e-06 3.123047e-06 -2.931641e-06 -4.787110e-06 3.123047e-06 -2.931641e-06 -2.931641e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 -2.931641e-06 4.978516e-06 -2.931641e-06 -2.931641e-06 -5.878903e-07 2.245899e-05 -1.076172e-06 1.951172e-06 4.978516e-06 -2.931641e-06 -2.031445e-05 -2.931641e-06 -2.931641e-06 6.150391e-06 2.548633e-05 -1.076172e-06 -2.931641e-06 -1.660352e-05 -1.076172e-06 -1.759766e-06 -1.963086e-05 -1.543164e-05 -1.076172e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 1.951172e-06 -1.076172e-06 1.951172e-06 -1.076172e-06 9.570317e-08 -4.298828e-06 -5.878904e-07 -2.931641e-06 1.064258e-05 -1.777539e-05 1.951172e-06 1.951172e-06 1.267578e-06 -1.543164e-05 -1.076172e-06 -1.759766e-06 4.978516e-06 -4.787110e-06 -2.931641e-06 -1.759766e-06 -2.931641e-06 1.951172e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/ds-s010_a.txt
================================================
2.04e-01 2.00e-02 
2.10e-01 2.00e-02 
2.07e-01 2.00e-02 
2.06e-01 2.00e-02 
2.09e-01 2.00e-02 
2.04e-01 2.00e-02 
2.08e-01 2.00e-02 
2.07e-01 3.71e-02 
2.08e-01 2.00e-02 
2.08e-01 2.00e-02 
2.10e-01 2.00e-02 
2.05e-01 2.00e-02 
2.07e-01 2.00e-02 
2.04e-01 2.00e-02 
2.07e-01 2.00e-02 
2.06e-01 2.00e-02 
2.07e-01 2.00e-02 
2.06e-01 2.00e-02 
2.07e-01 2.00e-02 
2.06e-01 2.00e-02 
2.05e-01 2.00e-02 
2.05e-01 2.00e-02 
2.06e-01 2.00e-02 
2.04e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.06e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.09e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ds-s010_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ds-s010
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 10 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.82 s
Mean overlap 0.045 --> 1.000

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ds-s010_mclassic.txt
================================================
 0.066  1.001 
 0.010  1.001 
-0.012  1.001 
-0.011  1.001 
 0.011  1.001 
-0.084  1.001 
 0.112  1.001 
 0.113  0.984 
-0.013  1.001 
-0.088  1.001 
 0.110  1.001 
-0.010  1.001 
-0.062  1.001 
 0.016  1.001 
 0.113  1.001 
 0.014  1.001 
 0.013  1.001 
-0.011  1.001 
-0.037  1.001 
 0.014  1.001 
 0.015  1.001 
 0.040  1.001 
-0.061  1.001 
-0.059  1.001 
 0.013  1.001 
 0.038  1.001 
 0.114  1.001 
 0.038  1.001 
-0.012  1.001 
-0.039  1.001 


================================================
FILE: hippocampus/out/sweep/ds-s010_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.146 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/ds-s010_params.txt
================================================
seed             = 45400598

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 10
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ds-s010_qcue.txt
================================================
0 10 20 1 11 21 2 12 22 3 13 23 4 14 24 5 15 25 6 16 26 7 17 27 8 18 28 9 19 29 

================================================
FILE: hippocampus/out/sweep/ds-s010_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ds-s010_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 

================================================
FILE: hippocampus/out/sweep/ds-s010_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/ds-s030_a.txt
================================================
2.06e-01 2.00e-02 
2.09e-01 2.00e-02 
2.02e-01 2.00e-02 
2.07e-01 2.00e-02 
2.05e-01 2.00e-02 
2.08e-01 2.00e-02 
2.05e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.08e-01 2.00e-02 
2.06e-01 2.00e-02 
2.06e-01 2.00e-02 
2.08e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.05e-01 2.00e-02 
2.09e-01 2.00e-02 
2.04e-01 2.00e-02 
2.08e-01 2.00e-02 
2.07e-01 2.00e-02 
2.07e-01 2.00e-02 
2.09e-01 2.00e-02 
2.06e-01 2.00e-02 
2.02e-01 2.00e-02 
2.05e-01 2.00e-02 
2.08e-01 2.00e-02 
2.04e-01 2.00e-02 
2.06e-01 2.00e-02 
2.05e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ds-s030_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ds-s030
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 30 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.94 s
Mean overlap 0.046 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ds-s030_mclassic.txt
================================================
 0.014  1.001 
 0.036  1.001 
 0.018  1.001 
-0.012  1.001 
 0.040  1.001 
-0.063  1.001 
 0.115  1.001 
 0.138  1.001 
 0.013  1.001 
-0.087  1.001 
 0.137  1.001 
 0.014  1.001 
-0.061  1.001 
 0.012  1.001 
 0.113  1.001 
 0.013  1.001 
 0.015  1.001 
-0.014  1.001 
-0.034  1.001 
 0.037  1.001 
 0.013  1.001 
 0.038  1.001 
-0.064  1.001 
-0.036  1.001 
 0.018  1.001 
 0.040  1.001 
 0.112  1.001 
 0.041  1.001 
-0.036  1.001 
-0.010  1.001 


================================================
FILE: hippocampus/out/sweep/ds-s030_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/ds-s030_params.txt
================================================
seed             = 45544662

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 30
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ds-s030_qcue.txt
================================================
0 30 60 1 31 61 2 32 62 3 33 63 4 34 64 5 35 65 6 36 66 7 37 67 8 38 68 9 39 69 

================================================
FILE: hippocampus/out/sweep/ds-s030_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ds-s030_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 

================================================
FILE: hippocampus/out/sweep/ds-s030_wsample.txt
================================================
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-1.769531e-05 2.195312e-05 1.130860e-05 3.347656e-05 -1.046874e-05 9.941414e-06 4.949220e-05 -5.666017e-05 -9.296866e-06 -7.570315e-05 -1.691406e-05 1.542976e-06 3.787109e-05 -1.134765e-05 -3.810548e-05 7.597664e-06 1.257812e-05 -1.466797e-05 -6.074212e-06 -1.271483e-05 -2.167963e-06 -1.164062e-05 1.560547e-05 -2.628906e-05 -1.271486e-05 -4.552735e-05 -4.416014e-05 1.482423e-05 -1.720702e-05 -2.833983e-05 -6.291016e-05 1.072267e-05 -4.201171e-05 2.302735e-05 2.283203e-05 -3.185546e-05 -5.158204e-05 -1.330078e-05 -3.458983e-05 -4.826173e-05 7.597657e-06 3.175585e-04 -2.443358e-05 -2.375000e-05 -9.589843e-06 -3.925779e-06 3.064453e-05 6.328126e-06 -5.060546e-05 -6.339845e-05 7.742186e-05 5.652344e-05 3.591795e-05 1.023438e-05 3.738282e-05 -3.742187e-05 -3.205077e-05 -3.124967e-07 6.160157e-05 -3.371094e-05 4.783202e-05 2.078126e-05 2.507813e-05 1.267579e-05 3.477343e-04 -4.923827e-05 -2.248049e-05 -3.339845e-06 -1.466796e-05 -9.960941e-07 -9.785151e-06 -4.757813e-05 -5.382812e-05 3.308594e-05 4.177734e-05 1.335938e-05 6.707032e-05 -3.878905e-05 1.082032e-05 -1.828128e-05 1.941407e-05 1.082031e-05 -2.462890e-05 -1.837891e-05 -5.714844e-05 -4.855467e-05 -2.833983e-05 2.156250e-05 -9.492202e-06 -3.576173e-05 2.742188e-05 1.013672e-05 -3.136718e-05 -1.701171e-05 1.542974e-06 -3.124933e-07 1.179688e-05 0.000000e+00 -1.906250e-05 5.546881e-06 
4.001953e-05 5.037109e-05 -9.101560e-06 5.212891e-05 -4.552734e-05 4.324217e-05 4.667971e-06 8.406250e-05 -3.947265e-05 -2.775391e-05 -3.244141e-05 -4.218747e-06 -2.160156e-05 -6.105469e-05 -4.875001e-05 -3.046873e-06 -6.154297e-05 8.867190e-06 2.234375e-05 -6.730467e-05 2.625000e-05 -4.669921e-05 1.960937e-05 -3.693360e-05 -8.710929e-06 5.613281e-05 5.750001e-05 -1.046875e-05 -1.808593e-05 -4.874999e-05 -6.378906e-05 4.402343e-05 -7.707031e-05 -4.621093e-05 -7.343753e-06 -4.249999e-05 -3.632817e-06 -2.882812e-05 -2.570311e-05 3.951952e-04 -1.769531e-05 -8.371093e-05 -5.781241e-06 1.443360e-05 -5.585935e-06 -3.410155e-05 1.511718e-05 5.449216e-06 -6.613281e-05 8.964840e-06 -3.576173e-05 -1.759765e-05 2.039063e-05 3.865235e-05 3.650391e-05 -1.876952e-05 -5.246094e-05 -2.072265e-05 -3.693359e-05 -3.458983e-05 3.230469e-05 -4.357424e-05 1.931639e-05 2.031256e-06 3.273241e-04 7.683594e-05 3.965624e-04 -9.101559e-06 -2.531250e-05 3.007817e-06 8.867190e-06 2.478515e-05 4.783204e-05 4.685546e-05 -1.281249e-05 1.248048e-05 1.248046e-05 2.869139e-05 -9.589843e-06 3.568163e-04 -5.878901e-06 1.757835e-07 1.843751e-05 1.003907e-05 -2.384765e-05 4.277363e-06 9.843763e-06 1.152352e-06 -6.054652e-07 -1.222658e-05 7.011724e-06 -1.515625e-05 4.587891e-05 3.093749e-05 -4.218749e-06 -1.583984e-05 3.044922e-05 -1.906250e-05 0.000000e+00 -2.148413e-07 
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================================================
FILE: hippocampus/out/sweep/ds-s100_a.txt
================================================
2.07e-01 2.00e-02 
2.09e-01 2.00e-02 
2.06e-01 2.00e-02 
2.07e-01 2.64e-01 
2.05e-01 2.78e-01 
2.06e-01 2.63e-01 
2.06e-01 2.00e-02 
2.07e-01 2.11e-01 
2.08e-01 2.43e-01 
2.06e-01 2.00e-02 
2.05e-01 2.65e-01 
2.02e-01 2.00e-02 
2.06e-01 2.00e-02 
2.04e-01 2.66e-01 
2.08e-01 2.53e-01 
2.08e-01 2.00e-02 
2.08e-01 2.76e-01 
2.09e-01 3.86e-02 
2.06e-01 2.62e-01 
2.08e-01 2.00e-02 
2.07e-01 2.00e-02 
2.06e-01 2.61e-01 
2.05e-01 2.73e-01 
2.07e-01 2.53e-01 
2.03e-01 2.60e-01 
2.07e-01 2.76e-01 
2.07e-01 2.67e-01 
2.06e-01 2.00e-02 
2.02e-01 2.00e-02 
2.03e-01 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ds-s100_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ds-s100
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 100 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.94 s
Mean overlap 0.045 --> 0.611

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ds-s100_mclassic.txt
================================================
 0.038  1.001 
 0.061  1.001 
-0.011  1.001 
-0.012  0.428 
 0.015 -0.059 
-0.086  0.379 
 0.114  1.001 
 0.113  0.581 
-0.013  0.300 
-0.061  1.001 
 0.115  0.203 
 0.018  1.001 
-0.061  1.001 
-0.009  0.127 
 0.112 -0.009 
 0.037  1.001 
 0.012  0.366 
-0.039  0.982 
 0.014  0.356 
 0.012  1.001 
 0.013  1.001 
 0.064  0.132 
-0.035  0.170 
-0.037  0.215 
 0.017  0.482 
 0.038  0.142 
 0.113  0.376 
 0.014  1.001 
-0.032  1.001 
-0.033  1.001 


================================================
FILE: hippocampus/out/sweep/ds-s100_mcustom.txt
================================================
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  0.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.073 
 0.000  0.000 
 0.000  1.000 
 0.000  1.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  1.000 
 0.000  1.000 
 0.000  1.000 


================================================
FILE: hippocampus/out/sweep/ds-s100_params.txt
================================================
seed             = 45329910

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 100
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 1
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ds-s100_qcue.txt
================================================
0 100 200 1 101 201 2 102 202 3 103 203 4 104 204 5 105 205 6 106 206 7 107 207 8 108 208 9 109 209 

================================================
FILE: hippocampus/out/sweep/ds-s100_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ds-s100_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 

================================================
FILE: hippocampus/out/sweep/ds-s100_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/sc-s001_a.txt
================================================
2.98e-02 3.40e-01 
2.98e-02 3.41e-01 
2.98e-02 3.62e-01 
2.78e-02 3.36e-01 
2.88e-02 3.41e-01 
2.98e-02 2.15e-01 
2.88e-02 3.43e-01 
2.98e-02 3.39e-01 
2.88e-02 2.17e-01 
2.98e-02 2.70e-01 
2.98e-02 2.71e-01 
2.88e-02 2.88e-01 
2.98e-02 3.36e-01 
2.98e-02 2.71e-01 
2.98e-02 2.48e-01 
2.88e-02 3.43e-01 
2.98e-02 3.39e-01 
2.98e-02 2.43e-01 
2.78e-02 3.40e-01 
2.98e-02 3.41e-01 
2.88e-02 2.16e-01 
2.88e-02 3.40e-01 
2.98e-02 3.39e-01 
2.98e-02 2.23e-01 
2.98e-02 3.37e-01 
2.98e-02 3.37e-01 
2.88e-02 2.50e-01 
2.98e-02 3.42e-01 
2.88e-02 3.43e-01 
2.98e-02 2.17e-01 


================================================
FILE: hippocampus/out/sweep/sc-s001_log.txt
================================================

STARTING SIMULATION FOR out/sweep/sc-s001
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 1 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.82 s
Mean overlap 0.009 --> 0.099

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/sc-s001_mclassic.txt
================================================
 0.018 -0.046 
-0.007  0.089 
 0.002  0.197 
 0.014 -0.048 
-0.009  0.087 
-0.004  0.240 
 0.013 -0.045 
-0.001  0.092 
 0.001  0.244 
 0.005 -0.020 
-0.010  0.062 
 0.007  0.208 
 0.015 -0.048 
 0.002  0.062 
 0.009  0.069 
 0.028 -0.056 
-0.010  0.095 
 0.002  0.078 
 0.014 -0.047 
-0.007  0.087 
-0.005  0.245 
 0.019 -0.052 
-0.016  0.085 
-0.013  0.090 
 0.009 -0.046 
 0.002  0.085 
 0.001  0.065 
 0.015 -0.043 
 0.004  0.090 
 0.002  0.247 


================================================
FILE: hippocampus/out/sweep/sc-s001_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/sc-s001_params.txt
================================================
seed             = 44787670

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 1
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/sc-s001_qcue.txt
================================================
0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 

================================================
FILE: hippocampus/out/sweep/sc-s001_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/sc-s001_qnu.txt
================================================
0 

================================================
FILE: hippocampus/out/sweep/sc-s001_wsample.txt
================================================
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-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 0.000000e+00 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 0.000000e+00 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 0.000000e+00 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 0.000000e+00 -1.595703e-06 
-4.238279e-07 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 2.603516e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 1.431641e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 4.458985e-06 2.565039e-05 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -3.451172e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.712305e-05 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -1.595703e-06 2.379492e-05 -1.595703e-06 -1.595703e-06 1.431641e-06 1.431641e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/sc-s003_a.txt
================================================
2.88e-02 2.65e-01 
2.98e-02 2.58e-01 
2.98e-02 7.48e-01 
2.98e-02 2.59e-01 
2.88e-02 2.44e-01 
2.98e-02 2.88e-01 
2.88e-02 2.50e-01 
2.88e-02 2.90e-01 
2.98e-02 2.88e-01 
2.78e-02 2.64e-01 
2.98e-02 2.65e-01 
2.78e-02 7.45e-01 
2.88e-02 2.50e-01 
2.98e-02 2.65e-01 
2.98e-02 2.98e-01 
2.98e-02 2.59e-01 
2.88e-02 3.73e-01 
2.88e-02 2.63e-01 
2.98e-02 2.56e-01 
2.98e-02 2.56e-01 
2.88e-02 2.44e-01 
2.98e-02 2.49e-01 
2.88e-02 3.70e-01 
2.98e-02 2.49e-01 
2.98e-02 3.65e-01 
2.88e-02 2.61e-01 
2.88e-02 2.87e-01 
2.98e-02 2.67e-01 
2.98e-02 2.88e-01 
2.98e-02 4.28e-01 


================================================
FILE: hippocampus/out/sweep/sc-s003_log.txt
================================================

STARTING SIMULATION FOR out/sweep/sc-s003
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 3 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.80 s
Mean overlap 0.008 --> 0.099

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/sc-s003_mclassic.txt
================================================
 0.010 -0.023 
-0.010  0.104 
 0.002  0.063 
-0.010  0.048 
-0.005  0.131 
 0.018  0.114 
 0.007  0.032 
-0.005  0.190 
 0.002  0.104 
 0.014 -0.012 
-0.004  0.068 
 0.008  0.076 
-0.005  0.035 
-0.004  0.069 
 0.021  0.244 
 0.009  0.048 
 0.007  0.221 
 0.010  0.046 
 0.005 -0.012 
-0.007  0.110 
-0.002  0.245 
-0.004  0.046 
-0.015  0.237 
 0.018  0.135 
 0.005 -0.032 
-0.002  0.098 
 0.007  0.118 
 0.018 -0.025 
-0.004 -0.015 
 0.005  0.280 


================================================
FILE: hippocampus/out/sweep/sc-s003_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/sc-s003_params.txt
================================================
seed             = 44827862

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 3
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/sc-s003_qcue.txt
================================================
0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 

================================================
FILE: hippocampus/out/sweep/sc-s003_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/sc-s003_qnu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/sc-s003_wsample.txt
================================================
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-2.931641e-06 -2.931641e-06 7.517579e-06 7.792967e-07 2.634765e-06 5.662109e-06 3.806641e-06 2.634765e-06 3.806641e-06 4.490234e-06 4.490234e-06 1.951172e-06 7.792967e-07 2.634765e-06 7.792967e-07 2.634765e-06 7.792967e-07 7.792967e-07 7.792967e-07 7.792967e-07 -1.076172e-06 4.490234e-06 -1.076172e-06 4.490234e-06 4.490234e-06 3.806641e-06 7.792967e-07 2.634765e-06 -1.406445e-05 2.634765e-06 2.634765e-06 7.517579e-06 -1.591992e-05 2.634765e-06 2.919727e-05 4.490234e-06 -1.777539e-05 4.490234e-06 7.792967e-07 2.634765e-06 2.634765e-06 3.806641e-06 -1.076172e-06 2.634765e-06 7.792967e-07 -1.076172e-06 2.634765e-06 2.634765e-06 2.634765e-06 2.634765e-06 1.951172e-06 2.634765e-06 7.792967e-07 2.634765e-06 2.634765e-06 -4.787110e-06 -1.591992e-05 4.490234e-06 7.517579e-06 7.792967e-07 2.634765e-06 -1.963086e-05 2.634765e-06 2.634765e-06 1.951172e-06 2.616992e-05 4.490234e-06 2.634765e-06 -1.591992e-05 4.490234e-06 -1.076172e-06 -1.406445e-05 -1.474805e-05 4.490234e-06 2.634765e-06 7.517579e-06 -2.931641e-06 7.517579e-06 4.490234e-06 2.634765e-06 4.490234e-06 5.662109e-06 -3.615235e-06 9.570294e-08 2.634765e-06 -2.773633e-05 -1.220898e-05 2.634765e-06 2.634765e-06 1.951172e-06 -1.963086e-05 4.490234e-06 -1.076172e-06 5.662109e-06 7.792967e-07 2.634765e-06 -1.076172e-06 2.634765e-06 0.000000e+00 1.951172e-06 
-3.615234e-06 1.267578e-06 1.951172e-06 9.570317e-08 1.951172e-06 4.978516e-06 3.123047e-06 -2.931641e-06 3.123047e-06 -1.076172e-06 -1.076172e-06 1.267578e-06 4.978516e-06 -2.931641e-06 -4.787110e-06 1.951172e-06 -4.787110e-06 -4.787110e-06 9.570317e-08 -4.787110e-06 3.123047e-06 -1.076172e-06 -1.759766e-06 -1.076172e-06 -1.076172e-06 8.005860e-06 -4.787110e-06 -2.931641e-06 -1.474805e-05 1.951172e-06 -2.931641e-06 1.951172e-06 2.734180e-05 -2.931641e-06 2.851367e-05 -1.076172e-06 -1.845898e-05 -1.076172e-06 -4.787110e-06 -2.931641e-06 -2.931641e-06 3.123047e-06 3.123047e-06 -2.931641e-06 -4.787110e-06 3.123047e-06 -2.931641e-06 -2.931641e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 -2.931641e-06 4.978516e-06 -2.931641e-06 -2.931641e-06 -5.878903e-07 2.245899e-05 -1.076172e-06 1.951172e-06 4.978516e-06 -2.931641e-06 -2.031445e-05 -2.931641e-06 -2.931641e-06 6.150391e-06 2.548633e-05 -1.076172e-06 -2.931641e-06 -1.660352e-05 -1.076172e-06 -1.759766e-06 -1.963086e-05 -1.543164e-05 -1.076172e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 1.951172e-06 -1.076172e-06 1.951172e-06 -1.076172e-06 9.570317e-08 -4.298828e-06 -5.878904e-07 -2.931641e-06 1.064258e-05 -1.777539e-05 1.951172e-06 1.951172e-06 1.267578e-06 -1.543164e-05 -1.076172e-06 -1.759766e-06 4.978516e-06 -4.787110e-06 -2.931641e-06 -1.759766e-06 -2.931641e-06 1.951172e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/sc-s010_a.txt
================================================
2.98e-02 3.38e-01 
2.88e-02 3.40e-01 
2.98e-02 3.61e-01 
2.98e-02 3.14e-01 
2.88e-02 3.32e-01 
2.78e-02 3.48e-01 
2.98e-02 3.29e-01 
2.88e-02 3.33e-01 
2.98e-02 3.21e-01 
2.98e-02 3.07e-01 
2.88e-02 3.36e-01 
2.88e-02 3.33e-01 
2.98e-02 3.27e-01 
2.88e-02 3.10e-01 
2.88e-02 3.29e-01 
2.98e-02 3.41e-01 
2.98e-02 3.03e-01 
2.98e-02 3.45e-01 
2.98e-02 3.24e-01 
2.98e-02 3.41e-01 
2.98e-02 3.30e-01 
2.98e-02 3.10e-01 
2.98e-02 3.33e-01 
2.98e-02 3.40e-01 
2.98e-02 3.07e-01 
2.98e-02 3.29e-01 
2.98e-02 3.44e-01 
2.98e-02 3.35e-01 
2.88e-02 3.23e-01 
2.88e-02 3.32e-01 


================================================
FILE: hippocampus/out/sweep/sc-s010_log.txt
================================================

STARTING SIMULATION FOR out/sweep/sc-s010
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 10 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.80 s
Mean overlap 0.008 --> 0.099

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/sc-s010_mclassic.txt
================================================
 0.024  0.026 
-0.009 -0.071 
 0.009  0.186 
-0.010  0.092 
-0.005  0.125 
 0.017  0.062 
 0.009  0.056 
-0.002  0.142 
 0.012  0.062 
-0.001  0.071 
-0.005  0.078 
 0.007  0.139 
-0.007  0.126 
-0.009  0.128 
 0.001  0.169 
 0.005  0.053 
-0.013  0.092 
 0.012  0.137 
 0.002  0.084 
-0.001 -0.008 
-0.007  0.089 
 0.015  0.095 
 0.005  0.081 
-0.007  0.137 
 0.015  0.065 
 0.012  0.206 
-0.007  0.201 
-0.007  0.069 
-0.012  0.030 
 0.004  0.107 


================================================
FILE: hippocampus/out/sweep/sc-s010_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/sc-s010_params.txt
================================================
seed             = 44839606

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 10
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/sc-s010_qcue.txt
================================================
0 10 20 1 11 21 2 12 22 3 13 23 4 14 24 5 15 25 6 16 26 7 17 27 8 18 28 9 19 29 

================================================
FILE: hippocampus/out/sweep/sc-s010_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/sc-s010_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 

================================================
FILE: hippocampus/out/sweep/sc-s010_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/sc-s030_a.txt
================================================
2.98e-02 5.33e-01 
2.98e-02 4.29e-01 
2.98e-02 4.46e-01 
2.98e-02 4.20e-01 
2.69e-02 5.28e-01 
2.98e-02 4.12e-01 
2.98e-02 5.61e-01 
2.88e-02 4.22e-01 
2.78e-02 4.36e-01 
2.98e-02 4.38e-01 
2.98e-02 5.33e-01 
2.98e-02 4.33e-01 
2.98e-02 4.23e-01 
2.98e-02 4.27e-01 
2.88e-02 4.15e-01 
2.98e-02 4.42e-01 
2.98e-02 4.91e-01 
2.98e-02 4.28e-01 
2.98e-02 4.12e-01 
2.98e-02 5.50e-01 
2.88e-02 4.43e-01 
2.98e-02 4.49e-01 
2.98e-02 4.46e-01 
2.98e-02 4.57e-01 
2.88e-02 4.15e-01 
2.88e-02 5.28e-01 
2.78e-02 4.13e-01 
2.98e-02 5.04e-01 
2.88e-02 5.04e-01 
2.98e-02 4.43e-01 


================================================
FILE: hippocampus/out/sweep/sc-s030_log.txt
================================================

STARTING SIMULATION FOR out/sweep/sc-s030
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 30 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.81 s
Mean overlap 0.008 --> 0.213

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/sc-s030_mclassic.txt
================================================
 0.009 -0.230 
-0.013 -0.020 
 0.002  0.287 
-0.016  0.290 
-0.009  0.189 
 0.018  0.175 
 0.012 -0.244 
 0.004  0.272 
 0.005  0.255 
 0.005 -0.118 
-0.007  0.143 
 0.005  0.359 
-0.004  0.289 
-0.004  0.065 
 0.016  0.253 
 0.005  0.253 
-0.007  0.253 
-0.001  0.268 
 0.005  0.281 
 0.012 -0.038 
-0.002  0.184 
 0.009  0.259 
 0.009  0.215 
-0.004  0.305 
 0.022  0.324 
 0.007  0.191 
 0.008 -0.015 
-0.007 -0.090 
-0.005  0.239 
 0.005  0.292 


================================================
FILE: hippocampus/out/sweep/sc-s030_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/sc-s030_params.txt
================================================
seed             = 44983670

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 30
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/sc-s030_qcue.txt
================================================
0 30 60 1 31 61 2 32 62 3 33 63 4 34 64 5 35 65 6 36 66 7 37 67 8 38 68 9 39 69 

================================================
FILE: hippocampus/out/sweep/sc-s030_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/sc-s030_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 

================================================
FILE: hippocampus/out/sweep/sc-s030_wsample.txt
================================================
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-1.769531e-05 2.195312e-05 1.130860e-05 3.347656e-05 -1.046874e-05 9.941414e-06 4.949220e-05 -5.666017e-05 -9.296866e-06 -7.570315e-05 -1.691406e-05 1.542976e-06 3.787109e-05 -1.134765e-05 -3.810548e-05 7.597664e-06 1.257812e-05 -1.466797e-05 -6.074212e-06 -1.271483e-05 -2.167963e-06 -1.164062e-05 1.560547e-05 -2.628906e-05 -1.271486e-05 -4.552735e-05 -4.416014e-05 1.482423e-05 -1.720702e-05 -2.833983e-05 -6.291016e-05 1.072267e-05 -4.201171e-05 2.302735e-05 2.283203e-05 -3.185546e-05 -5.158204e-05 -1.330078e-05 -3.458983e-05 -4.826173e-05 7.597657e-06 3.175585e-04 -2.443358e-05 -2.375000e-05 -9.589843e-06 -3.925779e-06 3.064453e-05 6.328126e-06 -5.060546e-05 -6.339845e-05 7.742186e-05 5.652344e-05 3.591795e-05 1.023438e-05 3.738282e-05 -3.742187e-05 -3.205077e-05 -3.124967e-07 6.160157e-05 -3.371094e-05 4.783202e-05 2.078126e-05 2.507813e-05 1.267579e-05 3.477343e-04 -4.923827e-05 -2.248049e-05 -3.339845e-06 -1.466796e-05 -9.960941e-07 -9.785151e-06 -4.757813e-05 -5.382812e-05 3.308594e-05 4.177734e-05 1.335938e-05 6.707032e-05 -3.878905e-05 1.082032e-05 -1.828128e-05 1.941407e-05 1.082031e-05 -2.462890e-05 -1.837891e-05 -5.714844e-05 -4.855467e-05 -2.833983e-05 2.156250e-05 -9.492202e-06 -3.576173e-05 2.742188e-05 1.013672e-05 -3.136718e-05 -1.701171e-05 1.542974e-06 -3.124933e-07 1.179688e-05 0.000000e+00 -1.906250e-05 5.546881e-06 
4.001953e-05 5.037109e-05 -9.101560e-06 5.212891e-05 -4.552734e-05 4.324217e-05 4.667971e-06 8.406250e-05 -3.947265e-05 -2.775391e-05 -3.244141e-05 -4.218747e-06 -2.160156e-05 -6.105469e-05 -4.875001e-05 -3.046873e-06 -6.154297e-05 8.867190e-06 2.234375e-05 -6.730467e-05 2.625000e-05 -4.669921e-05 1.960937e-05 -3.693360e-05 -8.710929e-06 5.613281e-05 5.750001e-05 -1.046875e-05 -1.808593e-05 -4.874999e-05 -6.378906e-05 4.402343e-05 -7.707031e-05 -4.621093e-05 -7.343753e-06 -4.249999e-05 -3.632817e-06 -2.882812e-05 -2.570311e-05 3.951952e-04 -1.769531e-05 -8.371093e-05 -5.781241e-06 1.443360e-05 -5.585935e-06 -3.410155e-05 1.511718e-05 5.449216e-06 -6.613281e-05 8.964840e-06 -3.576173e-05 -1.759765e-05 2.039063e-05 3.865235e-05 3.650391e-05 -1.876952e-05 -5.246094e-05 -2.072265e-05 -3.693359e-05 -3.458983e-05 3.230469e-05 -4.357424e-05 1.931639e-05 2.031256e-06 3.273241e-04 7.683594e-05 3.965624e-04 -9.101559e-06 -2.531250e-05 3.007817e-06 8.867190e-06 2.478515e-05 4.783204e-05 4.685546e-05 -1.281249e-05 1.248048e-05 1.248046e-05 2.869139e-05 -9.589843e-06 3.568163e-04 -5.878901e-06 1.757835e-07 1.843751e-05 1.003907e-05 -2.384765e-05 4.277363e-06 9.843763e-06 1.152352e-06 -6.054652e-07 -1.222658e-05 7.011724e-06 -1.515625e-05 4.587891e-05 3.093749e-05 -4.218749e-06 -1.583984e-05 3.044922e-05 -1.906250e-05 0.000000e+00 -2.148413e-07 
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================================================
FILE: hippocampus/out/sweep/sc-s100_a.txt
================================================
2.98e-02 4.26e-01 
2.98e-02 4.23e-01 
2.78e-02 5.33e-01 
2.98e-02 4.11e-01 
2.98e-02 5.41e-01 
2.98e-02 5.32e-01 
2.98e-02 4.95e-01 
2.98e-02 5.36e-01 
2.98e-02 5.35e-01 
2.78e-02 5.39e-01 
2.88e-02 4.28e-01 
2.98e-02 5.31e-01 
2.88e-02 4.14e-01 
2.98e-02 4.22e-01 
2.98e-02 4.10e-01 
2.88e-02 4.20e-01 
2.98e-02 4.27e-01 
2.98e-02 4.10e-01 
2.98e-02 4.23e-01 
2.98e-02 4.41e-01 
2.98e-02 5.19e-01 
2.98e-02 4.22e-01 
2.98e-02 4.28e-01 
2.98e-02 4.09e-01 
2.98e-02 4.15e-01 
2.98e-02 4.97e-01 
2.98e-02 5.28e-01 
2.78e-02 5.31e-01 
2.98e-02 5.41e-01 
2.88e-02 4.14e-01 


================================================
FILE: hippocampus/out/sweep/sc-s100_log.txt
================================================

STARTING SIMULATION FOR out/sweep/sc-s100
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 100 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.80 s
Mean overlap 0.006 --> 0.255

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/sc-s100_mclassic.txt
================================================
 0.018  0.471 
-0.004  0.146 
 0.008  0.219 
-0.007  0.502 
-0.007 -0.078 
 0.009  0.217 
-0.001 -0.255 
-0.001  0.032 
 0.009  0.204 
-0.001 -0.488 
-0.009  0.170 
 0.015  0.218 
-0.009  0.505 
 0.002  0.114 
 0.002 -0.113 
 0.004  0.482 
-0.001  0.159 
 0.012 -0.113 
 0.009  0.490 
 0.012  0.230 
 0.002 -0.164 
 0.002  0.480 
-0.001  0.173 
-0.007 -0.132 
 0.005  0.498 
 0.005  0.313 
-0.007  0.212 
-0.001 -0.438 
 0.005  0.008 
-0.005  0.016 


================================================
FILE: hippocampus/out/sweep/sc-s100_mcustom.txt
================================================
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 
 0.000  0.000 


================================================
FILE: hippocampus/out/sweep/sc-s100_params.txt
================================================
seed             = 44768918

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 100
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 2
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.000000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/sc-s100_qcue.txt
================================================
0 100 200 1 101 201 2 102 202 3 103 203 4 104 204 5 105 205 6 106 206 7 107 207 8 108 208 9 109 209 

================================================
FILE: hippocampus/out/sweep/sc-s100_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/sc-s100_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 

================================================
FILE: hippocampus/out/sweep/sc-s100_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/ss-s001_a.txt
================================================
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.78e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.78e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ss-s001_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ss-s001
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 1 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.81 s
Mean overlap 0.982 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ss-s001_mclassic.txt
================================================
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.943  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.943  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 


================================================
FILE: hippocampus/out/sweep/ss-s001_mcustom.txt
================================================
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 


================================================
FILE: hippocampus/out/sweep/ss-s001_params.txt
================================================
seed             = 45400022

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 1
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ss-s001_qcue.txt
================================================
0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 

================================================
FILE: hippocampus/out/sweep/ss-s001_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ss-s001_qnu.txt
================================================
0 

================================================
FILE: hippocampus/out/sweep/ss-s001_wsample.txt
================================================
0.000000e+00 4.458985e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 4.458985e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 2.603516e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -3.451172e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -4.238279e-07 2.565039e-05 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -4.238279e-07 -1.595703e-06 1.431641e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 2.682227e-05 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 4.458985e-06 1.431641e-06 -1.595703e-06 -1.526758e-05 -1.595703e-06 -1.595703e-06 1.431641e-06 1.431641e-06 -4.238279e-07 -1.595703e-06 -4.238279e-07 -3.451172e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 
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-4.238279e-07 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 0.000000e+00 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 2.603516e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 1.431641e-06 1.431641e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 1.431641e-06 -4.238279e-07 -1.829492e-05 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 4.458985e-06 -1.595703e-06 1.431641e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 3.170508e-05 -1.595703e-06 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -3.451172e-06 -1.595703e-06 2.867774e-05 -1.595703e-06 -1.595703e-06 -3.451172e-06 -3.451172e-06 -4.238279e-07 -1.595703e-06 4.458985e-06 1.431641e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 
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-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 0.000000e+00 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 0.000000e+00 2.115234e-06 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 0.000000e+00 2.115234e-06 -1.595703e-06 
-1.595703e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 -1.595703e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -3.451172e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 -1.595703e-06 -1.458398e-05 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 2.597656e-07 2.115234e-06 2.597656e-07 2.115234e-06 -1.829492e-05 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.115234e-06 -1.643945e-05 2.115234e-06 2.115234e-06 2.597656e-07 2.597656e-07 -1.595703e-06 2.115234e-06 -1.595703e-06 2.597656e-07 2.597656e-07 2.115234e-06 2.115234e-06 2.115234e-06 0.000000e+00 -1.595703e-06 
-4.238279e-07 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 2.603516e-06 -1.595703e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 1.431641e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -3.451172e-06 4.458985e-06 2.565039e-05 -1.595703e-06 -1.595703e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -3.451172e-06 1.431641e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 1.431641e-06 -1.595703e-06 -1.712305e-05 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -1.595703e-06 2.379492e-05 -1.595703e-06 -1.595703e-06 1.431641e-06 1.431641e-06 4.458985e-06 -1.595703e-06 -4.238279e-07 1.431641e-06 -3.451172e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 -1.595703e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/ss-s003_a.txt
================================================
2.78e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.78e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ss-s003_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ss-s003
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 3 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.82 s
Mean overlap 0.978 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ss-s003_mclassic.txt
================================================
 0.943  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.967  1.001 
 0.967  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.943  1.001 
 0.967  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 


================================================
FILE: hippocampus/out/sweep/ss-s003_mcustom.txt
================================================
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 


================================================
FILE: hippocampus/out/sweep/ss-s003_params.txt
================================================
seed             = 45440214

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 3
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ss-s003_qcue.txt
================================================
0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 1 4 7 2 5 8 0 3 6 

================================================
FILE: hippocampus/out/sweep/ss-s003_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ss-s003_qnu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ss-s003_wsample.txt
================================================
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-2.931641e-06 -2.931641e-06 7.517579e-06 7.792967e-07 2.634765e-06 5.662109e-06 3.806641e-06 2.634765e-06 3.806641e-06 4.490234e-06 4.490234e-06 1.951172e-06 7.792967e-07 2.634765e-06 7.792967e-07 2.634765e-06 7.792967e-07 7.792967e-07 7.792967e-07 7.792967e-07 -1.076172e-06 4.490234e-06 -1.076172e-06 4.490234e-06 4.490234e-06 3.806641e-06 7.792967e-07 2.634765e-06 -1.406445e-05 2.634765e-06 2.634765e-06 7.517579e-06 -1.591992e-05 2.634765e-06 2.919727e-05 4.490234e-06 -1.777539e-05 4.490234e-06 7.792967e-07 2.634765e-06 2.634765e-06 3.806641e-06 -1.076172e-06 2.634765e-06 7.792967e-07 -1.076172e-06 2.634765e-06 2.634765e-06 2.634765e-06 2.634765e-06 1.951172e-06 2.634765e-06 7.792967e-07 2.634765e-06 2.634765e-06 -4.787110e-06 -1.591992e-05 4.490234e-06 7.517579e-06 7.792967e-07 2.634765e-06 -1.963086e-05 2.634765e-06 2.634765e-06 1.951172e-06 2.616992e-05 4.490234e-06 2.634765e-06 -1.591992e-05 4.490234e-06 -1.076172e-06 -1.406445e-05 -1.474805e-05 4.490234e-06 2.634765e-06 7.517579e-06 -2.931641e-06 7.517579e-06 4.490234e-06 2.634765e-06 4.490234e-06 5.662109e-06 -3.615235e-06 9.570294e-08 2.634765e-06 -2.773633e-05 -1.220898e-05 2.634765e-06 2.634765e-06 1.951172e-06 -1.963086e-05 4.490234e-06 -1.076172e-06 5.662109e-06 7.792967e-07 2.634765e-06 -1.076172e-06 2.634765e-06 0.000000e+00 1.951172e-06 
-3.615234e-06 1.267578e-06 1.951172e-06 9.570317e-08 1.951172e-06 4.978516e-06 3.123047e-06 -2.931641e-06 3.123047e-06 -1.076172e-06 -1.076172e-06 1.267578e-06 4.978516e-06 -2.931641e-06 -4.787110e-06 1.951172e-06 -4.787110e-06 -4.787110e-06 9.570317e-08 -4.787110e-06 3.123047e-06 -1.076172e-06 -1.759766e-06 -1.076172e-06 -1.076172e-06 8.005860e-06 -4.787110e-06 -2.931641e-06 -1.474805e-05 1.951172e-06 -2.931641e-06 1.951172e-06 2.734180e-05 -2.931641e-06 2.851367e-05 -1.076172e-06 -1.845898e-05 -1.076172e-06 -4.787110e-06 -2.931641e-06 -2.931641e-06 3.123047e-06 3.123047e-06 -2.931641e-06 -4.787110e-06 3.123047e-06 -2.931641e-06 -2.931641e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 -2.931641e-06 4.978516e-06 -2.931641e-06 -2.931641e-06 -5.878903e-07 2.245899e-05 -1.076172e-06 1.951172e-06 4.978516e-06 -2.931641e-06 -2.031445e-05 -2.931641e-06 -2.931641e-06 6.150391e-06 2.548633e-05 -1.076172e-06 -2.931641e-06 -1.660352e-05 -1.076172e-06 -1.759766e-06 -1.963086e-05 -1.543164e-05 -1.076172e-06 -2.931641e-06 1.951172e-06 -3.615234e-06 1.951172e-06 -1.076172e-06 1.951172e-06 -1.076172e-06 9.570317e-08 -4.298828e-06 -5.878904e-07 -2.931641e-06 1.064258e-05 -1.777539e-05 1.951172e-06 1.951172e-06 1.267578e-06 -1.543164e-05 -1.076172e-06 -1.759766e-06 4.978516e-06 -4.787110e-06 -2.931641e-06 -1.759766e-06 -2.931641e-06 1.951172e-06 0.000000e+00 


================================================
FILE: hippocampus/out/sweep/ss-s010_a.txt
================================================
2.78e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.78e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.78e-02 2.00e-02 
2.78e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ss-s010_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ss-s010
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 10 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.81 s
Mean overlap 0.980 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ss-s010_mclassic.txt
================================================
 0.943  1.001 
 0.991  1.001 
 0.991  1.001 
 0.943  1.001 
 0.991  1.001 
 0.967  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.943  1.001 
 0.943  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 


================================================
FILE: hippocampus/out/sweep/ss-s010_mcustom.txt
================================================
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 


================================================
FILE: hippocampus/out/sweep/ss-s010_params.txt
================================================
seed             = 45451958

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 10
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ss-s010_qcue.txt
================================================
0 10 20 1 11 21 2 12 22 3 13 23 4 14 24 5 15 25 6 16 26 7 17 27 8 18 28 9 19 29 

================================================
FILE: hippocampus/out/sweep/ss-s010_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ss-s010_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 

================================================
FILE: hippocampus/out/sweep/ss-s010_wsample.txt
================================================
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================================================
FILE: hippocampus/out/sweep/ss-s030_a.txt
================================================
2.78e-02 2.00e-02 
2.88e-02 2.00e-02 
2.78e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.69e-02 2.00e-02 
2.88e-02 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ss-s030_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ss-s030
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 30 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.82 s
Mean overlap 0.978 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ss-s030_mclassic.txt
================================================
 0.943  1.001 
 0.967  1.001 
 0.943  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.919  1.001 
 0.967  1.001 


================================================
FILE: hippocampus/out/sweep/ss-s030_mcustom.txt
================================================
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 


================================================
FILE: hippocampus/out/sweep/ss-s030_params.txt
================================================
seed             = 45596022

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 30
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ss-s030_qcue.txt
================================================
0 30 60 1 31 61 2 32 62 3 33 63 4 34 64 5 35 65 6 36 66 7 37 67 8 38 68 9 39 69 

================================================
FILE: hippocampus/out/sweep/ss-s030_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ss-s030_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 

================================================
FILE: hippocampus/out/sweep/ss-s030_wsample.txt
================================================
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-1.769531e-05 2.195312e-05 1.130860e-05 3.347656e-05 -1.046874e-05 9.941414e-06 4.949220e-05 -5.666017e-05 -9.296866e-06 -7.570315e-05 -1.691406e-05 1.542976e-06 3.787109e-05 -1.134765e-05 -3.810548e-05 7.597664e-06 1.257812e-05 -1.466797e-05 -6.074212e-06 -1.271483e-05 -2.167963e-06 -1.164062e-05 1.560547e-05 -2.628906e-05 -1.271486e-05 -4.552735e-05 -4.416014e-05 1.482423e-05 -1.720702e-05 -2.833983e-05 -6.291016e-05 1.072267e-05 -4.201171e-05 2.302735e-05 2.283203e-05 -3.185546e-05 -5.158204e-05 -1.330078e-05 -3.458983e-05 -4.826173e-05 7.597657e-06 3.175585e-04 -2.443358e-05 -2.375000e-05 -9.589843e-06 -3.925779e-06 3.064453e-05 6.328126e-06 -5.060546e-05 -6.339845e-05 7.742186e-05 5.652344e-05 3.591795e-05 1.023438e-05 3.738282e-05 -3.742187e-05 -3.205077e-05 -3.124967e-07 6.160157e-05 -3.371094e-05 4.783202e-05 2.078126e-05 2.507813e-05 1.267579e-05 3.477343e-04 -4.923827e-05 -2.248049e-05 -3.339845e-06 -1.466796e-05 -9.960941e-07 -9.785151e-06 -4.757813e-05 -5.382812e-05 3.308594e-05 4.177734e-05 1.335938e-05 6.707032e-05 -3.878905e-05 1.082032e-05 -1.828128e-05 1.941407e-05 1.082031e-05 -2.462890e-05 -1.837891e-05 -5.714844e-05 -4.855467e-05 -2.833983e-05 2.156250e-05 -9.492202e-06 -3.576173e-05 2.742188e-05 1.013672e-05 -3.136718e-05 -1.701171e-05 1.542974e-06 -3.124933e-07 1.179688e-05 0.000000e+00 -1.906250e-05 5.546881e-06 
4.001953e-05 5.037109e-05 -9.101560e-06 5.212891e-05 -4.552734e-05 4.324217e-05 4.667971e-06 8.406250e-05 -3.947265e-05 -2.775391e-05 -3.244141e-05 -4.218747e-06 -2.160156e-05 -6.105469e-05 -4.875001e-05 -3.046873e-06 -6.154297e-05 8.867190e-06 2.234375e-05 -6.730467e-05 2.625000e-05 -4.669921e-05 1.960937e-05 -3.693360e-05 -8.710929e-06 5.613281e-05 5.750001e-05 -1.046875e-05 -1.808593e-05 -4.874999e-05 -6.378906e-05 4.402343e-05 -7.707031e-05 -4.621093e-05 -7.343753e-06 -4.249999e-05 -3.632817e-06 -2.882812e-05 -2.570311e-05 3.951952e-04 -1.769531e-05 -8.371093e-05 -5.781241e-06 1.443360e-05 -5.585935e-06 -3.410155e-05 1.511718e-05 5.449216e-06 -6.613281e-05 8.964840e-06 -3.576173e-05 -1.759765e-05 2.039063e-05 3.865235e-05 3.650391e-05 -1.876952e-05 -5.246094e-05 -2.072265e-05 -3.693359e-05 -3.458983e-05 3.230469e-05 -4.357424e-05 1.931639e-05 2.031256e-06 3.273241e-04 7.683594e-05 3.965624e-04 -9.101559e-06 -2.531250e-05 3.007817e-06 8.867190e-06 2.478515e-05 4.783204e-05 4.685546e-05 -1.281249e-05 1.248048e-05 1.248046e-05 2.869139e-05 -9.589843e-06 3.568163e-04 -5.878901e-06 1.757835e-07 1.843751e-05 1.003907e-05 -2.384765e-05 4.277363e-06 9.843763e-06 1.152352e-06 -6.054652e-07 -1.222658e-05 7.011724e-06 -1.515625e-05 4.587891e-05 3.093749e-05 -4.218749e-06 -1.583984e-05 3.044922e-05 -1.906250e-05 0.000000e+00 -2.148413e-07 
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================================================
FILE: hippocampus/out/sweep/ss-s100_a.txt
================================================
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 
2.88e-02 2.00e-02 
2.98e-02 2.00e-02 
2.98e-02 2.00e-02 


================================================
FILE: hippocampus/out/sweep/ss-s100_log.txt
================================================

STARTING SIMULATION FOR out/sweep/ss-s100
Pattern directory contains 2048 neurons, 3 categories, and 512 examples
Sparsenseses detected: 0.020 and 0.200

STARTING NETWORK SETUP
Storing 3 categories with 100 examples
Testing 30 cues

STARTING FINAL SIMULATION
Done in 0.80 s
Mean overlap 0.985 --> 1.001

SIMULATION COMPLETE



================================================
FILE: hippocampus/out/sweep/ss-s100_mclassic.txt
================================================
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.991  1.001 
 0.967  1.001 
 0.991  1.001 
 0.991  1.001 


================================================
FILE: hippocampus/out/sweep/ss-s100_mcustom.txt
================================================
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 
 0.512  1.000 


================================================
FILE: hippocampus/out/sweep/ss-s100_params.txt
================================================
seed             = 45381270

T_sim            = 10
T_rec            = 10
update_type      = 1

N                = 2048
p                = 3
s                = 100
gamma            = 0.050000
beta             = 100.000000

X_dir            = out/pathways/N2048-p3-s512-a02-2
shuffle_patterns = 0
n_cue            = 30
cue_type         = 0
target_type      = 0
incomp           = 0.000000
inacc            = 0.010000

search           = 0
criterion_type   = 0
theta_mid        = 0.500000
n_round          = 2
n_value          = 4
T_search         = 3
n_search         = 20


================================================
FILE: hippocampus/out/sweep/ss-s100_qcue.txt
================================================
0 100 200 1 101 201 2 102 202 3 103 203 4 104 204 5 105 205 6 106 206 7 107 207 8 108 208 9 109 209 

================================================
FILE: hippocampus/out/sweep/ss-s100_qmu.txt
================================================
0 1 2 

================================================
FILE: hippocampus/out/sweep/ss-s100_qnu.txt
================================================
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 

================================================
FILE: hippocampus/out/sweep/ss-s100_wsample.txt
================================================
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================================================
FILE: hippocampus/src/compile.sh
================================================
#!/bin/bash
if [[ $# -ne 1 ]]; then
  echo "Error: one argument required (e.g. ./compile.sh search.c)"
  exit 1
fi


args=" -DMKL_ILP64 -m64 -I\"${MKLROOT}/include\""
if [[ $(uname -s) == "Darwin" ]]
then
  args+=" -L${MKLROOT}/lib -Wl,-rpath,${MKLROOT}/lib -lmkl_intel_ilp64 -lmkl_sequential -lmkl_core -lpthread -lm -ldl"
else
  args+=" -L${MKLROOT}/lib/intel64 -Wl,--no-as-needed -lmkl_intel_ilp64 -lmkl_sequential -lmkl_core -lpthread -lm -ldl"
  args+=" -Wno-format-overflow"
fi

gcc -o "${1/%.c/.o}" "$1" -march=native -mtune=native -Ofast $args


================================================
FILE: hippocampus/src/dynamics.c
================================================
/*******************************************************************************
 *
 *  FILE:         dynamics.c
 *
 *  DATE:         24 February 2023
 *
 *  AUTHOR:       Louis Kang
 *
 *  LICENSE:      GPLv3
 *
 *  REFERENCE:    To be determined
 *
 *  PURPOSE:      Simulating a Hopfield model with dual encodings. The
 *                inhibition level can vary over time.
 *
 *  DEPENDENCIES: Intel Math Kernel Library
 *
 *******************************************************************************
 *
 *  NOTE:  Only differences between this code and search.c are commented here. 
 *         See search.c for much more explanation.
 *
 ******************************************************************************/

#include <stdlib.h>
#include <stdio.h>
#include <stdarg.h>
#include <stdint.h>
#include <math.h>
#include <string.h>
#include <time.h>
#include <unistd.h>
#include <fcntl.h>

#include "mkl.h"

//==============================================================================
// Parameters and global variables
//==============================================================================


// Random ----------------------------------------------------------------------
uint32_t r4seed = 0;
#define RUNI r4_uni(&r4seed)

// Iterations and time ---------------------------------------------------------
int T_sim = 100;
int T_rec = 10;
int T_subcycle = 0;
enum sequence_type {sequential, block_random, full_random};
enum sequence_type update_type = block_random;

// Network ---------------------------------------------------------------------
int N;
int p = 1;        
int s = 10;      
int N_bin;
int p_max;
int s_max;
float g = 0.1;
float beta = 0.;
float a_sparse;
float a_dense;
float a_fac;

float *w;
float f = 0.;     // strength of cue as input during retrieval

// Theta -----------------------------------------------------------------------
float *theta;
enum function_type {ramp, sine, square, file};
enum function_type theta_type = ramp;
float theta_start = 0.6;
float theta_end = 0.6;
int T_theta = 6;
char theta_name[256];
int cycle_theta = 0;

// Pattern ---------------------------------------------------------------------
char X_dir[256] = "";
int n_cue = 100;        
enum pattern_type {sparse, dense, cat};
float incomp = 0.;
float inacc = 0.;

int sparse_file, dense_file, cat_file;
int *q_mu, *q_nu, *q_cue;
int mu_cue, nu_cue;
unsigned char ***X_sparse, **X_dense, **X_cat;
unsigned char *X_cue, *X_bin;

// Recording -------------------------------------------------------------------
FILE *S_file, *a_file;
FILE *overlap_sparse_file, *overlap_cat_file, *overlap_other_file;
unsigned char *S_bin;
double *overlap_smean, *overlap_cmean;

enum overlap_type {classic, custom};
enum overlap_type record_type = classic;

// I/O -------------------------------------------------------------------------
char fileroot[256] = "";
int save_activity = 0;
int stat_screen = 1;
int stat_log = 1;
FILE *stat_file;

//==============================================================================
// END Parameters and global variables
//==============================================================================



//==============================================================================
// I/O utility functions
//==============================================================================

void print_screen (char *format, ...) {
  
  va_list args1;

  va_start(args1, format);

  if (stat_screen) {
    vprintf(format, args1);
    fflush(stdout);
  }

  va_end(args1);

}


void clear_screen() {

  print_screen("                                                  \r");

}


void print_stat (char *format, ...) {
  
  va_list args1, args2;

  va_start(args1, format);
  va_copy(args2, args1);

  if (stat_screen) {
    vprintf(format, args1);
    fflush(stdout);
  }

  if (stat_log) {
    vfprintf(stat_file, format, args2);
    fflush(stat_file);
  }

  va_end(args1);
  va_end(args2);

}


void print_err (char *format, ...) {
  
  va_list args1, args2;

  va_start(args1, format);
  va_copy(args2, args1);

  vfprintf(stderr, format, args1);
  fflush(stderr);

  if (stat_log) {
    vfprintf(stat_file, format, args2);
    fflush(stat_file);
  }

  va_end(args1);
  va_end(args2);

}


static inline unsigned char rotl (unsigned char c, unsigned int n) {

  n &= 7;
  return (c << n) | (c >> ((-n) & 7));

}

static inline unsigned char rotr (unsigned char c, unsigned int n) {

  n &= 7;
  return (c >> n) | (c << ((-n) & 7));

}

void compress_binary_char (
    unsigned char *raw, unsigned char *bin, int n_raw
) {

  int i;

  for (i = 0; i < n_raw; i += 8)
    bin[i/8] = 0;

  for (i = 0; i < n_raw; i++)
    bin[i/8] |= raw[i] << (7 - (i % 8));

}

void uncompress_binary_char (
    unsigned char *bin, unsigned char *raw, int n_raw
) {

  int i;

  for (i = 0; i < n_raw; i++) {
    bin[i/8] = rotl(bin[i/8], 1);  
    raw[i] = bin[i/8] & 1;
  }

}

void output_int_list(int *list, int n, char *extname) {

  char name[256];
  FILE *file;
  int i;

  sprintf(name, "%s_%s.txt", fileroot, extname);
  file = fopen(name, "w");

  for (i = 0; i < n; i++)
    fprintf(file, "%d ", list[i]); 

  fclose(file);

}

void output_float_list(float *list, int n, char *extname) {

  char name[256];
  FILE *file;
  int i;

  sprintf(name, "%s_%s.txt", fileroot, extname);
  file = fopen(name, "w");

  for (i = 0; i < n; i++)
    fprintf(file, "%f ", list[i]); 

  fclose(file);

}

void output_float_array(float **arr, int ni, int nj, char *extname) {

  char name[256];
  FILE *file;
  int i, j;

  sprintf(name, "%s_%s.txt", fileroot, extname);
  file = fopen(name, "w");

  for (i = 0; i < ni; i++) {
    for (j = 0; j < nj; j++) 
      fprintf(file, "%e ", arr[i][j]); 
    fprintf(file, "\n");
  }
  fclose(file);

}

void output_float_1darray(float *arr, int ni, int nj, int incj, char *extname) {

  char name[256];
  FILE *file;
  int i, j;

  sprintf(name, "%s_%s.txt", fileroot, extname);
  file = fopen(name, "w");

  for (i = 0; i < ni; i++) {
    for (j = 0; j < nj; j++) 
      fprintf(file, "%e ", arr[i*incj+j]); 
    fprintf(file, "\n");
  }
  fclose(file);

}

//==============================================================================
// END I/O utility functions
//==============================================================================



//==============================================================================
// Math utility functions
//==============================================================================

static inline int fmini (int a, int b) {

  return (a < b) ? a : b;

}

static inline int fmaxi (int a, int b) {

  return (a > b) ? a : b;
}

static inline unsigned char step (float a) { 
  
  return a < 0. ? 0 : 1;

} 

static inline void swap (int *a, int *b) { 

    int temp;

    temp = *a; 
    *a = *b; 
    *b = temp; 

} 


float r4_uni (uint32_t *jsr) {

  uint32_t jsr_input;
  float value;

  jsr_input = *jsr;

  *jsr = ( *jsr ^ ( *jsr <<   13 ) );
  *jsr = ( *jsr ^ ( *jsr >>   17 ) );
  *jsr = ( *jsr ^ ( *jsr <<    5 ) );

  value = fmod ( 0.5 
    + ( float ) ( jsr_input + *jsr ) / 65536.0 / 65536.0, 1.0 );

  return value;
}

void permutation (int n, int *arr) {
  
  int i, j;

  for (i = 0; i < n; i++)
    arr[i] = i;

  for (i = n-1; i > 0; i--) {
    j = (int) ((double)RUNI * (i+1));
    swap(&arr[i], &arr[j]);
  }

}

void sample (int n_pop, int n_samp, int *arr) {

  int i_pop = 0;
  int i_samp = 0;

  if (n_samp > n_pop) {

    print_err("Error: n_samp cannot be greater than n_pop ");
    print_err("in sample function\n");
    exit(1);

  } else if (n_samp == n_pop) {

     for (i_samp = 0; i_samp < n_samp; i_samp++)
       arr[i_samp] = i_samp;

  } else {

    while (i_samp < n_samp) {
      if ( (n_pop-i_pop) * RUNI >= n_samp-i_samp )
        i_pop++;
      else {
        arr[i_samp] = i_pop;
        i_pop++; i_samp++;
      }
    }

  }

}

//==============================================================================
// END Math utility functions
//==============================================================================



//==============================================================================
// Parameters
//==============================================================================

void read_parameters (int argc, char *argv[]) {

  int narg = 1;

  while (narg < argc) {
    if (!strcmp(argv[narg],"-fileroot")) {
      sscanf(argv[narg+1],"%s",fileroot);
      narg += 2;
    } else if (!strcmp(argv[narg],"-seed")) {
      sscanf(argv[narg+1],"%d",&r4seed);
      narg += 2;
    } 

    else if (!strcmp(argv[narg],"-T_sim")) {
      sscanf(argv[narg+1],"%d",&T_sim);
      narg += 2;
    } else if (!strcmp(argv[narg],"-T_rec")) {
      sscanf(argv[narg+1],"%d",&T_rec);
      narg += 2;
    } else if (!strcmp(argv[narg],"-sequential")) {
      update_type = sequential;
      narg++;
    } else if (!strcmp(argv[narg],"-block_random")) {
      update_type = block_random;
      narg++;
    } else if (!strcmp(argv[narg],"-full_random")) {
      update_type = full_random;
      narg++;
    }

    else if (!strcmp(argv[narg],"-N")) {
      sscanf(argv[narg+1],"%d",&N);
      narg += 2;
    } else if (!strcmp(argv[narg],"-p")) {
      sscanf(argv[narg+1],"%d",&p);
      narg += 2;
    } else if (!strcmp(argv[narg],"-s")) {
      sscanf(argv[narg+1],"%d",&s);
      narg += 2;
    } else if (!strcmp(argv[narg],"-gamma")) {
      sscanf(argv[narg+1],"%f",&g);
      narg += 2;
    } else if (!strcmp(argv[narg],"-beta")) {
      sscanf(argv[narg+1],"%f",&beta);
      narg += 2;
    } else if (!strcmp(argv[narg],"-field")) {
      sscanf(argv[narg+1],"%f",&f);
      narg += 2;
    } else if (!strcmp(argv[narg],"-ramp")) {
      theta_type = ramp;
      narg++;
    } else if (!strcmp(argv[narg],"-sine")) {
      theta_type = sine;
      narg++;
    } else if (!strcmp(argv[narg],"-square")) {
      theta_type = square;
      narg++;
    } else if (!strcmp(argv[narg],"-theta_range")) {
      sscanf(argv[narg+1],"%f",&theta_start);
      sscanf(argv[narg+2],"%f",&theta_end);
      sscanf(argv[narg+3],"%d",&T_theta);
      narg += 4;
    } else if (!strcmp(argv[narg],"-theta_file")) {
      sscanf(argv[narg+1],"%s",theta_name);
      theta_type = file;
      narg += 2;
    } else if (!strcmp(argv[narg],"-cycle_theta")) {
      cycle_theta = 1;
      narg++;
    }

    else if (!strcmp(argv[narg],"-X_dir")) {
      sscanf(argv[narg+1],"%s",X_dir);
      narg += 2;
    } else if (!strcmp(argv[narg],"-n_cue")) {
      sscanf(argv[narg+1],"%d",&n_cue);
      narg += 2;
    } else if (!strcmp(argv[narg],"-incomp")) {
      sscanf(argv[narg+1],"%f",&incomp);
      narg += 2;
    } else if (!strcmp(argv[narg],"-inacc")) {
      sscanf(argv[narg+1],"%f",&inacc);
      narg += 2;
    } else if (!strcmp(argv[narg],"-single_flip")) {
      inacc = -1.;
      narg++;
    } else if (!strcmp(argv[narg],"-noiseless")) {
      incomp = 0.;
      inacc = 0.;
      narg++;
    }

    else if (!strcmp(argv[narg],"-verbose")) {
      stat_screen = 1;
      narg++;
    } else if (!strcmp(argv[narg],"-quiet")) {
      stat_screen = 0;
      narg++;
    } else if (!strcmp(argv[narg],"-no_log")) {
      stat_log = 0;
      narg++;
    }

    else if (!strcmp(argv[narg],"-save_activity")) {
      save_activity = 1;
      narg++;
    } else if (!strcmp(argv[narg],"-no_activity")) {
      save_activity = 0;
      narg++;
    } else if (!strcmp(argv[narg],"-custom_overlap")) {
      record_type = custom;
      narg++;
    } else if (!strcmp(argv[narg],"-classic_overlap")) {
      record_type = classic;
      narg++;
    }


    else {
      fprintf(stderr, "unknown option: %s\n", argv[narg]);
      fflush(stderr);
      exit(1);
    }
  }  

}


void print_parameters () {

  FILE *file;
  char name[256];

  sprintf(name, "%s_params.txt", fileroot);
  file = fopen(name, "w");

  fprintf(file, "seed            = %d\n", r4seed);

  fprintf(file, "\n");
  fprintf(file, "T_sim           = %d\n", T_sim);
  fprintf(file, "T_rec           = %d\n", T_rec);
  fprintf(file, "update_type     = %d\n", update_type);

  fprintf(file, "\n");
  fprintf(file, "N               = %d\n", N);
  fprintf(file, "p               = %d\n", p);
  fprintf(file, "s               = %d\n", s);
  fprintf(file, "gamma           = %f\n", g);
  fprintf(file, "beta            = %f\n", beta);
  fprintf(file, "field           = %f\n", f);

  fprintf(file, "\n");
  fprintf(file, "theta_type      = %d\n", theta_type);
  fprintf(file, "theta_start     = %f\n", theta_start);
  fprintf(file, "theta_end       = %f\n", theta_end);
  fprintf(file, "T_theta         = %d\n", T_theta);
  fprintf(file, "theta_file      = %s\n", theta_name);
  fprintf(file, "cycle_theta     = %d\n", cycle_theta);

  fprintf(file, "\n");
  fprintf(file, "X_dir           = %s\n", X_dir);
  fprintf(file, "n_cue           = %d\n", n_cue);
  fprintf(file, "incomp          = %f\n", incomp);
  fprintf(file, "inacc           = %f\n", inacc);
  fprintf(file, "record_type     = %d\n", record_type);

  fclose(file);

}


void setup_parameters (int argc, char *argv[]) {
  
  char name[256];
  char *token;
  char a_buf[16];
  int ch, place;


  read_parameters(argc, argv);


  if (strcmp(fileroot, "") == 0 ||
      fileroot[0] == '-' ||
      fileroot[strlen(fileroot)-1] == '/') {
    fprintf(stderr, "Must set -fileroot correctly\n");
    fflush(stderr);
    exit(1);
  }
  if (stat_log) {
    sprintf(name, "%s_log.txt", fileroot);
    stat_file = fopen(name, "w");
  }


  print_stat("\nSTARTING SIMULATION FOR %s\n", fileroot);


  if (X_dir[strlen(X_dir)-1] == '/')
    X_dir[strlen(X_dir)-1] = '\0';
  
  strcpy(name, X_dir);
  token = strtok(name, "/-_.");
  while (token != NULL) {
    if (strlen(token) > 1 && token[1] >= '0' && token[1] <= '9') {
      if (token[0] == 'N')
        sscanf(token, "N%d", &N);
      else if (token[0] == 'p')
        sscanf(token, "p%d", &p_max);
      else if (token[0] == 's')
        sscanf(token, "s%d", &s_max);
      else if (token[0] == 'a') {
        sprintf(a_buf, "0.%s", token+1);
        a_sparse = strtof(a_buf, NULL);
        token = strtok(NULL, "/-.");
        sprintf(a_buf, "0.%s", token);
        a_dense = strtof(a_buf, NULL);
      }
    }
    token = strtok(NULL, "/-_.");
  }
  if (N == 0 || p_max == 0 || s_max == 0) {
    print_err("Error: pattern directory name %s must contain numbers ", X_dir);
    print_err("of neurons, categories, and examples\n");
    exit(1);
  } else if (p > p_max) {
    print_err("Error: requested categories %d exceeds maximum %d\n", p, p_max);
    exit(1);
  } else if (s > s_max) {
    print_err("Error: requested examples %d exceeds maximum %d\n", s, s_max);
    exit(1);
  } else {
    print_stat("Pattern directory contains %d neurons, ", N);
    print_stat("%d categories, and %d examples\n", p_max, s_max);
  }
  if (a_sparse == 0. || a_dense == 0.) {
    print_err("Error: pattern directory name %s must contain ", X_dir);
    print_err("sparsenesses\n");
    exit(1);
  } else {
    print_stat("Sparsenesses detected: %4.3f and %4.3f\n", a_sparse, a_dense);
  }


  if (r4seed == 0) {
    r4seed = (uint32_t)(time(NULL) % 1048576);
    place = 1;
    for (ch = 0; ch < strlen(fileroot); ch++) {
      r4seed += fileroot[ch] * place;
      place = (place * 128) % 100000;
    }
  }

  N_bin = (N-1)/8 + 1;


  print_parameters();

}

//==============================================================================
// END Parameters
//==============================================================================



//==============================================================================
// Setup
//==============================================================================

void read_pattern (unsigned char *X, int file, int mu, int nu) {

  int q;

  if (nu >= 0)
    q = q_mu[mu]*s_max + q_nu[nu];
  else
    q = q_mu[mu];

  if (pread(file, X_bin, N_bin, (long int) q*N_bin) != N_bin) {
    print_err("Error: pattern file too short\n");
    exit(1);
  };
  uncompress_binary_char(X_bin, X, N);

}


void setup_patterns () {

  float *X_combo;
  char sname[256], dname[256], cname[256];

  int i, j, mu, nu;


  print_stat("Storing %d categories with %d examples\n", p, s);

  sprintf(sname, "%s/x_sparse.dat", X_dir);
  sprintf(dname, "%s/x_dense.dat" , X_dir);
  sprintf(cname, "%s/x_cat.dat"   , X_dir);
  if ((sparse_file = open(sname, O_RDONLY)) < 0 ||
      (dense_file  = open(dname, O_RDONLY)) < 0 ||
      (cat_file    = open(cname, O_RDONLY)) < 0   ) {
    print_err("Error opening pattern files in directory %s\n", X_dir);
    exit(1);
  }


  q_mu = malloc(p * sizeof(int));
  sample(p_max, p, q_mu);
  output_int_list(q_mu, p, "qmu");

  q_nu = malloc(s * sizeof(int));
  sample(s_max, s, q_nu);
  output_int_list(q_nu, s, "qnu");


  X_bin = malloc(N_bin * sizeof(char));
  X_cue = malloc(N * sizeof(char));

  X_sparse = malloc(p * sizeof(char **));
  for (mu = 0; mu < p; mu++) {
    X_sparse[mu] = malloc(s * sizeof(char *));
    for (nu = 0; nu < s; nu++)
      X_sparse[mu][nu] = malloc(N * sizeof(char));
  }
  X_dense = malloc(s * sizeof(char *));
  for (nu = 0; nu < s; nu++)
    X_dense[nu] = malloc(N * sizeof(char));
  X_cat = malloc(p * sizeof(char *));
  for (mu = 0; mu < p; mu++)
    X_cat[mu] = malloc(N * sizeof(char));

  X_combo = mkl_malloc(s*N * sizeof(float), 64);
  w = mkl_calloc(N*N, sizeof(float *), 64);


  for (mu = 0; mu < p; mu++) {

    print_screen("%3d/%3d categories stored...\r", mu, p);

    read_pattern(X_cat[mu], cat_file, mu, -1);

    for (nu = 0; nu < s; nu++) {

      read_pattern(X_sparse[mu][nu], sparse_file, mu, nu);
      read_pattern(X_dense     [nu], dense_file , mu, nu);

    }

    for (nu = 0; nu < s; nu++)
      for (i = 0; i < N; i++)
        X_combo[nu*N+i] =   (1.-2.*g) * (X_sparse[mu][nu][i] - a_sparse)
                          + (   2.*g) * (X_dense     [nu][i] - a_dense );

    cblas_ssyrk(CblasRowMajor, CblasUpper, CblasTrans,
                N, s, 1./N, X_combo, N, 1., w, N     );

  } 

  clear_screen();

  for (i = 0; i < N; i++) {
    w[i*N+i] = 0.;
    for (j = i; j < N; j++)
      w[j*N+i] = w[i*N+j];
  }
 
  output_float_1darray(w, fmini(N,100), fmini(N,100), N, "wsample");

  free(X_bin);
  for (nu = 0; nu < s; nu++)
    free(X_dense[nu]);
  free(X_dense);
  mkl_free(X_combo);

  close(sparse_file);
  close(dense_file);
  close(cat_file);
  

  a_fac = (1.-2.*g)*(1.-2.*g) * a_sparse;
  beta /= a_fac;

}


void setup_network_shared () {

  char name[256];
  int i_rec, i_cue;
 

  if (T_rec > 0) {
    T_subcycle = N;
    T_rec = fmini(T_rec, T_sim);
  } else if (T_rec < 0) {
    T_subcycle = N / (-T_rec);
    T_rec = 1;
  } else {
    T_subcycle = N;
    T_rec = T_sim;
  }

  if (save_activity) {
    S_bin = malloc(N_bin * sizeof(char));
    sprintf(name, "%s_s.dat", fileroot);
    S_file = fopen(name, "wb");
  }
  sprintf(name, "%s_a.txt", fileroot);
  a_file = fopen(name, "w");
  sprintf(name, "%s_msparse.txt", fileroot);
  overlap_sparse_file = fopen(name, "w");
  sprintf(name, "%s_mcategory.txt", fileroot);
  overlap_cat_file = fopen(name, "w");
  sprintf(name, "%s_mother.txt", fileroot);
  overlap_other_file = fopen(name, "w");


  print_stat("Testing %d cues\n", n_cue);
  q_cue = malloc(n_cue * sizeof(int));

  sample(p*s, fmini(n_cue, p*s), q_cue);
  for (i_cue = p*s; i_cue < n_cue; i_cue++)
    q_cue[i_cue] = q_cue[i_cue%(p*s)];

  output_int_list(q_cue, n_cue, "qcue");

  
  overlap_smean = calloc(T_sim+1, sizeof(double));
  overlap_cmean = calloc(T_sim+1, sizeof(double));

} 

void setup_network_private (unsigned char **S, int **q_update) {

  int t_cycle;

  *S = malloc(N * sizeof(char));

  *q_update = malloc(N * sizeof(int));
  for (t_cycle = 0; t_cycle < N; t_cycle++)
    (*q_update)[t_cycle] = t_cycle;
   
} 

void cleanup_shared () {

  fclose(stat_file);

  if (save_activity)
    fclose(S_file);
  fclose(a_file);
  fclose(overlap_sparse_file);
  fclose(overlap_cat_file);
  fclose(overlap_other_file);

  free(overlap_smean);
  free(overlap_cmean);

}

void cleanup_private (unsigned char *S, int *q_update) {

  free(S);
  free(q_update);

}

//==============================================================================
// END Setup
//==============================================================================



//==============================================================================
// Theta
//==============================================================================

// Linearly interpolate between theta_start and theta_end over T_theta update
// cycles. Then maintain theta at theta_end.
void ramp_theta () {

  int t;
  float tt;

  for (t = 0; t < T_theta; t++) {
    tt = (float)t / T_theta;
    theta[t] = theta_start + (theta_end-theta_start) * tt;
  }
  for (; t < T_sim; t++)
    theta[t] = theta_end;

}

// Sinusoidal theta oscillation
void sine_theta () {

  int t;
  float tt;

  for (t = 0; t < T_theta; t++) {
    tt = (float)t / T_theta;
    theta[t] = theta_end + (theta_start-theta_end)
                                * (cos(2.*M_PI*tt) + 1.) / 2.;
  }
  for (; t < T_sim; t++)
    theta[t] = theta[t%T_theta];

}

// Sharply varying theta oscillation
void square_theta () {

  int t;

  for (t = 0; t < T_theta; t++)
    theta[t] = theta_start + (theta_end-theta_start) * (t/(T_theta/2));
  for (; t < T_sim; t++)
    theta[t] = theta[t%T_theta];

}

// Read in external file specifying theta for each update cycle
void read_theta () {

  FILE *file;
  int t;

  if ((file = fopen(theta_name, "r")) == NULL) {
    print_err("Error opening theta file %s\n", theta_name);
    exit(1);
  }

  for (t = 0; t < T_sim; t++)
    if (fscanf(file, "%f", &theta[t]) != 1)
      break;

  if (t == 0) {
    print_err("Error reading theta file\n");
    exit(1);
  }

  T_theta = t;
  if (cycle_theta)
    for (; t < T_sim; t++) 
      theta[t] = theta[t%T_theta];
  else
    for (; t < T_sim; t++) 
      theta[t] = theta[T_theta-1];

  fclose(file);

}


void setup_theta () {

  int t;

  theta = calloc(T_sim, sizeof(float));
 
  switch (theta_type) {

    case ramp :
      ramp_theta();
      break;
    case sine :
      sine_theta();
      break;
    case square :
      square_theta();
      break;
    case file :
      read_theta();
      break;

  } 

  print_stat("Theta values: ");
  for (t = 0; t < T_sim; t++)
    print_stat("%3.2f ", theta[t]);
  print_stat("\n");

  output_float_list(theta, T_sim, "theta");

  for (t = 0; t < T_sim; t++)
    theta[t] *= a_fac;

}

//==============================================================================
// END Theta
//==============================================================================



//==============================================================================
// Dynamics
//==============================================================================

void initialize_activity (int i_cue, unsigned char *S) {

  int n_active, n_incomp, n_inacc;
  int *q_active, *q_incomp, *q_inacc;

  int i, k;


  mu_cue = q_cue[i_cue]/s;
  nu_cue = q_cue[i_cue]%s;

  for (i = 0; i < N; i++)
    S[i] = X_sparse[mu_cue][nu_cue][i];

  if (incomp > 0.) {

    n_active = 0;
    q_active = malloc(N * sizeof(int));
    for (i = 0; i < N; i++)
      if (S[i])
        q_active[n_active++] = i;

    n_incomp = lrint(incomp * n_active);
    if (n_incomp == 0)
      print_stat("Warning: no neurons affected by nonzero incomp\n");
    else {
      q_incomp = malloc(n_incomp * sizeof(int));
      sample(n_active, n_incomp, q_incomp);
      for (k = 0; k < n_incomp; k++)
        S[q_active[q_incomp[k]]] = 0;
      free(q_incomp);
    }

    free(q_active);

  }

  if (inacc < 0.) {
    inacc = 1./N;
    print_stat("Initializing cues with single spin flip\n");
  }
  if (inacc > 0.) {

    n_inacc = lrint(inacc * N);
    if (n_inacc == 0)
      print_stat("Warning: no neurons affected by nonzero inacc\n");
    else {
      q_inacc = malloc(n_inacc * sizeof(int));
      sample(N, n_inacc, q_inacc);
      for (k = 0; k < n_inacc; k++)
        S[q_inacc[k]] = 1 - S[q_inacc[k]];
      free(q_inacc);
    }

  }
  
  memcpy(X_cue, S, N*sizeof(char));

} 


void plan_updates (unsigned char *S, int *q_update) {

  int t_cycle;

  switch (update_type) {

    case sequential :
      break;

    case block_random :
      permutation(N, q_update);
      break;

    case full_random :
      for (t_cycle = 0; t_cycle < N; t_cycle++)
        q_update[t_cycle] = (int) ((double)RUNI * N); 
      break;

  }
  
}


void update_activity (unsigned char *S, int q, float theta) {

  float h;

  int j;

  h = 0.;
  for (j = 0; j < N; j++)
    h += w[(long int)q*N+j] * S[j];
  h -= theta;
  h += f * X_cue[q];

  if (beta <= 0.)
    S[q] = step( h );
  else
    S[q] = step( 1./(1. + exp(-beta * h)) - RUNI );

} 

//==============================================================================
// END Dynamics
//==============================================================================



//==============================================================================
// Recording
//==============================================================================

float calculate_sparseness (unsigned char *S) {

  int sum;

  int i;

  sum = 0;

  for (i = 0; i < N; i++)
    sum += S[i];

  return (float) sum / N;

} 

double calculate_overlap (
    unsigned char *S, unsigned char *X, enum pattern_type type
) {

  double sum, dot, overlap;
  double a;

  int i;

  sum = 0.;
  dot = 0.; 
  
  switch (record_type) {
    
    case custom :

      for (i = 0; i < N; i++) {
        sum += X[i];
        dot += S[i] * (2.*X[i] - 1.);
      }
      overlap = fmin(fmax( dot / sum, 0.), 1.);
      break;

    case classic :

      if (type == sparse)
        a = a_sparse;
      else
        a = a_dense;
      
      for (i = 0; i < N; i++)
        dot += S[i] * (X[i]-a);

      overlap = dot / (N * a*(1.-a));
      break;

  }

  return overlap;

}


// Record data within each update cycle
void record_subcycle (unsigned char *S) {

  double overlap;
  int mu, nu;

  
  if (save_activity) {
    compress_binary_char(S, S_bin, N);
    fwrite(S_bin, sizeof(char), N_bin, S_file);
  }

  fprintf(a_file, "%.2e ", calculate_sparseness(S));

  // overlap with target sparse example
  overlap = calculate_overlap(S, X_sparse[mu_cue][nu_cue], sparse);
  fprintf(overlap_sparse_file, "% 4.3f ", overlap);

  // overlaps with other sparse examples within target concept
  for (nu = 0; nu < s; nu++) {
    if (nu == nu_cue)
      continue;
    overlap = calculate_overlap(S, X_sparse[mu_cue][nu], sparse);
    fprintf(overlap_sparse_file, "% 4.3f ", overlap);
  }
  fprintf(overlap_sparse_file, "\n");

  // overlaps with other sparse examples within other concepts
  for (mu = 0; mu < p; mu++) {
    if (mu == mu_cue)
      continue;
    for (nu = 0; nu < s; nu++) {
      overlap = calculate_overlap(S, X_sparse[mu][nu], sparse);
      fprintf(overlap_other_file, "% 4.3f ", overlap);
    }
  }
  fprintf(overlap_other_file, "\n");

  // overlap with target dense concept
  overlap = calculate_overlap(S, X_cat[mu_cue], cat);
  fprintf(overlap_cat_file, "% 4.3f ", overlap);

  // overlaps with other dense concepts
  for (mu = 0; mu < p; mu++) {
    if (mu == mu_cue)
      continue;
    overlap = calculate_overlap(S, X_cat[mu], cat);
    fprintf(overlap_cat_file, "% 4.3f ", overlap);
  }
  fprintf(overlap_cat_file, "\n");

}

// Prepare data files for next update cycle
void record_cycle (int t, unsigned char *S) {

  double overlap;

  
  overlap = calculate_overlap(S, X_sparse[mu_cue][nu_cue], sparse);
  overlap_smean[t] += fabs(overlap) / n_cue;

  overlap = calculate_overlap(S, X_cat[mu_cue], cat);
  overlap_cmean[t] += fabs(overlap) / n_cue;

  if (t == T_sim) {
    fprintf(a_file, "\n");
    fprintf(overlap_sparse_file, "\n");
    fprintf(overlap_cat_file, "\n");
    fprintf(overlap_other_file, "\n");
  }

}

//==============================================================================
// END Recording
//==============================================================================




int main (int argc, char *argv[]) {

  unsigned char *S;
  int *q_update;

  clock_t tic, toc;

  int i_cue, t, t_cycle;


  setup_parameters(argc, argv);

  print_stat("\nSTARTING NETWORK SETUP\n");

  setup_patterns();

  setup_theta();

  setup_network_shared();


  
  // No search over theta, just main simulation with data recording
  print_stat("\nSTARTING SIMULATION\n");

  tic = clock();
  setup_network_private(&S, &q_update);

  for (i_cue = 0; i_cue < n_cue; i_cue++) {

    print_screen("%2d/%2d cues tested...\r", i_cue, n_cue);

    initialize_activity(i_cue, S);
    record_subcycle(S);
    record_cycle(0, S);
    
    for (t = 1; t <= T_sim; t++) {

      plan_updates(S, q_update);
      for (t_cycle = 1; t_cycle <= N; t_cycle++) {

        update_activity(S, q_update[t_cycle-1], theta[t-1]);
        if (t % T_rec == 0 && t_cycle % T_subcycle == 0)
          record_subcycle(S);

      }

      record_cycle(t, S);

    }

  }

  clear_screen();


  cleanup_private(S, q_update);
  toc = clock();
  print_stat("Done in %.2f s\n", (double) (toc-tic)/CLOCKS_PER_SEC);

  print_stat("Mean sparse   overlaps: ");
  for (t = 0; t <= T_sim; t++)
    print_stat("%4.3f ", overlap_smean[t]);
  print_stat("\n");
  print_stat("Mean category overlaps: ");
  for (t = 0; t <= T_sim; t++)
    print_stat("%4.3f ", overlap_cmean[t]);
  print_stat("\n");

  print_stat("\nSIMULATION COMPLETE\n\n");

  cleanup_shared();

}


================================================
FILE: hippocampus/src/search.c
================================================
/*******************************************************************************
 *
 *  FILE:         search.c
 *
 *  DATE:         24 February 2023
 *
 *  AUTHOR:       Louis Kang
 *
 *  LICENSE:      GPLv3
 *
 *  REFERENCE:    To be determined
 *
 *  PURPOSE:      Simulating a Hopfield model with dual encodings. A search over
 *                the inhibition level can be performed to maximize overlap.
 *
 *  DEPENDENCIES: Intel Math Kernel Library
 *
 ******************************************************************************/


#include <stdlib.h>
#include <stdio.h>
#include <stdarg.h>
#include <stdint.h>
#include <math.h>
#include <string.h>
#include <time.h>
#include <unistd.h>
#include <fcntl.h>

#include "mkl.h"

//==============================================================================
// Parameters and global variables
//==============================================================================

// See Reading in parameters section for the syntax for setting parameters as
// command line arguments.

// Random ----------------------------------------------------------------------
uint32_t r4seed = 0;      // 0: use time as random seed
#define RUNI r4_uni(&r4seed)

// Iterations and time ---------------------------------------------------------
int T_sim = 100;    // Main simulation timesteps
int T_rec = 10;     // Print every tscreen timesteps
enum sequence_type {sequential, block_random, full_random};
enum sequence_type update_type = block_random;

// Network ---------------------------------------------------------------------
int N;                // number of neurons
int p = 1;            // number of categories stored
int s = 10;           // number of examples per category stored
int N_bin;
int p_max;            // number of categories in file
int s_max;            // number of examples per category in file
float g = 0.1;        // dense pattern strength; half of the corresponding value
                      //   in the manuscript.
float beta = 0.;      // rescaled inverse temperature
float a_sparse;       // sparse pattern sparsity
float a_dense;        // dense pattern sparsity
float a_fac;

float *w;

// Pattern ---------------------------------------------------------------------
char X_dir[256] = "";
int n_cue = 100;
enum pattern_type {sparse, dense, cat, both};
enum pattern_type cue_type = sparse;
enum pattern_type target_type = sparse;
float incomp = 0.;   // fraction of active neurons to inactivate in cue
float inacc = 0.;    // fraction of random flips in cue

int sparse_file, dense_file, cat_file;
int shuffle_patterns = 1;
int *q_mu, *q_nu;
unsigned char **X_sparse, **X_dense, **X_cat;
unsigned char **X_cue, **X_target;
unsigned char *X_bin;

// Recording -------------------------------------------------------------------
FILE *S_file, *a_file, *overlap_custom_file, *overlap_classic_file;
unsigned char *S_bin;
double overlap_start, overlap_end;

// Theta search ----------------------------------------------------------------
int search_over_theta = 1;
float theta_mid = 0.;
int n_round = 2;
int n_value = 4;

float theta_sim;
float theta_max;
double overlap_max;
float *theta_search;
double *overlap_search;
enum overlap_type {classic, custom};
enum overlap_type criterion_type = classic;

int T_search = 3;
int n_search = 20;

// I/O -------------------------------------------------------------------------
char fileroot[256] = "";  // Output filename root
int save_activity = 0;
int stat_screen = 1;
int stat_log = 1;
FILE *stat_file;

//==============================================================================
// END Parameters and global variables
//==============================================================================



//==============================================================================
// I/O utility functions
//==============================================================================

void print_screen (char *format, ...) {
  
  va_list args1;

  va_start(args1, format);

  if (stat_screen) {
    vprintf(format, args1);
    fflush(stdout);
  }

  va_end(args1);

}


void clear_screen() {

  print_screen("                                                  \r");

}


void print_stat (char *format, ...) {
  
  va_list args1, args2;

  va_start(args1, format);
  va_copy(args2, args1);

  if (stat_screen) {
    vprintf(format, args1);
    fflush(stdout);
  }

  if (stat_log) {
    vfprintf(stat_file, format, args2);
    fflush(stat_file);
  }

  va_end(args1);
  va_end(args2);

}


void print_err (char *format, ...) {
  
  va_list args1, args2;

  va_start(args1, format);
  va_copy(args2, args1);

  vfprintf(stderr, format, args1);
  fflush(stderr);

  if (stat_log) {
    vfprintf(stat_file, format, args2);
    fflush(stat_file);
  }

  va_end(args1);
  va_end(args2);

}


// Circularly rotate byte c by n places leftward
static inline unsigned char rotl (unsigned char c, unsigned int n) {

  n &= 7;
  return (c << n) | (c >> ((-n) & 7));

}

// Circularly rotate byte c by n places rightward
static inline unsigned char rotr (unsigned char c, unsigned int n) {

  n &= 7;
  return (c >> n) | (c << ((-n) & 7));

}

// Implements np.packbits with bitorder='big'
void compress_binary_char (
    unsigned char *raw, unsigned char *bin, int n_raw
) {

  int i;

  for (i = 0; i < n_raw; i += 8)
    bin[i/8] = 0;

  for (i = 0; i < n_raw; i++)
    bin[i/8] |= raw[i] << (7 - (i % 8));

}

// Implements np.unpackbits with bitorder='big'
void uncompress_binary_char (
    unsigned char *bin, unsigned char *raw, int n_raw
) {

  int i;

  for (i = 0; i < n_raw; i++) {
    bin[i/8] = rotl(bin[i/8], 1);  
    raw[i] = bin[i/8] & 1;
  }

}

void output_int_list(int *list, int n, char *extname) {

  char name[256];
  FILE *file;
  int i;

  sprintf(name, "%s_%s.txt", fileroot, extname);
  file = fopen(name, "w");

  for (i = 0; i < n; i++)
    fprintf(file, "%d ", list[i]); 

  fclose(file);

}

void output_float_array(float **arr, int ni, int nj, char *extname) {

  char name[256];
  FILE *file;
  int i, j;

  sprintf(name, "%s_%s.txt", fileroot, extname);
  file = fopen(name, "w");

  for (i = 0; i < ni; i++) {
    for (j = 0; j < nj; j++) 
      fprintf(file, "%e ", arr[i][j]); 
    fprintf(file, "\n");
  }
  fclose(file);

}

void output_float_1darray(float *arr, int ni, int nj, int incj, char *extname) {

  char name[256];
  FILE *file;
  int i, j;

  sprintf(name, "%s_%s.txt", fileroot, extname);
  file = fopen(name, "w");

  for (i = 0; i < ni; i++) {
    for (j = 0; j < nj; j++) 
      fprintf(file, "%e ", arr[i*incj+j]); 
    fprintf(file, "\n");
  }
  fclose(file);

}

//==============================================================================
// END I/O utility functions
//==============================================================================



//==============================================================================
// Math utility functions
//==============================================================================

static inline int fmini (int a, int b) {

  return (a < b) ? a : b;

}

static inline int fmaxi (int a, int b) {

  return (a > b) ? a : b;
}

static inline unsigned char step (float a) { 
  
  return a < 0. ? 0 : 1;

} 

static inline void swap (int *a, int *b) { 

    int temp;

    temp = *a; 
    *a = *b; 
    *b = temp; 

} 

// Generate random real between 0 and 1 based on the SHR3 Xorshift random number
// generator developed by George Marsaglia and implemented by John Burkhardt.
// See <https://people.sc.fsu.edu/~jburkardt/c_src/ziggurat/ziggurat.html>.
float r4_uni (uint32_t *jsr) {

  uint32_t jsr_input;
  float value;

  jsr_input = *jsr;

  *jsr = ( *jsr ^ ( *jsr <<   13 ) );
  *jsr = ( *jsr ^ ( *jsr >>   17 ) );
  *jsr = ( *jsr ^ ( *jsr <<    5 ) );

  value = fmod ( 0.5 
    + ( float ) ( jsr_input + *jsr ) / 65536.0 / 65536.0, 1.0 );

  return value;
}

void permutation (int n, int *arr) {
  
  int i, j;

  for (i = 0; i < n; i++)
    arr[i] = i;

  for (i = n-1; i > 0; i--) {
    j = (int) ((double)RUNI * (i+1));
    swap(&arr[i], &arr[j]);
  }

}

// Algorithm for sampling without replacement
void sample (int n_pop, int n_samp, int *arr) {

  int i_pop = 0;
  int i_samp = 0;

  if (n_samp > n_pop) {

    print_err("Error: n_samp cannot be greater than n_pop ");
    print_err("in sample function\n");
    exit(1);

  } else if (n_samp == n_pop) {

     for (i_samp = 0; i_samp < n_samp; i_samp++)
       arr[i_samp] = i_samp;

  } else {

    while (i_samp < n_samp) {
      if ( (n_pop-i_pop) * RUNI >= n_samp-i_samp )
        i_pop++;
      else {
        arr[i_samp] = i_pop;
        i_pop++; i_samp++;
      }
    }

  }

}

//==============================================================================
// END Math utility functions
//==============================================================================



//==============================================================================
// Parameters
//==============================================================================

void read_parameters (int argc, char *argv[]) {

  int narg = 1;

  while (narg < argc) {
    if (!strcmp(argv[narg],"-fileroot")) {
      sscanf(argv[narg+1],"%s",fileroot);
      narg += 2;
    } else if (!strcmp(argv[narg],"-seed")) {
      sscanf(argv[narg+1],"%d",&r4seed);
      narg += 2;
    } 

    else if (!strcmp(argv[narg],"-T_sim")) {
      sscanf(argv[narg+1],"%d",&T_sim);
      narg += 2;
    } else if (!strcmp(argv[narg],"-T_rec")) {
      sscanf(argv[narg+1],"%d",&T_rec);
      narg += 2;
    } else if (!strcmp(argv[narg],"-sequential")) {
      update_type = sequential;
      narg++;
    } else if (!strcmp(argv[narg],"-block_random")) {
      update_type = block_random;
      narg++;
    } else if (!strcmp(argv[narg],"-full_random")) {
      update_type = full_random;
      narg++;
    }

    else if (!strcmp(argv[narg],"-N")) {
      sscanf(argv[narg+1],"%d",&N);
      narg += 2;
    } else if (!strcmp(argv[narg],"-p")) {
      sscanf(argv[narg+1],"%d",&p);
      narg += 2;
    } else if (!strcmp(argv[narg],"-s")) {
      sscanf(argv[narg+1],"%d",&s);
      narg += 2;
    } else if (!strcmp(argv[narg],"-gamma")) {
      sscanf(argv[narg+1],"%f",&g);
      narg += 2;
    } else if (!strcmp(argv[narg],"-beta")) {
      sscanf(argv[narg+1],"%f",&beta);
      narg += 2;
    }

    else if (!strcmp(argv[narg],"-X_dir")) {
      sscanf(argv[narg+1],"%s",X_dir);
      narg += 2;
    } else if (!strcmp(argv[narg],"-no_shuffle")) {
      shuffle_patterns = 0;
      narg++;
    } else if (!strcmp(argv[narg],"-n_cue")) {
      sscanf(argv[narg+1],"%d",&n_cue);
      narg += 2;
    } else if (!strcmp(argv[narg],"-sparse_cue")) {
      cue_type = sparse;
      narg++;
    } else if (!strcmp(argv[narg],"-dense_cue")) {
      cue_type = dense;
      narg++;
    } else if (!strcmp(argv[narg],"-category_cue")) {
      cue_type = cat;
      narg++;
    } else if (!strcmp(argv[narg],"-both_cue")) {
      cue_type = both;
      narg++;
    } else if (!strcmp(argv[narg],"-sparse_target")) {
      target_type = sparse;
      narg++;
    } else if (!strcmp(argv[narg],"-dense_target")) {
      target_type = dense;
      narg++;
    } else if (!strcmp(argv[narg],"-category_target")) {
      target_type = cat;
      narg++;
    } else if (!strcmp(argv[narg],"-incomp")) {
      sscanf(argv[narg+1],"%f",&incomp);
      narg += 2;
    } else if (!strcmp(argv[narg],"-inacc")) {
      sscanf(argv[narg+1],"%f",&inacc);
      narg += 2;
    } else if (!strcmp(argv[narg],"-noiseless")) {
      incomp = 0.;
      inacc = 0.;
      narg++;
    }

    else if (!strcmp(argv[narg],"-verbose")) {
      stat_screen = 1;
      narg++;
    } else if (!strcmp(argv[narg],"-quiet")) {
      stat_screen = 0;
      narg++;
    } else if (!strcmp(argv[narg],"-no_log")) {
      stat_log = 0;
      narg++;
    }

    else if (!strcmp(argv[narg],"-save_activity")) {
      save_activity = 1;
      narg++;
    } else if (!strcmp(argv[narg],"-no_activity")) {
      save_activity = 0;
      narg++;
    }

    else if (!strcmp(argv[narg],"-search")) {
      search_over_theta = 1;
      narg++;
    } else if (!strcmp(argv[narg],"-no_search")) {
      search_over_theta = 0;
      narg++;
    } else if (!strcmp(argv[narg],"-custom_overlap")) {
      criterion_type = custom;
      narg++;
    } else if (!strcmp(argv[narg],"-classic_overlap")) {
      criterion_type = classic;
      narg++;
    } else if (!strcmp(argv[narg],"-theta")) {
      sscanf(argv[narg+1],"%f",&theta_mid);
      search_over_theta = 0;
      narg += 2;
    } else if (!strcmp(argv[narg],"-theta_mid")) {
      sscanf(argv[narg+1],"%f",&theta_mid);
      narg += 2;
    } else if (!strcmp(argv[narg],"-n_round")) {
      sscanf(argv[narg+1],"%d",&n_round);
      narg += 2;
    } else if (!strcmp(argv[narg],"-n_value")) {
      sscanf(argv[narg+1],"%d",&n_value);
      narg += 2;
    } else if (!strcmp(argv[narg],"-T_search")) {
      sscanf(argv[narg+1],"%d",&T_search);
      narg += 2;
    } else if (!strcmp(argv[narg],"-n_search")) {
      sscanf(argv[narg+1],"%d",&n_search);
      narg += 2;
    }


    else {
      fprintf(stderr, "unknown option: %s\n", argv[narg]);
      fflush(stderr);
      exit(1);
    }
  }  

}


void print_parameters () {

  FILE *file;
  char name[256];

  sprintf(name, "%s_params.txt", fileroot);
  file = fopen(name, "w");

  fprintf(file, "seed             = %d\n", r4seed);

  fprintf(file, "\n");
  fprintf(file, "T_sim            = %d\n", T_sim);
  fprintf(file, "T_rec            = %d\n", T_rec);
  fprintf(file, "update_type      = %d\n", update_type);

  fprintf(file, "\n");
  fprintf(file, "N                = %d\n", N);
  fprintf(file, "p                = %d\n", p);
  fprintf(file, "s                = %d\n", s);
  fprintf(file, "gamma            = %f\n", g);
  fprintf(file, "beta             = %f\n", beta);

  fprintf(file, "\n");
  fprintf(file, "X_dir            = %s\n", X_dir);
  fprintf(file, "shuffle_patterns = %d\n", shuffle_patterns);
  fprintf(file, "n_cue            = %d\n", n_cue);
  fprintf(file, "cue_type         = %d\n", cue_type);
  fprintf(file, "target_type      = %d\n", target_type);
  fprintf(file, "incomp           = %f\n", incomp);
  fprintf(file, "inacc            = %f\n", inacc);

  fprintf(file, "\n");
  fprintf(file, "search           = %d\n", search_over_theta);
  fprintf(file, "criterion_type   = %d\n", criterion_type);
  fprintf(file, "theta_mid        = %f\n", theta_mid);
  fprintf(file, "n_round          = %d\n", n_round);
  fprintf(file, "n_value          = %d\n", n_value);
  fprintf(file, "T_search         = %d\n", T_search);
  fprintf(file, "n_search         = %d\n", n_search);

  fclose(file);

}


void setup_parameters (int argc, char *argv[]) {
  
  char name[256];
  char *token;
  char a_buf[16];
  int ch, place;


  read_parameters(argc, argv);


  if (strcmp(fileroot, "") == 0 ||
      fileroot[0] == '-' ||
      fileroot[strlen(fileroot)-1] == '/') {
    fprintf(stderr, "Must set -fileroot correctly\n");
    fflush(stderr);
    exit(1);
  }
  if (stat_log) {
    sprintf(name, "%s_log.txt", fileroot);
    stat_file = fopen(name, "w");
  }


  print_stat("\nSTARTING SIMULATION FOR %s\n", fileroot);


  if (X_dir[strlen(X_dir)-1] == '/')
    X_dir[strlen(X_dir)-1] = '\0';
  
  // Pattern directory must contain pattern statistics in a strict format
  strcpy(name, X_dir);
  token = strtok(name, "/-_.");
  while (token != NULL) {
    if (strlen(token) > 1 && token[1] >= '0' && token[1] <= '9') {
      if (token[0] == 'N')
        sscanf(token, "N%d", &N);
      else if (token[0] == 'p')
        sscanf(token, "p%d", &p_max);
      else if (token[0] == 's')
        sscanf(token, "s%d", &s_max);
      else if (token[0] == 'a') {
        sprintf(a_buf, "0.%s", token+1);
        a_sparse = strtof(a_buf, NULL);
        token = strtok(NULL, "/-.");
        sprintf(a_buf, "0.%s", token);
        a_dense = strtof(a_buf, NULL);
      }
    }
    token = strtok(NULL, "/-_.");
  }
  if (N == 0 || p_max == 0 || s_max == 0) {
    print_err("Error: pattern directory name %s must contain numbers ", X_dir);
    print_err("of neurons, categories, and examples\n");
    exit(1);
  } else if (p > p_max) {
    print_err("Error: requested categories %d exceeds maximum %d\n", p, p_max);
    exit(1);
  } else if (s > s_max) {
    print_err("Error: requested examples %d exceeds maximum %d\n", s, s_max);
    exit(1);
  } else {
    print_stat("Pattern directory contains %d neurons, ", N);
    print_stat("%d categories, and %d examples\n", p_max, s_max);
  }
  if (a_sparse == 0. || a_dense == 0.) {
    print_err("Error: pattern directory name %s must contain ", X_dir);
    print_err("sparsenesses\n");
    exit(1);
  } else {
    print_stat("Sparsenesses detected: %4.3f and %4.3f\n", a_sparse, a_dense);
  }


  // Setting random number seed using time
  if (r4seed == 0) {
    r4seed = (uint32_t)(time(NULL) % 1048576);
    place = 1;
    for (ch = 0; ch < strlen(fileroot); ch++) {
      r4seed += fileroot[ch] * place;
      place = (place * 128) % 100000;
    }
  }

  // Number of packed bytes that contains pattern of length N
  N_bin = (N-1)/8 + 1;


  print_parameters();

}

//==============================================================================
// END Parameters
//==============================================================================



//==============================================================================
// Setup
//==============================================================================

void read_pattern (unsigned char *X, int file, int mu, int nu) {

  int q;

  if (nu >= 0)
    q = q_mu[mu]*s_max + q_nu[nu];
  else
    q = q_mu[mu];

  if (pread(file, X_bin, N_bin, (long int) q*N_bin) != N_bin) {
    print_err("Error: pattern file too short\n");
    exit(1);
  };
  uncompress_binary_char(X_bin, X, N);

}


void setup_patterns () {

  float *X_combo;
  char sname[256], dname[256], cname[256];

  int i, j, mu, nu;


  print_stat("Storing %d categories with %d examples\n", p, s);

  sprintf(sname, "%s/x_sparse.dat", X_dir);
  sprintf(dname, "%s/x_dense.dat" , X_dir);
  sprintf(cname, "%s/x_cat.dat"   , X_dir);
  if ((sparse_file = open(sname, O_RDONLY)) < 0 ||
      (dense_file  = open(dname, O_RDONLY)) < 0 ||
      (cat_file    = open(cname, O_RDONLY)) < 0   ) {
    print_err("Error opening pattern files in directory %s\n", X_dir);
    exit(1);
  }

  
  // q_mu contains indices of stored concepts
  q_mu = malloc(p * sizeof(int));
  if (shuffle_patterns)
    sample(p_max, p, q_mu);
  else
    for (mu = 0; mu < p; mu++)
      q_mu[mu] = mu;
  output_int_list(q_mu, p, "qmu");

  // q_mu contains indices of stored examples in each concept
  q_nu = malloc(s * sizeof(int));
  if (shuffle_patterns)
    sample(s_max, s, q_nu);
  else
    for (nu = 0; nu < s; nu++)
      q_nu[nu] = nu;
  output_int_list(q_nu, s, "qnu");


  // X_sparse and X_dense contain sparse and dense examples
  X_bin = malloc(N_bin * sizeof(char *));
  X_sparse = malloc(s * sizeof(char *));
  for (nu = 0; nu < s; nu++)
    X_sparse[nu] = malloc(N * sizeof(char));
  X_dense = malloc(s * sizeof(char *));
  for (nu = 0; nu < s; nu++)
    X_dense[nu] = malloc(N * sizeof(char));

  // w is the (flattened) connectivity matrix
  X_combo = mkl_malloc(s*N * sizeof(float), 64);
  w = mkl_calloc(N*N, sizeof(float *), 64);


  for (mu = 0; mu < p; mu++) {

    print_screen("%3d/%3d categories stored...\r", mu, p);

    for (nu = 0; nu < s; nu++) {

      read_pattern(X_sparse[nu], sparse_file, mu, nu);
      read_pattern(X_dense [nu], dense_file , mu, nu);

    }

    // Note that 2*g is the dense strength zeta in the manuscript
    for (nu = 0; nu < s; nu++)
      for (i = 0; i < N; i++)
        X_combo[nu*N+i] =   (1.-2.*g) * (X_sparse[nu][i] - a_sparse)
                          + (   2.*g) * (X_dense [nu][i] - a_dense );

    // Add X_combo multiplied with its transpose to w
    cblas_ssyrk(CblasRowMajor, CblasUpper, CblasTrans,
                N, s, 1./N, X_combo, N, 1., w, N     );

  } 

  clear_screen();

  for (i = 0; i < N; i++) {
    w[i*N+i] = 0.;
    for (j = i; j < N; j++)
      w[j*N+i] = w[i*N+j];
  }
 
  output_float_1darray(w, fmini(N,100), fmini(N,100), N, "wsample");

  for (nu = 0; nu < s; nu++)
    free(X_sparse[nu]);
  free(X_sparse);
  for (nu = 0; nu < s; nu++)
    free(X_dense[nu]);
  free(X_dense);
  mkl_free(X_combo);

  
  // Theoretically motiviated rescaling of beta
  a_fac = (1.-2.*g)*(1.-2.*g) * a_sparse;
  beta /= a_fac;

}


void setup_cue_target (unsigned char **X, int *q_cue, enum pattern_type type) {

  unsigned char *X_buf;
  int nu_cue, i;

  switch (type) {

    case sparse :
      for (nu_cue = 0; nu_cue < n_cue; nu_cue++)
        read_pattern(X[nu_cue], sparse_file, q_cue[nu_cue]/s, q_cue[nu_cue]%s);
      break;

    case dense :
      for (nu_cue = 0; nu_cue < n_cue; nu_cue++)
        read_pattern(X[nu_cue], dense_file, q_cue[nu_cue]/s, q_cue[nu_cue]%s);
      break;

    case cat :
      for (nu_cue = 0; nu_cue < n_cue; nu_cue++)
        read_pattern(X[nu_cue], cat_file, q_cue[nu_cue]/s, -1);
      break;

    case both :
      X_buf = malloc(N * sizeof(char));
      for (nu_cue = 0; nu_cue < n_cue; nu_cue++) {
        read_pattern(X[nu_cue], sparse_file, q_cue[nu_cue]/s, q_cue[nu_cue]%s);
        read_pattern(X_buf,     dense_file,  q_cue[nu_cue]/s, q_cue[nu_cue]%s);
        for (i = 0; i < N; i++)
          X[nu_cue][i] |= X_buf[i];
      }
      break;

  }
  
}


// Variables shared among cues
void setup_network_shared () {

  int *q_cue;

  char name[256];
  int i_rec, nu_cue;
 

  // Record data every T_rec update cycles
  T_rec = fmini(T_rec, T_sim);
  overlap_start = 0.;
  overlap_end = 0.;

  // Save raw network activities as packed binary file
  if (save_activity) {
    S_bin = malloc(N_bin * sizeof(char));
    sprintf(name, "%s_s.dat", fileroot);
    S_file = fopen(name, "wb");
  }
  sprintf(name, "%s_a.txt", fileroot);
  a_file = fopen(name, "w");
  sprintf(name, "%s_mcustom.txt", fileroot);
  overlap_custom_file = fopen(name, "w");
  sprintf(name, "%s_mclassic.txt", fileroot);
  overlap_classic_file = fopen(name, "w");


  print_stat("Testing %d cues\n", n_cue);
  q_cue = malloc(n_cue * sizeof(int));

  if (cue_type == cat && target_type == cat) {

    if (shuffle_patterns)
      sample(p, fmini(n_cue, p), q_cue);
    else
      for (nu_cue = 0; nu_cue < fmini(n_cue, p); nu_cue++)
        q_cue[nu_cue] = nu_cue;

    // Cycle through patterns if fewer than n_cue are stored
    for (nu_cue = p; nu_cue < n_cue; nu_cue++)
      q_cue[nu_cue] = q_cue[nu_cue%p];

    // Sets q_cue to first example in each selected concept; example identity
    // doesn't matter since we are only interested in cat cues and targets
    for (nu_cue = 0; nu_cue < n_cue; nu_cue++)
      q_cue[nu_cue] *= s;

  } else {

    if (shuffle_patterns)
      sample(p*s, fmini(n_cue, p*s), q_cue);
    else
      for (nu_cue = 0; nu_cue < fmini(n_cue, p*s); nu_cue++)
        q_cue[nu_cue] = (nu_cue%p) * s + nu_cue/p;

    for (nu_cue = p*s; nu_cue < n_cue; nu_cue++)
      q_cue[nu_cue] = q_cue[nu_cue%(p*s)];

  }

  output_int_list(q_cue, n_cue, "qcue");


  X_cue = malloc(n_cue * sizeof(char *));
  for (nu_cue = 0; nu_cue < n_cue; nu_cue++)
    X_cue[nu_cue] = malloc(N * sizeof(char));

  X_target = malloc(n_cue * sizeof(char *));
  for (nu_cue = 0; nu_cue < n_cue; nu_cue++)
    X_target[nu_cue] = malloc(N * sizeof(char));


  setup_cue_target(X_cue   , q_cue, cue_type   );
  setup_cue_target(X_target, q_cue, target_type);

  free(q_cue);
   
} 

// Variables private to each cue; can potentially be parallelized, but not
// implemented here
void setup_network_private (
    unsigned char **S, int **q_update, float *theta, float theta_base
) {

  int t_cycle;

  *S = malloc(N * sizeof(char));

  *q_update = malloc(N * sizeof(int));
  for (t_cycle = 0; t_cycle < N; t_cycle++)
    (*q_update)[t_cycle] = t_cycle;

  *theta = theta_base * a_fac;
   
} 

void cleanup_shared () {

  fclose(stat_file);
  close(sparse_file);
  close(dense_file);
  close(cat_file);

  if (save_activity)
    fclose(S_file);
  fclose(a_file);
  fclose(overlap_custom_file);
  fclose(overlap_classic_file);

}

void cleanup_private (unsigned char *S, int *q_update) {

  free(S);
  free(q_update);

}

//==============================================================================
// END Setup
//==============================================================================



//==============================================================================
// Dynamics
//==============================================================================

void initialize_activity (int nu_cue, unsigned char *S) {

  int n_active, n_incomp, n_inacc;
  int *q_active, *q_incomp, *q_inacc;

  int i, k;

  // Initialize network to cue
  for (i = 0; i < N; i++)
    S[i] = X_cue[nu_cue][i];

  // Randomly deactivate neurons
  if (incomp > 0.) {

    n_active = 0;
    q_active = malloc(N * sizeof(int));
    for (i = 0; i < N; i++)
      if (S[i])
        q_active[n_active++] = i;

    n_incomp = lrint(incomp * n_active);
    if (n_incomp == 0)
      print_stat("Warning: no neurons affected by nonzero incomp\n");
    else {
      q_incomp = malloc(n_incomp * sizeof(int));
      sample(n_active, n_incomp, q_incomp);
      for (k = 0; k < n_incomp; k++)
        S[q_active[q_incomp[k]]] = 0;
      free(q_incomp);
    }

    free(q_active);

  }

  // Randomly flip neurons between active and inactive
  if (inacc > 0.) {

    n_inacc = lrint(inacc * N);
    if (n_inacc == 0)
      print_stat("Warning: no neurons affected by nonzero inacc\n");
    else {
      q_inacc = malloc(n_inacc * sizeof(int));
      sample(N, n_inacc, q_inacc);
      for (k = 0; k < n_inacc; k++)
        S[q_inacc[k]] = 1 - S[q_inacc[k]];
      free(q_inacc);
    }

  }

} 


void plan_updates (unsigned char *S, int *q_update) {

  int t_cycle;

  switch (update_type) {

    // update neurons in sequence
    case sequential :
      break;

    // update one neuron per update cycle in random order
    case block_random :
      permutation(N, q_update);
      break;

    // update neurons randomly
    case full_random :
      for (t_cycle = 0; t_cycle < N; t_cycle++)
        q_update[t_cycle] = (int) ((double)RUNI * N); 
      break;

  }
  
}


// Glauber dynamics
void update_activity (unsigned char *S, int q, float theta) {

  float h;

  int j;

  h = 0.;
  for (j = 0; j < N; j++)
    h += w[(long int)q*N+j] * S[j];
  h -= theta;
  
  if (beta <= 0.)
    S[q] = step( h );
  else
    S[q] = step( 1./(1. + exp(-beta * h)) - RUNI );

} 

//==============================================================================
// END Dynamics
//==============================================================================



//==============================================================================
// Recording
//==============================================================================

float calculate_sparseness (unsigned char *S) {

  int sum;

  int i;

  sum = 0;

  for (i = 0; i < N; i++)
    sum += S[i];

  return (float) sum / N;

} 

// Only classic overlap was used in the manuscript
double calculate_overlap (
    unsigned char *S, unsigned char *X, enum overlap_type type
) {

  double sum, dot, overlap;
  double a;

  int i;

  sum = 0.;
  dot = 0.; 
  
  switch (type) {
    
    case custom :

      for (i = 0; i < N; i++) {
        sum += X[i];
        dot += S[i] * (2.*X[i] - 1.);
      }
      overlap = fmin(fmax( dot / sum, 0.), 1.);
      break;

    case classic :

      if (target_type == sparse)
        a = a_sparse;
      else
        a = a_dense;
      
      for (i = 0; i < N; i++)
        dot += S[i] * (X[i]-a);

      overlap = dot / (N * a*(1.-a));
      break;

  }

  return overlap;

}

void record_activity (int t, int nu_cue, unsigned char *S) {

  double overlap_custom, overlap_classic;

  if (save_activity) {
    compress_binary_char(S, S_bin, N);
    fwrite(S_bin, sizeof(char), N_bin, S_file);
  }

  fprintf(a_file, "%.2e ", calculate_sparseness(S));

  overlap_custom  = calculate_overlap(S, X_target[nu_cue], custom );
  overlap_classic = calculate_overlap(S, X_target[nu_cue], classic);

  fprintf(overlap_custom_file , "% 4.3f ", overlap_custom );
  fprintf(overlap_classic_file, "% 4.3f ", overlap_classic);

  if (t == 0)
    overlap_start +=
        fabs(calculate_overlap(S, X_target[nu_cue], criterion_type))
            / n_cue;
  if (t == T_sim)
    overlap_end +=
        fabs(calculate_overlap(S, X_target[nu_cue], criterion_type))
            / n_cue;

  if (t == T_sim) {
    fprintf(a_file, "\n");
    fprintf(overlap_custom_file , "\n");
    fprintf(overlap_classic_file, "\n");
  }

}

//==============================================================================
// END Recording
//==============================================================================



//==============================================================================
// Search over theta
//==============================================================================

// These functions allow the network to iteratively search over theta values to
// optimize overlap with the target pattern to a resolution of 0.01 in theta.
void plan_search () {

  float theta_width;

  int i_round, i_value;

  n_search = fmini(n_search, n_cue);
  T_search = fmini(T_search, T_sim);

  // In each search round, n_value theta values are searched. The value that
  // maximizes overlap with the target pattern is used as the midpoint for the
  // next round. The range of theta values searched spans from
  // theta_mid-theta_width to theta_mid+theta_width.
  theta_width = 0.;
  for (i_round = 0; i_round < n_round; i_round++)
    theta_width += 0.01 * pow(n_value-1., i_round+1) / 2.;

  print_stat("Maximizing overlap w.r.t. theta using %d rounds of %d values\n",
             n_round, n_value);
  print_stat("Theta search range from %4.3f to %4.3f\n",
             theta_mid-theta_width, theta_mid+theta_width);

  // Initial (coarsest) search values
  theta_search = malloc(n_value * sizeof(float));
  for (i_value = 0; i_value < n_value; i_value++)
    theta_search[i_value] = theta_mid + 0.01 * pow(n_value-1, n_round-1) *
                                        (-(n_value-1.)/2. + i_value);

  overlap_search = malloc(n_value * sizeof(double));

}


int update_search (int i_round) {

  int q_max1, q_max2;
  int rounds_left;
  
  int i_value;

  // Find argmax of overlap. Allow for tie between q_max1 and q_max2.
  overlap_max = overlap_search[0];
  q_max1 = 0;
  q_max2 = 0;
  for (i_value = 1; i_value < n_value; i_value++) {

    if (overlap_search[i_value] > overlap_max) {
      overlap_max = overlap_search[i_value];
      q_max1 = i_value;
      q_max2 = i_value;
    } else if (overlap_search[i_value] == overlap_max)
      q_max2 = i_value;

  }

  if (q_max1 != q_max2) {
    print_stat(
        "Maximum overlap achieved by multiple theta values, reporting mean\n"
    );
    theta_max = (theta_search[q_max1] + theta_search[q_max2]) / 2.;
  } else
    theta_max = theta_search[q_max1];

  // Stop search if highest overlap is achieved
  if (overlap_max > 0.9995) {
    print_stat("Full overlap of 1.000 achieved by theta = %4.3f in round %d\n",
               theta_max, i_round+1);
    return 1;
  } else {
    print_stat("Mean overlap of %4.3f achieved by theta = %4.3f in round %d\n",
               overlap_max, theta_max, i_round+1);

    // Update theta_search for the next round with finer values centered around
    // the best value discovered this round
    rounds_left = n_round - (i_round+1);
    if (rounds_left > 0)
      for (i_value = 0; i_value < n_value; i_value++)
        theta_search[i_value] = theta_max +
                                0.01 * pow(n_value-1, rounds_left-1) *
                                (-(n_value-1.)/2. + i_value);

    return 0;
  }

}

void print_theta () {

  FILE *file;
  char name[256];

  sprintf(name, "%s_params.txt", fileroot);
  file = fopen(name, "a");

  // Save theta value that maximized overlap
  fprintf(file, "\n");
  fprintf(file, "theta_max    = %f\n", theta_max);

  fclose(file);

}

//==============================================================================
// END Search over theta
//==============================================================================




int main (int argc, char *argv[]) {

  unsigned char *S;
  int *q_update;
  float theta;

  clock_t tic, toc;

  int i_round, i_value;
  int nu_cue, t, t_cycle;


  setup_parameters(argc, argv);

  print_stat("\nSTARTING NETWORK SETUP\n");

  setup_patterns();

  setup_network_shared();


  // Search over theta to maximize mean overlap with target patterns
  if (!search_over_theta) 
    theta_sim = theta_mid;
  else  {

    plan_search();

    for (i_round = 0; i_round < n_round; i_round++) {

      print_stat("\nSTARTING THETA SEARCH ROUND %d of %d\n\n",
                 i_round+1, n_round);

      for (i_value = 0; i_value < n_value; i_value++) {

        tic = clock();
        setup_network_private(&S, &q_update, &theta, theta_search[i_value]);
        overlap_search[i_value] = 0.;
        
        for (nu_cue = 0; nu_cue < n_search; nu_cue++) {

          initialize_activity(nu_cue, S);
          for (t = 1; t <= T_search; t++) {
            plan_updates(S, q_update);
            for (t_cycle = 0; t_cycle < N; t_cycle++) 
              update_activity(S, q_update[t_cycle], theta);
          }

          overlap_search[i_value] +=
              fabs(calculate_overlap(S, X_target[nu_cue], criterion_type))
                  / n_search;

        }

        cleanup_private(S, q_update);
        toc = clock();
        print_stat(
            "Round %d, theta = %4.3f: done in %.2f s, mean overlap %4.3f\n",
            i_round+1, theta_search[i_value], (double) (toc-tic)/CLOCKS_PER_SEC,
            overlap_search[i_value]
        );

      }

      if (update_search(i_round))
        break;

    }
    
    print_stat("\nTHETA SEARCH: %4.3f ACHIEVES MAXIMUM MEAN OVERLAP %4.3f\n",
                theta_max, overlap_max);
    print_theta();
    theta_sim = theta_max;

  }



  // Perform final simulation at optimal theta and record data
  print_stat("\nSTARTING FINAL SIMULATION\n");

  tic = clock();
  setup_network_private(&S, &q_update, &theta, theta_sim);

  for (nu_cue = 0; nu_cue < n_cue; nu_cue++) {

    print_screen("%2d/%2d cues tested...\r", nu_cue, n_cue);

    initialize_activity(nu_cue, S);
    record_activity(0, nu_cue, S);
    
    for (t = 1; t <= T_sim; t++) {

      plan_updates(S, q_update);
      for (t_cycle = 0; t_cycle < N; t_cycle++) 
        update_activity(S, q_update[t_cycle], theta);
      if (t % T_rec == 0)
        record_activity(t, nu_cue, S);

    }

  }

  clear_screen();


  cleanup_private(S, q_update);
  toc = clock();
  print_stat("Done in %.2f s\n", (double) (toc-tic)/CLOCKS_PER_SEC);

  print_stat("Mean overlap %4.3f --> %4.3f", overlap_start, overlap_end);
  if (search_over_theta)
    print_stat(" achieved by theta = %4.3f", theta_sim);
  print_stat("\n");

  print_stat("\nSIMULATION COMPLETE\n\n");

  cleanup_shared();

}


================================================
FILE: ml/1task-concept.ipynb
================================================
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "012dbd0a-82ff-4eed-9c02-3fb167e320f2",
   "metadata": {},
   "source": [
    "# General setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e66fd64e-d56f-4bf8-9b36-e92233d9477e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys, subprocess\n",
    "import time\n",
    "from glob import glob\n",
    "import itertools\n",
    "from functools import partial\n",
    "import copy\n",
    "import gc\n",
    "\n",
    "import importlib\n",
    "sys.path.insert(1, os.path.realpath('lib'))\n",
    "if \"utils\" not in sys.modules: import utils\n",
    "else: importlib.reload(utils)\n",
    "if \"ml\" not in sys.modules: import ml\n",
    "else: importlib.reload(ml)\n",
    "if \"train\" not in sys.modules: import train\n",
    "else: importlib.reload(train)\n",
    "\n",
    "# >>> exclude from multiprocessing\n",
    "import ipynbname\n",
    "nb_base = ipynbname.name().split('_')[0]\n",
    "# <<<\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "# >>> exclude from multiprocessing\n",
    "from scipy import stats\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams.update({'font.size': 14})\n",
    "from matplotlib import ticker\n",
    "import h5py\n",
    "# <<<\n",
    "\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "from torchvision import datasets\n",
    "from torchvision.transforms import Compose, ToTensor, Normalize\n",
    "if not utils.is_notebook():\n",
    "    import torch.multiprocessing as mp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6432fe38-e245-4d74-bebf-ffe9ebbd1335",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cuda device\n"
     ]
    }
   ],
   "source": [
    "# >>> exclude from multiprocessing\n",
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
    "print(f\"Using {device} device\")\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc9e2a1e-76a9-475f-b845-dec39bbb513f",
   "metadata": {},
   "source": [
    "# Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e8a0ac31-0c65-4489-9be5-4461b6695b88",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "transform = Compose([\n",
    "    ToTensor(),\n",
    "    Normalize((0.1307,), (0.3081,))\n",
    "])\n",
    "\n",
    "raw_train_dataset = datasets.MNIST(\n",
    "    root=\"../data\",\n",
    "    train=True,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")\n",
    "\n",
    "raw_test_dataset = datasets.MNIST(\n",
    "    root=\"../data\",\n",
    "    train=False,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a731b26c-f5b1-40c9-9aa0-7d698b7a3bd5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of X [N, C, H, W]:  torch.Size([16, 1, 28, 28])\n",
      "Shape of y:  torch.Size([16]) torch.int64\n",
      "Shape of z:  torch.Size([16]) torch.int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x72 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5, 2, 9, 1, 1, 9, 8, 2, 9, 3, 4, 0])\n",
      "tensor([14, 12, 12,  0, 13, 19, 16,  6,  6, 13, 17, 19])\n"
     ]
    }
   ],
   "source": [
    "# >>> exclude from multiprocessing\n",
    "# Example batch\n",
    "preview_dataloader = DataLoader(\n",
    "    ml.RelabeledSubset(raw_train_dataset, class_size=100,\n",
    "                       target2_config=20, transform=transform),\n",
    "    batch_size=16, shuffle=True)\n",
    "\n",
    "X, y, z = next(iter(preview_dataloader))\n",
    "print(\"Shape of X [N, C, H, W]: \", X.shape)\n",
    "print(\"Shape of y: \", y.shape, y.dtype)\n",
    "print(\"Shape of z: \", z.shape, z.dtype)\n",
    "    \n",
    "utils.plot_images(X.clamp_(-1, 1), num=12)\n",
    "print(y[:12])\n",
    "print(z[:12])\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a692324-6056-4ebd-9c8b-b17db6984505",
   "metadata": {},
   "source": [
    "# Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b24fa7f1-7336-433d-8b84-914ee02619d5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HIDDEN_SIZE = 50\n",
    "CLASS_SIZES = [200, 400, 600, 800, 1000]\n",
    "num_sizes = len(CLASS_SIZES)\n",
    "BATCH_SIZE = 50\n",
    "\n",
    "DECORR_STRENGTH = 0.5\n",
    "# Number of networks trained per class size\n",
    "NUM_REPLICATES = 8\n",
    "\n",
    "class_sizes = [rep\n",
    "               for size in CLASS_SIZES\n",
    "               for rep in (size,)*NUM_REPLICATES]*2\n",
    "# Baseline networks then DeCorr networks\n",
    "decorr_criteria = [rep\n",
    "                   for criterion in (None, ml.decorr_criterion)\n",
    "                   for rep in (criterion,)*NUM_REPLICATES*num_sizes]\n",
    "\n",
    "# Evaluate digit classification performance with held-out test data\n",
    "MODE = 'testval'\n",
    "\n",
    "# Defining datasets for each replicate\n",
    "train_datasets = [(\n",
    "    ml.RelabeledSubset,\n",
    "    dict(dataset=raw_train_dataset, class_size=class_size,\n",
    "         target2_config='none', transform=transform)\n",
    ") for class_size in class_sizes]\n",
    "test_dataset = (\n",
    "    ml.RelabeledSubset,\n",
    "    dict(dataset=raw_test_dataset,\n",
    "         target2_config='none', transform=transform)\n",
    ")\n",
    "\n",
    "# Defining multilayer perceptron\n",
    "model = (\n",
    "    ml.MLP,\n",
    "    dict(hidden_size=HIDDEN_SIZE, target_size=10,\n",
    "         nonlinearity1=nn.Tanh(), nonlinearity2=nn.Tanh())\n",
    ")\n",
    "\n",
    "# Looping through GPUs\n",
    "devices = itertools.cycle([torch.device('cuda', i)\n",
    "                           for i in range(torch.cuda.device_count())])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "efe080ae-adb4-4018-9f61-f9f592b8e4ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "NUM_EPOCHS = 40\n",
    "PRINT_EPOCHS = NUM_EPOCHS\n",
    "LEARNING_RATE = 1e-4\n",
    "WEIGHT_DECAY = 0\n",
    "NOISE_FN = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "3e0675d8-0ff7-4ddf-a2a6-543b8340a9a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'device': device(type='cuda', index=0),\n",
       " 'train_dataset': (ml.RelabeledSubset,\n",
       "  {'dataset': Dataset MNIST\n",
       "       Number of datapoints: 60000\n",
       "       Root location: ../../../PyTorchShared/Datasets\n",
       "       Split: Train\n",
       "       StandardTransform\n",
       "   Transform: Compose(\n",
       "                  ToTensor()\n",
       "                  Normalize(mean=(0.1307,), std=(0.3081,))\n",
       "              ),\n",
       "   'class_size': 200,\n",
       "   'target2_config': 'none',\n",
       "   'transform': Compose(\n",
       "       ToTensor()\n",
       "       Normalize(mean=(0.1307,), std=(0.3081,))\n",
       "   )}),\n",
       " 'decorr_criterion': None}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training keyword arguments that vary across replicates\n",
    "kwargs_map = [dict(device=dev,\n",
    "                   train_dataset=param0,\n",
    "                   decorr_criterion=param1)\n",
    "               for dev, param0, param1\n",
    "               in zip(devices,\n",
    "                      train_datasets,\n",
    "                      decorr_criteria)]\n",
    "# Training keyword arguments that remain constant\n",
    "kwargs_partial = dict(model=model,\n",
    "                      mode=MODE,\n",
    "                      test_dataset=test_dataset,\n",
    "                      decorr_strength=DECORR_STRENGTH,\n",
    "                      noise_fn=NOISE_FN,\n",
    "                      batch_size=BATCH_SIZE,\n",
    "                      learning_rate=LEARNING_RATE,\n",
    "                      num_epochs=NUM_EPOCHS,\n",
    "                      print_epochs=PRINT_EPOCHS)\n",
    "# >>> exclude from multiprocessing\n",
    "kwargs_map[0]\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ea5af23e-5c0d-4ffe-a963-7db0bbf65ab3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(<class 'ml.MLP'>, {'hidden_size': 50, 'target_size': 10, 'nonlinearity1': Tanh(), 'nonlinearity2': Tanh()})\n",
      "cuda:1   0)   target:  1.929  decorr:  8.156   train: 0.528  test: 0.689\n",
      "cuda:1   1)   target:  1.211  decorr:  8.939   train: 0.765  test: 0.787\n",
      "cuda:1   3)   target:  0.580  decorr:  8.400   train: 0.864  test: 0.853\n",
      "cuda:1   5)   target:  0.384  decorr:  7.807   train: 0.908  test: 0.876\n",
      "cuda:1   7)   target:  0.287  decorr:  7.670   train: 0.938  test: 0.890\n",
      "cuda:1   9)   target:  0.225  decorr:  7.442   train: 0.953  test: 0.894\n",
      "cuda:1  11)   target:  0.179  decorr:  7.436   train: 0.966  test: 0.897\n",
      "cuda:1  13)   target:  0.147  decorr:  7.237   train: 0.973  test: 0.898\n",
      "cuda:1  15)   target:  0.122  decorr:  7.173   train: 0.983  test: 0.898\n",
      "cuda:1  17)   target:  0.099  decorr:  7.283   train: 0.989  test: 0.904\n",
      "cuda:1  19)   target:  0.084  decorr:  7.104   train: 0.992  test: 0.902\n",
      "cuda:1  21)   target:  0.070  decorr:  7.009   train: 0.995  test: 0.903\n",
      "cuda:1  23)   target:  0.059  decorr:  7.001   train: 0.997  test: 0.904\n",
      "cuda:1  25)   target:  0.052  decorr:  7.008   train: 0.998  test: 0.904\n",
      "cuda:1  27)   target:  0.045  decorr:  6.989   train: 0.998  test: 0.904\n",
      "cuda:1  29)   target:  0.039  decorr:  6.979   train: 0.999  test: 0.904\n",
      "cuda:1  31)   target:  0.035  decorr:  6.954   train: 0.999  test: 0.903\n",
      "cuda:1  33)   target:  0.031  decorr:  6.890   train: 1.000  test: 0.902\n",
      "cuda:1  35)   target:  0.028  decorr:  7.029   train: 1.000  test: 0.903\n",
      "cuda:1  37)   target:  0.025  decorr:  6.979   train: 1.000  test: 0.904\n",
      "cuda:1  39)   target:  0.023  decorr:  6.901   train: 1.000  test: 0.904\n",
      "\n",
      "Total execution time 3.788 sec\n"
     ]
    }
   ],
   "source": [
    "# >>> exclude from multiprocessing\n",
    "# Example training\n",
    "i_train = 1\n",
    "print(model)\n",
    "utils.start_timer()\n",
    "result = train.train(\n",
    "    **(kwargs_partial | {'print_epochs': 2}),\n",
    "    **kwargs_map[i_train]\n",
    ")\n",
    "utils.end_timer_and_print()\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "6555452b-a351-4434-88cd-1cd262602a62",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Only evaluate in multiprocessing script, not in notebook\n",
    "if not utils.is_notebook():\n",
    "    train_partial = partial(train.train, **kwargs_partial)\n",
    "   \n",
    "    # On NVIDIA V100 GPUs, each GPU can simultaneously train two networks\n",
    "    MAX_PROCESSES = 2 * torch.cuda.device_count()\n",
    "    \n",
    "    # Use multiprocessing to train networks in parallel\n",
    "    if __name__ == \"__main__\":\n",
    "        utils.start_timer()\n",
    "        mp.set_start_method('spawn', force=True)\n",
    "        \n",
    "        num_processes = min(len(kwargs_map), MAX_PROCESSES)\n",
    "        with mp.Pool(num_processes) as p:\n",
    "            results = utils.kwstarmap(p, train_partial, kwargs_map)\n",
    "\n",
    "        utils.end_timer_and_print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e77c7d42-cebd-4dc0-a018-39b9186827fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] Converting notebook 1task-concept.ipynb to script\n",
      "[NbConvertApp] Writing 7087 bytes to converted/1task-concept.py\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# >>$ exclude from multiprocessing until end of notebook\n",
    "# Execute helper script to convert notebook to Python script\n",
    "subprocess.call([\"/bin/bash\", \"-c\",\n",
    "                 f\"$(pwd)/converted/nb2script.sh {nb_base}.ipynb\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "3c38f15d-7a9d-445f-ac08-38964454680d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cuda:6   0)   target:  1.293  decorr:  8.143   train: 0.705  test: 0.858\n",
      "cuda:6  39)   target:  0.010  decorr:  6.318   train: 1.000  test: 0.932\n",
      "cuda:7   0)   target:  1.265  decorr:  9.002   train: 0.728  test: 0.863\n",
      "cuda:7  39)   target:  0.010  decorr:  6.248   train: 1.000  test: 0.932\n",
      "cuda:4   0)   target:  1.840  decorr:  3.871   train: 0.524  test: 0.742\n",
      "cuda:4  39)   target:  0.040  decorr:  1.176   train: 1.000  test: 0.913\n",
      "cuda:5   0)   target:  1.815  decorr:  3.782   train: 0.518  test: 0.758\n",
      "cuda:5  39)   target:  0.040  decorr:  1.187   train: 1.000  test: 0.913\n",
      "cuda:4   0)   target:  1.322  decorr:  8.530   train: 0.705  test: 0.869\n",
      "cuda:4  39)   target:  0.009  decorr:  6.549   train: 1.000  test: 0.930\n",
      "cuda:5   0)   target:  1.282  decorr:  8.349   train: 0.707  test: 0.859\n",
      "cuda:5  39)   target:  0.010  decorr:  6.401   train: 1.000  test: 0.933\n",
      "cuda:6   0)   target:  1.881  decorr:  3.916   train: 0.494  test: 0.760\n",
      "cuda:6  39)   target:  0.040  decorr:  1.162   train: 1.000  test: 0.916\n",
      "cuda:7   0)   target:  1.772  decorr:  4.274   train: 0.543  test: 0.743\n",
      "cuda:7  39)   target:  0.044  decorr:  1.171   train: 1.000  test: 0.913\n",
      "cuda:4   0)   target:  1.879  decorr:  6.827   train: 0.517  test: 0.703\n",
      "cuda:4  39)   target:  0.023  decorr:  6.768   train: 0.999  test: 0.900\n",
      "cuda:5   0)   target:  1.952  decorr:  7.365   train: 0.490  test: 0.687\n",
      "cuda:5  39)   target:  0.023  decorr:  6.647   train: 0.999  test: 0.899\n",
      "cuda:2   0)   target:  0.995  decorr:  8.229   train: 0.762  test: 0.889\n",
      "cuda:2  39)   target:  0.007  decorr:  6.422   train: 1.000  test: 0.946\n",
      "cuda:3   0)   target:  1.003  decorr:  7.856   train: 0.784  test: 0.890\n",
      "cuda:3  39)   target:  0.007  decorr:  6.181   train: 1.000  test: 0.944\n",
      "cuda:2   0)   target:  1.961  decorr:  7.805   train: 0.481  test: 0.679\n",
      "cuda:2  39)   target:  0.022  decorr:  6.691   train: 1.000  test: 0.901\n",
      "cuda:3   0)   target:  1.983  decorr:  7.320   train: 0.498  test: 0.723\n",
      "cuda:3  39)   target:  0.024  decorr:  6.609   train: 0.999  test: 0.900\n",
      "cuda:4   0)   target:  1.060  decorr:  9.348   train: 0.752  test: 0.884\n",
      "cuda:4  39)   target:  0.008  decorr:  6.305   train: 1.000  test: 0.941\n",
      "cuda:5   0)   target:  1.036  decorr:  8.536   train: 0.760  test: 0.884\n",
      "cuda:5  39)   target:  0.007  decorr:  6.377   train: 1.000  test: 0.947\n",
      "cuda:2   0)   target:  1.314  decorr:  7.884   train: 0.713  test: 0.839\n",
      "cuda:2  39)   target:  0.010  decorr:  6.384   train: 1.000  test: 0.932\n",
      "cuda:3   0)   target:  1.290  decorr:  8.992   train: 0.709  test: 0.859\n",
      "cuda:3  39)   target:  0.009  decorr:  6.369   train: 1.000  test: 0.934\n",
      "cuda:0   0)   target:  1.611  decorr:  3.263   train: 0.629  test: 0.821\n",
      "cuda:0  39)   target:  0.032  decorr:  1.128   train: 1.000  test: 0.926\n",
      "cuda:1   0)   target:  1.627  decorr:  3.827   train: 0.589  test: 0.787\n",
      "cuda:1  39)   target:  0.033  decorr:  1.114   train: 0.999  test: 0.923\n",
      "cuda:4   0)   target:  1.131  decorr:  7.949   train: 0.749  test: 0.876\n",
      "cuda:4  39)   target:  0.008  decorr:  6.463   train: 1.000  test: 0.937\n",
      "cuda:5   0)   target:  1.140  decorr:  8.558   train: 0.736  test: 0.875\n",
      "cuda:5  39)   target:  0.008  decorr:  6.377   train: 1.000  test: 0.940\n",
      "cuda:4   0)   target:  1.607  decorr:  3.340   train: 0.629  test: 0.802\n",
      "cuda:4  39)   target:  0.033  decorr:  1.113   train: 1.000  test: 0.924\n",
      "cuda:5   0)   target:  1.584  decorr:  3.917   train: 0.592  test: 0.788\n",
      "cuda:5  39)   target:  0.034  decorr:  1.095   train: 1.000  test: 0.924\n",
      "cuda:0   0)   target:  1.143  decorr:  7.529   train: 0.735  test: 0.880\n",
      "cuda:0  39)   target:  0.008  decorr:  6.181   train: 1.000  test: 0.937\n",
      "cuda:1   0)   target:  1.117  decorr:  9.172   train: 0.744  test: 0.875\n",
      "cuda:1  39)   target:  0.007  decorr:  6.383   train: 1.000  test: 0.938\n",
      "cuda:2   0)   target:  1.613  decorr:  4.207   train: 0.607  test: 0.796\n",
      "cuda:2  39)   target:  0.034  decorr:  1.130   train: 1.000  test: 0.925\n",
      "cuda:3   0)   target:  1.645  decorr:  3.487   train: 0.620  test: 0.808\n",
      "cuda:3  39)   target:  0.032  decorr:  1.107   train: 1.000  test: 0.925\n",
      "cuda:4   0)   target:  1.556  decorr:  8.659   train: 0.625  test: 0.824\n",
      "cuda:4  39)   target:  0.014  decorr:  6.736   train: 1.000  test: 0.925\n",
      "cuda:5   0)   target:  1.569  decorr:  8.606   train: 0.654  test: 0.806\n",
      "cuda:5  39)   target:  0.013  decorr:  6.789   train: 1.000  test: 0.921\n",
      "cuda:2   0)   target:  2.043  decorr:  4.251   train: 0.414  test: 0.620\n",
      "cuda:2  39)   target:  0.066  decorr:  1.345   train: 1.000  test: 0.890\n",
      "cuda:3   0)   target:  2.106  decorr:  5.154   train: 0.335  test: 0.615\n",
      "cuda:3  39)   target:  0.066  decorr:  1.341   train: 1.000  test: 0.892\n",
      "cuda:6   0)   target:  1.693  decorr:  3.119   train: 0.613  test: 0.813\n",
      "cuda:6  39)   target:  0.032  decorr:  1.096   train: 1.000  test: 0.927\n",
      "cuda:7   0)   target:  1.588  decorr:  3.583   train: 0.638  test: 0.825\n",
      "cuda:7  39)   target:  0.032  decorr:  1.097   train: 1.000  test: 0.920\n",
      "cuda:6   0)   target:  1.596  decorr:  7.572   train: 0.629  test: 0.801\n",
      "cuda:6  39)   target:  0.013  decorr:  6.390   train: 1.000  test: 0.922\n",
      "cuda:7   0)   target:  1.598  decorr:  9.548   train: 0.617  test: 0.799\n",
      "cuda:7  39)   target:  0.013  decorr:  6.744   train: 1.000  test: 0.923\n",
      "cuda:4   0)   target:  2.095  decorr:  5.238   train: 0.312  test: 0.565\n",
      "cuda:4  39)   target:  0.066  decorr:  1.312   train: 1.000  test: 0.897\n",
      "cuda:5   0)   target:  2.137  decorr:  5.042   train: 0.323  test: 0.607\n",
      "cuda:5  39)   target:  0.071  decorr:  1.293   train: 0.999  test: 0.888\n",
      "cuda:4   0)   target:  1.479  decorr:  3.279   train: 0.687  test: 0.840\n",
      "cuda:4  39)   target:  0.029  decorr:  1.080   train: 0.999  test: 0.932\n",
      "cuda:5   0)   target:  1.500  decorr:  2.690   train: 0.680  test: 0.837\n",
      "cuda:5  39)   target:  0.026  decorr:  1.092   train: 1.000  test: 0.928\n",
      "cuda:2   0)   target:  1.565  decorr:  8.142   train: 0.621  test: 0.817\n",
      "cuda:2  39)   target:  0.013  decorr:  6.696   train: 1.000  test: 0.921\n",
      "cuda:3   0)   target:  1.628  decorr:  8.630   train: 0.584  test: 0.795\n",
      "cuda:3  39)   target:  0.013  decorr:  6.876   train: 1.000  test: 0.922\n",
      "cuda:6   0)   target:  2.182  decorr:  4.934   train: 0.264  test: 0.579\n",
      "cuda:6  39)   target:  0.072  decorr:  1.292   train: 1.000  test: 0.887\n",
      "cuda:7   0)   target:  2.105  decorr:  4.275   train: 0.344  test: 0.564\n",
      "cuda:7  39)   target:  0.065  decorr:  1.319   train: 0.999  test: 0.892\n",
      "cuda:6   0)   target:  1.542  decorr:  3.491   train: 0.645  test: 0.826\n",
      "cuda:6  39)   target:  0.030  decorr:  1.092   train: 0.999  test: 0.925\n",
      "cuda:7   0)   target:  1.529  decorr:  3.244   train: 0.652  test: 0.846\n",
      "cuda:7  39)   target:  0.027  decorr:  1.069   train: 1.000  test: 0.934\n",
      "cuda:2   0)   target:  1.158  decorr:  8.205   train: 0.741  test: 0.875\n",
      "cuda:2  39)   target:  0.007  decorr:  6.041   train: 1.000  test: 0.938\n",
      "cuda:3   0)   target:  1.097  decorr:  8.245   train: 0.743  test: 0.879\n",
      "cuda:3  39)   target:  0.008  decorr:  6.268   train: 1.000  test: 0.937\n",
      "cuda:0   0)   target:  1.455  decorr:  2.920   train: 0.690  test: 0.851\n",
      "cuda:0  39)   target:  0.027  decorr:  1.065   train: 1.000  test: 0.929\n",
      "cuda:1   0)   target:  1.480  decorr:  3.181   train: 0.650  test: 0.820\n",
      "cuda:1  39)   target:  0.027  decorr:  1.053   train: 1.000  test: 0.930\n",
      "cuda:6   0)   target:  1.115  decorr:  8.949   train: 0.742  test: 0.873\n",
      "cuda:6  39)   target:  0.008  decorr:  6.780   train: 1.000  test: 0.939\n",
      "cuda:7   0)   target:  1.148  decorr:  8.263   train: 0.741  test: 0.876\n",
      "cuda:7  39)   target:  0.008  decorr:  6.504   train: 1.000  test: 0.941\n",
      "cuda:2   0)   target:  1.439  decorr:  3.159   train: 0.691  test: 0.850\n",
      "cuda:2  39)   target:  0.028  decorr:  1.073   train: 1.000  test: 0.928\n",
      "cuda:3   0)   target:  1.483  decorr:  2.800   train: 0.674  test: 0.843\n",
      "cuda:3  39)   target:  0.028  decorr:  1.074   train: 1.000  test: 0.930\n",
      "cuda:0   0)   target:  1.966  decorr:  7.106   train: 0.476  test: 0.676\n",
      "cuda:0  39)   target:  0.024  decorr:  6.404   train: 0.999  test: 0.902\n",
      "cuda:1   0)   target:  1.967  decorr:  6.563   train: 0.498  test: 0.701\n",
      "cuda:1  39)   target:  0.022  decorr:  6.621   train: 1.000  test: 0.899\n",
      "cuda:0   0)   target:  1.040  decorr:  8.527   train: 0.751  test: 0.888\n",
      "cuda:0  39)   target:  0.007  decorr:  6.475   train: 1.000  test: 0.946\n",
      "cuda:1   0)   target:  1.018  decorr:  8.705   train: 0.755  test: 0.884\n",
      "cuda:1  39)   target:  0.007  decorr:  6.298   train: 1.000  test: 0.944\n",
      "cuda:2   0)   target:  1.314  decorr:  3.208   train: 0.714  test: 0.864\n",
      "cuda:2  39)   target:  0.025  decorr:  1.057   train: 1.000  test: 0.933\n",
      "cuda:3   0)   target:  1.324  decorr:  2.818   train: 0.719  test: 0.866\n",
      "cuda:3  39)   target:  0.026  decorr:  1.028   train: 0.999  test: 0.926\n",
      "cuda:0   0)   target:  1.316  decorr:  8.143   train: 0.706  test: 0.865\n",
      "cuda:0  39)   target:  0.010  decorr:  6.337   train: 1.000  test: 0.933\n",
      "cuda:1   0)   target:  1.332  decorr:  8.661   train: 0.690  test: 0.864\n",
      "cuda:1  39)   target:  0.010  decorr:  6.389   train: 1.000  test: 0.931\n",
      "cuda:0   0)   target:  1.810  decorr:  3.379   train: 0.542  test: 0.766\n",
      "cuda:0  39)   target:  0.040  decorr:  1.207   train: 1.000  test: 0.902\n",
      "cuda:1   0)   target:  1.765  decorr:  4.315   train: 0.583  test: 0.777\n",
      "cuda:1  39)   target:  0.044  decorr:  1.180   train: 1.000  test: 0.914\n",
      "cuda:0   0)   target:  1.290  decorr:  3.155   train: 0.722  test: 0.867\n",
      "cuda:0  39)   target:  0.025  decorr:  1.044   train: 1.000  test: 0.937\n",
      "cuda:1   0)   target:  1.348  decorr:  2.895   train: 0.713  test: 0.866\n",
      "cuda:1  39)   target:  0.025  decorr:  1.034   train: 0.999  test: 0.934\n",
      "cuda:0   0)   target:  1.546  decorr:  7.848   train: 0.671  test: 0.819\n",
      "cuda:0  39)   target:  0.012  decorr:  6.272   train: 1.000  test: 0.922\n",
      "cuda:1   0)   target:  1.546  decorr:  8.481   train: 0.626  test: 0.794\n",
      "cuda:1  39)   target:  0.013  decorr:  6.500   train: 1.000  test: 0.919\n",
      "cuda:0   0)   target:  2.102  decorr:  4.951   train: 0.319  test: 0.638\n",
      "cuda:0  39)   target:  0.067  decorr:  1.333   train: 1.000  test: 0.902\n",
      "cuda:1   0)   target:  2.094  decorr:  5.182   train: 0.330  test: 0.633\n",
      "cuda:1  39)   target:  0.065  decorr:  1.324   train: 1.000  test: 0.900\n",
      "cuda:2   0)   target:  1.834  decorr:  3.802   train: 0.536  test: 0.787\n",
      "cuda:2  39)   target:  0.041  decorr:  1.171   train: 0.999  test: 0.917\n",
      "cuda:3   0)   target:  1.854  decorr:  4.301   train: 0.518  test: 0.735\n",
      "cuda:3  39)   target:  0.048  decorr:  1.148   train: 0.999  test: 0.912\n",
      "cuda:4   0)   target:  1.386  decorr:  2.893   train: 0.692  test: 0.861\n",
      "cuda:4  39)   target:  0.025  decorr:  1.032   train: 0.999  test: 0.935\n",
      "cuda:5   0)   target:  1.321  decorr:  2.965   train: 0.715  test: 0.867\n",
      "cuda:5  39)   target:  0.026  decorr:  1.055   train: 1.000  test: 0.930\n",
      "cuda:6   0)   target:  1.890  decorr:  6.910   train: 0.551  test: 0.748\n",
      "cuda:6  39)   target:  0.022  decorr:  6.766   train: 1.000  test: 0.899\n",
      "cuda:7   0)   target:  1.968  decorr:  7.558   train: 0.495  test: 0.727\n",
      "cuda:7  39)   target:  0.023  decorr:  6.497   train: 1.000  test: 0.897\n",
      "cuda:6   0)   target:  1.052  decorr:  9.002   train: 0.750  test: 0.893\n",
      "cuda:6  39)   target:  0.006  decorr:  6.596   train: 1.000  test: 0.947\n",
      "cuda:7   0)   target:  0.989  decorr:  7.632   train: 0.783  test: 0.889\n",
      "cuda:7  39)   target:  0.007  decorr:  6.023   train: 1.000  test: 0.947\n",
      "cuda:6   0)   target:  1.371  decorr:  2.913   train: 0.697  test: 0.859\n",
      "cuda:6  39)   target:  0.025  decorr:  1.038   train: 0.999  test: 0.933\n",
      "cuda:7   0)   target:  1.408  decorr:  2.767   train: 0.698  test: 0.857\n",
      "cuda:7  39)   target:  0.025  decorr:  1.039   train: 1.000  test: 0.933\n",
      "\n",
      "Total execution time 111.485 sec\n"
     ]
    }
   ],
   "source": [
    "# Run script using multiprocessing. Progress can be monitored using\n",
    "# the jupyter terminal or by jupyterlab-nvdashboard\n",
    "nb_script = f\"converted/{nb_base}.py\"\n",
    "%run -i $nb_script"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49ea10c0-e09f-41ac-9cf5-02f6595e36df",
   "metadata": {},
   "source": [
    "# Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "50beeae4-ba15-429e-b794-f5acb768d24f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Collecting results across trained networks\n",
    "losses = np.array([result[0] for result in results])\n",
    "train_accuracies = np.array([result[1] for result in results])\n",
    "test_accuracies = np.array([result[2] for result in results])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "625022d8-16e5-476f-ac09-02d54d761d23",
   "metadata": {},
   "outputs": [],
   "source": [
    "if \"h5file\" in globals():\n",
    "    h5file.close()\n",
    "h5file = h5py.File(f\"out/{nb_base}.h5\", 'w')\n",
    "\n",
    "h5file.create_dataset(\"class_sizes\", data=class_sizes)\n",
    "h5file.create_dataset(\"losses\", data=losses)\n",
    "h5file.create_dataset(\"train_accuracies\", data=train_accuracies)\n",
    "h5file.create_dataset(\"test_accuracies\", data=test_accuracies)\n",
    "\n",
    "h5file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "8cc209de-ae17-4c05-8d73-7733d2e96d13",
   "metadata": {},
   "outputs": [],
   "source": [
    "sizes_by_criterion = np.array(class_sizes).reshape((2,-1))\n",
    "accuracies_by_criterion = test_accuracies[:,-1].reshape((2,-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "e3f311e0-71fc-4706-9dc2-7367869e87b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = ('baseline', 'DeCorr')\n",
    "colors = ('tab:orange', 'tab:purple')\n",
    "shift = 0.10\n",
    "shift_facs = sizes_by_criterion[0, 0] * np.array((-shift, shift))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 5))\n",
    "for sizes, accuracies, shift, color, label \\\n",
    "in zip(sizes_by_criterion, accuracies_by_criterion,\n",
    "       shift_facs, colors, labels):\n",
    "    ax.scatter(sizes + shift, accuracies, color=color, label=label)\n",
    "ax.set_xticks(CLASS_SIZES)\n",
    "ax.set_xlabel(\"dataset size per digit class\")\n",
    "ax.set_ylabel(\"concept accuracy\")\n",
    "ax.xaxis.set_major_formatter(ticker.ScalarFormatter())\n",
    "ax.xaxis.set_minor_formatter(ticker.NullFormatter())\n",
    "ax.legend(loc=\"lower right\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}


================================================
FILE: ml/1task-example.ipynb
================================================
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a30f02da-2469-40fb-a877-c60a11e99f51",
   "metadata": {},
   "source": [
    "Only differences between this notebook an `1task-concept.ipynb` will be commented here. See `1task-concept.ipynb` for more thorough explanations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "012dbd0a-82ff-4eed-9c02-3fb167e320f2",
   "metadata": {},
   "source": [
    "# General setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e66fd64e-d56f-4bf8-9b36-e92233d9477e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys, subprocess\n",
    "import time\n",
    "from glob import glob\n",
    "import itertools\n",
    "from functools import partial\n",
    "import copy\n",
    "import gc\n",
    "\n",
    "import importlib\n",
    "sys.path.insert(1, os.path.realpath('lib'))\n",
    "if \"utils\" not in sys.modules: import utils\n",
    "else: importlib.reload(utils)\n",
    "if \"ml\" not in sys.modules: import ml\n",
    "else: importlib.reload(ml)\n",
    "if \"train\" not in sys.modules: import train\n",
    "else: importlib.reload(train)\n",
    "\n",
    "# >>>\n",
    "import ipynbname\n",
    "nb_base = ipynbname.name().split('_')[0]\n",
    "# <<<\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "# >>>\n",
    "from scipy import stats\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams.update({'font.size': 14})\n",
    "from matplotlib import ticker\n",
    "import h5py\n",
    "# <<<\n",
    "\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "from torchvision import datasets\n",
    "from torchvision.transforms import Compose, ToTensor, Normalize\n",
    "if not utils.is_notebook():\n",
    "    import torch.multiprocessing as mp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6432fe38-e245-4d74-bebf-ffe9ebbd1335",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cuda device\n"
     ]
    }
   ],
   "source": [
    "# >>>\n",
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
    "print(f\"Using {device} device\")\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc9e2a1e-76a9-475f-b845-dec39bbb513f",
   "metadata": {},
   "source": [
    "# Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e8a0ac31-0c65-4489-9be5-4461b6695b88",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "transform = Compose([\n",
    "    ToTensor(),\n",
    "    Normalize((0.1307,), (0.3081,))\n",
    "])\n",
    "\n",
    "raw_train_dataset = datasets.MNIST(\n",
    "    root=\"../data\",\n",
    "    train=True,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")\n",
    "\n",
    "raw_test_dataset = datasets.MNIST(\n",
    "    root=\"../data\",\n",
    "    train=False,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a731b26c-f5b1-40c9-9aa0-7d698b7a3bd5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of X [N, C, H, W]:  torch.Size([16, 1, 28, 28])\n",
      "Shape of y:  torch.Size([16]) torch.int64\n",
      "Shape of z:  torch.Size([16]) torch.int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x72 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([8, 3, 2, 2, 2, 3, 1, 2, 0, 7, 9, 3])\n",
      "tensor([19, 10, 17, 14, 16, 13, 11, 12,  6, 12, 11, 12])\n"
     ]
    }
   ],
   "source": [
    "# >>>\n",
    "preview_dataloader = DataLoader(\n",
    "    ml.RelabeledSubset(raw_train_dataset, class_size=100,\n",
    "                       target2_config=20, transform=transform),\n",
    "    batch_size=16, shuffle=True)\n",
    "\n",
    "X, y, z = next(iter(preview_dataloader))\n",
    "print(\"Shape of X [N, C, H, W]: \", X.shape)\n",
    "print(\"Shape of y: \", y.shape, y.dtype)\n",
    "print(\"Shape of z: \", z.shape, z.dtype)\n",
    "    \n",
    "utils.plot_images(X.clamp_(-1, 1), num=12)\n",
    "print(y[:12])\n",
    "print(z[:12])\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a692324-6056-4ebd-9c8b-b17db6984505",
   "metadata": {},
   "source": [
    "# Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b24fa7f1-7336-433d-8b84-914ee02619d5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HIDDEN_SIZE = 50\n",
    "CLASS_SIZES = [20, 40, 60, 80, 100]\n",
    "num_sizes = len(CLASS_SIZES)\n",
    "BATCH_SIZE = 50\n",
    "NUM_SETS = 10\n",
    "\n",
    "DECORR_STRENGTH = 0.5\n",
    "NUM_REPLICATES = 8\n",
    "\n",
    "class_sizes = [rep\n",
    "               for size in CLASS_SIZES\n",
    "               for rep in (size,)*NUM_REPLICATES]*2\n",
    "decorr_criteria = [rep\n",
    "                   for criterion in (None, ml.decorr_criterion)\n",
    "                   for rep in (criterion,)*NUM_REPLICATES*num_sizes]\n",
    "\n",
    "# Evaluate set identification data with noisy test data\n",
    "MODE = 'set'\n",
    "\n",
    "train_datasets = [(\n",
    "    ml.RelabeledSubset,\n",
    "    dict(dataset=raw_train_dataset, class_size=class_size,\n",
    "         target2_config=NUM_SETS, transform=transform)\n",
    ") for class_size in class_sizes]\n",
    "test_dataset = None \n",
    "\n",
    "model = (\n",
    "    ml.MLP,\n",
    "    dict(hidden_size=HIDDEN_SIZE, target_size=NUM_SETS,\n",
    "         nonlinearity1=nn.Tanh(), nonlinearity2=nn.Tanh())\n",
    ")\n",
    "\n",
    "devices = itertools.cycle([torch.device('cuda', i)\n",
    "                           for i in range(torch.cuda.device_count())])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "efe080ae-adb4-4018-9f61-f9f592b8e4ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x72 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "NUM_EPOCHS = 100\n",
    "PRINT_EPOCHS = NUM_EPOCHS\n",
    "LEARNING_RATE = 1e-4\n",
    "WEIGHT_DECAY = 0\n",
    "\n",
    "# Function for randomly setting a fraction 0.2 of rescaled to pixels\n",
    "# to 0, which is the mean pixel value. Used for generating test data.\n",
    "def NOISE_FN(data):\n",
    "    mask = torch.rand_like(data)\n",
    "    threshold = mask.quantile(0.2)\n",
    "    mask = (mask - threshold > 0).float()\n",
    "    noisy_data = data * mask\n",
    "    return noisy_data\n",
    "\n",
    "# >>>\n",
    "# Sample test data\n",
    "X, _, _ = next(iter(preview_dataloader))\n",
    "noisy_X = NOISE_FN(X)\n",
    "utils.plot_images(noisy_X.clamp_(-1., 1.), num=12)\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3e0675d8-0ff7-4ddf-a2a6-543b8340a9a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'device': device(type='cuda', index=1),\n",
       " 'train_dataset': (ml.RelabeledSubset,\n",
       "  {'dataset': Dataset MNIST\n",
       "       Number of datapoints: 60000\n",
       "       Root location: ../../../PyTorchShared/Datasets\n",
       "       Split: Train\n",
       "       StandardTransform\n",
       "   Transform: Compose(\n",
       "                  ToTensor()\n",
       "                  Normalize(mean=(0.1307,), std=(0.3081,))\n",
       "              ),\n",
       "   'class_size': 20,\n",
       "   'target2_config': 10,\n",
       "   'transform': Compose(\n",
       "       ToTensor()\n",
       "       Normalize(mean=(0.1307,), std=(0.3081,))\n",
       "   )}),\n",
       " 'decorr_criterion': None}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kwargs_map = [dict(device=dev,\n",
    "                   train_dataset=param0,\n",
    "                   decorr_criterion=param1)\n",
    "               for dev, param0, param1\n",
    "               in zip(devices,\n",
    "                      train_datasets,\n",
    "                      decorr_criteria)]\n",
    "kwargs_partial = dict(model=model,\n",
    "                      mode=MODE,\n",
    "                      test_dataset=test_dataset,\n",
    "                      decorr_strength=DECORR_STRENGTH,\n",
    "                      noise_fn=NOISE_FN,\n",
    "                      batch_size=BATCH_SIZE,\n",
    "                      learning_rate=LEARNING_RATE,\n",
    "                      num_epochs=NUM_EPOCHS,\n",
    "                      print_epochs=PRINT_EPOCHS)\n",
    "# >>>\n",
    "kwargs_map[0]\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ea5af23e-5c0d-4ffe-a963-7db0bbf65ab3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(<class 'ml.MLP'>, {'hidden_size': 50, 'target_size': 10, 'nonlinearity1': Tanh(), 'nonlinearity2': Tanh()})\n",
      "cuda:0   0)   target:  2.328  decorr:  6.573   train: 0.105  test: 0.105\n",
      "cuda:0   4)   target:  2.280  decorr:  2.204   train: 0.144  test: 0.151\n",
      "cuda:0   9)   target:  2.239  decorr:  1.591   train: 0.205  test: 0.204\n",
      "cuda:0  14)   target:  2.196  decorr:  1.398   train: 0.250  test: 0.249\n",
      "cuda:0  19)   target:  2.137  decorr:  1.287   train: 0.296  test: 0.281\n",
      "cuda:0  24)   target:  2.063  decorr:  1.220   train: 0.356  test: 0.342\n",
      "cuda:0  29)   target:  1.960  decorr:  1.208   train: 0.405  test: 0.371\n",
      "cuda:0  34)   target:  1.834  decorr:  1.195   train: 0.478  test: 0.415\n",
      "cuda:0  39)   target:  1.668  decorr:  1.165   train: 0.545  test: 0.463\n",
      "cuda:0  44)   target:  1.482  decorr:  1.174   train: 0.624  test: 0.518\n",
      "cuda:0  49)   target:  1.279  decorr:  1.181   train: 0.697  test: 0.572\n",
      "cuda:0  54)   target:  1.078  decorr:  1.189   train: 0.774  test: 0.616\n",
      "cuda:0  59)   target:  0.884  decorr:  1.161   train: 0.831  test: 0.672\n",
      "cuda:0  64)   target:  0.705  decorr:  1.162   train: 0.896  test: 0.690\n",
      "cuda:0  69)   target:  0.570  decorr:  1.191   train: 0.923  test: 0.710\n",
      "cuda:0  74)   target:  0.454  decorr:  1.161   train: 0.957  test: 0.713\n",
      "cuda:0  79)   target:  0.368  decorr:  1.160   train: 0.969  test: 0.730\n",
      "cuda:0  84)   target:  0.303  decorr:  1.147   train: 0.982  test: 0.726\n",
      "cuda:0  89)   target:  0.250  decorr:  1.124   train: 0.991  test: 0.730\n",
      "cuda:0  94)   target:  0.210  decorr:  1.101   train: 0.997  test: 0.741\n",
      "cuda:0  99)   target:  0.179  decorr:  1.130   train: 0.998  test: 0.740\n",
      "\n",
      "Total execution time 5.644 sec\n"
     ]
    }
   ],
   "source": [
    "# >>>\n",
    "i_train = -1\n",
    "print(model)\n",
    "utils.start_timer()\n",
    "result = train.train(\n",
    "    **(kwargs_partial | {'print_epochs': 5}),\n",
    "    **kwargs_map[i_train]\n",
    ")\n",
    "utils.end_timer_and_print()\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6555452b-a351-4434-88cd-1cd262602a62",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "if not utils.is_notebook():\n",
    "    train_partial = partial(train.train, **kwargs_partial)\n",
    "   \n",
    "    MAX_PROCESSES = 2 * torch.cuda.device_count()\n",
    "    \n",
    "    if __name__ == \"__main__\":\n",
    "        utils.start_timer()\n",
    "        mp.set_start_method('spawn', force=True)\n",
    "        \n",
    "        num_processes = min(len(kwargs_map), MAX_PROCESSES)\n",
    "        with mp.Pool(num_processes) as p:\n",
    "            results = utils.kwstarmap(p, train_partial, kwargs_map)\n",
    "\n",
    "        utils.end_timer_and_print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e77c7d42-cebd-4dc0-a018-39b9186827fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] Converting notebook 1task-example.ipynb to script\n",
      "[NbConvertApp] Writing 6631 bytes to converted/1task-example.py\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# >>$\n",
    "subprocess.call([\"/bin/bash\", \"-c\",\n",
    "                 f\"$(pwd)/converted/nb2script.sh {nb_base}.ipynb\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3c38f15d-7a9d-445f-ac08-38964454680d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cuda:6   0)   target:  2.319  decorr:  7.952   train: 0.093  test: 0.110\n",
      "cuda:6  99)   target:  0.041  decorr:  4.459   train: 1.000  test: 0.743\n",
      "cuda:7   0)   target:  2.317  decorr:  5.690   train: 0.095  test: 0.098\n",
      "cuda:7  99)   target:  0.041  decorr:  4.669   train: 1.000  test: 0.720\n",
      "cuda:0   0)   target:  2.319  decorr:  7.814   train: 0.108  test: 0.127\n",
      "cuda:0  99)   target:  0.249  decorr:  1.214   train: 0.992  test: 0.868\n",
      "cuda:1   0)   target:  2.323  decorr:  7.660   train: 0.115  test: 0.107\n",
      "cuda:1  99)   target:  0.208  decorr:  1.167   train: 0.995  test: 0.863\n",
      "cuda:4   0)   target:  2.309  decorr:  8.601   train: 0.104  test: 0.121\n",
      "cuda:4  99)   target:  0.033  decorr:  4.467   train: 1.000  test: 0.679\n",
      "cuda:5   0)   target:  2.318  decorr:  5.643   train: 0.080  test: 0.110\n",
      "cuda:5  99)   target:  0.031  decorr:  4.429   train: 1.000  test: 0.697\n",
      "cuda:4   0)   target:  2.336  decorr:  6.471   train: 0.087  test: 0.119\n",
      "cuda:4  99)   target:  0.180  decorr:  1.152   train: 0.999  test: 0.825\n",
      "cuda:5   0)   target:  2.330  decorr:  8.218   train: 0.100  test: 0.095\n",
      "cuda:5  99)   target:  0.211  decorr:  1.176   train: 0.996  test: 0.801\n",
      "cuda:0   0)   target:  2.324  decorr:  8.133   train: 0.090  test: 0.090\n",
      "cuda:0  99)   target:  0.109  decorr:  5.346   train: 1.000  test: 0.955\n",
      "cuda:1   0)   target:  2.310  decorr:  7.080   train: 0.110  test: 0.130\n",
      "cuda:1  99)   target:  0.094  decorr:  5.824   train: 1.000  test: 0.940\n",
      "cuda:0   0)   target:  2.317  decorr:  7.070   train: 0.108  test: 0.117\n",
      "cuda:0  99)   target:  0.029  decorr:  4.265   train: 1.000  test: 0.636\n",
      "cuda:1   0)   target:  2.316  decorr:  8.519   train: 0.086  test: 0.138\n",
      "cuda:1  99)   target:  0.029  decorr:  4.151   train: 1.000  test: 0.637\n",
      "cuda:6   0)   target:  2.333  decorr:  7.444   train: 0.098  test: 0.115\n",
      "cuda:6  99)   target:  0.248  decorr:  1.248   train: 1.000  test: 0.930\n",
      "cuda:7   0)   target:  2.333  decorr: 11.923   train: 0.110  test: 0.107\n",
      "cuda:7  99)   target:  0.352  decorr:  1.333   train: 0.990  test: 0.912\n",
      "cuda:0   0)   target:  2.316  decorr:  6.737   train: 0.109  test: 0.106\n",
      "cuda:0  99)   target:  0.032  decorr:  4.240   train: 1.000  test: 0.697\n",
      "cuda:1   0)   target:  2.316  decorr:  8.873   train: 0.096  test: 0.120\n",
      "cuda:1  99)   target:  0.030  decorr:  4.435   train: 1.000  test: 0.656\n",
      "cuda:4   0)   target:  2.318  decorr: 12.656   train: 0.110  test: 0.122\n",
      "cuda:4  99)   target:  0.447  decorr:  1.237   train: 0.993  test: 0.885\n",
      "cuda:5   0)   target:  2.333  decorr:  8.497   train: 0.115  test: 0.110\n",
      "cuda:5  99)   target:  0.350  decorr:  1.229   train: 0.998  test: 0.920\n",
      "cuda:6   0)   target:  2.314  decorr:  9.573   train: 0.120  test: 0.140\n",
      "cuda:6  99)   target:  0.058  decorr:  4.990   train: 1.000  test: 0.805\n",
      "cuda:7   0)   target:  2.312  decorr:  9.038   train: 0.100  test: 0.093\n",
      "cuda:7  99)   target:  0.057  decorr:  5.081   train: 1.000  test: 0.782\n",
      "cuda:2   0)   target:  2.332  decorr: 11.255   train: 0.065  test: 0.095\n",
      "cuda:2  99)   target:  0.436  decorr:  1.299   train: 0.988  test: 0.890\n",
      "cuda:3   0)   target:  2.331  decorr:  9.963   train: 0.087  test: 0.085\n",
      "cuda:3  99)   target:  0.441  decorr:  1.274   train: 0.983  test: 0.900\n",
      "cuda:6   0)   target:  2.316  decorr:  8.566   train: 0.065  test: 0.090\n",
      "cuda:6  99)   target:  0.101  decorr:  5.807   train: 1.000  test: 0.945\n",
      "cuda:7   0)   target:  2.309  decorr:  6.929   train: 0.105  test: 0.115\n",
      "cuda:7  99)   target:  0.098  decorr:  5.451   train: 1.000  test: 0.945\n",
      "cuda:6   0)   target:  2.319  decorr:  5.833   train: 0.092  test: 0.115\n",
      "cuda:6  99)   target:  0.028  decorr:  4.403   train: 1.000  test: 0.620\n",
      "cuda:7   0)   target:  2.313  decorr:  6.496   train: 0.099  test: 0.131\n",
      "cuda:7  99)   target:  0.029  decorr:  4.275   train: 1.000  test: 0.652\n",
      "cuda:6   0)   target:  2.320  decorr:  6.209   train: 0.099  test: 0.111\n",
      "cuda:6  99)   target:  0.144  decorr:  1.134   train: 0.998  test: 0.830\n",
      "cuda:7   0)   target:  2.316  decorr:  6.845   train: 0.096  test: 0.116\n",
      "cuda:7  99)   target:  0.123  decorr:  1.097   train: 1.000  test: 0.854\n",
      "cuda:4   0)   target:  2.315  decorr:  6.918   train: 0.110  test: 0.150\n",
      "cuda:4  99)   target:  0.094  decorr:  5.542   train: 1.000  test: 0.970\n",
      "cuda:5   0)   target:  2.305  decorr:  8.100   train: 0.120  test: 0.120\n",
      "cuda:5  99)   target:  0.091  decorr:  5.144   train: 1.000  test: 0.925\n",
      "cuda:2   0)   target:  2.309  decorr:  8.523   train: 0.101  test: 0.140\n",
      "cuda:2  99)   target:  0.026  decorr:  4.227   train: 1.000  test: 0.620\n",
      "cuda:3   0)   target:  2.310  decorr:  8.302   train: 0.104  test: 0.128\n",
      "cuda:3  99)   target:  0.028  decorr:  4.307   train: 1.000  test: 0.633\n",
      "cuda:2   0)   target:  2.322  decorr:  6.603   train: 0.085  test: 0.110\n",
      "cuda:2  99)   target:  0.111  decorr:  5.295   train: 1.000  test: 0.890\n",
      "cuda:3   0)   target:  2.314  decorr:  5.988   train: 0.100  test: 0.090\n",
      "cuda:3  99)   target:  0.102  decorr:  5.637   train: 1.000  test: 0.940\n",
      "cuda:4   0)   target:  2.313  decorr:  8.597   train: 0.102  test: 0.119\n",
      "cuda:4  99)   target:  0.027  decorr:  4.233   train: 1.000  test: 0.637\n",
      "cuda:5   0)   target:  2.318  decorr:  7.489   train: 0.101  test: 0.120\n",
      "cuda:5  99)   target:  0.028  decorr:  4.364   train: 1.000  test: 0.647\n",
      "cuda:2   0)   target:  2.311  decorr:  7.169   train: 0.105  test: 0.125\n",
      "cuda:2  99)   target:  0.031  decorr:  4.379   train: 1.000  test: 0.704\n",
      "cuda:3   0)   target:  2.315  decorr: 10.004   train: 0.080  test: 0.110\n",
      "cuda:3  99)   target:  0.034  decorr:  4.313   train: 1.000  test: 0.686\n",
      "cuda:0   0)   target:  2.330  decorr:  7.294   train: 0.102  test: 0.120\n",
      "cuda:0  99)   target:  0.151  decorr:  1.098   train: 0.999  test: 0.845\n",
      "cuda:1   0)   target:  2.326  decorr:  6.870   train: 0.114  test: 0.130\n",
      "cuda:1  99)   target:  0.164  decorr:  1.141   train: 0.999  test: 0.819\n",
      "cuda:2   0)   target:  2.317  decorr: 10.325   train: 0.107  test: 0.125\n",
      "cuda:2  99)   target:  0.039  decorr:  4.704   train: 1.000  test: 0.775\n",
      "cuda:3   0)   target:  2.310  decorr:  7.176   train: 0.095  test: 0.155\n",
      "cuda:3  99)   target:  0.039  decorr:  4.669   train: 1.000  test: 0.738\n",
      "cuda:6   0)   target:  2.325  decorr:  7.353   train: 0.107  test: 0.100\n",
      "cuda:6  99)   target:  0.186  decorr:  1.177   train: 0.998  test: 0.900\n",
      "cuda:7   0)   target:  2.313  decorr:  7.108   train: 0.110  test: 0.105\n",
      "cuda:7  99)   target:  0.201  decorr:  1.177   train: 0.995  test: 0.880\n",
      "cuda:4   0)   target:  2.321  decorr:  6.838   train: 0.095  test: 0.117\n",
      "cuda:4  99)   target:  0.041  decorr:  4.393   train: 1.000  test: 0.748\n",
      "cuda:5   0)   target:  2.313  decorr:  7.625   train: 0.088  test: 0.112\n",
      "cuda:5  99)   target:  0.041  decorr:  4.630   train: 1.000  test: 0.712\n",
      "cuda:2   0)   target:  2.332  decorr:  7.802   train: 0.083  test: 0.102\n",
      "cuda:2  99)   target:  0.188  decorr:  1.170   train: 1.000  test: 0.867\n",
      "cuda:3   0)   target:  2.329  decorr:  8.340   train: 0.083  test: 0.102\n",
      "cuda:3  99)   target:  0.218  decorr:  1.145   train: 0.997  test: 0.885\n",
      "cuda:2   0)   target:  2.311  decorr:  8.247   train: 0.083  test: 0.115\n",
      "cuda:2  99)   target:  0.063  decorr:  4.923   train: 1.000  test: 0.812\n",
      "cuda:3   0)   target:  2.306  decorr:  6.875   train: 0.120  test: 0.120\n",
      "cuda:3  99)   target:  0.061  decorr:  5.319   train: 1.000  test: 0.822\n",
      "cuda:0   0)   target:  2.334  decorr: 10.178   train: 0.098  test: 0.125\n",
      "cuda:0  99)   target:  0.392  decorr:  1.274   train: 0.985  test: 0.887\n",
      "cuda:1   0)   target:  2.321  decorr:  7.232   train: 0.102  test: 0.107\n",
      "cuda:1  99)   target:  0.290  decorr:  1.247   train: 0.998  test: 0.933\n",
      "cuda:2   0)   target:  2.334  decorr:  7.541   train: 0.092  test: 0.112\n",
      "cuda:2  99)   target:  0.189  decorr:  1.115   train: 0.997  test: 0.760\n",
      "cuda:3   0)   target:  2.317  decorr:  6.115   train: 0.113  test: 0.118\n",
      "cuda:3  99)   target:  0.151  decorr:  1.095   train: 0.999  test: 0.739\n",
      "cuda:0   0)   target:  2.323  decorr:  8.722   train: 0.090  test: 0.087\n",
      "cuda:0  99)   target:  0.058  decorr:  4.664   train: 1.000  test: 0.752\n",
      "cuda:1   0)   target:  2.315  decorr:  8.328   train: 0.107  test: 0.097\n",
      "cuda:1  99)   target:  0.057  decorr:  4.858   train: 1.000  test: 0.810\n",
      "cuda:0   0)   target:  2.311  decorr:  9.436   train: 0.110  test: 0.085\n",
      "cuda:0  99)   target:  0.625  decorr:  1.357   train: 0.970  test: 0.930\n",
      "cuda:1   0)   target:  2.307  decorr: 15.325   train: 0.080  test: 0.080\n",
      "cuda:1  99)   target:  0.585  decorr:  1.424   train: 0.980  test: 0.960\n",
      "cuda:6   0)   target:  2.323  decorr: 15.196   train: 0.125  test: 0.105\n",
      "cuda:6  99)   target:  0.764  decorr:  1.362   train: 0.960  test: 0.895\n",
      "cuda:7   0)   target:  2.333  decorr: 14.943   train: 0.080  test: 0.105\n",
      "cuda:7  99)   target:  0.533  decorr:  1.468   train: 0.990  test: 0.970\n",
      "cuda:6   0)   target:  2.336  decorr:  6.897   train: 0.113  test: 0.107\n",
      "cuda:6  99)   target:  0.162  decorr:  1.090   train: 1.000  test: 0.782\n",
      "cuda:7   0)   target:  2.324  decorr:  7.100   train: 0.115  test: 0.111\n",
      "cuda:7  99)   target:  0.163  decorr:  1.114   train: 0.998  test: 0.758\n",
      "cuda:6   0)   target:  2.316  decorr:  4.865   train: 0.101  test: 0.138\n",
      "cuda:6  99)   target:  0.029  decorr:  4.349   train: 1.000  test: 0.689\n",
      "cuda:7   0)   target:  2.319  decorr:  4.968   train: 0.087  test: 0.120\n",
      "cuda:7  99)   target:  0.032  decorr:  4.297   train: 1.000  test: 0.629\n",
      "cuda:2   0)   target:  2.330  decorr:  7.317   train: 0.110  test: 0.107\n",
      "cuda:2  99)   target:  0.179  decorr:  1.150   train: 0.998  test: 0.840\n",
      "cuda:3   0)   target:  2.319  decorr:  6.733   train: 0.114  test: 0.109\n",
      "cuda:3  99)   target:  0.161  decorr:  1.096   train: 1.000  test: 0.811\n",
      "cuda:0   0)   target:  2.321  decorr:  7.472   train: 0.097  test: 0.117\n",
      "cuda:0  99)   target:  0.039  decorr:  4.434   train: 1.000  test: 0.712\n",
      "cuda:1   0)   target:  2.314  decorr:  6.724   train: 0.083  test: 0.103\n",
      "cuda:1  99)   target:  0.040  decorr:  4.377   train: 1.000  test: 0.747\n",
      "cuda:2   0)   target:  2.292  decorr: 13.930   train: 0.165  test: 0.155\n",
      "cuda:2  99)   target:  0.570  decorr:  1.393   train: 0.985  test: 0.925\n",
      "cuda:3   0)   target:  2.341  decorr: 18.165   train: 0.090  test: 0.090\n",
      "cuda:3  99)   target:  0.631  decorr:  1.440   train: 0.980  test: 0.915\n",
      "cuda:4   0)   target:  2.338  decorr:  6.413   train: 0.097  test: 0.120\n",
      "cuda:4  99)   target:  0.126  decorr:  1.087   train: 1.000  test: 0.745\n",
      "cuda:5   0)   target:  2.337  decorr:  6.629   train: 0.081  test: 0.085\n",
      "cuda:5  99)   target:  0.138  decorr:  1.085   train: 1.000  test: 0.751\n",
      "cuda:4   0)   target:  2.317  decorr:  5.758   train: 0.090  test: 0.097\n",
      "cuda:4  99)   target:  0.058  decorr:  5.007   train: 1.000  test: 0.800\n",
      "cuda:5   0)   target:  2.321  decorr:  5.494   train: 0.085  test: 0.087\n",
      "cuda:5  99)   target:  0.053  decorr:  4.846   train: 1.000  test: 0.808\n",
      "cuda:4   0)   target:  2.307  decorr:  9.210   train: 0.100  test: 0.125\n",
      "cuda:4  99)   target:  0.455  decorr:  1.422   train: 0.995  test: 0.960\n",
      "cuda:5   0)   target:  2.311  decorr:  7.970   train: 0.095  test: 0.055\n",
      "cuda:5  99)   target:  0.433  decorr:  1.399   train: 1.000  test: 0.970\n",
      "cuda:4   0)   target:  2.328  decorr:  8.408   train: 0.080  test: 0.103\n",
      "cuda:4  99)   target:  0.226  decorr:  1.169   train: 1.000  test: 0.872\n",
      "cuda:5   0)   target:  2.328  decorr:  7.533   train: 0.095  test: 0.107\n",
      "cuda:5  99)   target:  0.214  decorr:  1.156   train: 1.000  test: 0.865\n",
      "cuda:0   0)   target:  2.331  decorr:  5.676   train: 0.097  test: 0.116\n",
      "cuda:0  99)   target:  0.122  decorr:  1.077   train: 0.999  test: 0.783\n",
      "cuda:1   0)   target:  2.331  decorr:  7.127   train: 0.101  test: 0.099\n",
      "cuda:1  99)   target:  0.194  decorr:  1.118   train: 0.998  test: 0.732\n",
      "\n",
      "Total execution time 58.634 sec\n"
     ]
    }
   ],
   "source": [
    "nb_script = f\"converted/{nb_base}.py\"\n",
    "%run -i $nb_script"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49ea10c0-e09f-41ac-9cf5-02f6595e36df",
   "metadata": {},
   "source": [
    "# Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "50beeae4-ba15-429e-b794-f5acb768d24f",
   "metadata": {},
   "outputs": [],
   "source": [
    "losses = np.array([result[0] for result in results])\n",
    "train_accuracies = np.array([result[1] for result in results])\n",
    "test_accuracies = np.array([result[2] for result in results])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "625022d8-16e5-476f-ac09-02d54d761d23",
   "metadata": {},
   "outputs": [],
   "source": [
    "if \"h5file\" in globals():\n",
    "    h5file.close()\n",
    "h5file = h5py.File(f\"out/{nb_base}.h5\", 'w')\n",
    "\n",
    "h5file.create_dataset(\"class_sizes\", data=class_sizes)\n",
    "h5file.create_dataset(\"losses\", data=losses)\n",
    "h5file.create_dataset(\"train_accuracies\", data=train_accuracies)\n",
    "h5file.create_dataset(\"test_accuracies\", data=test_accuracies)\n",
    "\n",
    "h5file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8cc209de-ae17-4c05-8d73-7733d2e96d13",
   "metadata": {},
   "outputs": [],
   "source": [
    "sizes_by_criterion = np.array(class_sizes).reshape((2,-1))\n",
    "accuracies_by_criterion = test_accuracies[:,-1].reshape((2,-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e3f311e0-71fc-4706-9dc2-7367869e87b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = ('baseline', 'DeCorr')\n",
    "colors = ('tab:orange', 'tab:purple')\n",
    "shift = 0.10\n",
    "shift_facs = sizes_by_criterion[0, 0] * np.array((-shift, shift))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 5))\n",
    "for sizes, accuracies, shift, color, label \\\n",
    "in zip(sizes_by_criterion, accuracies_by_criterion,\n",
    "       shift_facs, colors, labels):\n",
    "    ax.scatter(sizes + shift, accuracies, color=color, label=label)\n",
    "ax.set_xticks(CLASS_SIZES)\n",
    "ax.set_xlabel(\"dataset size per digit class\")\n",
    "ax.set_ylabel(\"example accuracy\")\n",
    "ax.xaxis.set_major_formatter(ticker.ScalarFormatter())\n",
    "ax.xaxis.set_minor_formatter(ticker.NullFormatter())\n",
    "ax.legend(loc=\"lower left\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}


================================================
FILE: ml/2tasks.ipynb
================================================
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "424db820-9c7d-4f3e-a2cc-037f6e87fd1a",
   "metadata": {},
   "source": [
    "Only differences between this notebook an `1task-concept.ipynb` will be commented here. See `1task-concept.ipynb` for more thorough explanations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "012dbd0a-82ff-4eed-9c02-3fb167e320f2",
   "metadata": {},
   "source": [
    "# General setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "e66fd64e-d56f-4bf8-9b36-e92233d9477e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys, subprocess\n",
    "import time\n",
    "from glob import glob\n",
    "import itertools\n",
    "from functools import partial\n",
    "import copy\n",
    "import gc\n",
    "\n",
    "import importlib\n",
    "sys.path.insert(1, os.path.realpath('lib'))\n",
    "if \"utils\" not in sys.modules: import utils\n",
    "else: importlib.reload(utils)\n",
    "if \"ml\" not in sys.modules: import ml\n",
    "else: importlib.reload(ml)\n",
    "if \"train\" not in sys.modules: import train\n",
    "else: importlib.reload(train)\n",
    "\n",
    "# >>>\n",
    "import ipynbname\n",
    "nb_base = ipynbname.name().split('_')[0]\n",
    "# <<<\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "# >>>\n",
    "from scipy import stats\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams.update({'font.size': 14})\n",
    "import h5py\n",
    "# <<<\n",
    "\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "from torchvision import datasets\n",
    "from torchvision.transforms import Compose, ToTensor, Normalize\n",
    "if not utils.is_notebook():\n",
    "    import torch.multiprocessing as mp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "6432fe38-e245-4d74-bebf-ffe9ebbd1335",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cuda device\n"
     ]
    }
   ],
   "source": [
    "# >>>\n",
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
    "print(f\"Using {device} device\")\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc9e2a1e-76a9-475f-b845-dec39bbb513f",
   "metadata": {},
   "source": [
    "# Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e8a0ac31-0c65-4489-9be5-4461b6695b88",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "transform = Compose([\n",
    "    ToTensor(),\n",
    "    Normalize((0.1307,), (0.3081,))\n",
    "])\n",
    "\n",
    "raw_train_dataset = datasets.MNIST(\n",
    "    root=\"../data\",\n",
    "    train=True,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")\n",
    "\n",
    "raw_test_dataset = datasets.MNIST(\n",
    "    root=\"../data\",\n",
    "    train=False,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a731b26c-f5b1-40c9-9aa0-7d698b7a3bd5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of X [N, C, H, W]:  torch.Size([16, 1, 28, 28])\n",
      "Shape of y:  torch.Size([16]) torch.int64\n",
      "Shape of z:  torch.Size([16]) torch.int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x72 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0, 2, 0, 0, 0, 9, 3, 0, 0, 2, 7, 0])\n",
      "tensor([ 7, 11, 17, 15,  0,  3,  2,  7,  5, 15,  2,  3])\n"
     ]
    }
   ],
   "source": [
    "# >>>\n",
    "preview_dataloader = DataLoader(\n",
    "    ml.RelabeledSubset(raw_train_dataset, class_size=100,\n",
    "                       target2_config=20, transform=transform),\n",
    "    batch_size=16, shuffle=True)\n",
    "\n",
    "X, y, z = next(iter(preview_dataloader))\n",
    "print(\"Shape of X [N, C, H, W]: \", X.shape)\n",
    "print(\"Shape of y: \", y.shape, y.dtype)\n",
    "print(\"Shape of z: \", z.shape, z.dtype)\n",
    "    \n",
    "utils.plot_images(X.clamp_(-1, 1), num=12)\n",
    "print(y[:12])\n",
    "print(z[:12])\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a692324-6056-4ebd-9c8b-b17db6984505",
   "metadata": {},
   "source": [
    "# Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b24fa7f1-7336-433d-8b84-914ee02619d5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HIDDEN_SIZE = 100\n",
    "CLASS_SIZE = 100\n",
    "BATCH_SIZE = 50\n",
    "NUM_SETS = 10\n",
    "\n",
    "DECORR_STRENGTH = 0.5\n",
    "NUM_REPLICATES = 16\n",
    "decorr_criteria = itertools.chain.from_iterable((\n",
    "    itertools.repeat(None, NUM_REPLICATES),\n",
    "    itertools.repeat(ml.decorr_criterion, NUM_REPLICATES),\n",
    "    itertools.repeat(ml.halfcorr_criterion, NUM_REPLICATES)\n",
    "))\n",
    "\n",
    "# Evaluate digit classification performance with held-out test data and save test\n",
    "# activations and outputs.\n",
    "MODE = ['testval', 'testsave']\n",
    "\n",
    "train_dataset = (\n",
    "    ml.RelabeledSubset,\n",
    "    dict(dataset=raw_train_dataset, class_size=CLASS_SIZE,\n",
    "         target2_config=NUM_SETS, transform=transform)\n",
    ")\n",
    "test_dataset = (\n",
    "    ml.RelabeledSubset,\n",
    "    dict(dataset=raw_test_dataset,\n",
    "         target2_config='none', transform=transform)\n",
    ")\n",
    "\n",
    "model = (\n",
    "    ml.TwoTargetMLP,\n",
    "    dict(hidden_size=HIDDEN_SIZE,\n",
    "         target1_size=10, target2_size=NUM_SETS,\n",
    "         nonlinearity1=nn.Tanh(), nonlinearity2=nn.Tanh())\n",
    ")\n",
    "\n",
    "devices = itertools.cycle([torch.device('cuda', i)\n",
    "                           for i in range(torch.cuda.device_count())])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "efe080ae-adb4-4018-9f61-f9f592b8e4ca",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x72 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "NUM_EPOCHS = 100\n",
    "PRINT_EPOCHS = NUM_EPOCHS\n",
    "LEARNING_RATE = 1e-4\n",
    "WEIGHT_DECAY = 0\n",
    "\n",
    "def NOISE_FN(data):\n",
    "    mask = torch.rand_like(data)\n",
    "    threshold = mask.quantile(0.2)\n",
    "    mask = (mask - threshold > 0).float()\n",
    "    noisy_data = data * mask\n",
    "    return noisy_data\n",
    "\n",
    "# >>>\n",
    "X, _, _ = next(iter(preview_dataloader))\n",
    "noisy_X = NOISE_FN(X)\n",
    "utils.plot_images(noisy_X.clamp_(-1., 1.), num=12)\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e59ad133-e25a-4ec0-b718-97f25af2ede2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'device': device(type='cuda', index=0), 'decorr_criterion': None}\n",
      "48\n"
     ]
    }
   ],
   "source": [
    "kwargs_map = [dict(device=dev, decorr_criterion=param)\n",
    "               for dev, param\n",
    "               in zip(devices, decorr_criteria)]\n",
    "kwargs_partial = dict(model=model,\n",
    "                      mode=MODE,\n",
    "                      train_dataset=train_dataset,\n",
    "                      test_dataset=test_dataset,\n",
    "                      decorr_strength=DECORR_STRENGTH,\n",
    "                      noise_fn=NOISE_FN,\n",
    "                      batch_size=BATCH_SIZE,\n",
    "                      learning_rate=LEARNING_RATE,\n",
    "                      num_epochs=NUM_EPOCHS,\n",
    "                      print_epochs=PRINT_EPOCHS)\n",
    "# >>>\n",
    "print(kwargs_map[0])\n",
    "print(len(list(kwargs_map)))\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ea5af23e-5c0d-4ffe-a963-7db0bbf65ab3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(<class 'ml.TwoTargetMLP'>, {'hidden_size': 100, 'target1_size': 10, 'target2_size': 10, 'nonlinearity1': Tanh(), 'nonlinearity2': Tanh()})\n",
      "cuda:0   0)   loss:  2.175  2.327  3.684e+00   train: 0.298 0.108   test: 0.536 0.117\n",
      "cuda:0   4)   loss:  0.794  2.246  1.772e+00   train: 0.862 0.180   test: 0.828 0.181\n",
      "cuda:0   9)   loss:  0.377  2.155  1.486e+00   train: 0.932 0.242   test: 0.862 0.231\n",
      "cuda:0  14)   loss:  0.230  2.057  1.260e+00   train: 0.969 0.296   test: 0.875 0.269\n",
      "cuda:0  19)   loss:  0.154  1.920  1.223e+00   train: 0.986 0.377   test: 0.876 0.322\n",
      "cuda:0  24)   loss:  0.113  1.726  1.165e+00   train: 0.993 0.476   test: 0.874 0.408\n",
      "cuda:0  29)   loss:  0.087  1.470  1.159e+00   train: 0.999 0.612   test: 0.870 0.486\n",
      "cuda:0  34)   loss:  0.074  1.182  1.097e+00   train: 1.000 0.723   test: 0.867 0.571\n",
      "cuda:0  39)   loss:  0.067  0.865  1.114e+00   train: 1.000 0.841   test: 0.868 0.627\n",
      "cuda:0  44)   loss:  0.059  0.598  1.102e+00   train: 1.000 0.917   test: 0.864 0.701\n",
      "cuda:0  49)   loss:  0.052  0.399  1.050e+00   train: 1.000 0.976   test: 0.867 0.749\n",
      "cuda:0  54)   loss:  0.046  0.272  1.071e+00   train: 1.000 0.994   test: 0.868 0.759\n",
      "cuda:0  59)   loss:  0.040  0.191  1.043e+00   train: 1.000 0.998   test: 0.867 0.783\n",
      "cuda:0  64)   loss:  0.035  0.140  1.024e+00   train: 1.000 1.000   test: 0.868 0.779\n",
      "cuda:0  69)   loss:  0.030  0.107  1.020e+00   train: 1.000 1.000   test: 0.867 0.783\n",
      "cuda:0  74)   loss:  0.027  0.089  1.007e+00   train: 1.000 1.000   test: 0.867 0.782\n",
      "cuda:0  79)   loss:  0.024  0.072  9.715e-01   train: 1.000 1.000   test: 0.867 0.781\n",
      "cuda:0  84)   loss:  0.022  0.061  9.795e-01   train: 1.000 1.000   test: 0.867 0.792\n",
      "cuda:0  89)   loss:  0.020  0.053  9.840e-01   train: 1.000 1.000   test: 0.867 0.793\n",
      "cuda:0  94)   loss:  0.018  0.047  9.872e-01   train: 1.000 1.000   test: 0.867 0.794\n",
      "cuda:0  99)   loss:  0.017  0.043  9.825e-01   train: 1.000 1.000   test: 0.868 0.800\n",
      "\n",
      "Total execution time 6.863 sec\n"
     ]
    }
   ],
   "source": [
    "# >>>\n",
    "i_train = 2*NUM_REPLICATES\n",
    "print(model)\n",
    "utils.start_timer()\n",
    "result = train.two_target_train(\n",
    "    **(kwargs_partial | {'print_epochs': 5}),\n",
    "    **kwargs_map[i_train]\n",
    ")\n",
    "utils.end_timer_and_print()\n",
    "# <<<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6555452b-a351-4434-88cd-1cd262602a62",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "if not utils.is_notebook():\n",
    "    train_partial = partial(train.two_target_train, **kwargs_partial)\n",
    "   \n",
    "    MAX_PROCESSES = 2 * torch.cuda.device_count()\n",
    "    \n",
    "    if __name__ == \"__main__\":\n",
    "        utils.start_timer()\n",
    "        mp.set_start_method('spawn', force=True)\n",
    "        \n",
    "        num_processes = min(len(kwargs_map), MAX_PROCESSES)\n",
    "        with mp.Pool(num_processes) as p:\n",
    "            results = utils.kwstarmap(p, train_partial, kwargs_map)\n",
    "\n",
    "        utils.end_timer_and_print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e77c7d42-cebd-4dc0-a018-39b9186827fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] Converting notebook 2tasks.ipynb to script\n",
      "[NbConvertApp] Writing 10747 bytes to converted/2tasks.py\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# >>$\n",
    "subprocess.call([\"/bin/bash\", \"-c\",\n",
    "                 f\"$(pwd)/converted/nb2script.sh {nb_base}.ipynb\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3c38f15d-7a9d-445f-ac08-38964454680d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "cuda:6  99)   loss:  0.014  0.029  3.125e+00   train: 1.000 1.000   test: 0.868 0.776\n",
      "cuda:3   0)   loss:  2.159  2.319  4.365e+00   train: 0.290 0.100   test: 0.535 0.129\n",
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      "cuda:2  99)   loss:  0.018  0.044  9.722e-01   train: 1.000 1.000   test: 0.875 0.856\n",
      "cuda:4   0)   loss:  2.106  2.315  5.970e+00   train: 0.398 0.109   test: 0.633 0.122\n",
      "cuda:4  99)   loss:  0.015  0.029  3.206e+00   train: 1.000 1.000   test: 0.863 0.721\n",
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      "cuda:1  99)   loss:  0.018  0.046  9.997e-01   train: 1.000 1.000   test: 0.866 0.831\n",
      "cuda:0   0)   loss:  2.154  2.316  6.031e+00   train: 0.365 0.098   test: 0.641 0.121\n",
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      "cuda:3   0)   loss:  2.184  2.324  5.163e+00   train: 0.286 0.089   test: 0.559 0.094\n",
      "cuda:3  99)   loss:  0.018  0.044  9.937e-01   train: 1.000 1.000   test: 0.867 0.841\n",
      "cuda:1   0)   loss:  2.153  2.318  7.370e+00   train: 0.354 0.097   test: 0.683 0.118\n",
      "cuda:1  99)   loss:  0.015  0.031  3.202e+00   train: 1.000 1.000   test: 0.868 0.751\n",
      "cuda:0   0)   loss:  2.197  2.315  2.838e+00   train: 0.266 0.083   test: 0.529 0.118\n",
      "cuda:0  99)   loss:  0.025  0.039  8.935e-01   train: 1.000 1.000   test: 0.856 0.782\n",
      "cuda:4   0)   loss:  2.133  2.315  3.816e+00   train: 0.328 0.096   test: 0.597 0.116\n",
      "cuda:4  99)   loss:  0.017  0.043  9.786e-01   train: 1.000 1.000   test: 0.863 0.821\n",
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      "cuda:5   0)   loss:  2.166  2.322  4.119e+00   train: 0.320 0.080   test: 0.596 0.086\n",
      "cuda:5  99)   loss:  0.017  0.044  9.855e-01   train: 1.000 1.000   test: 0.863 0.804\n",
      "cuda:1   0)   loss:  2.159  2.317  4.830e+00   train: 0.345 0.099   test: 0.650 0.116\n",
      "cuda:1  99)   loss:  0.015  0.031  3.273e+00   train: 1.000 1.000   test: 0.865 0.759\n",
      "cuda:2   0)   loss:  2.208  2.310  4.071e+00   train: 0.244 0.108   test: 0.564 0.133\n",
      "cuda:2  99)   loss:  0.025  0.041  9.187e-01   train: 1.000 1.000   test: 0.865 0.810\n",
      "cuda:6   0)   loss:  2.135  2.314  4.280e+00   train: 0.342 0.100   test: 0.603 0.101\n",
      "cuda:6  99)   loss:  0.017  0.042  9.711e-01   train: 1.000 1.000   test: 0.876 0.840\n",
      "cuda:3   0)   loss:  2.162  2.313  7.401e+00   train: 0.307 0.096   test: 0.623 0.124\n",
      "cuda:3  99)   loss:  0.015  0.028  3.127e+00   train: 1.000 1.000   test: 0.869 0.776\n",
      "cuda:5   0)   loss:  2.152  2.315  4.113e+00   train: 0.314 0.101   test: 0.575 0.118\n",
      "cuda:5  99)   loss:  0.025  0.042  8.757e-01   train: 1.000 1.000   test: 0.859 0.800\n",
      "cuda:7   0)   loss:  2.188  2.322  5.750e+00   train: 0.259 0.098   test: 0.485 0.119\n",
      "cuda:7  99)   loss:  0.018  0.046  9.945e-01   train: 1.000 1.000   test: 0.872 0.844\n",
      "cuda:5   0)   loss:  2.155  2.316  7.161e+00   train: 0.328 0.106   test: 0.643 0.136\n",
      "cuda:5  99)   loss:  0.015  0.030  3.153e+00   train: 1.000 1.000   test: 0.864 0.756\n",
      "cuda:7   0)   loss:  2.125  2.321  3.500e+00   train: 0.364 0.093   test: 0.569 0.098\n",
      "cuda:7  99)   loss:  0.026  0.041  9.209e-01   train: 1.000 1.000   test: 0.847 0.783\n",
      "cuda:1   0)   loss:  2.163  2.323  3.806e+00   train: 0.299 0.098   test: 0.561 0.104\n",
      "cuda:1  99)   loss:  0.017  0.042  9.836e-01   train: 1.000 1.000   test: 0.864 0.824\n",
      "cuda:7   0)   loss:  2.144  2.317  5.919e+00   train: 0.361 0.098   test: 0.623 0.119\n",
      "cuda:7  99)   loss:  0.015  0.029  3.125e+00   train: 1.000 1.000   test: 0.873 0.764\n",
      "cuda:1   0)   loss:  2.188  2.310  3.128e+00   train: 0.275 0.106   test: 0.575 0.116\n",
      "cuda:1  99)   loss:  0.025  0.042  8.907e-01   train: 1.000 1.000   test: 0.859 0.779\n",
      "cuda:2   0)   loss:  2.118  2.322  4.583e+00   train: 0.349 0.107   test: 0.629 0.101\n",
      "cuda:2  99)   loss:  0.016  0.043  9.806e-01   train: 1.000 1.000   test: 0.872 0.834\n",
      "cuda:5   0)   loss:  2.126  2.316  7.169e+00   train: 0.361 0.100   test: 0.636 0.127\n",
      "cuda:5  99)   loss:  0.015  0.029  3.368e+00   train: 1.000 1.000   test: 0.865 0.758\n",
      "cuda:4   0)   loss:  2.163  2.322  3.060e+00   train: 0.312 0.097   test: 0.533 0.107\n",
      "cuda:4  99)   loss:  0.026  0.038  8.880e-01   train: 1.000 1.000   test: 0.845 0.770\n",
      "cuda:3   0)   loss:  2.165  2.332  4.963e+00   train: 0.264 0.090   test: 0.522 0.105\n",
      "cuda:3  99)   loss:  0.017  0.045  9.649e-01   train: 1.000 1.000   test: 0.874 0.815\n",
      "cuda:7   0)   loss:  2.161  2.313  5.475e+00   train: 0.340 0.102   test: 0.591 0.109\n",
      "cuda:7  99)   loss:  0.015  0.030  3.039e+00   train: 1.000 1.000   test: 0.867 0.725\n",
      "cuda:5   0)   loss:  2.145  2.304  3.697e+00   train: 0.337 0.113   test: 0.593 0.118\n",
      "cuda:5  99)   loss:  0.026  0.040  9.178e-01   train: 1.000 1.000   test: 0.862 0.779\n",
      "cuda:4   0)   loss:  2.126  2.347  4.809e+00   train: 0.324 0.076   test: 0.588 0.085\n",
      "cuda:4  99)   loss:  0.017  0.045  9.810e-01   train: 1.000 1.000   test: 0.871 0.830\n",
      "cuda:2   0)   loss:  2.152  2.313  6.833e+00   train: 0.375 0.086   test: 0.678 0.129\n",
      "cuda:2  99)   loss:  0.015  0.030  3.321e+00   train: 1.000 1.000   test: 0.868 0.732\n",
      "cuda:6   0)   loss:  2.184  2.312  3.047e+00   train: 0.261 0.098   test: 0.562 0.112\n",
      "cuda:6  99)   loss:  0.026  0.041  8.981e-01   train: 1.000 1.000   test: 0.851 0.770\n",
      "cuda:5   0)   loss:  2.138  2.310  5.050e+00   train: 0.329 0.100   test: 0.564 0.126\n",
      "cuda:5  99)   loss:  0.018  0.044  1.010e+00   train: 1.000 1.000   test: 0.869 0.836\n",
      "cuda:3   0)   loss:  2.118  2.318  6.244e+00   train: 0.375 0.090   test: 0.616 0.126\n",
      "cuda:3  99)   loss:  0.015  0.029  3.018e+00   train: 1.000 1.000   test: 0.864 0.751\n",
      "cuda:7   0)   loss:  2.176  2.308  3.744e+00   train: 0.293 0.112   test: 0.570 0.114\n",
      "cuda:7  99)   loss:  0.026  0.041  9.202e-01   train: 1.000 1.000   test: 0.858 0.783\n",
      "cuda:6   0)   loss:  2.201  2.325  5.578e+00   train: 0.259 0.098   test: 0.408 0.119\n",
      "cuda:6  99)   loss:  0.018  0.045  9.843e-01   train: 1.000 1.000   test: 0.869 0.847\n",
      "cuda:4   0)   loss:  2.159  2.312  6.654e+00   train: 0.338 0.087   test: 0.655 0.120\n",
      "cuda:4  99)   loss:  0.015  0.030  3.118e+00   train: 1.000 1.000   test: 0.873 0.758\n",
      "cuda:2   0)   loss:  2.161  2.315  3.673e+00   train: 0.314 0.111   test: 0.557 0.127\n",
      "cuda:2  99)   loss:  0.026  0.041  9.053e-01   train: 1.000 1.000   test: 0.853 0.803\n",
      "cuda:7   0)   loss:  2.162  2.327  4.640e+00   train: 0.280 0.108   test: 0.523 0.117\n",
      "cuda:7  99)   loss:  0.017  0.044  9.602e-01   train: 1.000 1.000   test: 0.867 0.789\n",
      "\n",
      "Total execution time 54.310 sec\n"
     ]
    }
   ],
   "source": [
    "nb_script = f\"converted/{nb_base}.py\"\n",
    "%run -i $nb_script"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49ea10c0-e09f-41ac-9cf5-02f6595e36df",
   "metadata": {},
   "source": [
    "# Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "d80faa31-46c9-4cef-86b5-f8cdf0fa0c3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "losses = np.array([result[0] for result in results])\n",
    "train_accuracies = np.array([result[1] for result in results])\n",
    "test_accuracies = np.array([result[2] for result in results])\n",
    "y_activations = np.array([result[3][0] for result in results])\n",
    "z_activations = np.array([result[3][1] for result in results])\n",
    "y_weights = np.array([result[4][0] for result in results])\n",
    "z_weights = np.array([result[4][1] for result in results])\n",
    "y_biases = np.array([result[5][0] for result in results])\n",
    "z_biases = np.array([result[5][1] for result in results])\n",
    "class_targets = np.array([result[6][0] for result in results])\n",
    "set_targets = np.array([result[6][1] for result in results])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "91c51522-bd59-4f6c-9b82-fee9274c6ea3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.236612770262297e-08\n",
      "0.16681370962415767\n",
      "1.293784260584245e-08\n",
      "4.594287906734713e-07\n",
      "7.146803536269428e-14\n",
      "2.1346290120781238e-07\n"
     ]
    }
   ],
   "source": [
    "class_accuracies = test_accuracies[:,-1,0].reshape(-1, NUM_REPLICATES)\n",
    "set_accuracies = test_accuracies[:,-1,1].reshape(-1, NUM_REPLICATES)\n",
    "\n",
    "mean_class_accs = class_accuracies.mean(-1)\n",
    "mean_set_accs = set_accuracies.mean(-1)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "labels = ('baseline', 'DeCorr', 'HalfCorr')\n",
    "colors = ('tab:orange', 'tab:purple', 'tab:blue')\n",
    "# individual values as points\n",
    "for accs1, accs2, color, label \\\n",
    "in zip(class_accuracies, set_accuracies, colors, labels):\n",
    "    ax.scatter(accs1, accs2, s=40, color=color, label=label)\n",
    "# means as x's\n",
    "for accs1, accs2, color, label \\\n",
    "in zip(mean_class_accs, mean_set_accs, colors, labels):\n",
    "    ax.scatter(accs1, accs2, s=200, marker=\"x\", color=color)\n",
    "ax.set_xlabel(\"concept accuracy\")\n",
    "ax.set_ylabel(\"episode accuracy\")\n",
    "ax.legend(loc=\"lower left\")\n",
    "plt.show()\n",
    "    \n",
    "print(stats.ttest_ind(class_accuracies[0], class_accuracies[1]).pvalue)\n",
    "print(stats.ttest_ind(class_accuracies[0], class_accuracies[2]).pvalue)\n",
    "print(stats.ttest_ind(class_accuracies[1], class_accuracies[2]).pvalue)\n",
    "print(stats.ttest_ind(set_accuracies[0], set_accuracies[1]).pvalue)\n",
    "print(stats.ttest_ind(set_accuracies[0], set_accuracies[2]).pvalue)\n",
    "print(stats.ttest_ind(set_accuracies[1], set_accuracies[2]).pvalue)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6a644e8-24ea-444c-8dd4-a6e205d50ca2",
   "metadata": {},
   "source": [
    "# Influence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "2d4e3437-0fd9-464d-9b02-f99038cdff0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Index limits for HalfCorr simulations\n",
    "start = 2 * NUM_REPLICATES\n",
    "stop = None\n",
    "\n",
    "# Taking only HalfCorr simulations\n",
    "y_activations = y_activations[start:stop]\n",
    "z_activations = z_activations[start:stop]\n",
    "y_weights = y_weights[start:stop]\n",
    "z_weights = z_weights[start:stop]\n",
    "y_biases = y_biases[start:stop]\n",
    "z_biases = z_biases[start:stop]\n",
    "class_targets = class_targets[start:stop]\n",
    "set_targets = set_targets[start:stop]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "cd3129c5-b01d-4989-9eab-42f142c1b779",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculating mean variance in neural activation within the same digit class\n",
    "inds_by_class = [[np.where(targets == target)[0]\n",
    "                  for target in np.unique(targets)]\n",
    "                 for targets in class_targets]\n",
    "variances = np.array([np.array([activations[inds].var(0)\n",
    "                       for inds in inds_by_class]).mean(0)\n",
    "                     for activations, inds_by_class\n",
    "                     in zip(y_activations, inds_by_class)]).mean(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "7683303c-0c0d-461d-adb2-956fb0b9b78d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(6, 4))\n",
    "ax.scatter(range(HIDDEN_SIZE), variances, color='tab:blue')\n",
    "ax.set_xlabel(\"neuron\")\n",
    "ax.set_ylabel(\"intraclass variance\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "571d2267-5932-491a-a3a4-0f7daa36082e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Computing logits used for concept and example predictions\n",
    "y_logits_by_neuron = (np.expand_dims(y_activations.transpose(0,2,1), 3)\n",
    "                      * np.expand_dims(y_weights.transpose(0,2,1), 2))\n",
    "z_logits_by_neuron = (np.expand_dims(z_activations.transpose(0,2,1), 3)\n",
    "                      * np.expand_dims(z_weights.transpose(0,2,1), 2))\n",
    "\n",
    "y_logits = np.expand_dims(y_logits_by_neuron.sum(1)\n",
    "                          + np.expand_dims(y_biases, 1), 1)\n",
    "z_logits = np.expand_dims(z_logits_by_neuron.sum(1)\n",
    "                          + np.expand_dims(z_biases, 1), 1)\n",
    "\n",
    "# Compute effect of silencing each neuron\n",
    "y_logits_without_neuron = y_logits - y_logits_by_neuron\n",
    "z_logits_without_neuron = z_logits - z_logits_by_neuron"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "dc5dba16-1c6e-431b-bd66-ac0c54f85e92",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Computing accuracies from logits\n",
    "class_accuracies = np.mean(y_logits.argmax(3)\n",
    "                           == np.expand_dims(class_targets, 1), (0,2))\n",
    "set_accuracies = np.mean(z_logits.argmax(3)\n",
    "                         == np.expand_dims(set_targets, 1), (0,2))\n",
    "\n",
    "class_acc_without_neuron = np.mean(y_logits_without_neuron.argmax(3)\n",
    "                                   == np.expand_dims(class_targets, 1), (0,2))\n",
    "set_acc_without_neuron = np.mean(z_logits_without_neuron.argmax(3)\n",
    "                                 == np.expand_dims(set_targets, 1), (0,2))\n",
    "\n",
    "# Influence is the mean decrease in accuracy upon silencing neuron\n",
    "class_influences = class_accuracies - class_acc_without_neuron\n",
    "set_influences = set_accuracies - set_acc_without_neuron"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "303acd53-376f-43e3-94b6-ab296f3b3e48",
   "metadata": {},
   "outputs": [],
   "source": [
    "if \"h5file\" in globals():\n",
    "    h5file.close()\n",
    "h5file = h5py.File(f\"out/{nb_base}.h5\", 'w')\n",
    "\n",
    "h5file.create_dataset(\"losses\", data=losses)\n",
    "h5file.create_dataset(\"test_accuracies\", data=test_accuracies)\n",
    "h5file.create_dataset(\"variances\", data=variances)\n",
    "h5file.create_dataset(\"class_influences\", data=class_influences)\n",
    "h5file.create_dataset(\"set_influences\", data=set_influences)\n",
    "\n",
    "h5file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "36b0b7ce-9e8a-4a29-92e7-6cc673e5ae8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.000378624999999988 0.00014624999999998333 3.9625259831892285e-07\n",
      "0.0014025000000000066 0.0023249999999999994 1.2441994283013196e-06\n"
     ]
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(10, 4))\n",
    "axes[0].scatter(range(HIDDEN_SIZE), class_influences, color='tab:blue')\n",
    "axes[0].set_xlabel(\"neuron\")\n",
    "axes[0].set_ylabel(\"concept influence\")\n",
    "axes[1].scatter(range(HIDDEN_SIZE), set_influences, color='tab:blue')\n",
    "axes[1].set_xlabel(\"neuron\")\n",
    "axes[1].set_ylabel(\"episode influence\")\n",
    "fig.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Comparing influences between first and second halves of the hidden layer\n",
    "half = int(round(HIDDEN_SIZE/2))\n",
    "class_influences0 = class_influences[:half]\n",
    "class_influences1 = class_influences[half:]\n",
    "set_influences0 = set_influences[:half]\n",
    "set_influences1 = set_influences[half:]\n",
    "print(class_influences0.mean(), class_influences1.mean(),\n",
    "      stats.ttest_ind(class_influences0, class_influences1).pvalue)\n",
    "print(set_influences0.mean(), set_influences1.mean(),\n",
    "      stats.ttest_ind(set_influences0, set_influences1).pvalue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0139bc01-7561-4d88-9b4b-bb47f1d317a5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}


================================================
FILE: ml/README.md
================================================
# Overview

This directory contains PyTorch code for example and concept learning in multilayer perceptrons using the DeCorr and HalfCorr loss functions.

Note that "category" or "class" in the code refers to "concept" in our manuscript.

Subdirectories:
- `converted`: Conversion script `nb2script.sh` and converted Jupyter notebooks
- `lib`: Modules used for network training
- `out`: Output files of trained networks


# Requirements

### Python packages

Required python packages are listed below, with versions checked in parentheses.
- python (3.9)
- numpy
- scipy
- pytorch (1.8.1)
- cudatoolkit (11.1.1; now superseded by pytorch-cuda)
- torchvision (0.9.1)
- matplotlib
- jupyterlab (or jupyter or a different notebook viewer)
- h5py
- ipynbname
- jupyterlab-nvdashboard (not required but helpful for monitoring multiprocessing)

### `multiprocessing` helper script `nb2script.sh`

We would like to use `torch.multiprocessing` to train replicate networks in parallel, but this library does not work from Jupyter notebooks. To provide this functionality, we provide a helper script `nb2script.sh` in the `converted` directory that converts the Jupyter notebook to a python script and discards code not required for multiprocessing. The multiprocessing script can then be called from the notebook. Remember to enable execution by running from the `converted` directory
```console
$ chmod +x nb2script.sh
```


# Training and evaluation

The following Jupyter notebooks can be evaluated in any order. In general, variable names with all capitals indicate modifiable hyperparameters.

### `1task-concept.ipynb`

This Jupyter notebook trains baseline and DeCorr networks to perform digit classification of MNIST images, which requires merging similar images into concepts.

### `1task-example.ipynb`

This Jupyter notebook trains baseline and DeCorr networks to perform set identification of MNIST images, which requires distinguishing similar images as separate examples.

### `2tasks.ipynb`

This Jupyter notebook trains baseline, DeCorr, and HalfCorr networks to perform digit classification and set identification of MNIST images.


================================================
FILE: ml/converted/1task-concept.py
================================================
#!/usr/bin/env python
# coding: utf-8

# # General setup

# In[7]:


import os, sys, subprocess
import time
from glob import glob
import itertools
from functools import partial
import copy
import gc

import importlib
sys.path.insert(1, os.path.realpath('lib'))
if "utils" not in sys.modules: import utils
else: importlib.reload(utils)
if "ml" not in sys.modules: import ml
else: importlib.reload(ml)
if "train" not in sys.modules: import train
else: importlib.reload(train)


import numpy as np


import torch
from torch import nn
from torch.utils.data import Dataset, DataLoader
from torch.optim import SGD
from torchvision import datasets
from torchvision.transforms import Compose, ToTensor, Normalize
if not utils.is_notebook():
    import torch.multiprocessing as mp


# In[8]:




# # Loading Data

# In[9]:


transform = Compose([
    ToTensor(),
    Normalize((0.1307,), (0.3081,))
])

raw_train_dataset = datasets.MNIST(
    root="../../../PyTorchShared/Datasets",
    train=True,
    download=True,
    transform=transform
)

raw_test_dataset = datasets.MNIST(
    root="../../../PyTorchShared/Datasets",
    train=False,
    download=True,
    transform=transform
)


# In[10]:




# # Training

# In[31]:


HIDDEN_SIZE = 50
CLASS_SIZES = [200, 400, 600, 800, 1000]
num_sizes = len(CLASS_SIZES)
BATCH_SIZE = 50

DECORR_STRENGTH = 0.5
# Number of networks trained per class size
NUM_REPLICATES = 8

class_sizes = [rep
               for size in CLASS_SIZES
               for rep in (size,)*NUM_REPLICATES]*2
# Baseline networks then DeCorr networks
decorr_criteria = [rep
                   for criterion in (None, ml.decorr_criterion)
                   for rep in (criterion,)*NUM_REPLICATES*num_sizes]

# Evaluate network performance with held-out test data
MODE = 'testval'

# Defining datasets for each replicate
train_datasets = [(
    ml.RelabeledSubset,
    dict(dataset=raw_train_dataset, class_size=class_size,
         target2_config='none', transform=transform)
) for class_size in class_sizes]
test_dataset = (
    ml.RelabeledSubset,
    dict(dataset=raw_test_dataset,
         target2_config='none', transform=transform)
)

# Defining multilayer perceptron
model = (
    ml.MLP,
    dict(hidden_size=HIDDEN_SIZE, target_size=10,
         nonlinearity1=nn.Tanh(), nonlinearity2=nn.Tanh())
)

# Looping through GPUs
devices = itertools.cycle([torch.device('cuda', i)
                           for i in range(torch.cuda.device_count())])


# In[12]:


NUM_EPOCHS = 40
PRINT_EPOCHS = NUM_EPOCHS
LEARNING_RATE = 1e-4
WEIGHT_DECAY = 0
NOISE_FN = None


# In[13]:


# Training keyword arguments that vary across replicates
kwargs_map = [dict(device=dev,
                   train_dataset=param0,
                   decorr_criterion=param1)
               for dev, param0, param1
               in zip(devices,
                      train_datasets,
                      decorr_criteria)]
# Training keyword arguments that remain constant
kwargs_partial = dict(model=model,
                      mode=MODE,
                      test_dataset=test_dataset,
                      decorr_strength=DECORR_STRENGTH,
                      noise_fn=NOISE_FN,
                      batch_size=BATCH_SIZE,
                      learning_rate=LEARNING_RATE,
                      num_epochs=NUM_EPOCHS,
                      print_epochs=PRINT_EPOCHS)


# In[14]:




# In[16]:


# Only evaluate in multiprocessing script, not in notebook
if not utils.is_notebook():
    train_partial = partial(train.train, **kwargs_partial)
   
    # On NVIDIA V100 GPUs, each GPU can simultaneously train two networks
    MAX_PROCESSES = 2 * torch.cuda.device_count()
    
    # Use multiprocessing to train networks in parallel
    if __name__ == "__main__":
        utils.start_timer()
        mp.set_start_method('spawn', force=True)
        
        num_processes = min(len(kwargs_map), MAX_PROCESSES)
        with mp.Pool(num_processes) as p:
            results = utils.kwstarmap(p, train_partial, kwargs_map)

        utils.end_timer_and_print()


# In[17]:




================================================
FILE: ml/converted/1task-example.py
================================================
#!/usr/bin/env python
# coding: utf-8

# Only differences between this notebook an `1task-concept.ipynb` will be commented here. See `1task-concept.ipynb` for more thorough explanations.

# # General setup

# In[1]:


import os, sys, subprocess
import time
from glob import glob
import itertools
from functools import partial
import copy
import gc

import importlib
sys.path.insert(1, os.path.realpath('lib'))
if "utils" not in sys.modules: import utils
else: importlib.reload(utils)
if "ml" not in sys.modules: import ml
else: importlib.reload(ml)
if "train" not in sys.modules: import train
else: importlib.reload(train)


import numpy as np


import torch
from torch import nn
from torch.utils.data import Dataset, DataLoader
from torchvision import datasets
from torchvision.transforms import Compose, ToTensor, Normalize
if not utils.is_notebook():
    import torch.multiprocessing as mp


# In[2]:




# # Loading Data

# In[3]:


transform = Compose([
    ToTensor(),
    Normalize((0.1307,), (0.3081,))
])

raw_train_dataset = datasets.MNIST(
    root="../../../PyTorchShared/Datasets",
    train=True,
    download=True,
    transform=transform
)

raw_test_dataset = datasets.MNIST(
    root="../../../PyTorchShared/Datasets",
    train=False,
    download=True,
    transform=transform
)


# In[4]:




# # Training

# In[5]:


HIDDEN_SIZE = 50
CLASS_SIZES = [20, 40, 60, 80, 100]
num_sizes = len(CLASS_SIZES)
BATCH_SIZE = 50
NUM_SETS = 10

DECORR_STRENGTH = 0.5
NUM_REPLICATES = 8

class_sizes = [rep
               for size in CLASS_SIZES
               for rep in (size,)*NUM_REPLICATES]*2
decorr_criteria = [rep
                   for criterion in (None, ml.decorr_criterion)
                   for rep in (criterion,)*NUM_REPLICATES*num_sizes]

# Evaluate set identification data with noisy test data
MODE = 'set'

train_datasets = [(
    ml.RelabeledSubset,
    dict(dataset=raw_train_dataset, class_size=class_size,
         target2_config=NUM_SETS, transform=transform)
) for class_size in class_sizes]
test_dataset = None 

model = (
    ml.MLP,
    dict(hidden_size=HIDDEN_SIZE, target_size=NUM_SETS,
         nonlinearity1=nn.Tanh(), nonlinearity2=nn.Tanh())
)

devices = itertools.cycle([torch.device('cuda', i)
                           for i in range(torch.cuda.device_count())])


# In[18]:


NUM_EPOCHS = 100
PRINT_EPOCHS = NUM_EPOCHS
LEARNING_RATE = 1e-4
WEIGHT_DECAY = 0

# Function for randomly setting a fraction 0.2 of rescaled to pixels
# to 0, which is the mean pixel value. Used for generating test data.
def NOISE_FN(data):
    mask = torch.rand_like(data)
    threshold = mask.quantile(0.2)
    mask = (mask - threshold > 0).float()
    noisy_data = data * mask
    return noisy_data



# In[19]:


kwargs_map = [dict(device=dev,
                   train_dataset=param0,
                   decorr_criterion=param1)
               for dev, param0, param1
               in zip(devices,
                      train_datasets,
                      decorr_criteria)]
kwargs_partial = dict(model=model,
                      mode=MODE,
                      test_dataset=test_dataset,
                      decorr_strength=DECORR_STRENGTH,
                      noise_fn=NOISE_FN,
                      batch_size=BATCH_SIZE,
                      learning_rate=LEARNING_RATE,
                      num_epochs=NUM_EPOCHS,
                      print_epochs=PRINT_EPOCHS)


# In[20]:




# In[21]:


if not utils.is_notebook():
    train_partial = partial(train.train, **kwargs_partial)
   
    MAX_PROCESSES = 2 * torch.cuda.device_count()
    
    if __name__ == "__main__":
        utils.start_timer()
        mp.set_start_method('spawn', force=True)
        
        num_processes = min(len(kwargs_map), MAX_PROCESSES)
        with mp.Pool(num_processes) as p:
            results = utils.kwstarmap(p, train_partial, kwargs_map)

        utils.end_timer_and_print()


# In[33]:




================================================
FILE: ml/converted/2tasks.py
================================================
#!/usr/bin/env python
# coding: utf-8

# Only differences between this notebook an `1task-concept.ipynb` will be commented here. See `1task-concept.ipynb` for more thorough explanations.

# # General setup

# In[15]:


import os, sys, subprocess
import time
from glob import glob
import itertools
from functools import partial
import copy
import gc

import importlib
sys.path.insert(1, os.path.realpath('lib'))
if "utils" not in sys.modules: import utils
else: importlib.reload(utils)
if "ml" not in sys.modules: import ml
else: importlib.reload(ml)
if "train" not in sys.modules: import train
else: importlib.reload(train)


import numpy as np


import torch
from torch import nn
from torch.utils.data import Dataset, DataLoader
from torch.optim import SGD
from torchvision import datasets
from torchvision.transforms import Compose, ToTensor, Normalize
if not utils.is_notebook():
    import torch.multiprocessing as mp


# In[16]:




# # Loading Data

# In[17]:


transform = Compose([
    ToTensor(),
    Normalize((0.1307,), (0.3081,))
])

raw_train_dataset = datasets.MNIST(
    root="../../PyTorchShared/Datasets",
    train=True,
    download=True,
    transform=transform
)

raw_test_dataset = datasets.MNIST(
    root="../../PyTorchShared/Datasets",
    train=False,
    download=True,
    transform=transform
)


# In[18]:




# # Training

# In[23]:


HIDDEN_SIZE = 100
CLASS_SIZE = 100
BATCH_SIZE = 50
NUM_SETS = 10

DECORR_STRENGTH = 0.5
NUM_REPLICATES = 16
decorr_criteria = itertools.chain.from_iterable((
    itertools.repeat(None, NUM_REPLICATES),
    itertools.repeat(ml.decorr_criterion, NUM_REPLICATES),
    itertools.repeat(ml.halfcorr_criterion, NUM_REPLICATES)
))

# Evaluate digit classification performance with held-out test data and save test
# activations and outputs.
MODE = ['testval', 'testsave']

train_dataset = (
    ml.RelabeledSubset,
    dict(dataset=raw_train_dataset, class_size=CLASS_SIZE,
         target2_config=NUM_SETS, transform=transform)
)
test_dataset = (
    ml.RelabeledSubset,
    dict(dataset=raw_test_dataset,
         target2_config='none', transform=transform)
)

model = (
    ml.TwoTargetMLP,
    dict(hidden_size=HIDDEN_SIZE,
         target1_size=10, target2_size=NUM_SETS,
         nonlinearity1=nn.Tanh(), nonlinearity2=nn.Tanh())
)

devices = itertools.cycle([torch.device('cuda', i)
                           for i in range(torch.cuda.device_count())])


# In[24]:


NUM_EPOCHS = 100
PRINT_EPOCHS = NUM_EPOCHS
LEARNING_RATE = 1e-4
WEIGHT_DECAY = 0

def NOISE_FN(data):
    mask = torch.rand_like(data)
    threshold = mask.quantile(0.2)
    mask = (mask - threshold > 0).float()
    noisy_data = data * mask
    return noisy_data



# In[25]:


kwargs_map = [dict(device=dev, decorr_criterion=param)
               for dev, param
               in zip(devices, decorr_criteria)]
kwargs_partial = dict(model=model,
                      mode=MODE,
                      train_dataset=train_dataset,
                      test_dataset=test_dataset,
                      decorr_strength=DECORR_STRENGTH,
                      noise_fn=NOISE_FN,
                      batch_size=BATCH_SIZE,
                      learning_rate=LEARNING_RATE,
                      num_epochs=NUM_EPOCHS,
                      print_epochs=PRINT_EPOCHS)


# In[26]:




# In[27]:


if not utils.is_notebook():
    train_partial = partial(train.two_target_train, **kwargs_partial)
   
    MAX_PROCESSES = 2 * torch.cuda.device_count()
    
    if __name__ == "__main__":
        utils.start_timer()
        mp.set_start_method('spawn', force=True)
        
        num_processes = min(len(kwargs_map), MAX_PROCESSES)
        with mp.Pool(num_processes) as p:
            results = utils.kwstarmap(p, train_partial, kwargs_map)

        utils.end_timer_and_print()


# In[28]:




================================================
FILE: ml/converted/nb2script.sh
================================================
#!/bin/bash
# This script is called from Jupyter notebooks in the parent directory to convert
# produce Python scripts that can be called by torch.multiprocessing

nbname="${1:?Error: the notebook name must be specified}" 
scriptname="converted/${nbname%.ipynb}" 
jupyter nbconvert --to script --output "$scriptname" "$nbname"

# Removing converted code not required for multiprocessing. This code is designated
# with the following comment text:
# Remove all code from '# >>$' to the end of the notebook
sed -i '/^# >>\$/,$d' "$scriptname.py"
# Remove all code from '# >>>' to '# <<<'
sed -i '/^# >>>/,/^# <<</d' "$scriptname.py"

================================================
FILE: ml/lib/ml.py
================================================
"""

ml.py:  Classes for introducing a second set label to a dataset; computing the
        DeCorr, HalfCorr, and DeCov loss functions; and creating one-target and
        two-target multilayer perceptrons.

"""

__author__ = "Louis Kang"
__date__ = "2023/03/07"
__license__ = "GPLv3"
__reference__ = "To be determined"



import os, sys

import numpy as np
import torch
from torch import nn
from torch.utils.data import Dataset


# Taking a subset of a dataset and adding an additional label to each item
class RelabeledSubset(Dataset):
    def __init__(self, dataset, class_size='all', class_inds='all',
                 target2_config='none',
                 transform=None, target_transform=None):
        self.class_inds = class_inds
        self.class_size = class_size
        
        if class_inds == 'all' and class_size == 'all':
            self.data = torch.as_tensor(dataset.data)
            self.targets = torch.as_tensor(dataset.targets)
        
        else:
            if class_inds == 'all':
                class_inds = list(dataset.class_to_idx.values())
            # If class_inds are provided, take only those classes
            inds_by_class = [torch.where(dataset.targets == class_idx)[0]
                             for class_idx in class_inds]
            # Pick subsample of images in each valid class
            if class_size != 'all':
                inds_by_class = [inds[:class_size] for inds in inds_by_class]
                
            # Generate subset
            subset_inds = torch.cat(inds_by_class)
            subset_inds = subset_inds[torch.randperm(len(subset_inds))]
            self.data = torch.index_select(torch.as_tensor(dataset.data),
                                           0, subset_inds)
            self.targets = torch.index_select(torch.as_tensor(dataset.targets),
                                              0, subset_inds)
        
        # Each item gets a different second label
        if target2_config == 'index':
            self.targets2 = torch.arange(len(self.targets),
                                         device=self.targets.device)
        # Second labels are obtained by shuffling the original labels
        elif target2_config == 'shuffle':
            perm = torch.randperm(len(self.targets))
            self.targets2 = self.targets[perm].clone()
        # An integer argument determines the number of randomly assigned sets
        elif type(target2_config) == int:
            self.targets2 = torch.arange(len(self.targets),
                                         device=self.targets.device)
            perm = torch.randperm(len(self.targets))
            self.targets2 = (self.targets2 % target2_config)[perm]
        elif target2_config == 'none':
            self.targets2 = None
        else:
            raise Exception("target2_config must be 'index',"
                            " 'shuffle', 'none', or an integer")
        
        self.transform = transform
        self.target_transform = target_transform

    def __len__(self):
        return len(self.targets)
        
    def __getitem__(self, idx):
        img = self.data[idx].numpy()
        target = int(self.targets[idx])
        
        if self.transform:
            img = self.transform(img)
        if self.target_transform:
            target = self.target_transform(target)
        
        if self.targets2 is None:
            return img, target
        
        else:
            target2 = int(self.targets2[idx])
            if self.target_transform:
                target2 = self.target_transform(target2)
            return img, target, target2



# Covariance matrix
def cov_matrix(X):
    if X.ndim < 2:
        raise Exception("input must have at least 2 dimensions")
    N = X.shape[-1]
    mean = torch.mean(X, dim=-1, keepdim=True)
    X = X - mean
    return 1./(N-1) * X @ X.transpose(-1, -2)

# DeCov loss by Cogswell et al., ICLR (2016)
def decov_criterion(activations):
    cov = cov_matrix(activations.T)
    cov.diagonal().zero_()
    decov_loss = cov.square().sum()
    
    return decov_loss


# Square of correlation matrix with eps introduced in the denominator to aid
# numerical convergence
def corr_matrix_sq(X, eps=0.):
    if X.ndim < 2:
        raise Exception("input must have at least 2 dimensions")
    N = X.shape[-1]
    mean = torch.mean(X, dim=-1, keepdim=True)
    X = X - mean
    var = torch.var(X, dim=-1) + eps
    corr_sq = X @ X.transpose(-1, -2)
    corr_sq = corr_sq.square()
    corr_sq /= torch.outer(var, var)
    return 1./(N-1.)**2 * corr_sq

# DeCorr loss function
def decorr_criterion(activations, eps=1e-3):
    corr_sq = corr_matrix_sq(activations, eps)
    corr_sq.diagonal().zero_()
    decorr_loss = corr_sq.sum()
    
    return decorr_loss

# HalfCorr loss function
def halfcorr_criterion(activations, eps=1e-3):
    half = int(round(activations.shape[-1]/2))
    corr_sq = corr_matrix_sq(activations[:,half:], eps)
    corr_sq.diagonal().zero_()
    halfcorr_loss = corr_sq.sum()
    
    return halfcorr_loss


# Two-layer perceptron for MNIST data and a single task
class MLP(nn.Module):
    def __init__(self, hidden_size, target_size,
                 nonlinearity1=nn.ReLU(inplace=True), nonlinearity2=nn.Identity()):
        super().__init__()
        self.hidden_size = hidden_size
        self.target_size = target_size
        self.nonlinearity1 = nonlinearity1
        self.nonlinearity2 = nonlinearity2
        
        self.linear_block1 = nn.Sequential(
            nn.Flatten(),
            nn.Linear(28 * 28, hidden_size),
            self.nonlinearity1,
        )
        self.linear_block2 = nn.Sequential(
            nn.Linear(hidden_size, hidden_size),
            self.nonlinearity2,
        )
        self.classifier = nn.Linear(hidden_size, target_size)

    def forward(self, x):
        x = self.linear_block1(x)
        activations = self.linear_block2(x)
        logits = self.classifier(activations)
        return activations, logits
    
    
# Two-layer perceptron with MNIST data and two tasks
class TwoTargetMLP(nn.Module):
    def __init__(self, hidden_size, target1_size, target2_size,
                 nonlinearity1=nn.ReLU(inplace=True), nonlinearity2=nn.Identity()):
        super().__init__()
        self.hidden_size = hidden_size
        self.target1_size = target1_size
        self.target2_size = target2_size
        self.nonlinearity1 = nonlinearity1
        self.nonlinearity2 = nonlinearity2
        
        self.linear_block1 = nn.Sequential(
            nn.Flatten(),
            nn.Linear(28 * 28, hidden_size),
            self.nonlinearity1,
        )
        self.linear_block2 = nn.Sequential(
            nn.Linear(hidden_size, hidden_size),
            self.nonlinearity2,
        )
        self.classifier1 = nn.Linear(hidden_size, target1_size)
        self.classifier2 = nn.Linear(hidden_size, target2_size)

    def forward(self, x):
        x = self.linear_block1(x)
        activations = self.linear_block2(x)
        logits1 = self.classifier1(activations)
        logits2 = self.classifier2(activations)
        return activations, logits1, logits2


================================================
FILE: ml/lib/train.py
================================================
"""

train.py:   Functions for training neural networks on single tasks and two tasks.

"""

__author__ = "Louis Kang"
__date__ = "2023/03/07"
__license__ = "GPLv3"
__reference__ = "To be determined"



import os, sys
import gc

import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader
from torch.optim import SGD
import utils
import ml


# Train single-task networks
def train(device, model, mode,
          train_dataset, test_dataset,
          decorr_criterion, decorr_strength,
          noise_fn, batch_size, learning_rate,
          num_epochs, print_epochs):
    
    torch.seed()
    
    # Allow for defining models as a tuple as (model_name, model_keyword_arguments).
    # This is helpful for multiprocessing because the models can be created in each
    # thread instead of being all created by the parent thread and sent to each child.
    if isinstance(model, tuple):
        model = model[0](**model[1]).to(device)
    else:
        model = model.to(device)
    
    # Similarly, create datasets locally in each child thread.
    set_seed = True
    if isinstance(train_dataset, tuple):
        train_dataset = train_dataset[0](**train_dataset[1])
        set_seed = False
    if isinstance(test_dataset, tuple):
        test_dataset = test_dataset[0](**test_dataset[1])
        set_seed = False
    train_size = len(train_dataset)
    num_batches = train_size / batch_size
    if num_batches.is_integer():
        num_batches = int(num_batches)
    else:
        raise Exception(f"num_batches must divide {train_size},"
                        " the size of train_dataset")
   
    # For MNIST, GPU memory generally large enough to load entire train subset
    # Set identification
    if mode == 'set':
        train_X, _, train_target = next(iter(
            DataLoader(train_dataset, batch_size=train_size)
        ))
    # Digit classification
    elif mode in {'testval', 'trainval'}:
        train_X, train_target = next(iter(
            DataLoader(train_dataset, batch_size=train_size)
        ))
    else:
        raise Exception("mode must be 'testval', 'trainval', or 'set'")
    train_X = train_X.to(device)
    train_target = train_target.to(device)
    
    X_batch_dims = (num_batches, batch_size, *train_X.shape[1:])
    target_batch_dims = (num_batches, batch_size, *train_target.shape[1:])
    
    if set_seed:
        rand_seed = torch.sum(
            train_target * torch.arange(len(train_target), device=device)
        ).item()
        torch.manual_seed(rand_seed)
        
    # Validate with held-out test dataset
    if mode == 'testval':
        # For MNIST, GPU memory generally large enough to load entire test dataset
        test_size = len(test_dataset)
        test_X, test_target = next(iter(
            DataLoader(test_dataset, batch_size=test_size)
        ))
        test_X = test_X.to(device)
        test_target = test_target.to(device)
    # Validate with noisy train dataset
    elif mode in {'trainval', 'set'}:
        test_X = noise_fn(train_X)
        test_target = train_target
        
    
    class_criterion = nn.CrossEntropyLoss(reduction='sum')
    set_criterion = nn.CrossEntropyLoss(reduction='sum')
    if decorr_criterion is None:
        decorr_strength = 0.
        # This allows for evaluation of correlations even in the baseline condition
        decorr_criterion = ml.decorr_criterion
    optimizer = SGD(model.parameters(), lr=learning_rate, momentum=0.9)
    
    loss_result = []
    train_accuracy_result = []
    test_accuracy_result = []

    
    for t in range(num_epochs):
        
        losses = np.array([0., 0.])
        train_correct = 0
        
        model.train()
        # Generate randomly ordered batches
        train_perm = torch.randperm(train_size)
        X_batches = train_X[train_perm].view(X_batch_dims)
        target_batches = train_target[train_perm].view(target_batch_dims)
        
        for X, target in zip(X_batches, target_batches):
            activations, logits = model(X)
            target_loss = class_criterion(logits, target)
            decorr_loss = decorr_criterion(activations)
            loss = target_loss + decorr_strength * decorr_loss

            optimizer.zero_grad()
            loss.backward()
            optimizer.step()
            
            with torch.no_grad():
                losses += np.array([target_loss.item(), decorr_loss.item()])
                train_correct += utils.logits_to_accuracy(logits, target,
                                                          reduction='sum')
        
        losses /= train_size
        loss_result.append(losses)
        train_accuracy = train_correct / train_size
        train_accuracy_result.append(train_accuracy)
        
        # During each epoch, validate trained network on full test dataset
        model.eval()
        with torch.no_grad():
            _, logits = model(test_X)
            test_accuracy = utils.logits_to_accuracy(logits, test_target,
                                                     reduction='mean')
            test_accuracy_result.append(test_accuracy)
                
        if (print_epochs > 0
            and ((t+1) % print_epochs == 0 or t == 0)):    
            print(f"{device} {t:>3d})"
                  f"   target: {losses[0]:>6.3f}  decorr: {losses[1]:>6.3f}"
                  f"   train: {train_accuracy:>5.3f}  test: {test_accuracy:>5.3f}")
        
    loss_result = np.array(loss_result)
    train_accuracy_result = np.array(train_accuracy_result)
    test_accuracy_result = np.array(test_accuracy_result)

    # Save activations of trained network with test dataset
    model.eval()
    with torch.no_grad():
        activations, _ = model(test_X)
    activations = activations.cpu().numpy()
        
    # Free GPU memory
    del train_X, train_target, X_batches, target_batches
    del test_X, test_target, model
    gc.collect()
    torch.cuda.empty_cache()
    
    return (loss_result,
            train_accuracy_result, test_accuracy_result,
            activations)



# See comments above for the train function for more information
def two_target_train(device, model, mode,
                     train_dataset, test_dataset,
                     decorr_criterion, decorr_strength,
                     noise_fn, batch_size, learning_rate,
                     num_epochs, print_epochs):
    
    torch.seed()
    
    if isinstance(model, tuple):
        model = model[0](**model[1]).to(device)
    else:
        model = model.to(device)
        
    set_seed = True
    if isinstance(train_dataset, tuple):
        train_dataset = train_dataset[0](**train_dataset[1])
        set_seed = False
    if isinstance(test_dataset, tuple):
        test_dataset = test_dataset[0](**test_dataset[1])
        set_seed = False
    train_size = len(train_dataset)
    num_batches = train_size / batch_size
    if num_batches.is_integer():
        num_batches = int(num_batches)
    else:
        raise Exception(f"num_batches must divide {train_size},"
                        " the size of train_dataset")
    
    # y is class target, z is set target
    train_X, train_y, train_z = next(iter(
        DataLoader(train_dataset, batch_size=train_size)
    ))
    train_X = train_X.to(device)
    train_y = train_y.to(device)
    train_z = train_z.to(device)
    print_X = torch.mean(train_X[0]).item()
    print_z = train_z[0].item()
    
    X_batch_dims = (num_batches, batch_size, *train_X.shape[1:])
    y_batch_dims = (num_batches, batch_size, *train_y.shape[1:])
    z_batch_dims = (num_batches, batch_size, *train_z.shape[1:])
    
    if set_seed:
        rand_seed = torch.sum(
            train_z * torch.arange(len(train_z), device=device)
        ).item()
        torch.manual_seed(rand_seed)
    
    # trainsave and testsave save activations and logits of trained network with
    # train and test datasets, respectively. The former is the default option.
    if isinstance(mode, str):
        mode = [mode, 'trainsave']
    if mode[0] != 'trainval' and mode[0] != 'testval':
        raise Exception("mode[0] must be 'trainval' or 'testval'")
    if mode[1] != 'trainsave' and mode[1] != 'testsave':
        raise Exception("mode[1] must be 'trainsave' or 'testsave'")
    
    if mode[0] == 'trainval':
        test_X = noise_fn(train_X)
        test_y = train_y
        test_z = train_z
    # Digit classification and set identification are validated with different
    # test datasets.
    elif mode[0] == 'testval':
        test_size = len(test_dataset)
        test_X_for_y, test_y = next(iter(
            DataLoader(test_dataset, batch_size=test_size)
        ))
        test_X_for_y = test_X_for_y.to(device)
        test_y = test_y.to(device)
        test_X_for_z = noise_fn(train_X)
        test_z = train_z
    
    class_criterion = nn.CrossEntropyLoss(reduction='sum')
    set_criterion = nn.CrossEntropyLoss(reduction='sum')
    if decorr_criterion is None:
        decorr_strength = 0.
        decorr_criterion = ml.decorr_criterion
    optimizer = SGD(model.parameters(), lr=learning_rate, momentum=0.9)
    
    loss_result = []
    train_accuracy_result = []
    test_accuracy_result = []
    activation_result = []
    

    for t in range(num_epochs):
        
        # Digit classification loss, set identification loss, DeCorr/HalfCorr loss
        losses = np.array([0., 0., 0.])
        # Digit classification accuracy, set identification accuracy
        train_correct = np.array([0, 0])
        
        model.train()
        train_perm = torch.randperm(train_size)
        X_batches = train_X[train_perm].view(X_batch_dims)
        y_batches = train_y[train_perm].view(y_batch_dims)
        z_batches = train_z[train_perm].view(z_batch_dims)
        
        for X, y, z in zip(X_batches, y_batches, z_batches):
            activations, y_logits, z_logits = model(X)
            class_loss = class_criterion(y_logits, y)
            set_loss = set_criterion(z_logits, z)
            decorr_loss = decorr_criterion(activations)
            loss = (class_loss + set_loss + decorr_strength * decorr_loss)

            optimizer.zero_grad()
            loss.backward()
            optimizer.step()
            
            with torch.no_grad():
                losses += np.array([class_loss.item(), set_loss.item(),
                                    decorr_loss.item()])
                train_correct += np.array([
                    utils.logits_to_accuracy(y_logits, y, reduction='sum'),
                    utils.logits_to_accuracy(z_logits, z, reduction='sum')
                ])
        
        losses /= train_size
        loss_result.append(losses)
        train_accuracies = train_correct / train_size
        train_accuracy_result.append(train_accuracies)
        
        model.eval()
        with torch.no_grad():
            if mode[0] == 'trainval':
                _, y_logits, z_logits = model(test_X)
            elif mode[0] == 'testval':
                _, y_logits, _ = model(test_X_for_y)
                _, _, z_logits = model(test_X_for_z)
                
            test_accuracies = np.array([
                utils.logits_to_accuracy(y_logits, test_y, reduction='mean'),
                utils.logits_to_accuracy(z_logits, test_z, reduction='mean')
            ])
            test_accuracy_result.append(test_accuracies)
                
        if (print_epochs > 0
            and ((t+1) % print_epochs == 0 or t == 0)):    
            print(f"{device} {t:>3d})"
                  f"   loss: {losses[0]:>6.3f} {losses[1]:>6.3f}  {losses[2]:>.3e}"
                  f"   train: {train_accuracies[0]:>5.3f} {train_accuracies[1]:>5.3f}"
                  f"   test: {test_accuracies[0]:>5.3f} {test_accuracies[1]:>5.3f}")
        
    loss_result = np.array(loss_result)
    train_accuracy_result = np.array(train_accuracy_result)
    test_accuracy_result = np.array(test_accuracy_result)
        
    model.eval()
    weights = (model.classifier1.weight.detach().cpu().numpy(),
               model.classifier2.weight.detach().cpu().numpy())
    biases = (model.classifier1.bias.detach().cpu().numpy(),
              model.classifier2.bias.detach().cpu().numpy())
    # Save activations with train dataset
    if mode[1] == 'trainsave':
        with torch.no_grad():
            activations, _, _ = model(train_X)
        activations = activations.cpu().numpy()
        targets = (train_y.cpu().numpy(), train_z.cpu().numpy())
    # Save activations with test datasets
    elif mode[1] == 'testsave':
        if mode[0] == 'trainval':
            with torch.no_grad():
                activations, _, _ = model(test_X)
            activations = activations.cpu().numpy()
        elif mode[0] == 'testval':
            with torch.no_grad():
                y_activations, _, _ = model(test_X_for_y)
                z_activations, _, _ = model(test_X_for_z)
            activations = (y_activations.cpu().numpy(),
                           z_activations.cpu().numpy())
        targets = (test_y.cpu().numpy(), test_z.cpu().numpy())
    
    del train_X, train_y, train_z
    if mode[0] == 'trainval':
        del test_X
    elif mode[0] == 'testval':
        del test_X_for_y, test_X_for_z
        if mode[1] == 'testsave':
            del y_activations, z_activations
    del test_y, test_z, model
    gc.collect()
    torch.cuda.empty_cache()
    
    return (loss_result,
            train_accuracy_result, test_accuracy_result,
            activations, weights, biases, targets)


================================================
FILE: ml/lib/utils.py
================================================
"""

utils.py:   Useful utility functions.

"""

__author__ = "Louis Kang"
__date__ = "2023/03/07"
__license__ = "GPLv3"
__reference__ = "To be determined"



import os, sys
import time
import itertools

import numpy as np
import torch

import matplotlib.pyplot as plt


# Detecting if code is run from a Jupyter notebook
def is_notebook():
    return os.path.basename(sys.argv[0]) == 'ipykernel_launcher.py'

# General ReLU function that works for NumPy and PyTorch
def relu(x):
    return x * (x > 0)


# Timing utilities
start_time = None

def start_timer():
    global start_time
    if torch.cuda.is_available(): torch.cuda.synchronize()
    start_time = time.time()

def end_timer_and_print():
    if torch.cuda.is_available(): torch.cuda.synchronize()
    end_time = time.time()
    print("\nTotal execution time {:.3f} sec".format(end_time - start_time))

   
# Extends multiprocessing method Pool.starmap() to accept keyword arguments
def kwstarmap(pool, fn, kwargs_iter):
    args_for_starmap = zip(itertools.repeat(fn), kwargs_iter)
    return pool.starmap(apply_kwargs, args_for_starmap)

def apply_kwargs(fn, kwargs):
    return fn(**kwargs)
    

def plot_images(img_list, num=6, size=12):
    """
    Plot batches of grayscale images as a grid
    
    Inputs
    ------
    img_list : tuple, list, NumPy array, or PyTorch tensor with dimensions
        (image_width, image_height) or (n_columns, image_width, image_height) or
        (n_rows, n_columns, image_width, image_height)
    num : maximum number of image columns
    size : width of image grid
    """
    # Converts all img_list types to list
    if isinstance(img_list, tuple):
        img_list = list(img_list)
    elif isinstance(img_list, (np.ndarray, torch.Tensor)):
        img_list = [img_list]
    elif not isinstance(img_list, list):
        raise Exception("input must be ndarray or sequence or list of ndarrays")
        
    for i in range(len(img_list)):
        if isinstance(img_list[i], torch.Tensor):
            img_list[i] = img_list[i].cpu().numpy()
            
        # Expanding all img_list depths to 4
        depth = img_list[i].ndim
        if depth == 4:
            continue
        elif depth == 3:
            img_list[i] = np.expand_dims(img_list[i], 0)
        elif depth == 2:
            img_list[i] = np.expand_dims(img_list[i], (0,1))
        else:
            raise Exception("image arrays must have depth between 2 and 4, inclusive")
            
    lengths = [imgs.shape[0] for imgs in img_list]
    if lengths.count(lengths[0]) != len(lengths):
        raise Exception("image arrays must have the same first dimension size")
    if num == -1 or num > lengths[0]:
        num = lengths[0]
    num_list = len(img_list)
    
    if num == 1:
        n_rows = 1
        n_columns = num_list
    else:
        n_rows = num_list
        n_columns = num
    ysize = size * n_rows/n_columns
    
    plt.figure(figsize=(size, ysize))
    for i, imgs in enumerate(img_list):
        # Converting pixel values between -1 and 1 to between 0 and 1
        if np.min(imgs) < 0.:
            imgs = 0.5 * (imgs + 1.)
        for j, img in enumerate(imgs):
            if j >= num: break
            plt.subplot(n_rows, n_columns, num*i+j+1)
            if len(img) == 1:
                plt.imshow(img[0], cmap='gray_r')
            else:
                plt.imshow(np.transpose(img, (1,2,0)))
            plt.axis('off')

    plt.show()


# Estimation using the largest, possibly unnormalized logit
def logits_to_accuracy(logits, targets, reduction='mean'):
    accuracies = logits.argmax(-1) == targets
    if reduction == 'mean':
        return accuracies.float().mean().item()
    elif reduction == 'sum':
        return accuracies.int().sum().item()
    else:
        return accuracies.int()