Repository: IGLICT/NeUDF Branch: main Commit: 01fa557958a4 Files: 35 Total size: 29.6 MB Directory structure: gitextract_vbzbbjy4/ ├── LICENSE ├── README.md ├── confs/ │ ├── wmask_old.conf │ ├── wmask_open.conf │ └── womask_open.conf ├── custom_mc/ │ ├── _marching_cubes_lewiner.py │ ├── _marching_cubes_lewiner_cy.c │ ├── _marching_cubes_lewiner_cy.pyx │ ├── _marching_cubes_lewiner_luts.py │ ├── build/ │ │ ├── temp.linux-x86_64-3.8/ │ │ │ └── _marching_cubes_lewiner_cy.o │ │ └── temp.linux-x86_64-cpython-38/ │ │ └── _marching_cubes_lewiner_cy.o │ └── setup.py ├── exp/ │ ├── my_rack_test/ │ │ └── womask_open/ │ │ └── checkpoints/ │ │ └── ckpt_400000.pth │ └── my_whale_test/ │ └── wmask_open/ │ └── checkpoints/ │ └── ckpt_2000000.pth ├── exp_runner.py ├── lib/ │ ├── __init__.py │ ├── models/ │ │ └── deep_udf_decoder.py │ └── workspace.py ├── models/ │ ├── dataset.py │ ├── embedder.py │ ├── fields.py │ └── renderer.py ├── preprocess_custom_data/ │ ├── aruco_preprocess/ │ │ ├── CMakeLists.txt │ │ ├── calibration.cpp │ │ ├── gen_cameras.py │ │ └── run.sh │ ├── colmap_preprocess/ │ │ ├── colmap_read_model.py │ │ ├── colmap_wrapper.py │ │ ├── gen_cameras.py │ │ ├── imgs2poses.py │ │ └── pose_utils.py │ └── readme.md ├── public_data/ │ ├── my_rack_test/ │ │ └── cameras_sphere.npz │ └── my_whale_test/ │ └── cameras_sphere.npz └── requirements.txt ================================================ FILE CONTENTS ================================================ ================================================ FILE: LICENSE ================================================ MIT License Copyright (c) 2023 IGLICT Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ================================================ FILE: README.md ================================================ # NeUDF We present an open surface reconstruction method using UDF, called NeUDF, for reconstructing objects with high-fidelity open surfaces from 2D image inputs. ![](./static/teaser.jpg) ## [Project page](http://geometrylearning.com/neudf/) | [Paper](http://geometrylearning.com/neudf/paper.pdf) This is the official repo for the implementation of **NeUDF: Leaning Neural Unsigned Distance Fields with Volume Rendering** (CVPR 2023). ## Usage ### Setup environment Installing the requirements using: ```shell pip install -r requirements.txt ``` To compile [MeshUDF](https://github.com/cvlab-epfl/MeshUDF) to extract open mesh from the learned UDF field, please run: ```shell cd custom_mc python setup.py build_ext --inplace cd .. ``` To use [PyMeshLab](https://github.com/cnr-isti-vclab/PyMeshLab) and a customized Screened poisson to extract open mesh from the learned UDF field, please run: ```shell pip install pymeshlab ``` To build PyMeshLab from source, please refer to [PyMeshLab](https://github.com/cnr-isti-vclab/PyMeshLab). ### Running - **Train without mask** ```shell python exp_runner.py --mode train --conf ./confs/womask_open.conf --case ``` - **Train with mask** ```shell python exp_runner.py --mode train --conf ./confs/wmask_open.conf --case ``` - **Extract surface using MeshUDF** ```shell python exp_runner.py --mode validate_mesh_udf --conf --case --is_continue ``` The corresponding mesh can be found in `exp///meshes/mu.ply`. - **Extract surface using Screened Poisson** ```shell python exp_runner.py --mode validate_mesh_spsr --conf --case --is_continue ``` The corresponding mesh can be found in `exp///meshes/spsr.ply`. - **Extract surface using MarchingCubes** ```shell python exp_runner.py --mode validate_mesh --conf --case --is_continue ``` The corresponding mesh can be found in `exp///meshes/.ply`. ### Evaluation using pretrained models - **Without mask setting** ```shell python exp_runner.py --mode validate_mesh_udf --conf ./confs/womask_open.conf --case my_rack_test --is_continue --resolution 512 ``` - **With mask setting** ```shell python exp_runner.py --mode validate_mesh_udf --conf ./confs/wmask_open.conf --case my_whale_test --is_continue --resolution 512 ``` ### Datasets and results You can download the full datasets and results [here](https://drive.google.com/drive/folders/1g2x5v6QWUdjQkNoszL2d68I2Gp0VRj5E?usp=sharing) and put them in ./public_data/ and ./exp/, respectively. The data is organized as follows: ``` public_data |-- |-- cameras_xxx.npz |-- image |-- 000.png |-- 001.png ... |-- mask |-- 000.png |-- 001.png ... exp |-- |-- |-- checkpoints |-- ckpt_400000.pth ``` ### Train NeUDF with custom data Please refer to the [Data Conversion](https://github.com/Totoro97/NeuS/tree/main/preprocess_custom_data) in NeuS. ## Citation Cite as below if you find this repository is helpful to your project: ``` @inproceedings{Liu23NeUDF, author = {Liu, Yu-Tao and Wang, Li and Yang, Jie and Chen, Weikai and Meng, Xiaoxu and Yang, Bo and Gao, Lin}, title = {NeUDF: Leaning Neural Unsigned Distance Fields with Volume Rendering}, booktitle={Computer Vision and Pattern Recognition (CVPR)}, year = {2023}, } ``` ## Acknowledgement Some code snippets are borrowed from [NeuS](https://github.com/Totoro97/NeuS), [NDF](https://github.com/jchibane/ndf) and [MeshUDF](https://github.com/cvlab-epfl/MeshUDF). Thanks for these great projects. ================================================ FILE: confs/wmask_old.conf ================================================ general { base_exp_dir = ./exp/CASE_NAME/wmask recording = [ ./, ./models ] } dataset { data_dir = ./public_data/CASE_NAME/ render_cameras_name = cameras_sphere.npz object_cameras_name = cameras_sphere.npz } train { learning_rate = 2e-4 learning_rate_alpha = 0.05 end_iter = 400000 batch_size = 512 validate_resolution_level = 4 warm_up_end = 5000 anneal_end = 0 use_white_bkgd = False save_freq = 10000 val_freq = 2500 val_mesh_freq = 5000 report_freq = 100 mask_weight = 0.1 igr_weight = 0.1 normal_weight = 0.02 dist_weight = 0.0 geo_reg_weight = 0.0 sym_weight = 0.0 mcube_threshold = 0.005 up_sample_start = 100000 perm_num = 8 } model { nerf { D = 8, d_in = 4, d_in_view = 3, W = 256, multires = 10, multires_view = 4, output_ch = 4, skips=[4], use_viewdirs=True } sdf_network { d_out = 257 d_in = 3 d_hidden = 256 n_layers = 8 skip_in = [4] multires = 6 bias = 0.5 scale = 1.0 geometric_init = True weight_norm = True } variance_network { init_val = 0.3 } rendering_network { d_feature = 256 mode = normal_appr d_in = 9 d_out = 3 d_hidden = 256 n_layers = 4 weight_norm = True multires_view = 4 squeeze_out = True } neus_renderer { n_samples = 64 n_importance = 64 n_outside = 0 perturb = 1.0 disturb = 0.0 disturb_end = 0 up_sample_mode = naive_appr up_sample_steps = 2 # 1 for simple coarse-to-fine sampling up_sample_appr_level = 3 up_sample_s = 64 render_mode = div } } ================================================ FILE: confs/wmask_open.conf ================================================ general { base_exp_dir = ./exp/CASE_NAME/wmask_open recording = [ ./, ./models ] } dataset { data_dir = ./public_data/CASE_NAME/ render_cameras_name = cameras_sphere.npz object_cameras_name = cameras_sphere.npz } train { learning_rate = 2e-4 learning_rate_alpha = 0.05 end_iter = 400000 batch_size = 512 validate_resolution_level = 4 warm_up_end = 5000 anneal_end = 0 use_white_bkgd = False save_freq = 10000 val_freq = 2500 val_mesh_freq = 5000 report_freq = 100 mask_weight = 0.1 igr_weight = 0.1 normal_weight = 0.02 mcube_threshold = 0.005 up_sample_start = 0 perm_num = 8 } model { nerf { D = 8, d_in = 4, d_in_view = 3, W = 256, multires = 10, multires_view = 4, output_ch = 4, skips=[4], use_viewdirs=True } sdf_network { d_out = 257 d_in = 3 d_hidden = 256 n_layers = 8 skip_in = [4] multires = 6 bias = 0.5 scale = 1.0 geometric_init = True weight_norm = True } variance_network { init_val = 0.3 } rendering_network { d_feature = 256 mode = normal_appr d_in = 9 d_out = 3 d_hidden = 256 n_layers = 4 weight_norm = True multires_view = 4 squeeze_out = True } neus_renderer { n_samples = 64 n_importance = 64 n_outside = 0 perturb = 1.0 disturb = 0.0 disturb_end = 0 up_sample_mode = naive_appr up_sample_steps = 2 # 1 for simple coarse-to-fine sampling up_sample_appr_level = 3 up_sample_s = 64 render_mode = div } } ================================================ FILE: confs/womask_open.conf ================================================ general { base_exp_dir = ./exp/CASE_NAME/womask_open recording = [ ./, ./models ] } dataset { data_dir = ./public_data/CASE_NAME/ render_cameras_name = cameras_sphere.npz object_cameras_name = cameras_sphere.npz } train { learning_rate = 2e-4 learning_rate_alpha = 0.05 end_iter = 400000 batch_size = 512 validate_resolution_level = 4 warm_up_end = 5000 anneal_end = 10000 use_white_bkgd = False save_freq = 10000 val_freq = 2500 val_mesh_freq = 5000 report_freq = 100 mask_weight = 0.0 igr_weight = 0.1 normal_weight = 0.02 mcube_threshold = 0.005 up_sample_start = 100000 perm_num = 8 } model { nerf { D = 8, d_in = 4, d_in_view = 3, W = 256, multires = 10, multires_view = 4, output_ch = 4, skips=[4], use_viewdirs=True } sdf_network { d_out = 257 d_in = 3 d_hidden = 256 n_layers = 8 skip_in = [4] multires = 6 bias = 0.5 scale = 1.0 geometric_init = True weight_norm = True } variance_network { init_val = 0.3 } rendering_network { d_feature = 256 mode = normal_appr d_in = 9 d_out = 3 d_hidden = 256 n_layers = 4 weight_norm = True multires_view = 4 squeeze_out = True } neus_renderer { n_samples = 64 n_importance = 64 n_outside = 32 perturb = 1.0 disturb = 0.0 disturb_end = 0 up_sample_mode = naive_appr up_sample_steps = 2 # 1 for simple coarse-to-fine sampling up_sample_appr_level = 3 up_sample_s = 64 render_mode = div } } ================================================ FILE: custom_mc/_marching_cubes_lewiner.py ================================================ import base64 import numpy as np import _marching_cubes_lewiner_luts as mcluts import _marching_cubes_lewiner_cy def marching_cubes_lewiner(volume, level=None, spacing=(1., 1., 1.), gradient_direction='descent', step_size=1, allow_degenerate=True, use_classic=False, mask=None): """Lewiner et al. algorithm for marching cubes. See marching_cubes_lewiner for documentation. """ # Check volume and ensure its in the format that the alg needs if not isinstance(volume, np.ndarray) or (volume.ndim != 3): raise ValueError('Input volume should be a 3D numpy array.') if volume.shape[0] < 2 or volume.shape[1] < 2 or volume.shape[2] < 2: raise ValueError("Input array must be at least 2x2x2.") volume = np.ascontiguousarray(volume, np.float32) # no copy if not necessary # Check/convert other inputs: # level if level is None: level = 0.5 * (volume.min() + volume.max()) else: level = float(level) if level < volume.min() or level > volume.max(): raise ValueError("Surface level must be within volume data range.") # spacing if len(spacing) != 3: raise ValueError("`spacing` must consist of three floats.") # step_size step_size = int(step_size) if step_size < 1: raise ValueError('step_size must be at least one.') # use_classic use_classic = bool(use_classic) # Get LutProvider class (reuse if possible) L = _get_mc_luts() # Check if a mask array is passed if mask is not None: if not mask.shape == volume.shape: raise ValueError('volume and mask must have the same shape.') # Apply algorithm func = _marching_cubes_lewiner_cy.marching_cubes vertices, faces, normals, values = func(volume, level, L, step_size, use_classic, mask) if not len(vertices): raise RuntimeError('No surface found at the given iso value.') # Output in z-y-x order, as is common in skimage vertices = np.fliplr(vertices) normals = np.fliplr(normals) # Finishing touches to output faces.shape = -1, 3 if gradient_direction == 'descent': # MC implementation is right-handed, but gradient_direction is # left-handed faces = np.fliplr(faces) elif not gradient_direction == 'ascent': raise ValueError("Incorrect input %s in `gradient_direction`, see " "docstring." % (gradient_direction)) if not np.array_equal(spacing, (1, 1, 1)): vertices = vertices * np.r_[spacing] if allow_degenerate: return vertices, faces, normals, values else: fun = _marching_cubes_lewiner_cy.remove_degenerate_faces return fun(vertices.astype(np.float32), faces, normals, values) def udf_mc_lewiner(volume, grads, spacing=(1., 1., 1.), gradient_direction='descent', step_size=1, allow_degenerate=True, use_classic=False, mask=None): """Lewiner et al. algorithm for marching cubes. See marching_cubes_lewiner for documentation. """ # Check volume and ensure its in the format that the alg needs if not isinstance(volume, np.ndarray) or (volume.ndim != 3): raise ValueError('Input volume should be a 3D numpy array.') if volume.shape[0] < 2 or volume.shape[1] < 2 or volume.shape[2] < 2: raise ValueError("Input array must be at least 2x2x2.") volume = np.ascontiguousarray(volume, np.float32) # no copy if not necessary # spacing if len(spacing) != 3: raise ValueError("`spacing` must consist of three floats.") # step_size step_size = int(step_size) if step_size < 1: raise ValueError('step_size must be at least one.') # use_classic use_classic = bool(use_classic) # Get LutProvider class (reuse if possible) L = _get_mc_luts() # Check if a mask array is passed if mask is not None: if not mask.shape == volume.shape: raise ValueError('volume and mask must have the same shape.') # Apply algorithm func = _marching_cubes_lewiner_cy.marching_cubes_udf vertices, faces, normals, values = func(volume, grads, L, step_size, use_classic, mask) if not len(vertices): raise RuntimeError('No surface found at the given iso value.') # Output in z-y-x order, as is common in skimage vertices = np.fliplr(vertices) normals = np.fliplr(normals) # Finishing touches to output faces.shape = -1, 3 if gradient_direction == 'descent': # MC implementation is right-handed, but gradient_direction is # left-handed faces = np.fliplr(faces) elif not gradient_direction == 'ascent': raise ValueError("Incorrect input %s in `gradient_direction`, see " "docstring." % (gradient_direction)) if not np.array_equal(spacing, (1, 1, 1)): vertices = vertices * np.r_[spacing] if allow_degenerate: return vertices, faces, normals, values else: fun = _marching_cubes_lewiner_cy.remove_degenerate_faces return fun(vertices.astype(np.float32), faces, normals, values) def _to_array(args): shape, text = args byts = base64.decodebytes(text.encode('utf-8')) ar = np.frombuffer(byts, dtype='int8') ar.shape = shape return ar # Map an edge-index to two relative pixel positions. The ege index # represents a point that lies somewhere in between these pixels. # Linear interpolation should be used to determine where it is exactly. # 0 # 3 1 -> 0x # 2 xx EDGETORELATIVEPOSX = np.array([ [0,1],[1,1],[1,0],[0,0], [0,1],[1,1],[1,0],[0,0], [0,0],[1,1],[1,1],[0,0] ], 'int8') EDGETORELATIVEPOSY = np.array([ [0,0],[0,1],[1,1],[1,0], [0,0],[0,1],[1,1],[1,0], [0,0],[0,0],[1,1],[1,1] ], 'int8') EDGETORELATIVEPOSZ = np.array([ [0,0],[0,0],[0,0],[0,0], [1,1],[1,1],[1,1],[1,1], [0,1],[0,1],[0,1],[0,1] ], 'int8') def _get_mc_luts(): """ Kind of lazy obtaining of the luts. """ if not hasattr(mcluts, 'THE_LUTS'): mcluts.THE_LUTS = _marching_cubes_lewiner_cy.LutProvider( EDGETORELATIVEPOSX, EDGETORELATIVEPOSY, EDGETORELATIVEPOSZ, _to_array(mcluts.CASESCLASSIC), _to_array(mcluts.CASES), _to_array(mcluts.TILING1), _to_array(mcluts.TILING2), _to_array(mcluts.TILING3_1), _to_array(mcluts.TILING3_2), _to_array(mcluts.TILING4_1), _to_array(mcluts.TILING4_2), _to_array(mcluts.TILING5), _to_array(mcluts.TILING6_1_1), _to_array(mcluts.TILING6_1_2), _to_array(mcluts.TILING6_2), _to_array(mcluts.TILING7_1), _to_array(mcluts.TILING7_2), _to_array(mcluts.TILING7_3), _to_array(mcluts.TILING7_4_1), _to_array(mcluts.TILING7_4_2), _to_array(mcluts.TILING8), _to_array(mcluts.TILING9), _to_array(mcluts.TILING10_1_1), _to_array(mcluts.TILING10_1_1_), _to_array(mcluts.TILING10_1_2), _to_array(mcluts.TILING10_2), _to_array(mcluts.TILING10_2_), _to_array(mcluts.TILING11), _to_array(mcluts.TILING12_1_1), _to_array(mcluts.TILING12_1_1_), _to_array(mcluts.TILING12_1_2), _to_array(mcluts.TILING12_2), _to_array(mcluts.TILING12_2_), _to_array(mcluts.TILING13_1), _to_array(mcluts.TILING13_1_), _to_array(mcluts.TILING13_2), _to_array(mcluts.TILING13_2_), _to_array(mcluts.TILING13_3), _to_array(mcluts.TILING13_3_), _to_array(mcluts.TILING13_4), _to_array(mcluts.TILING13_5_1), _to_array(mcluts.TILING13_5_2), _to_array(mcluts.TILING14), _to_array(mcluts.TEST3), _to_array(mcluts.TEST4), _to_array(mcluts.TEST6), _to_array(mcluts.TEST7), _to_array(mcluts.TEST10), _to_array(mcluts.TEST12), _to_array(mcluts.TEST13), _to_array(mcluts.SUBCONFIG13), ) return mcluts.THE_LUTS ================================================ FILE: custom_mc/_marching_cubes_lewiner_cy.c ================================================ /* Generated by Cython 0.29.30 */ /* BEGIN: Cython Metadata { "distutils": { "depends": [], "name": "_marching_cubes_lewiner_cy", "sources": [ "_marching_cubes_lewiner_cy.pyx" ] }, "module_name": "_marching_cubes_lewiner_cy" } END: Cython Metadata */ 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CYTHON_USE_UNICODE_INTERNALS 1 #endif #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #undef CYTHON_PEP489_MULTI_PHASE_INIT #define CYTHON_PEP489_MULTI_PHASE_INIT 0 #undef CYTHON_USE_TP_FINALIZE #define CYTHON_USE_TP_FINALIZE 0 #undef CYTHON_USE_DICT_VERSIONS #define CYTHON_USE_DICT_VERSIONS 0 #undef CYTHON_USE_EXC_INFO_STACK #define CYTHON_USE_EXC_INFO_STACK 0 #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC #define CYTHON_UPDATE_DESCRIPTOR_DOC 0 #endif #else #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #if PY_VERSION_HEX < 0x02070000 #undef CYTHON_USE_PYTYPE_LOOKUP #define CYTHON_USE_PYTYPE_LOOKUP 0 #elif !defined(CYTHON_USE_PYTYPE_LOOKUP) #define CYTHON_USE_PYTYPE_LOOKUP 1 #endif #if PY_MAJOR_VERSION < 3 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #elif !defined(CYTHON_USE_ASYNC_SLOTS) #define CYTHON_USE_ASYNC_SLOTS 1 #endif #if PY_VERSION_HEX < 0x02070000 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #elif !defined(CYTHON_USE_PYLONG_INTERNALS) #define CYTHON_USE_PYLONG_INTERNALS 1 #endif #ifndef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 1 #endif #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #if PY_VERSION_HEX < 0x030300F0 || PY_VERSION_HEX >= 0x030B00A2 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #elif !defined(CYTHON_USE_UNICODE_WRITER) #define CYTHON_USE_UNICODE_WRITER 1 #endif #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #if PY_VERSION_HEX >= 0x030B00A4 #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #elif !defined(CYTHON_FAST_THREAD_STATE) #define CYTHON_FAST_THREAD_STATE 1 #endif #ifndef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL (PY_VERSION_HEX < 0x030A0000) #endif #ifndef CYTHON_PEP489_MULTI_PHASE_INIT #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000) #endif #ifndef CYTHON_USE_TP_FINALIZE #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1) #endif #ifndef CYTHON_USE_DICT_VERSIONS #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1) #endif #if PY_VERSION_HEX >= 0x030B00A4 #undef CYTHON_USE_EXC_INFO_STACK #define CYTHON_USE_EXC_INFO_STACK 0 #elif !defined(CYTHON_USE_EXC_INFO_STACK) #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3) #endif #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC #define CYTHON_UPDATE_DESCRIPTOR_DOC 1 #endif #endif #if !defined(CYTHON_FAST_PYCCALL) #define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) #endif #if CYTHON_USE_PYLONG_INTERNALS #if PY_MAJOR_VERSION < 3 #include "longintrepr.h" #endif #undef SHIFT #undef BASE #undef MASK #ifdef SIZEOF_VOID_P enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) }; #endif #endif #ifndef __has_attribute #define __has_attribute(x) 0 #endif #ifndef __has_cpp_attribute #define __has_cpp_attribute(x) 0 #endif #ifndef CYTHON_RESTRICT #if defined(__GNUC__) #define CYTHON_RESTRICT __restrict__ #elif defined(_MSC_VER) && _MSC_VER >= 1400 #define CYTHON_RESTRICT __restrict #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define CYTHON_RESTRICT restrict #else #define CYTHON_RESTRICT #endif #endif #ifndef CYTHON_UNUSED # if defined(__GNUC__) # if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) # define CYTHON_UNUSED __attribute__ ((__unused__)) # else # define CYTHON_UNUSED # endif # elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) # define CYTHON_UNUSED __attribute__ ((__unused__)) # else # define CYTHON_UNUSED # endif #endif #ifndef CYTHON_MAYBE_UNUSED_VAR # if defined(__cplusplus) template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } # else # define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) # endif #endif #ifndef CYTHON_NCP_UNUSED # if CYTHON_COMPILING_IN_CPYTHON # define CYTHON_NCP_UNUSED # else # define CYTHON_NCP_UNUSED CYTHON_UNUSED # endif #endif #define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) #ifdef _MSC_VER #ifndef _MSC_STDINT_H_ #if _MSC_VER < 1300 typedef unsigned char uint8_t; typedef unsigned int uint32_t; #else typedef unsigned __int8 uint8_t; typedef unsigned __int32 uint32_t; #endif #endif #else #include #endif #ifndef CYTHON_FALLTHROUGH #if defined(__cplusplus) && __cplusplus >= 201103L #if __has_cpp_attribute(fallthrough) #define CYTHON_FALLTHROUGH [[fallthrough]] #elif __has_cpp_attribute(clang::fallthrough) #define CYTHON_FALLTHROUGH [[clang::fallthrough]] #elif __has_cpp_attribute(gnu::fallthrough) #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] #endif #endif #ifndef CYTHON_FALLTHROUGH #if __has_attribute(fallthrough) #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) #else #define CYTHON_FALLTHROUGH #endif #endif #if defined(__clang__ ) && defined(__apple_build_version__) #if __apple_build_version__ < 7000000 #undef CYTHON_FALLTHROUGH #define CYTHON_FALLTHROUGH #endif #endif #endif #ifndef CYTHON_INLINE #if defined(__clang__) #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) #elif defined(__GNUC__) #define CYTHON_INLINE __inline__ #elif defined(_MSC_VER) #define CYTHON_INLINE __inline #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define CYTHON_INLINE inline #else #define CYTHON_INLINE #endif #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T "n" #define CYTHON_FORMAT_SSIZE_T "z" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" #define __Pyx_DefaultClassType PyType_Type #if PY_VERSION_HEX >= 0x030B00A1 static CYTHON_INLINE PyCodeObject* __Pyx_PyCode_New(int a, int k, int l, int s, int f, PyObject *code, PyObject *c, PyObject* n, PyObject *v, PyObject *fv, PyObject *cell, PyObject* fn, PyObject *name, int fline, PyObject *lnos) { PyObject *kwds=NULL, *argcount=NULL, *posonlyargcount=NULL, *kwonlyargcount=NULL; PyObject *nlocals=NULL, *stacksize=NULL, *flags=NULL, *replace=NULL, *call_result=NULL, *empty=NULL; const char *fn_cstr=NULL; const char *name_cstr=NULL; PyCodeObject* co=NULL; PyObject *type, *value, *traceback; PyErr_Fetch(&type, &value, &traceback); if (!(kwds=PyDict_New())) goto end; if (!(argcount=PyLong_FromLong(a))) goto end; if (PyDict_SetItemString(kwds, "co_argcount", argcount) != 0) goto end; if (!(posonlyargcount=PyLong_FromLong(0))) goto end; if (PyDict_SetItemString(kwds, "co_posonlyargcount", posonlyargcount) != 0) goto end; if (!(kwonlyargcount=PyLong_FromLong(k))) goto end; if (PyDict_SetItemString(kwds, "co_kwonlyargcount", kwonlyargcount) != 0) goto end; if (!(nlocals=PyLong_FromLong(l))) goto end; if (PyDict_SetItemString(kwds, "co_nlocals", nlocals) != 0) goto end; if (!(stacksize=PyLong_FromLong(s))) goto end; if (PyDict_SetItemString(kwds, "co_stacksize", stacksize) != 0) goto end; if (!(flags=PyLong_FromLong(f))) goto end; if (PyDict_SetItemString(kwds, "co_flags", flags) != 0) goto end; if (PyDict_SetItemString(kwds, "co_code", code) != 0) goto end; if (PyDict_SetItemString(kwds, "co_consts", c) != 0) goto end; if (PyDict_SetItemString(kwds, "co_names", n) != 0) goto end; if (PyDict_SetItemString(kwds, "co_varnames", v) != 0) goto end; if (PyDict_SetItemString(kwds, "co_freevars", fv) != 0) goto end; if (PyDict_SetItemString(kwds, "co_cellvars", cell) != 0) goto end; if (PyDict_SetItemString(kwds, "co_linetable", lnos) != 0) goto end; if (!(fn_cstr=PyUnicode_AsUTF8AndSize(fn, NULL))) goto end; if (!(name_cstr=PyUnicode_AsUTF8AndSize(name, NULL))) goto end; if (!(co = PyCode_NewEmpty(fn_cstr, name_cstr, fline))) goto end; if (!(replace = PyObject_GetAttrString((PyObject*)co, "replace"))) goto cleanup_code_too; if (!(empty = PyTuple_New(0))) goto cleanup_code_too; // unfortunately __pyx_empty_tuple isn't available here if (!(call_result = PyObject_Call(replace, empty, kwds))) goto cleanup_code_too; Py_XDECREF((PyObject*)co); co = (PyCodeObject*)call_result; call_result = NULL; if (0) { cleanup_code_too: Py_XDECREF((PyObject*)co); co = NULL; } end: Py_XDECREF(kwds); Py_XDECREF(argcount); Py_XDECREF(posonlyargcount); Py_XDECREF(kwonlyargcount); Py_XDECREF(nlocals); Py_XDECREF(stacksize); Py_XDECREF(replace); Py_XDECREF(call_result); Py_XDECREF(empty); if (type) { PyErr_Restore(type, value, traceback); } return co; } #else #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #endif #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 #endif #ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif #ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif #ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #ifndef METH_STACKLESS #define METH_STACKLESS 0 #endif #if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) #ifndef METH_FASTCALL #define METH_FASTCALL 0x80 #endif typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, Py_ssize_t nargs, PyObject *kwnames); #else #define __Pyx_PyCFunctionFast _PyCFunctionFast #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords #endif #if CYTHON_FAST_PYCCALL #define __Pyx_PyFastCFunction_Check(func)\ ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) #define PyObject_Realloc(p) PyMem_Realloc(p) #endif #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 #define PyMem_RawMalloc(n) PyMem_Malloc(n) #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) #define PyMem_RawFree(p) PyMem_Free(p) #endif #if CYTHON_COMPILING_IN_PYSTON #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) #else #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) #endif #if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 #define __Pyx_PyThreadState_Current PyThreadState_GET() #elif PY_VERSION_HEX >= 0x03060000 #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() #elif PY_VERSION_HEX >= 0x03000000 #define __Pyx_PyThreadState_Current PyThreadState_GET() #else #define __Pyx_PyThreadState_Current _PyThreadState_Current #endif #if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) #include "pythread.h" #define Py_tss_NEEDS_INIT 0 typedef int Py_tss_t; static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { *key = PyThread_create_key(); return 0; } static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); *key = Py_tss_NEEDS_INIT; return key; } static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { PyObject_Free(key); } static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { return *key != Py_tss_NEEDS_INIT; } static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { PyThread_delete_key(*key); *key = Py_tss_NEEDS_INIT; } static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { return PyThread_set_key_value(*key, value); } static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { return PyThread_get_key_value(*key); } #endif #if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) #define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) #else #define __Pyx_PyDict_NewPresized(n) PyDict_New() #endif #if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) #else #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) #endif #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS #define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) #else #define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) #endif #if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) #define CYTHON_PEP393_ENABLED 1 #if defined(PyUnicode_IS_READY) #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ 0 : _PyUnicode_Ready((PyObject *)(op))) #else #define __Pyx_PyUnicode_READY(op) (0) #endif #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03090000 #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : ((PyCompactUnicodeObject *)(u))->wstr_length)) #else #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) #endif #else #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) #endif #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 #define PyUnicode_2BYTE_KIND 2 #define PyUnicode_4BYTE_KIND 4 #define __Pyx_PyUnicode_READY(op) (0) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) #endif #if CYTHON_COMPILING_IN_PYPY #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) #endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) #define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) #else #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) #endif #if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) #define PyObject_ASCII(o) PyObject_Repr(o) #endif #if PY_MAJOR_VERSION >= 3 #define PyBaseString_Type PyUnicode_Type #define PyStringObject PyUnicodeObject #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact #ifndef PyObject_Unicode #define PyObject_Unicode PyObject_Str #endif #endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) #else #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) #endif #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif #if PY_VERSION_HEX >= 0x030900A4 #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) #else #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) #endif #if CYTHON_ASSUME_SAFE_MACROS #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) #else #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) #endif #if PY_MAJOR_VERSION >= 3 #define PyIntObject PyLongObject #define PyInt_Type PyLong_Type #define PyInt_Check(op) PyLong_Check(op) #define PyInt_CheckExact(op) PyLong_CheckExact(op) #define PyInt_FromString PyLong_FromString #define PyInt_FromUnicode PyLong_FromUnicode #define PyInt_FromLong PyLong_FromLong #define PyInt_FromSize_t PyLong_FromSize_t #define PyInt_FromSsize_t PyLong_FromSsize_t #define PyInt_AsLong PyLong_AsLong #define PyInt_AS_LONG PyLong_AS_LONG #define PyInt_AsSsize_t PyLong_AsSsize_t #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask #define PyNumber_Int PyNumber_Long #endif #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif #if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY #ifndef PyUnicode_InternFromString #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) #endif #endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong #define __Pyx_PyInt_AsHash_t __Pyx_PyIndex_AsHash_t #else #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t #define __Pyx_PyInt_AsHash_t __Pyx_PyIndex_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyMethod_New(func, self, klass) ((self) ? 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__Pyx_NewRef(obj) : PySequence_Tuple(obj)) static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject*); #if CYTHON_ASSUME_SAFE_MACROS #define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) #else #define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) #endif #define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) #else #define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) #endif #define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII static int __Pyx_sys_getdefaultencoding_not_ascii; static int __Pyx_init_sys_getdefaultencoding_params(void) { PyObject* sys; PyObject* default_encoding = NULL; PyObject* ascii_chars_u = NULL; PyObject* ascii_chars_b = NULL; const char* default_encoding_c; sys = PyImport_ImportModule("sys"); if (!sys) goto bad; default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); if (!default_encoding_c) goto bad; if (strcmp(default_encoding_c, "ascii") == 0) { __Pyx_sys_getdefaultencoding_not_ascii = 0; } else { char ascii_chars[128]; int c; for (c = 0; c < 128; c++) { ascii_chars[c] = c; } __Pyx_sys_getdefaultencoding_not_ascii = 1; ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); if (!ascii_chars_u) goto bad; ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { PyErr_Format( PyExc_ValueError, "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", default_encoding_c); goto bad; } Py_DECREF(ascii_chars_u); Py_DECREF(ascii_chars_b); } Py_DECREF(default_encoding); return 0; bad: Py_XDECREF(default_encoding); Py_XDECREF(ascii_chars_u); Py_XDECREF(ascii_chars_b); return -1; } #endif #if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 #define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) #else #define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) #if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT static char* __PYX_DEFAULT_STRING_ENCODING; static int __Pyx_init_sys_getdefaultencoding_params(void) { PyObject* sys; PyObject* default_encoding = NULL; char* default_encoding_c; sys = PyImport_ImportModule("sys"); if (!sys) goto bad; default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); if (!default_encoding_c) goto bad; __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); Py_DECREF(default_encoding); return 0; bad: Py_XDECREF(default_encoding); return -1; } #endif #endif /* Test for GCC > 2.95 */ #if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) #define likely(x) __builtin_expect(!!(x), 1) #define unlikely(x) __builtin_expect(!!(x), 0) #else /* !__GNUC__ or GCC < 2.95 */ #define likely(x) (x) #define unlikely(x) (x) #endif /* __GNUC__ */ static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; 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#if CYTHON_ATOMICS #define __pyx_add_acquisition_count(memview)\ __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #define __pyx_sub_acquisition_count(memview)\ __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #else #define __pyx_add_acquisition_count(memview)\ __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #define __pyx_sub_acquisition_count(memview)\ __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #endif /* BufferFormatStructs.proto */ #define IS_UNSIGNED(type) (((type) -1) > 0) struct __Pyx_StructField_; #define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) typedef struct { const char* name; struct __Pyx_StructField_* fields; size_t size; size_t arraysize[8]; int ndim; char typegroup; char is_unsigned; int flags; } __Pyx_TypeInfo; typedef struct __Pyx_StructField_ { __Pyx_TypeInfo* type; const char* name; size_t offset; } __Pyx_StructField; typedef struct { __Pyx_StructField* field; 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/* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< * ctypedef npy_int64 int64_t * #ctypedef npy_int96 int96_t */ typedef npy_int32 __pyx_t_5numpy_int32_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":693 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< * #ctypedef npy_int96 int96_t * #ctypedef npy_int128 int128_t */ typedef npy_int64 __pyx_t_5numpy_int64_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":697 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":698 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< * ctypedef npy_uint64 uint64_t * #ctypedef npy_uint96 uint96_t */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":700 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< * #ctypedef npy_uint96 uint96_t * #ctypedef npy_uint128 uint128_t */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":704 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< * ctypedef npy_float64 float64_t * #ctypedef npy_float80 float80_t */ typedef npy_float32 __pyx_t_5numpy_float32_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":705 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< * #ctypedef npy_float80 float80_t * #ctypedef npy_float128 float128_t */ typedef npy_float64 __pyx_t_5numpy_float64_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":714 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t */ typedef npy_long __pyx_t_5numpy_int_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":715 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< * ctypedef npy_longlong longlong_t * */ typedef npy_longlong __pyx_t_5numpy_long_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":716 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< * * ctypedef npy_ulong uint_t */ typedef npy_longlong __pyx_t_5numpy_longlong_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":718 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t */ typedef npy_ulong __pyx_t_5numpy_uint_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":719 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< * ctypedef npy_ulonglong ulonglong_t * */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":720 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< * * ctypedef npy_intp intp_t */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":722 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< * ctypedef npy_uintp uintp_t * */ typedef npy_intp __pyx_t_5numpy_intp_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":723 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< * * ctypedef npy_double float_t */ typedef npy_uintp __pyx_t_5numpy_uintp_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":725 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t */ typedef npy_double __pyx_t_5numpy_float_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":726 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< * ctypedef npy_longdouble longdouble_t * */ typedef npy_double __pyx_t_5numpy_double_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":727 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< * * ctypedef npy_cfloat cfloat_t */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; /* Declarations.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus typedef ::std::complex< float > __pyx_t_float_complex; #else typedef float _Complex __pyx_t_float_complex; #endif #else typedef struct { float real, imag; } __pyx_t_float_complex; #endif static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); /* Declarations.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus typedef ::std::complex< double > __pyx_t_double_complex; #else typedef double _Complex __pyx_t_double_complex; #endif #else typedef struct { double real, imag; } __pyx_t_double_complex; #endif static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); /*--- Type declarations ---*/ struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut; struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider; struct __pyx_array_obj; struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":729 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":730 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< * ctypedef npy_clongdouble clongdouble_t * */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":731 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< * * ctypedef npy_cdouble complex_t */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; /* "../../../../../data/liuyutao/anaconda3/envs/neus/lib/python3.8/site-packages/numpy/__init__.pxd":733 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< * * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; /* "_marching_cubes_lewiner_cy.pyx":83 * * * cdef class Cell: # <<<<<<<<<<<<<< * """ Class to keep track of some stuff during the whole cube marching * procedure. */ struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell { PyObject_HEAD struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *__pyx_vtab; struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *luts; int x; int y; int z; int step; double v0; double v1; double v2; double v3; double v4; double v5; double v6; double v7; double *vv; double *vg; double vmax; double v12_x; double v12_y; double v12_z; double v12_xg; double v12_yg; double v12_zg; int v12_calculated; int index; int nx; int ny; int nz; int *faceLayer; int *faceLayer1; int *faceLayer2; float *_vertices; float *_normals; float *_values; int _vertexCount; int _vertexMaxCount; int *_faces; int _faceCount; int _faceMaxCount; }; /* "_marching_cubes_lewiner_cy.pyx":747 * * * cdef class Lut: # <<<<<<<<<<<<<< * """ Representation of a lookup table. * The tables are initially defined as numpy arrays. On initialization, */ struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut { PyObject_HEAD struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *__pyx_vtab; signed char *VALUES; int L0; int L1; int L2; }; /* "_marching_cubes_lewiner_cy.pyx":799 * * * cdef class LutProvider: # <<<<<<<<<<<<<< * """ Class that provides a common interface to the many lookup tables * used by the algorithm. */ struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider { PyObject_HEAD struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *EDGESRELX; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *EDGESRELY; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *EDGESRELZ; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *CASESCLASSIC; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *CASES; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING3_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING3_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING4_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING4_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING5; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING6_1_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING6_1_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING6_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING7_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING7_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING7_3; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING7_4_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING7_4_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING8; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING9; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING10_1_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING10_1_1_; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING10_1_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING10_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING10_2_; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING11; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING12_1_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING12_1_1_; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING12_1_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING12_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING12_2_; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_1_; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_2_; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_3; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_3_; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_4; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_5_1; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING13_5_2; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TILING14; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TEST3; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TEST4; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TEST6; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TEST7; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TEST10; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TEST12; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *TEST13; struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *SUBCONFIG13; }; /* "View.MemoryView":105 * * @cname("__pyx_array") * cdef class array: # <<<<<<<<<<<<<< * * cdef: */ struct __pyx_array_obj { PyObject_HEAD struct __pyx_vtabstruct_array *__pyx_vtab; char *data; Py_ssize_t len; char *format; int ndim; Py_ssize_t *_shape; Py_ssize_t *_strides; Py_ssize_t itemsize; PyObject *mode; PyObject *_format; void (*callback_free_data)(void *); int free_data; int dtype_is_object; }; /* "View.MemoryView":279 * * @cname('__pyx_MemviewEnum') * cdef class Enum(object): # <<<<<<<<<<<<<< * cdef object name * def __init__(self, name): */ struct __pyx_MemviewEnum_obj { PyObject_HEAD PyObject *name; }; /* "View.MemoryView":330 * * @cname('__pyx_memoryview') * cdef class memoryview(object): # <<<<<<<<<<<<<< * * cdef object obj */ struct __pyx_memoryview_obj { PyObject_HEAD struct __pyx_vtabstruct_memoryview *__pyx_vtab; PyObject *obj; PyObject *_size; PyObject *_array_interface; PyThread_type_lock lock; __pyx_atomic_int acquisition_count[2]; __pyx_atomic_int *acquisition_count_aligned_p; Py_buffer view; int flags; int dtype_is_object; __Pyx_TypeInfo *typeinfo; }; /* "View.MemoryView":965 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< * "Internal class for passing memoryview slices to Python" * */ struct __pyx_memoryviewslice_obj { struct __pyx_memoryview_obj __pyx_base; __Pyx_memviewslice from_slice; PyObject *from_object; PyObject *(*to_object_func)(char *); int (*to_dtype_func)(char *, PyObject *); }; /* "_marching_cubes_lewiner_cy.pyx":83 * * * cdef class Cell: # <<<<<<<<<<<<<< * """ Class to keep track of some stuff during the whole cube marching * procedure. */ struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell { void (*_increase_size_vertices)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *); void (*_increase_size_faces)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *); int (*add_vertex)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, float, float, float); void (*add_gradient)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, int, float, float, float); void (*add_gradient_from_index)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, int, int, float); PyObject *(*add_face)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, int); void (*new_z_value)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *); void (*set_cube)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, double, int, int, int, int, double, double, double, double, double, double, double, double); void (*add_triangles)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *, int, int); void (*add_triangles2)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *, int, int, int); void (*_add_face_from_edge_index)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, int); int (*get_index_in_facelayer)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, int); void (*prepare_for_adding_triangles)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *); void (*calculate_center_vertex)(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *); }; static struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *__pyx_vtabptr_26_marching_cubes_lewiner_cy_Cell; /* "_marching_cubes_lewiner_cy.pyx":747 * * * cdef class Lut: # <<<<<<<<<<<<<< * """ Representation of a lookup table. * The tables are initially defined as numpy arrays. 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#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ static PY_UINT64_T __pyx_dict_version = 0;\ static PyObject *__pyx_dict_cached_value = NULL;\ if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ (VAR) = __pyx_dict_cached_value;\ } else {\ (VAR) = __pyx_dict_cached_value = (LOOKUP);\ __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ }\ } static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); #else #define __PYX_GET_DICT_VERSION(dict) (0) #define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) #define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); #endif /* GetModuleGlobalName.proto */ #if CYTHON_USE_DICT_VERSIONS #define __Pyx_GetModuleGlobalName(var, name) {\ static PY_UINT64_T __pyx_dict_version = 0;\ static PyObject *__pyx_dict_cached_value = NULL;\ (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ } #define __Pyx_GetModuleGlobalNameUncached(var, name) {\ PY_UINT64_T __pyx_dict_version;\ PyObject *__pyx_dict_cached_value;\ (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ } static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); #else #define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) #define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); #endif /* PyObjectCall.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); #else #define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) #endif /* PyFunctionFastCall.proto */ #if CYTHON_FAST_PYCALL #define __Pyx_PyFunction_FastCall(func, args, nargs)\ __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) #if 1 || PY_VERSION_HEX < 0x030600B1 static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); #else #define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) #endif #define __Pyx_BUILD_ASSERT_EXPR(cond)\ (sizeof(char [1 - 2*!(cond)]) - 1) #ifndef Py_MEMBER_SIZE #define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) #endif #if CYTHON_FAST_PYCALL static size_t __pyx_pyframe_localsplus_offset = 0; #include "frameobject.h" #if PY_VERSION_HEX >= 0x030b00a6 #ifndef Py_BUILD_CORE #define Py_BUILD_CORE 1 #endif #include "internal/pycore_frame.h" #endif #define __Pxy_PyFrame_Initialize_Offsets()\ ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) #define __Pyx_PyFrame_GetLocalsplus(frame)\ (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) #endif // CYTHON_FAST_PYCALL #endif /* PyObjectCallMethO.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); #endif /* PyObjectCallNoArg.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); #else #define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) #endif /* PyCFunctionFastCall.proto */ #if CYTHON_FAST_PYCCALL static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); #else #define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) #endif /* PyObjectCallOneArg.proto */ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); /* MemviewSliceInit.proto */ #define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d #define __Pyx_MEMVIEW_DIRECT 1 #define __Pyx_MEMVIEW_PTR 2 #define __Pyx_MEMVIEW_FULL 4 #define __Pyx_MEMVIEW_CONTIG 8 #define __Pyx_MEMVIEW_STRIDED 16 #define __Pyx_MEMVIEW_FOLLOW 32 #define __Pyx_IS_C_CONTIG 1 #define __Pyx_IS_F_CONTIG 2 static int __Pyx_init_memviewslice( struct __pyx_memoryview_obj *memview, int ndim, __Pyx_memviewslice *memviewslice, int memview_is_new_reference); static CYTHON_INLINE int __pyx_add_acquisition_count_locked( __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); #define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) #define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) #define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) #define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); /* PyIntBinop.proto */ #if !CYTHON_COMPILING_IN_PYPY static PyObject* __Pyx_PyInt_SubtractObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); #else #define __Pyx_PyInt_SubtractObjC(op1, op2, intval, inplace, zerodivision_check)\ (inplace ? 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(PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ __Pyx_GetItemInt_Generic(o, to_py_func(i)))) #define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); #define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, int wraparound, int boundscheck); /* ObjectGetItem.proto */ #if CYTHON_USE_TYPE_SLOTS static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); #else #define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) #endif /* ListCompAppend.proto */ #if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { PyListObject* L = (PyListObject*) list; Py_ssize_t len = Py_SIZE(list); if (likely(L->allocated > len)) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); __Pyx_SET_SIZE(list, len + 1); return 0; } return PyList_Append(list, x); } #else #define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) #endif /* ArgTypeTest.proto */ #define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ __Pyx__ArgTypeTest(obj, type, name, exact)) static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact); /* KeywordStringCheck.proto */ static int __Pyx_CheckKeywordStrings(PyObject *kwdict, const char* function_name, int kw_allowed); /* PyThreadStateGet.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; #define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; #define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type #else #define __Pyx_PyThreadState_declare #define __Pyx_PyThreadState_assign #define __Pyx_PyErr_Occurred() PyErr_Occurred() #endif /* PyErrFetchRestore.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) #define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) #define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) #define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) #define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); #if CYTHON_COMPILING_IN_CPYTHON #define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) #else #define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) #endif #else #define __Pyx_PyErr_Clear() PyErr_Clear() #define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) #define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) #define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) #define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) #define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) #define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) #define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) #endif /* WriteUnraisableException.proto */ static void __Pyx_WriteUnraisable(const char *name, int clineno, int lineno, const char *filename, int full_traceback, int nogil); /* RaiseException.proto */ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); /* PyErrExceptionMatches.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); #else #define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) #endif /* GetAttr.proto */ static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); /* GetAttr3.proto */ static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); /* IsLittleEndian.proto */ static CYTHON_INLINE int __Pyx_Is_Little_Endian(void); /* BufferFormatCheck.proto */ static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, __Pyx_BufFmt_StackElem* stack, __Pyx_TypeInfo* type); /* BufferGetAndValidate.proto */ #define __Pyx_GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)\ ((obj == Py_None || obj == NULL) ?\ (__Pyx_ZeroBuffer(buf), 0) :\ __Pyx__GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)) static int __Pyx__GetBufferAndValidate(Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); static void __Pyx_ZeroBuffer(Py_buffer* buf); static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); static Py_ssize_t __Pyx_minusones[] = { -1, -1, -1, -1, -1, -1, -1, -1 }; static Py_ssize_t __Pyx_zeros[] = { 0, 0, 0, 0, 0, 0, 0, 0 }; #define __Pyx_BufPtrStrided3d(type, buf, i0, s0, i1, s1, i2, s2) (type)((char*)buf + i0 * s0 + i1 * s1 + i2 * s2) /* ExtTypeTest.proto */ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); /* None.proto */ static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); /* PySequenceContains.proto */ static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) { int result = PySequence_Contains(seq, item); return unlikely(result < 0) ? result : (result == (eq == Py_EQ)); } /* Import.proto */ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); /* ImportFrom.proto */ static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); /* HasAttr.proto */ static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); /* GetTopmostException.proto */ #if CYTHON_USE_EXC_INFO_STACK static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); #endif /* SaveResetException.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); #define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); #else #define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) #define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) #endif /* GetException.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); 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return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); } static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { int byteorder = -1; return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); } static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { int byteorder = 1; return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); } /* decode_c_string.proto */ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( const char* cstring, Py_ssize_t start, Py_ssize_t stop, const char* encoding, const char* errors, PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); /* RaiseTooManyValuesToUnpack.proto */ static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); /* RaiseNeedMoreValuesToUnpack.proto */ static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); /* RaiseNoneIterError.proto */ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); /* SwapException.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); #else static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); #endif /* FastTypeChecks.proto */ #if CYTHON_COMPILING_IN_CPYTHON #define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); #else #define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) #define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) #define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) #endif #define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ /* PyIntBinop.proto */ #if !CYTHON_COMPILING_IN_PYPY static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); #else #define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) #endif /* ListExtend.proto */ static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { #if CYTHON_COMPILING_IN_CPYTHON PyObject* none = _PyList_Extend((PyListObject*)L, v); if (unlikely(!none)) return -1; Py_DECREF(none); return 0; #else return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); #endif } /* ListAppend.proto */ #if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { PyListObject* L = (PyListObject*) list; Py_ssize_t len = Py_SIZE(list); if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); __Pyx_SET_SIZE(list, len + 1); return 0; } return PyList_Append(list, x); } #else #define __Pyx_PyList_Append(L,x) PyList_Append(L,x) #endif /* PyObject_GenericGetAttrNoDict.proto */ #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); #else #define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr #endif /* PyObject_GenericGetAttr.proto */ #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); #else #define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr #endif /* SetVTable.proto */ static int __Pyx_SetVtable(PyObject *dict, void *vtable); /* PyObjectGetAttrStrNoError.proto */ static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); /* SetupReduce.proto */ static int __Pyx_setup_reduce(PyObject* type_obj); /* TypeImport.proto */ #ifndef __PYX_HAVE_RT_ImportType_proto #define __PYX_HAVE_RT_ImportType_proto enum __Pyx_ImportType_CheckSize { __Pyx_ImportType_CheckSize_Error = 0, __Pyx_ImportType_CheckSize_Warn = 1, __Pyx_ImportType_CheckSize_Ignore = 2 }; static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); #endif /* CLineInTraceback.proto */ #ifdef CYTHON_CLINE_IN_TRACEBACK #define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) #else static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); #endif /* CodeObjectCache.proto */ typedef struct { PyCodeObject* code_object; int code_line; } __Pyx_CodeObjectCacheEntry; struct __Pyx_CodeObjectCache { int count; int max_count; __Pyx_CodeObjectCacheEntry* entries; }; static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); static PyCodeObject *__pyx_find_code_object(int code_line); static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); /* AddTraceback.proto */ static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename); #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); static void __Pyx_ReleaseBuffer(Py_buffer *view); #else #define __Pyx_GetBuffer PyObject_GetBuffer #define __Pyx_ReleaseBuffer PyBuffer_Release #endif /* BufferStructDeclare.proto */ typedef struct { Py_ssize_t shape, strides, suboffsets; } __Pyx_Buf_DimInfo; typedef struct { size_t refcount; Py_buffer pybuffer; } __Pyx_Buffer; typedef struct { __Pyx_Buffer *rcbuffer; char *data; __Pyx_Buf_DimInfo diminfo[8]; } __Pyx_LocalBuf_ND; /* MemviewSliceIsContig.proto */ static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); /* OverlappingSlices.proto */ static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, __Pyx_memviewslice *slice2, int ndim, size_t itemsize); /* Capsule.proto */ static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); /* GCCDiagnostics.proto */ #if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) #define __Pyx_HAS_GCC_DIAGNOSTIC #endif /* TypeInfoCompare.proto */ static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); /* MemviewSliceValidateAndInit.proto */ static int __Pyx_ValidateAndInit_memviewslice( int *axes_specs, int c_or_f_flag, int buf_flags, int ndim, __Pyx_TypeInfo *dtype, __Pyx_BufFmt_StackElem stack[], __Pyx_memviewslice *memviewslice, PyObject *original_obj); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsdsds_float(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsdsdsds_float(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_float(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_int(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_int(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_float(PyObject *, int writable_flag); /* Print.proto */ static int __Pyx_Print(PyObject*, PyObject *, int); #if CYTHON_COMPILING_IN_PYPY || PY_MAJOR_VERSION >= 3 static PyObject* __pyx_print = 0; static PyObject* __pyx_print_kwargs = 0; #endif /* RealImag.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus #define __Pyx_CREAL(z) ((z).real()) #define __Pyx_CIMAG(z) ((z).imag()) #else #define __Pyx_CREAL(z) (__real__(z)) #define __Pyx_CIMAG(z) (__imag__(z)) #endif #else #define __Pyx_CREAL(z) ((z).real) #define __Pyx_CIMAG(z) ((z).imag) #endif #if defined(__cplusplus) && CYTHON_CCOMPLEX\ && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) #define __Pyx_SET_CREAL(z,x) ((z).real(x)) #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) #else #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) #endif /* Arithmetic.proto */ #if CYTHON_CCOMPLEX #define __Pyx_c_eq_float(a, b) ((a)==(b)) #define __Pyx_c_sum_float(a, b) ((a)+(b)) #define __Pyx_c_diff_float(a, b) ((a)-(b)) #define __Pyx_c_prod_float(a, b) ((a)*(b)) #define __Pyx_c_quot_float(a, b) ((a)/(b)) #define __Pyx_c_neg_float(a) (-(a)) #ifdef __cplusplus #define __Pyx_c_is_zero_float(z) ((z)==(float)0) #define __Pyx_c_conj_float(z) (::std::conj(z)) #if 1 #define __Pyx_c_abs_float(z) (::std::abs(z)) #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) #endif #else #define __Pyx_c_is_zero_float(z) ((z)==0) #define __Pyx_c_conj_float(z) (conjf(z)) #if 1 #define __Pyx_c_abs_float(z) (cabsf(z)) #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) #endif #endif #else static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); #if 1 static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); #endif #endif /* Arithmetic.proto */ #if CYTHON_CCOMPLEX #define __Pyx_c_eq_double(a, b) ((a)==(b)) #define __Pyx_c_sum_double(a, b) ((a)+(b)) #define __Pyx_c_diff_double(a, b) ((a)-(b)) #define __Pyx_c_prod_double(a, b) ((a)*(b)) #define __Pyx_c_quot_double(a, b) ((a)/(b)) #define __Pyx_c_neg_double(a) (-(a)) #ifdef __cplusplus #define __Pyx_c_is_zero_double(z) ((z)==(double)0) #define __Pyx_c_conj_double(z) (::std::conj(z)) #if 1 #define __Pyx_c_abs_double(z) (::std::abs(z)) #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) #endif #else #define __Pyx_c_is_zero_double(z) ((z)==0) #define __Pyx_c_conj_double(z) (conj(z)) #if 1 #define __Pyx_c_abs_double(z) (cabs(z)) #define __Pyx_c_pow_double(a, b) (cpow(a, b)) #endif #endif #else static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); #if 1 static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); #endif #endif /* MemviewSliceCopyTemplate.proto */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, const char *mode, int ndim, size_t sizeof_dtype, int contig_flag, int dtype_is_object); /* CIntFromPy.proto */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); /* CIntFromPy.proto */ static CYTHON_INLINE signed char __Pyx_PyInt_As_signed__char(PyObject *); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_bool(npy_bool value); /* PrintOne.proto */ static int __Pyx_PrintOne(PyObject* stream, PyObject *o); /* CIntFromPy.proto */ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); /* CheckBinaryVersion.proto */ static int __Pyx_check_binary_version(void); /* InitStrings.proto */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell__increase_size_vertices(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell__increase_size_faces(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_4Cell_add_vertex(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, float __pyx_v_x, float __pyx_v_y, float __pyx_v_z); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_add_gradient(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, int __pyx_v_vertexIndex, float __pyx_v_gx, float __pyx_v_gy, float __pyx_v_gz); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_add_gradient_from_index(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, int __pyx_v_vertexIndex, int __pyx_v_i, float __pyx_v_strength); /* proto*/ static PyObject *__pyx_f_26_marching_cubes_lewiner_cy_4Cell_add_face(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, int __pyx_v_index); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_new_z_value(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_set_cube(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, double __pyx_v_isovalue, int __pyx_v_x, int __pyx_v_y, int __pyx_v_z, int __pyx_v_step, double __pyx_v_v0, double __pyx_v_v1, double __pyx_v_v2, double __pyx_v_v3, double __pyx_v_v4, double __pyx_v_v5, double __pyx_v_v6, double __pyx_v_v7); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_add_triangles(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_lut, int __pyx_v_lutIndex, int __pyx_v_nt); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_add_triangles2(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_lut, int __pyx_v_lutIndex, int __pyx_v_lutIndex2, int __pyx_v_nt); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell__add_face_from_edge_index(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, int __pyx_v_vi); /* proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_4Cell_get_index_in_facelayer(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, int __pyx_v_vi); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_prepare_for_adding_triangles(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_calculate_center_vertex(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_3Lut_get1(struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_self, int __pyx_v_i0); /* proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_3Lut_get2(struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_self, int __pyx_v_i0, int __pyx_v_i1); /* proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_3Lut_get3(struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_self, int __pyx_v_i0, int __pyx_v_i1, int __pyx_v_i2); /* proto*/ static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ /* Module declarations from 'cpython.buffer' */ /* Module declarations from 'libc.string' */ /* Module declarations from 'libc.stdio' */ /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.type' */ static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; /* Module declarations from 'cpython' */ /* Module declarations from 'cpython.object' */ /* Module declarations from 'cpython.ref' */ /* Module declarations from 'cpython.mem' */ /* Module declarations from 'numpy' */ /* Module declarations from 'numpy' */ static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; static PyTypeObject *__pyx_ptype_5numpy_generic = 0; static PyTypeObject *__pyx_ptype_5numpy_number = 0; static PyTypeObject *__pyx_ptype_5numpy_integer = 0; static PyTypeObject *__pyx_ptype_5numpy_signedinteger = 0; static PyTypeObject *__pyx_ptype_5numpy_unsignedinteger = 0; static PyTypeObject *__pyx_ptype_5numpy_inexact = 0; static PyTypeObject *__pyx_ptype_5numpy_floating = 0; static PyTypeObject *__pyx_ptype_5numpy_complexfloating = 0; static PyTypeObject *__pyx_ptype_5numpy_flexible = 0; static PyTypeObject *__pyx_ptype_5numpy_character = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ /* Module declarations from 'cython.view' */ /* Module declarations from 'cython' */ /* Module declarations from 'libc.stdlib' */ /* Module declarations from '_marching_cubes_lewiner_cy' */ static PyTypeObject *__pyx_ptype_26_marching_cubes_lewiner_cy_Cell = 0; static PyTypeObject *__pyx_ptype_26_marching_cubes_lewiner_cy_Lut = 0; static PyTypeObject *__pyx_ptype_26_marching_cubes_lewiner_cy_LutProvider = 0; static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; static PyTypeObject *__pyx_memoryview_type = 0; static PyTypeObject *__pyx_memoryviewslice_type = 0; static double __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON; static PyObject *generic = 0; static PyObject *strided = 0; static PyObject *indirect = 0; static PyObject *contiguous = 0; static PyObject *indirect_contiguous = 0; static int __pyx_memoryview_thread_locks_used; static PyThread_type_lock __pyx_memoryview_thread_locks[8]; static CYTHON_INLINE double __pyx_f_26_marching_cubes_lewiner_cy_dabs(double); /*proto*/ static CYTHON_INLINE int __pyx_f_26_marching_cubes_lewiner_cy_imin(int, int); /*proto*/ static float __pyx_f_26_marching_cubes_lewiner_cy_my_sign(float); /*proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_non_zero_norm(__Pyx_memviewslice); /*proto*/ static float __pyx_f_26_marching_cubes_lewiner_cy_avg_cube(float, float, float, float, float, float, float, float); /*proto*/ static float __pyx_f_26_marching_cubes_lewiner_cy_max_cube(float, float, float, float, float, float, float, float); /*proto*/ static float __pyx_f_26_marching_cubes_lewiner_cy_dot3(__Pyx_memviewslice, __Pyx_memviewslice); /*proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_inwards_facing_normals(PyArrayObject *, __Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice); /*proto*/ static void __pyx_f_26_marching_cubes_lewiner_cy_the_big_switch(struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *, struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, int, int); /*proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_test_face(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, int); /*proto*/ static int __pyx_f_26_marching_cubes_lewiner_cy_test_internal(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *, struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *, int, int, int, int); /*proto*/ static PyObject *__pyx_f_26_marching_cubes_lewiner_cy___pyx_unpickle_LutProvider__set_state(struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *, PyObject *); /*proto*/ static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ static void *__pyx_align_pointer(void *, size_t); /*proto*/ static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ static PyObject *_unellipsify(PyObject *, int); /*proto*/ static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ static __Pyx_TypeInfo __Pyx_TypeInfo_nn_npy_bool = { "npy_bool", NULL, sizeof(npy_bool), { 0 }, 0, IS_UNSIGNED(npy_bool) ? 'U' : 'I', IS_UNSIGNED(npy_bool), 0 }; static __Pyx_TypeInfo __Pyx_TypeInfo_float = { "float", NULL, sizeof(float), { 0 }, 0, 'R', 0, 0 }; static __Pyx_TypeInfo __Pyx_TypeInfo_int = { "int", NULL, sizeof(int), { 0 }, 0, IS_UNSIGNED(int) ? 'U' : 'I', IS_UNSIGNED(int), 0 }; #define __Pyx_MODULE_NAME "_marching_cubes_lewiner_cy" extern int __pyx_module_is_main__marching_cubes_lewiner_cy; int __pyx_module_is_main__marching_cubes_lewiner_cy = 0; /* Implementation of '_marching_cubes_lewiner_cy' */ static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_TypeError; static PyObject *__pyx_builtin_ImportError; static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_enumerate; static PyObject *__pyx_builtin_Ellipsis; static PyObject *__pyx_builtin_id; static PyObject *__pyx_builtin_IndexError; static const char __pyx_k_O[] = "O"; static const char __pyx_k_c[] = "c"; static const char __pyx_k_j[] = "j"; static const char __pyx_k_x[] = "x"; static const char __pyx_k_y[] = "y"; static const char __pyx_k_z[] = "z"; static const char __pyx_k_Nx[] = "Nx"; static const char __pyx_k_Ny[] = "Ny"; static const char __pyx_k_Nz[] = "Nz"; static const char __pyx_k_i1[] = "i1"; static const char __pyx_k_i2[] = "i2"; static const char __pyx_k_i3[] = "i3"; static const char __pyx_k_id[] = "id"; static const char __pyx_k_im[] = "im"; static const char __pyx_k_np[] = "np"; static const char __pyx_k_nt[] = "nt"; static const char __pyx_k_nx[] = "nx"; static const char __pyx_k_ny[] = "ny"; static const char __pyx_k_nz[] = "nz"; static const char __pyx_k_st[] = "st"; static const char __pyx_k_v1[] = "v1"; static const char __pyx_k_v2[] = "v2"; static const char __pyx_k_v3[] = "v3"; static const char __pyx_k_Lut[] = "Lut"; static const char __pyx_k_arr[] = "arr"; static const char __pyx_k_end[] = "end"; static const char __pyx_k_new[] = "__new__"; static const char __pyx_k_obj[] = "obj"; static const char __pyx_k_Cell[] = "Cell"; static const char __pyx_k_base[] = "base"; static const char __pyx_k_case[] = "case"; static const char __pyx_k_cell[] = "cell"; static const char __pyx_k_copy[] = "copy"; static const char __pyx_k_dict[] = "__dict__"; static const char __pyx_k_file[] = "file"; static const char __pyx_k_luts[] = "luts"; static const char __pyx_k_main[] = "__main__"; static const char __pyx_k_mask[] = "mask"; static const char __pyx_k_mode[] = "mode"; static const char __pyx_k_name[] = "name"; static const char __pyx_k_ndim[] = "ndim"; static const char __pyx_k_ones[] = "ones"; static const char __pyx_k_pack[] = "pack"; static const char __pyx_k_size[] = "size"; static const char __pyx_k_step[] = "step"; static const char __pyx_k_stop[] = "stop"; static const char __pyx_k_test[] = "__test__"; static const char __pyx_k_x_st[] = "x_st"; static const char __pyx_k_y_st[] = "y_st"; static const char __pyx_k_z_st[] = "z_st"; static const char __pyx_k_ASCII[] = "ASCII"; static const char __pyx_k_CASES[] = "CASES"; static const char __pyx_k_TEST3[] = "TEST3"; static const char __pyx_k_TEST4[] = "TEST4"; static const char __pyx_k_TEST6[] = "TEST6"; static const char __pyx_k_TEST7[] = "TEST7"; static const char __pyx_k_array[] = "array"; static const char __pyx_k_class[] = "__class__"; static const char __pyx_k_dtype[] = "dtype"; static const char __pyx_k_empty[] = "empty"; static const char __pyx_k_error[] = "error"; static const char __pyx_k_faces[] = "faces"; static const char __pyx_k_flags[] = "flags"; static const char __pyx_k_grads[] = "grads"; static const char __pyx_k_int32[] = "int32"; static const char __pyx_k_numpy[] = "numpy"; static const char __pyx_k_print[] = "print"; static const char __pyx_k_range[] = "range"; static const char __pyx_k_ravel[] = "ravel"; static const char __pyx_k_shape[] = "shape"; static const char __pyx_k_start[] = "start"; static const char __pyx_k_TEST10[] = "TEST10"; static const char __pyx_k_TEST12[] = "TEST12"; static const char __pyx_k_TEST13[] = "TEST13"; static const char __pyx_k_arange[] = "arange"; static const char __pyx_k_arrays[] = "arrays"; static const char __pyx_k_config[] = "config"; static const char __pyx_k_cumsum[] = "cumsum"; static const char __pyx_k_encode[] = "encode"; static const char __pyx_k_faces2[] = "faces2"; static const char __pyx_k_format[] = "format"; static const char __pyx_k_import[] = "__import__"; static const char __pyx_k_name_2[] = "__name__"; static const char __pyx_k_pickle[] = "pickle"; static const char __pyx_k_reduce[] = "__reduce__"; static const char __pyx_k_struct[] = "struct"; static const char __pyx_k_unpack[] = "unpack"; static const char __pyx_k_update[] = "update"; static const char __pyx_k_TILING1[] = "TILING1"; static const char __pyx_k_TILING2[] = "TILING2"; static const char __pyx_k_TILING5[] = "TILING5"; static const char __pyx_k_TILING8[] = "TILING8"; static const char __pyx_k_TILING9[] = "TILING9"; static const char __pyx_k_arrays2[] = "arrays2"; static const char __pyx_k_classic[] = "classic"; static const char __pyx_k_faces_2[] = "faces_"; static const char __pyx_k_float32[] = "float32"; static const char __pyx_k_fortran[] = "fortran"; static const char __pyx_k_memview[] = "memview"; static const char __pyx_k_no_mask[] = "no_mask"; static const char __pyx_k_spacing[] = "spacing"; static const char __pyx_k_Ellipsis[] = "Ellipsis"; static const char __pyx_k_Nx_bound[] = "Nx_bound"; static const char __pyx_k_Ny_bound[] = "Ny_bound"; static const char __pyx_k_Nz_bound[] = "Nz_bound"; static const char __pyx_k_TILING11[] = "TILING11"; static const char __pyx_k_TILING14[] = "TILING14"; static const char __pyx_k_base_vec[] = "base_vec"; static const char __pyx_k_faces_ok[] = "faces_ok"; static const char __pyx_k_getstate[] = "__getstate__"; static const char __pyx_k_isovalue[] = "isovalue"; static const char __pyx_k_itemsize[] = "itemsize"; static const char __pyx_k_pyx_type[] = "__pyx_type"; static const char __pyx_k_setstate[] = "__setstate__"; static const char __pyx_k_vertices[] = "vertices"; static const char __pyx_k_EDGESRELX[] = "EDGESRELX"; static const char __pyx_k_EDGESRELY[] = "EDGESRELY"; static const char __pyx_k_EDGESRELZ[] = "EDGESRELZ"; static const char __pyx_k_TILING3_1[] = "TILING3_1"; static const char __pyx_k_TILING3_2[] = "TILING3_2"; static const char __pyx_k_TILING4_1[] = "TILING4_1"; static const char __pyx_k_TILING4_2[] = "TILING4_2"; static const char __pyx_k_TILING6_2[] = "TILING6_2"; static const char __pyx_k_TILING7_1[] = "TILING7_1"; static const char __pyx_k_TILING7_2[] = "TILING7_2"; static const char __pyx_k_TILING7_3[] = "TILING7_3"; static const char __pyx_k_TypeError[] = "TypeError"; static const char __pyx_k_enumerate[] = "enumerate"; static const char __pyx_k_get_faces[] = "get_faces"; static const char __pyx_k_pyx_state[] = "__pyx_state"; static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; static const char __pyx_k_subconfig[] = "subconfig"; static const char __pyx_k_vertices2[] = "vertices2"; static const char __pyx_k_IndexError[] = "IndexError"; static const char __pyx_k_TILING10_2[] = "TILING10_2"; static const char __pyx_k_TILING12_2[] = "TILING12_2"; static const char __pyx_k_TILING13_1[] = "TILING13_1"; static const char __pyx_k_TILING13_2[] = "TILING13_2"; static const char __pyx_k_TILING13_3[] = "TILING13_3"; static const char __pyx_k_TILING13_4[] = "TILING13_4"; static const char __pyx_k_ValueError[] = "ValueError"; static const char __pyx_k_faces_ok_2[] = "faces_ok_"; static const char __pyx_k_get_values[] = "get_values"; static const char __pyx_k_pyx_result[] = "__pyx_result"; static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; static const char __pyx_k_vertices_2[] = "vertices_"; static const char __pyx_k_voxel_size[] = "voxel_size"; static const char __pyx_k_ImportError[] = "ImportError"; static const char __pyx_k_LutProvider[] = "LutProvider"; static const char __pyx_k_MemoryError[] = "MemoryError"; static const char __pyx_k_PickleError[] = "PickleError"; static const char __pyx_k_SUBCONFIG13[] = "SUBCONFIG13"; static const char __pyx_k_TILING6_1_1[] = "TILING6_1_1"; static const char __pyx_k_TILING6_1_2[] = "TILING6_1_2"; static const char __pyx_k_TILING7_4_1[] = "TILING7_4_1"; static const char __pyx_k_TILING7_4_2[] = "TILING7_4_2"; static const char __pyx_k_get_normals[] = "get_normals"; static const char __pyx_k_vertices_ok[] = "vertices_ok"; static const char __pyx_k_CASESCLASSIC[] = "CASESCLASSIC"; static const char __pyx_k_TILING10_1_1[] = "TILING10_1_1"; static const char __pyx_k_TILING10_1_2[] = "TILING10_1_2"; static const char __pyx_k_TILING10_2_2[] = "TILING10_2_"; static const char __pyx_k_TILING12_1_1[] = "TILING12_1_1"; static const char __pyx_k_TILING12_1_2[] = "TILING12_1_2"; static const char __pyx_k_TILING12_2_2[] = "TILING12_2_"; static const char __pyx_k_TILING13_1_2[] = "TILING13_1_"; static const char __pyx_k_TILING13_2_2[] = "TILING13_2_"; static const char __pyx_k_TILING13_3_2[] = "TILING13_3_"; static const char __pyx_k_TILING13_5_1[] = "TILING13_5_1"; static const char __pyx_k_TILING13_5_2[] = "TILING13_5_2"; static const char __pyx_k_avg_cube_val[] = "avg_cube_val"; static const char __pyx_k_get_vertices[] = "get_vertices"; static const char __pyx_k_max_cube_val[] = "max_cube_val"; static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; static const char __pyx_k_stringsource[] = "stringsource"; static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; static const char __pyx_k_vertices_map0[] = "vertices_map0"; static const char __pyx_k_vertices_map1[] = "vertices_map1"; static const char __pyx_k_vertices_map2[] = "vertices_map2"; static const char __pyx_k_Invalid_edge_i[] = "Invalid edge %i."; static const char __pyx_k_TILING10_1_1_2[] = "TILING10_1_1_"; static const char __pyx_k_TILING12_1_1_2[] = "TILING12_1_1_"; static const char __pyx_k_marching_cubes[] = "marching_cubes"; static const char __pyx_k_View_MemoryView[] = "View.MemoryView"; static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError"; static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; static const char __pyx_k_vertices_map1_2[] = "vertices_map1_"; static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum"; static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; static const char __pyx_k_marching_cubes_udf[] = "marching_cubes_udf"; static const char __pyx_k_strided_and_direct[] = ""; static const char __pyx_k_strided_and_indirect[] = ""; static const char __pyx_k_contiguous_and_direct[] = ""; static const char __pyx_k_MemoryView_of_r_object[] = ""; static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; static const char __pyx_k_contiguous_and_indirect[] = ""; static const char __pyx_k_remove_degenerate_faces[] = "remove_degenerate_faces"; static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; static const char __pyx_k_Invalid_ambiguous_case_i[] = "Invalid ambiguous case %i."; static const char __pyx_k_pyx_unpickle_LutProvider[] = "__pyx_unpickle_LutProvider"; static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; static const char __pyx_k_marching_cubes_lewiner_cy[] = "_marching_cubes_lewiner_cy"; static const char __pyx_k_inwards_facing_normals_ref[] = "inwards_facing_normals_ref"; static const char __pyx_k_inwards_facing_normals_bool[] = "inwards_facing_normals_bool"; static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; static const char __pyx_k_marching_cubes_lewiner_cy_pyx[] = "_marching_cubes_lewiner_cy.pyx"; static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static const char __pyx_k_strided_and_direct_or_indirect[] = ""; static const char __pyx_k_This_is_an_implementation_of_th[] = "\nThis is an implementation of the marching cubes algorithm proposed in:\n\nEfficient implementation of Marching Cubes' cases with topological guarantees.\nThomas Lewiner, Helio Lopes, Antonio Wilson Vieira and Geovan Tavares.\nJournal of Graphics Tools 8(2): pp. 1-15 (december 2003)\n\nThis algorithm has the advantage that it provides topologically correct\nresults, and the algorithms implementation is relatively simple. Most\nof the magic is in the lookup tables, which are provided as open source.\n\nOriginally implemented in C++ by Thomas Lewiner in 2002, ported to Cython\nby Almar Klein in 2012. Adapted for scikit-image in 2016.\n\n"; static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; static const char __pyx_k_Incompatible_checksums_0x_x_vs_0[] = "Incompatible checksums (0x%x vs (0x3035ec8, 0x4a4e1b2, 0x53f5fc5) = (CASES, CASESCLASSIC, EDGESRELX, EDGESRELY, EDGESRELZ, SUBCONFIG13, TEST10, TEST12, TEST13, TEST3, TEST4, TEST6, TEST7, TILING1, TILING10_1_1, TILING10_1_1_, TILING10_1_2, TILING10_2, TILING10_2_, TILING11, TILING12_1_1, TILING12_1_1_, TILING12_1_2, TILING12_2, TILING12_2_, TILING13_1, TILING13_1_, TILING13_2, TILING13_2_, TILING13_3, TILING13_3_, TILING13_4, TILING13_5_1, TILING13_5_2, TILING14, TILING2, TILING3_1, TILING3_2, TILING4_1, TILING4_2, TILING5, TILING6_1_1, TILING6_1_2, TILING6_2, TILING7_1, TILING7_2, TILING7_3, TILING7_4_1, TILING7_4_2, TILING8, TILING9))"; static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; static const char __pyx_k_Marching_Cubes_Impossible_case_1[] = "Marching Cubes: Impossible case 13?"; static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; static const char __pyx_k_Incompatible_checksums_0x_x_vs_0_2[] = "Incompatible checksums (0x%x vs (0xb068931, 0x82a3537, 0x6ae9995) = (name))"; static PyObject *__pyx_n_s_ASCII; static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; static PyObject *__pyx_n_s_CASES; static PyObject *__pyx_n_s_CASESCLASSIC; static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; static PyObject *__pyx_kp_s_Cannot_assign_to_read_only_memor; static PyObject *__pyx_kp_s_Cannot_create_writable_memory_vi; static PyObject *__pyx_kp_s_Cannot_index_with_type_s; static PyObject *__pyx_n_s_Cell; static PyObject *__pyx_n_s_EDGESRELX; static PyObject *__pyx_n_s_EDGESRELY; static PyObject *__pyx_n_s_EDGESRELZ; static PyObject *__pyx_n_s_Ellipsis; static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; static PyObject *__pyx_n_s_ImportError; static PyObject *__pyx_kp_s_Incompatible_checksums_0x_x_vs_0; static PyObject *__pyx_kp_s_Incompatible_checksums_0x_x_vs_0_2; static PyObject *__pyx_n_s_IndexError; static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; static PyObject *__pyx_kp_s_Invalid_ambiguous_case_i; static PyObject *__pyx_kp_s_Invalid_edge_i; static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; static PyObject *__pyx_n_s_Lut; static PyObject *__pyx_n_s_LutProvider; static PyObject *__pyx_kp_s_Marching_Cubes_Impossible_case_1; static PyObject *__pyx_n_s_MemoryError; static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; static PyObject *__pyx_kp_s_MemoryView_of_r_object; static PyObject *__pyx_n_s_Nx; static PyObject *__pyx_n_s_Nx_bound; static PyObject *__pyx_n_s_Ny; static PyObject *__pyx_n_s_Ny_bound; static PyObject *__pyx_n_s_Nz; static PyObject *__pyx_n_s_Nz_bound; static PyObject *__pyx_n_b_O; static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_PickleError; static PyObject *__pyx_n_s_SUBCONFIG13; static PyObject *__pyx_n_s_TEST10; static PyObject *__pyx_n_s_TEST12; static PyObject *__pyx_n_s_TEST13; static PyObject *__pyx_n_s_TEST3; static PyObject *__pyx_n_s_TEST4; static PyObject *__pyx_n_s_TEST6; static PyObject *__pyx_n_s_TEST7; static PyObject *__pyx_n_s_TILING1; static PyObject *__pyx_n_s_TILING10_1_1; static PyObject *__pyx_n_s_TILING10_1_1_2; static PyObject *__pyx_n_s_TILING10_1_2; static PyObject *__pyx_n_s_TILING10_2; static PyObject *__pyx_n_s_TILING10_2_2; static PyObject *__pyx_n_s_TILING11; static PyObject *__pyx_n_s_TILING12_1_1; static PyObject *__pyx_n_s_TILING12_1_1_2; static PyObject *__pyx_n_s_TILING12_1_2; static PyObject *__pyx_n_s_TILING12_2; static PyObject *__pyx_n_s_TILING12_2_2; static PyObject *__pyx_n_s_TILING13_1; static PyObject *__pyx_n_s_TILING13_1_2; static PyObject *__pyx_n_s_TILING13_2; static PyObject *__pyx_n_s_TILING13_2_2; static PyObject *__pyx_n_s_TILING13_3; static PyObject *__pyx_n_s_TILING13_3_2; static PyObject *__pyx_n_s_TILING13_4; static PyObject *__pyx_n_s_TILING13_5_1; static PyObject *__pyx_n_s_TILING13_5_2; static PyObject *__pyx_n_s_TILING14; static PyObject *__pyx_n_s_TILING2; static PyObject *__pyx_n_s_TILING3_1; static PyObject *__pyx_n_s_TILING3_2; static PyObject *__pyx_n_s_TILING4_1; static PyObject *__pyx_n_s_TILING4_2; static PyObject *__pyx_n_s_TILING5; static PyObject *__pyx_n_s_TILING6_1_1; static PyObject *__pyx_n_s_TILING6_1_2; static PyObject *__pyx_n_s_TILING6_2; static PyObject *__pyx_n_s_TILING7_1; static PyObject *__pyx_n_s_TILING7_2; static PyObject *__pyx_n_s_TILING7_3; static PyObject *__pyx_n_s_TILING7_4_1; static PyObject *__pyx_n_s_TILING7_4_2; static PyObject *__pyx_n_s_TILING8; static PyObject *__pyx_n_s_TILING9; static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_n_s_View_MemoryView; static PyObject *__pyx_n_s_allocate_buffer; static PyObject *__pyx_n_s_arange; static PyObject *__pyx_n_s_arr; static PyObject *__pyx_n_s_array; static PyObject *__pyx_n_s_arrays; static PyObject *__pyx_n_s_arrays2; static PyObject *__pyx_n_s_avg_cube_val; static PyObject *__pyx_n_s_base; static PyObject *__pyx_n_s_base_vec; static PyObject *__pyx_n_s_c; static PyObject *__pyx_n_u_c; static PyObject *__pyx_n_s_case; static PyObject *__pyx_n_s_cell; static PyObject *__pyx_n_s_class; static PyObject *__pyx_n_s_classic; static PyObject *__pyx_n_s_cline_in_traceback; static PyObject *__pyx_n_s_config; static PyObject *__pyx_kp_s_contiguous_and_direct; static PyObject *__pyx_kp_s_contiguous_and_indirect; static PyObject *__pyx_n_s_copy; static PyObject *__pyx_n_s_cumsum; static PyObject *__pyx_n_s_dict; static PyObject *__pyx_n_s_dtype; static PyObject *__pyx_n_s_dtype_is_object; static PyObject *__pyx_n_s_empty; static PyObject *__pyx_n_s_encode; static PyObject *__pyx_n_s_end; static PyObject *__pyx_n_s_enumerate; static PyObject *__pyx_n_s_error; static PyObject *__pyx_n_s_faces; static PyObject *__pyx_n_s_faces2; static PyObject *__pyx_n_s_faces_2; static PyObject *__pyx_n_s_faces_ok; static PyObject *__pyx_n_s_faces_ok_2; static PyObject *__pyx_n_s_file; static PyObject *__pyx_n_s_flags; static PyObject *__pyx_n_s_float32; static PyObject *__pyx_n_s_format; static PyObject *__pyx_n_s_fortran; static PyObject *__pyx_n_u_fortran; static PyObject *__pyx_n_s_get_faces; static PyObject *__pyx_n_s_get_normals; static PyObject *__pyx_n_s_get_values; static PyObject *__pyx_n_s_get_vertices; static PyObject *__pyx_n_s_getstate; static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; static PyObject *__pyx_n_s_grads; static PyObject *__pyx_n_s_i1; static PyObject *__pyx_n_s_i2; static PyObject *__pyx_n_s_i3; static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_im; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_int32; static PyObject *__pyx_n_s_inwards_facing_normals_bool; static PyObject *__pyx_n_s_inwards_facing_normals_ref; static PyObject *__pyx_n_s_isovalue; static PyObject *__pyx_n_s_itemsize; static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; static PyObject *__pyx_n_s_j; static PyObject *__pyx_n_s_luts; static PyObject *__pyx_n_s_main; static PyObject *__pyx_n_s_marching_cubes; static PyObject *__pyx_n_s_marching_cubes_lewiner_cy; static PyObject *__pyx_kp_s_marching_cubes_lewiner_cy_pyx; static PyObject *__pyx_n_s_marching_cubes_udf; static PyObject *__pyx_n_s_mask; static PyObject *__pyx_n_s_max_cube_val; static PyObject *__pyx_n_s_memview; static PyObject *__pyx_n_s_mode; static PyObject *__pyx_n_s_name; static PyObject *__pyx_n_s_name_2; static PyObject *__pyx_n_s_ndim; static PyObject *__pyx_n_s_new; static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; static PyObject *__pyx_n_s_no_mask; static PyObject *__pyx_n_s_np; static PyObject *__pyx_n_s_nt; static PyObject *__pyx_n_s_numpy; static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to; static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor; static PyObject *__pyx_n_s_nx; static PyObject *__pyx_n_s_ny; static PyObject *__pyx_n_s_nz; static PyObject *__pyx_n_s_obj; static PyObject *__pyx_n_s_ones; static PyObject *__pyx_n_s_pack; static PyObject *__pyx_n_s_pickle; static PyObject *__pyx_n_s_print; static PyObject *__pyx_n_s_pyx_PickleError; static PyObject *__pyx_n_s_pyx_checksum; static PyObject *__pyx_n_s_pyx_getbuffer; static PyObject *__pyx_n_s_pyx_result; static PyObject *__pyx_n_s_pyx_state; static PyObject *__pyx_n_s_pyx_type; static PyObject *__pyx_n_s_pyx_unpickle_Enum; static PyObject *__pyx_n_s_pyx_unpickle_LutProvider; static PyObject *__pyx_n_s_pyx_vtable; static PyObject *__pyx_n_s_range; static PyObject *__pyx_n_s_ravel; static PyObject *__pyx_n_s_reduce; static PyObject *__pyx_n_s_reduce_cython; static PyObject *__pyx_n_s_reduce_ex; static PyObject *__pyx_n_s_remove_degenerate_faces; static PyObject *__pyx_n_s_setstate; static PyObject *__pyx_n_s_setstate_cython; static PyObject *__pyx_n_s_shape; static PyObject *__pyx_n_s_size; static PyObject *__pyx_n_s_spacing; static PyObject *__pyx_n_s_st; static PyObject *__pyx_n_s_start; static PyObject *__pyx_n_s_step; static PyObject *__pyx_n_s_stop; static PyObject *__pyx_kp_s_strided_and_direct; static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; static PyObject *__pyx_kp_s_strided_and_indirect; static PyObject *__pyx_kp_s_stringsource; static PyObject *__pyx_n_s_struct; static PyObject *__pyx_n_s_subconfig; static PyObject *__pyx_n_s_test; static PyObject *__pyx_kp_s_unable_to_allocate_array_data; static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; static PyObject *__pyx_n_s_unpack; static PyObject *__pyx_n_s_update; static PyObject *__pyx_n_s_v1; static PyObject *__pyx_n_s_v2; static PyObject *__pyx_n_s_v3; static PyObject *__pyx_n_s_vertices; static PyObject *__pyx_n_s_vertices2; static PyObject *__pyx_n_s_vertices_2; static PyObject *__pyx_n_s_vertices_map0; static PyObject *__pyx_n_s_vertices_map1; static PyObject *__pyx_n_s_vertices_map1_2; static PyObject *__pyx_n_s_vertices_map2; static PyObject *__pyx_n_s_vertices_ok; static PyObject *__pyx_n_s_voxel_size; static PyObject *__pyx_n_s_x; static PyObject *__pyx_n_s_x_st; static PyObject *__pyx_n_s_y; static PyObject *__pyx_n_s_y_st; static PyObject *__pyx_n_s_z; static PyObject *__pyx_n_s_z_st; static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_remove_degenerate_faces(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_vertices, PyObject *__pyx_v_faces, PyObject *__pyx_v_arrays); /* proto */ static int __pyx_pf_26_marching_cubes_lewiner_cy_4Cell___init__(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *__pyx_v_luts, int __pyx_v_nx, int __pyx_v_ny, int __pyx_v_nz); /* proto */ static int __pyx_pf_26_marching_cubes_lewiner_cy_4Cell_2__cinit__(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto */ static void __pyx_pf_26_marching_cubes_lewiner_cy_4Cell_4__dealloc__(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_4Cell_6get_vertices(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_4Cell_8get_normals(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_4Cell_10get_faces(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_4Cell_12get_values(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_4Cell_14__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_4Cell_16__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ static int __pyx_pf_26_marching_cubes_lewiner_cy_3Lut___init__(struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_self, PyObject *__pyx_v_array); /* proto */ static int __pyx_pf_26_marching_cubes_lewiner_cy_3Lut_2__cinit__(struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_self); /* proto */ static void __pyx_pf_26_marching_cubes_lewiner_cy_3Lut_4__dealloc__(struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_3Lut_6__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_3Lut_8__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ static int __pyx_pf_26_marching_cubes_lewiner_cy_11LutProvider___init__(struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *__pyx_v_self, PyObject *__pyx_v_EDGESRELX, PyObject *__pyx_v_EDGESRELY, PyObject *__pyx_v_EDGESRELZ, PyObject *__pyx_v_CASESCLASSIC, PyObject *__pyx_v_CASES, PyObject *__pyx_v_TILING1, PyObject *__pyx_v_TILING2, PyObject *__pyx_v_TILING3_1, PyObject *__pyx_v_TILING3_2, PyObject *__pyx_v_TILING4_1, PyObject *__pyx_v_TILING4_2, PyObject *__pyx_v_TILING5, PyObject *__pyx_v_TILING6_1_1, PyObject *__pyx_v_TILING6_1_2, PyObject *__pyx_v_TILING6_2, PyObject *__pyx_v_TILING7_1, PyObject *__pyx_v_TILING7_2, PyObject *__pyx_v_TILING7_3, PyObject *__pyx_v_TILING7_4_1, PyObject *__pyx_v_TILING7_4_2, PyObject *__pyx_v_TILING8, PyObject *__pyx_v_TILING9, PyObject *__pyx_v_TILING10_1_1, PyObject *__pyx_v_TILING10_1_1_, PyObject *__pyx_v_TILING10_1_2, PyObject *__pyx_v_TILING10_2, PyObject *__pyx_v_TILING10_2_, PyObject *__pyx_v_TILING11, PyObject *__pyx_v_TILING12_1_1, PyObject *__pyx_v_TILING12_1_1_, PyObject *__pyx_v_TILING12_1_2, PyObject *__pyx_v_TILING12_2, PyObject *__pyx_v_TILING12_2_, PyObject *__pyx_v_TILING13_1, PyObject *__pyx_v_TILING13_1_, PyObject *__pyx_v_TILING13_2, PyObject *__pyx_v_TILING13_2_, PyObject *__pyx_v_TILING13_3, PyObject *__pyx_v_TILING13_3_, PyObject *__pyx_v_TILING13_4, PyObject *__pyx_v_TILING13_5_1, PyObject *__pyx_v_TILING13_5_2, PyObject *__pyx_v_TILING14, PyObject *__pyx_v_TEST3, PyObject *__pyx_v_TEST4, PyObject *__pyx_v_TEST6, PyObject *__pyx_v_TEST7, PyObject *__pyx_v_TEST10, PyObject *__pyx_v_TEST12, PyObject *__pyx_v_TEST13, PyObject *__pyx_v_SUBCONFIG13); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_11LutProvider_2__reduce_cython__(struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_11LutProvider_4__setstate_cython__(struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_2marching_cubes(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_im, double __pyx_v_isovalue, struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *__pyx_v_luts, int __pyx_v_st, int __pyx_v_classic, PyArrayObject *__pyx_v_mask); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_4marching_cubes_udf(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_im, __Pyx_memviewslice __pyx_v_grads, struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *__pyx_v_luts, int __pyx_v_st, CYTHON_UNUSED int __pyx_v_classic, PyArrayObject *__pyx_v_mask); /* proto */ static PyObject *__pyx_pf_26_marching_cubes_lewiner_cy_6__pyx_unpickle_LutProvider(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); 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/* "_marching_cubes_lewiner_cy.pyx":192 * self.faceLayer2 = malloc(self.nx*self.ny*4 * sizeof(int)) * * if (self.faceLayer1 is NULL or self.faceLayer2 is NULL or # <<<<<<<<<<<<<< * self.vv is NULL or self.vg is NULL or self._vertices is NULL or * self._normals is NULL or self._values is NULL or */ __pyx_t_5 = ((__pyx_v_self->faceLayer1 == NULL) != 0); if (!__pyx_t_5) { } else { __pyx_t_4 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = ((__pyx_v_self->faceLayer2 == NULL) != 0); if (!__pyx_t_5) { } else { __pyx_t_4 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } /* "_marching_cubes_lewiner_cy.pyx":193 * * if (self.faceLayer1 is NULL or self.faceLayer2 is NULL or * self.vv is NULL or self.vg is NULL or self._vertices is NULL or # <<<<<<<<<<<<<< * self._normals is NULL or self._values is NULL or * self._faces is NULL): */ __pyx_t_5 = ((__pyx_v_self->vv == NULL) != 0); if (!__pyx_t_5) { } else { __pyx_t_4 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = ((__pyx_v_self->vg == NULL) != 0); 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__pyx_t_4 = __pyx_t_5; __pyx_L4_bool_binop_done:; /* "_marching_cubes_lewiner_cy.pyx":192 * self.faceLayer2 = malloc(self.nx*self.ny*4 * sizeof(int)) * * if (self.faceLayer1 is NULL or self.faceLayer2 is NULL or # <<<<<<<<<<<<<< * self.vv is NULL or self.vg is NULL or self._vertices is NULL or * self._normals is NULL or self._values is NULL or */ if (unlikely(__pyx_t_4)) { /* "_marching_cubes_lewiner_cy.pyx":196 * self._normals is NULL or self._values is NULL or * self._faces is NULL): * raise MemoryError() # <<<<<<<<<<<<<< * * cdef int i */ PyErr_NoMemory(); __PYX_ERR(0, 196, __pyx_L1_error) /* "_marching_cubes_lewiner_cy.pyx":192 * self.faceLayer2 = malloc(self.nx*self.ny*4 * sizeof(int)) * * if (self.faceLayer1 is NULL or self.faceLayer2 is NULL or # <<<<<<<<<<<<<< * self.vv is NULL or self.vg is NULL or self._vertices is NULL or * self._normals is NULL or self._values is NULL or */ } /* "_marching_cubes_lewiner_cy.pyx":199 * * cdef int i * for i in range(self.nx*self.ny*4): # <<<<<<<<<<<<<< * self.faceLayer1[i] = -1 * self.faceLayer2[i] = -1 */ __pyx_t_6 = ((__pyx_v_self->nx * __pyx_v_self->ny) * 4); 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/* "_marching_cubes_lewiner_cy.pyx":253 * cdef float *newVertices = malloc(newMaxCount*3 * sizeof(float)) * cdef float *newNormals = malloc(newMaxCount*3 * sizeof(float)) * cdef float *newValues = malloc(newMaxCount * sizeof(float)) # <<<<<<<<<<<<<< * if newVertices is NULL or newNormals is NULL or newValues is NULL: * free(newVertices) */ __pyx_v_newValues = ((float *)malloc((__pyx_v_newMaxCount * (sizeof(float))))); /* "_marching_cubes_lewiner_cy.pyx":254 * cdef float *newNormals = malloc(newMaxCount*3 * sizeof(float)) * cdef float *newValues = malloc(newMaxCount * sizeof(float)) * if newVertices is NULL or newNormals is NULL or newValues is NULL: # <<<<<<<<<<<<<< * free(newVertices) * free(newNormals) */ __pyx_t_2 = ((__pyx_v_newVertices == NULL) != 0); if (!__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = ((__pyx_v_newNormals == NULL) != 0); if (!__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = ((__pyx_v_newValues == NULL) != 0); 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__pyx_t_4 = __pyx_t_3; for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; /* "_marching_cubes_lewiner_cy.pyx":267 * # Copy * for i in range(self._vertexCount): * newValues[i] = self._values[i] # <<<<<<<<<<<<<< * for j in range(3): * newVertices[i*3+j] = self._vertices[i*3+j] */ (__pyx_v_newValues[__pyx_v_i]) = (__pyx_v_self->_values[__pyx_v_i]); /* "_marching_cubes_lewiner_cy.pyx":268 * for i in range(self._vertexCount): * newValues[i] = self._values[i] * for j in range(3): # <<<<<<<<<<<<<< * newVertices[i*3+j] = self._vertices[i*3+j] * newNormals[i*3+j] = self._normals[i*3+j] */ for (__pyx_t_6 = 0; __pyx_t_6 < 3; __pyx_t_6+=1) { __pyx_v_j = __pyx_t_6; /* "_marching_cubes_lewiner_cy.pyx":269 * newValues[i] = self._values[i] * for j in range(3): * newVertices[i*3+j] = self._vertices[i*3+j] # <<<<<<<<<<<<<< * newNormals[i*3+j] = self._normals[i*3+j] * # Apply */ (__pyx_v_newVertices[((__pyx_v_i * 3) + __pyx_v_j)]) = (__pyx_v_self->_vertices[((__pyx_v_i * 3) + __pyx_v_j)]); /* "_marching_cubes_lewiner_cy.pyx":270 * for j in range(3): * newVertices[i*3+j] = self._vertices[i*3+j] * newNormals[i*3+j] = self._normals[i*3+j] # <<<<<<<<<<<<<< * # Apply * free(self._vertices); self._vertices = newVertices */ (__pyx_v_newNormals[((__pyx_v_i * 3) + __pyx_v_j)]) = (__pyx_v_self->_normals[((__pyx_v_i * 3) + __pyx_v_j)]); } } /* "_marching_cubes_lewiner_cy.pyx":272 * newNormals[i*3+j] = self._normals[i*3+j] * # Apply * free(self._vertices); self._vertices = newVertices # <<<<<<<<<<<<<< * free(self._normals); self._normals = newNormals * free(self._values); self._values = newValues */ free(__pyx_v_self->_vertices); __pyx_v_self->_vertices = __pyx_v_newVertices; /* "_marching_cubes_lewiner_cy.pyx":273 * # Apply * free(self._vertices); self._vertices = newVertices * free(self._normals); self._normals = newNormals # <<<<<<<<<<<<<< * free(self._values); self._values = newValues * self._vertexMaxCount = newMaxCount */ free(__pyx_v_self->_normals); __pyx_v_self->_normals = __pyx_v_newNormals; 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} /* "_marching_cubes_lewiner_cy.pyx":444 * if self.v5 > 0.0: index += 32 * if self.v6 > 0.0: index += 64 * if self.v7 > 0.0: index += 128 # <<<<<<<<<<<<<< * self.index = index * */ __pyx_t_1 = ((__pyx_v_self->v7 > 0.0) != 0); if (__pyx_t_1) { __pyx_v_index = (__pyx_v_index + 0x80); } /* "_marching_cubes_lewiner_cy.pyx":445 * if self.v6 > 0.0: index += 64 * if self.v7 > 0.0: index += 128 * self.index = index # <<<<<<<<<<<<<< * * # Reset c12 */ __pyx_v_self->index = __pyx_v_index; /* "_marching_cubes_lewiner_cy.pyx":448 * * # Reset c12 * self.v12_calculated = 0 # <<<<<<<<<<<<<< * * */ __pyx_v_self->v12_calculated = 0; /* "_marching_cubes_lewiner_cy.pyx":406 * * * cdef void set_cube(self, double isovalue, int x, int y, int z, int step, # <<<<<<<<<<<<<< * double v0, double v1, double v2, double v3, * double v4, double v5, double v6, double v7): */ /* function exit code */ __Pyx_RefNannyFinishContext(); } /* "_marching_cubes_lewiner_cy.pyx":451 * * * cdef void add_triangles(self, Lut lut, int lutIndex, int nt): # <<<<<<<<<<<<<< * """ Add triangles. * */ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_add_triangles(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_lut, int __pyx_v_lutIndex, int __pyx_v_nt) { int __pyx_v_i; 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/* "_marching_cubes_lewiner_cy.pyx":470 * for j in range(3): * # Get two sides for each element in this vertex * vi = lut.get2(lutIndex, i*3+j) # <<<<<<<<<<<<<< * self._add_face_from_edge_index(vi) * */ __pyx_v_vi = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_lut->__pyx_vtab)->get2(__pyx_v_lut, __pyx_v_lutIndex, ((__pyx_v_i * 3) + __pyx_v_j)); /* "_marching_cubes_lewiner_cy.pyx":471 * # Get two sides for each element in this vertex * vi = lut.get2(lutIndex, i*3+j) * self._add_face_from_edge_index(vi) # <<<<<<<<<<<<<< * * */ ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->_add_face_from_edge_index(__pyx_v_self, __pyx_v_vi); } } /* "_marching_cubes_lewiner_cy.pyx":451 * * * cdef void add_triangles(self, Lut lut, int lutIndex, int nt): # <<<<<<<<<<<<<< * """ Add triangles. * */ /* function exit code */ __Pyx_RefNannyFinishContext(); } /* "_marching_cubes_lewiner_cy.pyx":474 * * * cdef void add_triangles2(self, Lut lut, int lutIndex, int lutIndex2, int nt): # <<<<<<<<<<<<<< * """ Same as add_triangles, except that now the geometry is in a LUT * with 3 dimensions, and an extra index is provided. */ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_add_triangles2(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *__pyx_v_lut, int __pyx_v_lutIndex, int __pyx_v_lutIndex2, int __pyx_v_nt) { int __pyx_v_i; 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/* "_marching_cubes_lewiner_cy.pyx":487 * for j in range(3): * # Get two sides for each element in this vertex * vi = lut.get3(lutIndex, lutIndex2, i*3+j) # <<<<<<<<<<<<<< * self._add_face_from_edge_index(vi) * */ __pyx_v_vi = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_lut->__pyx_vtab)->get3(__pyx_v_lut, __pyx_v_lutIndex, __pyx_v_lutIndex2, ((__pyx_v_i * 3) + __pyx_v_j)); /* "_marching_cubes_lewiner_cy.pyx":488 * # Get two sides for each element in this vertex * vi = lut.get3(lutIndex, lutIndex2, i*3+j) * self._add_face_from_edge_index(vi) # <<<<<<<<<<<<<< * * ## Used internally */ ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->_add_face_from_edge_index(__pyx_v_self, __pyx_v_vi); } } /* "_marching_cubes_lewiner_cy.pyx":474 * * * cdef void add_triangles2(self, Lut lut, int lutIndex, int lutIndex2, int nt): # <<<<<<<<<<<<<< * """ Same as add_triangles, except that now the geometry is in a LUT * with 3 dimensions, and an extra index is provided. */ /* function exit code */ __Pyx_RefNannyFinishContext(); 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/* "_marching_cubes_lewiner_cy.pyx":508 * * # Get index in the face layer and corresponding vertex number * indexInFaceLayer = self.get_index_in_facelayer(vi) # <<<<<<<<<<<<<< * indexInVertexArray = self.faceLayer[indexInFaceLayer] * */ __pyx_v_indexInFaceLayer = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->get_index_in_facelayer(__pyx_v_self, __pyx_v_vi); /* "_marching_cubes_lewiner_cy.pyx":509 * # Get index in the face layer and corresponding vertex number * indexInFaceLayer = self.get_index_in_facelayer(vi) * indexInVertexArray = self.faceLayer[indexInFaceLayer] # <<<<<<<<<<<<<< * * # If we have the center vertex, we have things pre-calculated, */ __pyx_v_indexInVertexArray = (__pyx_v_self->faceLayer[__pyx_v_indexInFaceLayer]); /* "_marching_cubes_lewiner_cy.pyx":516 * # or not. * * if vi == 12: # center vertex # <<<<<<<<<<<<<< * if self.v12_calculated == 0: * self.calculate_center_vertex() */ __pyx_t_1 = ((__pyx_v_vi == 12) != 0); if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":517 * * if vi == 12: # center vertex * if self.v12_calculated == 0: # <<<<<<<<<<<<<< * self.calculate_center_vertex() * if indexInVertexArray >= 0: */ __pyx_t_1 = ((__pyx_v_self->v12_calculated == 0) != 0); if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":518 * if vi == 12: # center vertex * if self.v12_calculated == 0: * self.calculate_center_vertex() # <<<<<<<<<<<<<< * if indexInVertexArray >= 0: * # Vertex already calculated, only need to add face and gradient */ ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->calculate_center_vertex(__pyx_v_self); /* "_marching_cubes_lewiner_cy.pyx":517 * * if vi == 12: # center vertex * if self.v12_calculated == 0: # <<<<<<<<<<<<<< * self.calculate_center_vertex() * if indexInVertexArray >= 0: */ } /* "_marching_cubes_lewiner_cy.pyx":519 * if self.v12_calculated == 0: * self.calculate_center_vertex() * if indexInVertexArray >= 0: # <<<<<<<<<<<<<< * # Vertex already calculated, only need to add face and gradient * self.add_face(indexInVertexArray) */ __pyx_t_1 = ((__pyx_v_indexInVertexArray >= 0) != 0); if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":521 * if indexInVertexArray >= 0: * # Vertex already calculated, only need to add face and gradient * self.add_face(indexInVertexArray) # <<<<<<<<<<<<<< * self.add_gradient(indexInVertexArray, self.v12_xg, self.v12_yg, self.v12_zg) * else: */ __pyx_t_2 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_face(__pyx_v_self, __pyx_v_indexInVertexArray); 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/* "_marching_cubes_lewiner_cy.pyx":527 * indexInVertexArray = self.add_vertex( self.v12_x, self.v12_y, self.v12_z) * # Update face layer * self.faceLayer[indexInFaceLayer] = indexInVertexArray # <<<<<<<<<<<<<< * # Add face and gradient * self.add_face(indexInVertexArray) */ (__pyx_v_self->faceLayer[__pyx_v_indexInFaceLayer]) = __pyx_v_indexInVertexArray; /* "_marching_cubes_lewiner_cy.pyx":529 * self.faceLayer[indexInFaceLayer] = indexInVertexArray * # Add face and gradient * self.add_face(indexInVertexArray) # <<<<<<<<<<<<<< * self.add_gradient(indexInVertexArray, self.v12_xg, self.v12_yg, self.v12_zg) * */ __pyx_t_2 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_face(__pyx_v_self, __pyx_v_indexInVertexArray); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 529, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; /* "_marching_cubes_lewiner_cy.pyx":530 * # Add face and gradient * self.add_face(indexInVertexArray) * self.add_gradient(indexInVertexArray, self.v12_xg, self.v12_yg, self.v12_zg) # <<<<<<<<<<<<<< * * else: */ ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_gradient(__pyx_v_self, __pyx_v_indexInVertexArray, __pyx_v_self->v12_xg, __pyx_v_self->v12_yg, __pyx_v_self->v12_zg); } __pyx_L5:; /* "_marching_cubes_lewiner_cy.pyx":516 * # or not. * * if vi == 12: # center vertex # <<<<<<<<<<<<<< * if self.v12_calculated == 0: * self.calculate_center_vertex() */ goto __pyx_L3; } /* "_marching_cubes_lewiner_cy.pyx":535 * * # Get relative edge indices for x, y and z * dx1, dx2 = self.luts.EDGESRELX.get2(vi,0), self.luts.EDGESRELX.get2(vi,1) # <<<<<<<<<<<<<< * dy1, dy2 = self.luts.EDGESRELY.get2(vi,0), self.luts.EDGESRELY.get2(vi,1) * dz1, dz2 = self.luts.EDGESRELZ.get2(vi,0), self.luts.EDGESRELZ.get2(vi,1) */ /*else*/ { __pyx_t_3 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_self->luts->EDGESRELX->__pyx_vtab)->get2(__pyx_v_self->luts->EDGESRELX, __pyx_v_vi, 0); __pyx_t_4 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_self->luts->EDGESRELX->__pyx_vtab)->get2(__pyx_v_self->luts->EDGESRELX, __pyx_v_vi, 1); __pyx_v_dx1 = __pyx_t_3; __pyx_v_dx2 = __pyx_t_4; /* "_marching_cubes_lewiner_cy.pyx":536 * # Get relative edge indices for x, y and z * dx1, dx2 = self.luts.EDGESRELX.get2(vi,0), self.luts.EDGESRELX.get2(vi,1) * dy1, dy2 = self.luts.EDGESRELY.get2(vi,0), self.luts.EDGESRELY.get2(vi,1) # <<<<<<<<<<<<<< * dz1, dz2 = self.luts.EDGESRELZ.get2(vi,0), self.luts.EDGESRELZ.get2(vi,1) * # Make two vertex indices */ __pyx_t_4 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_self->luts->EDGESRELY->__pyx_vtab)->get2(__pyx_v_self->luts->EDGESRELY, __pyx_v_vi, 0); __pyx_t_3 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_self->luts->EDGESRELY->__pyx_vtab)->get2(__pyx_v_self->luts->EDGESRELY, __pyx_v_vi, 1); __pyx_v_dy1 = __pyx_t_4; __pyx_v_dy2 = __pyx_t_3; /* "_marching_cubes_lewiner_cy.pyx":537 * dx1, dx2 = self.luts.EDGESRELX.get2(vi,0), self.luts.EDGESRELX.get2(vi,1) * dy1, dy2 = self.luts.EDGESRELY.get2(vi,0), self.luts.EDGESRELY.get2(vi,1) * dz1, dz2 = self.luts.EDGESRELZ.get2(vi,0), self.luts.EDGESRELZ.get2(vi,1) # <<<<<<<<<<<<<< * # Make two vertex indices * index1 = dz1*4 + dy1*2 + dx1 */ __pyx_t_3 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_self->luts->EDGESRELZ->__pyx_vtab)->get2(__pyx_v_self->luts->EDGESRELZ, __pyx_v_vi, 0); __pyx_t_4 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_self->luts->EDGESRELZ->__pyx_vtab)->get2(__pyx_v_self->luts->EDGESRELZ, __pyx_v_vi, 1); __pyx_v_dz1 = __pyx_t_3; __pyx_v_dz2 = __pyx_t_4; /* "_marching_cubes_lewiner_cy.pyx":539 * dz1, dz2 = self.luts.EDGESRELZ.get2(vi,0), self.luts.EDGESRELZ.get2(vi,1) * # Make two vertex indices * index1 = dz1*4 + dy1*2 + dx1 # <<<<<<<<<<<<<< * index2 = dz2*4 + dy2*2 + dx2 * # Define strength of both corners */ __pyx_v_index1 = (((__pyx_v_dz1 * 4) + (__pyx_v_dy1 * 2)) + __pyx_v_dx1); /* "_marching_cubes_lewiner_cy.pyx":540 * # Make two vertex indices * index1 = dz1*4 + dy1*2 + dx1 * index2 = dz2*4 + dy2*2 + dx2 # <<<<<<<<<<<<<< * # Define strength of both corners * tmpf1 = 1.0 / (FLT_EPSILON + dabs(self.vv[index1])) */ __pyx_v_index2 = (((__pyx_v_dz2 * 4) + (__pyx_v_dy2 * 2)) + __pyx_v_dx2); /* "_marching_cubes_lewiner_cy.pyx":542 * index2 = dz2*4 + dy2*2 + dx2 * # Define strength of both corners * tmpf1 = 1.0 / (FLT_EPSILON + dabs(self.vv[index1])) # <<<<<<<<<<<<<< * tmpf2 = 1.0 / (FLT_EPSILON + dabs(self.vv[index2])) * */ __pyx_v_tmpf1 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs((__pyx_v_self->vv[__pyx_v_index1])))); /* "_marching_cubes_lewiner_cy.pyx":543 * # Define strength of both corners * tmpf1 = 1.0 / (FLT_EPSILON + dabs(self.vv[index1])) * tmpf2 = 1.0 / (FLT_EPSILON + dabs(self.vv[index2])) # <<<<<<<<<<<<<< * * # print('indexInVertexArray', self.x, self.y, self.z, '-', vi, indexInVertexArray, indexInFaceLayer) */ __pyx_v_tmpf2 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs((__pyx_v_self->vv[__pyx_v_index2])))); /* "_marching_cubes_lewiner_cy.pyx":547 * # print('indexInVertexArray', self.x, self.y, self.z, '-', vi, indexInVertexArray, indexInFaceLayer) * * if indexInVertexArray >= 0: # <<<<<<<<<<<<<< * # Vertex already calculated, only need to add face and gradient * self.add_face(indexInVertexArray) */ __pyx_t_1 = ((__pyx_v_indexInVertexArray >= 0) != 0); if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":549 * if indexInVertexArray >= 0: * # Vertex already calculated, only need to add face and gradient * self.add_face(indexInVertexArray) # <<<<<<<<<<<<<< * self.add_gradient_from_index(indexInVertexArray, index1, tmpf1) * self.add_gradient_from_index(indexInVertexArray, index2, tmpf2) */ __pyx_t_2 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_face(__pyx_v_self, __pyx_v_indexInVertexArray); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 549, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; /* "_marching_cubes_lewiner_cy.pyx":550 * # Vertex already calculated, only need to add face and gradient * self.add_face(indexInVertexArray) * self.add_gradient_from_index(indexInVertexArray, index1, tmpf1) # <<<<<<<<<<<<<< * self.add_gradient_from_index(indexInVertexArray, index2, tmpf2) * */ ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_gradient_from_index(__pyx_v_self, __pyx_v_indexInVertexArray, __pyx_v_index1, __pyx_v_tmpf1); /* "_marching_cubes_lewiner_cy.pyx":551 * self.add_face(indexInVertexArray) * self.add_gradient_from_index(indexInVertexArray, index1, tmpf1) * self.add_gradient_from_index(indexInVertexArray, index2, tmpf2) # <<<<<<<<<<<<<< * * else: */ ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_gradient_from_index(__pyx_v_self, __pyx_v_indexInVertexArray, __pyx_v_index2, __pyx_v_tmpf2); /* "_marching_cubes_lewiner_cy.pyx":547 * # print('indexInVertexArray', self.x, self.y, self.z, '-', vi, indexInVertexArray, indexInFaceLayer) * * if indexInVertexArray >= 0: # <<<<<<<<<<<<<< * # Vertex already calculated, only need to add face and gradient * self.add_face(indexInVertexArray) */ goto __pyx_L6; } /* "_marching_cubes_lewiner_cy.pyx":555 * else: * # Interpolate by applying a kind of center-of-mass method * fx, fy, fz, ff = 0.0, 0.0, 0.0, 0.0 # <<<<<<<<<<<<<< * fx += dx1 * tmpf1; fy += dy1 * tmpf1; fz += dz1 * tmpf1; ff += tmpf1 * fx += dx2 * tmpf2; fy += dy2 * tmpf2; fz += dz2 * tmpf2; ff += tmpf2 */ /*else*/ { __pyx_t_5 = 0.0; __pyx_t_6 = 0.0; __pyx_t_7 = 0.0; __pyx_t_8 = 0.0; __pyx_v_fx = __pyx_t_5; __pyx_v_fy = __pyx_t_6; __pyx_v_fz = __pyx_t_7; __pyx_v_ff = __pyx_t_8; /* "_marching_cubes_lewiner_cy.pyx":556 * # Interpolate by applying a kind of center-of-mass method * fx, fy, fz, ff = 0.0, 0.0, 0.0, 0.0 * fx += dx1 * tmpf1; fy += dy1 * tmpf1; fz += dz1 * tmpf1; ff += tmpf1 # <<<<<<<<<<<<<< * fx += dx2 * tmpf2; fy += dy2 * tmpf2; fz += dz2 * tmpf2; ff += tmpf2 * */ __pyx_v_fx = (__pyx_v_fx + (((double)__pyx_v_dx1) * __pyx_v_tmpf1)); __pyx_v_fy = (__pyx_v_fy + (((double)__pyx_v_dy1) * __pyx_v_tmpf1)); __pyx_v_fz = (__pyx_v_fz + (((double)__pyx_v_dz1) * __pyx_v_tmpf1)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_tmpf1); /* "_marching_cubes_lewiner_cy.pyx":557 * fx, fy, fz, ff = 0.0, 0.0, 0.0, 0.0 * fx += dx1 * tmpf1; fy += dy1 * tmpf1; fz += dz1 * tmpf1; ff += tmpf1 * fx += dx2 * tmpf2; fy += dy2 * tmpf2; fz += dz2 * tmpf2; ff += tmpf2 # <<<<<<<<<<<<<< * * # Add vertex */ __pyx_v_fx = (__pyx_v_fx + (((double)__pyx_v_dx2) * __pyx_v_tmpf2)); __pyx_v_fy = (__pyx_v_fy + (((double)__pyx_v_dy2) * __pyx_v_tmpf2)); __pyx_v_fz = (__pyx_v_fz + (((double)__pyx_v_dz2) * __pyx_v_tmpf2)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_tmpf2); /* "_marching_cubes_lewiner_cy.pyx":560 * * # Add vertex * indexInVertexArray = self.add_vertex( # <<<<<<<<<<<<<< * self.x + stp*fx/ff, * self.y + stp*fy/ff, */ __pyx_v_indexInVertexArray = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_vertex(__pyx_v_self, (((double)__pyx_v_self->x) + ((__pyx_v_stp * __pyx_v_fx) / __pyx_v_ff)), (((double)__pyx_v_self->y) + ((__pyx_v_stp * __pyx_v_fy) / __pyx_v_ff)), (((double)__pyx_v_self->z) + ((__pyx_v_stp * __pyx_v_fz) / __pyx_v_ff))); /* "_marching_cubes_lewiner_cy.pyx":565 * self.z + stp*fz/ff ) * # Update face layer * self.faceLayer[indexInFaceLayer] = indexInVertexArray # <<<<<<<<<<<<<< * # Add face and gradient * self.add_face(indexInVertexArray) */ (__pyx_v_self->faceLayer[__pyx_v_indexInFaceLayer]) = __pyx_v_indexInVertexArray; /* "_marching_cubes_lewiner_cy.pyx":567 * self.faceLayer[indexInFaceLayer] = indexInVertexArray * # Add face and gradient * self.add_face(indexInVertexArray) # <<<<<<<<<<<<<< * self.add_gradient_from_index(indexInVertexArray, index1, tmpf1) * self.add_gradient_from_index(indexInVertexArray, index2, tmpf2) */ __pyx_t_2 = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_face(__pyx_v_self, __pyx_v_indexInVertexArray); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 567, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; /* "_marching_cubes_lewiner_cy.pyx":568 * # Add face and gradient * self.add_face(indexInVertexArray) * self.add_gradient_from_index(indexInVertexArray, index1, tmpf1) # <<<<<<<<<<<<<< * self.add_gradient_from_index(indexInVertexArray, index2, tmpf2) * */ ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_gradient_from_index(__pyx_v_self, __pyx_v_indexInVertexArray, __pyx_v_index1, __pyx_v_tmpf1); /* "_marching_cubes_lewiner_cy.pyx":569 * self.add_face(indexInVertexArray) * self.add_gradient_from_index(indexInVertexArray, index1, tmpf1) * self.add_gradient_from_index(indexInVertexArray, index2, tmpf2) # <<<<<<<<<<<<<< * * */ ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_self->__pyx_vtab)->add_gradient_from_index(__pyx_v_self, __pyx_v_indexInVertexArray, __pyx_v_index2, __pyx_v_tmpf2); } __pyx_L6:; } __pyx_L3:; /* "_marching_cubes_lewiner_cy.pyx":492 * ## Used internally * * cdef void _add_face_from_edge_index(self, int vi): # <<<<<<<<<<<<<< * """ Add one face from an edge index. Only adds a face if the * vertex already exists. Otherwise also adds a vertex and applies */ /* function exit code */ goto __pyx_L0; __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_2); __Pyx_WriteUnraisable("_marching_cubes_lewiner_cy.Cell._add_face_from_edge_index", __pyx_clineno, __pyx_lineno, __pyx_filename, 1, 0); __pyx_L0:; __Pyx_RefNannyFinishContext(); } /* "_marching_cubes_lewiner_cy.pyx":579 * * * cdef int get_index_in_facelayer(self, int vi): # <<<<<<<<<<<<<< * """ * Get the index of a vertex position, given the edge on which it lies. */ static int __pyx_f_26_marching_cubes_lewiner_cy_4Cell_get_index_in_facelayer(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self, int __pyx_v_vi) { int __pyx_v_i; int __pyx_v_j; CYTHON_UNUSED int __pyx_v_vi_; int *__pyx_v_faceLayer; int __pyx_r; __Pyx_RefNannyDeclarations int __pyx_t_1; int *__pyx_t_2; __Pyx_RefNannySetupContext("get_index_in_facelayer", 0); /* "_marching_cubes_lewiner_cy.pyx":608 * * # Init indices, both are corrected below * cdef int i = self.nx * self.y + self.x # Index of cube to get vertex at # <<<<<<<<<<<<<< * cdef int j = 0 # Vertex number for that cell * cdef int vi_ = vi */ __pyx_v_i = ((__pyx_v_self->nx * __pyx_v_self->y) + __pyx_v_self->x); /* "_marching_cubes_lewiner_cy.pyx":609 * # Init indices, both are corrected below * cdef int i = self.nx * self.y + self.x # Index of cube to get vertex at * cdef int j = 0 # Vertex number for that cell # <<<<<<<<<<<<<< * cdef int vi_ = vi * */ __pyx_v_j = 0; /* "_marching_cubes_lewiner_cy.pyx":610 * cdef int i = self.nx * self.y + self.x # Index of cube to get vertex at * cdef int j = 0 # Vertex number for that cell * cdef int vi_ = vi # <<<<<<<<<<<<<< * * cdef int *faceLayer */ __pyx_v_vi_ = __pyx_v_vi; /* "_marching_cubes_lewiner_cy.pyx":615 * * # Select either upper or lower half * if vi < 8: # <<<<<<<<<<<<<< * # 8 horizontal edges * if vi < 4: */ __pyx_t_1 = ((__pyx_v_vi < 8) != 0); if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":617 * if vi < 8: * # 8 horizontal edges * if vi < 4: # <<<<<<<<<<<<<< * faceLayer = self.faceLayer1 * else: */ __pyx_t_1 = ((__pyx_v_vi < 4) != 0); if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":618 * # 8 horizontal edges * if vi < 4: * faceLayer = self.faceLayer1 # <<<<<<<<<<<<<< * else: * vi -= 4 */ __pyx_t_2 = __pyx_v_self->faceLayer1; __pyx_v_faceLayer = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":617 * if vi < 8: * # 8 horizontal edges * if vi < 4: # <<<<<<<<<<<<<< * faceLayer = self.faceLayer1 * else: */ goto __pyx_L4; } /* "_marching_cubes_lewiner_cy.pyx":620 * faceLayer = self.faceLayer1 * else: * vi -= 4 # <<<<<<<<<<<<<< * faceLayer = self.faceLayer2 * */ /*else*/ { __pyx_v_vi = (__pyx_v_vi - 4); /* "_marching_cubes_lewiner_cy.pyx":621 * else: * vi -= 4 * faceLayer = self.faceLayer2 # <<<<<<<<<<<<<< * * # Calculate actual index based on edge */ __pyx_t_2 = __pyx_v_self->faceLayer2; __pyx_v_faceLayer = __pyx_t_2; } __pyx_L4:; /* "_marching_cubes_lewiner_cy.pyx":625 * # Calculate actual index based on edge * #if vi == 0: pass # no step * if vi == 1: # step in x # <<<<<<<<<<<<<< * i += self.step * j = 1 */ switch (__pyx_v_vi) { case 1: /* "_marching_cubes_lewiner_cy.pyx":626 * #if vi == 0: pass # no step * if vi == 1: # step in x * i += self.step # <<<<<<<<<<<<<< * j = 1 * elif vi == 2: # step in y */ __pyx_v_i = (__pyx_v_i + __pyx_v_self->step); /* "_marching_cubes_lewiner_cy.pyx":627 * if vi == 1: # step in x * i += self.step * j = 1 # <<<<<<<<<<<<<< * elif vi == 2: # step in y * i += self.nx * self.step */ __pyx_v_j = 1; /* "_marching_cubes_lewiner_cy.pyx":625 * # Calculate actual index based on edge * #if vi == 0: pass # no step * if vi == 1: # step in x # <<<<<<<<<<<<<< * i += self.step * j = 1 */ break; case 2: /* "_marching_cubes_lewiner_cy.pyx":629 * j = 1 * elif vi == 2: # step in y * i += self.nx * self.step # <<<<<<<<<<<<<< * elif vi == 3: # no step * j = 1 */ __pyx_v_i = (__pyx_v_i + (__pyx_v_self->nx * __pyx_v_self->step)); /* "_marching_cubes_lewiner_cy.pyx":628 * i += self.step * j = 1 * elif vi == 2: # step in y # <<<<<<<<<<<<<< * i += self.nx * self.step * elif vi == 3: # no step */ break; case 3: /* "_marching_cubes_lewiner_cy.pyx":631 * i += self.nx * self.step * elif vi == 3: # no step * j = 1 # <<<<<<<<<<<<<< * * elif vi < 12: */ __pyx_v_j = 1; /* "_marching_cubes_lewiner_cy.pyx":630 * elif vi == 2: # step in y * i += self.nx * self.step * elif vi == 3: # no step # <<<<<<<<<<<<<< * j = 1 * */ break; default: break; } /* "_marching_cubes_lewiner_cy.pyx":615 * * # Select either upper or lower half * if vi < 8: # <<<<<<<<<<<<<< * # 8 horizontal edges * if vi < 4: */ goto __pyx_L3; } /* "_marching_cubes_lewiner_cy.pyx":633 * j = 1 * * elif vi < 12: # <<<<<<<<<<<<<< * # 4 vertical edges * faceLayer = self.faceLayer1 */ __pyx_t_1 = ((__pyx_v_vi < 12) != 0); if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":635 * elif vi < 12: * # 4 vertical edges * faceLayer = self.faceLayer1 # <<<<<<<<<<<<<< * j = 2 * */ __pyx_t_2 = __pyx_v_self->faceLayer1; __pyx_v_faceLayer = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":636 * # 4 vertical edges * faceLayer = self.faceLayer1 * j = 2 # <<<<<<<<<<<<<< * * #if vi == 8: pass # no step */ __pyx_v_j = 2; /* "_marching_cubes_lewiner_cy.pyx":639 * * #if vi == 8: pass # no step * if vi == 9: # step in x # <<<<<<<<<<<<<< * i += self.step * elif vi == 10: # step in x and y */ switch (__pyx_v_vi) { case 9: /* "_marching_cubes_lewiner_cy.pyx":640 * #if vi == 8: pass # no step * if vi == 9: # step in x * i += self.step # <<<<<<<<<<<<<< * elif vi == 10: # step in x and y * i += self.nx * self.step + self.step */ __pyx_v_i = (__pyx_v_i + __pyx_v_self->step); /* "_marching_cubes_lewiner_cy.pyx":639 * * #if vi == 8: pass # no step * if vi == 9: # step in x # <<<<<<<<<<<<<< * i += self.step * elif vi == 10: # step in x and y */ break; case 10: /* "_marching_cubes_lewiner_cy.pyx":642 * i += self.step * elif vi == 10: # step in x and y * i += self.nx * self.step + self.step # <<<<<<<<<<<<<< * elif vi == 11: # step in y * i += self.nx * self.step */ __pyx_v_i = (__pyx_v_i + ((__pyx_v_self->nx * __pyx_v_self->step) + __pyx_v_self->step)); /* "_marching_cubes_lewiner_cy.pyx":641 * if vi == 9: # step in x * i += self.step * elif vi == 10: # step in x and y # <<<<<<<<<<<<<< * i += self.nx * self.step + self.step * elif vi == 11: # step in y */ break; case 11: /* "_marching_cubes_lewiner_cy.pyx":644 * i += self.nx * self.step + self.step * elif vi == 11: # step in y * i += self.nx * self.step # <<<<<<<<<<<<<< * * else: */ __pyx_v_i = (__pyx_v_i + (__pyx_v_self->nx * __pyx_v_self->step)); /* "_marching_cubes_lewiner_cy.pyx":643 * elif vi == 10: # step in x and y * i += self.nx * self.step + self.step * elif vi == 11: # step in y # <<<<<<<<<<<<<< * i += self.nx * self.step * */ break; default: break; } /* "_marching_cubes_lewiner_cy.pyx":633 * j = 1 * * elif vi < 12: # <<<<<<<<<<<<<< * # 4 vertical edges * faceLayer = self.faceLayer1 */ goto __pyx_L3; } /* "_marching_cubes_lewiner_cy.pyx":648 * else: * # center vertex * faceLayer = self.faceLayer1 # <<<<<<<<<<<<<< * j = 3 * */ /*else*/ { __pyx_t_2 = __pyx_v_self->faceLayer1; __pyx_v_faceLayer = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":649 * # center vertex * faceLayer = self.faceLayer1 * j = 3 # <<<<<<<<<<<<<< * * # Store facelayer and return index */ __pyx_v_j = 3; } __pyx_L3:; /* "_marching_cubes_lewiner_cy.pyx":652 * * # Store facelayer and return index * self.faceLayer = faceLayer # Dirty way of returning a value # <<<<<<<<<<<<<< * return 4*i + j * */ __pyx_v_self->faceLayer = __pyx_v_faceLayer; /* "_marching_cubes_lewiner_cy.pyx":653 * # Store facelayer and return index * self.faceLayer = faceLayer # Dirty way of returning a value * return 4*i + j # <<<<<<<<<<<<<< * * */ __pyx_r = ((4 * __pyx_v_i) + __pyx_v_j); goto __pyx_L0; /* "_marching_cubes_lewiner_cy.pyx":579 * * * cdef int get_index_in_facelayer(self, int vi): # <<<<<<<<<<<<<< * """ * Get the index of a vertex position, given the edge on which it lies. */ /* function exit code */ __pyx_L0:; __Pyx_RefNannyFinishContext(); return __pyx_r; } /* "_marching_cubes_lewiner_cy.pyx":656 * * * cdef void prepare_for_adding_triangles(self): # <<<<<<<<<<<<<< * """ Calculates some things to help adding the triangles: * array with corner values, max corner value, gradient at each corner. */ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_prepare_for_adding_triangles(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self) { int __pyx_v_i; double __pyx_v_vmin; double __pyx_v_vmax; __Pyx_RefNannyDeclarations double __pyx_t_1; double __pyx_t_2; int __pyx_t_3; int __pyx_t_4; double __pyx_t_5; __Pyx_RefNannySetupContext("prepare_for_adding_triangles", 0); /* "_marching_cubes_lewiner_cy.pyx":665 * # Copy values in array so we can index them. Note the misalignment * # because the numbering does not correspond with bitwise OR of xyz. * self.vv[0] = self.v0 # <<<<<<<<<<<<<< * self.vv[1] = self.v1 * self.vv[2] = self.v3# */ __pyx_t_1 = __pyx_v_self->v0; (__pyx_v_self->vv[0]) = __pyx_t_1; /* "_marching_cubes_lewiner_cy.pyx":666 * # because the numbering does not correspond with bitwise OR of xyz. * self.vv[0] = self.v0 * self.vv[1] = self.v1 # <<<<<<<<<<<<<< * self.vv[2] = self.v3# * self.vv[3] = self.v2# */ __pyx_t_1 = __pyx_v_self->v1; (__pyx_v_self->vv[1]) = __pyx_t_1; /* "_marching_cubes_lewiner_cy.pyx":667 * self.vv[0] = self.v0 * self.vv[1] = self.v1 * self.vv[2] = self.v3# # <<<<<<<<<<<<<< * self.vv[3] = self.v2# * self.vv[4] = self.v4 */ __pyx_t_1 = __pyx_v_self->v3; (__pyx_v_self->vv[2]) = __pyx_t_1; /* "_marching_cubes_lewiner_cy.pyx":668 * self.vv[1] = self.v1 * self.vv[2] = self.v3# * self.vv[3] = self.v2# # <<<<<<<<<<<<<< * self.vv[4] = self.v4 * self.vv[5] = self.v5 */ __pyx_t_1 = __pyx_v_self->v2; (__pyx_v_self->vv[3]) = __pyx_t_1; /* "_marching_cubes_lewiner_cy.pyx":669 * self.vv[2] = self.v3# * self.vv[3] = self.v2# * self.vv[4] = self.v4 # <<<<<<<<<<<<<< * self.vv[5] = self.v5 * self.vv[6] = self.v7# */ __pyx_t_1 = __pyx_v_self->v4; (__pyx_v_self->vv[4]) = __pyx_t_1; /* "_marching_cubes_lewiner_cy.pyx":670 * self.vv[3] = self.v2# * self.vv[4] = self.v4 * self.vv[5] = self.v5 # <<<<<<<<<<<<<< * self.vv[6] = self.v7# * self.vv[7] = self.v6# */ __pyx_t_1 = __pyx_v_self->v5; (__pyx_v_self->vv[5]) = __pyx_t_1; /* "_marching_cubes_lewiner_cy.pyx":671 * self.vv[4] = self.v4 * self.vv[5] = self.v5 * self.vv[6] = self.v7# # <<<<<<<<<<<<<< * self.vv[7] = self.v6# * */ __pyx_t_1 = __pyx_v_self->v7; (__pyx_v_self->vv[6]) = __pyx_t_1; /* "_marching_cubes_lewiner_cy.pyx":672 * self.vv[5] = self.v5 * self.vv[6] = self.v7# * self.vv[7] = self.v6# # <<<<<<<<<<<<<< * * # Calculate max */ __pyx_t_1 = __pyx_v_self->v6; (__pyx_v_self->vv[7]) = __pyx_t_1; /* "_marching_cubes_lewiner_cy.pyx":676 * # Calculate max * cdef double vmin, vmax * vmin, vmax = 0.0, 0.0 # <<<<<<<<<<<<<< * for i in range(8): * if self.vv[i] > vmax: */ __pyx_t_1 = 0.0; __pyx_t_2 = 0.0; __pyx_v_vmin = __pyx_t_1; __pyx_v_vmax = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":677 * cdef double vmin, vmax * vmin, vmax = 0.0, 0.0 * for i in range(8): # <<<<<<<<<<<<<< * if self.vv[i] > vmax: * vmax = self.vv[i] */ for (__pyx_t_3 = 0; __pyx_t_3 < 8; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* "_marching_cubes_lewiner_cy.pyx":678 * vmin, vmax = 0.0, 0.0 * for i in range(8): * if self.vv[i] > vmax: # <<<<<<<<<<<<<< * vmax = self.vv[i] * if self.vv[i] < vmin: */ __pyx_t_4 = (((__pyx_v_self->vv[__pyx_v_i]) > __pyx_v_vmax) != 0); if (__pyx_t_4) { /* "_marching_cubes_lewiner_cy.pyx":679 * for i in range(8): * if self.vv[i] > vmax: * vmax = self.vv[i] # <<<<<<<<<<<<<< * if self.vv[i] < vmin: * vmin = self.vv[i] */ __pyx_v_vmax = (__pyx_v_self->vv[__pyx_v_i]); /* "_marching_cubes_lewiner_cy.pyx":678 * vmin, vmax = 0.0, 0.0 * for i in range(8): * if self.vv[i] > vmax: # <<<<<<<<<<<<<< * vmax = self.vv[i] * if self.vv[i] < vmin: */ } /* "_marching_cubes_lewiner_cy.pyx":680 * if self.vv[i] > vmax: * vmax = self.vv[i] * if self.vv[i] < vmin: # <<<<<<<<<<<<<< * vmin = self.vv[i] * self.vmax = vmax-vmin */ __pyx_t_4 = (((__pyx_v_self->vv[__pyx_v_i]) < __pyx_v_vmin) != 0); if (__pyx_t_4) { /* "_marching_cubes_lewiner_cy.pyx":681 * vmax = self.vv[i] * if self.vv[i] < vmin: * vmin = self.vv[i] # <<<<<<<<<<<<<< * self.vmax = vmax-vmin * */ __pyx_v_vmin = (__pyx_v_self->vv[__pyx_v_i]); /* "_marching_cubes_lewiner_cy.pyx":680 * if self.vv[i] > vmax: * vmax = self.vv[i] * if self.vv[i] < vmin: # <<<<<<<<<<<<<< * vmin = self.vv[i] * self.vmax = vmax-vmin */ } } /* "_marching_cubes_lewiner_cy.pyx":682 * if self.vv[i] < vmin: * vmin = self.vv[i] * self.vmax = vmax-vmin # <<<<<<<<<<<<<< * * # Calculate gradients */ __pyx_v_self->vmax = (__pyx_v_vmax - __pyx_v_vmin); /* "_marching_cubes_lewiner_cy.pyx":689 * # by interpolating and averaging the normals this is solved. * # todo: we can potentially reuse these similar to how we store vertex indices in face layers * self.vg[0*3+0], self.vg[0*3+1], self.vg[0*3+2] = self.v0-self.v1, self.v0-self.v3, self.v0-self.v4 # <<<<<<<<<<<<<< * self.vg[1*3+0], self.vg[1*3+1], self.vg[1*3+2] = self.v0-self.v1, self.v1-self.v2, self.v1-self.v5 * self.vg[2*3+0], self.vg[2*3+1], self.vg[2*3+2] = self.v3-self.v2, self.v1-self.v2, self.v2-self.v6 */ __pyx_t_2 = (__pyx_v_self->v0 - __pyx_v_self->v1); __pyx_t_1 = (__pyx_v_self->v0 - __pyx_v_self->v3); __pyx_t_5 = (__pyx_v_self->v0 - __pyx_v_self->v4); (__pyx_v_self->vg[0]) = __pyx_t_2; (__pyx_v_self->vg[1]) = __pyx_t_1; (__pyx_v_self->vg[2]) = __pyx_t_5; /* "_marching_cubes_lewiner_cy.pyx":690 * # todo: we can potentially reuse these similar to how we store vertex indices in face layers * self.vg[0*3+0], self.vg[0*3+1], self.vg[0*3+2] = self.v0-self.v1, self.v0-self.v3, self.v0-self.v4 * self.vg[1*3+0], self.vg[1*3+1], self.vg[1*3+2] = self.v0-self.v1, self.v1-self.v2, self.v1-self.v5 # <<<<<<<<<<<<<< * self.vg[2*3+0], self.vg[2*3+1], self.vg[2*3+2] = self.v3-self.v2, self.v1-self.v2, self.v2-self.v6 * self.vg[3*3+0], self.vg[3*3+1], self.vg[3*3+2] = self.v3-self.v2, self.v0-self.v3, self.v3-self.v7 */ __pyx_t_5 = (__pyx_v_self->v0 - __pyx_v_self->v1); __pyx_t_1 = (__pyx_v_self->v1 - __pyx_v_self->v2); __pyx_t_2 = (__pyx_v_self->v1 - __pyx_v_self->v5); (__pyx_v_self->vg[3]) = __pyx_t_5; (__pyx_v_self->vg[4]) = __pyx_t_1; (__pyx_v_self->vg[5]) = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":691 * self.vg[0*3+0], self.vg[0*3+1], self.vg[0*3+2] = self.v0-self.v1, self.v0-self.v3, self.v0-self.v4 * self.vg[1*3+0], self.vg[1*3+1], self.vg[1*3+2] = self.v0-self.v1, self.v1-self.v2, self.v1-self.v5 * self.vg[2*3+0], self.vg[2*3+1], self.vg[2*3+2] = self.v3-self.v2, self.v1-self.v2, self.v2-self.v6 # <<<<<<<<<<<<<< * self.vg[3*3+0], self.vg[3*3+1], self.vg[3*3+2] = self.v3-self.v2, self.v0-self.v3, self.v3-self.v7 * self.vg[4*3+0], self.vg[4*3+1], self.vg[4*3+2] = self.v4-self.v5, self.v4-self.v7, self.v0-self.v4 */ __pyx_t_2 = (__pyx_v_self->v3 - __pyx_v_self->v2); __pyx_t_1 = (__pyx_v_self->v1 - __pyx_v_self->v2); __pyx_t_5 = (__pyx_v_self->v2 - __pyx_v_self->v6); (__pyx_v_self->vg[6]) = __pyx_t_2; (__pyx_v_self->vg[7]) = __pyx_t_1; (__pyx_v_self->vg[8]) = __pyx_t_5; /* "_marching_cubes_lewiner_cy.pyx":692 * self.vg[1*3+0], self.vg[1*3+1], self.vg[1*3+2] = self.v0-self.v1, self.v1-self.v2, self.v1-self.v5 * self.vg[2*3+0], self.vg[2*3+1], self.vg[2*3+2] = self.v3-self.v2, self.v1-self.v2, self.v2-self.v6 * self.vg[3*3+0], self.vg[3*3+1], self.vg[3*3+2] = self.v3-self.v2, self.v0-self.v3, self.v3-self.v7 # <<<<<<<<<<<<<< * self.vg[4*3+0], self.vg[4*3+1], self.vg[4*3+2] = self.v4-self.v5, self.v4-self.v7, self.v0-self.v4 * self.vg[5*3+0], self.vg[5*3+1], self.vg[5*3+2] = self.v4-self.v5, self.v5-self.v6, self.v1-self.v5 */ __pyx_t_5 = (__pyx_v_self->v3 - __pyx_v_self->v2); __pyx_t_1 = (__pyx_v_self->v0 - __pyx_v_self->v3); __pyx_t_2 = (__pyx_v_self->v3 - __pyx_v_self->v7); (__pyx_v_self->vg[9]) = __pyx_t_5; (__pyx_v_self->vg[10]) = __pyx_t_1; (__pyx_v_self->vg[11]) = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":693 * self.vg[2*3+0], self.vg[2*3+1], self.vg[2*3+2] = self.v3-self.v2, self.v1-self.v2, self.v2-self.v6 * self.vg[3*3+0], self.vg[3*3+1], self.vg[3*3+2] = self.v3-self.v2, self.v0-self.v3, self.v3-self.v7 * self.vg[4*3+0], self.vg[4*3+1], self.vg[4*3+2] = self.v4-self.v5, self.v4-self.v7, self.v0-self.v4 # <<<<<<<<<<<<<< * self.vg[5*3+0], self.vg[5*3+1], self.vg[5*3+2] = self.v4-self.v5, self.v5-self.v6, self.v1-self.v5 * self.vg[6*3+0], self.vg[6*3+1], self.vg[6*3+2] = self.v7-self.v6, self.v5-self.v6, self.v2-self.v6 */ __pyx_t_2 = (__pyx_v_self->v4 - __pyx_v_self->v5); __pyx_t_1 = (__pyx_v_self->v4 - __pyx_v_self->v7); __pyx_t_5 = (__pyx_v_self->v0 - __pyx_v_self->v4); (__pyx_v_self->vg[12]) = __pyx_t_2; (__pyx_v_self->vg[13]) = __pyx_t_1; (__pyx_v_self->vg[14]) = __pyx_t_5; /* "_marching_cubes_lewiner_cy.pyx":694 * self.vg[3*3+0], self.vg[3*3+1], self.vg[3*3+2] = self.v3-self.v2, self.v0-self.v3, self.v3-self.v7 * self.vg[4*3+0], self.vg[4*3+1], self.vg[4*3+2] = self.v4-self.v5, self.v4-self.v7, self.v0-self.v4 * self.vg[5*3+0], self.vg[5*3+1], self.vg[5*3+2] = self.v4-self.v5, self.v5-self.v6, self.v1-self.v5 # <<<<<<<<<<<<<< * self.vg[6*3+0], self.vg[6*3+1], self.vg[6*3+2] = self.v7-self.v6, self.v5-self.v6, self.v2-self.v6 * self.vg[7*3+0], self.vg[7*3+1], self.vg[7*3+2] = self.v7-self.v6, self.v4-self.v7, self.v3-self.v7 */ __pyx_t_5 = (__pyx_v_self->v4 - __pyx_v_self->v5); __pyx_t_1 = (__pyx_v_self->v5 - __pyx_v_self->v6); __pyx_t_2 = (__pyx_v_self->v1 - __pyx_v_self->v5); (__pyx_v_self->vg[15]) = __pyx_t_5; (__pyx_v_self->vg[16]) = __pyx_t_1; (__pyx_v_self->vg[17]) = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":695 * self.vg[4*3+0], self.vg[4*3+1], self.vg[4*3+2] = self.v4-self.v5, self.v4-self.v7, self.v0-self.v4 * self.vg[5*3+0], self.vg[5*3+1], self.vg[5*3+2] = self.v4-self.v5, self.v5-self.v6, self.v1-self.v5 * self.vg[6*3+0], self.vg[6*3+1], self.vg[6*3+2] = self.v7-self.v6, self.v5-self.v6, self.v2-self.v6 # <<<<<<<<<<<<<< * self.vg[7*3+0], self.vg[7*3+1], self.vg[7*3+2] = self.v7-self.v6, self.v4-self.v7, self.v3-self.v7 * */ __pyx_t_2 = (__pyx_v_self->v7 - __pyx_v_self->v6); __pyx_t_1 = (__pyx_v_self->v5 - __pyx_v_self->v6); __pyx_t_5 = (__pyx_v_self->v2 - __pyx_v_self->v6); (__pyx_v_self->vg[18]) = __pyx_t_2; (__pyx_v_self->vg[19]) = __pyx_t_1; (__pyx_v_self->vg[20]) = __pyx_t_5; /* "_marching_cubes_lewiner_cy.pyx":696 * self.vg[5*3+0], self.vg[5*3+1], self.vg[5*3+2] = self.v4-self.v5, self.v5-self.v6, self.v1-self.v5 * self.vg[6*3+0], self.vg[6*3+1], self.vg[6*3+2] = self.v7-self.v6, self.v5-self.v6, self.v2-self.v6 * self.vg[7*3+0], self.vg[7*3+1], self.vg[7*3+2] = self.v7-self.v6, self.v4-self.v7, self.v3-self.v7 # <<<<<<<<<<<<<< * * */ __pyx_t_5 = (__pyx_v_self->v7 - __pyx_v_self->v6); __pyx_t_1 = (__pyx_v_self->v4 - __pyx_v_self->v7); __pyx_t_2 = (__pyx_v_self->v3 - __pyx_v_self->v7); (__pyx_v_self->vg[21]) = __pyx_t_5; (__pyx_v_self->vg[22]) = __pyx_t_1; (__pyx_v_self->vg[23]) = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":656 * * * cdef void prepare_for_adding_triangles(self): # <<<<<<<<<<<<<< * """ Calculates some things to help adding the triangles: * array with corner values, max corner value, gradient at each corner. */ /* function exit code */ __Pyx_RefNannyFinishContext(); } /* "_marching_cubes_lewiner_cy.pyx":699 * * * cdef void calculate_center_vertex(self): # <<<<<<<<<<<<<< * """ Calculate interpolated center vertex and its gradient. * """ */ static void __pyx_f_26_marching_cubes_lewiner_cy_4Cell_calculate_center_vertex(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_self) { double __pyx_v_v0; double __pyx_v_v1; double __pyx_v_v2; double __pyx_v_v3; double __pyx_v_v4; double __pyx_v_v5; double __pyx_v_v6; double __pyx_v_v7; double __pyx_v_fx; double __pyx_v_fy; double __pyx_v_fz; double __pyx_v_ff; double __pyx_v_stp; __Pyx_RefNannyDeclarations double __pyx_t_1; double __pyx_t_2; double __pyx_t_3; double __pyx_t_4; __Pyx_RefNannySetupContext("calculate_center_vertex", 0); /* "_marching_cubes_lewiner_cy.pyx":704 * cdef double v0, v1, v2, v3, v4, v5, v6, v7 * cdef double fx, fy, fz, ff * fx, fy, fz, ff = 0.0, 0.0, 0.0, 0.0 # <<<<<<<<<<<<<< * * # Define "strength" of each corner of the cube that we need */ __pyx_t_1 = 0.0; __pyx_t_2 = 0.0; __pyx_t_3 = 0.0; __pyx_t_4 = 0.0; __pyx_v_fx = __pyx_t_1; __pyx_v_fy = __pyx_t_2; __pyx_v_fz = __pyx_t_3; __pyx_v_ff = __pyx_t_4; /* "_marching_cubes_lewiner_cy.pyx":707 * * # Define "strength" of each corner of the cube that we need * v0 = 1.0 / (FLT_EPSILON + dabs(self.v0)) # <<<<<<<<<<<<<< * v1 = 1.0 / (FLT_EPSILON + dabs(self.v1)) * v2 = 1.0 / (FLT_EPSILON + dabs(self.v2)) */ __pyx_v_v0 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs(__pyx_v_self->v0))); /* "_marching_cubes_lewiner_cy.pyx":708 * # Define "strength" of each corner of the cube that we need * v0 = 1.0 / (FLT_EPSILON + dabs(self.v0)) * v1 = 1.0 / (FLT_EPSILON + dabs(self.v1)) # <<<<<<<<<<<<<< * v2 = 1.0 / (FLT_EPSILON + dabs(self.v2)) * v3 = 1.0 / (FLT_EPSILON + dabs(self.v3)) */ __pyx_v_v1 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs(__pyx_v_self->v1))); /* "_marching_cubes_lewiner_cy.pyx":709 * v0 = 1.0 / (FLT_EPSILON + dabs(self.v0)) * v1 = 1.0 / (FLT_EPSILON + dabs(self.v1)) * v2 = 1.0 / (FLT_EPSILON + dabs(self.v2)) # <<<<<<<<<<<<<< * v3 = 1.0 / (FLT_EPSILON + dabs(self.v3)) * v4 = 1.0 / (FLT_EPSILON + dabs(self.v4)) */ __pyx_v_v2 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs(__pyx_v_self->v2))); /* "_marching_cubes_lewiner_cy.pyx":710 * v1 = 1.0 / (FLT_EPSILON + dabs(self.v1)) * v2 = 1.0 / (FLT_EPSILON + dabs(self.v2)) * v3 = 1.0 / (FLT_EPSILON + dabs(self.v3)) # <<<<<<<<<<<<<< * v4 = 1.0 / (FLT_EPSILON + dabs(self.v4)) * v5 = 1.0 / (FLT_EPSILON + dabs(self.v5)) */ __pyx_v_v3 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs(__pyx_v_self->v3))); /* "_marching_cubes_lewiner_cy.pyx":711 * v2 = 1.0 / (FLT_EPSILON + dabs(self.v2)) * v3 = 1.0 / (FLT_EPSILON + dabs(self.v3)) * v4 = 1.0 / (FLT_EPSILON + dabs(self.v4)) # <<<<<<<<<<<<<< * v5 = 1.0 / (FLT_EPSILON + dabs(self.v5)) * v6 = 1.0 / (FLT_EPSILON + dabs(self.v6)) */ __pyx_v_v4 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs(__pyx_v_self->v4))); /* "_marching_cubes_lewiner_cy.pyx":712 * v3 = 1.0 / (FLT_EPSILON + dabs(self.v3)) * v4 = 1.0 / (FLT_EPSILON + dabs(self.v4)) * v5 = 1.0 / (FLT_EPSILON + dabs(self.v5)) # <<<<<<<<<<<<<< * v6 = 1.0 / (FLT_EPSILON + dabs(self.v6)) * v7 = 1.0 / (FLT_EPSILON + dabs(self.v7)) */ __pyx_v_v5 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs(__pyx_v_self->v5))); /* "_marching_cubes_lewiner_cy.pyx":713 * v4 = 1.0 / (FLT_EPSILON + dabs(self.v4)) * v5 = 1.0 / (FLT_EPSILON + dabs(self.v5)) * v6 = 1.0 / (FLT_EPSILON + dabs(self.v6)) # <<<<<<<<<<<<<< * v7 = 1.0 / (FLT_EPSILON + dabs(self.v7)) * */ __pyx_v_v6 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs(__pyx_v_self->v6))); /* "_marching_cubes_lewiner_cy.pyx":714 * v5 = 1.0 / (FLT_EPSILON + dabs(self.v5)) * v6 = 1.0 / (FLT_EPSILON + dabs(self.v6)) * v7 = 1.0 / (FLT_EPSILON + dabs(self.v7)) # <<<<<<<<<<<<<< * * # Apply a kind of center-of-mass method */ __pyx_v_v7 = (1.0 / (__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON + __pyx_f_26_marching_cubes_lewiner_cy_dabs(__pyx_v_self->v7))); /* "_marching_cubes_lewiner_cy.pyx":717 * * # Apply a kind of center-of-mass method * fx += 0.0*v0; fy += 0.0*v0; fz += 0.0*v0; ff += v0 # <<<<<<<<<<<<<< * fx += 1.0*v1; fy += 0.0*v1; fz += 0.0*v1; ff += v1 * fx += 1.0*v2; fy += 1.0*v2; fz += 0.0*v2; ff += v2 */ __pyx_v_fx = (__pyx_v_fx + (0.0 * __pyx_v_v0)); __pyx_v_fy = (__pyx_v_fy + (0.0 * __pyx_v_v0)); __pyx_v_fz = (__pyx_v_fz + (0.0 * __pyx_v_v0)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_v0); /* "_marching_cubes_lewiner_cy.pyx":718 * # Apply a kind of center-of-mass method * fx += 0.0*v0; fy += 0.0*v0; fz += 0.0*v0; ff += v0 * fx += 1.0*v1; fy += 0.0*v1; fz += 0.0*v1; ff += v1 # <<<<<<<<<<<<<< * fx += 1.0*v2; fy += 1.0*v2; fz += 0.0*v2; ff += v2 * fx += 0.0*v3; fy += 1.0*v3; fz += 0.0*v3; ff += v3 */ __pyx_v_fx = (__pyx_v_fx + (1.0 * __pyx_v_v1)); __pyx_v_fy = (__pyx_v_fy + (0.0 * __pyx_v_v1)); __pyx_v_fz = (__pyx_v_fz + (0.0 * __pyx_v_v1)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_v1); /* "_marching_cubes_lewiner_cy.pyx":719 * fx += 0.0*v0; fy += 0.0*v0; fz += 0.0*v0; ff += v0 * fx += 1.0*v1; fy += 0.0*v1; fz += 0.0*v1; ff += v1 * fx += 1.0*v2; fy += 1.0*v2; fz += 0.0*v2; ff += v2 # <<<<<<<<<<<<<< * fx += 0.0*v3; fy += 1.0*v3; fz += 0.0*v3; ff += v3 * fx += 0.0*v4; fy += 0.0*v4; fz += 1.0*v4; ff += v4 */ __pyx_v_fx = (__pyx_v_fx + (1.0 * __pyx_v_v2)); __pyx_v_fy = (__pyx_v_fy + (1.0 * __pyx_v_v2)); __pyx_v_fz = (__pyx_v_fz + (0.0 * __pyx_v_v2)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_v2); /* "_marching_cubes_lewiner_cy.pyx":720 * fx += 1.0*v1; fy += 0.0*v1; fz += 0.0*v1; ff += v1 * fx += 1.0*v2; fy += 1.0*v2; fz += 0.0*v2; ff += v2 * fx += 0.0*v3; fy += 1.0*v3; fz += 0.0*v3; ff += v3 # <<<<<<<<<<<<<< * fx += 0.0*v4; fy += 0.0*v4; fz += 1.0*v4; ff += v4 * fx += 1.0*v5; fy += 0.0*v5; fz += 1.0*v5; ff += v5 */ __pyx_v_fx = (__pyx_v_fx + (0.0 * __pyx_v_v3)); __pyx_v_fy = (__pyx_v_fy + (1.0 * __pyx_v_v3)); __pyx_v_fz = (__pyx_v_fz + (0.0 * __pyx_v_v3)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_v3); /* "_marching_cubes_lewiner_cy.pyx":721 * fx += 1.0*v2; fy += 1.0*v2; fz += 0.0*v2; ff += v2 * fx += 0.0*v3; fy += 1.0*v3; fz += 0.0*v3; ff += v3 * fx += 0.0*v4; fy += 0.0*v4; fz += 1.0*v4; ff += v4 # <<<<<<<<<<<<<< * fx += 1.0*v5; fy += 0.0*v5; fz += 1.0*v5; ff += v5 * fx += 1.0*v6; fy += 1.0*v6; fz += 1.0*v6; ff += v6 */ __pyx_v_fx = (__pyx_v_fx + (0.0 * __pyx_v_v4)); __pyx_v_fy = (__pyx_v_fy + (0.0 * __pyx_v_v4)); __pyx_v_fz = (__pyx_v_fz + (1.0 * __pyx_v_v4)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_v4); /* "_marching_cubes_lewiner_cy.pyx":722 * fx += 0.0*v3; fy += 1.0*v3; fz += 0.0*v3; ff += v3 * fx += 0.0*v4; fy += 0.0*v4; fz += 1.0*v4; ff += v4 * fx += 1.0*v5; fy += 0.0*v5; fz += 1.0*v5; ff += v5 # <<<<<<<<<<<<<< * fx += 1.0*v6; fy += 1.0*v6; fz += 1.0*v6; ff += v6 * fx += 0.0*v7; fy += 1.0*v7; fz += 1.0*v7; ff += v7 */ __pyx_v_fx = (__pyx_v_fx + (1.0 * __pyx_v_v5)); __pyx_v_fy = (__pyx_v_fy + (0.0 * __pyx_v_v5)); __pyx_v_fz = (__pyx_v_fz + (1.0 * __pyx_v_v5)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_v5); /* "_marching_cubes_lewiner_cy.pyx":723 * fx += 0.0*v4; fy += 0.0*v4; fz += 1.0*v4; ff += v4 * fx += 1.0*v5; fy += 0.0*v5; fz += 1.0*v5; ff += v5 * fx += 1.0*v6; fy += 1.0*v6; fz += 1.0*v6; ff += v6 # <<<<<<<<<<<<<< * fx += 0.0*v7; fy += 1.0*v7; fz += 1.0*v7; ff += v7 * */ __pyx_v_fx = (__pyx_v_fx + (1.0 * __pyx_v_v6)); __pyx_v_fy = (__pyx_v_fy + (1.0 * __pyx_v_v6)); __pyx_v_fz = (__pyx_v_fz + (1.0 * __pyx_v_v6)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_v6); /* "_marching_cubes_lewiner_cy.pyx":724 * fx += 1.0*v5; fy += 0.0*v5; fz += 1.0*v5; ff += v5 * fx += 1.0*v6; fy += 1.0*v6; fz += 1.0*v6; ff += v6 * fx += 0.0*v7; fy += 1.0*v7; fz += 1.0*v7; ff += v7 # <<<<<<<<<<<<<< * * # Store */ __pyx_v_fx = (__pyx_v_fx + (0.0 * __pyx_v_v7)); __pyx_v_fy = (__pyx_v_fy + (1.0 * __pyx_v_v7)); __pyx_v_fz = (__pyx_v_fz + (1.0 * __pyx_v_v7)); __pyx_v_ff = (__pyx_v_ff + __pyx_v_v7); /* "_marching_cubes_lewiner_cy.pyx":727 * * # Store * cdef double stp = self.step # <<<<<<<<<<<<<< * self.v12_x = self.x + stp * fx / ff * self.v12_y = self.y + stp * fy / ff */ __pyx_v_stp = ((double)__pyx_v_self->step); /* "_marching_cubes_lewiner_cy.pyx":728 * # Store * cdef double stp = self.step * self.v12_x = self.x + stp * fx / ff # <<<<<<<<<<<<<< * self.v12_y = self.y + stp * fy / ff * self.v12_z = self.z + stp * fz / ff */ __pyx_v_self->v12_x = (__pyx_v_self->x + ((__pyx_v_stp * __pyx_v_fx) / __pyx_v_ff)); /* "_marching_cubes_lewiner_cy.pyx":729 * cdef double stp = self.step * self.v12_x = self.x + stp * fx / ff * self.v12_y = self.y + stp * fy / ff # <<<<<<<<<<<<<< * self.v12_z = self.z + stp * fz / ff * */ __pyx_v_self->v12_y = (__pyx_v_self->y + ((__pyx_v_stp * __pyx_v_fy) / __pyx_v_ff)); /* "_marching_cubes_lewiner_cy.pyx":730 * self.v12_x = self.x + stp * fx / ff * self.v12_y = self.y + stp * fy / ff * self.v12_z = self.z + stp * fz / ff # <<<<<<<<<<<<<< * * # Also pre-calculate gradient of center */ __pyx_v_self->v12_z = (__pyx_v_self->z + ((__pyx_v_stp * __pyx_v_fz) / __pyx_v_ff)); /* "_marching_cubes_lewiner_cy.pyx":735 * # note that prepare_for_adding_triangles() must have been called for * # the gradient data to exist. * self.v12_xg = ( v0*self.vg[0*3+0] + v1*self.vg[1*3+0] + v2*self.vg[2*3+0] + v3*self.vg[3*3+0] + # <<<<<<<<<<<<<< * v4*self.vg[4*3+0] + v5*self.vg[5*3+0] + v6*self.vg[6*3+0] + v7*self.vg[7*3+0] ) * self.v12_yg = ( v0*self.vg[0*3+1] + v1*self.vg[1*3+1] + v2*self.vg[2*3+1] + v3*self.vg[3*3+1] + */ __pyx_v_self->v12_xg = ((((((((__pyx_v_v0 * (__pyx_v_self->vg[0])) + (__pyx_v_v1 * (__pyx_v_self->vg[3]))) + (__pyx_v_v2 * (__pyx_v_self->vg[6]))) + (__pyx_v_v3 * (__pyx_v_self->vg[9]))) + (__pyx_v_v4 * (__pyx_v_self->vg[12]))) + (__pyx_v_v5 * (__pyx_v_self->vg[15]))) + (__pyx_v_v6 * (__pyx_v_self->vg[18]))) + (__pyx_v_v7 * (__pyx_v_self->vg[21]))); /* "_marching_cubes_lewiner_cy.pyx":737 * self.v12_xg = ( v0*self.vg[0*3+0] + v1*self.vg[1*3+0] + v2*self.vg[2*3+0] + v3*self.vg[3*3+0] + * v4*self.vg[4*3+0] + v5*self.vg[5*3+0] + v6*self.vg[6*3+0] + v7*self.vg[7*3+0] ) * self.v12_yg = ( v0*self.vg[0*3+1] + v1*self.vg[1*3+1] + v2*self.vg[2*3+1] + v3*self.vg[3*3+1] + # <<<<<<<<<<<<<< * v4*self.vg[4*3+1] + v5*self.vg[5*3+1] + v6*self.vg[6*3+1] + v7*self.vg[7*3+1] ) * self.v12_xg = ( v0*self.vg[0*3+2] + v1*self.vg[1*3+2] + v2*self.vg[2*3+2] + v3*self.vg[3*3+2] + */ __pyx_v_self->v12_yg = ((((((((__pyx_v_v0 * (__pyx_v_self->vg[1])) + (__pyx_v_v1 * (__pyx_v_self->vg[4]))) + (__pyx_v_v2 * (__pyx_v_self->vg[7]))) + (__pyx_v_v3 * (__pyx_v_self->vg[10]))) + (__pyx_v_v4 * (__pyx_v_self->vg[13]))) + (__pyx_v_v5 * (__pyx_v_self->vg[16]))) + (__pyx_v_v6 * (__pyx_v_self->vg[19]))) + (__pyx_v_v7 * (__pyx_v_self->vg[22]))); /* "_marching_cubes_lewiner_cy.pyx":739 * self.v12_yg = ( v0*self.vg[0*3+1] + v1*self.vg[1*3+1] + v2*self.vg[2*3+1] + v3*self.vg[3*3+1] + * v4*self.vg[4*3+1] + v5*self.vg[5*3+1] + v6*self.vg[6*3+1] + v7*self.vg[7*3+1] ) * self.v12_xg = ( v0*self.vg[0*3+2] + v1*self.vg[1*3+2] + v2*self.vg[2*3+2] + v3*self.vg[3*3+2] + # <<<<<<<<<<<<<< * v4*self.vg[4*3+2] + v5*self.vg[5*3+2] + v6*self.vg[6*3+2] + v7*self.vg[7*3+2] ) * */ __pyx_v_self->v12_xg = ((((((((__pyx_v_v0 * (__pyx_v_self->vg[2])) + (__pyx_v_v1 * (__pyx_v_self->vg[5]))) + (__pyx_v_v2 * (__pyx_v_self->vg[8]))) + (__pyx_v_v3 * (__pyx_v_self->vg[11]))) + (__pyx_v_v4 * (__pyx_v_self->vg[14]))) + (__pyx_v_v5 * (__pyx_v_self->vg[17]))) + (__pyx_v_v6 * (__pyx_v_self->vg[20]))) + (__pyx_v_v7 * (__pyx_v_self->vg[23]))); 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CYTHON_FALLTHROUGH; case 0: break; default: goto __pyx_L5_argtuple_error; } kw_args = PyDict_Size(__pyx_kwds); switch (pos_args) { case 0: if (likely((values[0] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_EDGESRELX)) != 0)) kw_args--; else goto __pyx_L5_argtuple_error; CYTHON_FALLTHROUGH; case 1: if (likely((values[1] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_EDGESRELY)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 1); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 2: if (likely((values[2] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_EDGESRELZ)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 2); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 3: if (likely((values[3] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_CASESCLASSIC)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 3); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 4: if (likely((values[4] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_CASES)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 4); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 5: if (likely((values[5] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 5); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 6: if (likely((values[6] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 6); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 7: if (likely((values[7] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING3_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 7); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 8: if (likely((values[8] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING3_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 8); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 9: if (likely((values[9] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING4_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 9); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 10: if (likely((values[10] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING4_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 10); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 11: if (likely((values[11] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING5)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 11); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 12: if (likely((values[12] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING6_1_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 12); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 13: if (likely((values[13] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING6_1_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 13); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 14: if (likely((values[14] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING6_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 14); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 15: if (likely((values[15] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING7_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 15); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 16: if (likely((values[16] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING7_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 16); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 17: if (likely((values[17] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING7_3)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 17); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 18: if (likely((values[18] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING7_4_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 18); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 19: if (likely((values[19] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING7_4_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 19); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 20: if (likely((values[20] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING8)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 20); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 21: if (likely((values[21] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING9)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 21); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 22: if (likely((values[22] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING10_1_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 22); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 23: if (likely((values[23] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING10_1_1_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 23); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 24: if (likely((values[24] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING10_1_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 24); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 25: if (likely((values[25] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING10_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 25); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 26: if (likely((values[26] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING10_2_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 26); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 27: if (likely((values[27] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING11)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 27); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 28: if (likely((values[28] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING12_1_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 28); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 29: if (likely((values[29] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING12_1_1_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 29); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 30: if (likely((values[30] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING12_1_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 30); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 31: if (likely((values[31] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING12_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 31); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 32: if (likely((values[32] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING12_2_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 32); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 33: if (likely((values[33] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 33); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 34: if (likely((values[34] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_1_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 34); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 35: if (likely((values[35] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 35); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 36: if (likely((values[36] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_2_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 36); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 37: if (likely((values[37] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_3)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 37); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 38: if (likely((values[38] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_3_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 38); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 39: if (likely((values[39] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_4)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 39); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 40: if (likely((values[40] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_5_1)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 40); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 41: if (likely((values[41] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING13_5_2)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 41); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 42: if (likely((values[42] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TILING14)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 42); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 43: if (likely((values[43] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TEST3)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 43); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 44: if (likely((values[44] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TEST4)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 44); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 45: if (likely((values[45] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TEST6)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 45); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 46: if (likely((values[46] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TEST7)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 46); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 47: if (likely((values[47] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TEST10)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 47); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 48: if (likely((values[48] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TEST12)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 48); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 49: if (likely((values[49] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_TEST13)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 49); __PYX_ERR(0, 862, __pyx_L3_error) } CYTHON_FALLTHROUGH; case 50: if (likely((values[50] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_SUBCONFIG13)) != 0)) kw_args--; else { __Pyx_RaiseArgtupleInvalid("__init__", 1, 51, 51, 50); __PYX_ERR(0, 862, __pyx_L3_error) } } if (unlikely(kw_args > 0)) { if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__init__") < 0)) __PYX_ERR(0, 862, __pyx_L3_error) } } else if (PyTuple_GET_SIZE(__pyx_args) != 51) { goto __pyx_L5_argtuple_error; } else { values[0] = PyTuple_GET_ITEM(__pyx_args, 0); values[1] = PyTuple_GET_ITEM(__pyx_args, 1); values[2] = PyTuple_GET_ITEM(__pyx_args, 2); values[3] = PyTuple_GET_ITEM(__pyx_args, 3); values[4] = PyTuple_GET_ITEM(__pyx_args, 4); values[5] = PyTuple_GET_ITEM(__pyx_args, 5); values[6] = PyTuple_GET_ITEM(__pyx_args, 6); values[7] = PyTuple_GET_ITEM(__pyx_args, 7); values[8] = PyTuple_GET_ITEM(__pyx_args, 8); values[9] = PyTuple_GET_ITEM(__pyx_args, 9); values[10] = PyTuple_GET_ITEM(__pyx_args, 10); values[11] = PyTuple_GET_ITEM(__pyx_args, 11); values[12] = PyTuple_GET_ITEM(__pyx_args, 12); values[13] = PyTuple_GET_ITEM(__pyx_args, 13); values[14] = PyTuple_GET_ITEM(__pyx_args, 14); values[15] = PyTuple_GET_ITEM(__pyx_args, 15); values[16] = PyTuple_GET_ITEM(__pyx_args, 16); values[17] = PyTuple_GET_ITEM(__pyx_args, 17); values[18] = PyTuple_GET_ITEM(__pyx_args, 18); values[19] = PyTuple_GET_ITEM(__pyx_args, 19); values[20] = PyTuple_GET_ITEM(__pyx_args, 20); values[21] = PyTuple_GET_ITEM(__pyx_args, 21); values[22] = PyTuple_GET_ITEM(__pyx_args, 22); values[23] = PyTuple_GET_ITEM(__pyx_args, 23); values[24] = PyTuple_GET_ITEM(__pyx_args, 24); values[25] = PyTuple_GET_ITEM(__pyx_args, 25); values[26] = PyTuple_GET_ITEM(__pyx_args, 26); values[27] = PyTuple_GET_ITEM(__pyx_args, 27); values[28] = PyTuple_GET_ITEM(__pyx_args, 28); values[29] = PyTuple_GET_ITEM(__pyx_args, 29); values[30] = PyTuple_GET_ITEM(__pyx_args, 30); values[31] = PyTuple_GET_ITEM(__pyx_args, 31); 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__pyx_t_1 = 0; /* "(tree fragment)":6 * cdef bint use_setstate * state = (self.CASES, self.CASESCLASSIC, self.EDGESRELX, self.EDGESRELY, self.EDGESRELZ, self.SUBCONFIG13, self.TEST10, self.TEST12, self.TEST13, self.TEST3, self.TEST4, self.TEST6, self.TEST7, self.TILING1, self.TILING10_1_1, self.TILING10_1_1_, self.TILING10_1_2, self.TILING10_2, self.TILING10_2_, self.TILING11, self.TILING12_1_1, self.TILING12_1_1_, self.TILING12_1_2, self.TILING12_2, self.TILING12_2_, self.TILING13_1, self.TILING13_1_, self.TILING13_2, self.TILING13_2_, self.TILING13_3, self.TILING13_3_, self.TILING13_4, self.TILING13_5_1, self.TILING13_5_2, self.TILING14, self.TILING2, self.TILING3_1, self.TILING3_2, self.TILING4_1, self.TILING4_2, self.TILING5, self.TILING6_1_1, self.TILING6_1_2, self.TILING6_2, self.TILING7_1, self.TILING7_2, self.TILING7_3, self.TILING7_4_1, self.TILING7_4_2, self.TILING8, self.TILING9) * _dict = getattr(self, '__dict__', None) # <<<<<<<<<<<<<< * if _dict is not None: * state += (_dict,) */ __pyx_t_1 = __Pyx_GetAttr3(((PyObject *)__pyx_v_self), __pyx_n_s_dict, Py_None); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 6, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_v__dict = __pyx_t_1; __pyx_t_1 = 0; /* "(tree fragment)":7 * state = (self.CASES, self.CASESCLASSIC, self.EDGESRELX, self.EDGESRELY, self.EDGESRELZ, self.SUBCONFIG13, self.TEST10, self.TEST12, self.TEST13, self.TEST3, self.TEST4, self.TEST6, self.TEST7, self.TILING1, self.TILING10_1_1, self.TILING10_1_1_, self.TILING10_1_2, self.TILING10_2, self.TILING10_2_, self.TILING11, self.TILING12_1_1, self.TILING12_1_1_, self.TILING12_1_2, self.TILING12_2, self.TILING12_2_, self.TILING13_1, self.TILING13_1_, self.TILING13_2, self.TILING13_2_, self.TILING13_3, self.TILING13_3_, self.TILING13_4, self.TILING13_5_1, self.TILING13_5_2, self.TILING14, self.TILING2, self.TILING3_1, self.TILING3_2, self.TILING4_1, self.TILING4_2, self.TILING5, self.TILING6_1_1, self.TILING6_1_2, self.TILING6_2, self.TILING7_1, self.TILING7_2, self.TILING7_3, self.TILING7_4_1, self.TILING7_4_2, self.TILING8, self.TILING9) * _dict = getattr(self, '__dict__', None) * if _dict is not None: # <<<<<<<<<<<<<< * state += (_dict,) * use_setstate = True */ __pyx_t_2 = (__pyx_v__dict != Py_None); __pyx_t_3 = (__pyx_t_2 != 0); if (__pyx_t_3) { /* "(tree fragment)":8 * _dict = getattr(self, '__dict__', None) * if _dict is not None: * state += (_dict,) # <<<<<<<<<<<<<< * use_setstate = True * else: */ __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 8, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_INCREF(__pyx_v__dict); __Pyx_GIVEREF(__pyx_v__dict); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_v__dict); __pyx_t_4 = PyNumber_InPlaceAdd(__pyx_v_state, __pyx_t_1); if (unlikely(!__pyx_t_4)) __PYX_ERR(1, 8, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF_SET(__pyx_v_state, ((PyObject*)__pyx_t_4)); __pyx_t_4 = 0; /* "(tree fragment)":9 * if _dict is not None: * state += (_dict,) * use_setstate = True # <<<<<<<<<<<<<< * else: * use_setstate = self.CASES is not None or self.CASESCLASSIC is not None or self.EDGESRELX is not None or self.EDGESRELY is not None or self.EDGESRELZ is not None or self.SUBCONFIG13 is not None or self.TEST10 is not None or self.TEST12 is not None or self.TEST13 is not None or self.TEST3 is not None or self.TEST4 is not None or self.TEST6 is not None or self.TEST7 is not None or self.TILING1 is not None or self.TILING10_1_1 is not None or self.TILING10_1_1_ is not None or self.TILING10_1_2 is not None or self.TILING10_2 is not None or self.TILING10_2_ is not None or self.TILING11 is not None or self.TILING12_1_1 is not None or self.TILING12_1_1_ is not None or self.TILING12_1_2 is not None or self.TILING12_2 is not None or self.TILING12_2_ is not None or self.TILING13_1 is not None or self.TILING13_1_ is not None or self.TILING13_2 is not None or self.TILING13_2_ is not None or self.TILING13_3 is not None or self.TILING13_3_ is not None or self.TILING13_4 is not None or self.TILING13_5_1 is not None or self.TILING13_5_2 is not None or self.TILING14 is not None or self.TILING2 is not None or self.TILING3_1 is not None or self.TILING3_2 is not None or self.TILING4_1 is not None or self.TILING4_2 is not None or self.TILING5 is not None or self.TILING6_1_1 is not None or self.TILING6_1_2 is not None or self.TILING6_2 is not None or self.TILING7_1 is not None or self.TILING7_2 is not None or self.TILING7_3 is not None or self.TILING7_4_1 is not None or self.TILING7_4_2 is not None or self.TILING8 is not None or self.TILING9 is not None */ __pyx_v_use_setstate = 1; /* "(tree fragment)":7 * state = (self.CASES, self.CASESCLASSIC, self.EDGESRELX, self.EDGESRELY, self.EDGESRELZ, self.SUBCONFIG13, self.TEST10, self.TEST12, self.TEST13, self.TEST3, self.TEST4, self.TEST6, self.TEST7, self.TILING1, self.TILING10_1_1, self.TILING10_1_1_, self.TILING10_1_2, self.TILING10_2, self.TILING10_2_, self.TILING11, self.TILING12_1_1, self.TILING12_1_1_, self.TILING12_1_2, self.TILING12_2, self.TILING12_2_, self.TILING13_1, self.TILING13_1_, self.TILING13_2, self.TILING13_2_, self.TILING13_3, self.TILING13_3_, self.TILING13_4, self.TILING13_5_1, self.TILING13_5_2, self.TILING14, self.TILING2, self.TILING3_1, self.TILING3_2, self.TILING4_1, self.TILING4_2, self.TILING5, self.TILING6_1_1, self.TILING6_1_2, self.TILING6_2, self.TILING7_1, self.TILING7_2, self.TILING7_3, self.TILING7_4_1, self.TILING7_4_2, self.TILING8, self.TILING9) * _dict = getattr(self, '__dict__', None) * if _dict is not None: # <<<<<<<<<<<<<< * state += (_dict,) * use_setstate = True */ goto __pyx_L3; } /* "(tree fragment)":11 * use_setstate = True * else: * use_setstate = self.CASES is not None or self.CASESCLASSIC is not None or self.EDGESRELX is not None or self.EDGESRELY is not None or self.EDGESRELZ is not None or self.SUBCONFIG13 is not None or self.TEST10 is not None or self.TEST12 is not None or self.TEST13 is not None or self.TEST3 is not None or self.TEST4 is not None or self.TEST6 is not None or self.TEST7 is not None or self.TILING1 is not None or self.TILING10_1_1 is not None or self.TILING10_1_1_ is not None or self.TILING10_1_2 is not None or self.TILING10_2 is not None or self.TILING10_2_ is not None or self.TILING11 is not None or self.TILING12_1_1 is not None or self.TILING12_1_1_ is not None or self.TILING12_1_2 is not None or self.TILING12_2 is not None or self.TILING12_2_ is not None or self.TILING13_1 is not None or self.TILING13_1_ is not None or self.TILING13_2 is not None or self.TILING13_2_ is not None or self.TILING13_3 is not None or self.TILING13_3_ is not None or self.TILING13_4 is not None or self.TILING13_5_1 is not None or self.TILING13_5_2 is not None or self.TILING14 is not None or self.TILING2 is not None or self.TILING3_1 is not None or self.TILING3_2 is not None or self.TILING4_1 is not None or self.TILING4_2 is not None or self.TILING5 is not None or self.TILING6_1_1 is not None or self.TILING6_1_2 is not None or self.TILING6_2 is not None or self.TILING7_1 is not None or self.TILING7_2 is not None or self.TILING7_3 is not None or self.TILING7_4_1 is not None or self.TILING7_4_2 is not None or self.TILING8 is not None or self.TILING9 is not None # <<<<<<<<<<<<<< * if use_setstate: * return __pyx_unpickle_LutProvider, (type(self), 0x3035ec8, None), state */ /*else*/ { __pyx_t_2 = (((PyObject *)__pyx_v_self->CASES) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->CASESCLASSIC) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->EDGESRELX) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->EDGESRELY) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->EDGESRELZ) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->SUBCONFIG13) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TEST10) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TEST12) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TEST13) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TEST3) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TEST4) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TEST6) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TEST7) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING1) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING10_1_1) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING10_1_1_) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING10_1_2) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING10_2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING10_2_) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING11) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING12_1_1) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING12_1_1_) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING12_1_2) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING12_2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING12_2_) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING13_1) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING13_1_) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING13_2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING13_2_) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING13_3) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING13_3_) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING13_4) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING13_5_1) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING13_5_2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING14) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING3_1) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING3_2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING4_1) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING4_2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING5) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING6_1_1) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING6_1_2) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING6_2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING7_1) != Py_None); __pyx_t_5 = (__pyx_t_2 != 0); if (!__pyx_t_5) { } else { __pyx_t_3 = __pyx_t_5; goto __pyx_L4_bool_binop_done; } __pyx_t_5 = (((PyObject *)__pyx_v_self->TILING7_2) != Py_None); __pyx_t_2 = (__pyx_t_5 != 0); if (!__pyx_t_2) { } else { __pyx_t_3 = __pyx_t_2; goto __pyx_L4_bool_binop_done; } __pyx_t_2 = (((PyObject *)__pyx_v_self->TILING7_3) != Py_None); 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/* "_marching_cubes_lewiner_cy.pyx":1077 * im[z_st,y, x], im[z_st,y, x_st], im[z_st,y_st, x_st], im[z_st,y_st, x]) * * max_cube_val = max_cube( im[z ,y, x], im[z ,y, x_st], im[z ,y_st, x_st], im[z ,y_st, x], # <<<<<<<<<<<<<< * im[z_st,y, x], im[z_st,y, x_st], im[z_st,y_st, x_st], im[z_st,y_st, x]) * */ __pyx_t_38 = __pyx_v_z; __pyx_t_37 = __pyx_v_y; __pyx_t_36 = __pyx_v_x; __pyx_t_35 = __pyx_v_z; __pyx_t_34 = __pyx_v_y; __pyx_t_33 = __pyx_v_x_st; __pyx_t_32 = __pyx_v_z; __pyx_t_31 = __pyx_v_y_st; __pyx_t_30 = __pyx_v_x_st; __pyx_t_29 = __pyx_v_z; __pyx_t_28 = __pyx_v_y_st; __pyx_t_27 = __pyx_v_x; /* "_marching_cubes_lewiner_cy.pyx":1078 * * max_cube_val = max_cube( im[z ,y, x], im[z ,y, x_st], im[z ,y_st, x_st], im[z ,y_st, x], * im[z_st,y, x], im[z_st,y, x_st], im[z_st,y_st, x_st], im[z_st,y_st, x]) # <<<<<<<<<<<<<< * * if avg_cube_val < 1.05 * voxel_size and max_cube_val <= 1.74 * voxel_size: */ __pyx_t_26 = __pyx_v_z_st; __pyx_t_25 = __pyx_v_y; __pyx_t_24 = __pyx_v_x; __pyx_t_23 = __pyx_v_z_st; 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/* "_marching_cubes_lewiner_cy.pyx":1080 * im[z_st,y, x], im[z_st,y, x_st], im[z_st,y_st, x_st], im[z_st,y_st, x]) * * if avg_cube_val < 1.05 * voxel_size and max_cube_val <= 1.74 * voxel_size: # <<<<<<<<<<<<<< * # Choose base vector for the dot product that is not (0,0,0) * # in a corner of the cube */ __pyx_t_5 = PyFloat_FromDouble(__pyx_v_avg_cube_val); if (unlikely(!__pyx_t_5)) __PYX_ERR(0, 1080, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); __pyx_t_13 = PyNumber_Multiply(__pyx_float_1_05, __pyx_v_voxel_size); if (unlikely(!__pyx_t_13)) __PYX_ERR(0, 1080, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_13); __pyx_t_12 = PyObject_RichCompare(__pyx_t_5, __pyx_t_13, Py_LT); __Pyx_XGOTREF(__pyx_t_12); if (unlikely(!__pyx_t_12)) __PYX_ERR(0, 1080, __pyx_L1_error) __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __Pyx_DECREF(__pyx_t_13); __pyx_t_13 = 0; __pyx_t_14 = __Pyx_PyObject_IsTrue(__pyx_t_12); if (unlikely(__pyx_t_14 < 0)) __PYX_ERR(0, 1080, __pyx_L1_error) __Pyx_DECREF(__pyx_t_12); __pyx_t_12 = 0; if (__pyx_t_14) { } else { __pyx_t_8 = __pyx_t_14; 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} /* "_marching_cubes_lewiner_cy.pyx":1085 * if not non_zero_norm(grads[z,y,x]) == 0: * base_vec = grads[z,y,x] * elif not non_zero_norm(grads[z,y,x_st]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z,y,x_st] * elif not non_zero_norm(grads[z,y_st,x]) == 0: */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __pyx_t_8 = ((!((__pyx_f_26_marching_cubes_lewiner_cy_non_zero_norm(__pyx_t_39) == 0) != 0)) != 0); __PYX_XDEC_MEMVIEW(&__pyx_t_39, 1); __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; if (__pyx_t_8) { /* "_marching_cubes_lewiner_cy.pyx":1086 * base_vec = grads[z,y,x] * elif not non_zero_norm(grads[z,y,x_st]) == 0: * base_vec = grads[z,y,x_st] # <<<<<<<<<<<<<< * elif not non_zero_norm(grads[z,y_st,x]) == 0: * base_vec = grads[z,y_st,x] */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __PYX_XDEC_MEMVIEW(&__pyx_v_base_vec, 1); __pyx_v_base_vec = __pyx_t_39; __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; /* "_marching_cubes_lewiner_cy.pyx":1085 * if not non_zero_norm(grads[z,y,x]) == 0: * base_vec = grads[z,y,x] * elif not non_zero_norm(grads[z,y,x_st]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z,y,x_st] * elif not non_zero_norm(grads[z,y_st,x]) == 0: */ goto __pyx_L15; } /* "_marching_cubes_lewiner_cy.pyx":1087 * elif not non_zero_norm(grads[z,y,x_st]) == 0: * base_vec = grads[z,y,x_st] * elif not non_zero_norm(grads[z,y_st,x]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z,y_st,x] * elif not non_zero_norm(grads[z,y_st,x_st]) == 0: */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __pyx_t_8 = ((!((__pyx_f_26_marching_cubes_lewiner_cy_non_zero_norm(__pyx_t_39) == 0) != 0)) != 0); __PYX_XDEC_MEMVIEW(&__pyx_t_39, 1); __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; if (__pyx_t_8) { /* "_marching_cubes_lewiner_cy.pyx":1088 * base_vec = grads[z,y,x_st] * elif not non_zero_norm(grads[z,y_st,x]) == 0: * base_vec = grads[z,y_st,x] # <<<<<<<<<<<<<< * elif not non_zero_norm(grads[z,y_st,x_st]) == 0: * base_vec = grads[z,y_st,x_st] */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __PYX_XDEC_MEMVIEW(&__pyx_v_base_vec, 1); __pyx_v_base_vec = __pyx_t_39; __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; /* "_marching_cubes_lewiner_cy.pyx":1087 * elif not non_zero_norm(grads[z,y,x_st]) == 0: * base_vec = grads[z,y,x_st] * elif not non_zero_norm(grads[z,y_st,x]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z,y_st,x] * elif not non_zero_norm(grads[z,y_st,x_st]) == 0: */ goto __pyx_L15; } /* "_marching_cubes_lewiner_cy.pyx":1089 * elif not non_zero_norm(grads[z,y_st,x]) == 0: * base_vec = grads[z,y_st,x] * elif not non_zero_norm(grads[z,y_st,x_st]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z,y_st,x_st] * elif not non_zero_norm(grads[z_st,y,x]) == 0: */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __pyx_t_8 = ((!((__pyx_f_26_marching_cubes_lewiner_cy_non_zero_norm(__pyx_t_39) == 0) != 0)) != 0); __PYX_XDEC_MEMVIEW(&__pyx_t_39, 1); __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; if (__pyx_t_8) { /* "_marching_cubes_lewiner_cy.pyx":1090 * base_vec = grads[z,y_st,x] * elif not non_zero_norm(grads[z,y_st,x_st]) == 0: * base_vec = grads[z,y_st,x_st] # <<<<<<<<<<<<<< * elif not non_zero_norm(grads[z_st,y,x]) == 0: * base_vec = grads[z_st,y,x] */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __PYX_XDEC_MEMVIEW(&__pyx_v_base_vec, 1); __pyx_v_base_vec = __pyx_t_39; __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; /* "_marching_cubes_lewiner_cy.pyx":1089 * elif not non_zero_norm(grads[z,y_st,x]) == 0: * base_vec = grads[z,y_st,x] * elif not non_zero_norm(grads[z,y_st,x_st]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z,y_st,x_st] * elif not non_zero_norm(grads[z_st,y,x]) == 0: */ goto __pyx_L15; } /* "_marching_cubes_lewiner_cy.pyx":1091 * elif not non_zero_norm(grads[z,y_st,x_st]) == 0: * base_vec = grads[z,y_st,x_st] * elif not non_zero_norm(grads[z_st,y,x]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z_st,y,x] * elif not non_zero_norm(grads[z_st,y,x_st]) == 0: */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __pyx_t_8 = ((!((__pyx_f_26_marching_cubes_lewiner_cy_non_zero_norm(__pyx_t_39) == 0) != 0)) != 0); __PYX_XDEC_MEMVIEW(&__pyx_t_39, 1); __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; if (__pyx_t_8) { /* "_marching_cubes_lewiner_cy.pyx":1092 * base_vec = grads[z,y_st,x_st] * elif not non_zero_norm(grads[z_st,y,x]) == 0: * base_vec = grads[z_st,y,x] # <<<<<<<<<<<<<< * elif not non_zero_norm(grads[z_st,y,x_st]) == 0: * base_vec = grads[z_st,y,x_st] */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __PYX_XDEC_MEMVIEW(&__pyx_v_base_vec, 1); __pyx_v_base_vec = __pyx_t_39; __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; /* "_marching_cubes_lewiner_cy.pyx":1091 * elif not non_zero_norm(grads[z,y_st,x_st]) == 0: * base_vec = grads[z,y_st,x_st] * elif not non_zero_norm(grads[z_st,y,x]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z_st,y,x] * elif not non_zero_norm(grads[z_st,y,x_st]) == 0: */ goto __pyx_L15; } /* "_marching_cubes_lewiner_cy.pyx":1093 * elif not non_zero_norm(grads[z_st,y,x]) == 0: * base_vec = grads[z_st,y,x] * elif not non_zero_norm(grads[z_st,y,x_st]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z_st,y,x_st] * elif not non_zero_norm(grads[z_st,y_st,x]) == 0: */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __pyx_t_8 = ((!((__pyx_f_26_marching_cubes_lewiner_cy_non_zero_norm(__pyx_t_39) == 0) != 0)) != 0); __PYX_XDEC_MEMVIEW(&__pyx_t_39, 1); __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; if (__pyx_t_8) { /* "_marching_cubes_lewiner_cy.pyx":1094 * base_vec = grads[z_st,y,x] * elif not non_zero_norm(grads[z_st,y,x_st]) == 0: * base_vec = grads[z_st,y,x_st] # <<<<<<<<<<<<<< * elif not non_zero_norm(grads[z_st,y_st,x]) == 0: * base_vec = grads[z_st,y_st,x] */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __PYX_XDEC_MEMVIEW(&__pyx_v_base_vec, 1); __pyx_v_base_vec = __pyx_t_39; __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; /* "_marching_cubes_lewiner_cy.pyx":1093 * elif not non_zero_norm(grads[z_st,y,x]) == 0: * base_vec = grads[z_st,y,x] * elif not non_zero_norm(grads[z_st,y,x_st]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z_st,y,x_st] * elif not non_zero_norm(grads[z_st,y_st,x]) == 0: */ goto __pyx_L15; } /* "_marching_cubes_lewiner_cy.pyx":1095 * elif not non_zero_norm(grads[z_st,y,x_st]) == 0: * base_vec = grads[z_st,y,x_st] * elif not non_zero_norm(grads[z_st,y_st,x]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z_st,y_st,x] * elif not non_zero_norm(grads[z_st,y_st,x_st]) == 0: */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __pyx_t_8 = ((!((__pyx_f_26_marching_cubes_lewiner_cy_non_zero_norm(__pyx_t_39) == 0) != 0)) != 0); __PYX_XDEC_MEMVIEW(&__pyx_t_39, 1); __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; if (__pyx_t_8) { /* "_marching_cubes_lewiner_cy.pyx":1096 * base_vec = grads[z_st,y,x_st] * elif not non_zero_norm(grads[z_st,y_st,x]) == 0: * base_vec = grads[z_st,y_st,x] # <<<<<<<<<<<<<< * elif not non_zero_norm(grads[z_st,y_st,x_st]) == 0: * base_vec = grads[z_st,y_st,x_st] */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __PYX_XDEC_MEMVIEW(&__pyx_v_base_vec, 1); __pyx_v_base_vec = __pyx_t_39; __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; /* "_marching_cubes_lewiner_cy.pyx":1095 * elif not non_zero_norm(grads[z_st,y,x_st]) == 0: * base_vec = grads[z_st,y,x_st] * elif not non_zero_norm(grads[z_st,y_st,x]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z_st,y_st,x] * elif not non_zero_norm(grads[z_st,y_st,x_st]) == 0: */ goto __pyx_L15; } /* "_marching_cubes_lewiner_cy.pyx":1097 * elif not non_zero_norm(grads[z_st,y_st,x]) == 0: * base_vec = grads[z_st,y_st,x] * elif not non_zero_norm(grads[z_st,y_st,x_st]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z_st,y_st,x_st] * # else: */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __pyx_t_8 = ((!((__pyx_f_26_marching_cubes_lewiner_cy_non_zero_norm(__pyx_t_39) == 0) != 0)) != 0); __PYX_XDEC_MEMVIEW(&__pyx_t_39, 1); __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; if (__pyx_t_8) { /* "_marching_cubes_lewiner_cy.pyx":1098 * base_vec = grads[z_st,y_st,x] * elif not non_zero_norm(grads[z_st,y_st,x_st]) == 0: * base_vec = grads[z_st,y_st,x_st] # <<<<<<<<<<<<<< * # else: * # print('all 0 vec...') */ __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __PYX_XDEC_MEMVIEW(&__pyx_v_base_vec, 1); __pyx_v_base_vec = __pyx_t_39; __pyx_t_39.memview = NULL; __pyx_t_39.data = NULL; /* "_marching_cubes_lewiner_cy.pyx":1097 * elif not non_zero_norm(grads[z_st,y_st,x]) == 0: * base_vec = grads[z_st,y_st,x] * elif not non_zero_norm(grads[z_st,y_st,x_st]) == 0: # <<<<<<<<<<<<<< * base_vec = grads[z_st,y_st,x_st] * # else: */ } __pyx_L15:; /* "_marching_cubes_lewiner_cy.pyx":1104 * # Initialize cell * cell.set_cube(0.0, x, y, z, st, * my_sign(dot3(base_vec, grads[z ,y, x])) * im[z ,y, x], # <<<<<<<<<<<<<< * my_sign(dot3(base_vec, grads[z ,y, x_st])) * im[z ,y, x_st], * my_sign(dot3(base_vec, grads[z ,y_st, x_st])) * im[z ,y_st, x_st], */ if (unlikely(!__pyx_v_base_vec.memview)) { __Pyx_RaiseUnboundLocalError("base_vec"); __PYX_ERR(0, 1104, __pyx_L1_error) } __pyx_t_39.data = __pyx_v_grads.data; __pyx_t_39.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_39, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_39.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_39.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_39.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_39.suboffsets[0] = -1; __pyx_t_17 = __pyx_v_z; __pyx_t_16 = __pyx_v_y; __pyx_t_15 = __pyx_v_x; /* "_marching_cubes_lewiner_cy.pyx":1105 * cell.set_cube(0.0, x, y, z, st, * my_sign(dot3(base_vec, grads[z ,y, x])) * im[z ,y, x], * my_sign(dot3(base_vec, grads[z ,y, x_st])) * im[z ,y, x_st], # <<<<<<<<<<<<<< * my_sign(dot3(base_vec, grads[z ,y_st, x_st])) * im[z ,y_st, x_st], * my_sign(dot3(base_vec, grads[z ,y_st, x])) * im[z ,y_st, x], */ if (unlikely(!__pyx_v_base_vec.memview)) { __Pyx_RaiseUnboundLocalError("base_vec"); __PYX_ERR(0, 1105, __pyx_L1_error) } __pyx_t_40.data = __pyx_v_grads.data; __pyx_t_40.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_40, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_40.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_40.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_40.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_40.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_40.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_40.suboffsets[0] = -1; __pyx_t_18 = __pyx_v_z; __pyx_t_19 = __pyx_v_y; __pyx_t_20 = __pyx_v_x_st; /* "_marching_cubes_lewiner_cy.pyx":1106 * my_sign(dot3(base_vec, grads[z ,y, x])) * im[z ,y, x], * my_sign(dot3(base_vec, grads[z ,y, x_st])) * im[z ,y, x_st], * my_sign(dot3(base_vec, grads[z ,y_st, x_st])) * im[z ,y_st, x_st], # <<<<<<<<<<<<<< * my_sign(dot3(base_vec, grads[z ,y_st, x])) * im[z ,y_st, x], * my_sign(dot3(base_vec, grads[z_st,y, x])) * im[z_st,y, x], */ if (unlikely(!__pyx_v_base_vec.memview)) { __Pyx_RaiseUnboundLocalError("base_vec"); __PYX_ERR(0, 1106, __pyx_L1_error) } __pyx_t_41.data = __pyx_v_grads.data; __pyx_t_41.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_41, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_41.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_41.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_41.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_41.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_41.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_41.suboffsets[0] = -1; __pyx_t_21 = __pyx_v_z; __pyx_t_22 = __pyx_v_y_st; __pyx_t_23 = __pyx_v_x_st; /* "_marching_cubes_lewiner_cy.pyx":1107 * my_sign(dot3(base_vec, grads[z ,y, x_st])) * im[z ,y, x_st], * my_sign(dot3(base_vec, grads[z ,y_st, x_st])) * im[z ,y_st, x_st], * my_sign(dot3(base_vec, grads[z ,y_st, x])) * im[z ,y_st, x], # <<<<<<<<<<<<<< * my_sign(dot3(base_vec, grads[z_st,y, x])) * im[z_st,y, x], * my_sign(dot3(base_vec, grads[z_st,y, x_st])) * im[z_st,y, x_st], */ if (unlikely(!__pyx_v_base_vec.memview)) { __Pyx_RaiseUnboundLocalError("base_vec"); __PYX_ERR(0, 1107, __pyx_L1_error) } __pyx_t_42.data = __pyx_v_grads.data; __pyx_t_42.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_42, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_42.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_42.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_42.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_42.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_42.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_42.suboffsets[0] = -1; __pyx_t_24 = __pyx_v_z; __pyx_t_25 = __pyx_v_y_st; __pyx_t_26 = __pyx_v_x; /* "_marching_cubes_lewiner_cy.pyx":1108 * my_sign(dot3(base_vec, grads[z ,y_st, x_st])) * im[z ,y_st, x_st], * my_sign(dot3(base_vec, grads[z ,y_st, x])) * im[z ,y_st, x], * my_sign(dot3(base_vec, grads[z_st,y, x])) * im[z_st,y, x], # <<<<<<<<<<<<<< * my_sign(dot3(base_vec, grads[z_st,y, x_st])) * im[z_st,y, x_st], * my_sign(dot3(base_vec, grads[z_st,y_st, x_st])) * im[z_st,y_st, x_st], */ if (unlikely(!__pyx_v_base_vec.memview)) { __Pyx_RaiseUnboundLocalError("base_vec"); __PYX_ERR(0, 1108, __pyx_L1_error) } __pyx_t_43.data = __pyx_v_grads.data; __pyx_t_43.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_43, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_43.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_43.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_43.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_43.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_43.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_43.suboffsets[0] = -1; __pyx_t_27 = __pyx_v_z_st; __pyx_t_28 = __pyx_v_y; __pyx_t_29 = __pyx_v_x; /* "_marching_cubes_lewiner_cy.pyx":1109 * my_sign(dot3(base_vec, grads[z ,y_st, x])) * im[z ,y_st, x], * my_sign(dot3(base_vec, grads[z_st,y, x])) * im[z_st,y, x], * my_sign(dot3(base_vec, grads[z_st,y, x_st])) * im[z_st,y, x_st], # <<<<<<<<<<<<<< * my_sign(dot3(base_vec, grads[z_st,y_st, x_st])) * im[z_st,y_st, x_st], * my_sign(dot3(base_vec, grads[z_st,y_st, x])) * im[z_st,y_st, x] ) */ if (unlikely(!__pyx_v_base_vec.memview)) { __Pyx_RaiseUnboundLocalError("base_vec"); __PYX_ERR(0, 1109, __pyx_L1_error) } __pyx_t_44.data = __pyx_v_grads.data; __pyx_t_44.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_44, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_44.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_44.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_44.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_44.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_44.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_44.suboffsets[0] = -1; __pyx_t_30 = __pyx_v_z_st; __pyx_t_31 = __pyx_v_y; __pyx_t_32 = __pyx_v_x_st; /* "_marching_cubes_lewiner_cy.pyx":1110 * my_sign(dot3(base_vec, grads[z_st,y, x])) * im[z_st,y, x], * my_sign(dot3(base_vec, grads[z_st,y, x_st])) * im[z_st,y, x_st], * my_sign(dot3(base_vec, grads[z_st,y_st, x_st])) * im[z_st,y_st, x_st], # <<<<<<<<<<<<<< * my_sign(dot3(base_vec, grads[z_st,y_st, x])) * im[z_st,y_st, x] ) * */ if (unlikely(!__pyx_v_base_vec.memview)) { __Pyx_RaiseUnboundLocalError("base_vec"); __PYX_ERR(0, 1110, __pyx_L1_error) } __pyx_t_45.data = __pyx_v_grads.data; __pyx_t_45.memview = __pyx_v_grads.memview; __PYX_INC_MEMVIEW(&__pyx_t_45, 0); { Py_ssize_t __pyx_tmp_idx = __pyx_v_z_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[0]; __pyx_t_45.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_y_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[1]; __pyx_t_45.data += __pyx_tmp_idx * __pyx_tmp_stride; } { Py_ssize_t __pyx_tmp_idx = __pyx_v_x_st; Py_ssize_t __pyx_tmp_stride = __pyx_v_grads.strides[2]; __pyx_t_45.data += __pyx_tmp_idx * __pyx_tmp_stride; } __pyx_t_45.shape[0] = __pyx_v_grads.shape[3]; __pyx_t_45.strides[0] = __pyx_v_grads.strides[3]; __pyx_t_45.suboffsets[0] = -1; __pyx_t_33 = __pyx_v_z_st; __pyx_t_34 = __pyx_v_y_st; __pyx_t_35 = __pyx_v_x_st; /* "_marching_cubes_lewiner_cy.pyx":1111 * my_sign(dot3(base_vec, grads[z_st,y, x_st])) * im[z_st,y, x_st], * my_sign(dot3(base_vec, grads[z_st,y_st, x_st])) * im[z_st,y_st, x_st], * my_sign(dot3(base_vec, grads[z_st,y_st, x])) * im[z_st,y_st, x] ) # <<<<<<<<<<<<<< * * # Get case, if non-nul, enter the big switch */ if (unlikely(!__pyx_v_base_vec.memview)) { __Pyx_RaiseUnboundLocalError("base_vec"); 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__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1266 * cell.add_triangles2(luts.TILING7_3, config, 0, 9) * elif subconfig == 4: cell.add_triangles2(luts.TILING7_2, config, 2, 5) * elif subconfig == 5: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING7_3, config, 1, 9) */ break; case 6: /* "_marching_cubes_lewiner_cy.pyx":1271 * elif subconfig == 6: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING7_3, config, 2, 9) # <<<<<<<<<<<<<< * elif subconfig == 7: * if test_internal(cell, luts, case, config, subconfig, luts.TEST7.get2(config,3)): */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING7_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 2, 9); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1269 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING7_3, config, 1, 9) * elif subconfig == 6: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING7_3, config, 2, 9) */ break; case 7: /* "_marching_cubes_lewiner_cy.pyx":1273 * cell.add_triangles2(luts.TILING7_3, config, 2, 9) * elif subconfig == 7: * if test_internal(cell, luts, case, config, subconfig, luts.TEST7.get2(config,3)): # <<<<<<<<<<<<<< * cell.add_triangles(luts.TILING7_4_2, config, 9) * else: */ __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_internal(__pyx_v_cell, __pyx_v_luts, __pyx_v_case, __pyx_v_config, __pyx_v_subconfig, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST7->__pyx_vtab)->get2(__pyx_v_luts->TEST7, __pyx_v_config, 3)) != 0); if (__pyx_t_2) { /* "_marching_cubes_lewiner_cy.pyx":1274 * elif subconfig == 7: * if test_internal(cell, luts, case, config, subconfig, luts.TEST7.get2(config,3)): * cell.add_triangles(luts.TILING7_4_2, config, 9) # <<<<<<<<<<<<<< * else: * cell.add_triangles(luts.TILING7_4_1, config, 5) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING7_4_2); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 9); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1273 * cell.add_triangles2(luts.TILING7_3, config, 2, 9) * elif subconfig == 7: * if test_internal(cell, luts, case, config, subconfig, luts.TEST7.get2(config,3)): # <<<<<<<<<<<<<< * cell.add_triangles(luts.TILING7_4_2, config, 9) * else: */ goto __pyx_L10; } /* "_marching_cubes_lewiner_cy.pyx":1276 * cell.add_triangles(luts.TILING7_4_2, config, 9) * else: * cell.add_triangles(luts.TILING7_4_1, config, 5) # <<<<<<<<<<<<<< * * elif case == 8 : */ /*else*/ { __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING7_4_1); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 5); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; } __pyx_L10:; /* "_marching_cubes_lewiner_cy.pyx":1272 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING7_3, config, 2, 9) * elif subconfig == 7: # <<<<<<<<<<<<<< * if test_internal(cell, luts, case, config, subconfig, luts.TEST7.get2(config,3)): * cell.add_triangles(luts.TILING7_4_2, config, 9) */ break; default: break; } /* "_marching_cubes_lewiner_cy.pyx":1253 * cell.add_triangles(luts.TILING6_1_2, config, 9) * * elif case == 7 : # <<<<<<<<<<<<<< * # Get subconfig * if test_face(cell, luts.TEST7.get2(config,0)): subconfig += 1 */ break; case 8: /* "_marching_cubes_lewiner_cy.pyx":1279 * * elif case == 8 : * cell.add_triangles(luts.TILING8, config, 2) # <<<<<<<<<<<<<< * * elif case == 9 : */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING8); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 2); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1278 * cell.add_triangles(luts.TILING7_4_1, config, 5) * * elif case == 8 : # <<<<<<<<<<<<<< * cell.add_triangles(luts.TILING8, config, 2) * */ break; case 9: /* "_marching_cubes_lewiner_cy.pyx":1282 * * elif case == 9 : * cell.add_triangles(luts.TILING9, config, 4) # <<<<<<<<<<<<<< * * elif case == 10 : */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING9); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1281 * cell.add_triangles(luts.TILING8, config, 2) * * elif case == 9 : # <<<<<<<<<<<<<< * cell.add_triangles(luts.TILING9, config, 4) * */ break; case 10: /* "_marching_cubes_lewiner_cy.pyx":1285 * * elif case == 10 : * if test_face(cell, luts.TEST10.get2(config,0)): # <<<<<<<<<<<<<< * if test_face(cell, luts.TEST10.get2(config,1)): * cell.add_triangles(luts.TILING10_1_1_, config, 4) */ __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_face(__pyx_v_cell, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST10->__pyx_vtab)->get2(__pyx_v_luts->TEST10, __pyx_v_config, 0)) != 0); if (__pyx_t_2) { /* "_marching_cubes_lewiner_cy.pyx":1286 * elif case == 10 : * if test_face(cell, luts.TEST10.get2(config,0)): * if test_face(cell, luts.TEST10.get2(config,1)): # <<<<<<<<<<<<<< * cell.add_triangles(luts.TILING10_1_1_, config, 4) * else: */ __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_face(__pyx_v_cell, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST10->__pyx_vtab)->get2(__pyx_v_luts->TEST10, __pyx_v_config, 1)) != 0); 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__Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 8); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; } __pyx_L12:; /* "_marching_cubes_lewiner_cy.pyx":1285 * * elif case == 10 : * if test_face(cell, luts.TEST10.get2(config,0)): # <<<<<<<<<<<<<< * if test_face(cell, luts.TEST10.get2(config,1)): * cell.add_triangles(luts.TILING10_1_1_, config, 4) */ goto __pyx_L11; } /* "_marching_cubes_lewiner_cy.pyx":1292 * cell.add_triangles(luts.TILING10_2, config, 8) * else: * if test_face(cell, luts.TEST10.get2(config,1)): # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles(luts.TILING10_2_, config, 8) */ /*else*/ { __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_face(__pyx_v_cell, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST10->__pyx_vtab)->get2(__pyx_v_luts->TEST10, __pyx_v_config, 1)) != 0); 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__Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 8); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; } __pyx_L16:; /* "_marching_cubes_lewiner_cy.pyx":1305 * * elif case == 12 : * if test_face(cell, luts.TEST12.get2(config,0)): # <<<<<<<<<<<<<< * if test_face(cell, luts.TEST12.get2(config,1)): * cell.add_triangles(luts.TILING12_1_1_, config, 4) */ goto __pyx_L15; } /* "_marching_cubes_lewiner_cy.pyx":1312 * cell.add_triangles(luts.TILING12_2, config, 8) * else: * if test_face(cell, luts.TEST12.get2(config,1)): # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles(luts.TILING12_2_, config, 8) */ /*else*/ { __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_face(__pyx_v_cell, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST12->__pyx_vtab)->get2(__pyx_v_luts->TEST12, __pyx_v_config, 1)) != 0); if (__pyx_t_2) { /* "_marching_cubes_lewiner_cy.pyx":1314 * if test_face(cell, luts.TEST12.get2(config,1)): * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles(luts.TILING12_2_, config, 8) # <<<<<<<<<<<<<< * else: * if test_internal(cell, luts, case, config, subconfig, luts.TEST12.get2(config,2)): */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING12_2_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 8); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1312 * cell.add_triangles(luts.TILING12_2, config, 8) * else: * if test_face(cell, luts.TEST12.get2(config,1)): # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles(luts.TILING12_2_, config, 8) */ goto __pyx_L17; } /* "_marching_cubes_lewiner_cy.pyx":1316 * cell.add_triangles(luts.TILING12_2_, config, 8) * else: * if test_internal(cell, luts, case, config, subconfig, luts.TEST12.get2(config,2)): # <<<<<<<<<<<<<< * cell.add_triangles(luts.TILING12_1_1, config, 4) * else: */ /*else*/ { __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_internal(__pyx_v_cell, __pyx_v_luts, __pyx_v_case, __pyx_v_config, __pyx_v_subconfig, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST12->__pyx_vtab)->get2(__pyx_v_luts->TEST12, __pyx_v_config, 2)) != 0); 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__Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 8); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; } __pyx_L18:; } __pyx_L17:; } __pyx_L15:; /* "_marching_cubes_lewiner_cy.pyx":1304 * cell.add_triangles(luts.TILING11, config, 4) * * elif case == 12 : # <<<<<<<<<<<<<< * if test_face(cell, luts.TEST12.get2(config,0)): * if test_face(cell, luts.TEST12.get2(config,1)): */ break; case 13: /* "_marching_cubes_lewiner_cy.pyx":1323 * elif case == 13 : * # Calculate subconfig * if test_face(cell, luts.TEST13.get2(config,0)): subconfig += 1 # <<<<<<<<<<<<<< * if test_face(cell, luts.TEST13.get2(config,1)): subconfig += 2 * if test_face(cell, luts.TEST13.get2(config,2)): subconfig += 4 */ __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_face(__pyx_v_cell, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST13->__pyx_vtab)->get2(__pyx_v_luts->TEST13, __pyx_v_config, 0)) != 0); 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case 10: /* "_marching_cubes_lewiner_cy.pyx":1353 * elif subconfig==10: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 3, 10) # <<<<<<<<<<<<<< * elif subconfig==11: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 3, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1351 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 2, 10) * elif subconfig==10: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 3, 10) */ break; case 11: /* "_marching_cubes_lewiner_cy.pyx":1356 * elif subconfig==11: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 4, 10) # <<<<<<<<<<<<<< * elif subconfig==12: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 4, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1354 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 3, 10) * elif subconfig==11: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 4, 10) */ break; case 12: /* "_marching_cubes_lewiner_cy.pyx":1359 * elif subconfig==12: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 5, 10) # <<<<<<<<<<<<<< * elif subconfig==13: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 5, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1357 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 4, 10) * elif subconfig==12: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 5, 10) */ break; case 13: /* "_marching_cubes_lewiner_cy.pyx":1362 * elif subconfig==13: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 6, 10) # <<<<<<<<<<<<<< * elif subconfig==14: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 6, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1360 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 5, 10) * elif subconfig==13: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 6, 10) */ break; case 14: /* "_marching_cubes_lewiner_cy.pyx":1365 * elif subconfig==14: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 7, 10) # <<<<<<<<<<<<<< * elif subconfig==15: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 7, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1363 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 6, 10) * elif subconfig==14: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 7, 10) */ break; case 15: /* "_marching_cubes_lewiner_cy.pyx":1368 * elif subconfig==15: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 8, 10) # <<<<<<<<<<<<<< * elif subconfig==16: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 8, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1366 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 7, 10) * elif subconfig==15: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 8, 10) */ break; case 16: /* "_marching_cubes_lewiner_cy.pyx":1371 * elif subconfig==16: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 9, 10) # <<<<<<<<<<<<<< * elif subconfig==17: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 9, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1369 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 8, 10) * elif subconfig==16: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 9, 10) */ break; case 17: /* "_marching_cubes_lewiner_cy.pyx":1374 * elif subconfig==17: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 10, 10) # <<<<<<<<<<<<<< * elif subconfig==18: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 10, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1372 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 9, 10) * elif subconfig==17: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 10, 10) */ break; case 18: /* "_marching_cubes_lewiner_cy.pyx":1377 * elif subconfig==18: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 11, 10) # <<<<<<<<<<<<<< * # * elif subconfig==19: */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 11, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1375 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 10, 10) * elif subconfig==18: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3, config, 11, 10) */ break; case 19: /* "_marching_cubes_lewiner_cy.pyx":1381 * elif subconfig==19: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 0, 12) # <<<<<<<<<<<<<< * elif subconfig==20: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_4); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 0, 12); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1379 * cell.add_triangles2(luts.TILING13_3, config, 11, 10) * # * elif subconfig==19: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 0, 12) */ break; case 20: /* "_marching_cubes_lewiner_cy.pyx":1384 * elif subconfig==20: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 1, 12) # <<<<<<<<<<<<<< * elif subconfig==21: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_4); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 1, 12); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1382 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 0, 12) * elif subconfig==20: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 1, 12) */ break; case 21: /* "_marching_cubes_lewiner_cy.pyx":1387 * elif subconfig==21: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 2, 12) # <<<<<<<<<<<<<< * elif subconfig==22: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_4); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 2, 12); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1385 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 1, 12) * elif subconfig==21: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 2, 12) */ break; case 22: /* "_marching_cubes_lewiner_cy.pyx":1390 * elif subconfig==22: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 3, 12) # <<<<<<<<<<<<<< * # * elif subconfig==23: */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_4); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 3, 12); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1388 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 2, 12) * elif subconfig==22: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_4, config, 3, 12) */ break; case 23: /* "_marching_cubes_lewiner_cy.pyx":1393 * # * elif subconfig==23: * subconfig = 0 # Note: the original source code sets the subconfig, without apparent reason # <<<<<<<<<<<<<< * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): * cell.add_triangles2(luts.TILING13_5_1, config, 0, 6) */ __pyx_v_subconfig = 0; /* "_marching_cubes_lewiner_cy.pyx":1394 * elif subconfig==23: * subconfig = 0 # Note: the original source code sets the subconfig, without apparent reason * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_5_1, config, 0, 6) * else: */ __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_internal(__pyx_v_cell, __pyx_v_luts, __pyx_v_case, __pyx_v_config, __pyx_v_subconfig, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST13->__pyx_vtab)->get2(__pyx_v_luts->TEST13, __pyx_v_config, 6)) != 0); if (__pyx_t_2) { /* "_marching_cubes_lewiner_cy.pyx":1395 * subconfig = 0 # Note: the original source code sets the subconfig, without apparent reason * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): * cell.add_triangles2(luts.TILING13_5_1, config, 0, 6) # <<<<<<<<<<<<<< * else: * cell.add_triangles2(luts.TILING13_5_2, config, 0, 10) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_5_1); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 0, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1394 * elif subconfig==23: * subconfig = 0 # Note: the original source code sets the subconfig, without apparent reason * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_5_1, config, 0, 6) * else: */ goto __pyx_L25; } /* "_marching_cubes_lewiner_cy.pyx":1397 * cell.add_triangles2(luts.TILING13_5_1, config, 0, 6) * else: * cell.add_triangles2(luts.TILING13_5_2, config, 0, 10) # <<<<<<<<<<<<<< * elif subconfig==24: * subconfig = 1 */ /*else*/ { __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_5_2); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 0, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; } __pyx_L25:; /* "_marching_cubes_lewiner_cy.pyx":1392 * cell.add_triangles2(luts.TILING13_4, config, 3, 12) * # * elif subconfig==23: # <<<<<<<<<<<<<< * subconfig = 0 # Note: the original source code sets the subconfig, without apparent reason * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): */ break; case 24: /* "_marching_cubes_lewiner_cy.pyx":1399 * cell.add_triangles2(luts.TILING13_5_2, config, 0, 10) * elif subconfig==24: * subconfig = 1 # <<<<<<<<<<<<<< * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): * cell.add_triangles2(luts.TILING13_5_1, config, 1, 6) */ __pyx_v_subconfig = 1; /* "_marching_cubes_lewiner_cy.pyx":1400 * elif subconfig==24: * subconfig = 1 * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_5_1, config, 1, 6) * else: */ __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_internal(__pyx_v_cell, __pyx_v_luts, __pyx_v_case, __pyx_v_config, __pyx_v_subconfig, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST13->__pyx_vtab)->get2(__pyx_v_luts->TEST13, __pyx_v_config, 6)) != 0); if (__pyx_t_2) { /* "_marching_cubes_lewiner_cy.pyx":1401 * subconfig = 1 * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): * cell.add_triangles2(luts.TILING13_5_1, config, 1, 6) # <<<<<<<<<<<<<< * else: * cell.add_triangles2(luts.TILING13_5_2, config, 1, 10) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_5_1); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 1, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1400 * elif subconfig==24: * subconfig = 1 * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_5_1, config, 1, 6) * else: */ goto __pyx_L26; } /* "_marching_cubes_lewiner_cy.pyx":1403 * cell.add_triangles2(luts.TILING13_5_1, config, 1, 6) * else: * cell.add_triangles2(luts.TILING13_5_2, config, 1, 10) # <<<<<<<<<<<<<< * elif subconfig==25: * subconfig = 2 ; */ /*else*/ { __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_5_2); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 1, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; } __pyx_L26:; /* "_marching_cubes_lewiner_cy.pyx":1398 * else: * cell.add_triangles2(luts.TILING13_5_2, config, 0, 10) * elif subconfig==24: # <<<<<<<<<<<<<< * subconfig = 1 * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): */ break; case 25: /* "_marching_cubes_lewiner_cy.pyx":1405 * cell.add_triangles2(luts.TILING13_5_2, config, 1, 10) * elif subconfig==25: * subconfig = 2 ; # <<<<<<<<<<<<<< * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): * cell.add_triangles2(luts.TILING13_5_1, config, 2, 6) */ __pyx_v_subconfig = 2; /* "_marching_cubes_lewiner_cy.pyx":1406 * elif subconfig==25: * subconfig = 2 ; * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_5_1, config, 2, 6) * else: */ __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_internal(__pyx_v_cell, __pyx_v_luts, __pyx_v_case, __pyx_v_config, __pyx_v_subconfig, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST13->__pyx_vtab)->get2(__pyx_v_luts->TEST13, __pyx_v_config, 6)) != 0); if (__pyx_t_2) { /* "_marching_cubes_lewiner_cy.pyx":1407 * subconfig = 2 ; * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): * cell.add_triangles2(luts.TILING13_5_1, config, 2, 6) # <<<<<<<<<<<<<< * else: * cell.add_triangles2(luts.TILING13_5_2, config, 2, 10) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_5_1); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 2, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1406 * elif subconfig==25: * subconfig = 2 ; * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_5_1, config, 2, 6) * else: */ goto __pyx_L27; } /* "_marching_cubes_lewiner_cy.pyx":1409 * cell.add_triangles2(luts.TILING13_5_1, config, 2, 6) * else: * cell.add_triangles2(luts.TILING13_5_2, config, 2, 10) # <<<<<<<<<<<<<< * elif subconfig==26: * subconfig = 3 ; */ /*else*/ { __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_5_2); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 2, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; } __pyx_L27:; /* "_marching_cubes_lewiner_cy.pyx":1404 * else: * cell.add_triangles2(luts.TILING13_5_2, config, 1, 10) * elif subconfig==25: # <<<<<<<<<<<<<< * subconfig = 2 ; * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): */ break; case 26: /* "_marching_cubes_lewiner_cy.pyx":1411 * cell.add_triangles2(luts.TILING13_5_2, config, 2, 10) * elif subconfig==26: * subconfig = 3 ; # <<<<<<<<<<<<<< * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): * cell.add_triangles2(luts.TILING13_5_1, config, 3, 6) */ __pyx_v_subconfig = 3; /* "_marching_cubes_lewiner_cy.pyx":1412 * elif subconfig==26: * subconfig = 3 ; * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_5_1, config, 3, 6) * else: */ __pyx_t_2 = (__pyx_f_26_marching_cubes_lewiner_cy_test_internal(__pyx_v_cell, __pyx_v_luts, __pyx_v_case, __pyx_v_config, __pyx_v_subconfig, ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST13->__pyx_vtab)->get2(__pyx_v_luts->TEST13, __pyx_v_config, 6)) != 0); if (__pyx_t_2) { /* "_marching_cubes_lewiner_cy.pyx":1413 * subconfig = 3 ; * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): * cell.add_triangles2(luts.TILING13_5_1, config, 3, 6) # <<<<<<<<<<<<<< * else: * cell.add_triangles2(luts.TILING13_5_2, config, 3, 10) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_5_1); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 3, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1412 * elif subconfig==26: * subconfig = 3 ; * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_5_1, config, 3, 6) * else: */ goto __pyx_L28; } /* "_marching_cubes_lewiner_cy.pyx":1415 * cell.add_triangles2(luts.TILING13_5_1, config, 3, 6) * else: * cell.add_triangles2(luts.TILING13_5_2, config, 3, 10) # <<<<<<<<<<<<<< * # * elif subconfig==27: */ /*else*/ { __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_5_2); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 3, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; } __pyx_L28:; /* "_marching_cubes_lewiner_cy.pyx":1410 * else: * cell.add_triangles2(luts.TILING13_5_2, config, 2, 10) * elif subconfig==26: # <<<<<<<<<<<<<< * subconfig = 3 ; * if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): */ break; case 27: /* "_marching_cubes_lewiner_cy.pyx":1419 * elif subconfig==27: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 0, 10) # <<<<<<<<<<<<<< * elif subconfig==28: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 0, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1417 * cell.add_triangles2(luts.TILING13_5_2, config, 3, 10) * # * elif subconfig==27: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 0, 10) */ break; case 28: /* "_marching_cubes_lewiner_cy.pyx":1422 * elif subconfig==28: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 1, 10) # <<<<<<<<<<<<<< * elif subconfig==29: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 1, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1420 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 0, 10) * elif subconfig==28: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 1, 10) */ break; case 29: /* "_marching_cubes_lewiner_cy.pyx":1425 * elif subconfig==29: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 2, 10) # <<<<<<<<<<<<<< * elif subconfig==30: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 2, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1423 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 1, 10) * elif subconfig==29: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 2, 10) */ break; case 30: /* "_marching_cubes_lewiner_cy.pyx":1428 * elif subconfig==30: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 3, 10) # <<<<<<<<<<<<<< * elif subconfig==31: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 3, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1426 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 2, 10) * elif subconfig==30: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 3, 10) */ break; case 31: /* "_marching_cubes_lewiner_cy.pyx":1431 * elif subconfig==31: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 4, 10) # <<<<<<<<<<<<<< * elif subconfig==32: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 4, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1429 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 3, 10) * elif subconfig==31: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 4, 10) */ break; case 32: /* "_marching_cubes_lewiner_cy.pyx":1434 * elif subconfig==32: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 5, 10) # <<<<<<<<<<<<<< * elif subconfig==33: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 5, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1432 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 4, 10) * elif subconfig==32: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 5, 10) */ break; case 33: /* "_marching_cubes_lewiner_cy.pyx":1437 * elif subconfig==33: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config,6, 10) # <<<<<<<<<<<<<< * elif subconfig==34: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 6, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1435 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 5, 10) * elif subconfig==33: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config,6, 10) */ break; case 34: /* "_marching_cubes_lewiner_cy.pyx":1440 * elif subconfig==34: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 7, 10) # <<<<<<<<<<<<<< * elif subconfig==35: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 7, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1438 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config,6, 10) * elif subconfig==34: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 7, 10) */ break; case 35: /* "_marching_cubes_lewiner_cy.pyx":1443 * elif subconfig==35: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 8, 10) # <<<<<<<<<<<<<< * elif subconfig==36: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 8, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1441 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 7, 10) * elif subconfig==35: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 8, 10) */ break; case 36: /* "_marching_cubes_lewiner_cy.pyx":1446 * elif subconfig==36: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 9, 10) # <<<<<<<<<<<<<< * elif subconfig==37: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 9, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1444 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 8, 10) * elif subconfig==36: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 9, 10) */ break; case 37: /* "_marching_cubes_lewiner_cy.pyx":1449 * elif subconfig==37: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 10, 10) # <<<<<<<<<<<<<< * elif subconfig==38: * #cell.calculate_center_vertex() # v12 needed */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 10, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1447 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 9, 10) * elif subconfig==37: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 10, 10) */ break; case 38: /* "_marching_cubes_lewiner_cy.pyx":1452 * elif subconfig==38: * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 11, 10) # <<<<<<<<<<<<<< * # * elif subconfig==39: */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_3_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 11, 10); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1450 * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 10, 10) * elif subconfig==38: # <<<<<<<<<<<<<< * #cell.calculate_center_vertex() # v12 needed * cell.add_triangles2(luts.TILING13_3_, config, 11, 10) */ break; case 39: /* "_marching_cubes_lewiner_cy.pyx":1455 * # * elif subconfig==39: * cell.add_triangles2(luts.TILING13_2_, config, 0, 6) # <<<<<<<<<<<<<< * elif subconfig==40: * cell.add_triangles2(luts.TILING13_2_, config, 1, 6) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_2_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 0, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1454 * cell.add_triangles2(luts.TILING13_3_, config, 11, 10) * # * elif subconfig==39: # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_2_, config, 0, 6) * elif subconfig==40: */ break; case 40: /* "_marching_cubes_lewiner_cy.pyx":1457 * cell.add_triangles2(luts.TILING13_2_, config, 0, 6) * elif subconfig==40: * cell.add_triangles2(luts.TILING13_2_, config, 1, 6) # <<<<<<<<<<<<<< * elif subconfig==41: * cell.add_triangles2(luts.TILING13_2_, config, 2, 6) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_2_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 1, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1456 * elif subconfig==39: * cell.add_triangles2(luts.TILING13_2_, config, 0, 6) * elif subconfig==40: # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_2_, config, 1, 6) * elif subconfig==41: */ break; case 41: /* "_marching_cubes_lewiner_cy.pyx":1459 * cell.add_triangles2(luts.TILING13_2_, config, 1, 6) * elif subconfig==41: * cell.add_triangles2(luts.TILING13_2_, config, 2, 6) # <<<<<<<<<<<<<< * elif subconfig==42: * cell.add_triangles2(luts.TILING13_2_, config, 3, 6) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_2_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 2, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1458 * elif subconfig==40: * cell.add_triangles2(luts.TILING13_2_, config, 1, 6) * elif subconfig==41: # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_2_, config, 2, 6) * elif subconfig==42: */ break; case 42: /* "_marching_cubes_lewiner_cy.pyx":1461 * cell.add_triangles2(luts.TILING13_2_, config, 2, 6) * elif subconfig==42: * cell.add_triangles2(luts.TILING13_2_, config, 3, 6) # <<<<<<<<<<<<<< * elif subconfig==43: * cell.add_triangles2(luts.TILING13_2_, config, 4, 6) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_2_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 3, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1460 * elif subconfig==41: * cell.add_triangles2(luts.TILING13_2_, config, 2, 6) * elif subconfig==42: # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_2_, config, 3, 6) * elif subconfig==43: */ break; case 43: /* "_marching_cubes_lewiner_cy.pyx":1463 * cell.add_triangles2(luts.TILING13_2_, config, 3, 6) * elif subconfig==43: * cell.add_triangles2(luts.TILING13_2_, config, 4, 6) # <<<<<<<<<<<<<< * elif subconfig==44: * cell.add_triangles2(luts.TILING13_2_, config, 5, 6) */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_2_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 4, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1462 * elif subconfig==42: * cell.add_triangles2(luts.TILING13_2_, config, 3, 6) * elif subconfig==43: # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_2_, config, 4, 6) * elif subconfig==44: */ break; case 44: /* "_marching_cubes_lewiner_cy.pyx":1465 * cell.add_triangles2(luts.TILING13_2_, config, 4, 6) * elif subconfig==44: * cell.add_triangles2(luts.TILING13_2_, config, 5, 6) # <<<<<<<<<<<<<< * # * elif subconfig==45: */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_2_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles2(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 5, 6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1464 * elif subconfig==43: * cell.add_triangles2(luts.TILING13_2_, config, 4, 6) * elif subconfig==44: # <<<<<<<<<<<<<< * cell.add_triangles2(luts.TILING13_2_, config, 5, 6) * # */ break; case 45: /* "_marching_cubes_lewiner_cy.pyx":1468 * # * elif subconfig==45: * cell.add_triangles(luts.TILING13_1_, config, 4) # <<<<<<<<<<<<<< * # * else: */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING13_1_); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1467 * cell.add_triangles2(luts.TILING13_2_, config, 5, 6) * # * elif subconfig==45: # <<<<<<<<<<<<<< * cell.add_triangles(luts.TILING13_1_, config, 4) * # */ break; default: /* "_marching_cubes_lewiner_cy.pyx":1471 * # * else: * print("Marching Cubes: Impossible case 13?" ) # <<<<<<<<<<<<<< * * elif case == 14 : */ if (__Pyx_PrintOne(0, __pyx_kp_s_Marching_Cubes_Impossible_case_1) < 0) __PYX_ERR(0, 1471, __pyx_L1_error) break; } /* "_marching_cubes_lewiner_cy.pyx":1321 * cell.add_triangles(luts.TILING12_1_2, config, 8) * * elif case == 13 : # <<<<<<<<<<<<<< * # Calculate subconfig * if test_face(cell, luts.TEST13.get2(config,0)): subconfig += 1 */ break; case 14: /* "_marching_cubes_lewiner_cy.pyx":1474 * * elif case == 14 : * cell.add_triangles(luts.TILING14, config, 4) # <<<<<<<<<<<<<< * * */ __pyx_t_1 = ((PyObject *)__pyx_v_luts->TILING14); __Pyx_INCREF(__pyx_t_1); ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Cell *)__pyx_v_cell->__pyx_vtab)->add_triangles(__pyx_v_cell, ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)__pyx_t_1), __pyx_v_config, 4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; /* "_marching_cubes_lewiner_cy.pyx":1473 * print("Marching Cubes: Impossible case 13?" ) * * elif case == 14 : # <<<<<<<<<<<<<< * cell.add_triangles(luts.TILING14, config, 4) * */ break; default: break; } /* "_marching_cubes_lewiner_cy.pyx":1208 * * * cdef void the_big_switch(LutProvider luts, Cell cell, int case, int config): # <<<<<<<<<<<<<< * """ The big switch (i.e. if-statement) that I meticulously ported from * the source code provided by Lewiner et. al. */ /* function exit code */ goto __pyx_L0; __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); __Pyx_WriteUnraisable("_marching_cubes_lewiner_cy.the_big_switch", __pyx_clineno, __pyx_lineno, __pyx_filename, 1, 0); __pyx_L0:; __Pyx_RefNannyFinishContext(); } /* "_marching_cubes_lewiner_cy.pyx":1477 * * * cdef int test_face(Cell cell, int face): # <<<<<<<<<<<<<< * """ Return True of the face contains part of the surface. * """ */ static int __pyx_f_26_marching_cubes_lewiner_cy_test_face(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_cell, int __pyx_v_face) { int __pyx_v_absFace; double __pyx_v_A; double __pyx_v_B; double __pyx_v_C; double __pyx_v_D; double __pyx_v_AC_BD; int __pyx_r; __Pyx_RefNannyDeclarations int __pyx_t_1; double __pyx_t_2; double __pyx_t_3; double __pyx_t_4; double __pyx_t_5; int __pyx_t_6; __Pyx_RefNannySetupContext("test_face", 0); /* "_marching_cubes_lewiner_cy.pyx":1482 * * # Get face absolute value * cdef int absFace = face # <<<<<<<<<<<<<< * if face < 0: * absFace *= -1 */ __pyx_v_absFace = __pyx_v_face; /* "_marching_cubes_lewiner_cy.pyx":1483 * # Get face absolute value * cdef int absFace = face * if face < 0: # <<<<<<<<<<<<<< * absFace *= -1 * */ __pyx_t_1 = ((__pyx_v_face < 0) != 0); if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":1484 * cdef int absFace = face * if face < 0: * absFace *= -1 # <<<<<<<<<<<<<< * * # Get values of corners A B C D */ __pyx_v_absFace = (__pyx_v_absFace * -1L); /* "_marching_cubes_lewiner_cy.pyx":1483 * # Get face absolute value * cdef int absFace = face * if face < 0: # <<<<<<<<<<<<<< * absFace *= -1 * */ } /* "_marching_cubes_lewiner_cy.pyx":1488 * # Get values of corners A B C D * cdef double A, B, C, D * if absFace == 1: # <<<<<<<<<<<<<< * A, B, C, D = cell.v0, cell.v4, cell.v5, cell.v1 * elif absFace == 2: */ switch (__pyx_v_absFace) { case 1: /* "_marching_cubes_lewiner_cy.pyx":1489 * cdef double A, B, C, D * if absFace == 1: * A, B, C, D = cell.v0, cell.v4, cell.v5, cell.v1 # <<<<<<<<<<<<<< * elif absFace == 2: * A, B, C, D = cell.v1, cell.v5, cell.v6, cell.v2 */ __pyx_t_2 = __pyx_v_cell->v0; __pyx_t_3 = __pyx_v_cell->v4; __pyx_t_4 = __pyx_v_cell->v5; __pyx_t_5 = __pyx_v_cell->v1; __pyx_v_A = __pyx_t_2; __pyx_v_B = __pyx_t_3; __pyx_v_C = __pyx_t_4; __pyx_v_D = __pyx_t_5; /* "_marching_cubes_lewiner_cy.pyx":1488 * # Get values of corners A B C D * cdef double A, B, C, D * if absFace == 1: # <<<<<<<<<<<<<< * A, B, C, D = cell.v0, cell.v4, cell.v5, cell.v1 * elif absFace == 2: */ break; case 2: /* "_marching_cubes_lewiner_cy.pyx":1491 * A, B, C, D = cell.v0, cell.v4, cell.v5, cell.v1 * elif absFace == 2: * A, B, C, D = cell.v1, cell.v5, cell.v6, cell.v2 # <<<<<<<<<<<<<< * elif absFace == 3: * A, B, C, D = cell.v2, cell.v6, cell.v7, cell.v3 */ __pyx_t_5 = __pyx_v_cell->v1; __pyx_t_4 = __pyx_v_cell->v5; __pyx_t_3 = __pyx_v_cell->v6; __pyx_t_2 = __pyx_v_cell->v2; __pyx_v_A = __pyx_t_5; __pyx_v_B = __pyx_t_4; __pyx_v_C = __pyx_t_3; __pyx_v_D = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":1490 * if absFace == 1: * A, B, C, D = cell.v0, cell.v4, cell.v5, cell.v1 * elif absFace == 2: # <<<<<<<<<<<<<< * A, B, C, D = cell.v1, cell.v5, cell.v6, cell.v2 * elif absFace == 3: */ break; case 3: /* "_marching_cubes_lewiner_cy.pyx":1493 * A, B, C, D = cell.v1, cell.v5, cell.v6, cell.v2 * elif absFace == 3: * A, B, C, D = cell.v2, cell.v6, cell.v7, cell.v3 # <<<<<<<<<<<<<< * elif absFace == 4: * A, B, C, D = cell.v3, cell.v7, cell.v4, cell.v0 */ __pyx_t_2 = __pyx_v_cell->v2; __pyx_t_3 = __pyx_v_cell->v6; __pyx_t_4 = __pyx_v_cell->v7; __pyx_t_5 = __pyx_v_cell->v3; __pyx_v_A = __pyx_t_2; __pyx_v_B = __pyx_t_3; __pyx_v_C = __pyx_t_4; __pyx_v_D = __pyx_t_5; /* "_marching_cubes_lewiner_cy.pyx":1492 * elif absFace == 2: * A, B, C, D = cell.v1, cell.v5, cell.v6, cell.v2 * elif absFace == 3: # <<<<<<<<<<<<<< * A, B, C, D = cell.v2, cell.v6, cell.v7, cell.v3 * elif absFace == 4: */ break; case 4: /* "_marching_cubes_lewiner_cy.pyx":1495 * A, B, C, D = cell.v2, cell.v6, cell.v7, cell.v3 * elif absFace == 4: * A, B, C, D = cell.v3, cell.v7, cell.v4, cell.v0 # <<<<<<<<<<<<<< * elif absFace == 5: * A, B, C, D = cell.v0, cell.v3, cell.v2, cell.v1 */ __pyx_t_5 = __pyx_v_cell->v3; __pyx_t_4 = __pyx_v_cell->v7; __pyx_t_3 = __pyx_v_cell->v4; __pyx_t_2 = __pyx_v_cell->v0; __pyx_v_A = __pyx_t_5; __pyx_v_B = __pyx_t_4; __pyx_v_C = __pyx_t_3; __pyx_v_D = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":1494 * elif absFace == 3: * A, B, C, D = cell.v2, cell.v6, cell.v7, cell.v3 * elif absFace == 4: # <<<<<<<<<<<<<< * A, B, C, D = cell.v3, cell.v7, cell.v4, cell.v0 * elif absFace == 5: */ break; case 5: /* "_marching_cubes_lewiner_cy.pyx":1497 * A, B, C, D = cell.v3, cell.v7, cell.v4, cell.v0 * elif absFace == 5: * A, B, C, D = cell.v0, cell.v3, cell.v2, cell.v1 # <<<<<<<<<<<<<< * elif absFace == 6: * A, B, C, D = cell.v4, cell.v7, cell.v6, cell.v5 */ __pyx_t_2 = __pyx_v_cell->v0; __pyx_t_3 = __pyx_v_cell->v3; __pyx_t_4 = __pyx_v_cell->v2; __pyx_t_5 = __pyx_v_cell->v1; __pyx_v_A = __pyx_t_2; __pyx_v_B = __pyx_t_3; __pyx_v_C = __pyx_t_4; __pyx_v_D = __pyx_t_5; /* "_marching_cubes_lewiner_cy.pyx":1496 * elif absFace == 4: * A, B, C, D = cell.v3, cell.v7, cell.v4, cell.v0 * elif absFace == 5: # <<<<<<<<<<<<<< * A, B, C, D = cell.v0, cell.v3, cell.v2, cell.v1 * elif absFace == 6: */ break; case 6: /* "_marching_cubes_lewiner_cy.pyx":1499 * A, B, C, D = cell.v0, cell.v3, cell.v2, cell.v1 * elif absFace == 6: * A, B, C, D = cell.v4, cell.v7, cell.v6, cell.v5 # <<<<<<<<<<<<<< * * # Return sign */ __pyx_t_5 = __pyx_v_cell->v4; __pyx_t_4 = __pyx_v_cell->v7; __pyx_t_3 = __pyx_v_cell->v6; __pyx_t_2 = __pyx_v_cell->v5; __pyx_v_A = __pyx_t_5; __pyx_v_B = __pyx_t_4; __pyx_v_C = __pyx_t_3; __pyx_v_D = __pyx_t_2; /* "_marching_cubes_lewiner_cy.pyx":1498 * elif absFace == 5: * A, B, C, D = cell.v0, cell.v3, cell.v2, cell.v1 * elif absFace == 6: # <<<<<<<<<<<<<< * A, B, C, D = cell.v4, cell.v7, cell.v6, cell.v5 * */ break; default: break; } /* "_marching_cubes_lewiner_cy.pyx":1502 * * # Return sign * cdef double AC_BD = A*C - B*D # <<<<<<<<<<<<<< * if AC_BD > - FLT_EPSILON and AC_BD < FLT_EPSILON: * return face >= 0 */ __pyx_v_AC_BD = ((__pyx_v_A * __pyx_v_C) - (__pyx_v_B * __pyx_v_D)); /* "_marching_cubes_lewiner_cy.pyx":1503 * # Return sign * cdef double AC_BD = A*C - B*D * if AC_BD > - FLT_EPSILON and AC_BD < FLT_EPSILON: # <<<<<<<<<<<<<< * return face >= 0 * else: */ __pyx_t_6 = ((__pyx_v_AC_BD > (-__pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)) != 0); if (__pyx_t_6) { } else { __pyx_t_1 = __pyx_t_6; goto __pyx_L5_bool_binop_done; } __pyx_t_6 = ((__pyx_v_AC_BD < __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON) != 0); __pyx_t_1 = __pyx_t_6; __pyx_L5_bool_binop_done:; if (__pyx_t_1) { /* "_marching_cubes_lewiner_cy.pyx":1504 * cdef double AC_BD = A*C - B*D * if AC_BD > - FLT_EPSILON and AC_BD < FLT_EPSILON: * return face >= 0 # <<<<<<<<<<<<<< * else: * return face * A * AC_BD >= 0; # face and A invert signs */ __pyx_r = (__pyx_v_face >= 0); goto __pyx_L0; /* "_marching_cubes_lewiner_cy.pyx":1503 * # Return sign * cdef double AC_BD = A*C - B*D * if AC_BD > - FLT_EPSILON and AC_BD < FLT_EPSILON: # <<<<<<<<<<<<<< * return face >= 0 * else: */ } /* "_marching_cubes_lewiner_cy.pyx":1506 * return face >= 0 * else: * return face * A * AC_BD >= 0; # face and A invert signs # <<<<<<<<<<<<<< * * */ /*else*/ { __pyx_r = (((__pyx_v_face * __pyx_v_A) * __pyx_v_AC_BD) >= 0.0); goto __pyx_L0; } /* "_marching_cubes_lewiner_cy.pyx":1477 * * * cdef int test_face(Cell cell, int face): # <<<<<<<<<<<<<< * """ Return True of the face contains part of the surface. * """ */ /* function exit code */ __pyx_L0:; __Pyx_RefNannyFinishContext(); return __pyx_r; } /* "_marching_cubes_lewiner_cy.pyx":1509 * * * cdef int test_internal(Cell cell, LutProvider luts, int case, int config, int subconfig, int s): # <<<<<<<<<<<<<< * """ Return True of the face contains part of the surface. * """ */ static int __pyx_f_26_marching_cubes_lewiner_cy_test_internal(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell *__pyx_v_cell, struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *__pyx_v_luts, int __pyx_v_case, int __pyx_v_config, int __pyx_v_subconfig, int __pyx_v_s) { double __pyx_v_t; double __pyx_v_At; double __pyx_v_Bt; double __pyx_v_Ct; double __pyx_v_Dt; double __pyx_v_a; double __pyx_v_b; int __pyx_v_test; int __pyx_v_edge; int __pyx_r; __Pyx_RefNannyDeclarations double __pyx_t_1; double __pyx_t_2; double __pyx_t_3; double __pyx_t_4; int __pyx_t_5; int __pyx_t_6; PyObject *__pyx_t_7 = NULL; PyObject *__pyx_t_8 = NULL; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; __Pyx_RefNannySetupContext("test_internal", 0); /* "_marching_cubes_lewiner_cy.pyx":1515 * # Typedefs * cdef double t, At, Bt, Ct, Dt, a, b * cdef int test = 0 # <<<<<<<<<<<<<< * cdef int edge = -1 # reference edge of the triangulation * */ __pyx_v_test = 0; /* "_marching_cubes_lewiner_cy.pyx":1516 * cdef double t, At, Bt, Ct, Dt, a, b * cdef int test = 0 * cdef int edge = -1 # reference edge of the triangulation # <<<<<<<<<<<<<< * * */ __pyx_v_edge = -1; /* "_marching_cubes_lewiner_cy.pyx":1521 * # Calculate At Bt Ct Dt a b * # Select case 4, 10, 7, 12, 13 * At, Bt, Ct, Dt = 0.0, 0.0, 0.0, 0.0 # <<<<<<<<<<<<<< * * if case==4 or case==10: */ __pyx_t_1 = 0.0; __pyx_t_2 = 0.0; __pyx_t_3 = 0.0; __pyx_t_4 = 0.0; __pyx_v_At = __pyx_t_1; __pyx_v_Bt = __pyx_t_2; __pyx_v_Ct = __pyx_t_3; __pyx_v_Dt = __pyx_t_4; /* "_marching_cubes_lewiner_cy.pyx":1523 * At, Bt, Ct, Dt = 0.0, 0.0, 0.0, 0.0 * * if case==4 or case==10: # <<<<<<<<<<<<<< * a = ( cell.v4 - cell.v0 ) * ( cell.v6 - cell.v2 ) - ( cell.v7 - cell.v3 ) * ( cell.v5 - cell.v1 ) * b = cell.v2 * ( cell.v4 - cell.v0 ) + cell.v0 * ( cell.v6 - cell.v2 ) - cell.v1 * ( cell.v7 - cell.v3 ) - cell.v3 * ( cell.v5 - cell.v1 ) */ switch (__pyx_v_case) { case 4: case 10: /* "_marching_cubes_lewiner_cy.pyx":1524 * * if case==4 or case==10: * a = ( cell.v4 - cell.v0 ) * ( cell.v6 - cell.v2 ) - ( cell.v7 - cell.v3 ) * ( cell.v5 - cell.v1 ) # <<<<<<<<<<<<<< * b = cell.v2 * ( cell.v4 - cell.v0 ) + cell.v0 * ( cell.v6 - cell.v2 ) - cell.v1 * ( cell.v7 - cell.v3 ) - cell.v3 * ( cell.v5 - cell.v1 ) * t = - b / (2*a + FLT_EPSILON) */ __pyx_v_a = (((__pyx_v_cell->v4 - __pyx_v_cell->v0) * (__pyx_v_cell->v6 - __pyx_v_cell->v2)) - ((__pyx_v_cell->v7 - __pyx_v_cell->v3) * (__pyx_v_cell->v5 - __pyx_v_cell->v1))); /* "_marching_cubes_lewiner_cy.pyx":1525 * if case==4 or case==10: * a = ( cell.v4 - cell.v0 ) * ( cell.v6 - cell.v2 ) - ( cell.v7 - cell.v3 ) * ( cell.v5 - cell.v1 ) * b = cell.v2 * ( cell.v4 - cell.v0 ) + cell.v0 * ( cell.v6 - cell.v2 ) - cell.v1 * ( cell.v7 - cell.v3 ) - cell.v3 * ( cell.v5 - cell.v1 ) # <<<<<<<<<<<<<< * t = - b / (2*a + FLT_EPSILON) * if t<0 or t>1: return s>0 ; */ __pyx_v_b = ((((__pyx_v_cell->v2 * (__pyx_v_cell->v4 - __pyx_v_cell->v0)) + (__pyx_v_cell->v0 * (__pyx_v_cell->v6 - __pyx_v_cell->v2))) - (__pyx_v_cell->v1 * (__pyx_v_cell->v7 - __pyx_v_cell->v3))) - (__pyx_v_cell->v3 * (__pyx_v_cell->v5 - __pyx_v_cell->v1))); /* "_marching_cubes_lewiner_cy.pyx":1526 * a = ( cell.v4 - cell.v0 ) * ( cell.v6 - cell.v2 ) - ( cell.v7 - cell.v3 ) * ( cell.v5 - cell.v1 ) * b = cell.v2 * ( cell.v4 - cell.v0 ) + cell.v0 * ( cell.v6 - cell.v2 ) - cell.v1 * ( cell.v7 - cell.v3 ) - cell.v3 * ( cell.v5 - cell.v1 ) * t = - b / (2*a + FLT_EPSILON) # <<<<<<<<<<<<<< * if t<0 or t>1: return s>0 ; * */ __pyx_v_t = ((-__pyx_v_b) / ((2.0 * __pyx_v_a) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1527 * b = cell.v2 * ( cell.v4 - cell.v0 ) + cell.v0 * ( cell.v6 - cell.v2 ) - cell.v1 * ( cell.v7 - cell.v3 ) - cell.v3 * ( cell.v5 - cell.v1 ) * t = - b / (2*a + FLT_EPSILON) * if t<0 or t>1: return s>0 ; # <<<<<<<<<<<<<< * * At = cell.v0 + ( cell.v4 - cell.v0 ) * t */ __pyx_t_6 = ((__pyx_v_t < 0.0) != 0); if (!__pyx_t_6) { } else { __pyx_t_5 = __pyx_t_6; goto __pyx_L4_bool_binop_done; } __pyx_t_6 = ((__pyx_v_t > 1.0) != 0); __pyx_t_5 = __pyx_t_6; __pyx_L4_bool_binop_done:; if (__pyx_t_5) { __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; } /* "_marching_cubes_lewiner_cy.pyx":1529 * if t<0 or t>1: return s>0 ; * * At = cell.v0 + ( cell.v4 - cell.v0 ) * t # <<<<<<<<<<<<<< * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t */ __pyx_v_At = (__pyx_v_cell->v0 + ((__pyx_v_cell->v4 - __pyx_v_cell->v0) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1530 * * At = cell.v0 + ( cell.v4 - cell.v0 ) * t * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t # <<<<<<<<<<<<<< * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v3 + ((__pyx_v_cell->v7 - __pyx_v_cell->v3) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1531 * At = cell.v0 + ( cell.v4 - cell.v0 ) * t * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t # <<<<<<<<<<<<<< * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t * */ __pyx_v_Ct = (__pyx_v_cell->v2 + ((__pyx_v_cell->v6 - __pyx_v_cell->v2) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1532 * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t # <<<<<<<<<<<<<< * * elif case==6 or case==7 or case==12 or case==13: */ __pyx_v_Dt = (__pyx_v_cell->v1 + ((__pyx_v_cell->v5 - __pyx_v_cell->v1) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1523 * At, Bt, Ct, Dt = 0.0, 0.0, 0.0, 0.0 * * if case==4 or case==10: # <<<<<<<<<<<<<< * a = ( cell.v4 - cell.v0 ) * ( cell.v6 - cell.v2 ) - ( cell.v7 - cell.v3 ) * ( cell.v5 - cell.v1 ) * b = cell.v2 * ( cell.v4 - cell.v0 ) + cell.v0 * ( cell.v6 - cell.v2 ) - cell.v1 * ( cell.v7 - cell.v3 ) - cell.v3 * ( cell.v5 - cell.v1 ) */ break; case 6: /* "_marching_cubes_lewiner_cy.pyx":1534 * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t * * elif case==6 or case==7 or case==12 or case==13: # <<<<<<<<<<<<<< * # Define edge * if case == 6: edge = luts.TEST6.get2(config, 2) */ case 7: case 12: case 13: /* "_marching_cubes_lewiner_cy.pyx":1536 * elif case==6 or case==7 or case==12 or case==13: * # Define edge * if case == 6: edge = luts.TEST6.get2(config, 2) # <<<<<<<<<<<<<< * elif case == 7: edge = luts.TEST7.get2(config, 4) * elif case == 12: edge = luts.TEST12.get2(config, 3) */ switch (__pyx_v_case) { case 6: __pyx_v_edge = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST6->__pyx_vtab)->get2(__pyx_v_luts->TEST6, __pyx_v_config, 2); break; case 7: /* "_marching_cubes_lewiner_cy.pyx":1537 * # Define edge * if case == 6: edge = luts.TEST6.get2(config, 2) * elif case == 7: edge = luts.TEST7.get2(config, 4) # <<<<<<<<<<<<<< * elif case == 12: edge = luts.TEST12.get2(config, 3) * elif case == 13: edge = luts.TILING13_5_1.get3(config, subconfig, 0) */ __pyx_v_edge = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST7->__pyx_vtab)->get2(__pyx_v_luts->TEST7, __pyx_v_config, 4); break; case 12: /* "_marching_cubes_lewiner_cy.pyx":1538 * if case == 6: edge = luts.TEST6.get2(config, 2) * elif case == 7: edge = luts.TEST7.get2(config, 4) * elif case == 12: edge = luts.TEST12.get2(config, 3) # <<<<<<<<<<<<<< * elif case == 13: edge = luts.TILING13_5_1.get3(config, subconfig, 0) * */ __pyx_v_edge = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TEST12->__pyx_vtab)->get2(__pyx_v_luts->TEST12, __pyx_v_config, 3); break; case 13: /* "_marching_cubes_lewiner_cy.pyx":1539 * elif case == 7: edge = luts.TEST7.get2(config, 4) * elif case == 12: edge = luts.TEST12.get2(config, 3) * elif case == 13: edge = luts.TILING13_5_1.get3(config, subconfig, 0) # <<<<<<<<<<<<<< * * if edge==0: */ __pyx_v_edge = ((struct __pyx_vtabstruct_26_marching_cubes_lewiner_cy_Lut *)__pyx_v_luts->TILING13_5_1->__pyx_vtab)->get3(__pyx_v_luts->TILING13_5_1, __pyx_v_config, __pyx_v_subconfig, 0); break; default: break; } /* "_marching_cubes_lewiner_cy.pyx":1541 * elif case == 13: edge = luts.TILING13_5_1.get3(config, subconfig, 0) * * if edge==0: # <<<<<<<<<<<<<< * t = cell.v0 / ( cell.v0 - cell.v1 + FLT_EPSILON ) * At = 0 */ switch (__pyx_v_edge) { case 0: /* "_marching_cubes_lewiner_cy.pyx":1542 * * if edge==0: * t = cell.v0 / ( cell.v0 - cell.v1 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v3 + ( cell.v2 - cell.v3 ) * t */ __pyx_v_t = (__pyx_v_cell->v0 / ((__pyx_v_cell->v0 - __pyx_v_cell->v1) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1543 * if edge==0: * t = cell.v0 / ( cell.v0 - cell.v1 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v3 + ( cell.v2 - cell.v3 ) * t * Ct = cell.v7 + ( cell.v6 - cell.v7 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1544 * t = cell.v0 / ( cell.v0 - cell.v1 + FLT_EPSILON ) * At = 0 * Bt = cell.v3 + ( cell.v2 - cell.v3 ) * t # <<<<<<<<<<<<<< * Ct = cell.v7 + ( cell.v6 - cell.v7 ) * t * Dt = cell.v4 + ( cell.v5 - cell.v4 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v3 + ((__pyx_v_cell->v2 - __pyx_v_cell->v3) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1545 * At = 0 * Bt = cell.v3 + ( cell.v2 - cell.v3 ) * t * Ct = cell.v7 + ( cell.v6 - cell.v7 ) * t # <<<<<<<<<<<<<< * Dt = cell.v4 + ( cell.v5 - cell.v4 ) * t * elif edge==1: */ __pyx_v_Ct = (__pyx_v_cell->v7 + ((__pyx_v_cell->v6 - __pyx_v_cell->v7) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1546 * Bt = cell.v3 + ( cell.v2 - cell.v3 ) * t * Ct = cell.v7 + ( cell.v6 - cell.v7 ) * t * Dt = cell.v4 + ( cell.v5 - cell.v4 ) * t # <<<<<<<<<<<<<< * elif edge==1: * t = cell.v1 / ( cell.v1 - cell.v2 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v4 + ((__pyx_v_cell->v5 - __pyx_v_cell->v4) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1541 * elif case == 13: edge = luts.TILING13_5_1.get3(config, subconfig, 0) * * if edge==0: # <<<<<<<<<<<<<< * t = cell.v0 / ( cell.v0 - cell.v1 + FLT_EPSILON ) * At = 0 */ break; case 1: /* "_marching_cubes_lewiner_cy.pyx":1548 * Dt = cell.v4 + ( cell.v5 - cell.v4 ) * t * elif edge==1: * t = cell.v1 / ( cell.v1 - cell.v2 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v0 + ( cell.v3 - cell.v0 ) * t */ __pyx_v_t = (__pyx_v_cell->v1 / ((__pyx_v_cell->v1 - __pyx_v_cell->v2) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1549 * elif edge==1: * t = cell.v1 / ( cell.v1 - cell.v2 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v0 + ( cell.v3 - cell.v0 ) * t * Ct = cell.v4 + ( cell.v7 - cell.v4 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1550 * t = cell.v1 / ( cell.v1 - cell.v2 + FLT_EPSILON ) * At = 0 * Bt = cell.v0 + ( cell.v3 - cell.v0 ) * t # <<<<<<<<<<<<<< * Ct = cell.v4 + ( cell.v7 - cell.v4 ) * t * Dt = cell.v5 + ( cell.v6 - cell.v5 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v0 + ((__pyx_v_cell->v3 - __pyx_v_cell->v0) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1551 * At = 0 * Bt = cell.v0 + ( cell.v3 - cell.v0 ) * t * Ct = cell.v4 + ( cell.v7 - cell.v4 ) * t # <<<<<<<<<<<<<< * Dt = cell.v5 + ( cell.v6 - cell.v5 ) * t * elif edge==2: */ __pyx_v_Ct = (__pyx_v_cell->v4 + ((__pyx_v_cell->v7 - __pyx_v_cell->v4) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1552 * Bt = cell.v0 + ( cell.v3 - cell.v0 ) * t * Ct = cell.v4 + ( cell.v7 - cell.v4 ) * t * Dt = cell.v5 + ( cell.v6 - cell.v5 ) * t # <<<<<<<<<<<<<< * elif edge==2: * t = cell.v2 / ( cell.v2 - cell.v3 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v5 + ((__pyx_v_cell->v6 - __pyx_v_cell->v5) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1547 * Ct = cell.v7 + ( cell.v6 - cell.v7 ) * t * Dt = cell.v4 + ( cell.v5 - cell.v4 ) * t * elif edge==1: # <<<<<<<<<<<<<< * t = cell.v1 / ( cell.v1 - cell.v2 + FLT_EPSILON ) * At = 0 */ break; case 2: /* "_marching_cubes_lewiner_cy.pyx":1554 * Dt = cell.v5 + ( cell.v6 - cell.v5 ) * t * elif edge==2: * t = cell.v2 / ( cell.v2 - cell.v3 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v1 + ( cell.v0 - cell.v1 ) * t */ __pyx_v_t = (__pyx_v_cell->v2 / ((__pyx_v_cell->v2 - __pyx_v_cell->v3) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1555 * elif edge==2: * t = cell.v2 / ( cell.v2 - cell.v3 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v1 + ( cell.v0 - cell.v1 ) * t * Ct = cell.v5 + ( cell.v4 - cell.v5 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1556 * t = cell.v2 / ( cell.v2 - cell.v3 + FLT_EPSILON ) * At = 0 * Bt = cell.v1 + ( cell.v0 - cell.v1 ) * t # <<<<<<<<<<<<<< * Ct = cell.v5 + ( cell.v4 - cell.v5 ) * t * Dt = cell.v6 + ( cell.v7 - cell.v6 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v1 + ((__pyx_v_cell->v0 - __pyx_v_cell->v1) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1557 * At = 0 * Bt = cell.v1 + ( cell.v0 - cell.v1 ) * t * Ct = cell.v5 + ( cell.v4 - cell.v5 ) * t # <<<<<<<<<<<<<< * Dt = cell.v6 + ( cell.v7 - cell.v6 ) * t * elif edge==3: */ __pyx_v_Ct = (__pyx_v_cell->v5 + ((__pyx_v_cell->v4 - __pyx_v_cell->v5) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1558 * Bt = cell.v1 + ( cell.v0 - cell.v1 ) * t * Ct = cell.v5 + ( cell.v4 - cell.v5 ) * t * Dt = cell.v6 + ( cell.v7 - cell.v6 ) * t # <<<<<<<<<<<<<< * elif edge==3: * t = cell.v3 / ( cell.v3 - cell.v0 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v6 + ((__pyx_v_cell->v7 - __pyx_v_cell->v6) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1553 * Ct = cell.v4 + ( cell.v7 - cell.v4 ) * t * Dt = cell.v5 + ( cell.v6 - cell.v5 ) * t * elif edge==2: # <<<<<<<<<<<<<< * t = cell.v2 / ( cell.v2 - cell.v3 + FLT_EPSILON ) * At = 0 */ break; case 3: /* "_marching_cubes_lewiner_cy.pyx":1560 * Dt = cell.v6 + ( cell.v7 - cell.v6 ) * t * elif edge==3: * t = cell.v3 / ( cell.v3 - cell.v0 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v2 + ( cell.v1 - cell.v2 ) * t */ __pyx_v_t = (__pyx_v_cell->v3 / ((__pyx_v_cell->v3 - __pyx_v_cell->v0) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1561 * elif edge==3: * t = cell.v3 / ( cell.v3 - cell.v0 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v2 + ( cell.v1 - cell.v2 ) * t * Ct = cell.v6 + ( cell.v5 - cell.v6 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1562 * t = cell.v3 / ( cell.v3 - cell.v0 + FLT_EPSILON ) * At = 0 * Bt = cell.v2 + ( cell.v1 - cell.v2 ) * t # <<<<<<<<<<<<<< * Ct = cell.v6 + ( cell.v5 - cell.v6 ) * t * Dt = cell.v7 + ( cell.v4 - cell.v7 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v2 + ((__pyx_v_cell->v1 - __pyx_v_cell->v2) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1563 * At = 0 * Bt = cell.v2 + ( cell.v1 - cell.v2 ) * t * Ct = cell.v6 + ( cell.v5 - cell.v6 ) * t # <<<<<<<<<<<<<< * Dt = cell.v7 + ( cell.v4 - cell.v7 ) * t * elif edge==4: */ __pyx_v_Ct = (__pyx_v_cell->v6 + ((__pyx_v_cell->v5 - __pyx_v_cell->v6) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1564 * Bt = cell.v2 + ( cell.v1 - cell.v2 ) * t * Ct = cell.v6 + ( cell.v5 - cell.v6 ) * t * Dt = cell.v7 + ( cell.v4 - cell.v7 ) * t # <<<<<<<<<<<<<< * elif edge==4: * t = cell.v4 / ( cell.v4 - cell.v5 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v7 + ((__pyx_v_cell->v4 - __pyx_v_cell->v7) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1559 * Ct = cell.v5 + ( cell.v4 - cell.v5 ) * t * Dt = cell.v6 + ( cell.v7 - cell.v6 ) * t * elif edge==3: # <<<<<<<<<<<<<< * t = cell.v3 / ( cell.v3 - cell.v0 + FLT_EPSILON ) * At = 0 */ break; case 4: /* "_marching_cubes_lewiner_cy.pyx":1566 * Dt = cell.v7 + ( cell.v4 - cell.v7 ) * t * elif edge==4: * t = cell.v4 / ( cell.v4 - cell.v5 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v7 + ( cell.v6 - cell.v7 ) * t */ __pyx_v_t = (__pyx_v_cell->v4 / ((__pyx_v_cell->v4 - __pyx_v_cell->v5) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1567 * elif edge==4: * t = cell.v4 / ( cell.v4 - cell.v5 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v7 + ( cell.v6 - cell.v7 ) * t * Ct = cell.v3 + ( cell.v2 - cell.v3 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1568 * t = cell.v4 / ( cell.v4 - cell.v5 + FLT_EPSILON ) * At = 0 * Bt = cell.v7 + ( cell.v6 - cell.v7 ) * t # <<<<<<<<<<<<<< * Ct = cell.v3 + ( cell.v2 - cell.v3 ) * t * Dt = cell.v0 + ( cell.v1 - cell.v0 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v7 + ((__pyx_v_cell->v6 - __pyx_v_cell->v7) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1569 * At = 0 * Bt = cell.v7 + ( cell.v6 - cell.v7 ) * t * Ct = cell.v3 + ( cell.v2 - cell.v3 ) * t # <<<<<<<<<<<<<< * Dt = cell.v0 + ( cell.v1 - cell.v0 ) * t * elif edge==5: */ __pyx_v_Ct = (__pyx_v_cell->v3 + ((__pyx_v_cell->v2 - __pyx_v_cell->v3) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1570 * Bt = cell.v7 + ( cell.v6 - cell.v7 ) * t * Ct = cell.v3 + ( cell.v2 - cell.v3 ) * t * Dt = cell.v0 + ( cell.v1 - cell.v0 ) * t # <<<<<<<<<<<<<< * elif edge==5: * t = cell.v5 / ( cell.v5 - cell.v6 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v0 + ((__pyx_v_cell->v1 - __pyx_v_cell->v0) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1565 * Ct = cell.v6 + ( cell.v5 - cell.v6 ) * t * Dt = cell.v7 + ( cell.v4 - cell.v7 ) * t * elif edge==4: # <<<<<<<<<<<<<< * t = cell.v4 / ( cell.v4 - cell.v5 + FLT_EPSILON ) * At = 0 */ break; case 5: /* "_marching_cubes_lewiner_cy.pyx":1572 * Dt = cell.v0 + ( cell.v1 - cell.v0 ) * t * elif edge==5: * t = cell.v5 / ( cell.v5 - cell.v6 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v4 + ( cell.v7 - cell.v4 ) * t */ __pyx_v_t = (__pyx_v_cell->v5 / ((__pyx_v_cell->v5 - __pyx_v_cell->v6) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1573 * elif edge==5: * t = cell.v5 / ( cell.v5 - cell.v6 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v4 + ( cell.v7 - cell.v4 ) * t * Ct = cell.v0 + ( cell.v3 - cell.v0 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1574 * t = cell.v5 / ( cell.v5 - cell.v6 + FLT_EPSILON ) * At = 0 * Bt = cell.v4 + ( cell.v7 - cell.v4 ) * t # <<<<<<<<<<<<<< * Ct = cell.v0 + ( cell.v3 - cell.v0 ) * t * Dt = cell.v1 + ( cell.v2 - cell.v1 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v4 + ((__pyx_v_cell->v7 - __pyx_v_cell->v4) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1575 * At = 0 * Bt = cell.v4 + ( cell.v7 - cell.v4 ) * t * Ct = cell.v0 + ( cell.v3 - cell.v0 ) * t # <<<<<<<<<<<<<< * Dt = cell.v1 + ( cell.v2 - cell.v1 ) * t * elif edge==6: */ __pyx_v_Ct = (__pyx_v_cell->v0 + ((__pyx_v_cell->v3 - __pyx_v_cell->v0) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1576 * Bt = cell.v4 + ( cell.v7 - cell.v4 ) * t * Ct = cell.v0 + ( cell.v3 - cell.v0 ) * t * Dt = cell.v1 + ( cell.v2 - cell.v1 ) * t # <<<<<<<<<<<<<< * elif edge==6: * t = cell.v6 / ( cell.v6 - cell.v7 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v1 + ((__pyx_v_cell->v2 - __pyx_v_cell->v1) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1571 * Ct = cell.v3 + ( cell.v2 - cell.v3 ) * t * Dt = cell.v0 + ( cell.v1 - cell.v0 ) * t * elif edge==5: # <<<<<<<<<<<<<< * t = cell.v5 / ( cell.v5 - cell.v6 + FLT_EPSILON ) * At = 0 */ break; case 6: /* "_marching_cubes_lewiner_cy.pyx":1578 * Dt = cell.v1 + ( cell.v2 - cell.v1 ) * t * elif edge==6: * t = cell.v6 / ( cell.v6 - cell.v7 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v5 + ( cell.v4 - cell.v5 ) * t */ __pyx_v_t = (__pyx_v_cell->v6 / ((__pyx_v_cell->v6 - __pyx_v_cell->v7) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1579 * elif edge==6: * t = cell.v6 / ( cell.v6 - cell.v7 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v5 + ( cell.v4 - cell.v5 ) * t * Ct = cell.v1 + ( cell.v0 - cell.v1 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1580 * t = cell.v6 / ( cell.v6 - cell.v7 + FLT_EPSILON ) * At = 0 * Bt = cell.v5 + ( cell.v4 - cell.v5 ) * t # <<<<<<<<<<<<<< * Ct = cell.v1 + ( cell.v0 - cell.v1 ) * t * Dt = cell.v2 + ( cell.v3 - cell.v2 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v5 + ((__pyx_v_cell->v4 - __pyx_v_cell->v5) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1581 * At = 0 * Bt = cell.v5 + ( cell.v4 - cell.v5 ) * t * Ct = cell.v1 + ( cell.v0 - cell.v1 ) * t # <<<<<<<<<<<<<< * Dt = cell.v2 + ( cell.v3 - cell.v2 ) * t * elif edge==7: */ __pyx_v_Ct = (__pyx_v_cell->v1 + ((__pyx_v_cell->v0 - __pyx_v_cell->v1) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1582 * Bt = cell.v5 + ( cell.v4 - cell.v5 ) * t * Ct = cell.v1 + ( cell.v0 - cell.v1 ) * t * Dt = cell.v2 + ( cell.v3 - cell.v2 ) * t # <<<<<<<<<<<<<< * elif edge==7: * t = cell.v7 / ( cell.v7 - cell.v4 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v2 + ((__pyx_v_cell->v3 - __pyx_v_cell->v2) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1577 * Ct = cell.v0 + ( cell.v3 - cell.v0 ) * t * Dt = cell.v1 + ( cell.v2 - cell.v1 ) * t * elif edge==6: # <<<<<<<<<<<<<< * t = cell.v6 / ( cell.v6 - cell.v7 + FLT_EPSILON ) * At = 0 */ break; case 7: /* "_marching_cubes_lewiner_cy.pyx":1584 * Dt = cell.v2 + ( cell.v3 - cell.v2 ) * t * elif edge==7: * t = cell.v7 / ( cell.v7 - cell.v4 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v6 + ( cell.v5 - cell.v6 ) * t */ __pyx_v_t = (__pyx_v_cell->v7 / ((__pyx_v_cell->v7 - __pyx_v_cell->v4) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1585 * elif edge==7: * t = cell.v7 / ( cell.v7 - cell.v4 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v6 + ( cell.v5 - cell.v6 ) * t * Ct = cell.v2 + ( cell.v1 - cell.v2 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1586 * t = cell.v7 / ( cell.v7 - cell.v4 + FLT_EPSILON ) * At = 0 * Bt = cell.v6 + ( cell.v5 - cell.v6 ) * t # <<<<<<<<<<<<<< * Ct = cell.v2 + ( cell.v1 - cell.v2 ) * t * Dt = cell.v3 + ( cell.v0 - cell.v3 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v6 + ((__pyx_v_cell->v5 - __pyx_v_cell->v6) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1587 * At = 0 * Bt = cell.v6 + ( cell.v5 - cell.v6 ) * t * Ct = cell.v2 + ( cell.v1 - cell.v2 ) * t # <<<<<<<<<<<<<< * Dt = cell.v3 + ( cell.v0 - cell.v3 ) * t * elif edge==8: */ __pyx_v_Ct = (__pyx_v_cell->v2 + ((__pyx_v_cell->v1 - __pyx_v_cell->v2) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1588 * Bt = cell.v6 + ( cell.v5 - cell.v6 ) * t * Ct = cell.v2 + ( cell.v1 - cell.v2 ) * t * Dt = cell.v3 + ( cell.v0 - cell.v3 ) * t # <<<<<<<<<<<<<< * elif edge==8: * t = cell.v0 / ( cell.v0 - cell.v4 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v3 + ((__pyx_v_cell->v0 - __pyx_v_cell->v3) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1583 * Ct = cell.v1 + ( cell.v0 - cell.v1 ) * t * Dt = cell.v2 + ( cell.v3 - cell.v2 ) * t * elif edge==7: # <<<<<<<<<<<<<< * t = cell.v7 / ( cell.v7 - cell.v4 + FLT_EPSILON ) * At = 0 */ break; case 8: /* "_marching_cubes_lewiner_cy.pyx":1590 * Dt = cell.v3 + ( cell.v0 - cell.v3 ) * t * elif edge==8: * t = cell.v0 / ( cell.v0 - cell.v4 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t */ __pyx_v_t = (__pyx_v_cell->v0 / ((__pyx_v_cell->v0 - __pyx_v_cell->v4) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1591 * elif edge==8: * t = cell.v0 / ( cell.v0 - cell.v4 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1592 * t = cell.v0 / ( cell.v0 - cell.v4 + FLT_EPSILON ) * At = 0 * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t # <<<<<<<<<<<<<< * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v3 + ((__pyx_v_cell->v7 - __pyx_v_cell->v3) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1593 * At = 0 * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t # <<<<<<<<<<<<<< * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t * elif edge==9: */ __pyx_v_Ct = (__pyx_v_cell->v2 + ((__pyx_v_cell->v6 - __pyx_v_cell->v2) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1594 * Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t # <<<<<<<<<<<<<< * elif edge==9: * t = cell.v1 / ( cell.v1 - cell.v5 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v1 + ((__pyx_v_cell->v5 - __pyx_v_cell->v1) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1589 * Ct = cell.v2 + ( cell.v1 - cell.v2 ) * t * Dt = cell.v3 + ( cell.v0 - cell.v3 ) * t * elif edge==8: # <<<<<<<<<<<<<< * t = cell.v0 / ( cell.v0 - cell.v4 + FLT_EPSILON ) * At = 0 */ break; case 9: /* "_marching_cubes_lewiner_cy.pyx":1596 * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t * elif edge==9: * t = cell.v1 / ( cell.v1 - cell.v5 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v0 + ( cell.v4 - cell.v0 ) * t */ __pyx_v_t = (__pyx_v_cell->v1 / ((__pyx_v_cell->v1 - __pyx_v_cell->v5) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1597 * elif edge==9: * t = cell.v1 / ( cell.v1 - cell.v5 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v0 + ( cell.v4 - cell.v0 ) * t * Ct = cell.v3 + ( cell.v7 - cell.v3 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1598 * t = cell.v1 / ( cell.v1 - cell.v5 + FLT_EPSILON ) * At = 0 * Bt = cell.v0 + ( cell.v4 - cell.v0 ) * t # <<<<<<<<<<<<<< * Ct = cell.v3 + ( cell.v7 - cell.v3 ) * t * Dt = cell.v2 + ( cell.v6 - cell.v2 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v0 + ((__pyx_v_cell->v4 - __pyx_v_cell->v0) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1599 * At = 0 * Bt = cell.v0 + ( cell.v4 - cell.v0 ) * t * Ct = cell.v3 + ( cell.v7 - cell.v3 ) * t # <<<<<<<<<<<<<< * Dt = cell.v2 + ( cell.v6 - cell.v2 ) * t * elif edge==10: */ __pyx_v_Ct = (__pyx_v_cell->v3 + ((__pyx_v_cell->v7 - __pyx_v_cell->v3) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1600 * Bt = cell.v0 + ( cell.v4 - cell.v0 ) * t * Ct = cell.v3 + ( cell.v7 - cell.v3 ) * t * Dt = cell.v2 + ( cell.v6 - cell.v2 ) * t # <<<<<<<<<<<<<< * elif edge==10: * t = cell.v2 / ( cell.v2 - cell.v6 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v2 + ((__pyx_v_cell->v6 - __pyx_v_cell->v2) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1595 * Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t * elif edge==9: # <<<<<<<<<<<<<< * t = cell.v1 / ( cell.v1 - cell.v5 + FLT_EPSILON ) * At = 0 */ break; case 10: /* "_marching_cubes_lewiner_cy.pyx":1602 * Dt = cell.v2 + ( cell.v6 - cell.v2 ) * t * elif edge==10: * t = cell.v2 / ( cell.v2 - cell.v6 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v1 + ( cell.v5 - cell.v1 ) * t */ __pyx_v_t = (__pyx_v_cell->v2 / ((__pyx_v_cell->v2 - __pyx_v_cell->v6) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1603 * elif edge==10: * t = cell.v2 / ( cell.v2 - cell.v6 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v1 + ( cell.v5 - cell.v1 ) * t * Ct = cell.v0 + ( cell.v4 - cell.v0 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1604 * t = cell.v2 / ( cell.v2 - cell.v6 + FLT_EPSILON ) * At = 0 * Bt = cell.v1 + ( cell.v5 - cell.v1 ) * t # <<<<<<<<<<<<<< * Ct = cell.v0 + ( cell.v4 - cell.v0 ) * t * Dt = cell.v3 + ( cell.v7 - cell.v3 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v1 + ((__pyx_v_cell->v5 - __pyx_v_cell->v1) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1605 * At = 0 * Bt = cell.v1 + ( cell.v5 - cell.v1 ) * t * Ct = cell.v0 + ( cell.v4 - cell.v0 ) * t # <<<<<<<<<<<<<< * Dt = cell.v3 + ( cell.v7 - cell.v3 ) * t * elif edge==11: */ __pyx_v_Ct = (__pyx_v_cell->v0 + ((__pyx_v_cell->v4 - __pyx_v_cell->v0) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1606 * Bt = cell.v1 + ( cell.v5 - cell.v1 ) * t * Ct = cell.v0 + ( cell.v4 - cell.v0 ) * t * Dt = cell.v3 + ( cell.v7 - cell.v3 ) * t # <<<<<<<<<<<<<< * elif edge==11: * t = cell.v3 / ( cell.v3 - cell.v7 + FLT_EPSILON ) */ __pyx_v_Dt = (__pyx_v_cell->v3 + ((__pyx_v_cell->v7 - __pyx_v_cell->v3) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1601 * Ct = cell.v3 + ( cell.v7 - cell.v3 ) * t * Dt = cell.v2 + ( cell.v6 - cell.v2 ) * t * elif edge==10: # <<<<<<<<<<<<<< * t = cell.v2 / ( cell.v2 - cell.v6 + FLT_EPSILON ) * At = 0 */ break; case 11: /* "_marching_cubes_lewiner_cy.pyx":1608 * Dt = cell.v3 + ( cell.v7 - cell.v3 ) * t * elif edge==11: * t = cell.v3 / ( cell.v3 - cell.v7 + FLT_EPSILON ) # <<<<<<<<<<<<<< * At = 0 * Bt = cell.v2 + ( cell.v6 - cell.v2 ) * t */ __pyx_v_t = (__pyx_v_cell->v3 / ((__pyx_v_cell->v3 - __pyx_v_cell->v7) + __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON)); /* "_marching_cubes_lewiner_cy.pyx":1609 * elif edge==11: * t = cell.v3 / ( cell.v3 - cell.v7 + FLT_EPSILON ) * At = 0 # <<<<<<<<<<<<<< * Bt = cell.v2 + ( cell.v6 - cell.v2 ) * t * Ct = cell.v1 + ( cell.v5 - cell.v1 ) * t */ __pyx_v_At = 0.0; /* "_marching_cubes_lewiner_cy.pyx":1610 * t = cell.v3 / ( cell.v3 - cell.v7 + FLT_EPSILON ) * At = 0 * Bt = cell.v2 + ( cell.v6 - cell.v2 ) * t # <<<<<<<<<<<<<< * Ct = cell.v1 + ( cell.v5 - cell.v1 ) * t * Dt = cell.v0 + ( cell.v4 - cell.v0 ) * t */ __pyx_v_Bt = (__pyx_v_cell->v2 + ((__pyx_v_cell->v6 - __pyx_v_cell->v2) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1611 * At = 0 * Bt = cell.v2 + ( cell.v6 - cell.v2 ) * t * Ct = cell.v1 + ( cell.v5 - cell.v1 ) * t # <<<<<<<<<<<<<< * Dt = cell.v0 + ( cell.v4 - cell.v0 ) * t * else: */ __pyx_v_Ct = (__pyx_v_cell->v1 + ((__pyx_v_cell->v5 - __pyx_v_cell->v1) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1612 * Bt = cell.v2 + ( cell.v6 - cell.v2 ) * t * Ct = cell.v1 + ( cell.v5 - cell.v1 ) * t * Dt = cell.v0 + ( cell.v4 - cell.v0 ) * t # <<<<<<<<<<<<<< * else: * print( "Invalid edge %i." % edge ) */ __pyx_v_Dt = (__pyx_v_cell->v0 + ((__pyx_v_cell->v4 - __pyx_v_cell->v0) * __pyx_v_t)); /* "_marching_cubes_lewiner_cy.pyx":1607 * Ct = cell.v0 + ( cell.v4 - cell.v0 ) * t * Dt = cell.v3 + ( cell.v7 - cell.v3 ) * t * elif edge==11: # <<<<<<<<<<<<<< * t = cell.v3 / ( cell.v3 - cell.v7 + FLT_EPSILON ) * At = 0 */ break; default: /* "_marching_cubes_lewiner_cy.pyx":1614 * Dt = cell.v0 + ( cell.v4 - cell.v0 ) * t * else: * print( "Invalid edge %i." % edge ) # <<<<<<<<<<<<<< * else: * print( "Invalid ambiguous case %i." % case ) */ __pyx_t_7 = __Pyx_PyInt_From_int(__pyx_v_edge); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 1614, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __pyx_t_8 = __Pyx_PyString_Format(__pyx_kp_s_Invalid_edge_i, __pyx_t_7); if (unlikely(!__pyx_t_8)) __PYX_ERR(0, 1614, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; if (__Pyx_PrintOne(0, __pyx_t_8) < 0) __PYX_ERR(0, 1614, __pyx_L1_error) __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; break; } /* "_marching_cubes_lewiner_cy.pyx":1534 * Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t * * elif case==6 or case==7 or case==12 or case==13: # <<<<<<<<<<<<<< * # Define edge * if case == 6: edge = luts.TEST6.get2(config, 2) */ break; default: /* "_marching_cubes_lewiner_cy.pyx":1616 * print( "Invalid edge %i." % edge ) * else: * print( "Invalid ambiguous case %i." % case ) # <<<<<<<<<<<<<< * * # Process results */ __pyx_t_8 = __Pyx_PyInt_From_int(__pyx_v_case); if (unlikely(!__pyx_t_8)) __PYX_ERR(0, 1616, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_8); __pyx_t_7 = __Pyx_PyString_Format(__pyx_kp_s_Invalid_ambiguous_case_i, __pyx_t_8); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 1616, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; if (__Pyx_PrintOne(0, __pyx_t_7) < 0) __PYX_ERR(0, 1616, __pyx_L1_error) __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; break; } /* "_marching_cubes_lewiner_cy.pyx":1619 * * # Process results * if At >= 0: test += 1 # <<<<<<<<<<<<<< * if Bt >= 0: test += 2 * if Ct >= 0: test += 4 */ __pyx_t_5 = ((__pyx_v_At >= 0.0) != 0); if (__pyx_t_5) { __pyx_v_test = (__pyx_v_test + 1); } /* "_marching_cubes_lewiner_cy.pyx":1620 * # Process results * if At >= 0: test += 1 * if Bt >= 0: test += 2 # <<<<<<<<<<<<<< * if Ct >= 0: test += 4 * if Dt >= 0: test += 8 */ __pyx_t_5 = ((__pyx_v_Bt >= 0.0) != 0); if (__pyx_t_5) { __pyx_v_test = (__pyx_v_test + 2); } /* "_marching_cubes_lewiner_cy.pyx":1621 * if At >= 0: test += 1 * if Bt >= 0: test += 2 * if Ct >= 0: test += 4 # <<<<<<<<<<<<<< * if Dt >= 0: test += 8 * */ __pyx_t_5 = ((__pyx_v_Ct >= 0.0) != 0); if (__pyx_t_5) { __pyx_v_test = (__pyx_v_test + 4); } /* "_marching_cubes_lewiner_cy.pyx":1622 * if Bt >= 0: test += 2 * if Ct >= 0: test += 4 * if Dt >= 0: test += 8 # <<<<<<<<<<<<<< * * # Determine what to return */ __pyx_t_5 = ((__pyx_v_Dt >= 0.0) != 0); if (__pyx_t_5) { __pyx_v_test = (__pyx_v_test + 8); } /* "_marching_cubes_lewiner_cy.pyx":1625 * * # Determine what to return * if test==0: return s>0 # <<<<<<<<<<<<<< * elif test==1: return s>0 * elif test==2: return s>0 */ switch (__pyx_v_test) { case 0: __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 1: /* "_marching_cubes_lewiner_cy.pyx":1626 * # Determine what to return * if test==0: return s>0 * elif test==1: return s>0 # <<<<<<<<<<<<<< * elif test==2: return s>0 * elif test==3: return s>0 */ __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 2: /* "_marching_cubes_lewiner_cy.pyx":1627 * if test==0: return s>0 * elif test==1: return s>0 * elif test==2: return s>0 # <<<<<<<<<<<<<< * elif test==3: return s>0 * elif test==4: return s>0 */ __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 3: /* "_marching_cubes_lewiner_cy.pyx":1628 * elif test==1: return s>0 * elif test==2: return s>0 * elif test==3: return s>0 # <<<<<<<<<<<<<< * elif test==4: return s>0 * elif test==5: */ __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 4: /* "_marching_cubes_lewiner_cy.pyx":1629 * elif test==2: return s>0 * elif test==3: return s>0 * elif test==4: return s>0 # <<<<<<<<<<<<<< * elif test==5: * if At * Ct - Bt * Dt < FLT_EPSILON: return s>0 */ __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 5: /* "_marching_cubes_lewiner_cy.pyx":1631 * elif test==4: return s>0 * elif test==5: * if At * Ct - Bt * Dt < FLT_EPSILON: return s>0 # <<<<<<<<<<<<<< * elif test==6: return s>0 * elif test==7: return s<0 */ __pyx_t_5 = ((((__pyx_v_At * __pyx_v_Ct) - (__pyx_v_Bt * __pyx_v_Dt)) < __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON) != 0); if (__pyx_t_5) { __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; } /* "_marching_cubes_lewiner_cy.pyx":1630 * elif test==3: return s>0 * elif test==4: return s>0 * elif test==5: # <<<<<<<<<<<<<< * if At * Ct - Bt * Dt < FLT_EPSILON: return s>0 * elif test==6: return s>0 */ break; case 6: /* "_marching_cubes_lewiner_cy.pyx":1632 * elif test==5: * if At * Ct - Bt * Dt < FLT_EPSILON: return s>0 * elif test==6: return s>0 # <<<<<<<<<<<<<< * elif test==7: return s<0 * elif test==8: return s>0 */ __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 7: /* "_marching_cubes_lewiner_cy.pyx":1633 * if At * Ct - Bt * Dt < FLT_EPSILON: return s>0 * elif test==6: return s>0 * elif test==7: return s<0 # <<<<<<<<<<<<<< * elif test==8: return s>0 * elif test==9: return s>0 */ __pyx_r = (__pyx_v_s < 0); goto __pyx_L0; break; case 8: /* "_marching_cubes_lewiner_cy.pyx":1634 * elif test==6: return s>0 * elif test==7: return s<0 * elif test==8: return s>0 # <<<<<<<<<<<<<< * elif test==9: return s>0 * elif test==10: */ __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 9: /* "_marching_cubes_lewiner_cy.pyx":1635 * elif test==7: return s<0 * elif test==8: return s>0 * elif test==9: return s>0 # <<<<<<<<<<<<<< * elif test==10: * if At * Ct - Bt * Dt >= FLT_EPSILON: return s>0 */ __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 10: /* "_marching_cubes_lewiner_cy.pyx":1637 * elif test==9: return s>0 * elif test==10: * if At * Ct - Bt * Dt >= FLT_EPSILON: return s>0 # <<<<<<<<<<<<<< * elif test==11: return s<0 * elif test==12: return s>0 */ __pyx_t_5 = ((((__pyx_v_At * __pyx_v_Ct) - (__pyx_v_Bt * __pyx_v_Dt)) >= __pyx_v_26_marching_cubes_lewiner_cy_FLT_EPSILON) != 0); if (__pyx_t_5) { __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; } /* "_marching_cubes_lewiner_cy.pyx":1636 * elif test==8: return s>0 * elif test==9: return s>0 * elif test==10: # <<<<<<<<<<<<<< * if At * Ct - Bt * Dt >= FLT_EPSILON: return s>0 * elif test==11: return s<0 */ break; case 11: /* "_marching_cubes_lewiner_cy.pyx":1638 * elif test==10: * if At * Ct - Bt * Dt >= FLT_EPSILON: return s>0 * elif test==11: return s<0 # <<<<<<<<<<<<<< * elif test==12: return s>0 * elif test==13: return s<0 */ __pyx_r = (__pyx_v_s < 0); goto __pyx_L0; break; case 12: /* "_marching_cubes_lewiner_cy.pyx":1639 * if At * Ct - Bt * Dt >= FLT_EPSILON: return s>0 * elif test==11: return s<0 * elif test==12: return s>0 # <<<<<<<<<<<<<< * elif test==13: return s<0 * elif test==14: return s<0 */ __pyx_r = (__pyx_v_s > 0); goto __pyx_L0; break; case 13: /* "_marching_cubes_lewiner_cy.pyx":1640 * elif test==11: return s<0 * elif test==12: return s>0 * elif test==13: return s<0 # <<<<<<<<<<<<<< * elif test==14: return s<0 * elif test==15: return s<0 */ __pyx_r = (__pyx_v_s < 0); goto __pyx_L0; break; case 14: /* "_marching_cubes_lewiner_cy.pyx":1641 * elif test==12: return s>0 * elif test==13: return s<0 * elif test==14: return s<0 # <<<<<<<<<<<<<< * elif test==15: return s<0 * else: return s<0 */ __pyx_r = (__pyx_v_s < 0); goto __pyx_L0; break; case 15: /* "_marching_cubes_lewiner_cy.pyx":1642 * elif test==13: return s<0 * elif test==14: return s<0 * elif test==15: return s<0 # <<<<<<<<<<<<<< * else: return s<0 */ __pyx_r = (__pyx_v_s < 0); goto __pyx_L0; break; default: /* "_marching_cubes_lewiner_cy.pyx":1643 * elif test==14: return s<0 * elif test==15: return s<0 * else: return s<0 # <<<<<<<<<<<<<< */ __pyx_r = (__pyx_v_s < 0); goto __pyx_L0; break; } /* "_marching_cubes_lewiner_cy.pyx":1509 * * * cdef int test_internal(Cell cell, LutProvider luts, int case, int config, int subconfig, int s): # <<<<<<<<<<<<<< * """ Return True of the face contains part of the surface. * """ */ /* function exit code */ __pyx_r = 0; 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if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 5, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_INCREF(__pyx_n_s_PickleError); __Pyx_GIVEREF(__pyx_n_s_PickleError); PyList_SET_ITEM(__pyx_t_1, 0, __pyx_n_s_PickleError); __pyx_t_4 = __Pyx_Import(__pyx_n_s_pickle, __pyx_t_1, -1); if (unlikely(!__pyx_t_4)) __PYX_ERR(1, 5, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_t_1 = __Pyx_ImportFrom(__pyx_t_4, __pyx_n_s_PickleError); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 5, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_INCREF(__pyx_t_1); __pyx_v___pyx_PickleError = __pyx_t_1; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; /* "(tree fragment)":6 * if __pyx_checksum not in (0x3035ec8, 0x4a4e1b2, 0x53f5fc5): * from pickle import PickleError as __pyx_PickleError * raise __pyx_PickleError("Incompatible checksums (0x%x vs (0x3035ec8, 0x4a4e1b2, 0x53f5fc5) = (CASES, CASESCLASSIC, EDGESRELX, EDGESRELY, EDGESRELZ, SUBCONFIG13, TEST10, TEST12, TEST13, TEST3, TEST4, TEST6, TEST7, TILING1, TILING10_1_1, TILING10_1_1_, TILING10_1_2, TILING10_2, TILING10_2_, TILING11, TILING12_1_1, TILING12_1_1_, TILING12_1_2, TILING12_2, TILING12_2_, TILING13_1, TILING13_1_, TILING13_2, TILING13_2_, TILING13_3, TILING13_3_, TILING13_4, TILING13_5_1, TILING13_5_2, TILING14, TILING2, TILING3_1, TILING3_2, TILING4_1, TILING4_2, TILING5, TILING6_1_1, TILING6_1_2, TILING6_2, TILING7_1, TILING7_2, TILING7_3, TILING7_4_1, TILING7_4_2, TILING8, TILING9))" % __pyx_checksum) # <<<<<<<<<<<<<< * __pyx_result = LutProvider.__new__(__pyx_type) * if __pyx_state is not None: */ __pyx_t_1 = __Pyx_PyInt_From_long(__pyx_v___pyx_checksum); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 6, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_t_5 = __Pyx_PyString_Format(__pyx_kp_s_Incompatible_checksums_0x_x_vs_0, __pyx_t_1); if (unlikely(!__pyx_t_5)) __PYX_ERR(1, 6, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_INCREF(__pyx_v___pyx_PickleError); __pyx_t_1 = __pyx_v___pyx_PickleError; __pyx_t_6 = NULL; if (CYTHON_UNPACK_METHODS && unlikely(PyMethod_Check(__pyx_t_1))) { __pyx_t_6 = PyMethod_GET_SELF(__pyx_t_1); if (likely(__pyx_t_6)) { PyObject* function = PyMethod_GET_FUNCTION(__pyx_t_1); __Pyx_INCREF(__pyx_t_6); __Pyx_INCREF(function); __Pyx_DECREF_SET(__pyx_t_1, function); } } __pyx_t_4 = (__pyx_t_6) ? __Pyx_PyObject_Call2Args(__pyx_t_1, __pyx_t_6, __pyx_t_5) : __Pyx_PyObject_CallOneArg(__pyx_t_1, __pyx_t_5); __Pyx_XDECREF(__pyx_t_6); __pyx_t_6 = 0; __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; if (unlikely(!__pyx_t_4)) __PYX_ERR(1, 6, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_Raise(__pyx_t_4, 0, 0, 0); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __PYX_ERR(1, 6, __pyx_L1_error) /* "(tree fragment)":4 * cdef object __pyx_PickleError * cdef object __pyx_result * if __pyx_checksum not in (0x3035ec8, 0x4a4e1b2, 0x53f5fc5): # <<<<<<<<<<<<<< * from pickle import PickleError as __pyx_PickleError * raise __pyx_PickleError("Incompatible checksums (0x%x vs (0x3035ec8, 0x4a4e1b2, 0x53f5fc5) = (CASES, CASESCLASSIC, EDGESRELX, EDGESRELY, EDGESRELZ, SUBCONFIG13, TEST10, TEST12, TEST13, TEST3, TEST4, TEST6, TEST7, TILING1, TILING10_1_1, TILING10_1_1_, TILING10_1_2, TILING10_2, TILING10_2_, TILING11, TILING12_1_1, TILING12_1_1_, TILING12_1_2, TILING12_2, TILING12_2_, TILING13_1, TILING13_1_, TILING13_2, TILING13_2_, TILING13_3, TILING13_3_, TILING13_4, TILING13_5_1, TILING13_5_2, TILING14, TILING2, TILING3_1, TILING3_2, TILING4_1, TILING4_2, TILING5, TILING6_1_1, TILING6_1_2, TILING6_2, TILING7_1, TILING7_2, TILING7_3, TILING7_4_1, TILING7_4_2, TILING8, TILING9))" % __pyx_checksum) */ } /* "(tree fragment)":7 * from pickle import PickleError as __pyx_PickleError * raise __pyx_PickleError("Incompatible checksums (0x%x vs (0x3035ec8, 0x4a4e1b2, 0x53f5fc5) = (CASES, CASESCLASSIC, EDGESRELX, EDGESRELY, EDGESRELZ, SUBCONFIG13, TEST10, TEST12, TEST13, TEST3, TEST4, TEST6, TEST7, TILING1, TILING10_1_1, TILING10_1_1_, TILING10_1_2, TILING10_2, TILING10_2_, TILING11, TILING12_1_1, TILING12_1_1_, TILING12_1_2, TILING12_2, TILING12_2_, TILING13_1, TILING13_1_, TILING13_2, TILING13_2_, TILING13_3, TILING13_3_, TILING13_4, TILING13_5_1, TILING13_5_2, TILING14, TILING2, TILING3_1, TILING3_2, TILING4_1, TILING4_2, TILING5, TILING6_1_1, TILING6_1_2, TILING6_2, TILING7_1, TILING7_2, TILING7_3, TILING7_4_1, TILING7_4_2, TILING8, TILING9))" % __pyx_checksum) * __pyx_result = LutProvider.__new__(__pyx_type) # <<<<<<<<<<<<<< * if __pyx_state is not None: * __pyx_unpickle_LutProvider__set_state( __pyx_result, __pyx_state) */ __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_ptype_26_marching_cubes_lewiner_cy_LutProvider), __pyx_n_s_new); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 7, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_t_5 = NULL; if (CYTHON_UNPACK_METHODS && likely(PyMethod_Check(__pyx_t_1))) { __pyx_t_5 = PyMethod_GET_SELF(__pyx_t_1); if (likely(__pyx_t_5)) { PyObject* function = PyMethod_GET_FUNCTION(__pyx_t_1); __Pyx_INCREF(__pyx_t_5); __Pyx_INCREF(function); __Pyx_DECREF_SET(__pyx_t_1, function); } } __pyx_t_4 = (__pyx_t_5) ? __Pyx_PyObject_Call2Args(__pyx_t_1, __pyx_t_5, __pyx_v___pyx_type) : __Pyx_PyObject_CallOneArg(__pyx_t_1, __pyx_v___pyx_type); __Pyx_XDECREF(__pyx_t_5); __pyx_t_5 = 0; if (unlikely(!__pyx_t_4)) __PYX_ERR(1, 7, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v___pyx_result = __pyx_t_4; __pyx_t_4 = 0; /* "(tree fragment)":8 * raise __pyx_PickleError("Incompatible checksums (0x%x vs (0x3035ec8, 0x4a4e1b2, 0x53f5fc5) = (CASES, CASESCLASSIC, EDGESRELX, EDGESRELY, EDGESRELZ, SUBCONFIG13, TEST10, TEST12, TEST13, TEST3, TEST4, TEST6, TEST7, TILING1, TILING10_1_1, TILING10_1_1_, TILING10_1_2, TILING10_2, TILING10_2_, TILING11, TILING12_1_1, TILING12_1_1_, TILING12_1_2, TILING12_2, TILING12_2_, TILING13_1, TILING13_1_, TILING13_2, TILING13_2_, TILING13_3, TILING13_3_, TILING13_4, TILING13_5_1, TILING13_5_2, TILING14, TILING2, TILING3_1, TILING3_2, TILING4_1, TILING4_2, TILING5, TILING6_1_1, TILING6_1_2, TILING6_2, TILING7_1, TILING7_2, TILING7_3, TILING7_4_1, TILING7_4_2, TILING8, TILING9))" % __pyx_checksum) * __pyx_result = LutProvider.__new__(__pyx_type) * if __pyx_state is not None: # <<<<<<<<<<<<<< * __pyx_unpickle_LutProvider__set_state( __pyx_result, __pyx_state) * return __pyx_result */ __pyx_t_3 = (__pyx_v___pyx_state != Py_None); 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int __pyx_v_negative_step; int __pyx_r; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; /* "View.MemoryView":827 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< * * if start < 0: */ __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0); if (__pyx_t_1) { /* "View.MemoryView":829 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< * start += shape * if not 0 <= start < shape: */ __pyx_t_1 = ((__pyx_v_start < 0) != 0); if (__pyx_t_1) { /* "View.MemoryView":830 * * if start < 0: * start += shape # <<<<<<<<<<<<<< * if not 0 <= start < shape: * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); /* "View.MemoryView":829 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< * start += shape * if not 0 <= start < shape: */ } /* "View.MemoryView":831 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) * else: */ __pyx_t_1 = (0 <= __pyx_v_start); 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goto __pyx_L6_bool_binop_done; } __pyx_t_1 = ((__pyx_v_step < 0) != 0); __pyx_t_2 = __pyx_t_1; __pyx_L6_bool_binop_done:; __pyx_v_negative_step = __pyx_t_2; /* "View.MemoryView":837 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) * */ __pyx_t_1 = (__pyx_v_have_step != 0); if (__pyx_t_1) { } else { __pyx_t_2 = __pyx_t_1; goto __pyx_L9_bool_binop_done; } __pyx_t_1 = ((__pyx_v_step == 0) != 0); __pyx_t_2 = __pyx_t_1; __pyx_L9_bool_binop_done:; if (__pyx_t_2) { /* "View.MemoryView":838 * * if have_step and step == 0: * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<< * * */ __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 838, __pyx_L1_error) /* "View.MemoryView":837 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) * */ } /* "View.MemoryView":841 * * * if have_start: # <<<<<<<<<<<<<< * if start < 0: * start += shape */ __pyx_t_2 = (__pyx_v_have_start != 0); if (__pyx_t_2) { /* "View.MemoryView":842 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< * start += shape * if start < 0: */ __pyx_t_2 = ((__pyx_v_start < 0) != 0); if (__pyx_t_2) { /* "View.MemoryView":843 * if have_start: * if start < 0: * start += shape # <<<<<<<<<<<<<< * if start < 0: * start = 0 */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); /* "View.MemoryView":844 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< * start = 0 * elif start >= shape: */ __pyx_t_2 = ((__pyx_v_start < 0) != 0); if (__pyx_t_2) { /* "View.MemoryView":845 * start += shape * if start < 0: * start = 0 # <<<<<<<<<<<<<< * elif start >= shape: * if negative_step: */ __pyx_v_start = 0; /* "View.MemoryView":844 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< * start = 0 * elif start >= shape: */ } /* "View.MemoryView":842 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< * start += shape * if start < 0: */ goto __pyx_L12; } /* "View.MemoryView":846 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< * if negative_step: * start = shape - 1 */ __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); 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} __pyx_L3:; /* "View.MemoryView":1101 * to_dtype_func = NULL * * return memoryview_fromslice(memviewslice[0], memview.view.ndim, # <<<<<<<<<<<<<< * to_object_func, to_dtype_func, * memview.dtype_is_object) */ __Pyx_XDECREF(__pyx_r); /* "View.MemoryView":1103 * return memoryview_fromslice(memviewslice[0], memview.view.ndim, * to_object_func, to_dtype_func, * memview.dtype_is_object) # <<<<<<<<<<<<<< * * */ __pyx_t_5 = __pyx_memoryview_fromslice((__pyx_v_memviewslice[0]), __pyx_v_memview->view.ndim, __pyx_v_to_object_func, __pyx_v_to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_5)) __PYX_ERR(1, 1101, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); __pyx_r = __pyx_t_5; __pyx_t_5 = 0; goto __pyx_L0; /* "View.MemoryView":1087 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< * """ * Create a new memoryview object from a given memoryview object and slice. */ /* function exit code */ __pyx_L1_error:; 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goto __pyx_L0; } /* "View.MemoryView":1109 * * * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< * if arg < 0: * return -arg */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1116 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< * """ * Figure out the best memory access order for a given slice. */ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) { int __pyx_v_i; Py_ssize_t __pyx_v_c_stride; Py_ssize_t __pyx_v_f_stride; char __pyx_r; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; int __pyx_t_4; /* "View.MemoryView":1121 * """ * cdef int i * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< * cdef Py_ssize_t f_stride = 0 * */ __pyx_v_c_stride = 0; /* "View.MemoryView":1122 * cdef int i * cdef Py_ssize_t c_stride = 0 * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< * * for i in range(ndim - 1, -1, -1): */ __pyx_v_f_stride = 0; /* "View.MemoryView":1124 * cdef Py_ssize_t f_stride = 0 * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] */ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; /* "View.MemoryView":1125 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * c_stride = mslice.strides[i] * break */ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { /* "View.MemoryView":1126 * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< * break * */ __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); /* "View.MemoryView":1127 * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< * * for i in range(ndim): */ goto __pyx_L4_break; /* "View.MemoryView":1125 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * c_stride = mslice.strides[i] * break */ } } __pyx_L4_break:; /* "View.MemoryView":1129 * break * * for i in range(ndim): # <<<<<<<<<<<<<< * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] */ __pyx_t_1 = __pyx_v_ndim; __pyx_t_3 = __pyx_t_1; for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; /* "View.MemoryView":1130 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * f_stride = mslice.strides[i] * break */ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { /* "View.MemoryView":1131 * for i in range(ndim): * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< * break * */ __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); /* "View.MemoryView":1132 * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): */ goto __pyx_L7_break; /* "View.MemoryView":1130 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * f_stride = mslice.strides[i] * break */ } } __pyx_L7_break:; /* "View.MemoryView":1134 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< * return 'C' * else: */ __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); if (__pyx_t_2) { /* "View.MemoryView":1135 * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): * return 'C' # <<<<<<<<<<<<<< * else: * return 'F' */ __pyx_r = 'C'; goto __pyx_L0; /* "View.MemoryView":1134 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< * return 'C' * else: */ } /* "View.MemoryView":1137 * return 'C' * else: * return 'F' # <<<<<<<<<<<<<< * * @cython.cdivision(True) */ /*else*/ { __pyx_r = 'F'; goto __pyx_L0; } /* "View.MemoryView":1116 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< * """ * Figure out the best memory access order for a given slice. */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1140 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< * char *dst_data, Py_ssize_t *dst_strides, * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, */ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { CYTHON_UNUSED Py_ssize_t __pyx_v_i; CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; Py_ssize_t __pyx_v_dst_extent; Py_ssize_t __pyx_v_src_stride; Py_ssize_t __pyx_v_dst_stride; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; Py_ssize_t __pyx_t_4; Py_ssize_t __pyx_t_5; Py_ssize_t __pyx_t_6; /* "View.MemoryView":1147 * * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] */ __pyx_v_src_extent = (__pyx_v_src_shape[0]); /* "View.MemoryView":1148 * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] */ __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); /* "View.MemoryView":1149 * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t dst_stride = dst_strides[0] * */ __pyx_v_src_stride = (__pyx_v_src_strides[0]); /* "View.MemoryView":1150 * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< * * if ndim == 1: */ __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); /* "View.MemoryView":1152 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): */ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); if (__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); if (__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } /* "View.MemoryView":1154 * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< * memcpy(dst_data, src_data, itemsize * dst_extent) * else: */ __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); if (__pyx_t_2) { __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); } __pyx_t_3 = (__pyx_t_2 != 0); __pyx_t_1 = __pyx_t_3; __pyx_L5_bool_binop_done:; /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ if (__pyx_t_1) { /* "View.MemoryView":1155 * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< * else: * for i in range(dst_extent): */ (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); /* "View.MemoryView":1153 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ goto __pyx_L4; } /* "View.MemoryView":1157 * memcpy(dst_data, src_data, itemsize * dst_extent) * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< * memcpy(dst_data, src_data, itemsize) * src_data += src_stride */ /*else*/ { __pyx_t_4 = __pyx_v_dst_extent; __pyx_t_5 = __pyx_t_4; for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; /* "View.MemoryView":1158 * else: * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< * src_data += src_stride * dst_data += dst_stride */ (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); /* "View.MemoryView":1159 * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< * dst_data += dst_stride * else: */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); /* "View.MemoryView":1160 * memcpy(dst_data, src_data, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< * else: * for i in range(dst_extent): */ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); } } __pyx_L4:; /* "View.MemoryView":1152 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): */ goto __pyx_L3; } /* "View.MemoryView":1162 * dst_data += dst_stride * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< * _copy_strided_to_strided(src_data, src_strides + 1, * dst_data, dst_strides + 1, */ /*else*/ { __pyx_t_4 = __pyx_v_dst_extent; __pyx_t_5 = __pyx_t_4; for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_i = __pyx_t_6; /* "View.MemoryView":1163 * else: * for i in range(dst_extent): * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< * dst_data, dst_strides + 1, * src_shape + 1, dst_shape + 1, */ _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); /* "View.MemoryView":1167 * src_shape + 1, dst_shape + 1, * ndim - 1, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< * dst_data += dst_stride * */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); /* "View.MemoryView":1168 * ndim - 1, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, */ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); 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if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(1, 1330, __pyx_L1_error) /* "View.MemoryView":1326 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< * * */ } /* "View.MemoryView":1332 * transpose_memslice(&dst) * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); /* "View.MemoryView":1333 * * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< * refcount_copying(&dst, dtype_is_object, ndim, True) * */ copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); /* "View.MemoryView":1334 * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< * * free(tmpdata) */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); /* "View.MemoryView":1336 * refcount_copying(&dst, dtype_is_object, ndim, True) * * free(tmpdata) # <<<<<<<<<<<<<< * return 0 * */ free(__pyx_v_tmpdata); /* "View.MemoryView":1337 * * free(tmpdata) * return 0 # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_broadcast_leading') */ __pyx_r = 0; goto __pyx_L0; /* "View.MemoryView":1268 * * @cname('__pyx_memoryview_copy_contents') * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< * __Pyx_memviewslice dst, * int src_ndim, int dst_ndim, */ /* function exit code */ __pyx_L1_error:; { #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif } __pyx_r = -1; __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1340 * * @cname('__pyx_memoryview_broadcast_leading') * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< * int ndim, * int ndim_other) nogil: */ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) { int __pyx_v_i; 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/* "View.MemoryView":1349 * mslice.shape[i + offset] = mslice.shape[i] * mslice.strides[i + offset] = mslice.strides[i] * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< * * for i in range(offset): */ (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); } /* "View.MemoryView":1351 * mslice.suboffsets[i + offset] = mslice.suboffsets[i] * * for i in range(offset): # <<<<<<<<<<<<<< * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] */ __pyx_t_1 = __pyx_v_offset; __pyx_t_2 = __pyx_t_1; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* "View.MemoryView":1352 * * for i in range(offset): * mslice.shape[i] = 1 # <<<<<<<<<<<<<< * mslice.strides[i] = mslice.strides[0] * mslice.suboffsets[i] = -1 */ (__pyx_v_mslice->shape[__pyx_v_i]) = 1; /* "View.MemoryView":1353 * for i in range(offset): * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< * mslice.suboffsets[i] = -1 * */ (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); 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/* "View.MemoryView":1371 * * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil') * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< * Py_ssize_t *strides, int ndim, * bint inc) with gil: */ /* function exit code */ __Pyx_RefNannyFinishContext(); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif } /* "View.MemoryView":1377 * * @cname('__pyx_memoryview_refcount_objects_in_slice') * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< * Py_ssize_t *strides, int ndim, bint inc): * cdef Py_ssize_t i */ static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) { CYTHON_UNUSED Py_ssize_t __pyx_v_i; __Pyx_RefNannyDeclarations Py_ssize_t __pyx_t_1; Py_ssize_t __pyx_t_2; Py_ssize_t __pyx_t_3; int __pyx_t_4; __Pyx_RefNannySetupContext("refcount_objects_in_slice", 0); /* "View.MemoryView":1381 * cdef Py_ssize_t i * * for i in range(shape[0]): # <<<<<<<<<<<<<< * if ndim == 1: * if inc: */ __pyx_t_1 = (__pyx_v_shape[0]); 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/* "View.MemoryView":1403 * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, * itemsize, item) * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< * * */ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1); /* "View.MemoryView":1397 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< * size_t itemsize, void *item, * bint dtype_is_object) nogil: */ /* function exit code */ } /* "View.MemoryView":1407 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< * Py_ssize_t *strides, int ndim, * size_t itemsize, void *item) nogil: */ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) { CYTHON_UNUSED Py_ssize_t __pyx_v_i; Py_ssize_t __pyx_v_stride; Py_ssize_t __pyx_v_extent; int __pyx_t_1; Py_ssize_t __pyx_t_2; Py_ssize_t __pyx_t_3; Py_ssize_t __pyx_t_4; /* "View.MemoryView":1411 * size_t itemsize, void *item) nogil: * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t extent = shape[0] * */ __pyx_v_stride = (__pyx_v_strides[0]); /* "View.MemoryView":1412 * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<< * * if ndim == 1: */ __pyx_v_extent = (__pyx_v_shape[0]); /* "View.MemoryView":1414 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< * for i in range(extent): * memcpy(data, item, itemsize) */ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { /* "View.MemoryView":1415 * * if ndim == 1: * for i in range(extent): # <<<<<<<<<<<<<< * memcpy(data, item, itemsize) * data += stride */ __pyx_t_2 = __pyx_v_extent; __pyx_t_3 = __pyx_t_2; for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { __pyx_v_i = __pyx_t_4; 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static PyTypeObject __pyx_type_26_marching_cubes_lewiner_cy_Cell = { PyVarObject_HEAD_INIT(0, 0) "_marching_cubes_lewiner_cy.Cell", /*tp_name*/ sizeof(struct __pyx_obj_26_marching_cubes_lewiner_cy_Cell), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_26_marching_cubes_lewiner_cy_Cell, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif #if PY_VERSION_HEX >= 0x030800b4 0, /*tp_vectorcall_offset*/ #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ " Class to keep track of some stuff during the whole cube marching\n procedure.\n\n This \"struct\" keeps track of the current cell location, and the values\n of corners of the cube. Gradients for the cube corners are calculated\n when needed.\n\n Additionally, it keeps track of the array of vertices, faces and normals.\n\n Notes on vertices\n -----------------\n The vertices are stored in a C-array that is increased in size with\n factors of two if needed. The same applies to the faces and normals.\n\n Notes on faces\n --------------\n To keep track of the vertices already defined, this class maintains\n two faceLayer arrays. faceLayer1 is of the current layer (z-value)\n and faceLayer2 is of the next. Both face layers have 4 elements per\n cell in that layer, 1 for each unique edge per cell (see\n get_index_in_facelayer). These are initialized as -1, and set to the\n index in the vertex array when a new vertex is created.\n In summary, this allows us to keep track of the already created\n vertices without keeping a very big array.\n\n Notes on normals\n ----------------\n The normal is simply defined as the gradient. 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Py_INCREF(Py_None); p->TILING10_1_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING10_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING10_2_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING11 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING12_1_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING12_1_1_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING12_1_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING12_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING12_2_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_1_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_2_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_3 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_3_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_4 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_5_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING13_5_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TILING14 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TEST3 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TEST4 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TEST6 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TEST7 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TEST10 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TEST12 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->TEST13 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); p->SUBCONFIG13 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); return o; } static void __pyx_tp_dealloc_26_marching_cubes_lewiner_cy_LutProvider(PyObject *o) { struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *p = (struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif PyObject_GC_UnTrack(o); Py_CLEAR(p->EDGESRELX); Py_CLEAR(p->EDGESRELY); Py_CLEAR(p->EDGESRELZ); Py_CLEAR(p->CASESCLASSIC); Py_CLEAR(p->CASES); Py_CLEAR(p->TILING1); Py_CLEAR(p->TILING2); Py_CLEAR(p->TILING3_1); Py_CLEAR(p->TILING3_2); Py_CLEAR(p->TILING4_1); Py_CLEAR(p->TILING4_2); Py_CLEAR(p->TILING5); Py_CLEAR(p->TILING6_1_1); Py_CLEAR(p->TILING6_1_2); Py_CLEAR(p->TILING6_2); Py_CLEAR(p->TILING7_1); Py_CLEAR(p->TILING7_2); Py_CLEAR(p->TILING7_3); Py_CLEAR(p->TILING7_4_1); Py_CLEAR(p->TILING7_4_2); Py_CLEAR(p->TILING8); Py_CLEAR(p->TILING9); Py_CLEAR(p->TILING10_1_1); Py_CLEAR(p->TILING10_1_1_); Py_CLEAR(p->TILING10_1_2); Py_CLEAR(p->TILING10_2); Py_CLEAR(p->TILING10_2_); Py_CLEAR(p->TILING11); Py_CLEAR(p->TILING12_1_1); Py_CLEAR(p->TILING12_1_1_); Py_CLEAR(p->TILING12_1_2); Py_CLEAR(p->TILING12_2); Py_CLEAR(p->TILING12_2_); Py_CLEAR(p->TILING13_1); Py_CLEAR(p->TILING13_1_); Py_CLEAR(p->TILING13_2); Py_CLEAR(p->TILING13_2_); Py_CLEAR(p->TILING13_3); Py_CLEAR(p->TILING13_3_); Py_CLEAR(p->TILING13_4); Py_CLEAR(p->TILING13_5_1); Py_CLEAR(p->TILING13_5_2); Py_CLEAR(p->TILING14); Py_CLEAR(p->TEST3); Py_CLEAR(p->TEST4); Py_CLEAR(p->TEST6); Py_CLEAR(p->TEST7); Py_CLEAR(p->TEST10); Py_CLEAR(p->TEST12); Py_CLEAR(p->TEST13); Py_CLEAR(p->SUBCONFIG13); (*Py_TYPE(o)->tp_free)(o); } static int __pyx_tp_traverse_26_marching_cubes_lewiner_cy_LutProvider(PyObject *o, visitproc v, void *a) { int e; struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *p = (struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *)o; if (p->EDGESRELX) { e = (*v)(((PyObject *)p->EDGESRELX), a); if (e) return e; } if (p->EDGESRELY) { e = (*v)(((PyObject *)p->EDGESRELY), a); if (e) return e; } if (p->EDGESRELZ) { e = (*v)(((PyObject *)p->EDGESRELZ), a); if (e) return e; } if (p->CASESCLASSIC) { e = (*v)(((PyObject *)p->CASESCLASSIC), a); if (e) return e; } if (p->CASES) { e = (*v)(((PyObject *)p->CASES), a); if (e) return e; } if (p->TILING1) { e = (*v)(((PyObject *)p->TILING1), a); if (e) return e; } if (p->TILING2) { e = (*v)(((PyObject *)p->TILING2), a); if (e) return e; } if (p->TILING3_1) { e = (*v)(((PyObject *)p->TILING3_1), a); if (e) return e; } if (p->TILING3_2) { e = (*v)(((PyObject *)p->TILING3_2), a); if (e) return e; } if (p->TILING4_1) { e = (*v)(((PyObject *)p->TILING4_1), a); if (e) return e; } if (p->TILING4_2) { e = (*v)(((PyObject *)p->TILING4_2), a); if (e) return e; } if (p->TILING5) { e = (*v)(((PyObject *)p->TILING5), a); if (e) return e; } if (p->TILING6_1_1) { e = (*v)(((PyObject *)p->TILING6_1_1), a); if (e) return e; } if (p->TILING6_1_2) { e = (*v)(((PyObject *)p->TILING6_1_2), a); if (e) return e; } if (p->TILING6_2) { e = (*v)(((PyObject *)p->TILING6_2), a); if (e) return e; } if (p->TILING7_1) { e = (*v)(((PyObject *)p->TILING7_1), a); if (e) return e; } if (p->TILING7_2) { e = (*v)(((PyObject *)p->TILING7_2), a); if (e) return e; } if (p->TILING7_3) { e = (*v)(((PyObject *)p->TILING7_3), a); if (e) return e; } if (p->TILING7_4_1) { e = (*v)(((PyObject *)p->TILING7_4_1), a); if (e) return e; } if (p->TILING7_4_2) { e = (*v)(((PyObject *)p->TILING7_4_2), a); if (e) return e; } if (p->TILING8) { e = (*v)(((PyObject *)p->TILING8), a); if (e) return e; } if (p->TILING9) { e = (*v)(((PyObject *)p->TILING9), a); if (e) return e; } if (p->TILING10_1_1) { e = (*v)(((PyObject *)p->TILING10_1_1), a); if (e) return e; } if (p->TILING10_1_1_) { e = (*v)(((PyObject *)p->TILING10_1_1_), a); if (e) return e; } if (p->TILING10_1_2) { e = (*v)(((PyObject *)p->TILING10_1_2), a); if (e) return e; } if (p->TILING10_2) { e = (*v)(((PyObject *)p->TILING10_2), a); if (e) return e; } if (p->TILING10_2_) { e = (*v)(((PyObject *)p->TILING10_2_), a); if (e) return e; } if (p->TILING11) { e = (*v)(((PyObject *)p->TILING11), a); if (e) return e; } if (p->TILING12_1_1) { e = (*v)(((PyObject *)p->TILING12_1_1), a); if (e) return e; } if (p->TILING12_1_1_) { e = (*v)(((PyObject *)p->TILING12_1_1_), a); if (e) return e; } if (p->TILING12_1_2) { e = (*v)(((PyObject *)p->TILING12_1_2), a); if (e) return e; } if (p->TILING12_2) { e = (*v)(((PyObject *)p->TILING12_2), a); if (e) return e; } if (p->TILING12_2_) { e = (*v)(((PyObject *)p->TILING12_2_), a); if (e) return e; } if (p->TILING13_1) { e = (*v)(((PyObject *)p->TILING13_1), a); if (e) return e; } if (p->TILING13_1_) { e = (*v)(((PyObject *)p->TILING13_1_), a); if (e) return e; } if (p->TILING13_2) { e = (*v)(((PyObject *)p->TILING13_2), a); if (e) return e; } if (p->TILING13_2_) { e = (*v)(((PyObject *)p->TILING13_2_), a); if (e) return e; } if (p->TILING13_3) { e = (*v)(((PyObject *)p->TILING13_3), a); if (e) return e; } if (p->TILING13_3_) { e = (*v)(((PyObject *)p->TILING13_3_), a); if (e) return e; } if (p->TILING13_4) { e = (*v)(((PyObject *)p->TILING13_4), a); if (e) return e; } if (p->TILING13_5_1) { e = (*v)(((PyObject *)p->TILING13_5_1), a); if (e) return e; } if (p->TILING13_5_2) { e = (*v)(((PyObject *)p->TILING13_5_2), a); if (e) return e; } if (p->TILING14) { e = (*v)(((PyObject *)p->TILING14), a); if (e) return e; } if (p->TEST3) { e = (*v)(((PyObject *)p->TEST3), a); if (e) return e; } if (p->TEST4) { e = (*v)(((PyObject *)p->TEST4), a); if (e) return e; } if (p->TEST6) { e = (*v)(((PyObject *)p->TEST6), a); if (e) return e; } if (p->TEST7) { e = (*v)(((PyObject *)p->TEST7), a); if (e) return e; } if (p->TEST10) { e = (*v)(((PyObject *)p->TEST10), a); if (e) return e; } if (p->TEST12) { e = (*v)(((PyObject *)p->TEST12), a); if (e) return e; } if (p->TEST13) { e = (*v)(((PyObject *)p->TEST13), a); if (e) return e; } if (p->SUBCONFIG13) { e = (*v)(((PyObject *)p->SUBCONFIG13), a); if (e) return e; } return 0; } static int __pyx_tp_clear_26_marching_cubes_lewiner_cy_LutProvider(PyObject *o) { PyObject* tmp; struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *p = (struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider *)o; tmp = ((PyObject*)p->EDGESRELX); p->EDGESRELX = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->EDGESRELY); p->EDGESRELY = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->EDGESRELZ); p->EDGESRELZ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->CASESCLASSIC); p->CASESCLASSIC = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->CASES); p->CASES = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING1); p->TILING1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING2); p->TILING2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING3_1); p->TILING3_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING3_2); p->TILING3_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING4_1); p->TILING4_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING4_2); p->TILING4_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING5); p->TILING5 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING6_1_1); p->TILING6_1_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING6_1_2); p->TILING6_1_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING6_2); p->TILING6_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING7_1); p->TILING7_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING7_2); p->TILING7_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING7_3); p->TILING7_3 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING7_4_1); p->TILING7_4_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING7_4_2); p->TILING7_4_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING8); p->TILING8 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING9); p->TILING9 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING10_1_1); p->TILING10_1_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING10_1_1_); p->TILING10_1_1_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING10_1_2); p->TILING10_1_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING10_2); p->TILING10_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING10_2_); p->TILING10_2_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING11); p->TILING11 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING12_1_1); p->TILING12_1_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING12_1_1_); p->TILING12_1_1_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING12_1_2); p->TILING12_1_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING12_2); p->TILING12_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING12_2_); p->TILING12_2_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_1); p->TILING13_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_1_); p->TILING13_1_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_2); p->TILING13_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_2_); p->TILING13_2_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_3); p->TILING13_3 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_3_); p->TILING13_3_ = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_4); p->TILING13_4 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_5_1); p->TILING13_5_1 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING13_5_2); p->TILING13_5_2 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TILING14); p->TILING14 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TEST3); p->TEST3 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TEST4); p->TEST4 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TEST6); p->TEST6 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TEST7); p->TEST7 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TEST10); p->TEST10 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TEST12); p->TEST12 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->TEST13); p->TEST13 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->SUBCONFIG13); p->SUBCONFIG13 = ((struct __pyx_obj_26_marching_cubes_lewiner_cy_Lut *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } static PyMethodDef __pyx_methods_26_marching_cubes_lewiner_cy_LutProvider[] = { {"__reduce_cython__", (PyCFunction)__pyx_pw_26_marching_cubes_lewiner_cy_11LutProvider_3__reduce_cython__, METH_NOARGS, 0}, {"__setstate_cython__", (PyCFunction)__pyx_pw_26_marching_cubes_lewiner_cy_11LutProvider_5__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; static PyTypeObject __pyx_type_26_marching_cubes_lewiner_cy_LutProvider = { PyVarObject_HEAD_INIT(0, 0) "_marching_cubes_lewiner_cy.LutProvider", /*tp_name*/ sizeof(struct __pyx_obj_26_marching_cubes_lewiner_cy_LutProvider), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_26_marching_cubes_lewiner_cy_LutProvider, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif #if PY_VERSION_HEX >= 0x030800b4 0, /*tp_vectorcall_offset*/ #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ " Class that provides a common interface to the many lookup tables\n used by the algorithm.\n All the lists of lut names are autogenerated to prevent human error.\n ", /*tp_doc*/ __pyx_tp_traverse_26_marching_cubes_lewiner_cy_LutProvider, /*tp_traverse*/ __pyx_tp_clear_26_marching_cubes_lewiner_cy_LutProvider, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ __pyx_methods_26_marching_cubes_lewiner_cy_LutProvider, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ __pyx_pw_26_marching_cubes_lewiner_cy_11LutProvider_1__init__, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_26_marching_cubes_lewiner_cy_LutProvider, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800) 0, /*tp_vectorcall*/ #endif #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 0, /*tp_print*/ #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000 0, /*tp_pypy_flags*/ #endif }; static struct __pyx_vtabstruct_array __pyx_vtable_array; static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) { struct __pyx_array_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_array_obj *)o); p->__pyx_vtab = __pyx_vtabptr_array; p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None); p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None); if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } static void __pyx_tp_dealloc_array(PyObject *o) { struct __pyx_array_obj *p = (struct __pyx_array_obj *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); __pyx_array___dealloc__(o); __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->mode); Py_CLEAR(p->_format); (*Py_TYPE(o)->tp_free)(o); } static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) { PyObject *r; PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); Py_DECREF(x); return r; } static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { if (v) { return __pyx_array___setitem__(o, i, v); } else { PyErr_Format(PyExc_NotImplementedError, "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); return -1; } } static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { PyObject *v = __Pyx_PyObject_GenericGetAttr(o, n); if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) { PyErr_Clear(); v = __pyx_array___getattr__(o, n); } return v; } static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o); } static PyMethodDef __pyx_methods_array[] = { {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_array_1__reduce_cython__, METH_NOARGS, 0}, {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_array_3__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; static struct PyGetSetDef __pyx_getsets_array[] = { {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0}, {0, 0, 0, 0, 0} }; static PySequenceMethods __pyx_tp_as_sequence_array = { __pyx_array___len__, /*sq_length*/ 0, /*sq_concat*/ 0, /*sq_repeat*/ __pyx_sq_item_array, /*sq_item*/ 0, /*sq_slice*/ 0, /*sq_ass_item*/ 0, /*sq_ass_slice*/ 0, /*sq_contains*/ 0, /*sq_inplace_concat*/ 0, /*sq_inplace_repeat*/ }; static PyMappingMethods __pyx_tp_as_mapping_array = { __pyx_array___len__, /*mp_length*/ __pyx_array___getitem__, /*mp_subscript*/ __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ }; static PyBufferProcs __pyx_tp_as_buffer_array = { #if PY_MAJOR_VERSION < 3 0, /*bf_getreadbuffer*/ #endif #if PY_MAJOR_VERSION < 3 0, /*bf_getwritebuffer*/ #endif #if PY_MAJOR_VERSION < 3 0, /*bf_getsegcount*/ #endif #if PY_MAJOR_VERSION < 3 0, /*bf_getcharbuffer*/ #endif __pyx_array_getbuffer, /*bf_getbuffer*/ 0, /*bf_releasebuffer*/ }; static PyTypeObject __pyx_type___pyx_array = { PyVarObject_HEAD_INIT(0, 0) "_marching_cubes_lewiner_cy.array", /*tp_name*/ sizeof(struct __pyx_array_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_array, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif #if PY_VERSION_HEX >= 0x030800b4 0, /*tp_vectorcall_offset*/ #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ &__pyx_tp_as_sequence_array, /*tp_as_sequence*/ &__pyx_tp_as_mapping_array, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ __pyx_tp_getattro_array, /*tp_getattro*/ 0, /*tp_setattro*/ &__pyx_tp_as_buffer_array, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ 0, /*tp_doc*/ 0, /*tp_traverse*/ 0, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ __pyx_methods_array, /*tp_methods*/ 0, /*tp_members*/ __pyx_getsets_array, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_array, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800) 0, /*tp_vectorcall*/ #endif #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 0, /*tp_print*/ #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000 0, /*tp_pypy_flags*/ #endif }; static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { struct __pyx_MemviewEnum_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_MemviewEnum_obj *)o); p->name = Py_None; Py_INCREF(Py_None); return o; } static void __pyx_tp_dealloc_Enum(PyObject *o) { struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif PyObject_GC_UnTrack(o); Py_CLEAR(p->name); (*Py_TYPE(o)->tp_free)(o); } static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { int e; struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; if (p->name) { e = (*v)(p->name, a); if (e) return e; } return 0; } static int __pyx_tp_clear_Enum(PyObject *o) { PyObject* tmp; struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; tmp = ((PyObject*)p->name); p->name = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } static PyMethodDef __pyx_methods_Enum[] = { {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_1__reduce_cython__, METH_NOARGS, 0}, {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_3__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; static PyTypeObject __pyx_type___pyx_MemviewEnum = { PyVarObject_HEAD_INIT(0, 0) "_marching_cubes_lewiner_cy.Enum", /*tp_name*/ sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_Enum, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif #if PY_VERSION_HEX >= 0x030800b4 0, /*tp_vectorcall_offset*/ #endif 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif __pyx_MemviewEnum___repr__, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ __pyx_tp_traverse_Enum, /*tp_traverse*/ __pyx_tp_clear_Enum, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ __pyx_methods_Enum, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ __pyx_MemviewEnum___init__, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_Enum, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800) 0, /*tp_vectorcall*/ #endif #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 0, /*tp_print*/ #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000 0, /*tp_pypy_flags*/ #endif }; static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { struct __pyx_memoryview_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_memoryview_obj *)o); p->__pyx_vtab = __pyx_vtabptr_memoryview; p->obj = Py_None; Py_INCREF(Py_None); p->_size = Py_None; Py_INCREF(Py_None); p->_array_interface = Py_None; Py_INCREF(Py_None); p->view.obj = NULL; if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } static void __pyx_tp_dealloc_memoryview(PyObject *o) { struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif PyObject_GC_UnTrack(o); { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); __pyx_memoryview___dealloc__(o); __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->obj); Py_CLEAR(p->_size); Py_CLEAR(p->_array_interface); (*Py_TYPE(o)->tp_free)(o); } static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { int e; struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; if (p->obj) { e = (*v)(p->obj, a); if (e) return e; } if (p->_size) { e = (*v)(p->_size, a); if (e) return e; } if (p->_array_interface) { e = (*v)(p->_array_interface, a); if (e) return e; } if (p->view.obj) { e = (*v)(p->view.obj, a); if (e) return e; } return 0; } static int __pyx_tp_clear_memoryview(PyObject *o) { PyObject* tmp; struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; tmp = ((PyObject*)p->obj); p->obj = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->_size); p->_size = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->_array_interface); p->_array_interface = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); Py_CLEAR(p->view.obj); return 0; } static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { PyObject *r; PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); Py_DECREF(x); return r; } static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { if (v) { return __pyx_memoryview___setitem__(o, i, v); } else { PyErr_Format(PyExc_NotImplementedError, "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); return -1; } } static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) { return 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__pyx_getsets_memoryview[] = { {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0}, {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0}, {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0}, {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0}, {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0}, {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0}, {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0}, {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0}, {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0}, {0, 0, 0, 0, 0} }; static PySequenceMethods __pyx_tp_as_sequence_memoryview = { __pyx_memoryview___len__, /*sq_length*/ 0, /*sq_concat*/ 0, /*sq_repeat*/ __pyx_sq_item_memoryview, /*sq_item*/ 0, /*sq_slice*/ 0, /*sq_ass_item*/ 0, /*sq_ass_slice*/ 0, /*sq_contains*/ 0, /*sq_inplace_concat*/ 0, 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TypeError("no default __reduce__ due to non-trivial __cinit__") */ __pyx_tuple__3 = PyTuple_Pack(1, __pyx_kp_s_no_default___reduce___due_to_non); if (unlikely(!__pyx_tuple__3)) __PYX_ERR(1, 2, __pyx_L1_error) __Pyx_GOTREF(__pyx_tuple__3); __Pyx_GIVEREF(__pyx_tuple__3); /* "(tree fragment)":4 * raise TypeError("no default __reduce__ due to non-trivial __cinit__") * def __setstate_cython__(self, __pyx_state): * raise TypeError("no default __reduce__ due to non-trivial __cinit__") # <<<<<<<<<<<<<< */ __pyx_tuple__4 = PyTuple_Pack(1, __pyx_kp_s_no_default___reduce___due_to_non); if (unlikely(!__pyx_tuple__4)) __PYX_ERR(1, 4, __pyx_L1_error) __Pyx_GOTREF(__pyx_tuple__4); __Pyx_GIVEREF(__pyx_tuple__4); /* "_marching_cubes_lewiner_cy.pyx":1171 * """ Return True if our heurisitic determines that normals are inwards facing * """ * return (avg_cube(dot3(inwards_facing_normals_ref[0,0,0], g1) >= -0.1, # <<<<<<<<<<<<<< * dot3(inwards_facing_normals_ref[0,0,1], g2) >= -0.1, * 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* dot3(inwards_facing_normals_ref[1,0,0], g5) >= -0.1, # <<<<<<<<<<<<<< * dot3(inwards_facing_normals_ref[1,0,1], g6) >= -0.1, * dot3(inwards_facing_normals_ref[1,1,1], g7) >= -0.1, */ __pyx_tuple__9 = PyTuple_Pack(3, __pyx_int_1, __pyx_int_0, __pyx_int_0); if (unlikely(!__pyx_tuple__9)) __PYX_ERR(0, 1175, __pyx_L1_error) __Pyx_GOTREF(__pyx_tuple__9); __Pyx_GIVEREF(__pyx_tuple__9); /* "_marching_cubes_lewiner_cy.pyx":1176 * dot3(inwards_facing_normals_ref[0,1,0], g4) >= -0.1, * dot3(inwards_facing_normals_ref[1,0,0], g5) >= -0.1, * dot3(inwards_facing_normals_ref[1,0,1], g6) >= -0.1, # <<<<<<<<<<<<<< * dot3(inwards_facing_normals_ref[1,1,1], g7) >= -0.1, * dot3(inwards_facing_normals_ref[1,1,0], g8) >= -0.1, */ __pyx_tuple__10 = PyTuple_Pack(3, __pyx_int_1, __pyx_int_0, __pyx_int_1); if (unlikely(!__pyx_tuple__10)) __PYX_ERR(0, 1176, __pyx_L1_error) __Pyx_GOTREF(__pyx_tuple__10); __Pyx_GIVEREF(__pyx_tuple__10); /* "_marching_cubes_lewiner_cy.pyx":1177 * 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__Pyx_GIVEREF(__pyx_tuple__15); /* "View.MemoryView":133 * * if not self.ndim: * raise ValueError("Empty shape tuple for cython.array") # <<<<<<<<<<<<<< * * if itemsize <= 0: */ __pyx_tuple__16 = PyTuple_Pack(1, __pyx_kp_s_Empty_shape_tuple_for_cython_arr); if (unlikely(!__pyx_tuple__16)) __PYX_ERR(1, 133, __pyx_L1_error) __Pyx_GOTREF(__pyx_tuple__16); __Pyx_GIVEREF(__pyx_tuple__16); /* "View.MemoryView":136 * * if itemsize <= 0: * raise ValueError("itemsize <= 0 for cython.array") # <<<<<<<<<<<<<< * * if not isinstance(format, bytes): */ __pyx_tuple__17 = PyTuple_Pack(1, __pyx_kp_s_itemsize_0_for_cython_array); if (unlikely(!__pyx_tuple__17)) __PYX_ERR(1, 136, __pyx_L1_error) __Pyx_GOTREF(__pyx_tuple__17); __Pyx_GIVEREF(__pyx_tuple__17); /* "View.MemoryView":148 * * if not self._shape: * raise MemoryError("unable to allocate shape and strides.") # <<<<<<<<<<<<<< * * */ __pyx_tuple__18 = PyTuple_Pack(1, __pyx_kp_s_unable_to_allocate_shape_and_str); if (unlikely(!__pyx_tuple__18)) 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__pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); __Pyx_XDECREF(__pyx_t_3); if (__pyx_m) { if (__pyx_d) { __Pyx_AddTraceback("init _marching_cubes_lewiner_cy", __pyx_clineno, __pyx_lineno, __pyx_filename); } Py_CLEAR(__pyx_m); } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_ImportError, "init _marching_cubes_lewiner_cy"); } __pyx_L0:; __Pyx_RefNannyFinishContext(); #if CYTHON_PEP489_MULTI_PHASE_INIT return (__pyx_m != NULL) ? 0 : -1; #elif PY_MAJOR_VERSION >= 3 return __pyx_m; #else return; #endif } /* --- Runtime support code --- */ /* Refnanny */ #if CYTHON_REFNANNY static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { PyObject *m = NULL, *p = NULL; void *r = NULL; m = PyImport_ImportModule(modname); if (!m) goto end; p = PyObject_GetAttrString(m, "RefNannyAPI"); if (!p) goto end; r = PyLong_AsVoidPtr(p); end: Py_XDECREF(p); Py_XDECREF(m); return (__Pyx_RefNannyAPIStruct *)r; } #endif /* PyObjectGetAttrStr */ #if CYTHON_USE_TYPE_SLOTS static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) { PyTypeObject* tp = Py_TYPE(obj); if (likely(tp->tp_getattro)) return tp->tp_getattro(obj, attr_name); #if PY_MAJOR_VERSION < 3 if (likely(tp->tp_getattr)) return tp->tp_getattr(obj, PyString_AS_STRING(attr_name)); #endif return PyObject_GetAttr(obj, attr_name); } #endif /* GetBuiltinName */ static PyObject *__Pyx_GetBuiltinName(PyObject *name) { PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name); if (unlikely(!result)) { PyErr_Format(PyExc_NameError, #if PY_MAJOR_VERSION >= 3 "name '%U' is not defined", name); #else "name '%.200s' is not defined", PyString_AS_STRING(name)); #endif } return result; } /* RaiseArgTupleInvalid */ static void __Pyx_RaiseArgtupleInvalid( const char* func_name, int exact, Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found) { Py_ssize_t num_expected; const char *more_or_less; if (num_found < num_min) { num_expected = num_min; more_or_less = "at least"; } else { num_expected = num_max; more_or_less = "at most"; } if (exact) { more_or_less = "exactly"; } PyErr_Format(PyExc_TypeError, "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", func_name, more_or_less, num_expected, (num_expected == 1) ? "" : "s", num_found); } /* RaiseDoubleKeywords */ static void __Pyx_RaiseDoubleKeywordsError( const char* func_name, PyObject* kw_name) { PyErr_Format(PyExc_TypeError, #if PY_MAJOR_VERSION >= 3 "%s() got multiple values for keyword argument '%U'", func_name, kw_name); #else "%s() got multiple values for keyword argument '%s'", func_name, PyString_AsString(kw_name)); #endif } /* ParseKeywords */ static int __Pyx_ParseOptionalKeywords( PyObject *kwds, PyObject **argnames[], PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, const char* function_name) { PyObject *key = 0, *value = 0; Py_ssize_t pos = 0; PyObject*** name; PyObject*** first_kw_arg = argnames + num_pos_args; while (PyDict_Next(kwds, &pos, &key, &value)) { name = first_kw_arg; while (*name && (**name != key)) name++; if (*name) { values[name-argnames] = value; continue; } name = first_kw_arg; #if PY_MAJOR_VERSION < 3 if (likely(PyString_Check(key))) { while (*name) { if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) && _PyString_Eq(**name, key)) { values[name-argnames] = value; break; } name++; } if (*name) continue; else { PyObject*** argname = argnames; while (argname != first_kw_arg) { if ((**argname == key) || ( (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) && _PyString_Eq(**argname, key))) { goto arg_passed_twice; } argname++; } } } else #endif if (likely(PyUnicode_Check(key))) { while (*name) { int cmp = (**name == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**name, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; if (cmp == 0) { values[name-argnames] = value; break; } name++; } if (*name) continue; else { PyObject*** argname = argnames; while (argname != first_kw_arg) { int cmp = (**argname == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : #endif PyUnicode_Compare(**argname, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; if (cmp == 0) goto arg_passed_twice; argname++; } } } else goto invalid_keyword_type; if (kwds2) { if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; } else { goto invalid_keyword; } } return 0; arg_passed_twice: __Pyx_RaiseDoubleKeywordsError(function_name, key); goto bad; invalid_keyword_type: PyErr_Format(PyExc_TypeError, "%.200s() keywords must be strings", function_name); goto bad; invalid_keyword: PyErr_Format(PyExc_TypeError, #if PY_MAJOR_VERSION < 3 "%.200s() got an unexpected keyword argument '%.200s'", function_name, PyString_AsString(key)); #else "%s() got an unexpected keyword argument '%U'", function_name, key); #endif bad: return -1; } /* PyDictVersioning */ #if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { PyObject *dict = Py_TYPE(obj)->tp_dict; return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; } static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { PyObject **dictptr = NULL; Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; if (offset) { #if CYTHON_COMPILING_IN_CPYTHON dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); #else dictptr = _PyObject_GetDictPtr(obj); #endif } return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; } static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { PyObject *dict = Py_TYPE(obj)->tp_dict; if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) return 0; return obj_dict_version == __Pyx_get_object_dict_version(obj); } #endif /* GetModuleGlobalName */ #if CYTHON_USE_DICT_VERSIONS static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) #else static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) #endif { PyObject *result; #if !CYTHON_AVOID_BORROWED_REFS #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) if (likely(result)) { return __Pyx_NewRef(result); } else if (unlikely(PyErr_Occurred())) { return NULL; } #else result = PyDict_GetItem(__pyx_d, name); __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) if (likely(result)) { return __Pyx_NewRef(result); } #endif #else result = PyObject_GetItem(__pyx_d, name); __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) if (likely(result)) { return __Pyx_NewRef(result); } PyErr_Clear(); #endif return __Pyx_GetBuiltinName(name); } /* PyObjectCall */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { PyObject *result; ternaryfunc call = Py_TYPE(func)->tp_call; if (unlikely(!call)) return PyObject_Call(func, arg, kw); if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) return NULL; result = (*call)(func, arg, kw); Py_LeaveRecursiveCall(); if (unlikely(!result) && unlikely(!PyErr_Occurred())) { PyErr_SetString( PyExc_SystemError, "NULL result without error in PyObject_Call"); } return result; } #endif /* PyFunctionFastCall */ #if CYTHON_FAST_PYCALL static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, PyObject *globals) { PyFrameObject *f; PyThreadState *tstate = __Pyx_PyThreadState_Current; PyObject **fastlocals; Py_ssize_t i; PyObject *result; assert(globals != NULL); /* XXX Perhaps we should create a specialized PyFrame_New() that doesn't take locals, but does take builtins without sanity checking them. */ assert(tstate != NULL); f = PyFrame_New(tstate, co, globals, NULL); if (f == NULL) { return NULL; } fastlocals = __Pyx_PyFrame_GetLocalsplus(f); for (i = 0; i < na; i++) { Py_INCREF(*args); fastlocals[i] = *args++; } result = PyEval_EvalFrameEx(f,0); ++tstate->recursion_depth; Py_DECREF(f); --tstate->recursion_depth; return result; } #if 1 || PY_VERSION_HEX < 0x030600B1 static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); PyObject *globals = PyFunction_GET_GLOBALS(func); PyObject *argdefs = PyFunction_GET_DEFAULTS(func); PyObject *closure; #if PY_MAJOR_VERSION >= 3 PyObject *kwdefs; #endif PyObject *kwtuple, **k; PyObject **d; Py_ssize_t nd; Py_ssize_t nk; PyObject *result; assert(kwargs == NULL || PyDict_Check(kwargs)); nk = kwargs ? PyDict_Size(kwargs) : 0; if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { return NULL; } if ( #if PY_MAJOR_VERSION >= 3 co->co_kwonlyargcount == 0 && #endif likely(kwargs == NULL || nk == 0) && co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { if (argdefs == NULL && co->co_argcount == nargs) { result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); goto done; } else if (nargs == 0 && argdefs != NULL && co->co_argcount == Py_SIZE(argdefs)) { /* function called with no arguments, but all parameters have a default value: use default values as arguments .*/ args = &PyTuple_GET_ITEM(argdefs, 0); result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); goto done; } } if (kwargs != NULL) { Py_ssize_t pos, i; kwtuple = PyTuple_New(2 * nk); if (kwtuple == NULL) { result = NULL; goto done; } k = &PyTuple_GET_ITEM(kwtuple, 0); pos = i = 0; while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { Py_INCREF(k[i]); Py_INCREF(k[i+1]); i += 2; } nk = i / 2; } else { kwtuple = NULL; k = NULL; } closure = PyFunction_GET_CLOSURE(func); #if PY_MAJOR_VERSION >= 3 kwdefs = PyFunction_GET_KW_DEFAULTS(func); #endif if (argdefs != NULL) { d = &PyTuple_GET_ITEM(argdefs, 0); nd = Py_SIZE(argdefs); } else { d = NULL; nd = 0; } #if PY_MAJOR_VERSION >= 3 result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, args, (int)nargs, k, (int)nk, d, (int)nd, kwdefs, closure); #else result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, args, (int)nargs, k, (int)nk, d, (int)nd, closure); #endif Py_XDECREF(kwtuple); done: Py_LeaveRecursiveCall(); return result; } #endif #endif /* PyObjectCallMethO */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { PyObject *self, *result; PyCFunction cfunc; cfunc = PyCFunction_GET_FUNCTION(func); self = PyCFunction_GET_SELF(func); if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) return NULL; result = cfunc(self, arg); Py_LeaveRecursiveCall(); if (unlikely(!result) && unlikely(!PyErr_Occurred())) { PyErr_SetString( PyExc_SystemError, "NULL result without error in PyObject_Call"); } return result; } #endif /* PyObjectCallNoArg */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { #if CYTHON_FAST_PYCALL if (PyFunction_Check(func)) { return __Pyx_PyFunction_FastCall(func, NULL, 0); } #endif #ifdef __Pyx_CyFunction_USED if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) #else if (likely(PyCFunction_Check(func))) #endif { if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { return __Pyx_PyObject_CallMethO(func, NULL); } } return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); } #endif /* PyCFunctionFastCall */ #if CYTHON_FAST_PYCCALL static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { PyCFunctionObject *func = (PyCFunctionObject*)func_obj; PyCFunction meth = PyCFunction_GET_FUNCTION(func); PyObject *self = PyCFunction_GET_SELF(func); int flags = PyCFunction_GET_FLAGS(func); assert(PyCFunction_Check(func)); assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); assert(nargs >= 0); assert(nargs == 0 || args != NULL); /* _PyCFunction_FastCallDict() must not be called with an exception set, because it may clear it (directly or indirectly) and so the caller loses its exception */ assert(!PyErr_Occurred()); if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); } else { return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); } } #endif /* PyObjectCallOneArg */ #if CYTHON_COMPILING_IN_CPYTHON static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { PyObject *result; PyObject *args = PyTuple_New(1); if (unlikely(!args)) return NULL; Py_INCREF(arg); PyTuple_SET_ITEM(args, 0, arg); result = __Pyx_PyObject_Call(func, args, NULL); Py_DECREF(args); return result; } static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { #if CYTHON_FAST_PYCALL if (PyFunction_Check(func)) { return __Pyx_PyFunction_FastCall(func, &arg, 1); } #endif if (likely(PyCFunction_Check(func))) { if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { return __Pyx_PyObject_CallMethO(func, arg); #if CYTHON_FAST_PYCCALL } else if (__Pyx_PyFastCFunction_Check(func)) { return __Pyx_PyCFunction_FastCall(func, &arg, 1); #endif } } return __Pyx__PyObject_CallOneArg(func, arg); } #else static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { PyObject *result; PyObject *args = PyTuple_Pack(1, arg); if (unlikely(!args)) return NULL; result = __Pyx_PyObject_Call(func, args, NULL); Py_DECREF(args); return result; } #endif /* MemviewSliceInit */ static int __Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, int ndim, __Pyx_memviewslice *memviewslice, int memview_is_new_reference) { __Pyx_RefNannyDeclarations int i, retval=-1; Py_buffer *buf = &memview->view; __Pyx_RefNannySetupContext("init_memviewslice", 0); if (unlikely(memviewslice->memview || memviewslice->data)) { PyErr_SetString(PyExc_ValueError, "memviewslice is already initialized!"); goto fail; } if (buf->strides) { for (i = 0; i < ndim; i++) { memviewslice->strides[i] = buf->strides[i]; } } else { Py_ssize_t stride = buf->itemsize; for (i = ndim - 1; i >= 0; i--) { memviewslice->strides[i] = stride; stride *= buf->shape[i]; } } for (i = 0; i < ndim; i++) { memviewslice->shape[i] = buf->shape[i]; if (buf->suboffsets) { memviewslice->suboffsets[i] = buf->suboffsets[i]; } else { memviewslice->suboffsets[i] = -1; } } memviewslice->memview = memview; memviewslice->data = (char *)buf->buf; if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { Py_INCREF(memview); } retval = 0; goto no_fail; fail: memviewslice->memview = 0; memviewslice->data = 0; retval = -1; no_fail: __Pyx_RefNannyFinishContext(); return retval; } #ifndef Py_NO_RETURN #define Py_NO_RETURN #endif static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { va_list vargs; char msg[200]; #ifdef HAVE_STDARG_PROTOTYPES va_start(vargs, fmt); #else va_start(vargs); #endif vsnprintf(msg, 200, fmt, vargs); va_end(vargs); Py_FatalError(msg); } static CYTHON_INLINE int __pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, PyThread_type_lock lock) { int result; PyThread_acquire_lock(lock, 1); result = (*acquisition_count)++; PyThread_release_lock(lock); return result; } static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, PyThread_type_lock lock) { int result; PyThread_acquire_lock(lock, 1); result = (*acquisition_count)--; PyThread_release_lock(lock); return result; } static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int first_time; struct __pyx_memoryview_obj *memview = memslice->memview; if (unlikely(!memview || (PyObject *) memview == Py_None)) return; if (unlikely(__pyx_get_slice_count(memview) < 0)) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); first_time = __pyx_add_acquisition_count(memview) == 0; if (unlikely(first_time)) { if (have_gil) { Py_INCREF((PyObject *) memview); } else { PyGILState_STATE _gilstate = PyGILState_Ensure(); Py_INCREF((PyObject *) memview); PyGILState_Release(_gilstate); } } } static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int last_time; struct __pyx_memoryview_obj *memview = memslice->memview; if (unlikely(!memview || (PyObject *) memview == Py_None)) { memslice->memview = NULL; return; } if (unlikely(__pyx_get_slice_count(memview) <= 0)) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); last_time = __pyx_sub_acquisition_count(memview) == 1; memslice->data = NULL; if (unlikely(last_time)) { if (have_gil) { Py_CLEAR(memslice->memview); } else { PyGILState_STATE _gilstate = PyGILState_Ensure(); Py_CLEAR(memslice->memview); PyGILState_Release(_gilstate); } } else { memslice->memview = NULL; } } /* PyIntBinop */ #if !CYTHON_COMPILING_IN_PYPY static PyObject* __Pyx_PyInt_SubtractObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) { (void)inplace; (void)zerodivision_check; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(op1))) { const long b = intval; long x; long a = PyInt_AS_LONG(op1); x = (long)((unsigned long)a - b); if (likely((x^a) >= 0 || (x^~b) >= 0)) return PyInt_FromLong(x); return PyLong_Type.tp_as_number->nb_subtract(op1, op2); } #endif #if CYTHON_USE_PYLONG_INTERNALS if (likely(PyLong_CheckExact(op1))) { const long b = intval; long a, x; #ifdef HAVE_LONG_LONG const PY_LONG_LONG llb = intval; PY_LONG_LONG lla, llx; #endif const digit* digits = ((PyLongObject*)op1)->ob_digit; const Py_ssize_t size = Py_SIZE(op1); if (likely(__Pyx_sst_abs(size) <= 1)) { a = likely(size) ? digits[0] : 0; if (size == -1) a = -a; } else { switch (size) { case -2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case 2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case -3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case 3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case -4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case 4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; default: return PyLong_Type.tp_as_number->nb_subtract(op1, op2); } } x = a - b; return PyLong_FromLong(x); #ifdef HAVE_LONG_LONG long_long: llx = lla - llb; return PyLong_FromLongLong(llx); #endif } #endif if (PyFloat_CheckExact(op1)) { const long b = intval; double a = PyFloat_AS_DOUBLE(op1); double result; PyFPE_START_PROTECT("subtract", return NULL) result = ((double)a) - (double)b; PyFPE_END_PROTECT(result) return PyFloat_FromDouble(result); } return (inplace ? PyNumber_InPlaceSubtract : PyNumber_Subtract)(op1, op2); } #endif /* PyObjectCall2Args */ static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { PyObject *args, *result = NULL; #if CYTHON_FAST_PYCALL if (PyFunction_Check(function)) { PyObject *args[2] = {arg1, arg2}; return __Pyx_PyFunction_FastCall(function, args, 2); } #endif #if CYTHON_FAST_PYCCALL if (__Pyx_PyFastCFunction_Check(function)) { PyObject *args[2] = {arg1, arg2}; return __Pyx_PyCFunction_FastCall(function, args, 2); } #endif args = PyTuple_New(2); if (unlikely(!args)) goto done; Py_INCREF(arg1); PyTuple_SET_ITEM(args, 0, arg1); Py_INCREF(arg2); PyTuple_SET_ITEM(args, 1, arg2); Py_INCREF(function); result = __Pyx_PyObject_Call(function, args, NULL); Py_DECREF(args); Py_DECREF(function); done: return result; } /* GetItemInt */ static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { PyObject *r; if (!j) return NULL; r = PyObject_GetItem(o, j); Py_DECREF(j); return r; } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS Py_ssize_t wrapped_i = i; if (wraparound & unlikely(i < 0)) { wrapped_i += PyList_GET_SIZE(o); } if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { PyObject *r = PyList_GET_ITEM(o, wrapped_i); Py_INCREF(r); return r; } return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); #else return PySequence_GetItem(o, i); #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS Py_ssize_t wrapped_i = i; if (wraparound & unlikely(i < 0)) { wrapped_i += PyTuple_GET_SIZE(o); } if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); Py_INCREF(r); return r; } return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); #else return PySequence_GetItem(o, i); #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS if (is_list || PyList_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { PyObject *r = PyList_GET_ITEM(o, n); Py_INCREF(r); return r; } } else if (PyTuple_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { PyObject *r = PyTuple_GET_ITEM(o, n); Py_INCREF(r); return r; } } else { PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; if (likely(m && m->sq_item)) { if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { Py_ssize_t l = m->sq_length(o); if (likely(l >= 0)) { i += l; } else { if (!PyErr_ExceptionMatches(PyExc_OverflowError)) return NULL; PyErr_Clear(); } } return m->sq_item(o, i); } } #else if (is_list || PySequence_Check(o)) { return PySequence_GetItem(o, i); } #endif return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); } /* ObjectGetItem */ #if CYTHON_USE_TYPE_SLOTS static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { PyObject *runerr; Py_ssize_t key_value; PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; if (unlikely(!(m && m->sq_item))) { PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); return NULL; } key_value = __Pyx_PyIndex_AsSsize_t(index); if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); } if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { PyErr_Clear(); PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); } return NULL; } static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; if (likely(m && m->mp_subscript)) { return m->mp_subscript(obj, key); } return __Pyx_PyObject_GetIndex(obj, key); } #endif /* ArgTypeTest */ static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) { if (unlikely(!type)) { PyErr_SetString(PyExc_SystemError, "Missing type object"); return 0; } else if (exact) { #if PY_MAJOR_VERSION == 2 if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; #endif } else { if (likely(__Pyx_TypeCheck(obj, type))) return 1; } PyErr_Format(PyExc_TypeError, "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", name, type->tp_name, Py_TYPE(obj)->tp_name); return 0; } /* KeywordStringCheck */ static int __Pyx_CheckKeywordStrings( PyObject *kwdict, const char* function_name, int kw_allowed) { PyObject* key = 0; Py_ssize_t pos = 0; #if CYTHON_COMPILING_IN_PYPY if (!kw_allowed && PyDict_Next(kwdict, &pos, &key, 0)) goto invalid_keyword; return 1; #else while (PyDict_Next(kwdict, &pos, &key, 0)) { #if PY_MAJOR_VERSION < 3 if (unlikely(!PyString_Check(key))) #endif if (unlikely(!PyUnicode_Check(key))) goto invalid_keyword_type; } if ((!kw_allowed) && unlikely(key)) goto invalid_keyword; return 1; invalid_keyword_type: PyErr_Format(PyExc_TypeError, "%.200s() keywords must be strings", function_name); return 0; #endif invalid_keyword: PyErr_Format(PyExc_TypeError, #if PY_MAJOR_VERSION < 3 "%.200s() got an unexpected keyword argument '%.200s'", function_name, PyString_AsString(key)); #else "%s() got an unexpected keyword argument '%U'", function_name, key); #endif return 0; } /* PyErrFetchRestore */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->curexc_type; tmp_value = tstate->curexc_value; tmp_tb = tstate->curexc_traceback; tstate->curexc_type = type; tstate->curexc_value = value; tstate->curexc_traceback = tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); } static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { *type = tstate->curexc_type; *value = tstate->curexc_value; *tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; } #endif /* WriteUnraisableException */ static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, int full_traceback, CYTHON_UNUSED int nogil) { PyObject *old_exc, *old_val, *old_tb; PyObject *ctx; __Pyx_PyThreadState_declare #ifdef WITH_THREAD PyGILState_STATE state; if (nogil) state = PyGILState_Ensure(); #ifdef _MSC_VER else state = (PyGILState_STATE)-1; #endif #endif __Pyx_PyThreadState_assign __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); if (full_traceback) { Py_XINCREF(old_exc); Py_XINCREF(old_val); Py_XINCREF(old_tb); __Pyx_ErrRestore(old_exc, old_val, old_tb); PyErr_PrintEx(1); } #if PY_MAJOR_VERSION < 3 ctx = PyString_FromString(name); #else ctx = PyUnicode_FromString(name); #endif __Pyx_ErrRestore(old_exc, old_val, old_tb); if (!ctx) { PyErr_WriteUnraisable(Py_None); } else { PyErr_WriteUnraisable(ctx); Py_DECREF(ctx); } #ifdef WITH_THREAD if (nogil) PyGILState_Release(state); #endif } /* RaiseException */ #if PY_MAJOR_VERSION < 3 static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, CYTHON_UNUSED PyObject *cause) { __Pyx_PyThreadState_declare Py_XINCREF(type); if (!value || value == Py_None) value = NULL; else Py_INCREF(value); if (!tb || tb == Py_None) tb = NULL; else { Py_INCREF(tb); if (!PyTraceBack_Check(tb)) { PyErr_SetString(PyExc_TypeError, "raise: arg 3 must be a traceback or None"); goto raise_error; } } if (PyType_Check(type)) { #if CYTHON_COMPILING_IN_PYPY if (!value) { Py_INCREF(Py_None); value = Py_None; } #endif PyErr_NormalizeException(&type, &value, &tb); } else { if (value) { PyErr_SetString(PyExc_TypeError, "instance exception may not have a separate value"); goto raise_error; } value = type; type = (PyObject*) Py_TYPE(type); Py_INCREF(type); if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { PyErr_SetString(PyExc_TypeError, "raise: exception class must be a subclass of BaseException"); goto raise_error; } } __Pyx_PyThreadState_assign __Pyx_ErrRestore(type, value, tb); return; raise_error: Py_XDECREF(value); Py_XDECREF(type); Py_XDECREF(tb); return; } #else static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { PyObject* owned_instance = NULL; if (tb == Py_None) { tb = 0; } else if (tb && !PyTraceBack_Check(tb)) { PyErr_SetString(PyExc_TypeError, "raise: arg 3 must be a traceback or None"); goto bad; } if (value == Py_None) value = 0; if (PyExceptionInstance_Check(type)) { if (value) { PyErr_SetString(PyExc_TypeError, "instance exception may not have a separate value"); goto bad; } value = type; type = (PyObject*) Py_TYPE(value); } else if (PyExceptionClass_Check(type)) { PyObject *instance_class = NULL; if (value && PyExceptionInstance_Check(value)) { instance_class = (PyObject*) Py_TYPE(value); if (instance_class != type) { int is_subclass = PyObject_IsSubclass(instance_class, type); if (!is_subclass) { instance_class = NULL; } else if (unlikely(is_subclass == -1)) { goto bad; } else { type = instance_class; } } } if (!instance_class) { PyObject *args; if (!value) args = PyTuple_New(0); else if (PyTuple_Check(value)) { Py_INCREF(value); args = value; } else args = PyTuple_Pack(1, value); if (!args) goto bad; owned_instance = PyObject_Call(type, args, NULL); Py_DECREF(args); if (!owned_instance) goto bad; value = owned_instance; if (!PyExceptionInstance_Check(value)) { PyErr_Format(PyExc_TypeError, "calling %R should have returned an instance of " "BaseException, not %R", type, Py_TYPE(value)); goto bad; } } } else { PyErr_SetString(PyExc_TypeError, "raise: exception class must be a subclass of BaseException"); goto bad; } if (cause) { PyObject *fixed_cause; if (cause == Py_None) { fixed_cause = NULL; } else if (PyExceptionClass_Check(cause)) { fixed_cause = PyObject_CallObject(cause, NULL); if (fixed_cause == NULL) goto bad; } else if (PyExceptionInstance_Check(cause)) { fixed_cause = cause; Py_INCREF(fixed_cause); } else { PyErr_SetString(PyExc_TypeError, "exception causes must derive from " "BaseException"); goto bad; } PyException_SetCause(value, fixed_cause); } PyErr_SetObject(type, value); if (tb) { #if CYTHON_COMPILING_IN_PYPY PyObject *tmp_type, *tmp_value, *tmp_tb; PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); Py_INCREF(tb); PyErr_Restore(tmp_type, tmp_value, tb); Py_XDECREF(tmp_tb); #else PyThreadState *tstate = __Pyx_PyThreadState_Current; PyObject* tmp_tb = tstate->curexc_traceback; if (tb != tmp_tb) { Py_INCREF(tb); tstate->curexc_traceback = tb; Py_XDECREF(tmp_tb); } #endif } bad: Py_XDECREF(owned_instance); return; } #endif /* PyErrExceptionMatches */ #if CYTHON_FAST_THREAD_STATE static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { Py_ssize_t i, n; n = PyTuple_GET_SIZE(tuple); #if PY_MAJOR_VERSION >= 3 for (i=0; icurexc_type; if (exc_type == err) return 1; if (unlikely(!exc_type)) return 0; if (unlikely(PyTuple_Check(err))) return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); } #endif /* GetAttr */ static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { #if CYTHON_USE_TYPE_SLOTS #if PY_MAJOR_VERSION >= 3 if (likely(PyUnicode_Check(n))) #else if (likely(PyString_Check(n))) #endif return __Pyx_PyObject_GetAttrStr(o, n); #endif return PyObject_GetAttr(o, n); } /* GetAttr3 */ static PyObject *__Pyx_GetAttr3Default(PyObject *d) { __Pyx_PyThreadState_declare __Pyx_PyThreadState_assign if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) return NULL; __Pyx_PyErr_Clear(); Py_INCREF(d); return d; } static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { PyObject *r = __Pyx_GetAttr(o, n); return (likely(r)) ? r : __Pyx_GetAttr3Default(d); } /* IsLittleEndian */ static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) { union { uint32_t u32; uint8_t u8[4]; } S; S.u32 = 0x01020304; return S.u8[0] == 4; } /* BufferFormatCheck */ static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, __Pyx_BufFmt_StackElem* stack, __Pyx_TypeInfo* type) { stack[0].field = &ctx->root; stack[0].parent_offset = 0; ctx->root.type = type; ctx->root.name = "buffer dtype"; ctx->root.offset = 0; ctx->head = stack; ctx->head->field = &ctx->root; ctx->fmt_offset = 0; ctx->head->parent_offset = 0; ctx->new_packmode = '@'; ctx->enc_packmode = '@'; ctx->new_count = 1; ctx->enc_count = 0; ctx->enc_type = 0; ctx->is_complex = 0; ctx->is_valid_array = 0; ctx->struct_alignment = 0; while (type->typegroup == 'S') { ++ctx->head; ctx->head->field = type->fields; ctx->head->parent_offset = 0; type = type->fields->type; } } static int __Pyx_BufFmt_ParseNumber(const char** ts) { int count; const char* t = *ts; if (*t < '0' || *t > '9') { return -1; } else { count = *t++ - '0'; while (*t >= '0' && *t <= '9') { count *= 10; count += *t++ - '0'; } } *ts = t; return count; } static int __Pyx_BufFmt_ExpectNumber(const char **ts) { int number = __Pyx_BufFmt_ParseNumber(ts); if (number == -1) PyErr_Format(PyExc_ValueError,\ "Does not understand character buffer dtype format string ('%c')", **ts); return number; } static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { PyErr_Format(PyExc_ValueError, "Unexpected format string character: '%c'", ch); } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { case '?': return "'bool'"; case 'c': return "'char'"; case 'b': return "'signed char'"; case 'B': return "'unsigned char'"; case 'h': return "'short'"; case 'H': return "'unsigned short'"; case 'i': return "'int'"; case 'I': return "'unsigned int'"; case 'l': return "'long'"; case 'L': return "'unsigned long'"; case 'q': return "'long long'"; case 'Q': return "'unsigned long long'"; case 'f': return (is_complex ? "'complex float'" : "'float'"); case 'd': return (is_complex ? "'complex double'" : "'double'"); case 'g': return (is_complex ? "'complex long double'" : "'long double'"); case 'T': return "a struct"; case 'O': return "Python object"; case 'P': return "a pointer"; case 's': case 'p': return "a string"; case 0: return "end"; default: return "unparseable format string"; } } static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return 2; case 'i': case 'I': case 'l': case 'L': return 4; case 'q': case 'Q': return 8; case 'f': return (is_complex ? 8 : 4); case 'd': return (is_complex ? 16 : 8); case 'g': { PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); return 0; } case 'O': case 'P': return sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(float) * (is_complex ? 2 : 1); case 'd': return sizeof(double) * (is_complex ? 2 : 1); case 'g': return sizeof(long double) * (is_complex ? 2 : 1); case 'O': case 'P': return sizeof(void*); default: { __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } } typedef struct { char c; short x; } __Pyx_st_short; typedef struct { char c; int x; } __Pyx_st_int; typedef struct { char c; long x; } __Pyx_st_long; typedef struct { char c; float x; } __Pyx_st_float; typedef struct { char c; double x; } __Pyx_st_double; typedef struct { char c; long double x; } __Pyx_st_longdouble; typedef struct { char c; void *x; } __Pyx_st_void_p; #ifdef HAVE_LONG_LONG typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; #endif static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(__Pyx_st_float) - sizeof(float); case 'd': return sizeof(__Pyx_st_double) - sizeof(double); case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } /* These are for computing the padding at the end of the struct to align on the first member of the struct. This will probably the same as above, but we don't have any guarantees. */ typedef struct { short x; char c; } __Pyx_pad_short; typedef struct { int x; char c; } __Pyx_pad_int; typedef struct { long x; char c; } __Pyx_pad_long; typedef struct { float x; char c; } __Pyx_pad_float; typedef struct { double x; char c; } __Pyx_pad_double; typedef struct { long double x; char c; } __Pyx_pad_longdouble; typedef struct { void *x; char c; } __Pyx_pad_void_p; #ifdef HAVE_LONG_LONG typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; #endif static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { switch (ch) { case 'c': return 'H'; case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); case 'O': return 'O'; case 'P': return 'P'; default: { __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } } static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { if (ctx->head == NULL || ctx->head->field == &ctx->root) { const char* expected; const char* quote; if (ctx->head == NULL) { expected = "end"; quote = ""; } else { expected = ctx->head->field->type->name; quote = "'"; } PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch, expected %s%s%s but got %s", quote, expected, quote, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); } else { __Pyx_StructField* field = ctx->head->field; __Pyx_StructField* parent = (ctx->head - 1)->field; PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), parent->type->name, field->name); } } static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { char group; size_t size, offset, arraysize = 1; if (ctx->enc_type == 0) return 0; if (ctx->head->field->type->arraysize[0]) { int i, ndim = 0; if (ctx->enc_type == 's' || ctx->enc_type == 'p') { ctx->is_valid_array = ctx->head->field->type->ndim == 1; ndim = 1; if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { PyErr_Format(PyExc_ValueError, "Expected a dimension of size %zu, got %zu", ctx->head->field->type->arraysize[0], ctx->enc_count); return -1; } } if (!ctx->is_valid_array) { PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", ctx->head->field->type->ndim, ndim); return -1; } for (i = 0; i < ctx->head->field->type->ndim; i++) { arraysize *= ctx->head->field->type->arraysize[i]; } ctx->is_valid_array = 0; ctx->enc_count = 1; } group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); do { __Pyx_StructField* field = ctx->head->field; __Pyx_TypeInfo* type = field->type; if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); } else { size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); } if (ctx->enc_packmode == '@') { size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); size_t align_mod_offset; if (align_at == 0) return -1; align_mod_offset = ctx->fmt_offset % align_at; if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; if (ctx->struct_alignment == 0) ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, ctx->is_complex); } if (type->size != size || type->typegroup != group) { if (type->typegroup == 'C' && type->fields != NULL) { size_t parent_offset = ctx->head->parent_offset + field->offset; ++ctx->head; ctx->head->field = type->fields; ctx->head->parent_offset = parent_offset; continue; } if ((type->typegroup == 'H' || group == 'H') && type->size == size) { } else { __Pyx_BufFmt_RaiseExpected(ctx); return -1; } } offset = ctx->head->parent_offset + field->offset; if (ctx->fmt_offset != offset) { PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); return -1; } ctx->fmt_offset += size; if (arraysize) ctx->fmt_offset += (arraysize - 1) * size; --ctx->enc_count; while (1) { if (field == &ctx->root) { ctx->head = NULL; if (ctx->enc_count != 0) { __Pyx_BufFmt_RaiseExpected(ctx); return -1; } break; } ctx->head->field = ++field; if (field->type == NULL) { --ctx->head; field = ctx->head->field; continue; } else if (field->type->typegroup == 'S') { size_t parent_offset = ctx->head->parent_offset + field->offset; if (field->type->fields->type == NULL) continue; field = field->type->fields; ++ctx->head; ctx->head->field = field; ctx->head->parent_offset = parent_offset; break; } else { break; } } } while (ctx->enc_count); ctx->enc_type = 0; ctx->is_complex = 0; return 0; } static PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; int i = 0, number, ndim; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, "Cannot handle repeated arrays in format string"); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ndim = ctx->head->field->type->ndim; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; default: break; } number = __Pyx_BufFmt_ExpectNumber(&ts); if (number == -1) return NULL; if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) return PyErr_Format(PyExc_ValueError, "Expected a dimension of size %zu, got %d", ctx->head->field->type->arraysize[i], number); if (*ts != ',' && *ts != ')') return PyErr_Format(PyExc_ValueError, "Expected a comma in format string, got '%c'", *ts); if (*ts == ',') ts++; i++; } if (i != ndim) return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", ctx->head->field->type->ndim, i); if (!*ts) { PyErr_SetString(PyExc_ValueError, "Unexpected end of format string, expected ')'"); return NULL; } ctx->is_valid_array = 1; ctx->new_count = 1; *tsp = ++ts; return Py_None; } static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { int got_Z = 0; while (1) { switch(*ts) { case 0: if (ctx->enc_type != 0 && ctx->head == NULL) { __Pyx_BufFmt_RaiseExpected(ctx); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; if (ctx->head != NULL) { __Pyx_BufFmt_RaiseExpected(ctx); return NULL; } return ts; case ' ': case '\r': case '\n': ++ts; break; case '<': if (!__Pyx_Is_Little_Endian()) { PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); return NULL; } ctx->new_packmode = '='; ++ts; break; case '>': case '!': if (__Pyx_Is_Little_Endian()) { PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); return NULL; } ctx->new_packmode = '='; ++ts; break; case '=': case '@': case '^': ctx->new_packmode = *ts++; break; case 'T': { const char* ts_after_sub; size_t i, struct_count = ctx->new_count; size_t struct_alignment = ctx->struct_alignment; ctx->new_count = 1; ++ts; if (*ts != '{') { PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_type = 0; ctx->enc_count = 0; ctx->struct_alignment = 0; ++ts; ts_after_sub = ts; for (i = 0; i != struct_count; ++i) { ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); if (!ts_after_sub) return NULL; } ts = ts_after_sub; if (struct_alignment) ctx->struct_alignment = struct_alignment; } break; case '}': { size_t alignment = ctx->struct_alignment; ++ts; if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_type = 0; if (alignment && ctx->fmt_offset % alignment) { ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); } } return ts; case 'x': if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->fmt_offset += ctx->new_count; ctx->new_count = 1; ctx->enc_count = 0; ctx->enc_type = 0; ctx->enc_packmode = ctx->new_packmode; ++ts; break; case 'Z': got_Z = 1; ++ts; if (*ts != 'f' && *ts != 'd' && *ts != 'g') { __Pyx_BufFmt_RaiseUnexpectedChar('Z'); return NULL; } CYTHON_FALLTHROUGH; case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; ++ts; break; } CYTHON_FALLTHROUGH; case 's': if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_count = ctx->new_count; ctx->enc_packmode = ctx->new_packmode; ctx->enc_type = *ts; ctx->is_complex = got_Z; ++ts; ctx->new_count = 1; got_Z = 0; break; case ':': ++ts; while(*ts != ':') ++ts; ++ts; break; case '(': if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; break; default: { int number = __Pyx_BufFmt_ExpectNumber(&ts); if (number == -1) return NULL; ctx->new_count = (size_t)number; } } } } /* BufferGetAndValidate */ static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { if (unlikely(info->buf == NULL)) return; if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; __Pyx_ReleaseBuffer(info); } static void __Pyx_ZeroBuffer(Py_buffer* buf) { buf->buf = NULL; buf->obj = NULL; buf->strides = __Pyx_zeros; buf->shape = __Pyx_zeros; buf->suboffsets = __Pyx_minusones; } static int __Pyx__GetBufferAndValidate( Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack) { buf->buf = NULL; if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { __Pyx_ZeroBuffer(buf); return -1; } if (unlikely(buf->ndim != nd)) { PyErr_Format(PyExc_ValueError, "Buffer has wrong number of dimensions (expected %d, got %d)", nd, buf->ndim); goto fail; } if (!cast) { __Pyx_BufFmt_Context ctx; __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } if (unlikely((size_t)buf->itemsize != dtype->size)) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); goto fail; } if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; return 0; fail:; __Pyx_SafeReleaseBuffer(buf); return -1; } /* ExtTypeTest */ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { if (unlikely(!type)) { PyErr_SetString(PyExc_SystemError, "Missing type object"); return 0; } if (likely(__Pyx_TypeCheck(obj, type))) return 1; PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", Py_TYPE(obj)->tp_name, type->tp_name); return 0; } /* None */ static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); } /* Import */ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { PyObject *empty_list = 0; PyObject *module = 0; PyObject *global_dict = 0; PyObject *empty_dict = 0; PyObject *list; #if PY_MAJOR_VERSION < 3 PyObject *py_import; py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); if (!py_import) goto bad; #endif if (from_list) list = from_list; else { empty_list = PyList_New(0); if (!empty_list) goto bad; list = empty_list; } global_dict = PyModule_GetDict(__pyx_m); if (!global_dict) goto bad; empty_dict = PyDict_New(); if (!empty_dict) goto bad; { #if PY_MAJOR_VERSION >= 3 if (level == -1) { if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, 1); if (!module) { if (!PyErr_ExceptionMatches(PyExc_ImportError)) goto bad; PyErr_Clear(); } } level = 0; } #endif if (!module) { #if PY_MAJOR_VERSION < 3 PyObject *py_level = PyInt_FromLong(level); if (!py_level) goto bad; module = PyObject_CallFunctionObjArgs(py_import, name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); Py_DECREF(py_level); #else module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, level); #endif } } bad: #if PY_MAJOR_VERSION < 3 Py_XDECREF(py_import); #endif Py_XDECREF(empty_list); Py_XDECREF(empty_dict); return module; } /* ImportFrom */ static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { PyErr_Format(PyExc_ImportError, #if PY_MAJOR_VERSION < 3 "cannot import name %.230s", PyString_AS_STRING(name)); #else "cannot import name %S", name); #endif } return value; } /* HasAttr */ static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { PyObject *r; if (unlikely(!__Pyx_PyBaseString_Check(n))) { PyErr_SetString(PyExc_TypeError, "hasattr(): attribute name must be string"); return -1; } r = __Pyx_GetAttr(o, n); if (unlikely(!r)) { PyErr_Clear(); return 0; } else { Py_DECREF(r); return 1; } } /* GetTopmostException */ #if CYTHON_USE_EXC_INFO_STACK static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate) { _PyErr_StackItem *exc_info = tstate->exc_info; while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && exc_info->previous_item != NULL) { exc_info = exc_info->previous_item; } return exc_info; } #endif /* SaveResetException */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { #if CYTHON_USE_EXC_INFO_STACK _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); *type = exc_info->exc_type; *value = exc_info->exc_value; *tb = exc_info->exc_traceback; #else *type = tstate->exc_type; *value = tstate->exc_value; *tb = tstate->exc_traceback; #endif Py_XINCREF(*type); Py_XINCREF(*value); Py_XINCREF(*tb); } static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; #if CYTHON_USE_EXC_INFO_STACK _PyErr_StackItem *exc_info = tstate->exc_info; tmp_type = exc_info->exc_type; tmp_value = exc_info->exc_value; tmp_tb = exc_info->exc_traceback; exc_info->exc_type = type; exc_info->exc_value = value; exc_info->exc_traceback = tb; #else tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = type; tstate->exc_value = value; tstate->exc_traceback = tb; #endif Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); } #endif /* GetException */ #if CYTHON_FAST_THREAD_STATE static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) #else static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) #endif { PyObject *local_type, *local_value, *local_tb; #if CYTHON_FAST_THREAD_STATE PyObject *tmp_type, *tmp_value, *tmp_tb; local_type = tstate->curexc_type; local_value = tstate->curexc_value; local_tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; #else PyErr_Fetch(&local_type, &local_value, &local_tb); #endif PyErr_NormalizeException(&local_type, &local_value, &local_tb); #if CYTHON_FAST_THREAD_STATE if (unlikely(tstate->curexc_type)) #else if (unlikely(PyErr_Occurred())) #endif goto bad; #if PY_MAJOR_VERSION >= 3 if (local_tb) { if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) goto bad; } #endif Py_XINCREF(local_tb); Py_XINCREF(local_type); Py_XINCREF(local_value); *type = local_type; *value = local_value; *tb = local_tb; #if CYTHON_FAST_THREAD_STATE #if CYTHON_USE_EXC_INFO_STACK { _PyErr_StackItem *exc_info = tstate->exc_info; tmp_type = exc_info->exc_type; tmp_value = exc_info->exc_value; tmp_tb = exc_info->exc_traceback; exc_info->exc_type = local_type; exc_info->exc_value = local_value; exc_info->exc_traceback = local_tb; } #else tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = local_type; tstate->exc_value = local_value; tstate->exc_traceback = local_tb; #endif Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); #else PyErr_SetExcInfo(local_type, local_value, local_tb); #endif return 0; bad: *type = 0; *value = 0; *tb = 0; Py_XDECREF(local_type); Py_XDECREF(local_value); Py_XDECREF(local_tb); return -1; } /* BytesEquals */ static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); #else if (s1 == s2) { return (equals == Py_EQ); } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { const char *ps1, *ps2; Py_ssize_t length = PyBytes_GET_SIZE(s1); if (length != PyBytes_GET_SIZE(s2)) return (equals == Py_NE); ps1 = PyBytes_AS_STRING(s1); ps2 = PyBytes_AS_STRING(s2); if (ps1[0] != ps2[0]) { return (equals == Py_NE); } else if (length == 1) { return (equals == Py_EQ); } else { int result; #if CYTHON_USE_UNICODE_INTERNALS && (PY_VERSION_HEX < 0x030B0000) Py_hash_t hash1, hash2; hash1 = ((PyBytesObject*)s1)->ob_shash; hash2 = ((PyBytesObject*)s2)->ob_shash; if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { return (equals == Py_NE); } #endif result = memcmp(ps1, ps2, (size_t)length); return (equals == Py_EQ) ? (result == 0) : (result != 0); } } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { return (equals == Py_NE); } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { return (equals == Py_NE); } else { int result; PyObject* py_result = PyObject_RichCompare(s1, s2, equals); if (!py_result) return -1; result = __Pyx_PyObject_IsTrue(py_result); Py_DECREF(py_result); return result; } #endif } /* UnicodeEquals */ static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); #else #if PY_MAJOR_VERSION < 3 PyObject* owned_ref = NULL; #endif int s1_is_unicode, s2_is_unicode; if (s1 == s2) { goto return_eq; } s1_is_unicode = PyUnicode_CheckExact(s1); s2_is_unicode = PyUnicode_CheckExact(s2); #if PY_MAJOR_VERSION < 3 if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { owned_ref = PyUnicode_FromObject(s2); if (unlikely(!owned_ref)) return -1; s2 = owned_ref; s2_is_unicode = 1; } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { owned_ref = PyUnicode_FromObject(s1); if (unlikely(!owned_ref)) return -1; s1 = owned_ref; s1_is_unicode = 1; } else if (((!s2_is_unicode) & (!s1_is_unicode))) { return __Pyx_PyBytes_Equals(s1, s2, equals); } #endif if (s1_is_unicode & s2_is_unicode) { Py_ssize_t length; int kind; void *data1, *data2; if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) return -1; length = __Pyx_PyUnicode_GET_LENGTH(s1); if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { goto return_ne; } #if CYTHON_USE_UNICODE_INTERNALS { Py_hash_t hash1, hash2; #if CYTHON_PEP393_ENABLED hash1 = ((PyASCIIObject*)s1)->hash; hash2 = ((PyASCIIObject*)s2)->hash; #else hash1 = ((PyUnicodeObject*)s1)->hash; hash2 = ((PyUnicodeObject*)s2)->hash; #endif if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { goto return_ne; } } #endif kind = __Pyx_PyUnicode_KIND(s1); if (kind != __Pyx_PyUnicode_KIND(s2)) { goto return_ne; } data1 = __Pyx_PyUnicode_DATA(s1); data2 = __Pyx_PyUnicode_DATA(s2); if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { goto return_ne; } else if (length == 1) { goto return_eq; } else { int result = memcmp(data1, data2, (size_t)(length * kind)); #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_EQ) ? (result == 0) : (result != 0); } } else if ((s1 == Py_None) & s2_is_unicode) { goto return_ne; } else if ((s2 == Py_None) & s1_is_unicode) { goto return_ne; } else { int result; PyObject* py_result = PyObject_RichCompare(s1, s2, equals); #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif if (!py_result) return -1; result = __Pyx_PyObject_IsTrue(py_result); Py_DECREF(py_result); return result; } return_eq: #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_EQ); return_ne: #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_NE); #endif } /* decode_c_string */ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( const char* cstring, Py_ssize_t start, Py_ssize_t stop, const char* encoding, const char* errors, PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { Py_ssize_t length; if (unlikely((start < 0) | (stop < 0))) { size_t slen = strlen(cstring); if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { PyErr_SetString(PyExc_OverflowError, "c-string too long to convert to Python"); return NULL; } length = (Py_ssize_t) slen; if (start < 0) { start += length; if (start < 0) start = 0; } if (stop < 0) stop += length; } if (unlikely(stop <= start)) return __Pyx_NewRef(__pyx_empty_unicode); length = stop - start; cstring += start; if (decode_func) { return decode_func(cstring, length, errors); } else { return PyUnicode_Decode(cstring, length, encoding, errors); } } /* RaiseTooManyValuesToUnpack */ static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { PyErr_Format(PyExc_ValueError, "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); } /* RaiseNeedMoreValuesToUnpack */ static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { PyErr_Format(PyExc_ValueError, "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", index, (index == 1) ? "" : "s"); } /* RaiseNoneIterError */ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); } /* SwapException */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; #if CYTHON_USE_EXC_INFO_STACK _PyErr_StackItem *exc_info = tstate->exc_info; tmp_type = exc_info->exc_type; tmp_value = exc_info->exc_value; tmp_tb = exc_info->exc_traceback; exc_info->exc_type = *type; exc_info->exc_value = *value; exc_info->exc_traceback = *tb; #else tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = *type; tstate->exc_value = *value; tstate->exc_traceback = *tb; #endif *type = tmp_type; *value = tmp_value; *tb = tmp_tb; } #else static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); PyErr_SetExcInfo(*type, *value, *tb); *type = tmp_type; *value = tmp_value; *tb = tmp_tb; } #endif /* FastTypeChecks */ #if CYTHON_COMPILING_IN_CPYTHON static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { while (a) { a = a->tp_base; if (a == b) return 1; } return b == &PyBaseObject_Type; } static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { PyObject *mro; if (a == b) return 1; mro = a->tp_mro; if (likely(mro)) { Py_ssize_t i, n; n = PyTuple_GET_SIZE(mro); for (i = 0; i < n; i++) { if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) return 1; } return 0; } return __Pyx_InBases(a, b); } #if PY_MAJOR_VERSION == 2 static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { PyObject *exception, *value, *tb; int res; __Pyx_PyThreadState_declare __Pyx_PyThreadState_assign __Pyx_ErrFetch(&exception, &value, &tb); res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; if (unlikely(res == -1)) { PyErr_WriteUnraisable(err); res = 0; } if (!res) { res = PyObject_IsSubclass(err, exc_type2); if (unlikely(res == -1)) { PyErr_WriteUnraisable(err); res = 0; } } __Pyx_ErrRestore(exception, value, tb); return res; } #else static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; if (!res) { res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); } return res; } #endif static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { Py_ssize_t i, n; assert(PyExceptionClass_Check(exc_type)); n = PyTuple_GET_SIZE(tuple); #if PY_MAJOR_VERSION >= 3 for (i=0; i= 0 || (x^b) >= 0)) return PyInt_FromLong(x); return PyLong_Type.tp_as_number->nb_add(op1, op2); } #endif #if CYTHON_USE_PYLONG_INTERNALS if (likely(PyLong_CheckExact(op1))) { const long b = intval; long a, x; #ifdef HAVE_LONG_LONG const PY_LONG_LONG llb = intval; PY_LONG_LONG lla, llx; #endif const digit* digits = ((PyLongObject*)op1)->ob_digit; const Py_ssize_t size = Py_SIZE(op1); if (likely(__Pyx_sst_abs(size) <= 1)) { a = likely(size) ? digits[0] : 0; if (size == -1) a = -a; } else { switch (size) { case -2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case 2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case -3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case 3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case -4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; case 4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } CYTHON_FALLTHROUGH; default: return PyLong_Type.tp_as_number->nb_add(op1, op2); } } x = a + b; return PyLong_FromLong(x); #ifdef HAVE_LONG_LONG long_long: llx = lla + llb; return PyLong_FromLongLong(llx); #endif } #endif if (PyFloat_CheckExact(op1)) { const long b = intval; double a = PyFloat_AS_DOUBLE(op1); double result; PyFPE_START_PROTECT("add", return NULL) result = ((double)a) + (double)b; PyFPE_END_PROTECT(result) return PyFloat_FromDouble(result); } return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); } #endif /* PyObject_GenericGetAttrNoDict */ #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) { PyErr_Format(PyExc_AttributeError, #if PY_MAJOR_VERSION >= 3 "'%.50s' object has no attribute '%U'", tp->tp_name, attr_name); #else "'%.50s' object has no attribute '%.400s'", tp->tp_name, PyString_AS_STRING(attr_name)); #endif return NULL; } static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { PyObject *descr; PyTypeObject *tp = Py_TYPE(obj); if (unlikely(!PyString_Check(attr_name))) { return PyObject_GenericGetAttr(obj, attr_name); } assert(!tp->tp_dictoffset); descr = _PyType_Lookup(tp, attr_name); if (unlikely(!descr)) { return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); } Py_INCREF(descr); #if PY_MAJOR_VERSION < 3 if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) #endif { descrgetfunc f = Py_TYPE(descr)->tp_descr_get; if (unlikely(f)) { PyObject *res = f(descr, obj, (PyObject *)tp); Py_DECREF(descr); return res; } } return descr; } #endif /* PyObject_GenericGetAttr */ #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { return PyObject_GenericGetAttr(obj, attr_name); } return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); } #endif /* SetVTable */ static int __Pyx_SetVtable(PyObject *dict, void *vtable) { #if PY_VERSION_HEX >= 0x02070000 PyObject *ob = PyCapsule_New(vtable, 0, 0); #else PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); #endif if (!ob) goto bad; if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) goto bad; Py_DECREF(ob); return 0; bad: Py_XDECREF(ob); return -1; } /* PyObjectGetAttrStrNoError */ static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { __Pyx_PyThreadState_declare __Pyx_PyThreadState_assign if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) __Pyx_PyErr_Clear(); } static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { PyObject *result; #if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 PyTypeObject* tp = Py_TYPE(obj); if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); } #endif result = __Pyx_PyObject_GetAttrStr(obj, attr_name); if (unlikely(!result)) { __Pyx_PyObject_GetAttrStr_ClearAttributeError(); } return result; } /* SetupReduce */ static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { int ret; PyObject *name_attr; name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); if (likely(name_attr)) { ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); } else { ret = -1; } if (unlikely(ret < 0)) { PyErr_Clear(); ret = 0; } Py_XDECREF(name_attr); return ret; } static int __Pyx_setup_reduce(PyObject* type_obj) { int ret = 0; PyObject *object_reduce = NULL; PyObject *object_getstate = NULL; PyObject *object_reduce_ex = NULL; PyObject *reduce = NULL; PyObject *reduce_ex = NULL; PyObject *reduce_cython = NULL; PyObject *setstate = NULL; PyObject *setstate_cython = NULL; PyObject *getstate = NULL; #if CYTHON_USE_PYTYPE_LOOKUP getstate = _PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate); #else getstate = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_getstate); if (!getstate && PyErr_Occurred()) { goto __PYX_BAD; } #endif if (getstate) { #if CYTHON_USE_PYTYPE_LOOKUP object_getstate = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_getstate); #else object_getstate = __Pyx_PyObject_GetAttrStrNoError((PyObject*)&PyBaseObject_Type, __pyx_n_s_getstate); if (!object_getstate && PyErr_Occurred()) { goto __PYX_BAD; } #endif if (object_getstate != getstate) { goto __PYX_GOOD; } } #if CYTHON_USE_PYTYPE_LOOKUP object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; #else object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; #endif reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; if (reduce_ex == object_reduce_ex) { #if CYTHON_USE_PYTYPE_LOOKUP object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; #else object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; #endif reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); if (likely(reduce_cython)) { ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; } else if (reduce == object_reduce || PyErr_Occurred()) { goto __PYX_BAD; } setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); if (!setstate) PyErr_Clear(); if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); if (likely(setstate_cython)) { ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; } else if (!setstate || PyErr_Occurred()) { goto __PYX_BAD; } } PyType_Modified((PyTypeObject*)type_obj); } } goto __PYX_GOOD; __PYX_BAD: if (!PyErr_Occurred()) PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); ret = -1; __PYX_GOOD: #if !CYTHON_USE_PYTYPE_LOOKUP Py_XDECREF(object_reduce); Py_XDECREF(object_reduce_ex); Py_XDECREF(object_getstate); Py_XDECREF(getstate); #endif Py_XDECREF(reduce); Py_XDECREF(reduce_ex); Py_XDECREF(reduce_cython); Py_XDECREF(setstate); Py_XDECREF(setstate_cython); return ret; } /* TypeImport */ #ifndef __PYX_HAVE_RT_ImportType #define __PYX_HAVE_RT_ImportType static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size) { PyObject *result = 0; char warning[200]; Py_ssize_t basicsize; #ifdef Py_LIMITED_API PyObject *py_basicsize; #endif result = PyObject_GetAttrString(module, class_name); if (!result) goto bad; if (!PyType_Check(result)) { PyErr_Format(PyExc_TypeError, "%.200s.%.200s is not a type object", module_name, class_name); goto bad; } #ifndef Py_LIMITED_API basicsize = ((PyTypeObject *)result)->tp_basicsize; #else py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); if (!py_basicsize) goto bad; basicsize = PyLong_AsSsize_t(py_basicsize); Py_DECREF(py_basicsize); py_basicsize = 0; if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) goto bad; #endif if ((size_t)basicsize < size) { PyErr_Format(PyExc_ValueError, "%.200s.%.200s size changed, may indicate binary incompatibility. " "Expected %zd from C header, got %zd from PyObject", module_name, class_name, size, basicsize); goto bad; } if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { PyErr_Format(PyExc_ValueError, "%.200s.%.200s size changed, may indicate binary incompatibility. " "Expected %zd from C header, got %zd from PyObject", module_name, class_name, size, basicsize); goto bad; } else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { PyOS_snprintf(warning, sizeof(warning), "%s.%s size changed, may indicate binary incompatibility. " "Expected %zd from C header, got %zd from PyObject", module_name, class_name, size, basicsize); if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; } return (PyTypeObject *)result; bad: Py_XDECREF(result); return NULL; } #endif /* CLineInTraceback */ #ifndef CYTHON_CLINE_IN_TRACEBACK static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { PyObject *use_cline; PyObject *ptype, *pvalue, *ptraceback; #if CYTHON_COMPILING_IN_CPYTHON PyObject **cython_runtime_dict; #endif if (unlikely(!__pyx_cython_runtime)) { return c_line; } __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); #if CYTHON_COMPILING_IN_CPYTHON cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); if (likely(cython_runtime_dict)) { __PYX_PY_DICT_LOOKUP_IF_MODIFIED( use_cline, *cython_runtime_dict, __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) } else #endif { PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); if (use_cline_obj) { use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; Py_DECREF(use_cline_obj); } else { PyErr_Clear(); use_cline = NULL; } } if (!use_cline) { c_line = 0; (void) PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); } else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { c_line = 0; } __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); return c_line; } #endif /* CodeObjectCache */ static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { int start = 0, mid = 0, end = count - 1; if (end >= 0 && code_line > entries[end].code_line) { return count; } while (start < end) { mid = start + (end - start) / 2; if (code_line < entries[mid].code_line) { end = mid; } else if (code_line > entries[mid].code_line) { start = mid + 1; } else { return mid; } } if (code_line <= entries[mid].code_line) { return mid; } else { return mid + 1; } } static PyCodeObject *__pyx_find_code_object(int code_line) { PyCodeObject* code_object; int pos; if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { return NULL; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { return NULL; } code_object = __pyx_code_cache.entries[pos].code_object; Py_INCREF(code_object); return code_object; } static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { int pos, i; __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; if (unlikely(!code_line)) { return; } if (unlikely(!entries)) { entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); if (likely(entries)) { __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = 64; __pyx_code_cache.count = 1; entries[0].code_line = code_line; entries[0].code_object = code_object; Py_INCREF(code_object); } return; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { PyCodeObject* tmp = entries[pos].code_object; entries[pos].code_object = code_object; Py_DECREF(tmp); return; } if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = new_max; } for (i=__pyx_code_cache.count; i>pos; i--) { entries[i] = entries[i-1]; } entries[pos].code_line = code_line; entries[pos].code_object = code_object; __pyx_code_cache.count++; Py_INCREF(code_object); } /* AddTraceback */ #include "compile.h" #include "frameobject.h" #include "traceback.h" #if PY_VERSION_HEX >= 0x030b00a6 #ifndef Py_BUILD_CORE #define Py_BUILD_CORE 1 #endif #include "internal/pycore_frame.h" #endif static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = NULL; PyObject *py_funcname = NULL; #if PY_MAJOR_VERSION < 3 PyObject *py_srcfile = NULL; py_srcfile = PyString_FromString(filename); if (!py_srcfile) goto bad; #endif if (c_line) { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); if (!py_funcname) goto bad; #else py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); if (!py_funcname) goto bad; funcname = PyUnicode_AsUTF8(py_funcname); if (!funcname) goto bad; #endif } else { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromString(funcname); if (!py_funcname) goto bad; #endif } #if PY_MAJOR_VERSION < 3 py_code = __Pyx_PyCode_New( 0, 0, 0, 0, 0, __pyx_empty_bytes, /*PyObject *code,*/ __pyx_empty_tuple, /*PyObject *consts,*/ __pyx_empty_tuple, /*PyObject *names,*/ __pyx_empty_tuple, /*PyObject *varnames,*/ __pyx_empty_tuple, /*PyObject *freevars,*/ __pyx_empty_tuple, /*PyObject *cellvars,*/ py_srcfile, /*PyObject *filename,*/ py_funcname, /*PyObject *name,*/ py_line, __pyx_empty_bytes /*PyObject *lnotab*/ ); Py_DECREF(py_srcfile); #else py_code = PyCode_NewEmpty(filename, funcname, py_line); #endif Py_XDECREF(py_funcname); // XDECREF since it's only set on Py3 if cline return py_code; bad: Py_XDECREF(py_funcname); #if PY_MAJOR_VERSION < 3 Py_XDECREF(py_srcfile); #endif return NULL; } static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyFrameObject *py_frame = 0; PyThreadState *tstate = __Pyx_PyThreadState_Current; PyObject *ptype, *pvalue, *ptraceback; if (c_line) { c_line = __Pyx_CLineForTraceback(tstate, c_line); } py_code = __pyx_find_code_object(c_line ? -c_line : py_line); if (!py_code) { __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); py_code = __Pyx_CreateCodeObjectForTraceback( funcname, c_line, py_line, filename); if (!py_code) { /* If the code object creation fails, then we should clear the fetched exception references and propagate the new exception */ Py_XDECREF(ptype); Py_XDECREF(pvalue); Py_XDECREF(ptraceback); goto bad; } __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); } py_frame = PyFrame_New( tstate, /*PyThreadState *tstate,*/ py_code, /*PyCodeObject *code,*/ __pyx_d, /*PyObject *globals,*/ 0 /*PyObject *locals*/ ); if (!py_frame) goto bad; __Pyx_PyFrame_SetLineNumber(py_frame, py_line); PyTraceBack_Here(py_frame); bad: Py_XDECREF(py_code); Py_XDECREF(py_frame); } #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); return -1; } static void __Pyx_ReleaseBuffer(Py_buffer *view) { PyObject *obj = view->obj; if (!obj) return; if (PyObject_CheckBuffer(obj)) { PyBuffer_Release(view); return; } if ((0)) {} view->obj = NULL; Py_DECREF(obj); } #endif /* MemviewSliceIsContig */ static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) { int i, index, step, start; Py_ssize_t itemsize = mvs.memview->view.itemsize; if (order == 'F') { step = 1; start = 0; } else { step = -1; start = ndim - 1; } for (i = 0; i < ndim; i++) { index = start + step * i; if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) return 0; itemsize *= mvs.shape[index]; } return 1; } /* OverlappingSlices */ static void __pyx_get_array_memory_extents(__Pyx_memviewslice *slice, void **out_start, void **out_end, int ndim, size_t itemsize) { char *start, *end; int i; start = end = slice->data; for (i = 0; i < ndim; i++) { Py_ssize_t stride = slice->strides[i]; Py_ssize_t extent = slice->shape[i]; if (extent == 0) { *out_start = *out_end = start; return; } else { if (stride > 0) end += stride * (extent - 1); else start += stride * (extent - 1); } } *out_start = start; *out_end = end + itemsize; } static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, __Pyx_memviewslice *slice2, int ndim, size_t itemsize) { void *start1, *end1, *start2, *end2; __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); return (start1 < end2) && (start2 < end1); } /* Capsule */ static CYTHON_INLINE PyObject * __pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) { PyObject *cobj; #if PY_VERSION_HEX >= 0x02070000 cobj = PyCapsule_New(p, sig, NULL); #else cobj = PyCObject_FromVoidPtr(p, NULL); #endif return cobj; } /* CIntFromPyVerify */ #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) #define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) #define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ {\ func_type value = func_value;\ if (sizeof(target_type) < sizeof(func_type)) {\ if (unlikely(value != (func_type) (target_type) value)) {\ func_type zero = 0;\ if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ return (target_type) -1;\ if (is_unsigned && unlikely(value < zero))\ goto raise_neg_overflow;\ else\ goto raise_overflow;\ }\ }\ return (target_type) value;\ } /* TypeInfoCompare */ static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) { int i; if (!a || !b) return 0; if (a == b) return 1; if (a->size != b->size || a->typegroup != b->typegroup || a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { if (a->typegroup == 'H' || b->typegroup == 'H') { return a->size == b->size; } else { return 0; } } if (a->ndim) { for (i = 0; i < a->ndim; i++) if (a->arraysize[i] != b->arraysize[i]) return 0; } if (a->typegroup == 'S') { if (a->flags != b->flags) return 0; if (a->fields || b->fields) { if (!(a->fields && b->fields)) return 0; for (i = 0; a->fields[i].type && b->fields[i].type; i++) { __Pyx_StructField *field_a = a->fields + i; __Pyx_StructField *field_b = b->fields + i; if (field_a->offset != field_b->offset || !__pyx_typeinfo_cmp(field_a->type, field_b->type)) return 0; } return !a->fields[i].type && !b->fields[i].type; } } return 1; } /* MemviewSliceValidateAndInit */ static int __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) { if (buf->shape[dim] <= 1) return 1; if (buf->strides) { if (spec & __Pyx_MEMVIEW_CONTIG) { if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { if (unlikely(buf->strides[dim] != sizeof(void *))) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly contiguous " "in dimension %d.", dim); goto fail; } } else if (unlikely(buf->strides[dim] != buf->itemsize)) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); goto fail; } } if (spec & __Pyx_MEMVIEW_FOLLOW) { Py_ssize_t stride = buf->strides[dim]; if (stride < 0) stride = -stride; if (unlikely(stride < buf->itemsize)) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); goto fail; } } } else { if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not contiguous in " "dimension %d", dim); goto fail; } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not indirect in " "dimension %d", dim); goto fail; } else if (unlikely(buf->suboffsets)) { PyErr_SetString(PyExc_ValueError, "Buffer exposes suboffsets but no strides"); goto fail; } } return 1; fail: return 0; } static int __pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) { if (spec & __Pyx_MEMVIEW_DIRECT) { if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) { PyErr_Format(PyExc_ValueError, "Buffer not compatible with direct access " "in dimension %d.", dim); goto fail; } } if (spec & __Pyx_MEMVIEW_PTR) { if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly accessible " "in dimension %d.", dim); goto fail; } } return 1; fail: return 0; } static int __pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) { int i; if (c_or_f_flag & __Pyx_IS_F_CONTIG) { Py_ssize_t stride = 1; for (i = 0; i < ndim; i++) { if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { PyErr_SetString(PyExc_ValueError, "Buffer not fortran contiguous."); goto fail; } stride = stride * buf->shape[i]; } } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { Py_ssize_t stride = 1; for (i = ndim - 1; i >- 1; i--) { if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { PyErr_SetString(PyExc_ValueError, "Buffer not C contiguous."); goto fail; } stride = stride * buf->shape[i]; } } return 1; fail: return 0; } static int __Pyx_ValidateAndInit_memviewslice( int *axes_specs, int c_or_f_flag, int buf_flags, int ndim, __Pyx_TypeInfo *dtype, __Pyx_BufFmt_StackElem stack[], __Pyx_memviewslice *memviewslice, PyObject *original_obj) { struct __pyx_memoryview_obj *memview, *new_memview; __Pyx_RefNannyDeclarations Py_buffer *buf; int i, spec = 0, retval = -1; __Pyx_BufFmt_Context ctx; int from_memoryview = __pyx_memoryview_check(original_obj); __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) original_obj)->typeinfo)) { memview = (struct __pyx_memoryview_obj *) original_obj; new_memview = NULL; } else { memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( original_obj, buf_flags, 0, dtype); new_memview = memview; if (unlikely(!memview)) goto fail; } buf = &memview->view; if (unlikely(buf->ndim != ndim)) { PyErr_Format(PyExc_ValueError, "Buffer has wrong number of dimensions (expected %d, got %d)", ndim, buf->ndim); goto fail; } if (new_memview) { __Pyx_BufFmt_Init(&ctx, stack, dtype); if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail; } if (unlikely((unsigned) buf->itemsize != dtype->size)) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", dtype->name, dtype->size, (dtype->size > 1) ? "s" : ""); goto fail; } if (buf->len > 0) { for (i = 0; i < ndim; i++) { spec = axes_specs[i]; if (unlikely(!__pyx_check_strides(buf, i, ndim, spec))) goto fail; if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec))) goto fail; } if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))) goto fail; } if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, new_memview != NULL) == -1)) { goto fail; } retval = 0; goto no_fail; fail: Py_XDECREF(new_memview); retval = -1; no_fail: __Pyx_RefNannyFinishContext(); return retval; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsdsds_float(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 3, &__Pyx_TypeInfo_float, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsdsdsds_float(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 4, &__Pyx_TypeInfo_float, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_float(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 2, &__Pyx_TypeInfo_float, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_int(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 2, &__Pyx_TypeInfo_int, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_int(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 1, &__Pyx_TypeInfo_int, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_float(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 1, &__Pyx_TypeInfo_float, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* Print */ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3 static PyObject *__Pyx_GetStdout(void) { PyObject *f = PySys_GetObject((char *)"stdout"); if (!f) { PyErr_SetString(PyExc_RuntimeError, "lost sys.stdout"); } return f; } static int __Pyx_Print(PyObject* f, PyObject *arg_tuple, int newline) { int i; if (!f) { if (!(f = __Pyx_GetStdout())) return -1; } Py_INCREF(f); for (i=0; i < PyTuple_GET_SIZE(arg_tuple); i++) { PyObject* v; if (PyFile_SoftSpace(f, 1)) { if (PyFile_WriteString(" ", f) < 0) goto error; } v = PyTuple_GET_ITEM(arg_tuple, i); if (PyFile_WriteObject(v, f, Py_PRINT_RAW) < 0) goto error; if (PyString_Check(v)) { char *s = PyString_AsString(v); Py_ssize_t len = PyString_Size(v); if (len > 0) { switch (s[len-1]) { case ' ': break; case '\f': case '\r': case '\n': case '\t': case '\v': PyFile_SoftSpace(f, 0); break; default: break; } } } } if (newline) { if (PyFile_WriteString("\n", f) < 0) goto error; PyFile_SoftSpace(f, 0); } Py_DECREF(f); return 0; error: Py_DECREF(f); return -1; } #else static int __Pyx_Print(PyObject* stream, PyObject *arg_tuple, int newline) { PyObject* kwargs = 0; PyObject* result = 0; PyObject* end_string; if (unlikely(!__pyx_print)) { __pyx_print = PyObject_GetAttr(__pyx_b, __pyx_n_s_print); if (!__pyx_print) return -1; } if (stream) { kwargs = PyDict_New(); if (unlikely(!kwargs)) return -1; if (unlikely(PyDict_SetItem(kwargs, __pyx_n_s_file, stream) < 0)) goto bad; if (!newline) { end_string = PyUnicode_FromStringAndSize(" ", 1); if (unlikely(!end_string)) goto bad; if (PyDict_SetItem(kwargs, __pyx_n_s_end, end_string) < 0) { Py_DECREF(end_string); goto bad; } Py_DECREF(end_string); } } else if (!newline) { if (unlikely(!__pyx_print_kwargs)) { __pyx_print_kwargs = PyDict_New(); if (unlikely(!__pyx_print_kwargs)) return -1; end_string = PyUnicode_FromStringAndSize(" ", 1); if (unlikely(!end_string)) return -1; if (PyDict_SetItem(__pyx_print_kwargs, __pyx_n_s_end, end_string) < 0) { Py_DECREF(end_string); return -1; } Py_DECREF(end_string); } kwargs = __pyx_print_kwargs; } result = PyObject_Call(__pyx_print, arg_tuple, kwargs); if (unlikely(kwargs) && (kwargs != __pyx_print_kwargs)) Py_DECREF(kwargs); if (!result) return -1; Py_DECREF(result); return 0; bad: if (kwargs != __pyx_print_kwargs) Py_XDECREF(kwargs); return -1; } #endif /* Declarations */ #if CYTHON_CCOMPLEX #ifdef __cplusplus static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { return ::std::complex< float >(x, y); } #else static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { return x + y*(__pyx_t_float_complex)_Complex_I; } #endif #else static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { __pyx_t_float_complex z; z.real = x; z.imag = y; return z; } #endif /* Arithmetic */ #if CYTHON_CCOMPLEX #else static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { return (a.real == b.real) && (a.imag == b.imag); } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real + b.real; z.imag = a.imag + b.imag; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real - b.real; z.imag = a.imag - b.imag; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real * b.real - a.imag * b.imag; z.imag = a.real * b.imag + a.imag * b.real; return z; } #if 1 static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { if (b.imag == 0) { return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); } else if (fabsf(b.real) >= fabsf(b.imag)) { if (b.real == 0 && b.imag == 0) { return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { float r = b.imag / b.real; float s = (float)(1.0) / (b.real + b.imag * r); return __pyx_t_float_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { float r = b.real / b.imag; float s = (float)(1.0) / (b.imag + b.real * r); return __pyx_t_float_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } } #else static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { if (b.imag == 0) { return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); } else { float denom = b.real * b.real + b.imag * b.imag; return __pyx_t_float_complex_from_parts( (a.real * b.real + a.imag * b.imag) / denom, (a.imag * b.real - a.real * b.imag) / denom); } } #endif static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { __pyx_t_float_complex z; z.real = -a.real; z.imag = -a.imag; return z; } static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { return (a.real == 0) && (a.imag == 0); } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { __pyx_t_float_complex z; z.real = a.real; z.imag = -a.imag; return z; } #if 1 static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { #if !defined(HAVE_HYPOT) || defined(_MSC_VER) return sqrtf(z.real*z.real + z.imag*z.imag); #else return hypotf(z.real, z.imag); #endif } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; float r, lnr, theta, z_r, z_theta; if (b.imag == 0 && b.real == (int)b.real) { if (b.real < 0) { float denom = a.real * a.real + a.imag * a.imag; a.real = a.real / denom; a.imag = -a.imag / denom; b.real = -b.real; } switch ((int)b.real) { case 0: z.real = 1; z.imag = 0; return z; case 1: return a; case 2: return __Pyx_c_prod_float(a, a); case 3: z = __Pyx_c_prod_float(a, a); return __Pyx_c_prod_float(z, a); case 4: z = __Pyx_c_prod_float(a, a); return __Pyx_c_prod_float(z, z); } } if (a.imag == 0) { if (a.real == 0) { return a; } else if (b.imag == 0) { z.real = powf(a.real, b.real); z.imag = 0; return z; } else if (a.real > 0) { r = a.real; theta = 0; } else { r = -a.real; theta = atan2f(0.0, -1.0); } } else { r = __Pyx_c_abs_float(a); theta = atan2f(a.imag, a.real); } lnr = logf(r); z_r = expf(lnr * b.real - theta * b.imag); z_theta = theta * b.real + lnr * b.imag; z.real = z_r * cosf(z_theta); z.imag = z_r * sinf(z_theta); return z; } #endif #endif /* Declarations */ #if CYTHON_CCOMPLEX #ifdef __cplusplus static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { return ::std::complex< double >(x, y); } #else static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { return x + y*(__pyx_t_double_complex)_Complex_I; } #endif #else static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { __pyx_t_double_complex z; z.real = x; z.imag = y; return z; } #endif /* Arithmetic */ #if CYTHON_CCOMPLEX #else static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { return (a.real == b.real) && (a.imag == b.imag); } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real + b.real; z.imag = a.imag + b.imag; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real - b.real; z.imag = a.imag - b.imag; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real * b.real - a.imag * b.imag; z.imag = a.real * b.imag + a.imag * b.real; return z; } #if 1 static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { if (b.imag == 0) { return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); } else if (fabs(b.real) >= fabs(b.imag)) { if (b.real == 0 && b.imag == 0) { return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); } else { double r = b.imag / b.real; double s = (double)(1.0) / (b.real + b.imag * r); return __pyx_t_double_complex_from_parts( (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); } } else { double r = b.real / b.imag; double s = (double)(1.0) / (b.imag + b.real * r); return __pyx_t_double_complex_from_parts( (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); } } #else static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { if (b.imag == 0) { return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); } else { double denom = b.real * b.real + b.imag * b.imag; return __pyx_t_double_complex_from_parts( (a.real * b.real + a.imag * b.imag) / denom, (a.imag * b.real - a.real * b.imag) / denom); } } #endif static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { __pyx_t_double_complex z; z.real = -a.real; z.imag = -a.imag; return z; } static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { return (a.real == 0) && (a.imag == 0); } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { __pyx_t_double_complex z; z.real = a.real; z.imag = -a.imag; return z; } #if 1 static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { #if !defined(HAVE_HYPOT) || defined(_MSC_VER) return sqrt(z.real*z.real + z.imag*z.imag); #else return hypot(z.real, z.imag); #endif } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; double r, lnr, theta, z_r, z_theta; if (b.imag == 0 && b.real == (int)b.real) { if (b.real < 0) { double denom = a.real * a.real + a.imag * a.imag; a.real = a.real / denom; a.imag = -a.imag / denom; b.real = -b.real; } switch ((int)b.real) { case 0: z.real = 1; z.imag = 0; return z; case 1: return a; case 2: return __Pyx_c_prod_double(a, a); case 3: z = __Pyx_c_prod_double(a, a); return __Pyx_c_prod_double(z, a); case 4: z = __Pyx_c_prod_double(a, a); return __Pyx_c_prod_double(z, z); } } if (a.imag == 0) { if (a.real == 0) { return a; } else if (b.imag == 0) { z.real = pow(a.real, b.real); z.imag = 0; return z; } else if (a.real > 0) { r = a.real; theta = 0; } else { r = -a.real; theta = atan2(0.0, -1.0); } } else { r = __Pyx_c_abs_double(a); theta = atan2(a.imag, a.real); } lnr = log(r); z_r = exp(lnr * b.real - theta * b.imag); z_theta = theta * b.real + lnr * b.imag; z.real = z_r * cos(z_theta); z.imag = z_r * sin(z_theta); return z; } #endif #endif /* MemviewSliceCopyTemplate */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, const char *mode, int ndim, size_t sizeof_dtype, int contig_flag, int dtype_is_object) { __Pyx_RefNannyDeclarations int i; __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; struct __pyx_memoryview_obj *from_memview = from_mvs->memview; Py_buffer *buf = &from_memview->view; PyObject *shape_tuple = NULL; PyObject *temp_int = NULL; struct __pyx_array_obj *array_obj = NULL; struct __pyx_memoryview_obj *memview_obj = NULL; __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); for (i = 0; i < ndim; i++) { if (unlikely(from_mvs->suboffsets[i] >= 0)) { PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " "indirect dimensions (axis %d)", i); goto fail; } } shape_tuple = PyTuple_New(ndim); if (unlikely(!shape_tuple)) { goto fail; } __Pyx_GOTREF(shape_tuple); for(i = 0; i < ndim; i++) { temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); if(unlikely(!temp_int)) { goto fail; } else { PyTuple_SET_ITEM(shape_tuple, i, temp_int); temp_int = NULL; } } array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); if (unlikely(!array_obj)) { goto fail; } __Pyx_GOTREF(array_obj); memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( (PyObject *) array_obj, contig_flag, dtype_is_object, from_mvs->memview->typeinfo); if (unlikely(!memview_obj)) goto fail; if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) goto fail; if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, dtype_is_object) < 0)) goto fail; goto no_fail; fail: __Pyx_XDECREF(new_mvs.memview); new_mvs.memview = NULL; new_mvs.data = NULL; no_fail: __Pyx_XDECREF(shape_tuple); __Pyx_XDECREF(temp_int); __Pyx_XDECREF(array_obj); __Pyx_RefNannyFinishContext(); return new_mvs; } /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wconversion" #endif const int neg_one = (int) -1, const_zero = (int) 0; #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic pop #endif const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) case -2: if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -3: if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -4: if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; } #endif if (sizeof(int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (int) -1; } } else { int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (int) -1; val = __Pyx_PyInt_As_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to int"); return (int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to int"); return (int) -1; } /* CIntFromPy */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wconversion" #endif const long neg_one = (long) -1, const_zero = (long) 0; #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic pop #endif const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(long) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (long) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (long) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(long) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) case -2: if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -3: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -4: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; } #endif if (sizeof(long) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else long val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (long) -1; } } else { long val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (long) -1; val = __Pyx_PyInt_As_long(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to long"); return (long) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to long"); return (long) -1; } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wconversion" #endif const long neg_one = (long) -1, const_zero = (long) 0; #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic pop #endif const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(long), little, !is_unsigned); } } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wconversion" #endif const int neg_one = (int) -1, const_zero = (int) 0; #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic pop #endif const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(int) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(int), little, !is_unsigned); } } /* CIntFromPy */ static CYTHON_INLINE signed char __Pyx_PyInt_As_signed__char(PyObject *x) { #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wconversion" #endif const signed char neg_one = (signed char) -1, const_zero = (signed char) 0; #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic pop #endif const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(signed char) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(signed char, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (signed char) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (signed char) 0; case 1: __PYX_VERIFY_RETURN_INT(signed char, digit, digits[0]) case 2: if (8 * sizeof(signed char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) >= 2 * PyLong_SHIFT) { return (signed char) (((((signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0])); } } break; case 3: if (8 * sizeof(signed char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) >= 3 * PyLong_SHIFT) { return (signed char) (((((((signed char)digits[2]) << PyLong_SHIFT) | (signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0])); } } break; case 4: if (8 * sizeof(signed char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) >= 4 * PyLong_SHIFT) { return (signed char) (((((((((signed char)digits[3]) << PyLong_SHIFT) | (signed char)digits[2]) << PyLong_SHIFT) | (signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (signed char) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(signed char) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(signed char, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(signed char) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(signed char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (signed char) 0; case -1: __PYX_VERIFY_RETURN_INT(signed char, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(signed char, digit, +digits[0]) case -2: if (8 * sizeof(signed char) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) - 1 > 2 * PyLong_SHIFT) { return (signed char) (((signed char)-1)*(((((signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0]))); } } break; case 2: if (8 * sizeof(signed char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) - 1 > 2 * PyLong_SHIFT) { return (signed char) ((((((signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0]))); } } break; case -3: if (8 * sizeof(signed char) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) - 1 > 3 * PyLong_SHIFT) { return (signed char) (((signed char)-1)*(((((((signed char)digits[2]) << PyLong_SHIFT) | (signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0]))); } } break; case 3: if (8 * sizeof(signed char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) - 1 > 3 * PyLong_SHIFT) { return (signed char) ((((((((signed char)digits[2]) << PyLong_SHIFT) | (signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0]))); } } break; case -4: if (8 * sizeof(signed char) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) - 1 > 4 * PyLong_SHIFT) { return (signed char) (((signed char)-1)*(((((((((signed char)digits[3]) << PyLong_SHIFT) | (signed char)digits[2]) << PyLong_SHIFT) | (signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0]))); } } break; case 4: if (8 * sizeof(signed char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(signed char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(signed char) - 1 > 4 * PyLong_SHIFT) { return (signed char) ((((((((((signed char)digits[3]) << PyLong_SHIFT) | (signed char)digits[2]) << PyLong_SHIFT) | (signed char)digits[1]) << PyLong_SHIFT) | (signed char)digits[0]))); } } break; } #endif if (sizeof(signed char) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(signed char, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(signed char) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(signed char, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else signed char val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (signed char) -1; } } else { signed char val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (signed char) -1; val = __Pyx_PyInt_As_signed__char(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to signed char"); return (signed char) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to signed char"); return (signed char) -1; } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_bool(npy_bool value) { #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wconversion" #endif const npy_bool neg_one = (npy_bool) -1, const_zero = (npy_bool) 0; #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic pop #endif const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(npy_bool) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(npy_bool) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(npy_bool) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(npy_bool) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(npy_bool) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(npy_bool), little, !is_unsigned); } } /* PrintOne */ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3 static int __Pyx_PrintOne(PyObject* f, PyObject *o) { if (!f) { if (!(f = __Pyx_GetStdout())) return -1; } Py_INCREF(f); if (PyFile_SoftSpace(f, 0)) { if (PyFile_WriteString(" ", f) < 0) goto error; } if (PyFile_WriteObject(o, f, Py_PRINT_RAW) < 0) goto error; if (PyFile_WriteString("\n", f) < 0) goto error; Py_DECREF(f); return 0; error: Py_DECREF(f); return -1; /* the line below is just to avoid C compiler * warnings about unused functions */ return __Pyx_Print(f, NULL, 0); } #else static int __Pyx_PrintOne(PyObject* stream, PyObject *o) { int res; PyObject* arg_tuple = PyTuple_Pack(1, o); if (unlikely(!arg_tuple)) return -1; res = __Pyx_Print(stream, arg_tuple, 1); Py_DECREF(arg_tuple); return res; } #endif /* CIntFromPy */ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wconversion" #endif const char neg_one = (char) -1, const_zero = (char) 0; #ifdef __Pyx_HAS_GCC_DIAGNOSTIC #pragma GCC diagnostic pop #endif const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(char) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (char) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (char) 0; case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) case 2: if (8 * sizeof(char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; case 3: if (8 * sizeof(char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; case 4: if (8 * sizeof(char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (char) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(char) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (char) 0; case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) case -2: if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 2: if (8 * sizeof(char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case -3: if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 3: if (8 * sizeof(char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case -4: if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 4: if (8 * sizeof(char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; } #endif if (sizeof(char) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else char val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (char) -1; } } else { char val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (char) -1; val = __Pyx_PyInt_As_char(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to char"); return (char) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to char"); return (char) -1; } /* CheckBinaryVersion */ static int __Pyx_check_binary_version(void) { char ctversion[5]; int same=1, i, found_dot; const char* rt_from_call = Py_GetVersion(); PyOS_snprintf(ctversion, 5, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); found_dot = 0; for (i = 0; i < 4; i++) { if (!ctversion[i]) { same = (rt_from_call[i] < '0' || rt_from_call[i] > '9'); break; } if (rt_from_call[i] != ctversion[i]) { same = 0; break; } } if (!same) { char rtversion[5] = {'\0'}; char message[200]; for (i=0; i<4; ++i) { if (rt_from_call[i] == '.') { if (found_dot) break; found_dot = 1; } else if (rt_from_call[i] < '0' || rt_from_call[i] > '9') { break; } rtversion[i] = rt_from_call[i]; } PyOS_snprintf(message, sizeof(message), "compiletime version %s of module '%.100s' " "does not match runtime version %s", ctversion, __Pyx_MODULE_NAME, rtversion); return PyErr_WarnEx(NULL, message, 1); } return 0; } /* InitStrings */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 if (t->is_unicode) { *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); } else if (t->intern) { *t->p = PyString_InternFromString(t->s); } else { *t->p = PyString_FromStringAndSize(t->s, t->n - 1); } #else if (t->is_unicode | t->is_str) { if (t->intern) { *t->p = PyUnicode_InternFromString(t->s); } else if (t->encoding) { *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); } else { *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); } } else { *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); } #endif if (!*t->p) return -1; if (PyObject_Hash(*t->p) == -1) return -1; ++t; } return 0; } static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); } static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { Py_ssize_t ignore; return __Pyx_PyObject_AsStringAndSize(o, &ignore); } #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT #if !CYTHON_PEP393_ENABLED static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { char* defenc_c; PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); if (!defenc) return NULL; defenc_c = PyBytes_AS_STRING(defenc); #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII { char* end = defenc_c + PyBytes_GET_SIZE(defenc); char* c; for (c = defenc_c; c < end; c++) { if ((unsigned char) (*c) >= 128) { PyUnicode_AsASCIIString(o); return NULL; } } } #endif *length = PyBytes_GET_SIZE(defenc); return defenc_c; } #else static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII if (likely(PyUnicode_IS_ASCII(o))) { *length = PyUnicode_GET_LENGTH(o); return PyUnicode_AsUTF8(o); } else { PyUnicode_AsASCIIString(o); return NULL; } #else return PyUnicode_AsUTF8AndSize(o, length); #endif } #endif #endif static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && #endif PyUnicode_Check(o)) { return __Pyx_PyUnicode_AsStringAndSize(o, length); } else #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); } else #endif { char* result; int r = PyBytes_AsStringAndSize(o, &result, length); if (unlikely(r < 0)) { return NULL; } else { return result; } } } static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { int is_true = x == Py_True; if (is_true | (x == Py_False) | (x == Py_None)) return is_true; else return PyObject_IsTrue(x); } static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { int retval; if (unlikely(!x)) return -1; retval = __Pyx_PyObject_IsTrue(x); Py_DECREF(x); return retval; } static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { #if PY_MAJOR_VERSION >= 3 if (PyLong_Check(result)) { if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, "__int__ returned non-int (type %.200s). " "The ability to return an instance of a strict subclass of int " "is deprecated, and may be removed in a future version of Python.", Py_TYPE(result)->tp_name)) { Py_DECREF(result); return NULL; } return result; } #endif PyErr_Format(PyExc_TypeError, "__%.4s__ returned non-%.4s (type %.200s)", type_name, type_name, Py_TYPE(result)->tp_name); Py_DECREF(result); return NULL; } static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { #if CYTHON_USE_TYPE_SLOTS PyNumberMethods *m; #endif const char *name = NULL; PyObject *res = NULL; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x) || PyLong_Check(x))) #else if (likely(PyLong_Check(x))) #endif return __Pyx_NewRef(x); #if CYTHON_USE_TYPE_SLOTS m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { name = "int"; res = m->nb_int(x); } else if (m && m->nb_long) { name = "long"; res = m->nb_long(x); } #else if (likely(m && m->nb_int)) { name = "int"; res = m->nb_int(x); } #endif #else if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { res = PyNumber_Int(x); } #endif if (likely(res)) { #if PY_MAJOR_VERSION < 3 if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { #else if (unlikely(!PyLong_CheckExact(res))) { #endif return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); } } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_TypeError, "an integer is required"); } return res; } static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(b))) { if (sizeof(Py_ssize_t) >= sizeof(long)) return PyInt_AS_LONG(b); else return PyInt_AsSsize_t(b); } #endif if (likely(PyLong_CheckExact(b))) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)b)->ob_digit; const Py_ssize_t size = Py_SIZE(b); if (likely(__Pyx_sst_abs(size) <= 1)) { ival = likely(size) ? digits[0] : 0; if (size == -1) ival = -ival; return ival; } else { switch (size) { case 2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; } } #endif return PyLong_AsSsize_t(b); } x = PyNumber_Index(b); if (!x) return -1; ival = PyInt_AsSsize_t(x); Py_DECREF(x); return ival; } static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject* o) { if (sizeof(Py_hash_t) == sizeof(Py_ssize_t)) { return (Py_hash_t) __Pyx_PyIndex_AsSsize_t(o); #if PY_MAJOR_VERSION < 3 } else if (likely(PyInt_CheckExact(o))) { return PyInt_AS_LONG(o); #endif } else { Py_ssize_t ival; PyObject *x; x = PyNumber_Index(o); if (!x) return -1; ival = PyInt_AsLong(x); Py_DECREF(x); return ival; } } static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); } static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { return PyInt_FromSize_t(ival); } #endif /* Py_PYTHON_H */ ================================================ FILE: custom_mc/_marching_cubes_lewiner_cy.pyx ================================================ #cython: cdivision=True #cython: boundscheck=False #cython: nonecheck=False #cython: wraparound=False """ This is an implementation of the marching cubes algorithm proposed in: Efficient implementation of Marching Cubes' cases with topological guarantees. Thomas Lewiner, Helio Lopes, Antonio Wilson Vieira and Geovan Tavares. Journal of Graphics Tools 8(2): pp. 1-15 (december 2003) This algorithm has the advantage that it provides topologically correct results, and the algorithms implementation is relatively simple. Most of the magic is in the lookup tables, which are provided as open source. Originally implemented in C++ by Thomas Lewiner in 2002, ported to Cython by Almar Klein in 2012. Adapted for scikit-image in 2016. """ # Cython specific imports import numpy as np cimport numpy as np import cython np.import_array() # Enable low level memory management from libc.stdlib cimport malloc, free # Define tiny winy number cdef double FLT_EPSILON = np.spacing(1.0) #0.0000001 # Define abs function for doubles cdef inline double dabs(double a): return a if a>=0 else -a cdef inline int imin(int a, int b): return a if a0]]] vertices2 = vertices[vertices_ok] arrays2 = [arr[vertices_ok] for arr in arrays] return (vertices2, faces2) + tuple(arrays2) cdef class Cell: """ Class to keep track of some stuff during the whole cube marching procedure. This "struct" keeps track of the current cell location, and the values of corners of the cube. Gradients for the cube corners are calculated when needed. Additionally, it keeps track of the array of vertices, faces and normals. Notes on vertices ----------------- The vertices are stored in a C-array that is increased in size with factors of two if needed. The same applies to the faces and normals. Notes on faces -------------- To keep track of the vertices already defined, this class maintains two faceLayer arrays. faceLayer1 is of the current layer (z-value) and faceLayer2 is of the next. Both face layers have 4 elements per cell in that layer, 1 for each unique edge per cell (see get_index_in_facelayer). These are initialized as -1, and set to the index in the vertex array when a new vertex is created. In summary, this allows us to keep track of the already created vertices without keeping a very big array. Notes on normals ---------------- The normal is simply defined as the gradient. Each time that a face is created, we also add the gradient of that vertex position to the normals array. The gradients are all calculated from the differences between the 8 corners of the current cube, but because the final value of a normal was contributed from multiple cells, the normals are quite accurate. """ # Reference to LUTS object cdef LutProvider luts # Location of cube cdef int x cdef int y cdef int z # Stepsize cdef int step # Values of cube corners (isovalue subtracted) cdef double v0 cdef double v1 cdef double v2 cdef double v3 cdef double v4 cdef double v5 cdef double v6 cdef double v7 # Small arrays to store the above values in (allowing indexing) # and also the gradient at these points cdef double *vv cdef double *vg # Max value of the eight corners cdef double vmax # Vertex position of center of cube (only calculated if needed) cdef double v12_x cdef double v12_y cdef double v12_z # And corresponding gradient cdef double v12_xg cdef double v12_yg cdef double v12_zg cdef int v12_calculated # a boolean # The index value, our magic 256 bit word cdef int index # Dimensions of the total volume cdef int nx cdef int ny cdef int nz # Arrays with face information cdef int *faceLayer # The current facelayer (reference-copy of one of the below) cdef int *faceLayer1 # The actual first face layer cdef int *faceLayer2 # The actual second face layer # Stuff to store the output vertices cdef float *_vertices cdef float *_normals cdef float *_values cdef int _vertexCount cdef int _vertexMaxCount # Stuff to store the output faces cdef int *_faces cdef int _faceCount cdef int _faceMaxCount def __init__(self, LutProvider luts, int nx, int ny, int nz): self.luts = luts self.nx, self.ny, self.nz = nx, ny, nz # Allocate face layers self.faceLayer1 = malloc(self.nx*self.ny*4 * sizeof(int)) self.faceLayer2 = malloc(self.nx*self.ny*4 * sizeof(int)) if (self.faceLayer1 is NULL or self.faceLayer2 is NULL or self.vv is NULL or self.vg is NULL or self._vertices is NULL or self._normals is NULL or self._values is NULL or self._faces is NULL): raise MemoryError() cdef int i for i in range(self.nx*self.ny*4): self.faceLayer1[i] = -1 self.faceLayer2[i] = -1 self.faceLayer = self.faceLayer1 def __cinit__(self): # Init tiny arrays for vertices and gradients at the vertices self.vv = malloc(8 * sizeof(double)) self.vg = malloc(8*3 * sizeof(double)) # Init face layers self.faceLayer1 = NULL self.faceLayer2 = NULL # Init vertices self._vertexCount = 0 self._vertexMaxCount = 8 self._vertices = malloc(self._vertexMaxCount*3 * sizeof(float)) self._normals = malloc(self._vertexMaxCount*3 * sizeof(float)) self._values = malloc(self._vertexMaxCount * sizeof(float)) # Clear normals and values cdef int i, j if self._values is not NULL and self._normals is not NULL: for i in range(self._vertexMaxCount): self._values[i] = 0.0 for j in range(3): self._normals[i*3+j] = 0.0 # Init faces self._faceCount = 0 self._faceMaxCount = 8 self._faces = malloc(self._faceMaxCount * sizeof(int)) def __dealloc__(self): free(self.vv) free(self.vg) free(self.faceLayer1) free(self.faceLayer2) free(self._vertices) free(self._normals) free(self._values) free(self._faces) cdef void _increase_size_vertices(self): """ Increase the size of the vertices array by a factor two. """ # Allocate new array cdef int newMaxCount = self._vertexMaxCount * 2 cdef float *newVertices = malloc(newMaxCount*3 * sizeof(float)) cdef float *newNormals = malloc(newMaxCount*3 * sizeof(float)) cdef float *newValues = malloc(newMaxCount * sizeof(float)) if newVertices is NULL or newNormals is NULL or newValues is NULL: free(newVertices) free(newNormals) free(newValues) raise MemoryError() # Clear cdef int i, j for i in range(self._vertexCount, newMaxCount): newValues[i] = 0.0 for j in range(3): newNormals[i*3+j] = 0.0 # Copy for i in range(self._vertexCount): newValues[i] = self._values[i] for j in range(3): newVertices[i*3+j] = self._vertices[i*3+j] newNormals[i*3+j] = self._normals[i*3+j] # Apply free(self._vertices); self._vertices = newVertices free(self._normals); self._normals = newNormals free(self._values); self._values = newValues self._vertexMaxCount = newMaxCount cdef void _increase_size_faces(self): """ Increase the size of the faces array by a factor two. """ # Allocate new array cdef int newMaxCount = self._faceMaxCount * 2 cdef int *newFaces = malloc(newMaxCount * sizeof(int)) if newFaces is NULL: raise MemoryError() # Copy cdef int i for i in range(self._faceCount): newFaces[i] = self._faces[i] # Apply free(self._faces) self._faces = newFaces self._faceMaxCount = newMaxCount ## Adding results cdef int add_vertex(self, float x, float y, float z): """ Add a vertex to the result. Return index in vertex array. """ # Check if array is large enough if self._vertexCount >= self._vertexMaxCount: self._increase_size_vertices() # Add vertex self._vertices[self._vertexCount*3+0] = x self._vertices[self._vertexCount*3+1] = y self._vertices[self._vertexCount*3+2] = z self._vertexCount += 1 return self._vertexCount -1 cdef void add_gradient(self, int vertexIndex, float gx, float gy, float gz): """ Add a gradient value to the vertex corresponding to the given index. """ self._normals[vertexIndex*3+0] += gx self._normals[vertexIndex*3+1] += gy self._normals[vertexIndex*3+2] += gz cdef void add_gradient_from_index(self, int vertexIndex, int i, float strength): """ Add a gradient value to the vertex corresponding to the given index. vertexIndex is the index in the large array of vertices that is returned. i is the index of the array of vertices 0-7 for the current cell. """ self.add_gradient(vertexIndex, self.vg[i*3+0] * strength, self.vg[i*3+1] * strength, self.vg[i*3+2] * strength) cdef add_face(self, int index): """ Add a face to the result. Also updates the value. """ # Check if array is large enough if self._faceCount >= self._faceMaxCount: self._increase_size_faces() # Add face self._faces[self._faceCount] = index self._faceCount += 1 # Also update value if self.vmax > self._values[index]: self._values[index] = self.vmax ## Getting results def get_vertices(self): """ Get the final vertex array. """ vertices = np.empty((self._vertexCount,3), np.float32) cdef float [:, :] vertices_ = vertices cdef int i, j for i in range(self._vertexCount): for j in range(3): vertices_[i, j] = self._vertices[i*3+j] return vertices def get_normals(self): """ Get the final normals array. The normals are normalized to unit length. """ normals = np.empty((self._vertexCount,3), np.float32) cdef float [:, :] normals_ = normals cdef int i, j cdef double length, dtmp for i in range(self._vertexCount): length = 0.0 for j in range(3): dtmp = self._normals[i*3+j] # Make it double before taking **2! length += dtmp*dtmp if length > 0.0: length = 1.0 / length**0.5 for j in range(3): normals_[i,j] = self._normals[i*3+j] * length return normals def get_faces(self): faces = np.empty((self._faceCount,), np.int32) cdef int [:] faces_ = faces cdef int i, j for i in range(self._faceCount): faces_[i] = self._faces[i] return faces def get_values(self): values = np.empty((self._vertexCount,), np.float32) cdef float [:] values_ = values cdef int i, j for i in range(self._vertexCount): values_[i] = self._values[i] return values ## Called from marching cube function cdef void new_z_value(self): """ This method should be called each time a new z layer is entered. We will swap the layers with face information and empty the second. """ # Swap layers self.faceLayer1, self.faceLayer2 = self.faceLayer2, self.faceLayer1 # Empty last cdef int i for i in range(self.nx*self.ny*4): self.faceLayer2[i] = -1 cdef void set_cube(self, double isovalue, int x, int y, int z, int step, double v0, double v1, double v2, double v3, double v4, double v5, double v6, double v7): """ Set the cube to the new location. Set the values of the cube corners. The isovalue is subtracted from them, such that in further calculations the isovalue can be taken as zero. This method also calculated the magic 256 word to identify the cases (i.e. cell.index). """ # Set location and step self.x = x self.y = y self.z = z self.step = step # Set values self.v0 = v0 - isovalue self.v1 = v1 - isovalue self.v2 = v2 - isovalue self.v3 = v3 - isovalue self.v4 = v4 - isovalue self.v5 = v5 - isovalue self.v6 = v6 - isovalue self.v7 = v7 - isovalue # Calculate index cdef int index = 0 if self.v0 > 0.0: index += 1 if self.v1 > 0.0: index += 2 if self.v2 > 0.0: index += 4 if self.v3 > 0.0: index += 8 if self.v4 > 0.0: index += 16 if self.v5 > 0.0: index += 32 if self.v6 > 0.0: index += 64 if self.v7 > 0.0: index += 128 self.index = index # Reset c12 self.v12_calculated = 0 cdef void add_triangles(self, Lut lut, int lutIndex, int nt): """ Add triangles. The vertices for the triangles are specified in the given Lut at the specified index. There are nt triangles. The reason that nt should be given is because it is often known beforehand. """ cdef int i, j cdef int vi self.prepare_for_adding_triangles() for i in range(nt): for j in range(3): # Get two sides for each element in this vertex vi = lut.get2(lutIndex, i*3+j) self._add_face_from_edge_index(vi) cdef void add_triangles2(self, Lut lut, int lutIndex, int lutIndex2, int nt): """ Same as add_triangles, except that now the geometry is in a LUT with 3 dimensions, and an extra index is provided. """ cdef int i, j cdef int vi self.prepare_for_adding_triangles() for i in range(nt): for j in range(3): # Get two sides for each element in this vertex vi = lut.get3(lutIndex, lutIndex2, i*3+j) self._add_face_from_edge_index(vi) ## Used internally cdef void _add_face_from_edge_index(self, int vi): """ Add one face from an edge index. Only adds a face if the vertex already exists. Otherwise also adds a vertex and applies interpolation. """ # typedefs cdef int indexInVertexArray, indexInFaceLayer cdef int dx1, dy1, dz1 cdef int dx2, dy2, dz2 cdef int index1, index2 cdef double tmpf1, tmpf2 cdef double fx, fy, fz, ff cdef double stp = self.step # Get index in the face layer and corresponding vertex number indexInFaceLayer = self.get_index_in_facelayer(vi) indexInVertexArray = self.faceLayer[indexInFaceLayer] # If we have the center vertex, we have things pre-calculated, # otherwise we need to interpolate. # In both cases we distinguish between having this vertex already # or not. if vi == 12: # center vertex if self.v12_calculated == 0: self.calculate_center_vertex() if indexInVertexArray >= 0: # Vertex already calculated, only need to add face and gradient self.add_face(indexInVertexArray) self.add_gradient(indexInVertexArray, self.v12_xg, self.v12_yg, self.v12_zg) else: # Add precalculated center vertex position (is interpolated) indexInVertexArray = self.add_vertex( self.v12_x, self.v12_y, self.v12_z) # Update face layer self.faceLayer[indexInFaceLayer] = indexInVertexArray # Add face and gradient self.add_face(indexInVertexArray) self.add_gradient(indexInVertexArray, self.v12_xg, self.v12_yg, self.v12_zg) else: # Get relative edge indices for x, y and z dx1, dx2 = self.luts.EDGESRELX.get2(vi,0), self.luts.EDGESRELX.get2(vi,1) dy1, dy2 = self.luts.EDGESRELY.get2(vi,0), self.luts.EDGESRELY.get2(vi,1) dz1, dz2 = self.luts.EDGESRELZ.get2(vi,0), self.luts.EDGESRELZ.get2(vi,1) # Make two vertex indices index1 = dz1*4 + dy1*2 + dx1 index2 = dz2*4 + dy2*2 + dx2 # Define strength of both corners tmpf1 = 1.0 / (FLT_EPSILON + dabs(self.vv[index1])) tmpf2 = 1.0 / (FLT_EPSILON + dabs(self.vv[index2])) # print('indexInVertexArray', self.x, self.y, self.z, '-', vi, indexInVertexArray, indexInFaceLayer) if indexInVertexArray >= 0: # Vertex already calculated, only need to add face and gradient self.add_face(indexInVertexArray) self.add_gradient_from_index(indexInVertexArray, index1, tmpf1) self.add_gradient_from_index(indexInVertexArray, index2, tmpf2) else: # Interpolate by applying a kind of center-of-mass method fx, fy, fz, ff = 0.0, 0.0, 0.0, 0.0 fx += dx1 * tmpf1; fy += dy1 * tmpf1; fz += dz1 * tmpf1; ff += tmpf1 fx += dx2 * tmpf2; fy += dy2 * tmpf2; fz += dz2 * tmpf2; ff += tmpf2 # Add vertex indexInVertexArray = self.add_vertex( self.x + stp*fx/ff, self.y + stp*fy/ff, self.z + stp*fz/ff ) # Update face layer self.faceLayer[indexInFaceLayer] = indexInVertexArray # Add face and gradient self.add_face(indexInVertexArray) self.add_gradient_from_index(indexInVertexArray, index1, tmpf1) self.add_gradient_from_index(indexInVertexArray, index2, tmpf2) # # Create vertex non-interpolated # self.add_vertex( self.x + 0.5* dx1 + 0.5 * dx2, # self.y + 0.5* dy1 + 0.5 * dy2, # self.z + 0.5* dz1 + 0.5 * dz2 ) cdef int get_index_in_facelayer(self, int vi): """ Get the index of a vertex position, given the edge on which it lies. We keep a list of faces so we can reuse vertices. This improves speed because we need less interpolation, and the result is more compact and can be visualized better because normals can be interpolated. For each cell, we store 4 vertex indices; all other edges can be represented as the edge of another cell. The fourth is the center vertex. This method returns -1 if no vertex has been defined yet. vertices edges edge-indices per cell * 7 ________ 6 _____6__ ________ * /| /| 7/| /| /| /| * / | / | / | /5 | / | / | * 4 /_______ / | /__4____ / 10 /_______ / | * | | |5 | | 11 | | | | | | * | 3|__|_____|2 | |__|__2__| | |__|_____| * | / | / 8 3/ 9 / 2 / | / * | / | / | / | /1 | 1 | / * |/_______|/ |/___0___|/ |/___0___|/ * 0 1 */ """ # Init indices, both are corrected below cdef int i = self.nx * self.y + self.x # Index of cube to get vertex at cdef int j = 0 # Vertex number for that cell cdef int vi_ = vi cdef int *faceLayer # Select either upper or lower half if vi < 8: # 8 horizontal edges if vi < 4: faceLayer = self.faceLayer1 else: vi -= 4 faceLayer = self.faceLayer2 # Calculate actual index based on edge #if vi == 0: pass # no step if vi == 1: # step in x i += self.step j = 1 elif vi == 2: # step in y i += self.nx * self.step elif vi == 3: # no step j = 1 elif vi < 12: # 4 vertical edges faceLayer = self.faceLayer1 j = 2 #if vi == 8: pass # no step if vi == 9: # step in x i += self.step elif vi == 10: # step in x and y i += self.nx * self.step + self.step elif vi == 11: # step in y i += self.nx * self.step else: # center vertex faceLayer = self.faceLayer1 j = 3 # Store facelayer and return index self.faceLayer = faceLayer # Dirty way of returning a value return 4*i + j cdef void prepare_for_adding_triangles(self): """ Calculates some things to help adding the triangles: array with corner values, max corner value, gradient at each corner. """ cdef int i # Copy values in array so we can index them. Note the misalignment # because the numbering does not correspond with bitwise OR of xyz. self.vv[0] = self.v0 self.vv[1] = self.v1 self.vv[2] = self.v3# self.vv[3] = self.v2# self.vv[4] = self.v4 self.vv[5] = self.v5 self.vv[6] = self.v7# self.vv[7] = self.v6# # Calculate max cdef double vmin, vmax vmin, vmax = 0.0, 0.0 for i in range(8): if self.vv[i] > vmax: vmax = self.vv[i] if self.vv[i] < vmin: vmin = self.vv[i] self.vmax = vmax-vmin # Calculate gradients # Derivatives, selected to always point in same direction. # Note that many corners have the same components as other points, # by interpolating and averaging the normals this is solved. # todo: we can potentially reuse these similar to how we store vertex indices in face layers self.vg[0*3+0], self.vg[0*3+1], self.vg[0*3+2] = self.v0-self.v1, self.v0-self.v3, self.v0-self.v4 self.vg[1*3+0], self.vg[1*3+1], self.vg[1*3+2] = self.v0-self.v1, self.v1-self.v2, self.v1-self.v5 self.vg[2*3+0], self.vg[2*3+1], self.vg[2*3+2] = self.v3-self.v2, self.v1-self.v2, self.v2-self.v6 self.vg[3*3+0], self.vg[3*3+1], self.vg[3*3+2] = self.v3-self.v2, self.v0-self.v3, self.v3-self.v7 self.vg[4*3+0], self.vg[4*3+1], self.vg[4*3+2] = self.v4-self.v5, self.v4-self.v7, self.v0-self.v4 self.vg[5*3+0], self.vg[5*3+1], self.vg[5*3+2] = self.v4-self.v5, self.v5-self.v6, self.v1-self.v5 self.vg[6*3+0], self.vg[6*3+1], self.vg[6*3+2] = self.v7-self.v6, self.v5-self.v6, self.v2-self.v6 self.vg[7*3+0], self.vg[7*3+1], self.vg[7*3+2] = self.v7-self.v6, self.v4-self.v7, self.v3-self.v7 cdef void calculate_center_vertex(self): """ Calculate interpolated center vertex and its gradient. """ cdef double v0, v1, v2, v3, v4, v5, v6, v7 cdef double fx, fy, fz, ff fx, fy, fz, ff = 0.0, 0.0, 0.0, 0.0 # Define "strength" of each corner of the cube that we need v0 = 1.0 / (FLT_EPSILON + dabs(self.v0)) v1 = 1.0 / (FLT_EPSILON + dabs(self.v1)) v2 = 1.0 / (FLT_EPSILON + dabs(self.v2)) v3 = 1.0 / (FLT_EPSILON + dabs(self.v3)) v4 = 1.0 / (FLT_EPSILON + dabs(self.v4)) v5 = 1.0 / (FLT_EPSILON + dabs(self.v5)) v6 = 1.0 / (FLT_EPSILON + dabs(self.v6)) v7 = 1.0 / (FLT_EPSILON + dabs(self.v7)) # Apply a kind of center-of-mass method fx += 0.0*v0; fy += 0.0*v0; fz += 0.0*v0; ff += v0 fx += 1.0*v1; fy += 0.0*v1; fz += 0.0*v1; ff += v1 fx += 1.0*v2; fy += 1.0*v2; fz += 0.0*v2; ff += v2 fx += 0.0*v3; fy += 1.0*v3; fz += 0.0*v3; ff += v3 fx += 0.0*v4; fy += 0.0*v4; fz += 1.0*v4; ff += v4 fx += 1.0*v5; fy += 0.0*v5; fz += 1.0*v5; ff += v5 fx += 1.0*v6; fy += 1.0*v6; fz += 1.0*v6; ff += v6 fx += 0.0*v7; fy += 1.0*v7; fz += 1.0*v7; ff += v7 # Store cdef double stp = self.step self.v12_x = self.x + stp * fx / ff self.v12_y = self.y + stp * fy / ff self.v12_z = self.z + stp * fz / ff # Also pre-calculate gradient of center # note that prepare_for_adding_triangles() must have been called for # the gradient data to exist. self.v12_xg = ( v0*self.vg[0*3+0] + v1*self.vg[1*3+0] + v2*self.vg[2*3+0] + v3*self.vg[3*3+0] + v4*self.vg[4*3+0] + v5*self.vg[5*3+0] + v6*self.vg[6*3+0] + v7*self.vg[7*3+0] ) self.v12_yg = ( v0*self.vg[0*3+1] + v1*self.vg[1*3+1] + v2*self.vg[2*3+1] + v3*self.vg[3*3+1] + v4*self.vg[4*3+1] + v5*self.vg[5*3+1] + v6*self.vg[6*3+1] + v7*self.vg[7*3+1] ) self.v12_xg = ( v0*self.vg[0*3+2] + v1*self.vg[1*3+2] + v2*self.vg[2*3+2] + v3*self.vg[3*3+2] + v4*self.vg[4*3+2] + v5*self.vg[5*3+2] + v6*self.vg[6*3+2] + v7*self.vg[7*3+2] ) # Set flag that this stuff is calculated self.v12_calculated = 1 cdef class Lut: """ Representation of a lookup table. The tables are initially defined as numpy arrays. On initialization, this class converts them to a C array for fast access. This class defines functions to look up values using 1, 2 or 3 indices. """ cdef signed char* VALUES cdef int L0 # Length cdef int L1 # size of tuple cdef int L2 # size of tuple in tuple (if any) def __init__(self, array): # Get the shape of the LUT self.L1 = 1 self.L2 = 1 # self.L0 = array.shape[0] if array.ndim > 1: self.L1 = array.shape[1] if array.ndim > 2: self.L2 = array.shape[2] # Copy the contents array = array.ravel() cdef int n, N N = self.L0 * self.L1 * self.L2 self.VALUES = malloc(N * sizeof(signed char)) if self.VALUES is NULL: raise MemoryError() for n in range(N): self.VALUES[n] = array[n] def __cinit__(self): self.VALUES = NULL def __dealloc__(self): if self.VALUES is not NULL: free(self.VALUES) cdef int get1(self, int i0): return self.VALUES[i0] cdef int get2(self, int i0, int i1): return self.VALUES[i0*self.L1 + i1] cdef int get3(self, int i0, int i1, int i2): return self.VALUES[i0*self.L1*self.L2 + i1*self.L2 + i2] cdef class LutProvider: """ Class that provides a common interface to the many lookup tables used by the algorithm. All the lists of lut names are autogenerated to prevent human error. """ cdef Lut EDGESRELX # Edges relative X cdef Lut EDGESRELY cdef Lut EDGESRELZ cdef Lut CASESCLASSIC cdef Lut CASES cdef Lut TILING1 cdef Lut TILING2 cdef Lut TILING3_1 cdef Lut TILING3_2 cdef Lut TILING4_1 cdef Lut TILING4_2 cdef Lut TILING5 cdef Lut TILING6_1_1 cdef Lut TILING6_1_2 cdef Lut TILING6_2 cdef Lut TILING7_1 cdef Lut TILING7_2 cdef Lut TILING7_3 cdef Lut TILING7_4_1 cdef Lut TILING7_4_2 cdef Lut TILING8 cdef Lut TILING9 cdef Lut TILING10_1_1 cdef Lut TILING10_1_1_ cdef Lut TILING10_1_2 cdef Lut TILING10_2 cdef Lut TILING10_2_ cdef Lut TILING11 cdef Lut TILING12_1_1 cdef Lut TILING12_1_1_ cdef Lut TILING12_1_2 cdef Lut TILING12_2 cdef Lut TILING12_2_ cdef Lut TILING13_1 cdef Lut TILING13_1_ cdef Lut TILING13_2 cdef Lut TILING13_2_ cdef Lut TILING13_3 cdef Lut TILING13_3_ cdef Lut TILING13_4 cdef Lut TILING13_5_1 cdef Lut TILING13_5_2 cdef Lut TILING14 cdef Lut TEST3 cdef Lut TEST4 cdef Lut TEST6 cdef Lut TEST7 cdef Lut TEST10 cdef Lut TEST12 cdef Lut TEST13 cdef Lut SUBCONFIG13 def __init__(self, EDGESRELX, EDGESRELY, EDGESRELZ, CASESCLASSIC, CASES, TILING1, TILING2, TILING3_1, TILING3_2, TILING4_1, TILING4_2, TILING5, TILING6_1_1, TILING6_1_2, TILING6_2, TILING7_1, TILING7_2, TILING7_3, TILING7_4_1, TILING7_4_2, TILING8, TILING9, TILING10_1_1, TILING10_1_1_, TILING10_1_2, TILING10_2, TILING10_2_, TILING11, TILING12_1_1, TILING12_1_1_, TILING12_1_2, TILING12_2, TILING12_2_, TILING13_1, TILING13_1_, TILING13_2, TILING13_2_, TILING13_3, TILING13_3_, TILING13_4, TILING13_5_1, TILING13_5_2, TILING14, TEST3, TEST4, TEST6, TEST7, TEST10, TEST12, TEST13, SUBCONFIG13, ): self.EDGESRELX = Lut(EDGESRELX) self.EDGESRELY = Lut(EDGESRELY) self.EDGESRELZ = Lut(EDGESRELZ) self.CASESCLASSIC = Lut(CASESCLASSIC) self.CASES = Lut(CASES) self.TILING1 = Lut(TILING1) self.TILING2 = Lut(TILING2) self.TILING3_1 = Lut(TILING3_1) self.TILING3_2 = Lut(TILING3_2) self.TILING4_1 = Lut(TILING4_1) self.TILING4_2 = Lut(TILING4_2) self.TILING5 = Lut(TILING5) self.TILING6_1_1 = Lut(TILING6_1_1) self.TILING6_1_2 = Lut(TILING6_1_2) self.TILING6_2 = Lut(TILING6_2) self.TILING7_1 = Lut(TILING7_1) self.TILING7_2 = Lut(TILING7_2) self.TILING7_3 = Lut(TILING7_3) self.TILING7_4_1 = Lut(TILING7_4_1) self.TILING7_4_2 = Lut(TILING7_4_2) self.TILING8 = Lut(TILING8) self.TILING9 = Lut(TILING9) self.TILING10_1_1 = Lut(TILING10_1_1) self.TILING10_1_1_ = Lut(TILING10_1_1_) self.TILING10_1_2 = Lut(TILING10_1_2) self.TILING10_2 = Lut(TILING10_2) self.TILING10_2_ = Lut(TILING10_2_) self.TILING11 = Lut(TILING11) self.TILING12_1_1 = Lut(TILING12_1_1) self.TILING12_1_1_ = Lut(TILING12_1_1_) self.TILING12_1_2 = Lut(TILING12_1_2) self.TILING12_2 = Lut(TILING12_2) self.TILING12_2_ = Lut(TILING12_2_) self.TILING13_1 = Lut(TILING13_1) self.TILING13_1_ = Lut(TILING13_1_) self.TILING13_2 = Lut(TILING13_2) self.TILING13_2_ = Lut(TILING13_2_) self.TILING13_3 = Lut(TILING13_3) self.TILING13_3_ = Lut(TILING13_3_) self.TILING13_4 = Lut(TILING13_4) self.TILING13_5_1 = Lut(TILING13_5_1) self.TILING13_5_2 = Lut(TILING13_5_2) self.TILING14 = Lut(TILING14) self.TEST3 = Lut(TEST3) self.TEST4 = Lut(TEST4) self.TEST6 = Lut(TEST6) self.TEST7 = Lut(TEST7) self.TEST10 = Lut(TEST10) self.TEST12 = Lut(TEST12) self.TEST13 = Lut(TEST13) self.SUBCONFIG13 = Lut(SUBCONFIG13) def marching_cubes(float[:, :, :] im not None, double isovalue, LutProvider luts, int st=1, int classic=0, np.ndarray[np.npy_bool, ndim=3, cast=True] mask=None): """ marching_cubes(im, double isovalue, LutProvider luts, int st=1, int classic=0) Main entry to apply marching cubes. Masked version of marching cubes. This function will check a masking array (same size as im) to decide if the algorithm must be computed for a given voxel. This adds a small overhead that rapidly gets compensated by the fewer computed cubes Returns (vertices, faces, normals, values) """ # Get dimemsnions cdef int Nx, Ny, Nz Nx, Ny, Nz = im.shape[2], im.shape[1], im.shape[0] # Create cell to use throughout cdef Cell cell = Cell(luts, Nx, Ny, Nz) # Typedef variables cdef int x, y, z, x_st, y_st, z_st cdef int nt cdef int case, config, subconfig cdef bint no_mask = mask is None # Unfortunately specifying a step in range() significantly degrades # performance. Therefore we use a while loop. # we have: max_x = Nx_bound + st + st - 1 # -> Nx_bound = max_allowable_x + 1 - 2 * st # -> Nx_bound = Nx - 2 * st assert st > 0 cdef int Nx_bound, Ny_bound, Nz_bound Nx_bound, Ny_bound, Nz_bound = Nx - 2 * st, Ny - 2 * st, Nz - 2 * st # precalculated index range z = -st while z < Nz_bound: z += st z_st = z + st cell.new_z_value() # Indicate that we enter a new layer y = -st while y < Ny_bound: y += st y_st = y + st x = -st while x < Nx_bound: x += st x_st = x + st if no_mask or mask[z_st, y_st, x_st]: # Initialize cell cell.set_cube(isovalue, x, y, z, st, im[z ,y, x], im[z ,y, x_st], im[z ,y_st, x_st], im[z ,y_st, x], im[z_st,y, x], im[z_st,y, x_st], im[z_st,y_st, x_st], im[z_st,y_st, x] ) # Do classic! if classic: # Determine number of vertices nt = 0 while luts.CASESCLASSIC.get2(cell.index, 3*nt) != -1: nt += 1 # Add triangles if nt > 0: cell.add_triangles(luts.CASESCLASSIC, cell.index, nt) else: # Get case, if non-nul, enter the big switch case = luts.CASES.get2(cell.index, 0) if case > 0: config = luts.CASES.get2(cell.index, 1) the_big_switch(luts, cell, case, config) # Done return cell.get_vertices(), cell.get_faces(), cell.get_normals(), cell.get_values() def marching_cubes_udf(float[:, :, :] im not None, float[:, :, :, :] grads not None, LutProvider luts, int st=1, int classic=0, np.ndarray[np.npy_bool, ndim=3, cast=True] mask=None): """ marching_cubes(im, grads, double isovalue, LutProvider luts, int st=1, int classic=0) Main entry to apply marching cubes. Masked version of marching cubes. This function will check a masking array (same size as im) to decide if the algorithm must be computed for a given voxel. This adds a small overhead that rapidly gets compensated by the fewer computed cubes Returns (vertices, faces, normals, values) """ # Get dimemsnions cdef int Nx, Ny, Nz Nx, Ny, Nz = im.shape[2], im.shape[1], im.shape[0] # Compute voxel size cdef voxel_size = 2.0 / (Nx - 1) # Create cell to use throughout cdef Cell cell = Cell(luts, Nx, Ny, Nz) # Typedef variables cdef int x, y, z, x_st, y_st, z_st cdef int nt cdef int case, config, subconfig cdef bint no_mask = mask is None # Unfortunately specifying a step in range() significantly degrades # performance. Therefore we use a while loop. # we have: max_x = Nx_bound + st + st - 1 # -> Nx_bound = max_allowable_x + 1 - 2 * st # -> Nx_bound = Nx - 2 * st assert st > 0 cdef int Nx_bound, Ny_bound, Nz_bound Nx_bound, Ny_bound, Nz_bound = Nx - 2 * st, Ny - 2 * st, Nz - 2 * st # precalculated index range cdef float[:] base_vec cdef float avg_cube_val cdef float max_cube_val cdef np.ndarray inwards_facing_normals_ref= np.array([[[[1., 1., 1.], [1., 1., -1.]], [[1., -1., 1.], [1., -1., -1.]]], [[[-1., 1., 1.], [-1., 1., -1.]], [[-1., -1., 1.], [-1., -1., -1.]]]], dtype=np.float32) cdef int inwards_facing_normals_bool z = -st while z < Nz_bound: z += st z_st = z + st cell.new_z_value() # Indicate that we enter a new layer y = -st while y < Ny_bound: y += st y_st = y + st x = -st while x < Nx_bound: x += st x_st = x + st if no_mask or mask[z_st, y_st, x_st]: avg_cube_val = avg_cube( im[z ,y, x], im[z ,y, x_st], im[z ,y_st, x_st], im[z ,y_st, x], im[z_st,y, x], im[z_st,y, x_st], im[z_st,y_st, x_st], im[z_st,y_st, x]) max_cube_val = max_cube( im[z ,y, x], im[z ,y, x_st], im[z ,y_st, x_st], im[z ,y_st, x], im[z_st,y, x], im[z_st,y, x_st], im[z_st,y_st, x_st], im[z_st,y_st, x]) if avg_cube_val < 1.05 * voxel_size and max_cube_val <= 1.74 * voxel_size: # Choose base vector for the dot product that is not (0,0,0) # in a corner of the cube if not non_zero_norm(grads[z,y,x]) == 0: base_vec = grads[z,y,x] elif not non_zero_norm(grads[z,y,x_st]) == 0: base_vec = grads[z,y,x_st] elif not non_zero_norm(grads[z,y_st,x]) == 0: base_vec = grads[z,y_st,x] elif not non_zero_norm(grads[z,y_st,x_st]) == 0: base_vec = grads[z,y_st,x_st] elif not non_zero_norm(grads[z_st,y,x]) == 0: base_vec = grads[z_st,y,x] elif not non_zero_norm(grads[z_st,y,x_st]) == 0: base_vec = grads[z_st,y,x_st] elif not non_zero_norm(grads[z_st,y_st,x]) == 0: base_vec = grads[z_st,y_st,x] elif not non_zero_norm(grads[z_st,y_st,x_st]) == 0: base_vec = grads[z_st,y_st,x_st] # else: # print('all 0 vec...') # Initialize cell cell.set_cube(0.0, x, y, z, st, my_sign(dot3(base_vec, grads[z ,y, x])) * im[z ,y, x], my_sign(dot3(base_vec, grads[z ,y, x_st])) * im[z ,y, x_st], my_sign(dot3(base_vec, grads[z ,y_st, x_st])) * im[z ,y_st, x_st], my_sign(dot3(base_vec, grads[z ,y_st, x])) * im[z ,y_st, x], my_sign(dot3(base_vec, grads[z_st,y, x])) * im[z_st,y, x], my_sign(dot3(base_vec, grads[z_st,y, x_st])) * im[z_st,y, x_st], my_sign(dot3(base_vec, grads[z_st,y_st, x_st])) * im[z_st,y_st, x_st], my_sign(dot3(base_vec, grads[z_st,y_st, x])) * im[z_st,y_st, x] ) # Get case, if non-nul, enter the big switch case = luts.CASES.get2(cell.index, 0) if case > 0: inwards_facing_normals_bool = inwards_facing_normals(inwards_facing_normals_ref, grads[z ,y,x], grads[z ,y,x_st], grads[z ,y_st,x_st], grads[z ,y_st,x], grads[z_st,y,x], grads[z_st,y,x_st], grads[z_st,y_st,x_st], grads[z_st,y_st,x]) if inwards_facing_normals_bool: config = luts.CASES.get2(cell.index, 1) the_big_switch(luts, cell, case, config) # Done return cell.get_vertices(), cell.get_faces(), cell.get_normals(), cell.get_values() cdef float my_sign(float a): if a > 0: return 1. if a < 0: return -1. if a == 0: return 0. cdef int non_zero_norm(float[:] a): """ Returns True if the sum of absolute values > 0 """ return (abs(a[0]) + abs(a[1]) + abs(a[2])) > 0 cdef float avg_cube(float v1, float v2, float v3, float v4, float v5, float v6, float v7, float v8): """ Return the average value of v_i's """ return 0.125 * (v1 + v2 + v3 + v4 + v5 + v6 + v7 + v8) cdef float max_cube(float v1, float v2, float v3, float v4, float v5, float v6, float v7, float v8): """ Return the max value of v_i's """ return max(v1, max( v2, max( v3, max( v4, max( v5, max( v6, max( v7, v8))))))) cdef float dot3(float[:] a, float[:] b): return a[0]*b[0] + a[1]*b[1] + a[2]*b[2] cdef int inwards_facing_normals(np.ndarray inwards_facing_normals_ref, float[:] g1, float[:] g2, float[:] g3, float[:] g4, float[:] g5, float[:] g6, float[:] g7, float[:] g8): """ Return True if our heurisitic determines that normals are inwards facing """ return (avg_cube(dot3(inwards_facing_normals_ref[0,0,0], g1) >= -0.1, dot3(inwards_facing_normals_ref[0,0,1], g2) >= -0.1, dot3(inwards_facing_normals_ref[0,1,1], g3) >= -0.1, dot3(inwards_facing_normals_ref[0,1,0], g4) >= -0.1, dot3(inwards_facing_normals_ref[1,0,0], g5) >= -0.1, dot3(inwards_facing_normals_ref[1,0,1], g6) >= -0.1, dot3(inwards_facing_normals_ref[1,1,1], g7) >= -0.1, dot3(inwards_facing_normals_ref[1,1,0], g8) >= -0.1, ) >= 2./8.) # cdef int inwards_facing_normals(float[:,:,:,:] inwards_facing_normals_ref, # float[:] g1, float[:] g2, float[:] g3, float[:] g4, # float[:] g5, float[:] g6, float[:] g7, float[:] g8): # """ Return True if our heurisitic determines that normals are inwards facing # """ # # return (avg_cube(np.dot(inwards_facing_normals_ref[0,0,0], g1), # # np.dot(inwards_facing_normals_ref[0,0,1], g2), # # np.dot(inwards_facing_normals_ref[0,1,1], g3), # # np.dot(inwards_facing_normals_ref[0,1,0], g4), # # np.dot(inwards_facing_normals_ref[1,0,0], g5), # # np.dot(inwards_facing_normals_ref[1,0,1], g6), # # np.dot(inwards_facing_normals_ref[1,1,1], g7), # # np.dot(inwards_facing_normals_ref[1,1,0], g8), # # ) >= 0.) # return (avg_cube(np.dot(inwards_facing_normals_ref[0,0,0], g1) >= -0.1, # np.dot(inwards_facing_normals_ref[0,0,1], g2) >= -0.1, # np.dot(inwards_facing_normals_ref[0,1,1], g3) >= -0.1, # np.dot(inwards_facing_normals_ref[0,1,0], g4) >= -0.1, # np.dot(inwards_facing_normals_ref[1,0,0], g5) >= -0.1, # np.dot(inwards_facing_normals_ref[1,0,1], g6) >= -0.1, # np.dot(inwards_facing_normals_ref[1,1,1], g7) >= -0.1, # np.dot(inwards_facing_normals_ref[1,1,0], g8) >= -0.1, # ) >= 2./8.) cdef void the_big_switch(LutProvider luts, Cell cell, int case, int config): """ The big switch (i.e. if-statement) that I meticulously ported from the source code provided by Lewiner et. al. Together with all the look-up tables, this is where the magic is ... """ cdef int subconfig = 0 # Sinatures for tests #test_face(cell, luts.TESTX.get1(config)): #test_internal(cell, luts, case, config, subconfig, luts.TESTX.get1(config)): #cell.add_triangles(luts.TILINGX, config, N) if case == 1: cell.add_triangles(luts.TILING1, config, 1) elif case == 2: cell.add_triangles(luts.TILING2, config, 2) elif case == 3: if test_face(cell, luts.TEST3.get1(config)): cell.add_triangles(luts.TILING3_2, config, 4) else: cell.add_triangles(luts.TILING3_1, config, 2) elif case == 4 : if test_internal(cell, luts, case, config, subconfig, luts.TEST4.get1(config)): cell.add_triangles(luts.TILING4_1, config, 2) else: cell.add_triangles(luts.TILING4_2, config, 6) elif case == 5 : cell.add_triangles(luts.TILING5, config, 3) elif case == 6 : if test_face(cell, luts.TEST6.get2(config,0)): cell.add_triangles(luts.TILING6_2, config, 5) else: if test_internal(cell, luts, case, config, subconfig, luts.TEST6.get2(config,1)): cell.add_triangles(luts.TILING6_1_1, config, 3) else: #cell.calculate_center_vertex() # v12 needed cell.add_triangles(luts.TILING6_1_2, config, 9) elif case == 7 : # Get subconfig if test_face(cell, luts.TEST7.get2(config,0)): subconfig += 1 if test_face(cell, luts.TEST7.get2(config,1)): subconfig += 2 if test_face(cell, luts.TEST7.get2(config,2)): subconfig += 4 # Behavior depends on subconfig if subconfig == 0: cell.add_triangles(luts.TILING7_1, config, 3) elif subconfig == 1: cell.add_triangles2(luts.TILING7_2, config, 0, 5) elif subconfig == 2: cell.add_triangles2(luts.TILING7_2, config, 1, 5) elif subconfig == 3: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING7_3, config, 0, 9) elif subconfig == 4: cell.add_triangles2(luts.TILING7_2, config, 2, 5) elif subconfig == 5: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING7_3, config, 1, 9) elif subconfig == 6: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING7_3, config, 2, 9) elif subconfig == 7: if test_internal(cell, luts, case, config, subconfig, luts.TEST7.get2(config,3)): cell.add_triangles(luts.TILING7_4_2, config, 9) else: cell.add_triangles(luts.TILING7_4_1, config, 5) elif case == 8 : cell.add_triangles(luts.TILING8, config, 2) elif case == 9 : cell.add_triangles(luts.TILING9, config, 4) elif case == 10 : if test_face(cell, luts.TEST10.get2(config,0)): if test_face(cell, luts.TEST10.get2(config,1)): cell.add_triangles(luts.TILING10_1_1_, config, 4) else: #cell.calculate_center_vertex() # v12 needed cell.add_triangles(luts.TILING10_2, config, 8) else: if test_face(cell, luts.TEST10.get2(config,1)): #cell.calculate_center_vertex() # v12 needed cell.add_triangles(luts.TILING10_2_, config, 8) else: if test_internal(cell, luts, case, config, subconfig, luts.TEST10.get2(config,2)): cell.add_triangles(luts.TILING10_1_1, config, 4) else: cell.add_triangles(luts.TILING10_1_2, config, 8) elif case == 11 : cell.add_triangles(luts.TILING11, config, 4) elif case == 12 : if test_face(cell, luts.TEST12.get2(config,0)): if test_face(cell, luts.TEST12.get2(config,1)): cell.add_triangles(luts.TILING12_1_1_, config, 4) else: #cell.calculate_center_vertex() # v12 needed cell.add_triangles(luts.TILING12_2, config, 8) else: if test_face(cell, luts.TEST12.get2(config,1)): #cell.calculate_center_vertex() # v12 needed cell.add_triangles(luts.TILING12_2_, config, 8) else: if test_internal(cell, luts, case, config, subconfig, luts.TEST12.get2(config,2)): cell.add_triangles(luts.TILING12_1_1, config, 4) else: cell.add_triangles(luts.TILING12_1_2, config, 8) elif case == 13 : # Calculate subconfig if test_face(cell, luts.TEST13.get2(config,0)): subconfig += 1 if test_face(cell, luts.TEST13.get2(config,1)): subconfig += 2 if test_face(cell, luts.TEST13.get2(config,2)): subconfig += 4 if test_face(cell, luts.TEST13.get2(config,3)): subconfig += 8 if test_face(cell, luts.TEST13.get2(config,4)): subconfig += 16 if test_face(cell, luts.TEST13.get2(config,5)): subconfig += 32 # Map via LUT subconfig = luts.SUBCONFIG13.get1(subconfig) # Behavior depends on subconfig if subconfig==0: cell.add_triangles(luts.TILING13_1, config, 4) elif subconfig==1: cell.add_triangles2(luts.TILING13_2, config, 0, 6) elif subconfig==2: cell.add_triangles2(luts.TILING13_2, config, 1, 6) elif subconfig==3: cell.add_triangles2(luts.TILING13_2, config, 2, 6) elif subconfig==4: cell.add_triangles2(luts.TILING13_2, config, 3, 6) elif subconfig==5: cell.add_triangles2(luts.TILING13_2, config, 4, 6) elif subconfig==6: cell.add_triangles2(luts.TILING13_2, config, 5, 6) # elif subconfig==7: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 0, 10) elif subconfig==8: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 1, 10) elif subconfig==9: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 2, 10) elif subconfig==10: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 3, 10) elif subconfig==11: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 4, 10) elif subconfig==12: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 5, 10) elif subconfig==13: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 6, 10) elif subconfig==14: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 7, 10) elif subconfig==15: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 8, 10) elif subconfig==16: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 9, 10) elif subconfig==17: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 10, 10) elif subconfig==18: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3, config, 11, 10) # elif subconfig==19: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_4, config, 0, 12) elif subconfig==20: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_4, config, 1, 12) elif subconfig==21: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_4, config, 2, 12) elif subconfig==22: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_4, config, 3, 12) # elif subconfig==23: subconfig = 0 # Note: the original source code sets the subconfig, without apparent reason if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): cell.add_triangles2(luts.TILING13_5_1, config, 0, 6) else: cell.add_triangles2(luts.TILING13_5_2, config, 0, 10) elif subconfig==24: subconfig = 1 if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): cell.add_triangles2(luts.TILING13_5_1, config, 1, 6) else: cell.add_triangles2(luts.TILING13_5_2, config, 1, 10) elif subconfig==25: subconfig = 2 ; if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): cell.add_triangles2(luts.TILING13_5_1, config, 2, 6) else: cell.add_triangles2(luts.TILING13_5_2, config, 2, 10) elif subconfig==26: subconfig = 3 ; if test_internal(cell, luts, case, config, subconfig, luts.TEST13.get2(config,6)): cell.add_triangles2(luts.TILING13_5_1, config, 3, 6) else: cell.add_triangles2(luts.TILING13_5_2, config, 3, 10) # elif subconfig==27: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 0, 10) elif subconfig==28: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 1, 10) elif subconfig==29: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 2, 10) elif subconfig==30: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 3, 10) elif subconfig==31: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 4, 10) elif subconfig==32: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 5, 10) elif subconfig==33: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config,6, 10) elif subconfig==34: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 7, 10) elif subconfig==35: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 8, 10) elif subconfig==36: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 9, 10) elif subconfig==37: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 10, 10) elif subconfig==38: #cell.calculate_center_vertex() # v12 needed cell.add_triangles2(luts.TILING13_3_, config, 11, 10) # elif subconfig==39: cell.add_triangles2(luts.TILING13_2_, config, 0, 6) elif subconfig==40: cell.add_triangles2(luts.TILING13_2_, config, 1, 6) elif subconfig==41: cell.add_triangles2(luts.TILING13_2_, config, 2, 6) elif subconfig==42: cell.add_triangles2(luts.TILING13_2_, config, 3, 6) elif subconfig==43: cell.add_triangles2(luts.TILING13_2_, config, 4, 6) elif subconfig==44: cell.add_triangles2(luts.TILING13_2_, config, 5, 6) # elif subconfig==45: cell.add_triangles(luts.TILING13_1_, config, 4) # else: print("Marching Cubes: Impossible case 13?" ) elif case == 14 : cell.add_triangles(luts.TILING14, config, 4) cdef int test_face(Cell cell, int face): """ Return True of the face contains part of the surface. """ # Get face absolute value cdef int absFace = face if face < 0: absFace *= -1 # Get values of corners A B C D cdef double A, B, C, D if absFace == 1: A, B, C, D = cell.v0, cell.v4, cell.v5, cell.v1 elif absFace == 2: A, B, C, D = cell.v1, cell.v5, cell.v6, cell.v2 elif absFace == 3: A, B, C, D = cell.v2, cell.v6, cell.v7, cell.v3 elif absFace == 4: A, B, C, D = cell.v3, cell.v7, cell.v4, cell.v0 elif absFace == 5: A, B, C, D = cell.v0, cell.v3, cell.v2, cell.v1 elif absFace == 6: A, B, C, D = cell.v4, cell.v7, cell.v6, cell.v5 # Return sign cdef double AC_BD = A*C - B*D if AC_BD > - FLT_EPSILON and AC_BD < FLT_EPSILON: return face >= 0 else: return face * A * AC_BD >= 0; # face and A invert signs cdef int test_internal(Cell cell, LutProvider luts, int case, int config, int subconfig, int s): """ Return True of the face contains part of the surface. """ # Typedefs cdef double t, At, Bt, Ct, Dt, a, b cdef int test = 0 cdef int edge = -1 # reference edge of the triangulation # Calculate At Bt Ct Dt a b # Select case 4, 10, 7, 12, 13 At, Bt, Ct, Dt = 0.0, 0.0, 0.0, 0.0 if case==4 or case==10: a = ( cell.v4 - cell.v0 ) * ( cell.v6 - cell.v2 ) - ( cell.v7 - cell.v3 ) * ( cell.v5 - cell.v1 ) b = cell.v2 * ( cell.v4 - cell.v0 ) + cell.v0 * ( cell.v6 - cell.v2 ) - cell.v1 * ( cell.v7 - cell.v3 ) - cell.v3 * ( cell.v5 - cell.v1 ) t = - b / (2*a + FLT_EPSILON) if t<0 or t>1: return s>0 ; At = cell.v0 + ( cell.v4 - cell.v0 ) * t Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t elif case==6 or case==7 or case==12 or case==13: # Define edge if case == 6: edge = luts.TEST6.get2(config, 2) elif case == 7: edge = luts.TEST7.get2(config, 4) elif case == 12: edge = luts.TEST12.get2(config, 3) elif case == 13: edge = luts.TILING13_5_1.get3(config, subconfig, 0) if edge==0: t = cell.v0 / ( cell.v0 - cell.v1 + FLT_EPSILON ) At = 0 Bt = cell.v3 + ( cell.v2 - cell.v3 ) * t Ct = cell.v7 + ( cell.v6 - cell.v7 ) * t Dt = cell.v4 + ( cell.v5 - cell.v4 ) * t elif edge==1: t = cell.v1 / ( cell.v1 - cell.v2 + FLT_EPSILON ) At = 0 Bt = cell.v0 + ( cell.v3 - cell.v0 ) * t Ct = cell.v4 + ( cell.v7 - cell.v4 ) * t Dt = cell.v5 + ( cell.v6 - cell.v5 ) * t elif edge==2: t = cell.v2 / ( cell.v2 - cell.v3 + FLT_EPSILON ) At = 0 Bt = cell.v1 + ( cell.v0 - cell.v1 ) * t Ct = cell.v5 + ( cell.v4 - cell.v5 ) * t Dt = cell.v6 + ( cell.v7 - cell.v6 ) * t elif edge==3: t = cell.v3 / ( cell.v3 - cell.v0 + FLT_EPSILON ) At = 0 Bt = cell.v2 + ( cell.v1 - cell.v2 ) * t Ct = cell.v6 + ( cell.v5 - cell.v6 ) * t Dt = cell.v7 + ( cell.v4 - cell.v7 ) * t elif edge==4: t = cell.v4 / ( cell.v4 - cell.v5 + FLT_EPSILON ) At = 0 Bt = cell.v7 + ( cell.v6 - cell.v7 ) * t Ct = cell.v3 + ( cell.v2 - cell.v3 ) * t Dt = cell.v0 + ( cell.v1 - cell.v0 ) * t elif edge==5: t = cell.v5 / ( cell.v5 - cell.v6 + FLT_EPSILON ) At = 0 Bt = cell.v4 + ( cell.v7 - cell.v4 ) * t Ct = cell.v0 + ( cell.v3 - cell.v0 ) * t Dt = cell.v1 + ( cell.v2 - cell.v1 ) * t elif edge==6: t = cell.v6 / ( cell.v6 - cell.v7 + FLT_EPSILON ) At = 0 Bt = cell.v5 + ( cell.v4 - cell.v5 ) * t Ct = cell.v1 + ( cell.v0 - cell.v1 ) * t Dt = cell.v2 + ( cell.v3 - cell.v2 ) * t elif edge==7: t = cell.v7 / ( cell.v7 - cell.v4 + FLT_EPSILON ) At = 0 Bt = cell.v6 + ( cell.v5 - cell.v6 ) * t Ct = cell.v2 + ( cell.v1 - cell.v2 ) * t Dt = cell.v3 + ( cell.v0 - cell.v3 ) * t elif edge==8: t = cell.v0 / ( cell.v0 - cell.v4 + FLT_EPSILON ) At = 0 Bt = cell.v3 + ( cell.v7 - cell.v3 ) * t Ct = cell.v2 + ( cell.v6 - cell.v2 ) * t Dt = cell.v1 + ( cell.v5 - cell.v1 ) * t elif edge==9: t = cell.v1 / ( cell.v1 - cell.v5 + FLT_EPSILON ) At = 0 Bt = cell.v0 + ( cell.v4 - cell.v0 ) * t Ct = cell.v3 + ( cell.v7 - cell.v3 ) * t Dt = cell.v2 + ( cell.v6 - cell.v2 ) * t elif edge==10: t = cell.v2 / ( cell.v2 - cell.v6 + FLT_EPSILON ) At = 0 Bt = cell.v1 + ( cell.v5 - cell.v1 ) * t Ct = cell.v0 + ( cell.v4 - cell.v0 ) * t Dt = cell.v3 + ( cell.v7 - cell.v3 ) * t elif edge==11: t = cell.v3 / ( cell.v3 - cell.v7 + FLT_EPSILON ) At = 0 Bt = cell.v2 + ( cell.v6 - cell.v2 ) * t Ct = cell.v1 + ( cell.v5 - cell.v1 ) * t Dt = cell.v0 + ( cell.v4 - cell.v0 ) * t else: print( "Invalid edge %i." % edge ) else: print( "Invalid ambiguous case %i." % case ) # Process results if At >= 0: test += 1 if Bt >= 0: test += 2 if Ct >= 0: test += 4 if Dt >= 0: test += 8 # Determine what to return if test==0: return s>0 elif test==1: return s>0 elif test==2: return s>0 elif test==3: return s>0 elif test==4: return s>0 elif test==5: if At * Ct - Bt * Dt < FLT_EPSILON: return s>0 elif test==6: return s>0 elif test==7: return s<0 elif test==8: return s>0 elif test==9: return s>0 elif test==10: if At * Ct - Bt * Dt >= FLT_EPSILON: return s>0 elif test==11: return s<0 elif test==12: return s>0 elif test==13: return s<0 elif test==14: return s<0 elif test==15: return s<0 else: return s<0 ================================================ FILE: custom_mc/_marching_cubes_lewiner_luts.py ================================================ # -*- coding: utf-8 -*- # This file was auto-generated from `mc_meta/LookUpTable.h` by # `mc_meta/createluts.py`. #static const char casesClassic[256][16] CASESCLASSIC = (256, 16), """ /////////////////////wAIA/////////////////8AAQn/////////////////AQgDCQgB//// /////////wECCv////////////////8ACAMBAgr/////////////CQIKAAIJ/////////////wII AwIKCAoJCP////////8DCwL/////////////////AAsCCAsA/////////////wEJAAIDC/////// //////8BCwIBCQsJCAv/////////AwoBCwoD/////////////wAKAQAICggLCv////////8DCQAD CwkLCgn/////////CQgKCggL/////////////wQHCP////////////////8EAwAHAwT///////// ////AAEJCAQH/////////////wQBCQQHAQcDAf////////8BAgoIBAf/////////////AwQHAwAE AQIK/////////wkCCgkAAggEB/////////8CCgkCCQcCBwMHCQT/////CAQHAwsC//////////// /wsEBwsCBAIABP////////8JAAEIBAcCAwv/////////BAcLCQQLCQsCCQIB/////wMKAQMLCgcI BP////////8BCwoBBAsBAAQHCwT/////BAcICQALCQsKCwAD/////wQHCwQLCQkLCv////////8J BQT/////////////////CQUEAAgD/////////////wAFBAEFAP////////////8IBQQIAwUDAQX/ ////////AQIKCQUE/////////////wMACAECCgQJBf////////8FAgoFBAIEAAL/////////AgoF AwIFAwUEAwQI/////wkFBAIDC/////////////8ACwIACAsECQX/////////AAUEAAEFAgML//// /////wIBBQIFCAIICwQIBf////8KAwsKAQMJBQT/////////BAkFAAgBCAoBCAsK/////wUEAAUA CwULCgsAA/////8FBAgFCAoKCAv/////////CQcIBQcJ/////////////wkDAAkFAwUHA/////// //8ABwgAAQcBBQf/////////AQUDAwUH/////////////wkHCAkFBwoBAv////////8KAQIJBQAF AwAFBwP/////CAACCAIFCAUHCgUC/////wIKBQIFAwMFB/////////8HCQUHCAkDCwL///////// CQUHCQcCCQIAAgcL/////wIDCwABCAEHCAEFB/////8LAgELAQcHAQX/////////CQUICAUHCgED CgML/////wUHAAUACQcLAAEACgsKAP8LCgALAAMKBQAIAAcFBwD/CwoFBwsF/////////////woG Bf////////////////8ACAMFCgb/////////////CQABBQoG/////////////wEIAwEJCAUKBv// //////8BBgUCBgH/////////////AQYFAQIGAwAI/////////wkGBQkABgACBv////////8FCQgF CAIFAgYDAgj/////AgMLCgYF/////////////wsACAsCAAoGBf////////8AAQkCAwsFCgb///// ////BQoGAQkCCQsCCQgL/////wYDCwYFAwUBA/////////8ACAsACwUABQEFCwb/////AwsGAAMG AAYFAAUJ/////wYFCQYJCwsJCP////////8FCgYEBwj/////////////BAMABAcDBgUK//////// /wEJAAUKBggEB/////////8KBgUBCQcBBwMHCQT/////BgECBgUBBAcI/////////wECBQUCBgMA BAMEB/////8IBAcJAAUABgUAAgb/////BwMJBwkEAwIJBQkGAgYJ/wMLAgcIBAoGBf////////8F CgYEBwIEAgACBwv/////AAEJBAcIAgMLBQoG/////wkCAQkLAgkECwcLBAUKBv8IBAcDCwUDBQEF Cwb/////BQELBQsGAQALBwsEAAQL/wAFCQAGBQADBgsGAwgEB/8GBQkGCQsEBwkHCwn/////CgQJ BgQK/////////////wQKBgQJCgAIA/////////8KAAEKBgAGBAD/////////CAMBCAEGCAYEBgEK /////wEECQECBAIGBP////////8DAAgBAgkCBAkCBgT/////AAIEBAIG/////////////wgDAggC BAQCBv////////8KBAkKBgQLAgP/////////AAgCAggLBAkKBAoG/////wMLAgABBgAGBAYBCv// //8GBAEGAQoECAECAQsICwH/CQYECQMGCQEDCwYD/////wgLAQgBAAsGAQkBBAYEAf8DCwYDBgAA BgT/////////BgQICwYI/////////////wcKBgcICggJCv////////8ABwMACgcACQoGBwr///// CgYHAQoHAQcIAQgA/////woGBwoHAQEHA/////////8BAgYBBggBCAkIBgf/////AgYJAgkBBgcJ AAkDBwMJ/wcIAAcABgYAAv////////8HAwIGBwL/////////////AgMLCgYICggJCAYH/////wIA 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AgUKBQILBwb/BwIDBwYCBQQJ/////////wkFBAAIBgAGAgYIB/////8DBgIDBwYBBQAFBAD///// BgIIBggHAgEIBAgFAQUI/wkFBAoBBgEHBgEDB/////8BBgoBBwYBAAcIBwAJBQT/BAAKBAoFAAMK BgoHAwcK/wcGCgcKCAUECgQICv////8GCQUGCwkLCAn/////////AwYLAAYDAAUGAAkF/////wAL CAAFCwABBQUGC/////8GCwMGAwUFAwH/////////AQIKCQULCQsICwUG/////wALAwAGCwAJBgUG CQECCv8LCAULBQYIAAUKBQIAAgX/BgsDBgMFAgoDCgUD/////wUICQUCCAUGAgMIAv////8JBQYJ BgAABgL/////////AQUIAQgABQYIAwgCBgII/wEFBgIBBv////////////8BAwYBBgoDCAYFBgkI CQb/CgEACgAGCQUABQYA/////wADCAUGCv////////////8KBQb/////////////////CwUKBwUL /////////////wsFCgsHBQgDAP////////8FCwcFCgsBCQD/////////CgcFCgsHCQgBCAMB//// /wsBAgsHAQcFAf////////8ACAMBAgcBBwUHAgv/////CQcFCQIHCQACAgsH/////wcFAgcCCwUJ AgMCCAkIAv8CBQoCAwUDBwX/////////CAIACAUCCAcFCgIF/////wkAAQUKAwUDBwMKAv////8J CAIJAgEIBwIKAgUHBQL/AQMFAwcF/////////////wAIBwAHAQEHBf////////8JAAMJAwUFAwf/ ////////CQgHBQkH/////////////wUIBAUKCAoLCP////////8FAAQFCwAFCgsLAwD/////AAEJ CAQKCAoLCgQF/////woLBAoEBQsDBAkEAQMBBP8CBQECCAUCCwgEBQj/////AAQLAAsDBAULAgsB BQEL/wACBQAFCQILBQQFCAsIBf8JBAUCCwP/////////////AgUKAwUCAwQFAwgE/////wUKAgUC BAQCAP////////8DCgIDBQoDCAUEBQgAAQn/BQoCBQIEAQkCCQQC/////wgEBQgFAwMFAf////// //8ABAUBAAX/////////////CAQFCAUDCQAFAAMF/////wkEBf////////////////8ECwcECQsJ Cgv/////////AAgDBAkHCQsHCQoL/////wEKCwELBAEEAAcEC/////8DAQQDBAgBCgQHBAsKCwT/ BAsHCQsECQILCQEC/////wkHBAkLBwkBCwILAQAIA/8LBwQLBAICBAD/////////CwcECwQCCAME AwIE/////wIJCgIHCQIDBwcECf////8JCgcJBwQKAgcIBwACAAf/AwcKAwoCBwQKAQoABAAK/wEK AggHBP////////////8ECQEEAQcHAQP/////////BAkBBAEHAAgBCAcB/////wQAAwcEA/////// //////8ECAf/////////////////CQoICgsI/////////////wMACQMJCwsJCv////////8AAQoA CggICgv/////////AwEKCwMK/////////////wECCwELCQkLCP////////8DAAkDCQsBAgkCCwn/ ////AAILCAAL/////////////wMCC/////////////////8CAwgCCAoKCAn/////////CQoCAAkC /////////////wIDCAIICgABCAEKCP////8BCgL/////////////////AQMICQEI//////////// /wAJAf////////////////8AAwj//////////////////////////////////////w== """ #static const char cases[256][2] CASES = (256, 2), """ AP8BAAEBAgABAgMAAgMFAAEDAgEDAwUBAgUFBAUJCAABBAICAwQFAgQCBgIGCQsAAwgFBQcDCQEG EA4DDAwFGAEFAwECBAUDAwYHAAUKCQAEAwYEBgsOAQYRDAQLBgUZAggFBwUMCAEGEgwFDgcFHAYV CwQMDwUeCgUGIAYnAgwBBgQAAwUGAAIGBgMFCw4AAwkGBQcEDAEFDgsDCQQFGgMKBgYHBQwCBhMK AQwNBhgHBwwJDQEHCQwUBiEHDQMMAgoGBwUNCwIFEAwHCAMFHQYWCgIMEQYbDgkGIgUnAg4FFA4F CQUFIAsKBiMFKQIQDBcGJQcOAxAGLgQGAxUBCAEHAwIEAQYBAwcHAQYKDAACBwUGBgwLAQUPCQIO BgUbAgkFCAYNDgIGFAwGCgMGGQUSCAIMEAUfCwkFIgYoAg0DCwcCBg4MAwcGDQAMDgcIBhcMCgoE BhwMFQcKBikDDQUVCQMLCAUhDBYHCwYqAw4OCwUkBiwCEQYvAxIEBwEJAgsGCAYPCgAFEQwICwcG GgUTDgQMEgYdCAQFIwUoAg8FFgsFDBMGHg4KBiQGKwQECQcFJQcPAxEFLAITAxYBCgUXDAsOCAYf CQYHDAUqAw8LCwYmBi0EBQUtAxMCFQELCAUFJgUrAhIFLgMUAhYBDAUvAhQDFwENAhcBDgEPAP8= """ #static const char tiling1[16][3] TILING1 = (16, 3), """ AAgDAAEJAQIKAwsCBAcICQUECgYFBwYLBwsGCgUGCQQFBAgHAwILAQoCAAkBAAMI """ #static const char tiling2[24][6] TILING2 = (24, 6), """ AQgDCQgBAAsCCAsABAMABwMECQIKAAIJAAUEAQUAAwoBCwoDAQYFAgYBBwIDBgIHCQcIBQcJBggE CwgGCgQJBgQKCwUKBwULCwoFBwsFCgkEBgoEBgQICwYICQgHBQkHBwMCBgcCAQUGAgEGAwEKCwMK AAQFAQAFCQoCAAkCBAADBwQDAAILCAALAQMICQEI """ #static const char tiling3_1[24][6] TILING3_1 = (24, 6), """ AAgDAQIKCQUEAAgDAwAICwcGAQkAAgMLAAEJCAQHCQABBQoGAQIKCQUECgECBgsHCAQHAwsCAgML CgYFBQoGBAcIBAkFBwYLBQkECwYHBgoFCAcECwMCBQYKBwQIAgsDAgEKBwsGCgIBBAUJAQAJBgoF CQEABwQIAAkBCwMCCAADBgcLBAUJAwgAAwgACgIB """ #static const char tiling3_2[24][12] TILING3_2 = (24, 12), """ CgMCCggDCgEACAoAAwQIAwUEAwAJBQMJBggHBgAIBgsDAAYDCwADCwkACwIBCQsBBwkEBwEJBwgA AQcABgEKBgABCQAGCQYFBAoFBAIKBAkBAgQBBwILBwECBwYKAQcKAgcLAgQHAgMIBAIIBQsGBQML BQoCAwUCCAYHCAoGCAQFCggFCwUGCwkFCwcECQsEBgULBQkLBAcLBAsJBwYIBgoIBQQIBQgKBgsF CwMFAgoFAgUDCwcCBwQCCAMCCAIECwIHAgEHCgYHCgcBBQoECgIEAQkEAQQCCgEGAQAGBgAJBQYJ BAkHCQEHAAgHAAcBAwALAAkLAQILAQsJBwgGCAAGAwsGAwYACAQDBAUDCQADCQMFAgMKAwgKAAEK AAoI """ #static const char tiling4_1[8][6] TILING4_1 = (8, 6), """ AAgDBQoGAAEJCwcGAQIKCAQHCQUEAgMLBAUJCwMCCgIBBwQICQEABgcLAwgABgoF """ #static const char tiling4_2[8][18] TILING4_2 = (8, 18), """ CAUABQgGAwYIBgMKAAoDCgAFCQYBBgkHAAcJBwALAQsACwEGCgcCBwoEAQQKBAEIAggBCAIHCwQD BAsFAgULBQIJAwkCCQMEAwQLBQsECwUCCQIFAgkDBAMJAgcKBAoHCgQBCAEEAQgCBwIIAQYJBwkG CQcACwAHAAsBBgELAAUIBggFCAYDCgMGAwoABQAK """ #static const char tiling5[48][9] TILING5 = (48, 9), """ AggDAgoICgkIAQsCAQkLCQgLBAEJBAcBBwMBCAUECAMFAwEFAAoBAAgKCAsKCwQHCwIEAgAEBwAI BwYABgIACQMACQUDBQcDAwYLAwAGAAQGAwkAAwsJCwoJBQIKBQQCBAACCQYFCQAGAAIGAAcIAAEH AQUHCgABCgYABgQABgMLBgUDBQEDCgcGCgEHAQMHAQQJAQIEAgYECwECCwcBBwUBCAIDCAQCBAYC AgUKAgMFAwcFBwoGBwgKCAkKBgkFBgsJCwgJBQgEBQoICgsIBAsHBAkLCQoLBAcLBAsJCQsKBQQI BQgKCggLBgUJBgkLCwkIBwYKBwoICAoJAgoFAgUDAwUHCAMCCAIEBAIGCwIBCwEHBwEFAQkEAQQC AgQGCgYHCgcBAQcDBgsDBgMFBQMBCgEACgAGBgAEAAgHAAcBAQcFCQUGCQYAAAYCBQoCBQIEBAIA AwAJAwkLCwkKAwsGAwYAAAYECQADCQMFBQMHBwgABwAGBgACCwcECwQCAgQAAAEKAAoICAoLCAQF CAUDAwUBBAkBBAEHBwEDAQILAQsJCQsIAgMIAggKCggJ """ #static const char tiling6_1_1[48][9] TILING6_1_1 = (48, 9), """ BgUKAwEICQgBCwcGCQMBAwkIAQIKBwAEAAcDAwAIBQIGAgUBBQQJAgALCAsACgYFCAIAAggLCgYF AAQDBwMEAwAIBgQKCQoECAMACgcFBwoLCAQHCgACAAoJBwYLAAIJCgkCAgMLBAEFAQQAAAEJBgMH AwYCCQABCwQGBAsICwcGAQUABAAFAAEJBwULCgsFBAcIAQMKCwoDCQUECwEDAQsKCgECCAUHBQgJ CAQHAgYBBQEGAQIKBAYICwgGAgMLBQcJCAkHCwIDCQYEBgkKCQUEAwcCBgIHBAUJAgcDBwIGAwIL BAYJCgkGCwMCCQcFBwkICgIBCAYEBggLBwQIAQYCBgEFAgEKBwUICQgFBAUJAwELCgsBCAcECgMB AwoLCQEACwUHBQsKBgcLAAUBBQAEAQAJBgQLCAsECQEABwMGAgYDCwMCBQEEAAQBCwYHCQIAAgkK BwQIAgAKCQoAAAMIBQcKCwoHCAADCgQGBAoJBQYKAwQABAMHBQYKAAIICwgCCQQFCwACAAsICAAD BgIFAQUCCgIBBAAHAwcABgcLAQMJCAkDCgUGCAEDAQgJ """ #static const char tiling6_1_2[48][27] TILING6_1_2 = (48, 27), """ AQwDDAoDBgMKAwYIBQgGCAUMDAkIAQkMDAUKAQwDAQsMCwEGCQYBBgkHDAcJCQgMDAgDCwcMBAwA BAEMAQQKBwoECgcCDAIHBwMMDAMAAQIMBgwCBgMMAwYIBQgGCAUADAAFBQEMDAECAwAMAAwCDAkC BQIJAgULBAsFCwQMDAgLAAgMDAQJAAwCAAoMCgAFCAUABQgGDAYICAsMDAsCCgYMBAwADAUACgAF AAoDBgMKAwYMDAcDBAcMDAYFBAwGDAgGAwYIBgMKAAoDCgAMDAkKBAkMDAAIBQwHBQgMCAUACgAF AAoDDAMKCgsMDAsHCAMMAgwAAggMCAIHCgcCBwoEDAQKCgkMDAkACAQMAgwADAsABwALAAcJBgkH CQYMDAoJAgoMDAYLBQwBBQIMAgULBAsFCwQDDAMEBAAMDAABAgMMBwwDBwAMAAcJBgkHCQYBDAEG BgIMDAIDAAEMBgwEBgkMCQYBCwEGAQsADAALCwgMDAgECQAMBQwBDAYBCwEGAQsABwALAAcMDAQA BQQMDAcGBQwHDAkHAAcJBwALAQsACwEMDAoLBQoMDAEJAwwBDAgBBAEIAQQKBwoECgcMDAsKAwsM DAcIAwwBAwkMCQMECwQDBAsFDAULCwoMDAoBCQUMBwwFBwoMCgcCCAIHAggBDAEICAkMDAkFCgEM BgwCDAcCCAIHAggBBAEIAQQMDAUBBgUMDAQHBgwEDAoEAQQKBAEIAggBCAIMDAsIBgsMDAIKBwwF DAsFAgULBQIJAwkCCQMMDAgJBwgMDAMLBAwGBAsMCwQDCQMEAwkCDAIJCQoMDAoGCwIMBwwDDAQD CQMEAwkCBQIJAgUMDAYCBwYMDAUEAwwHAwQMBAMJAgkDCQIFDAUCAgYMDAYHBAUMBgwEDAsEAwQL BAMJAgkDCQIMDAoJBgoMDAILBQwHBQsMCwUCCQIFAgkDDAMJCQgMDAgHCwMMBAwGBAoMCgQBCAEE AQgCDAIICAsMDAsGCgIMAgwGAgcMBwIIAQgCCAEEDAQBAQUMDAUGBwQMBQwHDAoHAgcKBwIIAQgC CAEMDAkIBQkMDAEKAQwDDAkDBAMJAwQLBQsECwUMDAoLAQoMDAUJAQwDAQgMCAEECgQBBAoHDAcK CgsMDAsDCAcMBwwFBwkMCQcACwAHAAsBDAELCwoMDAoFCQEMAQwFAQYMBgELAAsBCwAHDAcAAAQM DAQFBgcMBAwGDAkGAQYJBgELAAsBCwAMDAgLBAgMDAAJAwwHDAAHCQcABwkGAQYJBgEMDAIGAwIM DAEAAQwFDAIFCwUCBQsEAwQLBAMMDAAEAQAMDAMCAAwCAAsMCwAHCQcABwkGDAYJCQoMDAoCCwYM AAwCDAgCBwIIAgcKBAoHCgQMDAkKAAkMDAQIBwwFDAgFAAUIBQAKAwoACgMMDAsKBwsMDAMIBgwE BggMCAYDCgMGAwoADAAKCgkMDAkECAAMAAwEAAUMBQAKAwoACgMGDAYDAwcMDAcEBQYMAgwADAoA BQAKAAUIBggFCAYMDAsIAgsMDAYKAgwAAgkMCQIFCwUCBQsEDAQLCwgMDAgACQQMAgwGDAMGCAYD BggFAAUIBQAMDAEFAgEMDAADAAwEDAEECgQBBAoHAgcKBwIMDAMHAAMMDAIBAwwBDAsBBgELAQYJ BwkGCQcMDAgJAwgMDAcLAwwBAwoMCgMGCAYDBggFDAUICAkMDAkBCgUM """ #static const char tiling6_2[48][15] TILING6_2 = (48, 15), """ AQoDBgMKAwYIBQgGCAUJAQsDCwEGCQYBBgkHCAcJBAEAAQQKBwoECgcCAwIHBgMCAwYIBQgGCAUA AQAFAAkCBQIJAgULBAsFCwQIAAoCCgAFCAUABQgGCwYIBAUACgAFAAoDBgMKAwYHBAgGAwYIBgMK AAoDCgAJBQgHCAUACgAFAAoDCwMKAggACAIHCgcCBwoECQQKAgsABwALAAcJBgkHCQYKBQIBAgUL BAsFCwQDAAMEBwADAAcJBgkHCQYBAgEGBgkECQYBCwEGAQsACAALBQYBCwEGAQsABwALAAcEBQkH AAcJBwALAQsACwEKAwgBBAEIAQQKBwoECgcLAwkBCQMECwQDBAsFCgULBwoFCgcCCAIHAggBCQEI BgcCCAIHAggBBAEIAQQFBgoEAQQKBAEIAggBCAILBwsFAgULBQIJAwkCCQMIBAsGCwQDCQMEAwkC CgIJBwQDCQMEAwkCBQIJAgUGAwQHBAMJAgkDCQIFBgUCBgsEAwQLBAMJAgkDCQIKBQsHCwUCCQIF AgkDCAMJBAoGCgQBCAEEAQgCCwIIAgcGBwIIAQgCCAEEBQQBBQoHAgcKBwIIAQgCCAEJAQkDBAMJ AwQLBQsECwUKAQgDCAEECgQBBAoHCwcKBwkFCQcACwAHAAsBCgELAQYFBgELAAsBCwAHBAcABAkG AQYJBgELAAsBCwAIAwAHCQcABwkGAQYJBgECAQIFCwUCBQsEAwQLBAMAAAsCCwAHCQcABwkGCgYJ AAgCBwIIAgcKBAoHCgQJBwgFAAUIBQAKAwoACgMLBggECAYDCgMGAwoACQAKAAUEBQAKAwoACgMG BwYDAgoABQAKAAUIBggFCAYLAgkACQIFCwUCBQsECAQLAgMGCAYDBggFAAUIBQABAAEECgQBBAoH AgcKBwIDAwsBBgELAQYJBwkGCQcIAwoBCgMGCAYDBggFCQUI """ #static const char tiling7_1[16][9] TILING7_1 = (16, 9), """ CQUECgECCAMACwcGCAMACgECAwAIBQQJBwYLCAQHCQABCwIDCgYFCwIDCQABAAEJBgUKBAcIAQIK BwYLBQQJAgMLBAcIBgUKCwMCCAcECgUGCgIBCwYHCQQFCQEACgUGCAcEBQYKAwILAQAJBwQIAQAJ AwILCAADCQQFCwYHBgcLAAMIAgEKBAUJAgEKAAMI """ #static const char tiling7_2[16][3][15] TILING7_2 = (16, 3, 15), """ AQIKAwQIBAMFAAUDBQAJAwAICQEEAgQBBAIFCgUCCQUEAAoBCgAICggCAwIIAwAIAQYKBgEHAgcB BwILAQIKCwMGAAYDBgAHCAcACwcGAggDCAIKCAoAAQAKCQUECwMGAAYDBgAHCAcACwcGAwQIBAMF AAUDBQAJAwAIBAkHCwcJBQsJCwUGAAEJAgcLBwIEAwQCBAMIAgMLCAAHAQcABwEECQQBCAQHAwkA CQMLCQsBAgELAgMLAAUJBQAGAQYABgEKAAEJCgIFAwUCBQMGCwYDBgUKAQsCCwEJCwkDAAMJBgUK CAAHAQcABwEECQQBCAQHAAUJBQAGAQYABgEKAAEJBQoECAQKBggKCAYHCwcGCQEEAgQBBAIFCgUC CQUEAQYKBgEHAgcBBwILAQIKBgsFCQULBwkLCQcECAQHCgIFAwUCBQMGCwYDBgUKAgcLBwIEAwQC BAMIAgMLBwgGCgYIBAoICgQFBwQIBQIKAgUDBgMFAwYLCgUGCwcCBAIHAgQDCAMECwMCBggHCAYK CAoEBQQKBgcLBAEJAQQCBQIEAgUKBAUJCgYBBwEGAQcCCwIHCgIBBQsGCwUJCwkHBAcJCgUGBwAI AAcBBAEHAQQJBwQICQUABgAFAAYBCgEGCQEABAoFCgQICggGBwYICwMCCQUABgAFAAYBCgEGCQEA BQIKAgUDBgMFAwYLCgUGAgsBCQELAwkLCQMACQEACwcCBAIHAgQDCAMECwMCBwAIAAcBBAEHAQQJ BwQIAAkDCwMJAQsJCwECBAUJBgMLAwYABwAGAAcIBgcLCAQDBQMEAwUACQAFCAADBwkECQcLCQsF BgULCAADCgYBBwEGAQcCCwIHCgIBBgMLAwYABwAGAAcIBgcLAwgCCgIIAAoICgABCgIBCAQDBQME AwUACQAFCAADBAEJAQQCBQIEAgUKBAUJAQoACAAKAggKCAID """ #static const char tiling7_3[16][3][27] TILING7_3 = (16, 3, 27), """ DAIKDAoFDAUEDAQIDAgDDAMADAAJDAkBDAECDAUEDAQIDAgDDAMCDAIKDAoBDAEADAAJDAkFBQQM CgUMAgoMAwIMCAMMAAgMAQAMCQEMBAkMDAAIDAgHDAcGDAYKDAoBDAECDAILDAsDDAMADAcGDAYK DAoBDAEADAAIDAgDDAMCDAILDAsHBwYMCAcMAAgMAQAMCgEMAgoMAwIMCwMMBgsMCQUMAAkMAwAM CwMMBgsMBwYMCAcMBAgMBQQMAwAMCwMMBgsMBQYMCQUMBAkMBwQMCAcMAAgMDAMADAAJDAkFDAUG DAYLDAsHDAcEDAQIDAgDDAEJDAkEDAQHDAcLDAsCDAIDDAMIDAgADAABDAQHDAcLDAsCDAIBDAEJ DAkADAADDAMIDAgEBAcMCQQMAQkMAgEMCwIMAwsMAAMMCAAMBwgMDAMLDAsGDAYFDAUJDAkADAAB DAEKDAoCDAIDDAYFDAUJDAkADAADDAMLDAsCDAIBDAEKDAoGBgUMCwYMAwsMAAMMCQAMAQkMAgEM CgIMBQoMCgYMAQoMAAEMCAAMBwgMBAcMCQQMBQkMBgUMAAEMCAAMBwgMBgcMCgYMBQoMBAUMCQQM AQkMDAABDAEKDAoGDAYHDAcIDAgEDAQFDAUJDAkACwcMAgsMAQIMCQEMBAkMBQQMCgUMBgoMBwYM AQIMCQEMBAkMBwQMCwcMBgsMBQYMCgUMAgoMDAECDAILDAsHDAcEDAQJDAkFDAUGDAYKDAoBCAQM AwgMAgMMCgIMBQoMBgUMCwYMBwsMBAcMAgMMCgIMBQoMBAUMCAQMBwgMBgcMCwYMAwsMDAIDDAMI DAgEDAQFDAUKDAoGDAYHDAcLDAsCDAQIDAgDDAMCDAIKDAoFDAUGDAYLDAsHDAcEDAMCDAIKDAoF DAUEDAQIDAgHDAcGDAYLDAsDAwIMCAMMBAgMBQQMCgUMBgoMBwYMCwcMAgsMDAcLDAsCDAIBDAEJ DAkEDAQFDAUKDAoGDAYHDAIBDAEJDAkEDAQHDAcLDAsGDAYFDAUKDAoCAgEMCwIMBwsMBAcMCQQM BQkMBgUMCgYMAQoMDAYKDAoBDAEADAAIDAgHDAcEDAQJDAkFDAUGDAEADAAIDAgHDAcGDAYKDAoF DAUEDAQJDAkBAQAMCgEMBgoMBwYMCAcMBAgMBQQMCQUMAAkMCwMMBgsMBQYMCQUMAAkMAQAMCgEM AgoMAwIMBQYMCQUMAAkMAwAMCwMMAgsMAQIMCgEMBgoMDAUGDAYLDAsDDAMADAAJDAkBDAECDAIK DAoFCQEMBAkMBwQMCwcMAgsMAwIMCAMMAAgMAQAMBwQMCwcMAgsMAQIMCQEMAAkMAwAMCAMMBAgM DAcEDAQJDAkBDAECDAILDAsDDAMADAAIDAgHDAUJDAkADAADDAMLDAsGDAYHDAcIDAgEDAQFDAAD DAMLDAsGDAYFDAUJDAkEDAQHDAcIDAgAAAMMCQAMBQkMBgUMCwYMBwsMBAcMCAQMAwgMCAAMBwgM BgcMCgYMAQoMAgEMCwIMAwsMAAMMBgcMCgYMAQoMAAEMCAAMAwgMAgMMCwIMBwsMDAYHDAcIDAgA DAABDAEKDAoCDAIDDAMLDAsGCgIMBQoMBAUMCAQMAwgMAAMMCQAMAQkMAgEMBAUMCAQMAwgMAgMM CgIMAQoMAAEMCQAMBQkMDAQFDAUKDAoCDAIDDAMIDAgADAABDAEJDAkE """ #static const char tiling7_4_1[16][15] TILING7_4_1 = (16, 15), """ AwQIBAMKAgoDBAoFCQEAAQYKBgEIAAgBBggHCwMCCwMGCQYDBgkFAAkDBwQIAgcLBwIJAQkCBwkE CAADAAUJBQALAwsABQsGCgIBCAAHCgcABwoGAQoABAUJCQEECwQBBAsHAgsBBQYKCgIFCAUCBQgE AwgCBgcLBQIKAgUIBAgFAggDCwcGBAEJAQQLBwsEAQsCCgYFBwAIAAcKBgoHAAoBCQUECQUACwAF AAsDBgsFAQIKCwcCCQIHAgkBBAkHAwAIBgMLAwYJBQkGAwkACAQHCgYBCAEGAQgABwgGAgMLCAQD CgMEAwoCBQoEAAEJ """ #static const char tiling7_4_2[16][27] TILING7_4_2 = (16, 27), """ CQQIBAkFCgUJAQoJCgECAAIBAgADCAMACQgACwYKBgsHCAcLAwgLCAMAAgADAAIBCgECCwoCCwMI AAgDCAAJCAkEBQQJBAUHBgcFBwYLBwsICAcLBwgECQQIAAkICQABAwEAAQMCCwIDCAsDCgUJBQoG CwYKAgsKCwIDAQMCAwEACQABCgkBCAAJAQkACQEKCQoFBgUKBQYEBwQGBAcIBAgJCQEKAgoBCgIL CgsGBwYLBgcFBAUHBQQJBQkKCgILAwsCCwMICwgHBAcIBwQGBQYEBgUKBgoLCwIKAgsDCAMLBwgL CAcEBgQHBAYFCgUGCwoGCgEJAQoCCwIKBgsKCwYHBQcGBwUECQQFCgkFCQAIAAkBCgEJBQoJCgUG BAYFBgQHCAcECQgECQUKBgoFCgYLCgsCAwILAgMBAAEDAQAJAQkKCwcIBAgHCAQJCAkAAQAJAAED AgMBAwILAwsICAMLAwgACQAIBAkICQQFBwUEBQcGCwYHCAsHCgYLBwsGCwcICwgDAAMIAwACAQIA AgEKAgoLCAQJBQkECQUKCQoBAgEKAQIAAwACAAMIAAgJ """ #static const char tiling8[6][6] TILING8 = (6, 6), """ CQgKCggLAQUDAwUHAAQCBAYCAAIEBAIGAQMFAwcFCQoICgsI """ #static const char tiling9[8][12] TILING9 = (8, 12), """ AgoFAwIFAwUEAwQIBAcLCQQLCQsCCQIBCgcGAQcKAQgHAQAIAwYLAAYDAAUGAAkFAwsGAAMGAAYF AAUJCgYHAQoHAQcIAQgABAsHCQsECQILCQECAgUKAwUCAwQFAwgE """ #static const char tiling10_1_1[6][12] TILING10_1_1 = (6, 12), """ BQoHCwcKCAEJAQgDAQIFBgUCBAMAAwQHCwAIAAsCBAkGCgYJCQAKAgoABggECAYLBwIDAgcGAAEE BQQBBwkFCQcICgELAwsB """ #static const char tiling10_1_1_[6][12] TILING10_1_1_ = (6, 12), """ BQkHCAcJCwEKAQsDAwIHBgcCBAEAAQQFCgAJAAoCBAgGCwYICAALAgsABgkECQYKBQIBAgUGAAME BwQDBwoFCgcLCQEIAwgB """ #static const char tiling10_1_2[6][24] TILING10_1_2 = (6, 24), """ AwsHAwcICQgHBQkHCQUKCQoBAwEKCwMKBwYFBwUEAAQFAQAFAAECAAIDBwMCBgcCCwIKBgsKCwYE CwQIAAgECQAEAAkKAAoCCwIKCwoGBAYKCQQKBAkABAAICwgAAgsABwYFBAcFBwQABwADAgMAAQIA AgEFAgUGBwgDCwcDBwsKBwoFCQUKAQkKCQEDCQMI """ #static const char tiling10_2[6][24] TILING10_2 = (6, 24), """ DAUJDAkIDAgDDAMBDAEKDAoLDAsHDAcFDAEADAAEDAQHDAcDDAMCDAIGDAYFDAUBBAgMBgQMCgYM CQoMAAkMAgAMCwIMCAsMDAkEDAQGDAYLDAsIDAgADAACDAIKDAoJAAMMBAAMBQQMAQUMAgEMBgIM BwYMAwcMCgUMCwoMAwsMAQMMCQEMCAkMBwgMBQcM """ #static const char tiling10_2_[6][24] TILING10_2_ = (6, 24), """ CAcMCQgMAQkMAwEMCwMMCgsMBQoMBwUMBAUMAAQMAwAMBwMMBgcMAgYMAQIMBQEMDAsGDAYEDAQJ DAkKDAoCDAIADAAIDAgLBgoMBAYMCAQMCwgMAgsMAAIMCQAMCgkMDAcEDAQADAABDAEFDAUGDAYC DAIDDAMHDAcLDAsKDAoBDAEDDAMIDAgJDAkFDAUH """ #static const char tiling11[12][12] TILING11 = (12, 12), """ AgoJAgkHAgcDBwkEAQYCAQgGAQkICAcGCAMBCAEGCAYEBgEKAAgLAAsFAAUBBQsGCQUHCQcCCQIA AgcLBQAEBQsABQoLCwMABQQABQALBQsKCwADCQcFCQIHCQACAgsHAAsIAAULAAEFBQYLCAEDCAYB CAQGBgoBAQIGAQYIAQgJCAYHAgkKAgcJAgMHBwQJ """ #static const char tiling12_1_1[24][12] TILING12_1_1 = (24, 12), """ BwYLCgMCAwoICQgKBgUKCQIBAgkLCAsJCgYFBwkECQcBAwEHBwYLBAgFAwUIBQMBBQQJCAEAAQgK CwoIAQIKAAkDBQMJAwUHCgECAAsDCwAGBAYACAMAAgkBCQIEBgQCAwAIAgsBBwELAQcFBgUKBwsE AgQLBAIACQUEBggHCAYAAgAGCAMABwQLCQsECwkKBAcICwADAAsJCgkLBAcIBQkGAAYJBgACCwcG BAoFCgQCAAIECwIDAQgACAEHBQcBAAEJAwgCBAIIAgQGAgMLAQoABgAKAAYECQABAwoCCgMFBwUD CQABBAUICggFCAoLCAQHBQsGCwUDAQMFBQQJBgoHAQcKBwEDCgECBQYJCwkGCQsICwIDBgcKCAoH CggJ """ #static const char tiling12_1_1_[24][12] TILING12_1_1_ = (24, 12), """ AwILCgcGBwoICQgKAgEKCQYFBgkLCAsJCQQFBwoGCgcBAwEHBwQIBgsFAwULBQMBAQAJCAUEBQgK CwoIAQAJAgoDBQMKAwUHCwMCAAoBCgAGBAYACQEAAggDCAIEBgQCAwILAAgBBwEIAQcFBgcLBQoE AgQKBAIACAcEBgkFCQYAAgAGCAcEAwALCQsACwkKAAMICwQHBAsJCgkLBAUJBwgGAAYIBgACCgUG BAsHCwQCAAIECAADAQsCCwEHBQcBAAMIAQkCBAIJAgQGAgEKAwsABgALAAYECgIBAwkACQMFBwUD CQQFAAEICggBCAoLCwYHBQgECAUDAQMFBQYKBAkHAQcJBwEDCgUGAQIJCwkCCQsICwYHAgMKCAoD CggJ """ #static const char tiling12_1_2[24][24] TILING12_1_2 = (24, 24), """ BwMLAwcICQgHBgkHCQYKAgoGCwIGAgsDBgIKAgYLCAsGBQgGCAUJAQkFCgEFAQoCCgkFCQoBAwEK BgMKAwYHBAcGBQQGBAUJBwgLAwsICwMBCwEGBQYBBgUEBgQHCAcEBQEJAQUKCwoFBAsFCwQIAAgE CQAEAAkBAQkKBQoJCgUHCgcCAwIHAgMAAgABCQEACgsCCwoGBAYKAQQKBAEAAwABAgMBAwILCAkA CQgEBgQIAwYIBgMCAQIDAAEDAQAJAwsIBwgLCAcFCAUAAQAFAAECAAIDCwMCBgsKAgoLCgIACgAF BAUABQQHBQcGCwYHCQgECAkAAgAJBQIJAgUGBwYFBAcFBwQICAQACQAEAAkKAAoDCwMKAwsHAwcI BAgHBAAIAAQJCgkEBwoECgcLAwsHCAMHAwgABAkIAAgJCAACCAIHBgcCBwYFBwUECQQFCwoGCgsC AAILBwALAAcEBQQHBgUHBQYKCwgDCAsHBQcLAgULBQIBAAECAwACAAMIAAgJBAkICQQGCQYBAgEG AQIDAQMACAADAgoLBgsKCwYECwQDAAMEAwABAwECCgIBCQoBCgkFBwUJAAcJBwADAgMAAQIAAgEK CQUBCgEFAQoLAQsACAALAAgEAAQJBQkECAsHCwgDAQMIBAEIAQQFBgUEBwYEBgcLBQoJAQkKCQED CQMEBwQDBAcGBAYFCgUGCgYCCwIGAgsIAggBCQEIAQkFAQUKBgoFCwcDCAMHAwgJAwkCCgIJAgoG AgYLBwsG """ #static const char tiling12_2[24][24] TILING12_2 = (24, 24), """ CQgMCgkMAgoMAwIMCwMMBgsMBwYMCAcMCAsMCQgMAQkMAgEMCgIMBQoMBgUMCwYMAwEMBwMMBAcM CQQMBQkMBgUMCgYMAQoMDAMBDAEFDAUGDAYLDAsHDAcEDAQIDAgDCwoMCAsMAAgMAQAMCQEMBAkM BQQMCgUMDAUHDAcDDAMCDAIKDAoBDAEADAAJDAkFBAYMAAQMAQAMCgEMAgoMAwIMCwMMBgsMBgQM AgYMAwIMCAMMAAgMAQAMCQEMBAkMDAcFDAUBDAEADAAIDAgDDAMCDAILDAsHDAIADAAEDAQFDAUK DAoGDAYHDAcLDAsCAgAMBgIMBwYMCAcMBAgMBQQMCQUMAAkMDAkKDAoLDAsHDAcEDAQIDAgDDAMA DAAJCgkMCwoMBwsMBAcMCAQMAwgMAAMMCQAMDAACDAIGDAYHDAcIDAgEDAQFDAUJDAkAAAIMBAAM BQQMCgUMBgoMBwYMCwcMAgsMBQcMAQUMAAEMCAAMAwgMAgMMCwIMBwsMDAQGDAYCDAIDDAMIDAgA DAABDAEJDAkEDAYEDAQADAABDAEKDAoCDAIDDAMLDAsGBwUMAwcMAgMMCgIMAQoMAAEMCQAMBQkM DAoLDAsIDAgADAABDAEJDAkEDAQFDAUKAQMMBQEMBgUMCwYMBwsMBAcMCAQMAwgMDAEDDAMHDAcE DAQJDAkFDAUGDAYKDAoBDAsIDAgJDAkBDAECDAIKDAoFDAUGDAYLDAgJDAkKDAoCDAIDDAMLDAsG DAYHDAcI """ #static const char tiling12_2_[24][24] TILING12_2_ = (24, 24), """ DAILDAsHDAcGDAYKDAoJDAkIDAgDDAMCDAEKDAoGDAYFDAUJDAkIDAgLDAsCDAIBDAQFDAUKDAoG DAYHDAcDDAMBDAEJDAkEBwYMCAcMBAgMBQQMAQUMAwEMCwMMBgsMDAAJDAkFDAUEDAQIDAgLDAsK DAoBDAEAAQIMCQEMAAkMAwAMBwMMBQcMCgUMAgoMDAECDAILDAsDDAMADAAEDAQGDAYKDAoBDAMA DAAJDAkBDAECDAIGDAYEDAQIDAgDAwAMCwMMAgsMAQIMBQEMBwUMCAcMAAgMBgUMCwYMBwsMBAcM AAQMAgAMCgIMBQoMDAcEDAQJDAkFDAUGDAYCDAIADAAIDAgHCAcMAAgMAwAMCwMMCgsMCQoMBAkM BwQMDAcIDAgADAADDAMLDAsKDAoJDAkEDAQHBAcMCQQMBQkMBgUMAgYMAAIMCAAMBwgMDAUGDAYL DAsHDAcEDAQADAACDAIKDAoFDAADDAMLDAsCDAIBDAEFDAUHDAcIDAgAAAMMCQAMAQkMAgEMBgIM BAYMCAQMAwgMAgEMCwIMAwsMAAMMBAAMBgQMCgYMAQoMDAIBDAEJDAkADAADDAMHDAcFDAUKDAoC CQAMBQkMBAUMCAQMCwgMCgsMAQoMAAEMDAYHDAcIDAgEDAQFDAUBDAEDDAMLDAsGBQQMCgUMBgoM BwYMAwcMAQMMCQEMBAkMCgEMBgoMBQYMCQUMCAkMCwgMAgsMAQIMCwIMBwsMBgcMCgYMCQoMCAkM AwgMAgMM """ #static const char tiling13_1[2][12] TILING13_1 = (2, 12), """ CwcGAQIKCAMACQUECAQHAgMLCQABCgYF """ #static const char tiling13_1_[2][12] TILING13_1_ = (2, 12), """ BwQICwMCAQAJBQYKBgcLCgIBAAMIBAUJ """ #static const char tiling13_2[2][6][18] TILING13_2 = (2, 6, 18), """ AQIKCwcGAwQIBAMFAAUDBQAJCAMACwcGCQEEAgQBBAIFCgUCCQUECAMAAQYKBgEHAgcBBwILCQUE AQIKCwMGAAYDBgAHCAcACQUECwcGAAoBCgAICggCAwIIAQIKAwAIBAkHCwcJBQsJCwUGAgMLCAQH AAUJBQAGAQYABgEKCQABCAQHCgIFAwUCBQMGCwYDBgUKCQABAgcLBwIEAwQCBAMIBgUKAgMLCAAH AQcABwEECQQBBgUKCAQHAQsCCwEJCwkDAAMJAgMLAAEJBQoECAQKBggKCAYH """ #static const char tiling13_2_[2][6][18] TILING13_2_ = (2, 6, 18), """ CgUGCwMCBwAIAAcBBAEHAQQJCwMCBwQICQUABgAFAAYBCgEGAQAJBwQIBQIKAgUDBgMFAwYLCgUG AQAJCwcCBAIHAgQDCAMECgUGBwQIAgsBCQELAwkLCQMACwMCCQEABAoFCgQICggGBwYIBgcLCAAD BAEJAQQCBQIEAgUKCAADBAUJCgYBBwEGAQcCCwIHAgEKBAUJBgMLAwYABwAGAAcIBgcLAgEKCAQD BQMEAwUACQAFBgcLBAUJAwgCCgIIAAoICgABCAADCgIBBQsGCwUJCwkHBAcJ """ #static const char tiling13_3[2][12][30] TILING13_3 = (2, 12, 30), """ CwcGDAIKDAoFDAUEDAQIDAgDDAMADAAJDAkBDAECAQIKCQUMAAkMAwAMCwMMBgsMBwYMCAcMBAgM BQQMCwcGDAUEDAQIDAgDDAMCDAIKDAoBDAEADAAJDAkFAQIKDAMADAAJDAkFDAUGDAYLDAsHDAcE DAQIDAgDCAMACwcMAgsMAQIMCQEMBAkMBQQMCgUMBgoMBwYMCwcGBQQMCgUMAgoMAwIMCAMMAAgM AQAMCQEMBAkMCAMAAQIMCQEMBAkMBwQMCwcMBgsMBQYMCgUMAgoMCQUEDAAIDAgHDAcGDAYKDAoB DAECDAILDAsDDAMACQUEDAcGDAYKDAoBDAEADAAIDAgDDAMCDAILDAsHCAMADAECDAILDAsHDAcE DAQJDAkFDAUGDAYKDAoBCQUEBwYMCAcMAAgMAQAMCgEMAgoMAwIMCwMMBgsMAQIKAwAMCwMMBgsM BQYMCQUMBAkMBwQMCAcMAAgMCAQHDAMLDAsGDAYFDAUJDAkADAABDAEKDAoCDAIDAgMLCgYMAQoM AAEMCAAMBwgMBAcMCQQMBQkMBgUMCAQHDAYFDAUJDAkADAADDAMLDAsCDAIBDAEKDAoGAgMLDAAB DAEKDAoGDAYHDAcIDAgEDAQFDAUJDAkAAAEJCAQMAwgMAgMMCgIMBQoMBgUMCwYMBwsMBAcMCAQH BgUMCwYMAwsMAAMMCQAMAQkMAgEMCgIMBQoMCQABAgMMCgIMBQoMBAUMCAQMBwgMBgcMCwYMAwsM BgUKDAEJDAkEDAQHDAcLDAsCDAIDDAMIDAgADAABBgUKDAQHDAcLDAsCDAIBDAEJDAkADAADDAMI DAgECQABDAIDDAMIDAgEDAQFDAUKDAoGDAYHDAcLDAsCBgUKBAcMCQQMAQkMAgEMCwIMAwsMAAMM CAAMBwgMAgMLAAEMCAAMBwgMBgcMCgYMBQoMBAUMCQQMAQkM """ #static const char tiling13_3_[2][12][30] TILING13_3_ = (2, 12, 30), """ AwILCAcMAAgMAQAMCgEMBgoMBQYMCQUMBAkMBwQMBQYKDAILDAsHDAcEDAQJDAkBDAEADAAIDAgD DAMCCgUGDAcEDAQJDAkBDAECDAILDAsDDAMADAAIDAgHCwMCDAEADAAIDAgHDAcGDAYKDAoFDAUE DAQJDAkBBwQICwMMBgsMBQYMCQUMAAkMAQAMCgEMAgoMAwIMBwQIBQYMCQUMAAkMAwAMCwMMAgsM AQIMCgEMBgoMCwMCAQAMCgEMBgoMBwYMCAcMBAgMBQQMCQUMAAkMAQAJDAQIDAgDDAMCDAIKDAoF DAUGDAYLDAsHDAcEBwQIDAUGDAYLDAsDDAMADAAJDAkBDAECDAIKDAoFAQAJDAMCDAIKDAoFDAUE DAQIDAgHDAcGDAYLDAsDCgUGBwQMCwcMAgsMAQIMCQEMAAkMAwAMCAMMBAgMCQEAAwIMCAMMBAgM BQQMCgUMBgoMBwYMCwcMAgsMAAMICQQMAQkMAgEMCwIMBwsMBgcMCgYMBQoMBAUMCwYHDAMIDAgE DAQFDAUKDAoCDAIBDAEJDAkADAADBgcLDAQFDAUKDAoCDAIDDAMIDAgADAABDAEJDAkECAADDAIB DAEJDAkEDAQHDAcLDAsGDAYFDAUKDAoCBAUJCAAMBwgMBgcMCgYMAQoMAgEMCwIMAwsMAAMMBAUJ BgcMCgYMAQoMAAEMCAAMAwgMAgMMCwIMBwsMCAADAgEMCwIMBwsMBAcMCQQMBQkMBgUMCgYMAQoM AgEKDAUJDAkADAADDAMLDAsGDAYHDAcIDAgEDAQFBAUJDAYHDAcIDAgADAABDAEKDAoCDAIDDAML DAsGAgEKDAADDAMLDAsGDAYFDAUJDAkEDAQHDAcIDAgABgcLBAUMCAQMAwgMAgMMCgIMAQoMAAEM CQAMBQkMCgIBAAMMCQAMBQkMBgUMCwYMBwsMBAcMCAQMAwgM """ #static const char tiling13_4[2][4][36] TILING13_4 = (2, 4, 36), """ DAIKDAoFDAUGDAYLDAsHDAcEDAQIDAgDDAMADAAJDAkBDAECCwMMBgsMBwYMCAcMBAgMBQQMCQUM AAkMAQAMCgEMAgoMAwIMCQEMBAkMBQQMCgUMBgoMBwYMCwcMAgsMAwIMCAMMAAgMAQAMDAAIDAgH DAcEDAQJDAkFDAUGDAYKDAoBDAECDAILDAsDDAMADAMLDAsGDAYHDAcIDAgEDAQFDAUJDAkADAAB DAEKDAoCDAIDCAAMBwgMBAcMCQQMBQkMBgUMCgYMAQoMAgEMCwIMAwsMAAMMCgIMBQoMBgUMCwYM BwsMBAcMCAQMAwgMAAMMCQAMAQkMAgEMDAEJDAkEDAQFDAUKDAoGDAYHDAcLDAsCDAIDDAMIDAgA DAAB """ #static const char tiling13_5_1[2][4][18] TILING13_5_1 = (2, 4, 18), """ BwYLAQAJCgMCAwoFAwUIBAgFAQIKBwQIAwALBgsACQYABgkFAwAIBQYKAQIJBAkCCwQCBAsHBQQJ AwILCAEAAQgHAQcKBgoHBAcIAgEKCwADAAsGAAYJBQkGAgMLBAUJAAEIBwgBCgcBBwoGAAEJBgcL AgMKBQoDCAUDBQgEBgUKAAMICQIBAgkEAgQLBwsE """ #static const char tiling13_5_2[2][4][30] TILING13_5_2 = (2, 4, 30), """ AQAJBwQIBwgDBwMLAgsDCwIKCwoGBQYKBgUHBAcFBwQICwMCBgsCCgYCBgoFCQUKAQkKCQEAAgAB AAIDBQYKCQEABAkACAQABAgHCwcIAwsICwMCAAIDAgABAwILBQYKBQoBBQEJAAkBCQAICQgEBAgH BAcFBgUHAgEKBAUJBAkABAAIAwgACAMLCAsHBgcLBwYEBQQGBAUJCAADBwgDCwcDBwsGCgYLAgoL CgIBAwECAQMABgcLCgIBBQoBCQUBBQkECAQJAAgJCAADAQMAAwECAAMIBgcLBgsCBgIKAQoCCgEJ CgkFBQkEBQQGBwYE """ #static const char tiling14[12][12] TILING14 = (12, 12), """ BQkIBQgCBQIGAwIIAgEFAgUIAggLBAgFCQQGCQYDCQMBCwMGAQsKAQQLAQAEBwsECAIACAUCCAcF CgIFAAcDAAoHAAkKBgcKAAMHAAcKAAoJBgoHCAACCAIFCAUHCgUCAQoLAQsEAQQABwQLCQYECQMG CQEDCwYDAgUBAggFAgsIBAUIBQgJBQIIBQYCAwgC """ #static const char test3[24] TEST3 = (24,), """ BQEEBQECAgMEAwYG+vr9/P3+/v/7/P/7 """ #static const char test4[8] TEST4 = (8,), """ BwcHB/n5+fk= """ #static const char test6[48][3] TEST6 = (48, 3), """ AgcKBAcLBQcBBQcDAQcJAwcKBgcFAQcIBAcIAQcIAwcLBQcCBQcAAQcJBgcGAgcJBAcIAgcJAgcK BgcHAwcKBAcLAwcLBgcE+vkE/fkL/PkL/fkK+vkH/vkK/vkJ/PkI/vkJ+vkG//kJ+/kA+/kC/fkL //kI/PkI//kI+vkF/fkK//kJ+/kD+/kB/PkL/vkK """ #static const char test7[16][5] TEST7 = (16, 5), """ AQIFBwEDBAUHAwQBBgcEBAEFBwACAwUHAgECBgcFAgMGBwYDBAYHB/38+vkH/v36+Qb//vr5Bf79 +/kC/P/7+QD8//r5BP38+/kD//77+QE= """ #static const char test10[6][3] TEST10 = (6, 3), """ AgQHBQYHAQMHAQMHBQYHAgQH """ #static const char test12[24][4] TEST12 = (24, 4), """ BAMHCwMCBwoCBgcFBgQHBwIBBwkFAgcBBQMHAgUBBwAFBAcDBgMHBgEGBwQBBAcIBAEHCAYBBwQD BgcGBAUHAwEFBwADBQcCAgUHAQECBwkEBgcHBgIHBQIDBwoDBAcL """ #static const char test13[2][7] TEST13 = (2, 7), """ AQIDBAUGBwIDBAEFBgc= """ #static const char subconfig13[64] SUBCONFIG13 = (64,), """ AAECBwP/C/8ECP//Dv///wUJDBcP/xUmERT/JBohHiwGCg0TEP8ZJRIY/yMWIB0r////Iv//HCr/ H/8pGygnLQ== """ ================================================ FILE: custom_mc/setup.py ================================================ # python setup.py build_ext --inplace from setuptools import setup from Cython.Build import cythonize import numpy as np import os includes_numpy = '-I ' + np.get_include() + ' ' os.environ['CFLAGS'] = includes_numpy + (os.environ['CFLAGS'] if 'CFLAGS' in os.environ else '') setup( name="My MC", ext_modules=cythonize("_marching_cubes_lewiner_cy.pyx", include_path=[np.get_include()]), ) ================================================ FILE: exp/my_rack_test/womask_open/checkpoints/ckpt_400000.pth ================================================ [File too large to display: 16.2 MB] ================================================ FILE: exp/my_whale_test/wmask_open/checkpoints/ckpt_2000000.pth ================================================ [File too large to display: 11.5 MB] ================================================ FILE: exp_runner.py ================================================ import os import time import logging import argparse import numpy as np import cv2 as cv import trimesh import torch import torch.nn.functional as F from torch.utils.tensorboard import SummaryWriter from shutil import copyfile from icecream import ic from tqdm import tqdm from pyhocon import ConfigFactory from models.dataset import Dataset from models.fields import RenderingNetwork, SDFNetwork, SingleVarianceNetwork, NeRF from models.renderer import NeuSRenderer from matplotlib import pyplot as plt from scipy.sparse import coo_matrix from collections import defaultdict import lib.workspace as ws import sys sys.path.append('custom_mc') from _marching_cubes_lewiner import udf_mc_lewiner # import pymeshlab as ml class Runner: def __init__(self, conf_path, mode='train', case='CASE_NAME', is_continue=False): self.device = torch.device('cuda') # Configuration self.conf_path = conf_path f = open(self.conf_path) conf_text = f.read() conf_text = conf_text.replace('CASE_NAME', case) f.close() self.conf = ConfigFactory.parse_string(conf_text) self.conf['dataset.data_dir'] = self.conf['dataset.data_dir'].replace('CASE_NAME', case) self.base_exp_dir = self.conf['general.base_exp_dir'] os.makedirs(self.base_exp_dir, exist_ok=True) self.dataset = Dataset(self.conf['dataset']) self.iter_step = 0 # Training parameters self.end_iter = self.conf.get_int('train.end_iter') self.save_freq = self.conf.get_int('train.save_freq') self.report_freq = self.conf.get_int('train.report_freq') self.val_freq = self.conf.get_int('train.val_freq') self.val_mesh_freq = self.conf.get_int('train.val_mesh_freq') self.batch_size = self.conf.get_int('train.batch_size') self.validate_resolution_level = self.conf.get_int('train.validate_resolution_level') self.learning_rate = self.conf.get_float('train.learning_rate') self.learning_rate_alpha = self.conf.get_float('train.learning_rate_alpha') # self.learning_rate_sdf = self.conf.get_float('train.learning_rate_sdf') self.use_white_bkgd = self.conf.get_bool('train.use_white_bkgd') self.warm_up_end = self.conf.get_float('train.warm_up_end', default=0.0) self.anneal_end = self.conf.get_float('train.anneal_end', default=0.0) self.weight_anneal_end = self.conf.get_float('train.weight_anneal_end', default=0.) self.mcube_threshold = self.conf.get_float('train.mcube_threshold') self.up_sample_start = self.conf.get_int('train.up_sample_start') self.perm_num = self.conf.get_int('train.perm_num') # Weights self.igr_weight = self.conf.get_float('train.igr_weight') self.mask_weight = self.conf.get_float('train.mask_weight') self.normal_weight = self.conf.get_float('train.normal_weight') self.is_continue = is_continue self.mode = mode self.model_list = [] self.writer = None # Networks params_to_train = [] self.nerf_outside = NeRF(**self.conf['model.nerf']).to(self.device) self.sdf_network = SDFNetwork(**self.conf['model.sdf_network']).to(self.device) self.deviation_network = SingleVarianceNetwork(**self.conf['model.variance_network']).to(self.device) self.color_network = RenderingNetwork(**self.conf['model.rendering_network']).to(self.device) # params_to_train += list(self.nerf_outside.parameters()) # params_to_train += list(self.deviation_network.parameters()) # params_to_train += list(self.color_network.parameters()) # params_to_train_sdf = list(self.sdf_network.parameters()) # self.optimizer = torch.optim.Adam([{'params':params_to_train}, {'params':params_to_train_sdf}], lr=self.learning_rate) params_to_train += list(self.nerf_outside.parameters()) params_to_train += list(self.sdf_network.parameters()) params_to_train += list(self.deviation_network.parameters()) params_to_train += list(self.color_network.parameters()) self.optimizer = torch.optim.Adam(params_to_train, lr=self.learning_rate) self.renderer = NeuSRenderer(self.nerf_outside, self.sdf_network, self.deviation_network, self.color_network, **self.conf['model.neus_renderer']) self.n_samples = self.renderer.n_samples # Load checkpoint latest_model_name = None if is_continue and os.path.exists(os.path.join(self.base_exp_dir, 'checkpoints')): model_list_raw = os.listdir(os.path.join(self.base_exp_dir, 'checkpoints')) model_list = [] for model_name in model_list_raw: if model_name[-3:] == 'pth' and int(model_name[5:-4]): model_list.append(model_name) model_list.sort() latest_model_name = model_list[-1] if latest_model_name is not None: logging.info('Found checkpoint: {}'.format(latest_model_name)) self.load_checkpoint(latest_model_name) # Backup codes and configs for debug if self.mode[:5] == 'train': self.file_backup() def train(self): self.writer = SummaryWriter(log_dir=os.path.join(self.base_exp_dir, 'logs')) self.update_learning_rate() res_step = self.end_iter - self.iter_step image_perm = [] for _ in range(self.perm_num): image_perm.append(self.get_image_perm()) for iter_i in tqdm(range(res_step)): self.patch_size = 1 self.patch_num = int(self.batch_size/self.patch_size/self.patch_size) self.renderer.patch_num = self.patch_num self.renderer.patch_size = self.patch_size for i in range(self.perm_num): if i == 0: data = self.dataset.gen_random_rays_at(image_perm[0][self.iter_step % len(image_perm)], int(self.batch_size/self.perm_num)) else: data_p = self.dataset.gen_random_rays_at(image_perm[i][self.iter_step % len(image_perm)], int(self.batch_size/self.perm_num)) data = torch.cat([data, data_p], dim=0) rays_o, rays_d, true_rgb, mask = data[:, :3], data[:, 3: 6], data[:, 6: 9], data[:, 9: 10] near, far = self.dataset.near_far_from_sphere(rays_o, rays_d) background_rgb = None if self.use_white_bkgd: background_rgb = torch.ones([1, 3]) if self.mask_weight > 0.0: mask = (mask > 0.5).float() else: mask = torch.ones_like(mask) mask_sum = mask.sum() + 1e-5 up_sample = False if self.iter_step >= self.up_sample_start: up_sample = True self.renderer.iter_step = self.iter_step render_out = self.renderer.render(rays_o, rays_d, near, far, background_rgb=background_rgb, cos_anneal_ratio=self.get_cos_anneal_ratio(), weight_anneal_ratio=self.get_weight_anneal_ratio(), up_sample=up_sample, ) color_fine = render_out['color_fine'] s_val = render_out['s_val'] cdf_fine = render_out['cdf_fine'] gradient_error = render_out['gradient_error'] weight_max = render_out['weight_max'] weight_sum = render_out['weight_sum'] normal_error = render_out['normal_error'] # Loss color_error = (color_fine - true_rgb) * mask color_fine_loss = F.l1_loss(color_error, torch.zeros_like(color_error), reduction='sum') / mask_sum psnr = 20.0 * torch.log10(1.0 / (((color_fine - true_rgb)**2 * mask).sum() / (mask_sum * 3.0)).sqrt()) eikonal_loss = gradient_error mask_loss = F.binary_cross_entropy(weight_sum.clip(1e-3, 1.0 - 1e-3), mask) normal_loss = normal_error loss = color_fine_loss loss += eikonal_loss * self.igr_weight loss += mask_loss * self.mask_weight loss += normal_loss * self.normal_weight self.optimizer.zero_grad() loss.backward() self.optimizer.step() self.iter_step += 1 self.writer.add_scalar('Loss/loss', loss, self.iter_step) self.writer.add_scalar('Loss/color_loss', color_fine_loss, self.iter_step) self.writer.add_scalar('Loss/eikonal_loss', eikonal_loss, self.iter_step) self.writer.add_scalar('Loss/normal_loss', normal_loss, self.iter_step) self.writer.add_scalar('Statistics/s_val', s_val.mean(), self.iter_step) self.writer.add_scalar('Statistics/cdf', (cdf_fine[:, :1] * mask).sum() / mask_sum, self.iter_step) self.writer.add_scalar('Statistics/weight_max', (weight_max * mask).sum() / mask_sum, self.iter_step) self.writer.add_scalar('Statistics/psnr', psnr, self.iter_step) if self.iter_step % self.report_freq == 0: print(self.base_exp_dir) print('iter:{:8>d} loss = {} lr={}'.format(self.iter_step, loss, self.optimizer.param_groups[0]['lr'])) if self.iter_step % self.save_freq == 0: self.save_checkpoint() if self.iter_step % self.val_freq == 0: self.validate_image(up_sample=True) if self.iter_step % self.val_mesh_freq == 0: self.validate_mesh(world_space=True, resolution=256, threshold=self.mcube_threshold) self.update_learning_rate() if self.iter_step % self.perm_num == 0: image_perm = [] for _ in range(self.perm_num): image_perm.append(self.get_image_perm()) def get_image_perm(self): return torch.randperm(self.dataset.n_images) def get_cos_anneal_ratio(self): if self.anneal_end == 0.0: return 1.0 else: return np.min([1.0, self.iter_step / self.anneal_end]) def get_weight_anneal_ratio(self): if self.weight_anneal_end == 0.0: return 1.0 else: return np.min([1.0, self.iter_step / self.weight_anneal_end]) def update_learning_rate(self): if self.iter_step < self.warm_up_end: learning_factor = self.iter_step / self.warm_up_end else: alpha = self.learning_rate_alpha progress = (self.iter_step - self.warm_up_end) / (self.end_iter - self.warm_up_end) learning_factor = (np.cos(np.pi * progress) + 1.0) * 0.5 * (1 - alpha) + alpha for g in self.optimizer.param_groups: g['lr'] = self.learning_rate * learning_factor # self.optimizer.param_groups[0]['lr'] = self.learning_rate * learning_factor # self.optimizer.param_groups[1]['lr'] = self.learning_rate_sdf * learning_factor def file_backup(self): dir_lis = self.conf['general.recording'] os.makedirs(os.path.join(self.base_exp_dir, 'recording'), exist_ok=True) for dir_name in dir_lis: cur_dir = os.path.join(self.base_exp_dir, 'recording', dir_name) os.makedirs(cur_dir, exist_ok=True) files = os.listdir(dir_name) for f_name in files: if f_name[-3:] == '.py': copyfile(os.path.join(dir_name, f_name), os.path.join(cur_dir, f_name)) copyfile(self.conf_path, os.path.join(self.base_exp_dir, 'recording', 'config.conf')) def load_checkpoint(self, checkpoint_name): checkpoint = torch.load(os.path.join(self.base_exp_dir, 'checkpoints', checkpoint_name), map_location=self.device) self.nerf_outside.load_state_dict(checkpoint['nerf']) self.sdf_network.load_state_dict(checkpoint['sdf_network_fine']) self.deviation_network.load_state_dict(checkpoint['variance_network_fine']) self.color_network.load_state_dict(checkpoint['color_network_fine']) self.optimizer.load_state_dict(checkpoint['optimizer']) self.iter_step = checkpoint['iter_step'] logging.info('End') def save_checkpoint(self): checkpoint = { 'nerf': self.nerf_outside.state_dict(), 'sdf_network_fine': self.sdf_network.state_dict(), 'variance_network_fine': self.deviation_network.state_dict(), 'color_network_fine': self.color_network.state_dict(), 'optimizer': self.optimizer.state_dict(), 'iter_step': self.iter_step, } os.makedirs(os.path.join(self.base_exp_dir, 'checkpoints'), exist_ok=True) torch.save(checkpoint, os.path.join(self.base_exp_dir, 'checkpoints', 'ckpt_{:0>6d}.pth'.format(self.iter_step))) def validate_image(self, idx=-1, resolution_level=-1, up_sample=True): if idx < 0: idx = np.random.randint(self.dataset.n_images) print('Validate: iter: {}, camera: {}'.format(self.iter_step, idx)) if resolution_level < 0: resolution_level = self.validate_resolution_level rays_o, rays_d = self.dataset.gen_rays_at(idx, resolution_level=resolution_level) H, W, _ = rays_o.shape rays_o = rays_o.reshape(-1, 3).split(self.batch_size) rays_d = rays_d.reshape(-1, 3).split(self.batch_size) out_rgb_fine = [] out_normal_fine = [] for rays_o_batch, rays_d_batch in zip(rays_o, rays_d): near, far = self.dataset.near_far_from_sphere(rays_o_batch, rays_d_batch) background_rgb = torch.ones([1, 3]) if self.use_white_bkgd else None render_out = self.renderer.render(rays_o_batch, rays_d_batch, near, far, cos_anneal_ratio=self.get_cos_anneal_ratio(), background_rgb=background_rgb, up_sample=up_sample, ) def feasible(key): return (key in render_out) and (render_out[key] is not None) if feasible('color_fine'): out_rgb_fine.append(render_out['color_fine'].detach().cpu().numpy()) if feasible('gradients') and feasible('weights'): n_samples = self.renderer.n_samples + self.renderer.n_importance normals = render_out['gradients'] * render_out['weights'][:, :n_samples, None] if feasible('inside_sphere'): normals = normals * render_out['inside_sphere'][..., None] normals = normals.sum(dim=1).detach().cpu().numpy() out_normal_fine.append(normals) del render_out img_fine = None if len(out_rgb_fine) > 0: img_fine = (np.concatenate(out_rgb_fine, axis=0).reshape([H, W, 3, -1]) * 256).clip(0, 255) normal_img = None if len(out_normal_fine) > 0: normal_img = np.concatenate(out_normal_fine, axis=0) rot = np.linalg.inv(self.dataset.pose_all[idx, :3, :3].detach().cpu().numpy()) normal_img = (np.matmul(rot[None, :, :], normal_img[:, :, None]) .reshape([H, W, 3, -1]) * 128 + 128).clip(0, 255) os.makedirs(os.path.join(self.base_exp_dir, 'validations_fine'), exist_ok=True) os.makedirs(os.path.join(self.base_exp_dir, 'normals'), exist_ok=True) for i in range(img_fine.shape[-1]): if len(out_rgb_fine) > 0: cv.imwrite(os.path.join(self.base_exp_dir, 'validations_fine', '{:0>8d}_{}_{}.png'.format(self.iter_step, i, idx)), np.concatenate([img_fine[..., i], self.dataset.image_at(idx, resolution_level=resolution_level)])) if len(out_normal_fine) > 0: cv.imwrite(os.path.join(self.base_exp_dir, 'normals', '{:0>8d}_{}_{}.png'.format(self.iter_step, i, idx)), normal_img[..., i]) def render_novel_image(self, idx_0, idx_1, ratio, resolution_level): """ Interpolate view between two cameras. """ rays_o, rays_d = self.dataset.gen_rays_between(idx_0, idx_1, ratio, resolution_level=resolution_level) H, W, _ = rays_o.shape rays_o = rays_o.reshape(-1, 3).split(self.batch_size) rays_d = rays_d.reshape(-1, 3).split(self.batch_size) out_rgb_fine = [] for rays_o_batch, rays_d_batch in zip(rays_o, rays_d): near, far = self.dataset.near_far_from_sphere(rays_o_batch, rays_d_batch) background_rgb = torch.ones([1, 3]) if self.use_white_bkgd else None render_out = self.renderer.render(rays_o_batch, rays_d_batch, near, far, cos_anneal_ratio=self.get_cos_anneal_ratio(), background_rgb=background_rgb) out_rgb_fine.append(render_out['color_fine'].detach().cpu().numpy()) del render_out img_fine = (np.concatenate(out_rgb_fine, axis=0).reshape([H, W, 3]) * 256).clip(0, 255).astype(np.uint8) return img_fine def validate_mesh(self, world_space=False, resolution=64, threshold=0.0): bound_min = torch.tensor(self.dataset.object_bbox_min, dtype=torch.float32) bound_max = torch.tensor(self.dataset.object_bbox_max, dtype=torch.float32) vertices, triangles =\ self.renderer.extract_geometry(bound_min, bound_max, resolution=resolution, threshold=threshold) os.makedirs(os.path.join(self.base_exp_dir, 'meshes'), exist_ok=True) if world_space: vertices = vertices * self.dataset.scale_mats_np[0][0, 0] + self.dataset.scale_mats_np[0][:3, 3][None] mesh = trimesh.Trimesh(vertices, triangles) mesh.export(os.path.join(self.base_exp_dir, 'meshes', '{:0>8d}.ply'.format(self.iter_step))) logging.info('End') def validate_point(self, num_steps=10, world_space=True, patch_size=10000, color=False): point_cloud, duration = self.renderer.generate_point_cloud(num_steps=num_steps, device=self.device, num_points=1000000, filter_val=0.001) print('num_steps', num_steps, 'duration', duration) if color: color_cpu = [] while len(color_cpu) < len(point_cloud): print(len(color_cpu)) min_idx = len(color_cpu) max_idx = np.min([len(point_cloud), min_idx+patch_size]) color = self.get_vertices_color(vertices=torch.from_numpy(point_cloud[min_idx:max_idx, :].astype(np.float32)).to(self.device)) if len(color_cpu)==0: color_cpu = color else: color_cpu = np.vstack((color_cpu, color)) else: color_cpu = np.ones_like(point_cloud) if world_space: point_cloud = point_cloud * self.dataset.scale_mats_np[0][0, 0] + self.dataset.scale_mats_np[0][:3, 3][None] cloud = trimesh.points.PointCloud(vertices=point_cloud, colors=color_cpu[:, ::-1]) cloud.export(os.path.join(self.base_exp_dir, 'meshes', 'pc{:0>8d}.ply'.format(self.iter_step))) def interpolate_view(self, img_idx_0, img_idx_1): images = [] n_frames = 60 for i in range(n_frames): print(i) images.append(self.render_novel_image(img_idx_0, img_idx_1, np.sin(((i / n_frames) - 0.5) * np.pi) * 0.5 + 0.5, resolution_level=4)) for i in range(n_frames): images.append(images[n_frames - i - 1]) fourcc = cv.VideoWriter_fourcc(*'mp4v') video_dir = os.path.join(self.base_exp_dir, 'render') os.makedirs(video_dir, exist_ok=True) h, w, _ = images[0].shape writer = cv.VideoWriter(os.path.join(video_dir, '{:0>8d}_{}_{}.mp4'.format(self.iter_step, img_idx_0, img_idx_1)), fourcc, 30, (w, h)) for image in images: writer.write(image) writer.release() def validate_mesh_udf_backups(self, world_space=False, resolution=64, color=False): bound_min = torch.tensor(self.dataset.object_bbox_min, dtype=torch.float32) bound_max = torch.tensor(self.dataset.object_bbox_max, dtype=torch.float32) os.makedirs(os.path.join(self.base_exp_dir, 'meshes'), exist_ok=True) vertices, triangles, vertices_color = validate_mesh_udf.main(bound_min, bound_max, self.sdf_network, self.color_network, resolution, color) if world_space: vertices = vertices * self.dataset.scale_mats_np[0][0, 0] + self.dataset.scale_mats_np[0][:3, 3][None] mesh = trimesh.Trimesh(vertices, triangles) if color: mesh.visual.vertex_colors = vertices_color mesh.export(os.path.join(self.base_exp_dir, 'meshes', 'mu{:0>8d}.ply'.format(self.iter_step))) logging.info('End') def validate_ray(self, idx=-1): if idx < 0: idx = self.dataset.n_images // 2 print('Validate: iter: {}, camera: {}'.format(self.iter_step, idx)) rays_o, rays_d = self.dataset.gen_rays_at(idx) H, W, _ = rays_o.shape ray_o = rays_o[H//2, W//2, :].reshape(1, 3) ray_d = rays_d[H//2, W//2, :].reshape(1, 3) near, far = self.dataset.near_far_from_sphere(ray_o, ray_d) background_rgb = torch.ones([1, 3]) if self.use_white_bkgd else None z_vals, sdf, weights = self.renderer.generate_ray(ray_o, ray_d, near, far, cos_anneal_ratio=self.get_cos_anneal_ratio(), background_rgb=background_rgb) weights = weights/(z_vals[1:]-z_vals[:-1]) os.makedirs(os.path.join(self.base_exp_dir, 'validations_ray'), exist_ok=True) plt.plot(z_vals, sdf, marker='1') plt.plot((z_vals[1:] / 2 + z_vals[:-1] / 2), weights/weights.max()) plt.savefig(os.path.join(self.base_exp_dir, 'validations_ray', '{:0>8d}_{}.png'.format(self.iter_step, idx))) plt.close() def get_vertices_color(self, vertices): pts = vertices dirs = torch.zeros_like(pts) sdf_nn_output = self.sdf_network(pts) sdf = sdf_nn_output[:, :1] feature_vector = sdf_nn_output[:, 1:] print(self.color_network.mode) if self.color_network.mode == 'second_order_udf': second_order_gradients, gradients = self.sdf_network.second_order_gradient(pts) second_order_gradients = second_order_gradients.squeeze() gradients = gradients.squeeze() else: second_order_gradients = None gradients = self.sdf_network.gradient(pts).squeeze() sampled_color = self.color_network(pts, gradients, dirs, feature_vector, sdf, second_order_gradients).reshape(-1, 3) return sampled_color.detach().cpu().numpy() def get_vertices_normal(self, vertices): normals = self.sdf_network.gradient(vertices).reshape(-1, 3) return normals.detach().cpu().numpy() def get_vertices_sdf(self, vertices): normals = self.sdf_network.sdf(vertices) return normals.detach().cpu().numpy() def validate_normal(self, num_steps=10, world_space=True, patch_size=10000, num_points=900000, disturb=0.01): point_cloud, duration = self.renderer.generate_point_cloud(num_steps=num_steps, device=self.device, num_points=num_points) point_cloud = (np.random.rand(len(point_cloud), 3) * 2 - 1) * disturb + point_cloud print('num_steps', num_steps, 'duration', duration) normal_cpu = [] while len(normal_cpu) < len(point_cloud): print(len(normal_cpu)) min_idx = len(normal_cpu) max_idx = np.min([len(point_cloud), min_idx+patch_size]) normal = self.get_vertices_normal(vertices=torch.from_numpy(point_cloud[min_idx:max_idx, :].astype(np.float32)).to(self.device)) if len(normal_cpu)==0: normal_cpu = normal else: normal_cpu = np.vstack((normal_cpu, normal)) if world_space: point_cloud = point_cloud * self.dataset.scale_mats_np[0][0, 0] + self.dataset.scale_mats_np[0][:3, 3][None] normal_cpu_p = normal_cpu.clip(0, 1) normal_cpu_n = -normal_cpu.clip(-1, 0) normal_cpu = (normal_cpu_p + normal_cpu_n[:, [1, 2, 0]])*255 normal_cpu = np.clip(normal_cpu, 0, 255) cloud = trimesh.points.PointCloud(vertices=point_cloud, colors=normal_cpu) cloud.export(os.path.join(self.base_exp_dir, 'meshes', 'pn{:0>8d}.ply'.format(self.iter_step))) def validate_udf(self, num_steps=10, world_space=True, patch_size=10000, num_points=900000, disturb=0.01): point_cloud, duration = self.renderer.generate_point_cloud(num_steps=num_steps, device=self.device, num_points=num_points) point_cloud = (np.random.rand(len(point_cloud), 3) * 2 - 1) * disturb + point_cloud print('num_steps', num_steps, 'duration', duration) sdf_cpu = [] while len(sdf_cpu) < len(point_cloud): print(len(sdf_cpu)) min_idx = len(sdf_cpu) max_idx = np.min([len(point_cloud), min_idx+patch_size]) sdf = self.get_vertices_sdf(vertices=torch.from_numpy(point_cloud[min_idx:max_idx, :].astype(np.float32)).to(self.device)) if len(sdf_cpu)==0: sdf_cpu = sdf else: sdf_cpu = np.vstack((sdf_cpu, sdf)) if world_space: point_cloud = point_cloud * self.dataset.scale_mats_np[0][0, 0] + self.dataset.scale_mats_np[0][:3, 3][None] sdf_cpu = np.column_stack((np.zeros_like(sdf_cpu), (sdf_cpu*100).clip(0, 1)*255, (sdf_cpu*100).clip(0, 1)*255)) cloud = trimesh.points.PointCloud(vertices=point_cloud, colors=sdf_cpu) cloud.export(os.path.join(self.base_exp_dir, 'meshes', 'pu{:0>8d}.ply'.format(self.iter_step))) def get_udf_normals_grid_slow(self, b_min, b_max, N=56, max_batch=int(2 ** 20), fourier=False): """ Fills a dense N*N*N regular grid by querying the decoder network Inputs: decoder: coordinate network to evaluate latent_vec: conditioning vector N: grid size max_batch: number of points we can simultaneously evaluate fourier: are xyz coordinates encoded with fourier? Returns: df_values: (N,N,N) tensor representing distance field values on the grid vecs: (N,N,N,3) tensor representing gradients values on the grid, only for locations with a small distance field value samples: (N**3, 7) tensor representing (x,y,z, distance field, grad_x, grad_y, grad_z) """ self.sdf_network.eval() ################ # 1: setting up the empty grid ################ # NOTE: the voxel_origin is actually the (bottom, left, down) corner, not the middle voxel_origin = [b_min, b_min, b_min] voxel_size = (b_max - b_min) / (N - 1) overall_index = torch.arange(0, N ** 3, 1, out=torch.LongTensor()) samples = torch.zeros(N ** 3, 7).cpu() # transform first 3 columns # to be the x, y, z index samples[:, 2] = overall_index % N samples[:, 1] = torch.div(overall_index, N, rounding_mode='floor') % N samples[:, 0] = torch.div(torch.div(overall_index, N, rounding_mode='floor'), N, rounding_mode='floor') % N # transform first 3 columns # to be the x, y, z coordinate samples[:, 0] = (samples[:, 0] * voxel_size) + voxel_origin[2] samples[:, 1] = (samples[:, 1] * voxel_size) + voxel_origin[1] samples[:, 2] = (samples[:, 2] * voxel_size) + voxel_origin[0] num_samples = N ** 3 samples.requires_grad = False # samples.pin_memory() ################ # 2: Run forward pass to fill the grid ################ head = 0 ## FIRST: fill distance field grid without gradients while head < num_samples: # xyz coords sample_subset = samples[head: min(head + max_batch, num_samples), 0:3].clone().cuda() # Create input if fourier: xyz = ws.fourier_transform(sample_subset) else: xyz = sample_subset # Run forward pass with torch.no_grad(): df = self.sdf_network.sdf(xyz) # Store df samples[head: min(head + max_batch, num_samples), 3] = df.squeeze(-1).detach().cpu() # Next iter head += max_batch # ## THEN: compute gradients only where needed, # ie. where the predicted df value is small max_batch = max_batch // 4 norm_mask = samples[:, 3] < 2 * voxel_size norm_idx = torch.where(norm_mask)[0] head, num_samples = 0, norm_idx.shape[0] while head < num_samples: # Find the subset of indices to compute: # -> a subset of indices where normal computations are needed sample_subset_mask = torch.zeros_like(norm_mask) sample_subset_mask[norm_idx[head]: norm_idx[min(head + max_batch, num_samples) - 1] + 1] = True sample_subset_mask = norm_mask * sample_subset_mask # xyz coords sample_subset = samples[sample_subset_mask, 0:3].clone().cuda() sample_subset.requires_grad = True # Create input if fourier: xyz = ws.fourier_transform(sample_subset) else: xyz = sample_subset # Run forward pass df = self.sdf_network.sdf(xyz) # Compute and store normalized vectors pointing towards the surface df.sum().backward() grad = sample_subset.grad.detach() samples[sample_subset_mask, 4:] = - F.normalize(grad, dim=1).cpu() # Next iter head += max_batch # # Separate values in DF / gradients df_values = samples[:, 3] df_values = df_values.reshape(N, N, N) vecs = samples[:, 4:] vecs = vecs.reshape(N, N, N, 3) return df_values, vecs, samples def get_mesh_udf_fast(self, b_min, b_max, N_MC=128, fourier=False, gradient=True, eps=0.1, border_gradients=False, smooth_borders=False): """ Computes a triangulated mesh from a distance field network conditioned on the latent vector Inputs: decoder: coordinate network to evaluate latent_vec: conditioning vector samples: already computed (N**3, 7) tensor representing (x,y,z, distance field, grad_x, grad_y, grad_z) for a previous latent_vec, which is assumed to be close to the current one, if any indices: tensor representing the coordinates that need updating in the previous samples tensor (to speed up iterations) N_MC: grid size fourier: are xyz coordinates encoded with fourier? gradient: do we need gradients? eps: length of the normal vectors used to derive gradients border_gradients: add a special case for border gradients? smooth_borders: do we smooth borders with a Laplacian? Returns: verts: vertices of the mesh faces: faces of the mesh mesh: trimesh object of the mesh samples: (N**3, 7) tensor representing (x,y,z, distance field, grad_x, grad_y, grad_z) indices: tensor representing the coordinates that need updating in the next iteration """ ### 1: sample grid df_values, normals, samples = self.get_udf_normals_grid_slow(b_min, b_max, N=N_MC, fourier=fourier) df_values[df_values < 0] = 0 ### 2: run our custom MC on it N = df_values.shape[0] voxel_size = (b_max - b_min) / (N - 1) voxel_origin = [b_min, b_min, b_min] verts, faces, _, _ = udf_mc_lewiner(df_values.cpu().detach().numpy(), normals.cpu().detach().numpy(), spacing=[voxel_size] * 3) verts = verts + b_min # since voxel_origin = [-1, -1, -1] ### 3: evaluate vertices DF, and remove the ones that are too far verts_torch = torch.from_numpy(verts).float().cuda() with torch.no_grad(): if fourier: xyz = ws.fourier_transform(verts_torch) else: xyz = verts_torch pred_df_verts = self.sdf_network.sdf(xyz) pred_df_verts = pred_df_verts.cpu().numpy() # Remove faces that have vertices far from the surface filtered_faces = faces[np.max(pred_df_verts[faces], axis=1)[:, 0] < voxel_size / 6] filtered_mesh = trimesh.Trimesh(verts, filtered_faces) ### 4: clean the mesh a bit # Remove NaNs, flat triangles, duplicate faces filtered_mesh = filtered_mesh.process( validate=False) # DO NOT try to consistently align winding directions: too slow and poor results filtered_mesh.remove_duplicate_faces() filtered_mesh.remove_degenerate_faces() # Fill single triangle holes filtered_mesh.fill_holes() filtered_mesh_2 = trimesh.Trimesh(filtered_mesh.vertices, filtered_mesh.faces) # Re-process the mesh until it is stable: n_verts, n_faces, n_iter = 0, 0, 0 while (n_verts, n_faces) != (len(filtered_mesh_2.vertices), len(filtered_mesh_2.faces)) and n_iter < 10: filtered_mesh_2 = filtered_mesh_2.process(validate=False) filtered_mesh_2.remove_duplicate_faces() filtered_mesh_2.remove_degenerate_faces() (n_verts, n_faces) = (len(filtered_mesh_2.vertices), len(filtered_mesh_2.faces)) n_iter += 1 filtered_mesh_2 = trimesh.Trimesh(filtered_mesh_2.vertices, filtered_mesh_2.faces) filtered_mesh = trimesh.Trimesh(filtered_mesh_2.vertices, filtered_mesh_2.faces) if smooth_borders: # Identify borders: those appearing only once border_edges = trimesh.grouping.group_rows(filtered_mesh.edges_sorted, require_count=1) # Build a dictionnary of (u,l): l is the list of vertices that are adjacent to u neighbours = defaultdict(lambda: []) for (u, v) in filtered_mesh.edges_sorted[border_edges]: neighbours[u].append(v) neighbours[v].append(u) border_vertices = np.array(list(neighbours.keys())) # Build a sparse matrix for computing laplacian pos_i, pos_j = [], [] for k, ns in enumerate(neighbours.values()): for j in ns: pos_i.append(k) pos_j.append(j) sparse = coo_matrix((np.ones(len(pos_i)), # put ones (pos_i, pos_j)), # at these locations shape=(len(border_vertices), len(filtered_mesh.vertices))) # Smoothing operation: lambda_ = 0.3 for _ in range(5): border_neighbouring_averages = sparse @ filtered_mesh.vertices / sparse.sum(axis=1) laplacian = border_neighbouring_averages - filtered_mesh.vertices[border_vertices] filtered_mesh.vertices[border_vertices] = filtered_mesh.vertices[border_vertices] + lambda_ * laplacian if not gradient: return torch.tensor(filtered_mesh.vertices).float().cuda(), torch.tensor( filtered_mesh.faces).long().cuda(), filtered_mesh else: ### 5: use the mesh to compute normals normals = trimesh.geometry.weighted_vertex_normals(vertex_count=len(filtered_mesh.vertices), faces=filtered_mesh.faces, face_normals=filtered_mesh.face_normals, face_angles=filtered_mesh.face_angles) ### 6: evaluate the DF around each vertex, based on normals normals = torch.tensor(normals).float().cuda() verts = torch.tensor(filtered_mesh.vertices).float().cuda() if fourier: xyz_s1 = ws.fourier_transform(verts + eps * normals) xyz_s2 = ws.fourier_transform(verts - eps * normals) else: xyz_s1 = verts + eps * normals xyz_s2 = verts - eps * normals s1 = decoder(torch.cat([latent_vec.repeat(verts.shape[0], 1), xyz_s1], dim=1)) s2 = decoder(torch.cat([latent_vec.repeat(verts.shape[0], 1), xyz_s2], dim=1)) # Re-plug differentiability here, by this rewriting trick new_verts = verts - eps * s1 * normals + eps * s2 * normals ## Compute indices needed for re-evaluation at the next iteration # fetch bins that are activated k = ((new_verts[:, 2].detach().cpu().numpy() - voxel_origin[2]) / voxel_size).astype(int) j = ((new_verts[:, 1].detach().cpu().numpy() - voxel_origin[1]) / voxel_size).astype(int) i = ((new_verts[:, 0].detach().cpu().numpy() - voxel_origin[0]) / voxel_size).astype(int) # find points around next_samples = i * N_MC * N_MC + j * N_MC + k next_samples_ip = np.minimum(i + 1, N_MC - 1) * N_MC * N_MC + j * N_MC + k next_samples_jp = i * N_MC * N_MC + np.minimum(j + 1, N_MC - 1) * N_MC + k next_samples_kp = i * N_MC * N_MC + j * N_MC + np.minimum(k + 1, N - 1) next_samples_im = np.maximum(i - 1, 0) * N_MC * N_MC + j * N_MC + k next_samples_jm = i * N_MC * N_MC + np.maximum(j - 1, 0) * N_MC + k next_samples_km = i * N_MC * N_MC + j * N_MC + np.maximum(k - 1, 0) # Concatenate next_indices = np.concatenate((next_samples, next_samples_ip, next_samples_jp, next_samples_kp, next_samples_im, next_samples_jm, next_samples_km)) if border_gradients: ### 7: Add gradients at the surface borders? # Identify borders border_edges = trimesh.grouping.group_rows(filtered_mesh.edges_sorted, require_count=1) # Build a dictionnary of (u,v) edges, such that each vertex on the border # gets associated to exactly one border edge border_edges_dict = {} for (u, v) in filtered_mesh.edges_sorted[border_edges]: border_edges_dict[u] = v border_edges_dict[v] = u u_v_border = np.array(list(border_edges_dict.items())) u_border = u_v_border[:, 0] # split border edges (u,v) into u and v arrays v_border = u_v_border[:, 1] # For each vertex on the border, take the cross product between # its normal and the border's edge normals_border = normals[u_border] edge_border = filtered_mesh.vertices[v_border] - filtered_mesh.vertices[u_border] edge_border = torch.tensor(edge_border).float().cuda() out_vec = torch.cross(edge_border, normals_border, dim=1) out_vec = out_vec / (torch.norm(out_vec, dim=1, keepdim=True) + 1e-6) # make it unit length # Then we need to orient the out_vec such that they point outwards # To do so, we evaluate at +- their offset, and take the corresponding max DF value border_verts = torch.tensor(filtered_mesh.vertices[u_border]).float().cuda() if fourier: xyz_s1_border = ws.fourier_transform(border_verts + 3 * eps * out_vec) xyz_s2_border = ws.fourier_transform(border_verts - 3 * eps * out_vec) else: xyz_s1_border = border_verts + 3 * eps * out_vec xyz_s2_border = border_verts - 3 * eps * out_vec s1_border = decoder(torch.cat([latent_vec.repeat(border_verts.shape[0], 1), xyz_s1_border], dim=1)) s2_border = decoder(torch.cat([latent_vec.repeat(border_verts.shape[0], 1), xyz_s2_border], dim=1)) s1s2 = torch.stack((s1_border, s2_border)) sign_out_vec = -torch.argmax(s1s2, dim=0) * 2 + 1 out_vec = sign_out_vec * out_vec # Filter out the verts borders for which a displacement of out_vec # still evaluates at < eps DF, ie. verts classified as borders which are not really so u_border_filtered = u_border[((s1_border + s2_border)[:, 0] > eps).detach().cpu().numpy()] out_vec_filtered = out_vec[(s1_border + s2_border)[:, 0] > eps] out_df_filtered = torch.max(s1_border, s2_border)[(s1_border + s2_border) > eps] # Plug gradients to verts positions s_border = (eps * (out_df_filtered - out_df_filtered.detach())).unsqueeze( -1) # Fake zero, just to pass grads new_verts[u_border_filtered] = new_verts[u_border_filtered] - s_border * out_vec_filtered return new_verts, torch.tensor(filtered_mesh.faces).long().cuda(), filtered_mesh, samples, next_indices def validate_mesh_udf(self, world_space=False, resolution=64, color=False): bound_min = torch.tensor(self.dataset.object_bbox_min, dtype=torch.float32) bound_max = torch.tensor(self.dataset.object_bbox_max, dtype=torch.float32) os.makedirs(os.path.join(self.base_exp_dir, 'meshes'), exist_ok=True) vertices, triangles, vertices_color = self.validate_mesh_udf_main(bound_min, bound_max, resolution, color) if world_space: vertices = vertices * self.dataset.scale_mats_np[0][0, 0] + self.dataset.scale_mats_np[0][:3, 3][None] mesh = trimesh.Trimesh(vertices, triangles) if color: mesh.visual.vertex_colors = vertices_color mesh.export(os.path.join(self.base_exp_dir, 'meshes', 'mu{:0>8d}.ply'.format(self.iter_step))) logging.info('End') def validate_mesh_udf_main(self, b_min, b_max, n, color): b_min_np = b_min.detach().cpu().numpy().min() b_max_np = b_max.detach().cpu().numpy().max() vertices, triangles, _ = self.get_mesh_udf_fast(b_min=b_min_np, b_max=b_max_np, N_MC=n, gradient=False, smooth_borders=False, fourier=False) if color: vertices_color = self.get_vertices_color(vertices) else: vertices_color = torch.zeros_like(vertices) return vertices.detach().cpu().numpy(), triangles.detach().cpu().numpy(), vertices_color.detach().cpu().numpy()[ :, ::-1] if __name__ == '__main__': print('Hello Wooden') torch.set_default_tensor_type('torch.cuda.FloatTensor') FORMAT = "[%(filename)s:%(lineno)s - %(funcName)20s() ] %(message)s" logging.basicConfig(level=logging.DEBUG, format=FORMAT) parser = argparse.ArgumentParser() parser.add_argument('--conf', type=str, default='./confs/base.conf') parser.add_argument('--mode', type=str, default='train') parser.add_argument('--mcube_threshold', type=float, default=0.0025) parser.add_argument('--is_continue', default=False, action="store_true") parser.add_argument('--gpu', type=int, default=0) parser.add_argument('--case', type=str, default='') parser.add_argument('--resolution', type=int, default=512) parser.add_argument('--idx', type=int, default=-1) parser.add_argument('--is_sequence', default=False, action='store_true') parser.add_argument('--unit_sphere', default=False, action='store_true') parser.add_argument('--rev_sequence', default=False, action='store_true') parser.add_argument('--use_color', default=False, action='store_true') args = parser.parse_args() torch.cuda.set_device(args.gpu) if not args.is_sequence: runner = Runner(args.conf, args.mode, args.case, args.is_continue) if args.mode == 'train': runner.train() elif args.mode == 'validate_mesh': runner.validate_mesh(world_space=not args.unit_sphere, resolution=args.resolution, threshold=args.mcube_threshold) elif args.mode == 'validate_point': runner.validate_point(10, color=args.use_color, world_space=not args.unit_sphere) elif args.mode.startswith('interpolate'): # Interpolate views given two image indices _, img_idx_0, img_idx_1 = args.mode.split('_') img_idx_0 = int(img_idx_0) img_idx_1 = int(img_idx_1) runner.interpolate_view(img_idx_0, img_idx_1) elif args.mode == 'validate_mesh_udf': runner.validate_mesh_udf(world_space=not args.unit_sphere, resolution=args.resolution, color=args.use_color) elif args.mode == 'refine': runner.refine() elif args.mode == 'validate_image': runner.validate_image(idx=args.idx) elif args.mode == 'validate_ray': runner.renderer.iter_step = runner.iter_step runner.validate_ray() elif args.mode == 'validate_normal': runner.validate_normal() elif args.mode == 'validate_udf': runner.validate_udf() elif args.mode == 'validate_mesh_poisson': runner.validate_mesh_poisson() elif args.mode == 'validate_mesh_poisson_test': runner.validate_mesh_poisson_test(threshold=args.mcube_threshold) else: case_list = os.listdir(os.path.join('./public_data', args.case)) if args.rev_sequence: case_list = reversed(case_list) for case in case_list: runner = Runner(args.conf, args.mode, os.path.join(args.case, case), args.is_continue) if args.mode == 'train': runner.train() runner.validate_point() # try: # runner.validate_mesh_udf(world_space=True, resolution=args.resolution) # except: # print('validate_mesh_udf error') # finally: # pass elif args.mode == 'validate_mesh': runner.validate_mesh(world_space=True, resolution=args.resolution, threshold=args.mcube_threshold) elif args.mode == 'validate_point': runner.validate_point(10, color=args.use_color, world_space=not args.unit_sphere) elif args.mode.startswith('interpolate'): # Interpolate views given two image indices _, img_idx_0, img_idx_1 = args.mode.split('_') img_idx_0 = int(img_idx_0) img_idx_1 = int(img_idx_1) runner.interpolate_view(img_idx_0, img_idx_1) elif args.mode == 'validate_mesh_udf': runner.validate_mesh_udf(world_space=True, resolution=args.resolution, color=args.use_color) elif args.mode == 'refine': runner.refine() elif args.mode == 'validate_image': runner.validate_image(idx=args.idx) elif args.mode == 'validate_ray': runner.renderer.iter_step = runner.iter_step runner.validate_ray() elif args.mode == 'validate_normal': runner.validate_normal() elif args.mode == 'validate_udf': runner.validate_udf() del runner.dataset del runner ================================================ FILE: lib/__init__.py ================================================ from lib.workspace import * ================================================ FILE: lib/models/deep_udf_decoder.py ================================================ import torch.nn as nn import torch import torch.nn.functional as F class Decoder(nn.Module): def __init__( self, latent_size, dims, dropout=None, dropout_prob=0.0, norm_layers=(), latent_in=(), weight_norm=False, xyz_in_all=None, use_tanh=False, latent_dropout=False, fourier = False, fourier_add = False, fourier_latent = False, fourier_latent_add = False ): super(Decoder, self).__init__() # handle fourier transform of latent code if fourier_latent is True and fourier_latent_add is False: latent_dimension = 2*4*latent_size elif fourier_latent is False and fourier_latent_add is True: latent_dimension = 2*4*latent_size + latent_size else: latent_dimension = latent_size # handle fourier transform of poisitional coordinates if fourier is True and fourier_add is False: spatial_dimension = 2*5*3 elif fourier is False and fourier_add is True: spatial_dimension = 2*5*3+3 else: spatial_dimension = 3 dims = [latent_dimension + spatial_dimension] + dims + [1] self.num_layers = len(dims) self.norm_layers = norm_layers self.latent_in = latent_in self.latent_dropout = latent_dropout if self.latent_dropout: self.lat_dp = nn.Dropout(0.2) self.xyz_in_all = xyz_in_all self.weight_norm = weight_norm for layer in range(0, self.num_layers - 1): if layer + 1 in latent_in: out_dim = dims[layer + 1] - dims[0] else: out_dim = dims[layer + 1] if self.xyz_in_all and layer != self.num_layers - 2: out_dim -= 3 if weight_norm and layer in self.norm_layers: setattr( self, "lin" + str(layer), nn.utils.weight_norm(nn.Linear(dims[layer], out_dim)), ) else: setattr(self, "lin" + str(layer), nn.Linear(dims[layer], out_dim)) if ( (not weight_norm) and self.norm_layers is not None and layer in self.norm_layers ): setattr(self, "bn" + str(layer), nn.LayerNorm(out_dim)) self.use_tanh = use_tanh if use_tanh: self.tanh = nn.Tanh() self.relu = nn.ReLU() self.dropout_prob = dropout_prob self.dropout = dropout self.relu = nn.ReLU() # input: N x (L+3) def forward(self, input): xyz = input[:, -3:] if input.shape[1] > 3 and self.latent_dropout: latent_vecs = input[:, :-3] latent_vecs = F.dropout(latent_vecs, p=0.2, training=self.training) x = torch.cat([latent_vecs, xyz], 1) else: x = input for layer in range(0, self.num_layers - 1): lin = getattr(self, "lin" + str(layer)) if layer in self.latent_in: x = torch.cat([x, input], 1) elif layer != 0 and self.xyz_in_all: x = torch.cat([x, xyz], 1) x = lin(x) # last layer Tanh if layer == self.num_layers - 2 and self.use_tanh: x = self.tanh(x) if layer < self.num_layers - 2: if ( self.norm_layers is not None and layer in self.norm_layers and not self.weight_norm ): bn = getattr(self, "bn" + str(layer)) x = bn(x) x = self.relu(x) if self.dropout is not None and layer in self.dropout: x = F.dropout(x, p=self.dropout_prob, training=self.training) x = self.relu(x) return x ================================================ FILE: lib/workspace.py ================================================ import json import os import torch model_params_subdir = "ModelParameters" latent_codes_subdir = "LatentCodes" specifications_filename = "specs.json" def load_experiment_specifications(experiment_directory): filename = os.path.join(experiment_directory, specifications_filename) if not os.path.isfile(filename): raise Exception( "The experiment directory ({}) does not include specifications file " + '"specs.json"'.format(experiment_directory) ) return json.load(open(filename)) def load_model_parameters_decoder(experiment_directory, checkpoint, decoder): filename = os.path.join( experiment_directory, model_params_subdir, checkpoint + ".pth" ) if not os.path.isfile(filename): raise Exception('model state dict "{}" does not exist'.format(filename)) data = torch.load(filename) decoder.load_state_dict(data["model_state_dict"]) return data["epoch"] def get_latent_codes_dir(experiment_dir, create_if_nonexistent=False): dir = os.path.join(experiment_dir, latent_codes_subdir) if create_if_nonexistent and not os.path.isdir(dir): os.makedirs(dir) return dir def load_latent_vectors(experiment_directory, filename): full_filename = os.path.join( get_latent_codes_dir(experiment_directory), filename ) if not os.path.isfile(full_filename): raise Exception('latent state file "{}" does not exist'.format(full_filename)) return torch.load(full_filename)["latent_codes"] def fourier_transform(x, L=5): cosines = torch.cat([torch.cos(2**l*3.1415*x) for l in range(L)], -1) sines = torch.cat([torch.sin(2**l*3.1415*x) for l in range(L)], -1) transformed_x = torch.cat((cosines,sines),-1) return transformed_x ================================================ FILE: models/dataset.py ================================================ import torch import torch.nn.functional as F import cv2 as cv import numpy as np import os from glob import glob from icecream import ic from scipy.spatial.transform import Rotation as Rot from scipy.spatial.transform import Slerp # This function is borrowed from IDR: https://github.com/lioryariv/idr def load_K_Rt_from_P(filename, P=None): if P is None: lines = open(filename).read().splitlines() if len(lines) == 4: lines = lines[1:] lines = [[x[0], x[1], x[2], x[3]] for x in (x.split(" ") for x in lines)] P = np.asarray(lines).astype(np.float32).squeeze() out = cv.decomposeProjectionMatrix(P) K = out[0] R = out[1] t = out[2] K = K / K[2, 2] intrinsics = np.eye(4) intrinsics[:3, :3] = K pose = np.eye(4, dtype=np.float32) pose[:3, :3] = R.transpose() pose[:3, 3] = (t[:3] / t[3])[:, 0] return intrinsics, pose class Dataset: def __init__(self, conf): super(Dataset, self).__init__() print('Load data: Begin') self.device = torch.device('cuda') self.conf = conf self.data_dir = conf.get_string('data_dir') self.render_cameras_name = conf.get_string('render_cameras_name') self.object_cameras_name = conf.get_string('object_cameras_name') self.camera_outside_sphere = conf.get_bool('camera_outside_sphere', default=True) self.scale_mat_scale = conf.get_float('scale_mat_scale', default=1.1) camera_dict = np.load(os.path.join(self.data_dir, self.render_cameras_name)) self.camera_dict = camera_dict self.images_lis = sorted(glob(os.path.join(self.data_dir, 'image/*.png'))) self.n_images = len(self.images_lis) self.images_np = np.stack([cv.imread(im_name) for im_name in self.images_lis]) / 256.0 self.masks_lis = sorted(glob(os.path.join(self.data_dir, 'mask/*.png'))) self.masks_np = np.stack([cv.imread(im_name) for im_name in self.masks_lis]) / 256.0 # world_mat is a projection matrix from world to image self.world_mats_np = [camera_dict['world_mat_%d' % idx].astype(np.float32) for idx in range(self.n_images)] self.scale_mats_np = [] # scale_mat: used for coordinate normalization, we assume the scene to render is inside a unit sphere at origin. self.scale_mats_np = [camera_dict['scale_mat_%d' % idx].astype(np.float32) for idx in range(self.n_images)] self.intrinsics_all = [] self.pose_all = [] for scale_mat, world_mat in zip(self.scale_mats_np, self.world_mats_np): P = world_mat @ scale_mat P = P[:3, :4] intrinsics, pose = load_K_Rt_from_P(None, P) self.intrinsics_all.append(torch.from_numpy(intrinsics).float()) self.pose_all.append(torch.from_numpy(pose).float()) self.images = torch.from_numpy(self.images_np.astype(np.float32)).cpu() # [n_images, H, W, 3] self.masks = torch.from_numpy(self.masks_np.astype(np.float32)).cpu() # [n_images, H, W, 3] self.intrinsics_all = torch.stack(self.intrinsics_all).to(self.device) # [n_images, 4, 4] self.intrinsics_all_inv = torch.inverse(self.intrinsics_all) # [n_images, 4, 4] self.focal = self.intrinsics_all[0][0, 0] self.pose_all = torch.stack(self.pose_all).to(self.device) # [n_images, 4, 4] self.H, self.W = self.images.shape[1], self.images.shape[2] self.image_pixels = self.H * self.W object_bbox_min = np.array([-1.01, -1.01, -1.01, 1.0]) object_bbox_max = np.array([ 1.01, 1.01, 1.01, 1.0]) # Object scale mat: region of interest to **extract mesh** object_scale_mat = np.load(os.path.join(self.data_dir, self.object_cameras_name))['scale_mat_0'] object_bbox_min = np.linalg.inv(self.scale_mats_np[0]) @ object_scale_mat @ object_bbox_min[:, None] object_bbox_max = np.linalg.inv(self.scale_mats_np[0]) @ object_scale_mat @ object_bbox_max[:, None] self.object_bbox_min = object_bbox_min[:3, 0] self.object_bbox_max = object_bbox_max[:3, 0] print('Load data: End') def gen_rays_at(self, img_idx, resolution_level=1): """ Generate rays at world space from one camera. """ l = resolution_level tx = torch.linspace(0, self.W - 1, self.W // l) ty = torch.linspace(0, self.H - 1, self.H // l) pixels_x, pixels_y = torch.meshgrid(tx, ty) p = torch.stack([pixels_x, pixels_y, torch.ones_like(pixels_y)], dim=-1) # W, H, 3 p = torch.matmul(self.intrinsics_all_inv[img_idx, None, None, :3, :3], p[:, :, :, None]).squeeze() # W, H, 3 rays_v = p / torch.linalg.norm(p, ord=2, dim=-1, keepdim=True) # W, H, 3 rays_v = torch.matmul(self.pose_all[img_idx, None, None, :3, :3], rays_v[:, :, :, None]).squeeze() # W, H, 3 rays_o = self.pose_all[img_idx, None, None, :3, 3].expand(rays_v.shape) # W, H, 3 return rays_o.transpose(0, 1), rays_v.transpose(0, 1) def gen_random_rays_at(self, img_idx, batch_size): """ Generate random rays at world space from one camera. """ pixels_x = torch.randint(low=0, high=self.W, size=[batch_size]) pixels_y = torch.randint(low=0, high=self.H, size=[batch_size]) color = self.images[img_idx][(pixels_y, pixels_x)] # batch_size, 3 mask = self.masks[img_idx][(pixels_y, pixels_x)] # batch_size, 3 p = torch.stack([pixels_x, pixels_y, torch.ones_like(pixels_y)], dim=-1).float() # batch_size, 3 p = torch.matmul(self.intrinsics_all_inv[img_idx, None, :3, :3], p[:, :, None]).squeeze() # batch_size, 3 rays_v = p / torch.linalg.norm(p, ord=2, dim=-1, keepdim=True) # batch_size, 3 rays_v = torch.matmul(self.pose_all[img_idx, None, :3, :3], rays_v[:, :, None]).squeeze() # batch_size, 3 rays_o = self.pose_all[img_idx, None, :3, 3].expand(rays_v.shape) # batch_size, 3 return torch.cat([rays_o.cpu(), rays_v.cpu(), color, mask[:, :1]], dim=-1).cuda() # batch_size, 10 def gen_rays_between(self, idx_0, idx_1, ratio, resolution_level=1): """ Interpolate pose between two cameras. """ l = resolution_level tx = torch.linspace(0, self.W - 1, self.W // l) ty = torch.linspace(0, self.H - 1, self.H // l) pixels_x, pixels_y = torch.meshgrid(tx, ty) p = torch.stack([pixels_x, pixels_y, torch.ones_like(pixels_y)], dim=-1) # W, H, 3 p = torch.matmul(self.intrinsics_all_inv[0, None, None, :3, :3], p[:, :, :, None]).squeeze() # W, H, 3 rays_v = p / torch.linalg.norm(p, ord=2, dim=-1, keepdim=True) # W, H, 3 trans = self.pose_all[idx_0, :3, 3] * (1.0 - ratio) + self.pose_all[idx_1, :3, 3] * ratio pose_0 = self.pose_all[idx_0].detach().cpu().numpy() pose_1 = self.pose_all[idx_1].detach().cpu().numpy() pose_0 = np.linalg.inv(pose_0) pose_1 = np.linalg.inv(pose_1) rot_0 = pose_0[:3, :3] rot_1 = pose_1[:3, :3] rots = Rot.from_matrix(np.stack([rot_0, rot_1])) key_times = [0, 1] slerp = Slerp(key_times, rots) rot = slerp(ratio) pose = np.diag([1.0, 1.0, 1.0, 1.0]) pose = pose.astype(np.float32) pose[:3, :3] = rot.as_matrix() pose[:3, 3] = ((1.0 - ratio) * pose_0 + ratio * pose_1)[:3, 3] pose = np.linalg.inv(pose) rot = torch.from_numpy(pose[:3, :3]).cuda() trans = torch.from_numpy(pose[:3, 3]).cuda() rays_v = torch.matmul(rot[None, None, :3, :3], rays_v[:, :, :, None]).squeeze() # W, H, 3 rays_o = trans[None, None, :3].expand(rays_v.shape) # W, H, 3 return rays_o.transpose(0, 1), rays_v.transpose(0, 1) def near_far_from_sphere(self, rays_o, rays_d): a = torch.sum(rays_d**2, dim=-1, keepdim=True) b = 2.0 * torch.sum(rays_o * rays_d, dim=-1, keepdim=True) mid = 0.5 * (-b) / a near = mid - 1.0 far = mid + 1.0 return near, far def image_at(self, idx, resolution_level): img = cv.imread(self.images_lis[idx]) return (cv.resize(img, (self.W // resolution_level, self.H // resolution_level))).clip(0, 255) def gen_patch_rays_at(self, img_idx, batch_size, patch_size): """ Generate rays at world space from one camera. """ # tx = torch.arange(patch_size)[None, :]+torch.randint(low=0, high=self.W-patch_size+1, size=[batch_size])[:, None].reshape(-1) # ty = torch.arange(patch_size)[None, :]+torch.randint(low=0, high=self.H-patch_size+1, size=[batch_size])[:, None].reshape(-1) # pixels_x, pixels_y = torch.meshgrid(tx, ty) # pixels_x = pixels_x.reshape(-1) # pixels_y = pixels_y.reshape(-1) # print(self.W-patch_size+1, [batch_size]) anchor_x = torch.randint(low=0, high=self.W-patch_size+1, size=[batch_size]) anchor_y = torch.randint(low=0, high=self.H-patch_size+1, size=[batch_size]) patch_x = torch.arange(patch_size) patch_y = torch.arange(patch_size) patch_pixel_x, patch_pixel_y = torch.meshgrid(patch_x, patch_y) pixels_x = (anchor_x[:, None, None] + patch_pixel_x[None, :, :]).reshape(-1) pixels_y = (anchor_y[:, None, None] + patch_pixel_y[None, :, :]).reshape(-1) color = self.images[img_idx][(pixels_y, pixels_x)] # batch_size, 3 mask = self.masks[img_idx][(pixels_y, pixels_x)] # batch_size, 3 p = torch.stack([pixels_x, pixels_y, torch.ones_like(pixels_y)], dim=-1).float() # batch_size, 3 p = torch.matmul(self.intrinsics_all_inv[img_idx, None, :3, :3], p[:, :, None]).squeeze() # batch_size, 3 rays_v = p / torch.linalg.norm(p, ord=2, dim=-1, keepdim=True) # batch_size, 3 rays_v = torch.matmul(self.pose_all[img_idx, None, :3, :3], rays_v[:, :, None]).squeeze() # batch_size, 3 rays_o = self.pose_all[img_idx, None, :3, 3].expand(rays_v.shape) # batch_size, 3 return torch.cat([rays_o.cpu(), rays_v.cpu(), color, mask[:, :1]], dim=-1).cuda() # batch_size, 10 ================================================ FILE: models/embedder.py ================================================ import torch import torch.nn as nn # Positional encoding embedding. Code was taken from https://github.com/bmild/nerf. class Embedder: def __init__(self, **kwargs): self.kwargs = kwargs self.create_embedding_fn() def create_embedding_fn(self): embed_fns = [] d = self.kwargs['input_dims'] out_dim = 0 if self.kwargs['include_input']: embed_fns.append(lambda x: x) out_dim += d max_freq = self.kwargs['max_freq_log2'] N_freqs = self.kwargs['num_freqs'] if self.kwargs['log_sampling']: freq_bands = 2. ** torch.linspace(0., max_freq, N_freqs) else: freq_bands = torch.linspace(2.**0., 2.**max_freq, N_freqs) for freq in freq_bands: for p_fn in self.kwargs['periodic_fns']: embed_fns.append(lambda x, p_fn=p_fn, freq=freq: p_fn(x * freq)) out_dim += d self.embed_fns = embed_fns self.out_dim = out_dim def embed(self, inputs): return torch.cat([fn(inputs) for fn in self.embed_fns], -1) def get_embedder(multires, input_dims=3): embed_kwargs = { 'include_input': True, 'input_dims': input_dims, 'max_freq_log2': multires-1, 'num_freqs': multires, 'log_sampling': True, 'periodic_fns': [torch.sin, torch.cos], } embedder_obj = Embedder(**embed_kwargs) def embed(x, eo=embedder_obj): return eo.embed(x) return embed, embedder_obj.out_dim ================================================ FILE: models/fields.py ================================================ import torch import torch.nn as nn import torch.nn.functional as F import numpy as np from models.embedder import get_embedder # This implementation is borrowed from IDR: https://github.com/lioryariv/idr class SDFNetwork(nn.Module): def __init__(self, d_in, d_out, d_hidden, n_layers, skip_in=(4,), multires=0, bias=0.5, scale=1, geometric_init=True, weight_norm=True, inside_outside=False, mode='act'): super(SDFNetwork, self).__init__() dims = [d_in] + [d_hidden for _ in range(n_layers)] + [d_out] self.embed_fn_fine = None if multires > 0: embed_fn, input_ch = get_embedder(multires, input_dims=d_in) self.embed_fn_fine = embed_fn dims[0] = input_ch self.num_layers = len(dims) self.skip_in = skip_in self.scale = scale for l in range(0, self.num_layers - 1): if l + 1 in self.skip_in: out_dim = dims[l + 1] - dims[0] else: out_dim = dims[l + 1] lin = nn.Linear(dims[l], out_dim) if geometric_init: if l == self.num_layers - 2: if not inside_outside: torch.nn.init.normal_(lin.weight, mean=np.sqrt(np.pi) / np.sqrt(dims[l]), std=0.0001) torch.nn.init.constant_(lin.bias, -bias) else: torch.nn.init.normal_(lin.weight, mean=-np.sqrt(np.pi) / np.sqrt(dims[l]), std=0.0001) torch.nn.init.constant_(lin.bias, bias) elif multires > 0 and l == 0: torch.nn.init.constant_(lin.bias, 0.0) torch.nn.init.constant_(lin.weight[:, 3:], 0.0) torch.nn.init.normal_(lin.weight[:, :3], 0.0, np.sqrt(2) / np.sqrt(out_dim)) elif multires > 0 and l in self.skip_in: torch.nn.init.constant_(lin.bias, 0.0) torch.nn.init.normal_(lin.weight, 0.0, np.sqrt(2) / np.sqrt(out_dim)) torch.nn.init.constant_(lin.weight[:, -(dims[0] - 3):], 0.0) else: torch.nn.init.constant_(lin.bias, 0.0) torch.nn.init.normal_(lin.weight, 0.0, np.sqrt(2) / np.sqrt(out_dim)) if weight_norm: lin = nn.utils.weight_norm(lin) setattr(self, "lin" + str(l), lin) self.activation = nn.Softplus(beta=100) self.mode = mode def forward(self, inputs): inputs = inputs * self.scale if self.embed_fn_fine is not None: inputs = self.embed_fn_fine(inputs) x = inputs for l in range(0, self.num_layers - 1): lin = getattr(self, "lin" + str(l)) if l in self.skip_in: x = torch.cat([x, inputs], 1) / np.sqrt(2) x = lin(x) if l < self.num_layers - 2: x = self.activation(x) x = self.activation(x) return torch.cat([x[:, :1] / self.scale, x[:, 1:]], dim=-1) def sdf(self, x): return self.forward(x)[:, :1] def sdf_hidden_appearance(self, x): return self.forward(x) def gradient(self, x): x.requires_grad_(True) y = self.sdf(x) d_output = torch.ones_like(y, requires_grad=False, device=y.device) gradients = torch.autograd.grad( outputs=y, inputs=x, grad_outputs=d_output, create_graph=True, retain_graph=True, only_inputs=True)[0] return gradients.unsqueeze(1) # This implementation is borrowed from IDR: https://github.com/lioryariv/idr class RenderingNetwork(nn.Module): def __init__(self, d_feature, mode, d_in, d_out, d_hidden, n_layers, weight_norm=True, multires_view=0, squeeze_out=True): super().__init__() self.mode = mode self.squeeze_out = squeeze_out dims = [d_in + d_feature] + [d_hidden for _ in range(n_layers)] + [d_out] self.embedview_fn = None if multires_view > 0: embedview_fn, input_ch = get_embedder(multires_view) self.embedview_fn = embedview_fn dims[0] += (input_ch - 3) self.num_layers = len(dims) for l in range(0, self.num_layers - 1): out_dim = dims[l + 1] lin = nn.Linear(dims[l], out_dim) if weight_norm: lin = nn.utils.weight_norm(lin) setattr(self, "lin" + str(l), lin) self.relu = nn.ReLU() def forward(self, points, normals, view_dirs, feature_vectors, sdf=None, second_order_gradients=None): view_dirs_raw = view_dirs if self.embedview_fn is not None: view_dirs = self.embedview_fn(view_dirs) rendering_input = None if self.mode == 'idr' or self.mode == 'normal_appr': rendering_input = torch.cat([points, view_dirs, normals, feature_vectors], dim=-1) elif self.mode == 'no_view_dir': rendering_input = torch.cat([points, normals, feature_vectors], dim=-1) elif self.mode == 'no_normal': rendering_input = torch.cat([points, view_dirs, feature_vectors], dim=-1) elif self.mode == 'udf': rendering_input = torch.cat([points, view_dirs, sdf, feature_vectors], dim=-1) elif self.mode == 'second_order_udf': rendering_input = torch.cat([points, view_dirs, second_order_gradients, feature_vectors], dim=-1) elif self.mode == 'approximate_udf': appr_gradients = (normals[:, 2:] - normals[:, :-2]) appr_zeros = torch.zeros_like(appr_gradients[:, :1]) appr_gradients = torch.cat([appr_zeros, appr_gradients, appr_zeros], dim=-1) rendering_input = torch.cat([points, view_dirs, appr_gradients, feature_vectors], dim=-1) elif self.mode == 'multi_udf': prev_normals = torch.cat([torch.zeros_like(normals[:, :1]), normals[:, :-1]], dim=-1) next_normals = torch.cat([normals[:, 1:], torch.zeros_like(normals[:, :1])], dim=-1) rendering_input = torch.cat([points, view_dirs, prev_normals, normals, next_normals, feature_vectors], dim=-1) elif self.mode == 'positive_normal_z': normals_z = normals[..., 2] is_invert = torch.where(normals_z>0, torch.ones_like(normals_z), -torch.ones_like(normals_z)) rendering_input = torch.cat([points, view_dirs, normals*is_invert[..., None], feature_vectors], dim=-1) elif self.mode == 'prev_normal': prev_normals = torch.cat([torch.zeros_like(normals[:, :1]), normals[:, :-1]], dim=-1) rendering_input = torch.cat([points, view_dirs, prev_normals, feature_vectors], dim=-1) elif self.mode == 'random_normal': sign = torch.sign(torch.randn(1)).item() rendering_input = torch.cat([points, view_dirs, normals*sign, feature_vectors], dim=-1) elif self.mode == 'npnz': n_normals = normals / torch.linalg.norm(normals, ord=2, dim=-1)[..., None] normals_z = n_normals[..., 2] is_invert = torch.where(normals_z>0, torch.ones_like(normals_z), -torch.ones_like(normals_z)) rendering_input = torch.cat([points, view_dirs, n_normals*is_invert[..., None], feature_vectors], dim=-1) elif self.mode == 'multi_npnz': n_normals = normals / torch.linalg.norm(normals, ord=2, dim=-1)[..., None] normals_z = n_normals[..., 2] is_invert_z = torch.where(normals_z > 0, torch.ones_like(normals_z), -torch.ones_like(normals_z)) normals_y = n_normals[..., 1] is_invert_y = torch.where(normals_y > 0, torch.ones_like(normals_y), -torch.ones_like(normals_y)) normals_x = n_normals[..., 0] is_invert_x = torch.where(normals_x > 0, torch.ones_like(normals_x), -torch.ones_like(normals_x)) rendering_input = torch.cat([points, view_dirs, n_normals * is_invert_z[..., None], n_normals * is_invert_y[..., None], n_normals * is_invert_x[..., None], feature_vectors], dim=-1) elif self.mode == 'angle': norm = torch.linalg.norm(normals, ord=2, dim=-1, keepdim=True) theta = torch.acos(normals[:, :1]/((normals[:, 1:2]**2+normals[:, :1]**2)**0.5+1e-10))*torch.sign(normals[:, 1:2]) phi = torch.asin(normals[:, -1:]/(norm+1e-10)) rendering_input = torch.cat([points, view_dirs, norm, theta, phi, feature_vectors], dim=-1) elif self.mode == 'reflect': normals = normals / torch.linalg.norm(normals) # print(view_dirs_raw.shape) # print(normals.shape) view_cos = (view_dirs_raw * normals).sum(dim=-1, keepdim=True) reflect_dir = view_dirs_raw - 2 * view_cos * normals rendering_input = torch.cat([points, view_dirs, reflect_dir, feature_vectors], dim=-1) elif self.mode == 'obtuse_normal': cos = (normals * view_dirs_raw).sum(dim=-1, keepdim=True) is_invert = torch.where(cos<0, torch.ones_like(cos), -torch.ones_like(cos)) rendering_input = torch.cat([points, view_dirs, normals*is_invert, feature_vectors], dim=-1) x = rendering_input for l in range(0, self.num_layers - 1): lin = getattr(self, "lin" + str(l)) x = lin(x) if l < self.num_layers - 2: x = self.relu(x) if self.squeeze_out: x = torch.sigmoid(x) return x # This implementation is borrowed from nerf-pytorch: https://github.com/yenchenlin/nerf-pytorch class NeRF(nn.Module): def __init__(self, D=8, W=256, d_in=3, d_in_view=3, multires=0, multires_view=0, output_ch=4, skips=[4], use_viewdirs=False): super(NeRF, self).__init__() self.D = D self.W = W self.d_in = d_in self.d_in_view = d_in_view self.input_ch = 3 self.input_ch_view = 3 self.embed_fn = None self.embed_fn_view = None if multires > 0: embed_fn, input_ch = get_embedder(multires, input_dims=d_in) self.embed_fn = embed_fn self.input_ch = input_ch if multires_view > 0: embed_fn_view, input_ch_view = get_embedder(multires_view, input_dims=d_in_view) self.embed_fn_view = embed_fn_view self.input_ch_view = input_ch_view self.skips = skips self.use_viewdirs = use_viewdirs self.pts_linears = nn.ModuleList( [nn.Linear(self.input_ch, W)] + [nn.Linear(W, W) if i not in self.skips else nn.Linear(W + self.input_ch, W) for i in range(D - 1)]) ### Implementation according to the official code release ### (https://github.com/bmild/nerf/blob/master/run_nerf_helpers.py#L104-L105) self.views_linears = nn.ModuleList([nn.Linear(self.input_ch_view + W, W // 2)]) ### Implementation according to the paper # self.views_linears = nn.ModuleList( # [nn.Linear(input_ch_views + W, W//2)] + [nn.Linear(W//2, W//2) for i in range(D//2)]) if use_viewdirs: self.feature_linear = nn.Linear(W, W) self.alpha_linear = nn.Linear(W, 1) self.rgb_linear = nn.Linear(W // 2, 3) else: self.output_linear = nn.Linear(W, output_ch) def forward(self, input_pts, input_views): if self.embed_fn is not None: input_pts = self.embed_fn(input_pts) if self.embed_fn_view is not None: input_views = self.embed_fn_view(input_views) h = input_pts for i, l in enumerate(self.pts_linears): h = self.pts_linears[i](h) h = F.relu(h) if i in self.skips: h = torch.cat([input_pts, h], -1) if self.use_viewdirs: alpha = self.alpha_linear(h) feature = self.feature_linear(h) h = torch.cat([feature, input_views], -1) for i, l in enumerate(self.views_linears): h = self.views_linears[i](h) h = F.relu(h) rgb = self.rgb_linear(h) return alpha, rgb else: assert False class SingleVarianceNetwork(nn.Module): def __init__(self, init_val): super(SingleVarianceNetwork, self).__init__() self.register_parameter('variance', nn.Parameter(torch.tensor(init_val))) def forward(self, x): return torch.ones([len(x), 1]) * torch.exp(self.variance * 10.0) ================================================ FILE: models/renderer.py ================================================ import torch import torch.nn as nn import torch.nn.functional as F import numpy as np import logging import mcubes from icecream import ic import time from skimage.measure import marching_cubes def extract_fields(bound_min, bound_max, resolution, query_func): N = 64 X = torch.linspace(bound_min[0], bound_max[0], resolution).split(N) Y = torch.linspace(bound_min[1], bound_max[1], resolution).split(N) Z = torch.linspace(bound_min[2], bound_max[2], resolution).split(N) u = np.zeros([resolution, resolution, resolution], dtype=np.float32) with torch.no_grad(): for xi, xs in enumerate(X): for yi, ys in enumerate(Y): for zi, zs in enumerate(Z): xx, yy, zz = torch.meshgrid(xs, ys, zs) pts = torch.cat([xx.reshape(-1, 1), yy.reshape(-1, 1), zz.reshape(-1, 1)], dim=-1) #print('pts shape: {}'.format(pts.shape)) val = query_func(pts).reshape(len(xs), len(ys), len(zs)).detach().cpu().numpy() u[xi * N: xi * N + len(xs), yi * N: yi * N + len(ys), zi * N: zi * N + len(zs)] = val return u def extract_geometry(bound_min, bound_max, resolution, threshold, query_func): print('threshold: {}'.format(threshold)) #print('bound_min: {}'.format(bound_min)) #print('bound_max: {}'.format(bound_max)) u = extract_fields(bound_min, bound_max, resolution, query_func) # for debug udf u_min = np.min(u) u_max = np.max(u) print('u max: {}'.format(u_max)) print('u min: {}'.format(u_min)) if threshold < np.min(u) or threshold > np.max(u): threshold_mc = 0.99*u_min+0.01*u_max else: threshold_mc = threshold vertices, triangles, _, _ = marching_cubes(u, threshold_mc) b_max_np = bound_max.detach().cpu().numpy() b_min_np = bound_min.detach().cpu().numpy() vertices = vertices / (resolution - 1.0) * (b_max_np - b_min_np)[None, :] + b_min_np[None, :] return vertices, triangles def sample_pdf(bins, weights, n_samples, det=False): # This implementation is from NeRF # Get pdf weights = weights + 1e-5 # prevent nans pdf = weights / torch.sum(weights, -1, keepdim=True) cdf = torch.cumsum(pdf, -1) cdf = torch.cat([torch.zeros_like(cdf[..., :1]), cdf], -1) # Take uniform samples if det: u = torch.linspace(0. + 0.5 / n_samples, 1. - 0.5 / n_samples, steps=n_samples) u = u.expand(list(cdf.shape[:-1]) + [n_samples]) else: u = torch.rand(list(cdf.shape[:-1]) + [n_samples]) # Invert CDF u = u.contiguous() inds = torch.searchsorted(cdf, u, right=True) below = torch.max(torch.zeros_like(inds - 1), inds - 1) above = torch.min((cdf.shape[-1] - 1) * torch.ones_like(inds), inds) inds_g = torch.stack([below, above], -1) # (batch, N_samples, 2) matched_shape = [inds_g.shape[0], inds_g.shape[1], cdf.shape[-1]] cdf_g = torch.gather(cdf.unsqueeze(1).expand(matched_shape), 2, inds_g) bins_g = torch.gather(bins.unsqueeze(1).expand(matched_shape), 2, inds_g) denom = (cdf_g[..., 1] - cdf_g[..., 0]) denom = torch.where(denom < 1e-5, torch.ones_like(denom), denom) t = (u - cdf_g[..., 0]) / denom samples = bins_g[..., 0] + t * (bins_g[..., 1] - bins_g[..., 0]) return samples class NeuSRenderer: def __init__(self, nerf, sdf_network, deviation_network, color_network, n_samples, n_importance, n_outside, up_sample_steps, perturb, disturb=0., disturb_end=100000, up_sample_mode='naive_appr', up_sample_appr_level=0, up_sample_s=64, up_sample_min=1e-2, render_mode='div', ): self.nerf = nerf self.sdf_network = sdf_network self.deviation_network = deviation_network self.color_network = color_network self.n_samples = n_samples self.n_importance = n_importance self.n_outside = n_outside self.up_sample_steps = up_sample_steps self.perturb = perturb self.disturb = disturb self.disturb_end = disturb_end self.up_sample_mode = up_sample_mode self.up_sample_appr_level = up_sample_appr_level self.up_sample_s = up_sample_s self.up_sample_min = up_sample_min self.render_mode = render_mode def render_core_outside(self, rays_o, rays_d, z_vals, sample_dist, nerf, background_rgb=None): """ Render background """ batch_size, n_samples = z_vals.shape # Section length dists = z_vals[..., 1:] - z_vals[..., :-1] dists = torch.cat([dists, torch.Tensor([sample_dist]).expand(dists[..., :1].shape)], -1) mid_z_vals = z_vals + dists * 0.5 # Section midpoints pts = rays_o[:, None, :] + rays_d[:, None, :] * mid_z_vals[..., :, None] # batch_size, n_samples, 3 dis_to_center = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=True).clip(1.0, 1e10) pts = torch.cat([pts / dis_to_center, 1.0 / dis_to_center], dim=-1) # batch_size, n_samples, 4 dirs = rays_d[:, None, :].expand(batch_size, n_samples, 3) pts = pts.reshape(-1, 3 + int(self.n_outside > 0)) dirs = dirs.reshape(-1, 3) density, sampled_color = nerf(pts, dirs) alpha = 1.0 - torch.exp(-F.softplus(density.reshape(batch_size, n_samples)) * dists) alpha = alpha.reshape(batch_size, n_samples) weights = alpha * torch.cumprod(torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] sampled_color = sampled_color.reshape(batch_size, n_samples, 3) color = (weights[:, :, None] * sampled_color).sum(dim=1) if background_rgb is not None: color = color + background_rgb * (1.0 - weights.sum(dim=-1, keepdim=True)) return { 'color': color, 'sampled_color': sampled_color, 'alpha': alpha, 'weights': weights, } def up_sample(self, rays_o, rays_d, z_vals, sdf, n_importance, i): """ Up sampling give a fixed inv_s """ inv_s = 64 * 2 ** i batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) # ---------------------------------------------------------------------------------------------------------- # Use min value of [ cos, prev_cos ] # Though it makes the sampling (not rendering) a little bit biased, this strategy can make the sampling more # robust when meeting situations like below: # # SDF # ^ # |\ -----x----... # | \ / # | x x # |---\----/-------------> 0 level # | \ / # | \/ # | # ---------------------------------------------------------------------------------------------------------- prev_cos_val = torch.cat([torch.zeros([batch_size, 1]), cos_val[:, :-1]], dim=-1) cos_val = torch.stack([prev_cos_val, cos_val], dim=-1) cos_val, _ = torch.min(cos_val, dim=-1, keepdim=False) cos_val = cos_val * inside_sphere dist = (next_z_vals - prev_z_vals) # prev_esti_sdf = mid_sdf - cos_val * dist * 0.5 # next_esti_sdf = mid_sdf + cos_val * dist * 0.5 # prev_cdf = torch.sigmoid(prev_esti_sdf * inv_s) # next_cdf = torch.sigmoid(next_esti_sdf * inv_s) prev_esti_sdf = (mid_sdf - cos_val * dist * 0.5).clip(0., 1e6) next_esti_sdf = (mid_sdf + cos_val * dist * 0.5).clip(0., 1e6) prev_cdf = prev_esti_sdf*inv_s/(1+prev_esti_sdf*inv_s) next_cdf = next_esti_sdf*inv_s/(1+next_esti_sdf*inv_s) alpha = ((torch.abs(prev_cdf - next_cdf) +0) / (torch.abs(prev_cdf) + 1e-20)).clip(0., 1.) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] # print(weights.min(), alpha.min(), alpha.max()) # if weights.min() < 0: # exit() z_samples = sample_pdf(z_vals, weights, n_importance, det=True).detach() return z_samples def cat_z_vals(self, rays_o, rays_d, z_vals, new_z_vals, sdf, last=False): # print(z_vals) # print(new_z_vals) batch_size, n_samples = z_vals.shape _, n_importance = new_z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * new_z_vals[..., :, None] z_vals = torch.cat([z_vals, new_z_vals], dim=-1) z_vals, index = torch.sort(z_vals, dim=-1) if not last: new_sdf = self.sdf_network.sdf(pts.reshape(-1, 3)).reshape(batch_size, n_importance) sdf = torch.cat([sdf, new_sdf], dim=-1) xx = torch.arange(batch_size)[:, None].expand(batch_size, n_samples + n_importance).reshape(-1) index = index.reshape(-1) sdf = sdf[(xx, index)].reshape(batch_size, n_samples + n_importance) return z_vals, sdf def render_core(self, near, far, rays_o, rays_d, z_vals, sample_dist, sdf_network, deviation_network, color_network, background_alpha=None, background_sampled_color=None, background_rgb=None, cos_anneal_ratio=0.0, weight_anneal_ratio=0.0,): batch_size, n_samples = z_vals.shape # Section length dists = z_vals[..., 1:] - z_vals[..., :-1] dists = torch.cat([dists, torch.Tensor([sample_dist]).expand(dists[..., :1].shape)], -1) mid_z_vals = z_vals + dists * 0.5 # Section midpoints pts = rays_o[:, None, :] + rays_d[:, None, :] * mid_z_vals[..., :, None] # n_rays, n_samples, 3 dirs = rays_d[:, None, :].expand(pts.shape) pts = pts.reshape(-1, 3) dirs = dirs.reshape(-1, 3) sdf_nn_output = sdf_network(pts) sdf = sdf_nn_output[:, :1] feature_vector = sdf_nn_output[:, 1:] #print('sdf max: {}'.format(torch.max(sdf))) #print('sdf min: {}'.format(torch.min(sdf))) if color_network.mode == 'second_order_udf': second_order_gradients, gradients = sdf_network.second_order_gradient(pts) second_order_gradients = second_order_gradients.squeeze() gradients = gradients.squeeze() else: second_order_gradients = None gradients = sdf_network.gradient(pts).squeeze() gradients_original = gradients if color_network.mode == 'normal_appr': sdf_bn = sdf.reshape(batch_size, n_samples) grad_bn = gradients.reshape(batch_size, n_samples, 3) grad_norm_bn = torch.linalg.norm(grad_bn, ord=2, dim=-1) is_sdf_small = (sdf_bn < 0.01) is_grad_small = (grad_norm_bn < 0.1) prev_grad_bn = grad_bn next_grad_bn = grad_bn prev_grad_sum = torch.zeros_like(grad_bn) next_grad_sum = torch.zeros_like(grad_bn) for _ in range(5): prev_grad_bn = torch.cat([prev_grad_bn[:, :1, :], prev_grad_bn[:, :-1, :]], dim=1) next_grad_bn = torch.cat([next_grad_bn[:, 1:, :], next_grad_bn[:, -1:, :]], dim=1) prev_grad_sum = prev_grad_sum + prev_grad_bn next_grad_sum = next_grad_sum + next_grad_bn grad_sum_delta = (prev_grad_sum * next_grad_sum).sum(-1) is_grad_singular = (grad_sum_delta < 0) is_normal_appr = (is_sdf_small & is_grad_small & is_grad_singular) # mid_z_vals_bn = mid_z_vals.reshape(batch_size, n_samples) # mid_z_vals_bn_delta = mid_z_vals_bn - 0.01 # pts_bn_delta = rays_o[:, None, :] + rays_d[:, None, :] * mid_z_vals_bn_delta[..., :, None] pts_bn = pts.reshape(batch_size, n_samples, 3) dirs_bn = F.normalize(prev_grad_bn, dim=-1).reshape(batch_size, n_samples, 3) pts_bn_delta = pts_bn + dirs_bn * 0.01 pts_appr = pts_bn_delta[is_normal_appr, :] grad_appr = sdf_network.gradient(pts_appr.reshape(-1, 3)).squeeze() grad_bn[is_normal_appr, :] = grad_appr gradients = grad_bn.reshape(-1, 3) # print(grad_appr.shape) sampled_color = color_network(pts, gradients, dirs, feature_vector, sdf, second_order_gradients).reshape(batch_size, n_samples, 3) # inv_s = deviation_network(torch.zeros([1, 3]))[:, :1].clip(1e-6, 1e6) # Single parameter inv_s = deviation_network(torch.zeros([1, 3]))[:, :1] inv_s = inv_s.expand(batch_size * n_samples, 1) # inv_s = inv_s.squeeze() # print(inv_s,inv_s.shape) true_cos = (dirs * gradients).sum(-1, keepdim=True) # "cos_anneal_ratio" grows from 0 to 1 in the beginning training iterations. The anneal strategy below makes # the cos value "not dead" at the beginning training iterations, for better convergence. true_cos_sign = torch.where(true_cos > 0, 1, -1) iter_cos = ((true_cos * 0.5 + 0.5 * true_cos_sign) * (1.0 - cos_anneal_ratio) + (true_cos) * cos_anneal_ratio) # not always non-positive # Estimate signed distances at section points estimated_next_sdf = (sdf + iter_cos * dists.reshape(-1, 1) * 0.5).clip(0., 1e6) estimated_prev_sdf = (sdf - iter_cos * dists.reshape(-1, 1) * 0.5).clip(0., 1e6) #print('estimated_next_sdf max: {}'.format(torch.max(estimated_next_sdf))) #print('estimated_next_sdf min: {}'.format(torch.min(estimated_next_sdf))) #print('estimated_prev_sdf max: {}'.format(torch.max(estimated_prev_sdf))) #print('estimated_prev_sdf min: {}'.format(torch.min(estimated_prev_sdf))) if self.render_mode == 'div' or 'div_anneal': prev_cdf = (estimated_prev_sdf * inv_s / (1+estimated_prev_sdf * inv_s)).clip(0., 1e6) next_cdf = (estimated_next_sdf * inv_s / (1+estimated_next_sdf * inv_s)).clip(0., 1e6) elif self.render_mode == 'exp': prev_cdf = (1 - torch.exp(-estimated_prev_sdf * inv_s)).clip(0., 1e6) next_cdf = (1 - torch.exp(-estimated_next_sdf * inv_s)).clip(0., 1e6) elif self.render_mode == 'atan': prev_cdf = (torch.atan(estimated_prev_sdf * inv_s) * 2 / np.pi).clip(0., 1e6) next_cdf = (torch.atan(estimated_next_sdf * inv_s) * 2 / np.pi).clip(0., 1e6) elif self.render_mode == 'neus': prev_cdf = torch.sigmoid(estimated_prev_sdf * inv_s) next_cdf = torch.sigmoid(estimated_next_sdf * inv_s) elif self.render_mode == 'neus_abs': prev_cdf = torch.abs(torch.sigmoid(estimated_prev_sdf * inv_s)) next_cdf = torch.abs(torch.sigmoid(estimated_next_sdf * inv_s)) elif self.render_mode == 'div_appr': prev_cdf = ((0.1+estimated_prev_sdf * inv_s) / (1+estimated_prev_sdf * inv_s)).clip(0., 1e6) next_cdf = ((0.1+estimated_next_sdf * inv_s) / (1+estimated_next_sdf * inv_s)).clip(0., 1e6) p = torch.abs(prev_cdf - next_cdf) c = torch.max(prev_cdf, next_cdf) alpha = ((p + 0) / (c + 1e-10)).reshape(batch_size, n_samples).clip(0.0, 1.0) pts_norm = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=True).reshape(batch_size, n_samples) inside_sphere = (pts_norm < 1.0).float().detach() relax_inside_sphere = (pts_norm < 1.2).float().detach() # Render with background if background_alpha is not None: alpha = alpha * inside_sphere + background_alpha[:, :n_samples] * (1.0 - inside_sphere) alpha = torch.cat([alpha, background_alpha[:, n_samples:]], dim=-1) sampled_color = sampled_color * inside_sphere[:, :, None] +\ background_sampled_color[:, :n_samples] * (1.0 - inside_sphere)[:, :, None] sampled_color = torch.cat([sampled_color, background_sampled_color[:, n_samples:]], dim=1) weights = alpha * torch.cumprod(torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] if self.render_mode == 'div_anneal': weights = (weights * 0.5 + 0.5 / n_samples) * (1. - weight_anneal_ratio) + weights * weight_anneal_ratio weights_sum = weights.sum(dim=-1, keepdim=True) color = (sampled_color * weights[:, :, None]).sum(dim=1) if background_rgb is not None: # Fixed background, usually black color = color + background_rgb * (1.0 - weights_sum) # Eikonal loss gradient_error = (torch.linalg.norm(gradients_original.reshape(batch_size, n_samples, 3), ord=2, dim=-1) - 1.0) ** 2 # gradient_error = gradient_error * dists * 64 / 2 gradient_error = (relax_inside_sphere * gradient_error).sum() / (relax_inside_sphere.sum() + 1e-5) # normal loss normals = gradients.reshape(batch_size, n_samples, 3) normals = normals / torch.linalg.norm(normals, ord=2, dim=-1, keepdim=True) prev_normals = torch.cat([normals[:, :1, :], normals[:, :-1, :]], dim=1) sin_p = torch.abs((normals-prev_normals)).sum(dim=-1) sin_n = torch.abs((normals+prev_normals)).sum(dim=-1) sin = torch.min(sin_p, sin_n) normal_error = torch.abs(sin) normal_error = (normal_error * relax_inside_sphere).sum() / (relax_inside_sphere.sum() + 1e-5) return { 'color': color, 'dists': dists, 'gradients': gradients.reshape(batch_size, n_samples, 3), 's_val': 1.0 / inv_s, 'mid_z_vals': mid_z_vals, 'weights': weights, 'cdf': c.reshape(batch_size, n_samples), 'gradient_error': gradient_error, 'inside_sphere': inside_sphere, 'normal_error': normal_error, } def render(self, rays_o, rays_d, near, far, perturb_overwrite=-1, background_rgb=None, cos_anneal_ratio=0.0, weight_anneal_ratio=0.0, up_sample=False): z_dist_sdf_gradient = 0 batch_size = len(rays_o) sample_dist = 2.0 / self.n_samples # Assuming the region of interest is a unit sphere z_vals = torch.linspace(0.0, 1.0, self.n_samples) z_vals = near + (far - near) * z_vals[None, :] z_vals_outside = None if self.n_outside > 0: z_vals_outside = torch.linspace(1e-3, 1.0 - 1.0 / (self.n_outside + 1.0), self.n_outside) n_samples = self.n_samples perturb = self.perturb if perturb_overwrite >= 0: perturb = perturb_overwrite if perturb > 0: t_rand = (torch.rand([batch_size, 1]) - 0.5) z_vals = z_vals + t_rand * 2.0 / self.n_samples if self.n_outside > 0: mids = .5 * (z_vals_outside[..., 1:] + z_vals_outside[..., :-1]) upper = torch.cat([mids, z_vals_outside[..., -1:]], -1) lower = torch.cat([z_vals_outside[..., :1], mids], -1) t_rand = torch.rand([batch_size, z_vals_outside.shape[-1]]) z_vals_outside = lower[None, :] + (upper - lower)[None, :] * t_rand if self.n_outside > 0: z_vals_outside = far / torch.flip(z_vals_outside, dims=[-1]) + 1.0 / self.n_samples background_alpha = None background_sampled_color = None # Up sample if up_sample and self.n_importance > 0: with torch.no_grad(): pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] sdf = self.sdf_network.sdf(pts.reshape(-1, 3)).reshape(batch_size, self.n_samples) if self.up_sample_mode == 'surface': max_r = 0.1 min_r = 0.005 beta = 1.5e-5 interval_radius = np.max([max_r * np.exp(-self.iter_step * beta), min_r]) new_z_vals, new_z_vals_inv = self.up_sample_surface(rays_o, rays_d, z_vals, sdf, self.n_importance//2, interval_radius) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=True) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals_inv, sdf, last=True) elif self.up_sample_mode == 'naive': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_naive(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'neus': for i in range(self.up_sample_steps): new_z_vals = self.up_sample(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'udf': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_udf(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'neus_appr': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_neus_appr(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'naive_appr': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_naive_appr(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'fake_f': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_fake_f(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'uniform': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_uniform(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) n_samples = self.n_samples + self.n_importance # Background model if self.n_outside > 0: z_vals_feed = torch.cat([z_vals, z_vals_outside], dim=-1) z_vals_feed, _ = torch.sort(z_vals_feed, dim=-1) ret_outside = self.render_core_outside(rays_o, rays_d, z_vals_feed, sample_dist, self.nerf) background_sampled_color = ret_outside['sampled_color'] background_alpha = ret_outside['alpha'] # Render core ret_fine = self.render_core(near, far, rays_o, rays_d, z_vals, sample_dist, self.sdf_network, self.deviation_network, self.color_network, background_rgb=background_rgb, background_alpha=background_alpha, background_sampled_color=background_sampled_color, cos_anneal_ratio=cos_anneal_ratio, weight_anneal_ratio=weight_anneal_ratio,) color_fine = ret_fine['color'] weights = ret_fine['weights'] weights_sum = weights.sum(dim=-1, keepdim=True) gradients = ret_fine['gradients'] s_val = ret_fine['s_val'].reshape(batch_size, n_samples).mean(dim=-1, keepdim=True) return { 'color_fine': color_fine, 's_val': s_val, 'cdf_fine': ret_fine['cdf'], 'weight_sum': weights_sum, 'weight_max': torch.max(weights, dim=-1, keepdim=True)[0], 'gradients': gradients, 'weights': weights, 'gradient_error': ret_fine['gradient_error'], 'inside_sphere': ret_fine['inside_sphere'], 'normal_error': ret_fine['normal_error'], } def extract_geometry(self, bound_min, bound_max, resolution, threshold=0.0): return extract_geometry(bound_min, bound_max, resolution=resolution, threshold=threshold, query_func=lambda pts: self.sdf_network.sdf(pts)) def generate_point_cloud(self, device, num_steps = 10, num_points = 900000, filter_val = 0.009, threshold=0.1): start = time.time() for param in self.sdf_network.parameters(): param.requires_grad = False sample_num = 200000 samples_cpu = np.zeros((0, 3)) samples = torch.rand(1, sample_num, 3).float().to(device) * 2 - 1 samples.requires_grad = True #encoding = self.model.encoder(inputs) i = 0 while len(samples_cpu) < num_points: print('iteration', i) for j in range(num_steps): print('refinement', j) df_pred = torch.clamp(self.sdf_network.sdf(samples.squeeze(0)), max=threshold).unsqueeze(0) df_pred.sum().backward() gradient = samples.grad.detach() samples = samples.detach() df_pred = df_pred.detach() #inputs = inputs.detach() samples = samples - F.normalize(gradient, dim=2) * df_pred.reshape(-1, 1) # better use Tensor.copy method? samples = samples.detach() samples.requires_grad = True print('finished refinement') if not i == 0: samples_cpu = np.vstack((samples_cpu, samples[df_pred.squeeze(-1) < filter_val].detach().cpu().numpy())) samples = samples[df_pred.squeeze(-1) < 0.03].unsqueeze(0) indices = torch.randint(samples.shape[1], (1, sample_num)) samples = samples[[[0, ] * sample_num], indices] samples += (threshold / 3) * torch.randn(samples.shape).to(device) # 3 sigma rule samples = samples.detach() samples.requires_grad = True i += 1 print(samples_cpu.shape) duration = time.time() - start return samples_cpu, duration def up_sample_uniformity(self, rays_o, rays_d, z_vals, sdf, n_importance): batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :] < 1.0) sdf = sdf.reshape(batch_size, n_samples) new_z_vals = torch.linspace(0. + 0.5 / n_importance, 1. - 0.5 / n_importance, steps=n_importance) new_z_vals = new_z_vals.expand([batch_size, n_importance]) _, bins_index = torch.min(torch.max(sdf,100*(1-1*inside_sphere)), dim=-1) prev_z_val = z_vals[torch.arange(0, batch_size), (bins_index-1).clip(0, n_samples)] next_z_val = z_vals[torch.arange(0, batch_size), (bins_index+1).clip(0, n_samples)] new_z_vals = torch.ones_like(new_z_vals)*prev_z_val[:,None]+new_z_vals*(next_z_val-prev_z_val)[:,None] return new_z_vals.detach() def up_sample_surface(self, rays_o, rays_d, z_vals, sdf, n_importance, interval_radius): batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) prev_cos_val = torch.cat([torch.zeros([batch_size, 1]), cos_val[:, :-1]], dim=-1) cos_val = torch.stack([prev_cos_val, cos_val], dim=-1) cos_val, _ = torch.min(cos_val, dim=-1, keepdim=False) cos_val = cos_val * inside_sphere dist = (next_z_vals - prev_z_vals) inv_s = self.deviation_network(torch.zeros([1, 3]))[:, :1].detach() prev_esti_sdf = (mid_sdf - cos_val * dist * 0.5).clip(0., 1e6) next_esti_sdf = (mid_sdf + cos_val * dist * 0.5).clip(0., 1e6) prev_cdf = prev_esti_sdf * inv_s / (1 + prev_esti_sdf * inv_s) next_cdf = next_esti_sdf * inv_s / (1 + next_esti_sdf * inv_s) alpha = ((torch.abs(prev_cdf - next_cdf) + 0) / (torch.abs(prev_cdf) + 1e-20)).clip(0., 1.) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] _, min_weight_idx = torch.max(weights, dim=-1) prev_z_val = z_vals[torch.arange(0, batch_size), (min_weight_idx - 1).clip(0, n_samples - 1)] next_z_val = z_vals[torch.arange(0, batch_size), (min_weight_idx + 1).clip(0, n_samples - 1)] new_z_vals = torch.linspace(0. + 0.5 / n_importance, 1. - 0.5 / n_importance, steps=n_importance) new_z_vals = new_z_vals.expand([batch_size, n_importance]) new_z_vals = torch.ones_like(new_z_vals) * prev_z_val[:, None] + new_z_vals * (next_z_val - prev_z_val)[:, None] new_pts = rays_o[:, None, :] + rays_d[:, None, :] * new_z_vals[..., :, None] new_sdf = self.sdf_network.sdf(new_pts.reshape(-1, 3)).reshape(batch_size, n_importance) _, min_sdf_idx = torch.min(new_sdf, dim=-1) min_sdf_z = new_z_vals[torch.arange(0, batch_size), min_sdf_idx] sample_distribution = torch.abs(torch.randn(batch_size, n_importance)) * interval_radius sample_z_vals = sample_distribution + min_sdf_z[:, None] sample_z_vals_inv = -sample_distribution + min_sdf_z[:, None] new_pts_norm = torch.linalg.norm(new_pts.reshape(-1, 3), ord=2, dim=-1, keepdim=True).reshape(batch_size, -1) new_pts_inside_sphere = (new_pts_norm < 1.2).float() min_sdf_inside_sphere = new_pts_inside_sphere[torch.arange(0, batch_size), min_sdf_idx] uniform_sample_distribution = torch.linspace(0.+1./n_importance, 1.-1./n_importance, n_importance*2) uniform_sample_z_vals = z_vals[:, :1] + uniform_sample_distribution[None, :] * (z_vals[:, -1:]-z_vals[:, :1]) uniform_sample_z_vals_inv = uniform_sample_z_vals[:, :n_importance] uniform_sample_z_vals = uniform_sample_z_vals[:, n_importance:] sample_z_vals = min_sdf_inside_sphere[:, None] * sample_z_vals + (1-min_sdf_inside_sphere)[:, None] * uniform_sample_z_vals sample_z_vals_inv = min_sdf_inside_sphere[:, None] * sample_z_vals_inv + (1-min_sdf_inside_sphere)[:, None] * uniform_sample_z_vals_inv return sample_z_vals.detach(), sample_z_vals_inv.detach() def up_sample_udf(self, rays_o, rays_d, z_vals, sdf, n_importance, i): """ Up sampling give a fixed inv_s """ batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) mid_sdf = sdf[:, 1:]+sdf[:, :-1] inv_s = 64 * 2 ** i sigma = 1 / (1 + torch.exp(-mid_sdf * inv_s)) rho = sigma * (1 - sigma) * inv_s weights = rho z_samples = sample_pdf(z_vals, weights, n_importance, det=True).detach() return z_samples def up_sample_naive(self, rays_o, rays_d, z_vals, sdf, n_importance, i): """ Up sampling give a fixed inv_s """ with torch.enable_grad(): batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) inv_s = 64 * 2 ** i sigma = 1/(1+torch.exp(-mid_sdf * inv_s)) rho = sigma * (1 - sigma) * inv_s alpha = 1 - torch.exp(-rho * (next_z_vals - prev_z_vals)) # print('alpha',alpha[0]) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] z_samples = sample_pdf(z_vals, weights, n_importance, det=True).detach() return z_samples def up_sample_naive_appr(self, rays_o, rays_d, z_vals, sdf, n_importance, i): """ Up sampling give a fixed inv_s """ batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) inv_s = self.up_sample_s * 2 ** i sigma = 1 / (1 + torch.exp(-mid_sdf * inv_s)) rho = sigma * (1 - sigma) * inv_s alpha = 1 - torch.exp(-rho * (next_z_vals - prev_z_vals)) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] for _ in range(self.up_sample_appr_level): weights_prev = torch.cat([weights[:, :1], weights[:, :-1]], dim=-1) weights_next = torch.cat([weights[:, 1:], weights[:, -1:]], dim=-1) weights = torch.max(weights, weights_prev) weights = torch.max(weights, weights_next) z_samples = sample_pdf(z_vals, weights, n_importance, det=True).detach() return z_samples def up_sample_neus_appr(self, rays_o, rays_d, z_vals, sdf, n_importance, i): inv_s = 64 * 2 ** i batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) prev_cos_val = torch.cat([torch.zeros([batch_size, 1]), cos_val[:, :-1]], dim=-1) cos_val = torch.stack([prev_cos_val, cos_val], dim=-1) cos_val, _ = torch.min(cos_val, dim=-1, keepdim=False) cos_val = cos_val * inside_sphere dist = (next_z_vals - prev_z_vals) prev_esti_sdf = (mid_sdf - cos_val * dist * 0.5).clip(0., 1e6) next_esti_sdf = (mid_sdf + cos_val * dist * 0.5).clip(0., 1e6) prev_cdf = prev_esti_sdf * inv_s / (1 + prev_esti_sdf * inv_s) next_cdf = next_esti_sdf * inv_s / (1 + next_esti_sdf * inv_s) alpha = ((torch.abs(prev_cdf - next_cdf) + 0) / (torch.abs(prev_cdf) + 1e-20)).clip(0., 1.) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] for _ in range(3): weights_prev = torch.cat([weights[:, :1], weights[:, :-1]], dim=-1) weights_next = torch.cat([weights[:, 1:], weights[:, -1:]], dim=-1) weights = torch.max(weights, weights_prev) weights = torch.max(weights, weights_next) z_samples = sample_pdf(z_vals, weights, n_importance, det=True).detach() return z_samples def up_sample_fake_f(self, rays_o, rays_d, z_vals, sdf, n_importance, i): """ Up sampling give a fixed inv_s """ inv_s = self.up_sample_s * 2 ** i batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) is_cos_inverse = torch.where(cos_val < 0, 1, -1) is_sdf_big = torch.where(sdf > 1e-2, 1, -1) is_fake_sdf = torch.max(torch.cat([torch.ones_like(is_cos_inverse[:, :1]), is_cos_inverse], dim=-1), is_sdf_big) fake_sdf = sdf * is_fake_sdf fake_cos_val = cos_val * is_cos_inverse fake_mid_sdf = (fake_sdf[:, 1:] + fake_sdf[:, :-1])/2 dist = next_z_vals - prev_z_vals fake_prev_esti_sdf = fake_mid_sdf - fake_cos_val * dist * 0.5 fake_next_esti_sdf = fake_mid_sdf + fake_cos_val * dist * 0.5 fake_prev_cdf = torch.sigmoid(fake_prev_esti_sdf * inv_s) fake_next_cdf = torch.sigmoid(fake_next_esti_sdf * inv_s) alpha = ((torch.abs(fake_prev_cdf - fake_next_cdf) + 1e-10) / (torch.abs(fake_prev_cdf) + 1e-10)).clip(0., 1.) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] z_samples = sample_pdf(z_vals, weights, n_importance, det=True).detach() return z_samples def up_sample_uniform(self, rays_o, rays_d, z_vals, sdf, n_importance, i): inv_s = 64 * 2 ** i batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) cos_val = cos_val * inside_sphere dist = (next_z_vals - prev_z_vals) prev_esti_sdf = (mid_sdf - cos_val * dist * 0.5).clip(0., 1e6) next_esti_sdf = (mid_sdf + cos_val * dist * 0.5).clip(0., 1e6) prev_cdf = prev_esti_sdf * inv_s / (1 + prev_esti_sdf * inv_s) next_cdf = next_esti_sdf * inv_s / (1 + next_esti_sdf * inv_s) alpha = ((torch.abs(prev_cdf - next_cdf) + 0) / (torch.abs(prev_cdf) + 1e-20)).clip(0., 1.) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] weights = weights / (next_z_vals - prev_z_vals + 1e-5) for _ in range(self.up_sample_appr_level): weights_prev = torch.cat([weights[:, :1], weights[:, :-1]], dim=-1) weights_next = torch.cat([weights[:, 1:], weights[:, -1:]], dim=-1) weights = torch.max(weights, weights_prev) weights = torch.max(weights, weights_next) weights = weights * inside_sphere use_rand_us = ((weights.sum(dim=-1)) < 0.2).float() weights = weights / (mid_sdf + 1e-5) _, bin_idx = torch.max(weights, dim=-1) prev_z_val = z_vals[torch.arange(0, batch_size), (bin_idx - self.up_sample_appr_level).clip(0, n_samples-2)] next_z_val = z_vals[torch.arange(0, batch_size), (bin_idx + self.up_sample_appr_level + 1).clip(0, n_samples-2)] cos_val_mean = torch.abs(cos_val).sum(dim=-1)/(inside_sphere.sum(dim=-1)+1e-5) delta_z_val = (next_z_val - prev_z_val) / (cos_val_mean + 1e-5) delta_z_val = (delta_z_val - (next_z_val - prev_z_val)) / 2 prev_z_val = prev_z_val - delta_z_val next_z_val = next_z_val + delta_z_val new_z_vals = torch.linspace(0. + 0.5 / n_importance, 1. - 0.5 / n_importance, steps=n_importance) new_z_vals = new_z_vals.expand([batch_size, n_importance]) new_z_vals = torch.ones_like(new_z_vals) * prev_z_val[:, None] + new_z_vals * (next_z_val - prev_z_val)[:, None] begin_z_vals = z_vals[:, 0] end_z_vals = z_vals[:, -1] rand_z_vals = torch.rand(batch_size, n_importance) rand_z_vals = torch.ones_like(rand_z_vals) * begin_z_vals[:, None] + rand_z_vals * (end_z_vals - begin_z_vals)[:, None] new_z_vals = rand_z_vals * use_rand_us[:, None] + new_z_vals * (1 - use_rand_us[:, None]) return new_z_vals.detach() def generate_ray(self, rays_o, rays_d, near, far, perturb_overwrite=-1, background_rgb=None, cos_anneal_ratio=0.0): batch_size = len(rays_o) sample_dist = 2.0 / self.n_samples # Assuming the region of interest is a unit sphere z_vals = torch.linspace(0.0, 1.0, self.n_samples) z_vals = near + (far - near) * z_vals[None, :] z_vals_outside = None if self.n_outside > 0: z_vals_outside = torch.linspace(1e-3, 1.0 - 1.0 / (self.n_outside + 1.0), self.n_outside) n_samples = self.n_samples perturb = self.perturb if perturb_overwrite >= 0: perturb = perturb_overwrite if perturb > 0: t_rand = (torch.rand([batch_size, 1]) - 0.5) z_vals = z_vals + t_rand * 2.0 / self.n_samples if self.n_outside > 0: mids = .5 * (z_vals_outside[..., 1:] + z_vals_outside[..., :-1]) upper = torch.cat([mids, z_vals_outside[..., -1:]], -1) lower = torch.cat([z_vals_outside[..., :1], mids], -1) t_rand = torch.rand([batch_size, z_vals_outside.shape[-1]]) z_vals_outside = lower[None, :] + (upper - lower)[None, :] * t_rand pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] sdf = self.sdf_network.sdf(pts.reshape(-1, 3)).reshape(batch_size, self.n_samples) # Up sample if self.n_importance > 0: with torch.no_grad(): if self.up_sample_mode == 'surface': max_r = 0.1 min_r = 0.005 beta = 1.5e-5 interval_radius = np.max([max_r * np.exp(-self.iter_step * beta), min_r]) new_z_vals, new_z_vals_inv = self.up_sample_surface(rays_o, rays_d, z_vals, sdf, self.n_importance // 2, interval_radius) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=True) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals_inv, sdf, last=True) elif self.up_sample_mode == 'naive': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_naive(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'neus': for i in range(self.up_sample_steps): new_z_vals = self.up_sample(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'udf': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_udf(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'neus_appr': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_neus_appr(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) elif self.up_sample_mode == 'naive_appr': for i in range(self.up_sample_steps): new_z_vals = self.up_sample_naive_appr(rays_o, rays_d, z_vals, sdf, self.n_importance // self.up_sample_steps, i) z_vals, sdf = self.cat_z_vals(rays_o, rays_d, z_vals, new_z_vals, sdf, last=False) batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) prev_cos_val = torch.cat([torch.zeros([batch_size, 1]), cos_val[:, :-1]], dim=-1) cos_val = torch.stack([prev_cos_val, cos_val], dim=-1) cos_val, _ = torch.min(cos_val, dim=-1, keepdim=False) # cos_val = cos_val.clip(-1e3, 0.0) * inside_sphere cos_val = cos_val * inside_sphere dist = (next_z_vals - prev_z_vals) prev_esti_sdf = (mid_sdf - cos_val * dist * 0.5).clip(0., 1e6) next_esti_sdf = (mid_sdf + cos_val * dist * 0.5).clip(0., 1e6) inv_s = 64 * 2 ** (self.up_sample_steps - 1) prev_cdf = (prev_esti_sdf * inv_s / (1 + prev_esti_sdf * inv_s)).clip(0., 1e6) next_cdf = (next_esti_sdf * inv_s / (1 + next_esti_sdf * inv_s)).clip(0., 1e6) alpha = ((torch.abs(prev_cdf - next_cdf) + 1e-5) / (prev_cdf + 1e-5)).clip(0., 1.) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] return z_vals.detach().cpu().numpy().flatten(), \ sdf.detach().cpu().numpy().flatten(), \ weights.detach().cpu().numpy().flatten() def sample_symmetry(self, rays_o, rays_d, z_vals, sdf, n_importance, interval_radius): batch_size, n_samples = z_vals.shape pts = rays_o[:, None, :] + rays_d[:, None, :] * z_vals[..., :, None] # n_rays, n_samples, 3 radius = torch.linalg.norm(pts, ord=2, dim=-1, keepdim=False) inside_sphere = (radius[:, :-1] < 1.0) | (radius[:, 1:] < 1.0) sdf = sdf.reshape(batch_size, n_samples) prev_sdf, next_sdf = sdf[:, :-1], sdf[:, 1:] prev_z_vals, next_z_vals = z_vals[:, :-1], z_vals[:, 1:] mid_sdf = (prev_sdf + next_sdf) * 0.5 cos_val = (next_sdf - prev_sdf) / (next_z_vals - prev_z_vals + 1e-5) prev_cos_val = torch.cat([torch.zeros([batch_size, 1]), cos_val[:, :-1]], dim=-1) cos_val = torch.stack([prev_cos_val, cos_val], dim=-1) cos_val, _ = torch.min(cos_val, dim=-1, keepdim=False) cos_val = cos_val * inside_sphere dist = (next_z_vals - prev_z_vals) inv_s = inv_s = self.deviation_network(torch.zeros([1, 3]))[:, :1].detach() prev_esti_sdf = (mid_sdf - cos_val * dist * 0.5).clip(0., 1e6) next_esti_sdf = (mid_sdf + cos_val * dist * 0.5).clip(0., 1e6) prev_cdf = prev_esti_sdf * inv_s / (1 + prev_esti_sdf * inv_s) next_cdf = next_esti_sdf * inv_s / (1 + next_esti_sdf * inv_s) alpha = ((torch.abs(prev_cdf - next_cdf) + 0) / (torch.abs(prev_cdf) + 1e-20)).clip(0., 1.) weights = alpha * torch.cumprod( torch.cat([torch.ones([batch_size, 1]), 1. - alpha + 1e-7], -1), -1)[:, :-1] _, min_weight_idx = torch.max(weights, dim=-1) prev_z_val = z_vals[torch.arange(0, batch_size), (min_weight_idx - 1).clip(0, n_samples - 1)] next_z_val = z_vals[torch.arange(0, batch_size), (min_weight_idx + 1).clip(0, n_samples - 1)] new_z_vals = torch.linspace(0. + 0.5 / n_importance, 1. - 0.5 / n_importance, steps=n_importance) new_z_vals = new_z_vals.expand([batch_size, n_importance]) new_z_vals = torch.ones_like(new_z_vals) * prev_z_val[:, None] + new_z_vals * (next_z_val - prev_z_val)[:, None] new_pts = rays_o[:, None, :] + rays_d[:, None, :] * new_z_vals[..., :, None] new_sdf = self.sdf_network.sdf(new_pts.reshape(-1, 3)).reshape(batch_size, n_importance) _, min_sdf_idx = torch.min(new_sdf, dim=-1) min_sdf_z = new_z_vals[torch.arange(0, batch_size), min_sdf_idx] # sample_distribution = torch.randn(batch_size, n_importance) * interval_radius sample_distribution = torch.linspace(0. + 0.5 / n_importance, 1. - 0.5 / n_importance, steps=n_importance) sample_distribution = (sample_distribution * interval_radius).expand([batch_size, n_importance]) sample_z_vals = sample_distribution + min_sdf_z[:, None] sample_z_vals_inv = -sample_distribution + min_sdf_z[:, None] return sample_z_vals.detach(), sample_z_vals_inv.detach() def approximate_normal(self, pts, dirs, max_delta_z=0.01, min_delta_z=0.001): delta_z = 0 steps = int(max_delta_z/min_delta_z) is_appr = torch.zeros_like(pts[:, 0]) grad_all = torch.zeros_like(pts) is_to_appr = torch.ones_like(pts[:, 0]).bool() pts_to_appr = pts dirs_to_appr = dirs for i in range(steps): delta_z = min_delta_z rand_theta = torch.rand(4) * np.pi * 2 rand_phi = torch.rand(4) * np.pi rand_pts = torch.zeros(4, 3) rand_pts[:, 0] = torch.cos(rand_phi) * torch.cos(rand_theta) rand_pts[:, 1] = torch.cos(rand_phi) * torch.sin(rand_theta) rand_pts[:, 2] = torch.sin(rand_phi) rand_pts_norm = torch.mm(dirs_to_appr, rand_pts.transpose(0, 1)) rand_pts = rand_pts[None, ...] - rand_pts_norm[..., None] * dirs_to_appr[:, None, :] rand_pts = rand_pts * delta_z / 10 rand_pts = torch.cat([rand_pts, torch.zeros_like(rand_pts[:, :1, :])], dim=1) rand_pts = rand_pts + pts_to_appr[:, None, :] + dirs_to_appr[:, None, :] * delta_z rand_pts_grad = self.sdf_network.gradient(rand_pts.reshape(-1, 3)).reshape(-1, 5, 3) grad_mean = rand_pts_grad.mean(dim=1) grad_norm = torch.linalg.norm(grad_mean, dim=-1) grad_var = rand_pts_grad.var(dim=1).sum(-1) if i == steps - 1: grad_all[is_to_appr, :] = grad_mean else: is_norm_reliable = (grad_norm > 0.5) & (grad_var < 0.1) grad_all[is_to_appr, :][is_norm_reliable, :] = grad_mean[is_norm_reliable, :] is_appr[is_to_appr][is_norm_reliable] = 1. is_to_appr = (is_appr < 1) pts_to_appr = pts[is_to_appr, :] dirs_to_appr = dirs[is_to_appr, :] return grad_all ================================================ FILE: preprocess_custom_data/aruco_preprocess/CMakeLists.txt ================================================ project(PieceSeg) cmake_minimum_required(VERSION 3.0) set(CMAKE_CXX_STANDARD 14) set(CMAKE_BUILD_TYPE Release) find_package(OpenCV REQUIRED) include_directories(${OpenCV_INCLUDE_DIRS}) add_executable(calibration calibration.cpp) target_link_libraries(calibration ${OpenCV_LIBS} cnpy) ================================================ FILE: preprocess_custom_data/aruco_preprocess/calibration.cpp ================================================ #include #include #include #include #include #include #include #include void Calibrate(std::string work_dir, int n_images, double raw_scale) { std::vector> obj_points; std::vector board_ids; int n_rows = 20; int n_cols = 20; double scale = (n_cols * 8 - 1) / double(std::sqrt(2) * raw_scale); // Define the coordinates of markers in the board. for (int x = 0; x < n_rows; x++) { for (int y = 0; y < n_cols; y++) { int a = (x - n_rows / 2) * 8; int b = (y - n_cols / 2) * 8; obj_points.emplace_back(); board_ids.emplace_back(x * n_cols + y); auto& current_vec = obj_points.back(); current_vec.emplace_back(a / scale, b / scale, 0); current_vec.emplace_back((a + 7) / scale, b / scale, 0); current_vec.emplace_back((a + 7) / scale, (b + 7) / scale, 0); current_vec.emplace_back(a / scale, (b + 7) / scale, 0); } } // Create ArUco board cv::Ptr parameters = cv::aruco::DetectorParameters::create(); cv::Ptr dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_5X5_1000); cv::Ptr board = cv::aruco::Board::create(obj_points, dictionary, board_ids); std::vector> all_corners_cated; std::vector all_ids_cated; std::vector marker_count_per_frame; cv::Size img_size; for (int i = 0; i < n_images; i++) { std::string idx = std::to_string(i); while (idx.length() < 3) { idx = "0" + idx; } cv::Mat img = cv::imread(work_dir + "/images/" + idx + ".png"); int height = img.rows; int width = img.cols; uint8_t* data = img.data; for (int k = 0; k < height * width * 3; k += 3) { uint8_t color = 255 - data[k + 1]; data[k] = data[k + 1] = data[k + 2] = color; } cv::imwrite(work_dir + "/tmp/image_for_aruco/" + idx + ".png", img); img_size = img.size(); std::vector marker_ids; std::vector> marker_corners, rejected_candidates; cv::aruco::detectMarkers(img, dictionary, marker_corners, marker_ids, parameters, rejected_candidates); std::cout << marker_corners.size() << " " << marker_ids.size() << std::endl; for (auto& corner : marker_corners) { all_corners_cated.emplace_back(corner); } for (auto& id : marker_ids) { all_ids_cated.emplace_back(id); } marker_count_per_frame.emplace_back(marker_ids.size()); } cv::Mat cameraMatrix, distCoeffs; std::vector rvecs, tvecs; double repError = cv::aruco::calibrateCameraAruco(all_corners_cated, all_ids_cated, marker_count_per_frame, board, img_size, cameraMatrix, distCoeffs, rvecs, tvecs); std::vector poses(n_images * 6); std::vector intrinsic(9); for (int i = 0; i < n_images; i++) { for (int j = 0; j < 3; j++) { poses[i * 6 + j] = rvecs[i].at(j, 0); poses[i * 6 + j + 3] = tvecs[i].at(j, 0); } } for (int i = 0; i < 9; i++) { intrinsic[i] = cameraMatrix.at(i / 3, i % 3); } cnpy::npy_save(work_dir + "/tmp/poses.npy", poses.data(), { (unsigned int) n_images, 2, 3 }, "w"); cnpy::npy_save(work_dir + "/tmp/intrinsic.npy", intrinsic.data(), { 3, 3 }, "w"); std::cout << "r_vecs: " << rvecs.size() << std::endl; std::cout << cameraMatrix << std::endl; std::cout << distCoeffs << std::endl; for (int i = 0; i < n_images; i++) { std::string idx = std::to_string(i); while (idx.length() < 3) { idx = "0" + idx; } cv::Mat img = cv::imread(work_dir + "/images/" + idx + ".png"); cv::Mat new_img; cv::Mat new_mat; cv::undistort(img, new_img, cameraMatrix, distCoeffs, new_mat); cv::imwrite(work_dir + "/tmp/image_undistort/" + idx + ".png", new_img); } } int main(int argc, char* argv[]) { Calibrate(std::string(argv[1]), std::stoi(argv[2]), std::stod(argv[3])); } ================================================ FILE: preprocess_custom_data/aruco_preprocess/gen_cameras.py ================================================ import numpy as np import os import sys import cv2 as cv from glob import glob from scipy.spatial.transform import Rotation as Rot from shutil import copytree import trimesh def convert_cameras(work_dir, crop_pixels): # load cameras poses = np.load(os.path.join(work_dir, './tmp/poses.npy')) intrinsic_raw = np.load(os.path.join(work_dir, './tmp/intrinsic.npy')) n_images = len(poses) intrinsic = np.diag([1.0, 1.0, 1.0, 1.0]).astype(np.float32) intrinsic[:3, :3] = intrinsic_raw intrinsic[0, 2] = intrinsic[0, 2] - crop_pixels intrinsic[1, 2] = intrinsic[1, 2] - crop_pixels cam_dict = {} for i in range(n_images): pe = poses[i] rot = np.zeros([3, 3]) cv.Rodrigues(pe[0], rot) trans = pe[1] pose = np.diag([1.0, 1.0, 1.0, 1.0]) pose[:3, :3] = rot pose[:3, 3] = trans # w2c world_mat = intrinsic @ pose world_mat = world_mat.astype(np.float32) cam_dict['camera_mat_{}'.format(i)] = intrinsic cam_dict['camera_mat_inv_{}'.format(i)] = np.linalg.inv(intrinsic) cam_dict['world_mat_{}'.format(i)] = world_mat cam_dict['world_mat_inv_{}'.format(i)] = np.linalg.inv(world_mat) scale_mat = np.diag([1.0, 1.0, 1.0, 1.0]).astype(np.float32) for i in range(n_images): cam_dict['scale_mat_{}'.format(i)] = scale_mat cam_dict['scale_mat_inv_{}'.format(i)] = np.linalg.inv(scale_mat) out_dir = os.path.join(work_dir, 'preprocessed') os.makedirs(out_dir, exist_ok=True) np.savez(os.path.join(out_dir, 'cameras_sphere.npz'), **cam_dict) # provide images image_list = glob(os.path.join(work_dir, './tmp/image_undistort/*.png')) image_list.sort() os.makedirs(os.path.join(out_dir, 'image'), exist_ok=True) os.makedirs(os.path.join(out_dir, 'mask'), exist_ok=True) for i, image_path in enumerate(image_list): img = cv.imread(image_path) img = img[crop_pixels: -crop_pixels, crop_pixels: -crop_pixels] # remove black area of undistorted images cv.imwrite(os.path.join(out_dir, 'image', '{:0>3d}.png'.format(i)), img) cv.imwrite(os.path.join(out_dir, 'mask', '{:0>3d}.png'.format(i)), np.ones_like(img) * 255) if __name__ == '__main__': convert_cameras(sys.argv[1], int(sys.argv[2])) ================================================ FILE: preprocess_custom_data/aruco_preprocess/run.sh ================================================ calib_bin=./build/calibration work_dir=../example/thin_rope n_images=32 # Define the region of interest (ROI). # We assume the center of the ROI is the center of the calibration board. # The lower the value, the larger the ROI is. When the value is 1, the ROI is a sphere that exactly bound the calibration board. board_scale=0.9 # Crop the pixels (to remove the black region) after undistortion. crop_pixels=10 mkdir ${work_dir}/tmp mkdir ${work_dir}/tmp/image_undistort mkdir ${work_dir}/tmp/image_for_aruco ${calib_bin} ${work_dir} ${n_images} ${board_scale} python gen_cameras.py ${work_dir} ${crop_pixels} ================================================ FILE: preprocess_custom_data/colmap_preprocess/colmap_read_model.py ================================================ # Copyright (c) 2018, ETH Zurich and UNC Chapel Hill. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # # * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of # its contributors may be used to endorse or promote products derived # from this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF # SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. # # Author: Johannes L. Schoenberger (jsch at inf.ethz.ch) import os import sys import collections import numpy as np import struct CameraModel = collections.namedtuple( "CameraModel", ["model_id", "model_name", "num_params"]) Camera = collections.namedtuple( "Camera", ["id", "model", "width", "height", "params"]) BaseImage = collections.namedtuple( "Image", ["id", "qvec", "tvec", "camera_id", "name", "xys", "point3D_ids"]) Point3D = collections.namedtuple( "Point3D", ["id", "xyz", "rgb", "error", "image_ids", "point2D_idxs"]) class Image(BaseImage): def qvec2rotmat(self): return qvec2rotmat(self.qvec) CAMERA_MODELS = { CameraModel(model_id=0, model_name="SIMPLE_PINHOLE", num_params=3), CameraModel(model_id=1, model_name="PINHOLE", num_params=4), CameraModel(model_id=2, model_name="SIMPLE_RADIAL", num_params=4), CameraModel(model_id=3, model_name="RADIAL", num_params=5), CameraModel(model_id=4, model_name="OPENCV", num_params=8), CameraModel(model_id=5, model_name="OPENCV_FISHEYE", num_params=8), CameraModel(model_id=6, model_name="FULL_OPENCV", num_params=12), CameraModel(model_id=7, model_name="FOV", num_params=5), CameraModel(model_id=8, model_name="SIMPLE_RADIAL_FISHEYE", num_params=4), CameraModel(model_id=9, model_name="RADIAL_FISHEYE", num_params=5), CameraModel(model_id=10, model_name="THIN_PRISM_FISHEYE", num_params=12) } CAMERA_MODEL_IDS = dict([(camera_model.model_id, camera_model) \ for camera_model in CAMERA_MODELS]) def read_next_bytes(fid, num_bytes, format_char_sequence, endian_character="<"): """Read and unpack the next bytes from a binary file. :param fid: :param num_bytes: Sum of combination of {2, 4, 8}, e.g. 2, 6, 16, 30, etc. :param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}. :param endian_character: Any of {@, =, <, >, !} :return: Tuple of read and unpacked values. """ data = fid.read(num_bytes) return struct.unpack(endian_character + format_char_sequence, data) def read_cameras_text(path): """ see: src/base/reconstruction.cc void Reconstruction::WriteCamerasText(const std::string& path) void Reconstruction::ReadCamerasText(const std::string& path) """ cameras = {} with open(path, "r") as fid: while True: line = fid.readline() if not line: break line = line.strip() if len(line) > 0 and line[0] != "#": elems = line.split() camera_id = int(elems[0]) model = elems[1] width = int(elems[2]) height = int(elems[3]) params = np.array(tuple(map(float, elems[4:]))) cameras[camera_id] = Camera(id=camera_id, model=model, width=width, height=height, params=params) return cameras def read_cameras_binary(path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::WriteCamerasBinary(const std::string& path) void Reconstruction::ReadCamerasBinary(const std::string& path) """ cameras = {} with open(path_to_model_file, "rb") as fid: num_cameras = read_next_bytes(fid, 8, "Q")[0] for camera_line_index in range(num_cameras): camera_properties = read_next_bytes( fid, num_bytes=24, format_char_sequence="iiQQ") camera_id = camera_properties[0] model_id = camera_properties[1] model_name = CAMERA_MODEL_IDS[camera_properties[1]].model_name width = camera_properties[2] height = camera_properties[3] num_params = CAMERA_MODEL_IDS[model_id].num_params params = read_next_bytes(fid, num_bytes=8*num_params, format_char_sequence="d"*num_params) cameras[camera_id] = Camera(id=camera_id, model=model_name, width=width, height=height, params=np.array(params)) assert len(cameras) == num_cameras return cameras def read_images_text(path): """ see: src/base/reconstruction.cc void Reconstruction::ReadImagesText(const std::string& path) void Reconstruction::WriteImagesText(const std::string& path) """ images = {} with open(path, "r") as fid: while True: line = fid.readline() if not line: break line = line.strip() if len(line) > 0 and line[0] != "#": elems = line.split() image_id = int(elems[0]) qvec = np.array(tuple(map(float, elems[1:5]))) tvec = np.array(tuple(map(float, elems[5:8]))) camera_id = int(elems[8]) image_name = elems[9] elems = fid.readline().split() xys = np.column_stack([tuple(map(float, elems[0::3])), tuple(map(float, elems[1::3]))]) point3D_ids = np.array(tuple(map(int, elems[2::3]))) images[image_id] = Image( id=image_id, qvec=qvec, tvec=tvec, camera_id=camera_id, name=image_name, xys=xys, point3D_ids=point3D_ids) return images def read_images_binary(path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::ReadImagesBinary(const std::string& path) void Reconstruction::WriteImagesBinary(const std::string& path) """ images = {} with open(path_to_model_file, "rb") as fid: num_reg_images = read_next_bytes(fid, 8, "Q")[0] for image_index in range(num_reg_images): binary_image_properties = read_next_bytes( fid, num_bytes=64, format_char_sequence="idddddddi") image_id = binary_image_properties[0] qvec = np.array(binary_image_properties[1:5]) tvec = np.array(binary_image_properties[5:8]) camera_id = binary_image_properties[8] image_name = "" current_char = read_next_bytes(fid, 1, "c")[0] while current_char != b"\x00": # look for the ASCII 0 entry image_name += current_char.decode("utf-8") current_char = read_next_bytes(fid, 1, "c")[0] num_points2D = read_next_bytes(fid, num_bytes=8, format_char_sequence="Q")[0] x_y_id_s = read_next_bytes(fid, num_bytes=24*num_points2D, format_char_sequence="ddq"*num_points2D) xys = np.column_stack([tuple(map(float, x_y_id_s[0::3])), tuple(map(float, x_y_id_s[1::3]))]) point3D_ids = np.array(tuple(map(int, x_y_id_s[2::3]))) images[image_id] = Image( id=image_id, qvec=qvec, tvec=tvec, camera_id=camera_id, name=image_name, xys=xys, point3D_ids=point3D_ids) return images def read_points3D_text(path): """ see: src/base/reconstruction.cc void Reconstruction::ReadPoints3DText(const std::string& path) void Reconstruction::WritePoints3DText(const std::string& path) """ points3D = {} with open(path, "r") as fid: while True: line = fid.readline() if not line: break line = line.strip() if len(line) > 0 and line[0] != "#": elems = line.split() point3D_id = int(elems[0]) xyz = np.array(tuple(map(float, elems[1:4]))) rgb = np.array(tuple(map(int, elems[4:7]))) error = float(elems[7]) image_ids = np.array(tuple(map(int, elems[8::2]))) point2D_idxs = np.array(tuple(map(int, elems[9::2]))) points3D[point3D_id] = Point3D(id=point3D_id, xyz=xyz, rgb=rgb, error=error, image_ids=image_ids, point2D_idxs=point2D_idxs) return points3D def read_points3d_binary(path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::ReadPoints3DBinary(const std::string& path) void Reconstruction::WritePoints3DBinary(const std::string& path) """ points3D = {} with open(path_to_model_file, "rb") as fid: num_points = read_next_bytes(fid, 8, "Q")[0] for point_line_index in range(num_points): binary_point_line_properties = read_next_bytes( fid, num_bytes=43, format_char_sequence="QdddBBBd") point3D_id = binary_point_line_properties[0] xyz = np.array(binary_point_line_properties[1:4]) rgb = np.array(binary_point_line_properties[4:7]) error = np.array(binary_point_line_properties[7]) track_length = read_next_bytes( fid, num_bytes=8, format_char_sequence="Q")[0] track_elems = read_next_bytes( fid, num_bytes=8*track_length, format_char_sequence="ii"*track_length) image_ids = np.array(tuple(map(int, track_elems[0::2]))) point2D_idxs = np.array(tuple(map(int, track_elems[1::2]))) points3D[point3D_id] = Point3D( id=point3D_id, xyz=xyz, rgb=rgb, error=error, image_ids=image_ids, point2D_idxs=point2D_idxs) return points3D def read_model(path, ext): if ext == ".txt": cameras = read_cameras_text(os.path.join(path, "cameras" + ext)) images = read_images_text(os.path.join(path, "images" + ext)) points3D = read_points3D_text(os.path.join(path, "points3D") + ext) else: cameras = read_cameras_binary(os.path.join(path, "cameras" + ext)) images = read_images_binary(os.path.join(path, "images" + ext)) points3D = read_points3d_binary(os.path.join(path, "points3D") + ext) return cameras, images, points3D def qvec2rotmat(qvec): return np.array([ [1 - 2 * qvec[2]**2 - 2 * qvec[3]**2, 2 * qvec[1] * qvec[2] - 2 * qvec[0] * qvec[3], 2 * qvec[3] * qvec[1] + 2 * qvec[0] * qvec[2]], [2 * qvec[1] * qvec[2] + 2 * qvec[0] * qvec[3], 1 - 2 * qvec[1]**2 - 2 * qvec[3]**2, 2 * qvec[2] * qvec[3] - 2 * qvec[0] * qvec[1]], [2 * qvec[3] * qvec[1] - 2 * qvec[0] * qvec[2], 2 * qvec[2] * qvec[3] + 2 * qvec[0] * qvec[1], 1 - 2 * qvec[1]**2 - 2 * qvec[2]**2]]) def rotmat2qvec(R): Rxx, Ryx, Rzx, Rxy, Ryy, Rzy, Rxz, Ryz, Rzz = R.flat K = np.array([ [Rxx - Ryy - Rzz, 0, 0, 0], [Ryx + Rxy, Ryy - Rxx - Rzz, 0, 0], [Rzx + Rxz, Rzy + Ryz, Rzz - Rxx - Ryy, 0], [Ryz - Rzy, Rzx - Rxz, Rxy - Ryx, Rxx + Ryy + Rzz]]) / 3.0 eigvals, eigvecs = np.linalg.eigh(K) qvec = eigvecs[[3, 0, 1, 2], np.argmax(eigvals)] if qvec[0] < 0: qvec *= -1 return qvec def main(): if len(sys.argv) != 3: print("Usage: python read_model.py path/to/model/folder [.txt,.bin]") return cameras, images, points3D = read_model(path=sys.argv[1], ext=sys.argv[2]) print("num_cameras:", len(cameras)) print("num_images:", len(images)) print("num_points3D:", len(points3D)) if __name__ == "__main__": main() ================================================ FILE: preprocess_custom_data/colmap_preprocess/colmap_wrapper.py ================================================ import os import subprocess # $ DATASET_PATH=/path/to/dataset # $ colmap feature_extractor \ # --database_path $DATASET_PATH/database.db \ # --image_path $DATASET_PATH/images # $ colmap exhaustive_matcher \ # --database_path $DATASET_PATH/database.db # $ mkdir $DATASET_PATH/sparse # $ colmap mapper \ # --database_path $DATASET_PATH/database.db \ # --image_path $DATASET_PATH/images \ # --output_path $DATASET_PATH/sparse # $ mkdir $DATASET_PATH/dense def run_colmap(basedir, match_type): logfile_name = os.path.join(basedir, 'colmap_output.txt') logfile = open(logfile_name, 'w') feature_extractor_args = [ 'colmap', 'feature_extractor', '--database_path', os.path.join(basedir, 'database.db'), '--image_path', os.path.join(basedir, 'images'), '--ImageReader.single_camera', '1', # '--SiftExtraction.use_gpu', '0', ] feat_output = ( subprocess.check_output(feature_extractor_args, universal_newlines=True) ) logfile.write(feat_output) print('Features extracted') exhaustive_matcher_args = [ 'colmap', match_type, '--database_path', os.path.join(basedir, 'database.db'), ] match_output = ( subprocess.check_output(exhaustive_matcher_args, universal_newlines=True) ) logfile.write(match_output) print('Features matched') p = os.path.join(basedir, 'sparse') if not os.path.exists(p): os.makedirs(p) # mapper_args = [ # 'colmap', 'mapper', # '--database_path', os.path.join(basedir, 'database.db'), # '--image_path', os.path.join(basedir, 'images'), # '--output_path', os.path.join(basedir, 'sparse'), # '--Mapper.num_threads', '16', # '--Mapper.init_min_tri_angle', '4', # ] mapper_args = [ 'colmap', 'mapper', '--database_path', os.path.join(basedir, 'database.db'), '--image_path', os.path.join(basedir, 'images'), '--output_path', os.path.join(basedir, 'sparse'), # --export_path changed to --output_path in colmap 3.6 '--Mapper.num_threads', '16', '--Mapper.init_min_tri_angle', '4', '--Mapper.multiple_models', '0', '--Mapper.extract_colors', '0', ] map_output = ( subprocess.check_output(mapper_args, universal_newlines=True) ) logfile.write(map_output) logfile.close() print('Sparse map created') print( 'Finished running COLMAP, see {} for logs'.format(logfile_name) ) ================================================ FILE: preprocess_custom_data/colmap_preprocess/gen_cameras.py ================================================ import numpy as np import trimesh import cv2 as cv import sys import os from glob import glob if __name__ == '__main__': work_dir = sys.argv[1] poses_hwf = np.load(os.path.join(work_dir, 'poses.npy')) # n_images, 3, 5 poses_raw = poses_hwf[:, :, :4] hwf = poses_hwf[:, :, 4] pose = np.diag([1.0, 1.0, 1.0, 1.0]) pose[:3, :4] = poses_raw[0] pts = [] pts.append((pose @ np.array([0, 0, 0, 1])[:, None]).squeeze()[:3]) pts.append((pose @ np.array([1, 0, 0, 1])[:, None]).squeeze()[:3]) pts.append((pose @ np.array([0, 1, 0, 1])[:, None]).squeeze()[:3]) pts.append((pose @ np.array([0, 0, 1, 1])[:, None]).squeeze()[:3]) pts = np.stack(pts, axis=0) pcd = trimesh.PointCloud(pts) pcd.export(os.path.join(work_dir, 'pose.ply')) # cam_dict = dict() n_images = len(poses_raw) # Convert space convert_mat = np.zeros([4, 4], dtype=np.float32) convert_mat[0, 1] = 1.0 convert_mat[1, 0] = 1.0 convert_mat[2, 2] =-1.0 convert_mat[3, 3] = 1.0 for i in range(n_images): pose = np.diag([1.0, 1.0, 1.0, 1.0]).astype(np.float32) pose[:3, :4] = poses_raw[i] pose = pose @ convert_mat h, w, f = hwf[i, 0], hwf[i, 1], hwf[i, 2] intrinsic = np.diag([f, f, 1.0, 1.0]).astype(np.float32) intrinsic[0, 2] = (w - 1) * 0.5 intrinsic[1, 2] = (h - 1) * 0.5 w2c = np.linalg.inv(pose) world_mat = intrinsic @ w2c world_mat = world_mat.astype(np.float32) cam_dict['camera_mat_{}'.format(i)] = intrinsic cam_dict['camera_mat_inv_{}'.format(i)] = np.linalg.inv(intrinsic) cam_dict['world_mat_{}'.format(i)] = world_mat cam_dict['world_mat_inv_{}'.format(i)] = np.linalg.inv(world_mat) pcd = trimesh.load(os.path.join(work_dir, 'sparse_points_interest.ply')) vertices = pcd.vertices bbox_max = np.max(vertices, axis=0) bbox_min = np.min(vertices, axis=0) center = (bbox_max + bbox_min) * 0.5 radius = np.linalg.norm(vertices - center, ord=2, axis=-1).max() scale_mat = np.diag([radius, radius, radius, 1.0]).astype(np.float32) scale_mat[:3, 3] = center for i in range(n_images): cam_dict['scale_mat_{}'.format(i)] = scale_mat cam_dict['scale_mat_inv_{}'.format(i)] = np.linalg.inv(scale_mat) out_dir = os.path.join(work_dir, 'preprocessed') os.makedirs(out_dir, exist_ok=True) os.makedirs(os.path.join(out_dir, 'image'), exist_ok=True) os.makedirs(os.path.join(out_dir, 'mask'), exist_ok=True) image_list = glob(os.path.join(work_dir, 'images/*.png')) image_list.sort() for i, image_path in enumerate(image_list): img = cv.imread(image_path) cv.imwrite(os.path.join(out_dir, 'image', '{:0>3d}.png'.format(i)), img) cv.imwrite(os.path.join(out_dir, 'mask', '{:0>3d}.png'.format(i)), np.ones_like(img) * 255) np.savez(os.path.join(out_dir, 'cameras_sphere.npz'), **cam_dict) print('Process done!') ================================================ FILE: preprocess_custom_data/colmap_preprocess/imgs2poses.py ================================================ from pose_utils import gen_poses import sys import argparse parser = argparse.ArgumentParser() parser.add_argument('--match_type', type=str, default='exhaustive_matcher', help='type of matcher used. Valid options: \ exhaustive_matcher sequential_matcher. Other matchers not supported at this time') parser.add_argument('scenedir', type=str, help='input scene directory') args = parser.parse_args() if args.match_type != 'exhaustive_matcher' and args.match_type != 'sequential_matcher': print('ERROR: matcher type ' + args.match_type + ' is not valid. Aborting') sys.exit() if __name__=='__main__': gen_poses(args.scenedir, args.match_type) ================================================ FILE: preprocess_custom_data/colmap_preprocess/pose_utils.py ================================================ import numpy as np import os import sys import imageio import skimage.transform import trimesh from colmap_wrapper import run_colmap import colmap_read_model as read_model def load_colmap_data(realdir): camerasfile = os.path.join(realdir, 'sparse/0/cameras.bin') camdata = read_model.read_cameras_binary(camerasfile) # cam = camdata[camdata.keys()[0]] list_of_keys = list(camdata.keys()) cam = camdata[list_of_keys[0]] print( 'Cameras', len(cam)) h, w, f = cam.height, cam.width, cam.params[0] # w, h, f = factor * w, factor * h, factor * f hwf = np.array([h,w,f]).reshape([3,1]) imagesfile = os.path.join(realdir, 'sparse/0/images.bin') imdata = read_model.read_images_binary(imagesfile) w2c_mats = [] bottom = np.array([0,0,0,1.]).reshape([1,4]) names = [imdata[k].name for k in imdata] print( 'Images #', len(names)) perm = np.argsort(names) for k in imdata: im = imdata[k] R = im.qvec2rotmat() t = im.tvec.reshape([3,1]) m = np.concatenate([np.concatenate([R, t], 1), bottom], 0) w2c_mats.append(m) w2c_mats = np.stack(w2c_mats, 0) c2w_mats = np.linalg.inv(w2c_mats) poses = c2w_mats[:, :3, :4].transpose([1,2,0]) poses = np.concatenate([poses, np.tile(hwf[..., np.newaxis], [1,1,poses.shape[-1]])], 1) points3dfile = os.path.join(realdir, 'sparse/0/points3D.bin') pts3d = read_model.read_points3d_binary(points3dfile) # must switch to [-u, r, -t] from [r, -u, t], NOT [r, u, -t] poses = np.concatenate([poses[:, 1:2, :], poses[:, 0:1, :], -poses[:, 2:3, :], poses[:, 3:4, :], poses[:, 4:5, :]], 1) return poses, pts3d, perm def save_poses(basedir, poses, pts3d, perm): pts_arr = [] vis_arr = [] for k in pts3d: pts_arr.append(pts3d[k].xyz) cams = [0] * poses.shape[-1] for ind in pts3d[k].image_ids: if len(cams) < ind - 1: print('ERROR: the correct camera poses for current points cannot be accessed') return cams[ind-1] = 1 vis_arr.append(cams) pts = np.stack(pts_arr, axis=0) pcd = trimesh.PointCloud(pts) pcd.export(os.path.join(basedir, 'sparse_points.ply')) pts_arr = np.array(pts_arr) vis_arr = np.array(vis_arr) print('Points', pts_arr.shape, 'Visibility', vis_arr.shape ) poses = np.moveaxis(poses, -1, 0) poses = poses[perm] np.save(os.path.join(basedir, 'poses.npy'), poses) def minify_v0(basedir, factors=[], resolutions=[]): needtoload = False for r in factors: imgdir = os.path.join(basedir, 'images_{}'.format(r)) if not os.path.exists(imgdir): needtoload = True for r in resolutions: imgdir = os.path.join(basedir, 'images_{}x{}'.format(r[1], r[0])) if not os.path.exists(imgdir): needtoload = True if not needtoload: return def downsample(imgs, f): sh = list(imgs.shape) sh = sh[:-3] + [sh[-3]//f, f, sh[-2]//f, f, sh[-1]] imgs = np.reshape(imgs, sh) imgs = np.mean(imgs, (-2, -4)) return imgs imgdir = os.path.join(basedir, 'images') imgs = [os.path.join(imgdir, f) for f in sorted(os.listdir(imgdir))] imgs = [f for f in imgs if any([f.endswith(ex) for ex in ['JPG', 'jpg', 'png', 'jpeg', 'PNG']])] imgs = np.stack([imageio.imread(img)/255. for img in imgs], 0) for r in factors + resolutions: if isinstance(r, int): name = 'images_{}'.format(r) else: name = 'images_{}x{}'.format(r[1], r[0]) imgdir = os.path.join(basedir, name) if os.path.exists(imgdir): continue print('Minifying', r, basedir) if isinstance(r, int): imgs_down = downsample(imgs, r) else: imgs_down = skimage.transform.resize(imgs, [imgs.shape[0], r[0], r[1], imgs.shape[-1]], order=1, mode='constant', cval=0, clip=True, preserve_range=False, anti_aliasing=True, anti_aliasing_sigma=None) os.makedirs(imgdir) for i in range(imgs_down.shape[0]): imageio.imwrite(os.path.join(imgdir, 'image{:03d}.png'.format(i)), (255*imgs_down[i]).astype(np.uint8)) def minify(basedir, factors=[], resolutions=[]): needtoload = False for r in factors: imgdir = os.path.join(basedir, 'images_{}'.format(r)) if not os.path.exists(imgdir): needtoload = True for r in resolutions: imgdir = os.path.join(basedir, 'images_{}x{}'.format(r[1], r[0])) if not os.path.exists(imgdir): needtoload = True if not needtoload: return from shutil import copy from subprocess import check_output imgdir = os.path.join(basedir, 'images') imgs = [os.path.join(imgdir, f) for f in sorted(os.listdir(imgdir))] imgs = [f for f in imgs if any([f.endswith(ex) for ex in ['JPG', 'jpg', 'png', 'jpeg', 'PNG']])] imgdir_orig = imgdir wd = os.getcwd() for r in factors + resolutions: if isinstance(r, int): name = 'images_{}'.format(r) resizearg = '{}%'.format(int(100./r)) else: name = 'images_{}x{}'.format(r[1], r[0]) resizearg = '{}x{}'.format(r[1], r[0]) imgdir = os.path.join(basedir, name) if os.path.exists(imgdir): continue print('Minifying', r, basedir) os.makedirs(imgdir) check_output('cp {}/* {}'.format(imgdir_orig, imgdir), shell=True) ext = imgs[0].split('.')[-1] args = ' '.join(['mogrify', '-resize', resizearg, '-format', 'png', '*.{}'.format(ext)]) print(args) os.chdir(imgdir) check_output(args, shell=True) os.chdir(wd) if ext != 'png': check_output('rm {}/*.{}'.format(imgdir, ext), shell=True) print('Removed duplicates') print('Done') def load_data(basedir, factor=None, width=None, height=None, load_imgs=True): poses_arr = np.load(os.path.join(basedir, 'poses_bounds.npy')) poses = poses_arr[:, :-2].reshape([-1, 3, 5]).transpose([1,2,0]) bds = poses_arr[:, -2:].transpose([1,0]) img0 = [os.path.join(basedir, 'images', f) for f in sorted(os.listdir(os.path.join(basedir, 'images'))) \ if f.endswith('JPG') or f.endswith('jpg') or f.endswith('png')][0] sh = imageio.imread(img0).shape sfx = '' if factor is not None: sfx = '_{}'.format(factor) minify(basedir, factors=[factor]) factor = factor elif height is not None: factor = sh[0] / float(height) width = int(sh[1] / factor) minify(basedir, resolutions=[[height, width]]) sfx = '_{}x{}'.format(width, height) elif width is not None: factor = sh[1] / float(width) height = int(sh[0] / factor) minify(basedir, resolutions=[[height, width]]) sfx = '_{}x{}'.format(width, height) else: factor = 1 imgdir = os.path.join(basedir, 'images' + sfx) if not os.path.exists(imgdir): print( imgdir, 'does not exist, returning' ) return imgfiles = [os.path.join(imgdir, f) for f in sorted(os.listdir(imgdir)) if f.endswith('JPG') or f.endswith('jpg') or f.endswith('png')] if poses.shape[-1] != len(imgfiles): print( 'Mismatch between imgs {} and poses {} !!!!'.format(len(imgfiles), poses.shape[-1]) ) return sh = imageio.imread(imgfiles[0]).shape poses[:2, 4, :] = np.array(sh[:2]).reshape([2, 1]) poses[2, 4, :] = poses[2, 4, :] * 1./factor if not load_imgs: return poses, bds # imgs = [imageio.imread(f, ignoregamma=True)[...,:3]/255. for f in imgfiles] def imread(f): if f.endswith('png'): return imageio.imread(f, ignoregamma=True) else: return imageio.imread(f) imgs = imgs = [imread(f)[...,:3]/255. for f in imgfiles] imgs = np.stack(imgs, -1) print('Loaded image data', imgs.shape, poses[:,-1,0]) return poses, bds, imgs def gen_poses(basedir, match_type, factors=None): files_needed = ['{}.bin'.format(f) for f in ['cameras', 'images', 'points3D']] if os.path.exists(os.path.join(basedir, 'sparse/0')): files_had = os.listdir(os.path.join(basedir, 'sparse/0')) else: files_had = [] if not all([f in files_had for f in files_needed]): print( 'Need to run COLMAP' ) run_colmap(basedir, match_type) else: print('Don\'t need to run COLMAP') print('Post-colmap') poses, pts3d, perm = load_colmap_data(basedir) save_poses(basedir, poses, pts3d, perm) if factors is not None: print( 'Factors:', factors) minify(basedir, factors) print( 'Done with imgs2poses' ) return True ================================================ FILE: preprocess_custom_data/readme.md ================================================ # Training NeuS Using Your Custom Data ### [Example data link](https://drive.google.com/file/d/1nZBY--rvi3dUKGVz-d1jCpppkeD_tBiB/view?usp=sharing) ### Option 1. Use ArUco We take the images in `examples/thin_catbus` for example. These images were captured with an ArUco board. The pattern image of this board can be found in `./static/aruco_board.png`. **Step 1. Build the calibration code (c++)** Dependencies: - cnpy (https://github.com/rogersce/cnpy) - OpenCV Run commands ``` cd aruco_preprocess mkdir build cd build cmake .. & make cd .. ``` **Step 2. Get the preprocessed data** First indicate `data_dir`,`n_images` in `run.sh`. For example, `data_dir=./example/thin_catbus` Run commands ``` bash run.sh ``` Then the preprocessed data can be found in `${data_dir}/preprocessed`. Here we define the region of interest as the bounding sphere of the calibration board. ### Option 2. Use COLMAP **Step 1. Run COLMAP SfM** Run commands ``` cd colmap_preprocess python img2poses.py ${data_dir} ``` After running the commands above, a sparse point cloud is saved in `${data_dir}/sparse_points.ply`. **Step 2. Define the region of interest** The raw sparse point cloud may be noisy and may not be appropriate to define a region of interest (The white frame indicates the bounding box of the point cloud): ![raw_sparse_points](./static/raw_sparse_points.png) And you may need to clean it by yourself (here we use Meshlab to clean it manually). After cleaning: ![interest_sparse_points](./static/interest_sparse_points.png) Save it as `${data_dir}/sparse_point_interest.ply`. Then run the commands: ``` python gen_cameras.py ${data_dir} ``` Then the preprocessed data can be found in `${data_dir}/preprocessed`. ### Notes Here we just use the image without undistortion in the second option. To get better results, you may need to undistort your images in advance. ## Acknowledgement The python scripts to run COLMAP SfM are heavily borrowed from LLFF: https://github.com/Fyusion/LLFF ================================================ FILE: requirements.txt ================================================ trimesh==3.9.8 numpy==1.19.2 pyhocon==0.3.57 icecream==2.1.0 opencv_python==4.5.2.52 tqdm==4.50.2 torch==1.8.0 scipy==1.7.0 PyMCubes==0.1.2