gudhi
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Wheel Details
Project: | gudhi |
Version: | 3.10.1 |
Filename: | gudhi-3.10.1-cp38-cp38-win_amd64.whl |
Download: | [link] |
Size: | 2888788 |
MD5: | 627512ee39e7e4d82ec3e536755fad69 |
SHA256: | 93dd9a15314d2e26ef28c44833ba385301bd26a255a5a9a5811bad8a604ca4b4 |
Uploaded: | 2024-07-02 13:36:22 +0000 |
dist-info
METADATA · WHEEL · RECORD · top_level.txt
METADATA
WHEEL
Wheel-Version: | 1.0 |
Generator: | bdist_wheel (0.43.0) |
Root-Is-Purelib: | false |
Tag: | cp38-cp38-win_amd64 |
RECORD
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gudhi/_kepler_mapper.py | sha256=q5f6f6JXid2PJmNbiV5olxjQzeM4kSvASsgrAlvdHH4 | 17765 |
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gudhi/cover_complex.py | sha256=lNmB2bdj-nKp6StFwywYZHYHRn5fsXimZ4Hv-G4p3nU | 38210 |
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gudhi/point_cloud/__init__.py | sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU | 0 |
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gudhi/representations/metrics.py | sha256=c-I5pZAchjoy0zbtAN35SdOStBPYh7kfWv4eqaadE8U | 24045 |
gudhi/representations/preprocessing.py | sha256=llnxfa8P8Ce75T4C9_H71uErV6fpvs0Ji_yr3yew_hY | 19030 |
gudhi/representations/vector_methods.py | sha256=u8ltNZysjho5P4252a74FgfdNgLh1LLgP3vbxnyHWoE | 43978 |
gudhi/sklearn/__init__.py | sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU | 0 |
gudhi/sklearn/cubical_persistence.py | sha256=FnhmlCvCoGmnP4c95xC5iabK6yq8F5q4uUIGEM5ztiQ | 6297 |
gudhi/sklearn/rips_persistence.py | sha256=HvfnOQx1Whezq1667QnXRcnj_cSdI944C6GI8e2eMRk | 6021 |
gudhi/tensorflow/__init__.py | sha256=Uyeu-xy0W62cbUodC2XEt0yL0-r4_3YReH_SssQ6Ivw | 218 |
gudhi/tensorflow/cubical_layer.py | sha256=ojZE4EyBFr5erI-DGDJt_E76cKz_ELXGycb6uNlyggE | 4440 |
gudhi/tensorflow/lower_star_simplex_tree_layer.py | sha256=ikZGUiOWUEVKu010rGwoTzI9DecQZHGcBkchQyxEKw0 | 5190 |
gudhi/tensorflow/perslay.py | sha256=TISu71R8HKmmzwc6k4sFGcoKmeqHZrSJQnNXu7466zc | 15588 |
gudhi/tensorflow/rips_layer.py | sha256=HLAgvNoDybSuIiUiFBya7y1jKlUqv1PTcPXUdp3b4XM | 4965 |
gudhi/wasserstein/__init__.py | sha256=SctIz2GwFD9cgdLs76VnXgnQSJI_E1xZy-KwGpMIpVo | 47 |
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gudhi-3.10.1.dist-info/RECORD | — | — |
top_level.txt
gudhi