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pyproject.toml
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pyproject.toml
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[build-system]
requires = ["setuptools >= 61.0"]
build-backend = "setuptools.build_meta"
[project]
name = "persim"
dynamic = ["version"]
description = "Distances and representations of persistence diagrams"
readme = "README.md"
authors = [
{ name = "Nathaniel Saul", email = "[email protected]" },
{ name = "Chris Tralie", email = "[email protected]" },
{ name = "Francis Motta", email = "[email protected]" },
{ name = "Michael Catanzaro", email = "[email protected]" },
{ name = "Gabrielle Angeloro", email = "[email protected]" },
{ name = "Calder Sheagren", email = "[email protected]" },
]
maintainers = [
{ name = "Nathaniel Saul", email = "[email protected]" },
{ name = "Chris Tralie", email = "[email protected]" },
{ name = "Michael Catanzaro", email = "[email protected]" },
{ name = "Abraham Smith", email = "[email protected]" },
]
dependencies = [
"deprecated",
"hopcroftkarp",
"joblib",
"matplotlib",
"numpy",
"scikit-learn",
]
classifiers = [
"Development Status :: 3 - Alpha",
"Intended Audience :: Science/Research",
"Intended Audience :: Education",
"Intended Audience :: Financial and Insurance Industry",
"Intended Audience :: Healthcare Industry",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Scientific/Engineering :: Mathematics",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python",
]
keywords = [
"persistent homology",
"persistence images",
"persistence diagrams",
"topological data analysis",
"algebraic topology",
"unsupervised learning",
"supervised learning",
"machine learning",
"sliced wasserstein distance",
"bottleneck distance",
]
[project.optional-dependencies]
testing = ["pytest", "pytest-cov"]
docs = ["ripser", "sktda_docs_config"]
[project.urls]
Homepage = "https://persim.scikit-tda.org"
Documentation = "https://persim.scikit-tda.org"
Repository = "https://github.com/scikit-tda/persim"
Issues = "https://github.com/scikit-tda/persim/issues"
Changelog = "https://github.com/scikit-tda/persim/blob/master/RELEASE.txt"