/
setup.cfg
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/
setup.cfg
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[metadata]
name = geomstats
version = attr: geomstats.__version__
author = Nina Miolane
author_email = nmiolane@gmail.com
description = Geometric statistics on manifolds
long_description = file: README.rst
long_description_content_type = text/x-rst
licence = MIT
url = http://github.com/geomstats/geomstats
project_urls =
Homepage = http://github.com/geomstats/geomstats
Documentation = https://geomstats.github.io/
Bug Tracker = http://github.com/geomstats/geomstats/-/issues
classifiers =
License :: OSI Approved :: MIT License
Development Status :: 5 - Production/Stable
Intended Audience :: Science/Research
Topic :: Scientific/Engineering
Topic :: Scientific/Engineering :: Artificial Intelligence
Topic :: Scientific/Engineering :: Mathematics
License :: OSI Approved :: MIT License
Programming Language :: Python :: 3
Programming Language :: Python :: 3.7
Programming Language :: Python :: 3.8
Programming Language :: Python :: 3.9
Programming Language :: Python :: 3.10
[options]
packages = find:
python_requires = >= 3.7
zip_safe = False
install_requires =
joblib >= 0.14.1
matplotlib >= 3.3.4
numpy >= 1.18.1
pandas >= 1.1.5
scikit-learn >= 0.22.1
scipy >= 1.4.1
[options.packages.find]
include =
geomstats
geomstats.*
[options.package_data]
* =
datasets/data/**/*
[options.extras_require]
doc =
jupyter
cloudpickle
dask_sphinx_theme>=1.1.0
distributed
nbsphinx
nbsphinx_link
numpydoc==0.8
sphinx
sphinx-click
sphinx_gallery
sphinx_rtd_theme
toolz
ci =
codecov
coverage
dev =
pytest
pytest-cov
black
flake8
flake8-docstrings
isort
pre-commit
autograd =
autograd >= 1.3
tensorflow =
tensorflow >= 2.2
tensorflow-probability >= 0.9
torch =
torch == 1.9.1
opt = geomstats[autograd,tensorflow,torch]
test = geomstats[dev]
all = geomstats[test,opt]
[flake8]
application_import_names = geomstats
docstring-convention = numpy
exclude = examples/*.ipynb
ignore = W503, W504
import_order_style = smarkets
max-line-length = 88
extend-ignore = E203
per-file-ignores =
geomstats/_backend/autograd/*:F401, D103
geomstats/_backend/numpy/*:F401, D103
geomstats/_backend/pytorch/*:F401, D103
geomstats/_backend/tensorflow/*:F401, D103
geomstats/visualization/*: D101, D102
geomstats/visualization/__init__.py: F401
geomstats/tests.py : D101, D102
tests/*: D100, D101, D102, D103, D106, D200, D201, D205, D400, D404, I100, I101, I201, I202
*/__init__.py: D104
[tool:pytest]
markers =
smoke: simple and basic numerical tests.
random: tests that use randomized data.