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setup.py
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setup.py
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#!/usr/bin/env python
from setuptools import setup
import re
VERSIONFILE="sktda/_version.py"
verstrline = open(VERSIONFILE, "rt").read()
VSRE = r"^__version__ = ['\"]([^'\"]*)['\"]"
mo = re.search(VSRE, verstrline, re.M)
if mo:
verstr = mo.group(1)
else:
raise RuntimeError("Unable to find version string in %s." % (VERSIONFILE,))
with open('README.md') as f:
long_description = f.read()
setup(name='scikit-tda',
version=verstr,
description='Topological Data Analysis for humans',
long_description=long_description,
long_description_content_type="text/markdown",
author='Nathaniel Saul, Chris Tralie',
author_email='nathaniel.saul@wsu.edu, chris.tralie@gmail.com',
url='https://github.com/scikit-tda/scikit-tda',
license='MIT',
packages=['sktda'],
include_package_data=True,
install_requires=[
# Common requirements
'numpy',
'scipy',
'scikit-learn',
'matplotlib',
# Ripser
'Cython',
'ripser',
# Persim
'persim',
# Kepler Mapper
'pillow', # for some kmapper examples
'kmapper',
# tadasets
'tadasets',
],
extras_require={
'testing': [ # `pip install -e ".[testing]"``
'pytest'
],
'docs': [ # `pip install -e ".[docs]"``
'sktda_docs_config',
'pyyaml'
]
},
python_requires='>3.3',
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 :: 3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8'
],
keywords='topology data analysis, algebraic topology, unsupervised learning, persistent homology, persistence images, persistence diagrams, uniform manifold approximation and projection, sheaf theory, mapper, data visualization'
)