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setup.py
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setup.py
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"""
Setup script for the inverse-canopy package
"""
from setuptools import setup
with open('README.md', encoding='utf-8') as f:
README = f.read()
setup(
name='inverse-canopy',
url='https://openpra.org',
version='0.0.21',
author='Arjun Earthperson',
author_email='arjun@openpra.org',
license='AGPL-3.0',
description='Tensorflow based library for back-fitting event tree conditional/functional event probability '
'distributions to match target end-state frequencies.',
long_description_content_type='text/markdown',
long_description=README,
install_requires=[
'tensorflow>=2.15.0',
'tensorflow-probability>=0.23.0',
'numpy',
'scipy',
'matplotlib'
],
extras_require={
'cuda': [
'tensorflow[and-cuda]'
],
'metal': [
'tensorflow==2.13.1',
'tensorflow-metal==1.0.0',
'tensorflow-probability==0.21.0',
],
'dev': [
'pyarrow',
'pytest',
'pytest-cov',
'pylint',
'pylint[spelling]',
'twine'
]
},
classifiers=[
'Development Status :: 2 - Pre-Alpha',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)',
'Operating System :: OS Independent',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Programming Language :: Python :: 3.11',
'Topic :: Software Development :: Libraries',
'Topic :: Scientific/Engineering',
'Typing :: Typed'
],
packages=['inverse_canopy'],
python_requires='>=3.8',
entry_points={
},
)