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setup.py
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setup.py
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from setuptools import setup, find_packages
import pathlib
here = pathlib.Path(__file__).parent.resolve()
long_description = (here / 'README.md').read_text(encoding='utf-8')
setup(
name='ionimage_embedding',
version='0.3.0',
description='Deep learning-based clustering approach to cluster ion images from mass spectrometry imaging data '
'across datasets. Optimized to work with datasets from the METASPACE database.',
long_description=long_description,
long_description_content_type='text/markdown',
url='https://github.com/tdrose/ionimage_embedding',
project_urls={ # Optional
'Source': 'https://github.com/tdrose/ionimage_embedding',
#'Publication': ""
},
author="Tim Daniel Rose",
author_email="[email protected]",
license='MIT',
packages=find_packages(),
install_requires=[
'pandas',
'numpy',
'torch',
'lightning',
'torchvision',
'metaspace2020',
'scikit-learn',
'anndata',
'scanpy',
'umap-learn',
'open_clip_torch>=2.23.0', # Known bug in model loading, fixed in version 0.23.0
'torch_geometric',
'rdkit',
'molmass'
],
python_requires=">=3.8",
zip_safe=False,
classifiers=[
"License :: OSI Approved :: GNU General Public License v3",
"Topic :: Scientific/Engineering :: Bio-Informatics",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Intended Audience :: Science/Research",
"Natural Language :: English",
"Operating System :: MacOS",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX :: Linux",
"Programming Language :: Python :: 3"
]
)