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setup.py
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from setuptools import setup, find_packages
import subprocess
import sys
import os
import time
# Read the contents of your README file
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setup(name='GammaBayes',
description='A package for Bayesian dark matter inference',
url='https://github.com/lpin0002/GammaBayes',
author='Liam Pinchbeck',
author_email='[email protected]',
license="MIT",
version='0.1.9',
packages=find_packages(),
long_description=long_description, # This is the long description, read from README.md
long_description_content_type="text/markdown",
# For a lot of the DM spectral classes we require that dict types are ordered
python_requires='>=3.6',
install_requires=[
"astropy==5.3.4",
"corner>=2.2.2",
"dynesty==2.1.2",
"jupyterlab>=3.6.3",
"matplotlib>=3.7.1",
"scipy==1.11.3",
"tqdm>=4.65.0",
"numpy>=1.23",
"gammapy==1.1",
"pandas>=1.5.3",
"healpy",
"pytest",
"h5py",
"icecream",
"seaborn"
],
classifiers=[
"License :: OSI Approved :: MIT License",
"Operating System :: Unix",
],
package_data={
'gammabayes':['package_data/gll_iem_v06_gc.fits.gz',
'package_data/hgps_catalog_v1.fits.gz',
'package_data/*.txt',
'package_data/*.fits',
'package_data/irf_fits_files/*',
'package_data/irf_fits_files/prod5/*.FITS.tar.gz',
'package_data/irf_fits_files/prod3b/*',
'dark_matter/channel_spectra/PPPC_Tables/*.dat',
'dark_matter/spectral_models/Z2_ScalarSinglet/annihilation_ratio_data/*',
'dark_matter/spectral_models/Z5/annihilation_ratio_data/*',
'standard_inference/*',
'utils/ozstar/*'
]
},
)