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#!/usr/bin/env python
################################################################################
# Copyright (C) 2011-2015 Jaakko Luttinen
#
# This file is licensed under the MIT License.
################################################################################
import os
import versioneer
meta = {}
base_dir = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(base_dir, 'bayespy', '_meta.py')) as fp:
exec(fp.read(), meta)
NAME = 'bayespy'
DESCRIPTION = 'Variational Bayesian inference tools for Python'
AUTHOR = meta['__author__']
AUTHOR_EMAIL = meta['__contact__']
URL = 'http://bayespy.org'
VERSION = versioneer.get_version()
COPYRIGHT = meta['__copyright__']
if __name__ == "__main__":
import os
import sys
python_version = int(sys.version.split('.')[0])
if python_version < 3:
raise RuntimeError("BayesPy requires Python 3. You are running Python "
"{0}.".format(python_version))
# This is annoying: Because readthedocs.org doesn't support depending on
# h5py, we need to remove that dependency if we are on the readthedocs
# servers..
ON_RTD = os.environ.get('READTHEDOCS') == 'True'
if ON_RTD:
# Workaround for https://github.com/rtfd/readthedocs.org/issues/2149
install_requires = [
'sphinx>=1.4.0'
]
else:
install_requires = [
'numpy>=1.10.0', # 1.10 implements broadcast_to
# 1.8 implements broadcasting in numpy.linalg
'scipy>=0.13.0', # <0.13 have a bug in special.multigammaln
'h5py',
]
# Utility function to read the README file.
# Used for the long_description. It's nice, because now 1) we have a top level
# README file and 2) it's easier to type in the README file than to put a raw
# string in below ...
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
from setuptools import setup, find_packages
# Setup for BayesPy
setup(
install_requires = install_requires,
extras_require = {
'doc': [
'sphinx>=1.4.0', # 1.4.0 adds imgmath extension
'sphinxcontrib-tikz>=0.4.2',
'sphinxcontrib-bayesnet',
'sphinxcontrib-bibtex',
'numpydoc>=0.5',
'nbsphinx',
],
'dev': [
'nose',
'nosebook',
]
},
packages = find_packages(),
package_data = {
NAME: ["tests/baseline_images/test_plot/*.png"]
},
name = NAME,
version = VERSION,
author = AUTHOR,
author_email = AUTHOR_EMAIL,
description = DESCRIPTION,
url = URL,
long_description = read('README.rst'),
cmdclass = versioneer.get_cmdclass(),
keywords = [
'variational Bayes',
'probabilistic programming',
'Bayesian networks',
'graphical models',
'variational message passing'
],
classifiers = [
'Programming Language :: Python :: 3 :: Only',
'Programming Language :: Python :: 3.3',
'Programming Language :: Python :: 3.4',
'Development Status :: 4 - Beta',
'Environment :: Console',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: {0}'.format(meta['__license__']),
'Operating System :: OS Independent',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Information Analysis'
],
entry_points = {
'nose.plugins': [
'warnaserror = bayespy.testing:WarnAsError',
]
},
)
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