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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010 Matej Laitl <matej@laitl.cz>
# Distributed under the terms of the GNU General Public License v2 or any
# later version of the license, at your option.
from distutils.core import setup
import os.path
from support import determine_pybayes_version
from support.dist import PyBayesDistribution
dir = os.path.dirname(os.path.realpath(__file__))
version = determine_pybayes_version(dir=dir, fallback='0.3-post-nongit')
params = {
# meta-data; see http://docs.python.org/distutils/setupscript.html#additional-meta-data
'name':'PyBayes',
'version':version,
'author':u'Matěj Laitl',
'author_email':'matej@laitl.cz',
'maintainer':u'Matěj Laitl',
'maintainer_email':'matej@laitl.cz',
'url':'https://github.com/strohel/PyBayes',
'description':'Python library for recursive Bayesian estimation (Bayesian filtering)',
'long_description':'PyBayes is an object-oriented Python library for recursive Bayesian ' +
'estimation (Bayesian filtering) that is convenient to use. Already implemented are ' +
'Kalman filter, particle filter and marginalized particle filter, all built atop of ' +
'a light framework of probability density functions. PyBayes can optionally use Cython ' +
'for lage speed gains (Cython build can be several times faster in some situations).',
# Note to myself: must manually upload on each release!
'download_url':'https://github.com/downloads/strohel/PyBayes/PyBayes-'+version+'.tar.gz',
'platforms':'cross-platform',
'license':'GNU GPL v2+',
'classifiers':[
'Development Status :: 3 - Alpha',
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: GNU General Public License (GPL)',
'Operating System :: OS Independent',
'Programming Language :: Cython',
'Programming Language :: Python',
'Topic :: Scientific/Engineering :: Mathematics',
'Topic :: Scientific/Engineering :: Physics',
'Topic :: Software Development :: Libraries :: Python Modules',
],
# Python (Cython) packages to build:
'packages':['pybayes', 'pybayes.stresses', 'pybayes.tests', 'pybayes.wrappers'],
'package_data':{'pybayes.tests':['stress_kalman_data.mat']},
# THE trick - custom distribution that handles Python/Cython build
'distclass':PyBayesDistribution
}
if __name__ == '__main__':
setup(**params)
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