#!/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))

    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',
        'truncnorm',
    ]

    # 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',
                'nbsphinx',
                'matplotlib',
            ],
            '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',
            ]
        },
    )