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import os
from setuptools import setup, find_packages
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def setup_package():
"""Setup function"""
name = 'scikit-multimodallearn'
version = multiconfusion.__version__
description = 'A scikit-learn compatible package for multimodal Classifiers'
here = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(here, 'README.rst'), encoding='utf-8') as readme:
long_description = readme.read()
group = 'dev'
url = 'https://gitlab.lis-lab.fr/{}/{}'.format(group, name)
project_urls = {
'Documentation': 'http://{}.pages.lis-lab.fr/{}'.format(group, name),
'Source': url,
'Tracker': '{}/issues'.format(url)}
author = 'Dominique Benielli'
author_email = 'contact.dev@lis-lab.fr'
license = 'newBSD'
classifiers = [
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: GNU Lesser General Public License'
' v3 or later (LGPLv3+)',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX :: Linux',
'Operating System :: MacOS'],
keywords = ('machine learning, supervised learning, classification, '
'ensemble methods, boosting, kernel')
packages = find_packages(exclude=['*.tests'])
install_requires = ['scikit-learn>=0.19', 'numpy', 'scipy', 'cvxopt' ]
python_requires = '>=3.5'
extras_require = {
'dev': ['pytest', 'pytest-cov'],
'doc': ['sphinx', 'numpydoc', 'sphinx_gallery', 'matplotlib']}
include_package_data = True
setup(name=name,
version=version,
description=description,
long_description=long_description,
url=url,
project_urls=project_urls,
author=author,
author_email=author_email,
license=license,
classifiers=classifiers,
keywords=keywords,
packages=packages,
install_requires=install_requires,
python_requires=python_requires,
extras_require=extras_require,
include_package_data=include_package_data)
if __name__ == "__main__":
setup_package()