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# -*- coding: utf-8 -*-
# ######### COPYRIGHT #########
#
# Copyright(c) 2020
# -----------------
#
# * Université d'Aix Marseille (AMU) -
# * Centre National de la Recherche Scientifique (CNRS) -
# * Université de Toulon (UTLN).
# * Copyright © 2019-2020 AMU, CNRS, UTLN
#
# Contributors:
# ------------
#
# * Sokol Koço <sokol.koco_AT_lis-lab.fr>
# * Cécile Capponi <cecile.capponi_AT_univ-amu.fr>
# * Florent Jaillet <florent.jaillet_AT_math.cnrs.fr>
# * Dominique Benielli <dominique.benielli_AT_univ-amu.fr>
# * Riikka Huusari <rikka.huusari_AT_univ-amu.fr>
# * Baptiste Bauvin <baptiste.bauvin_AT_univ-amu.fr>
# * Hachem Kadri <hachem.kadri_AT_lis-lab.fr>
#
# Description:
# -----------
#
# The multimodal package implement classifiers multiview,
# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
# -------
#
# * multimodal version = 0.0.dev0
#
# Licence:
# -------
#
# License: New BSD License
#
#
# ######### COPYRIGHT #########
from distutils.command.clean import clean as _clean
from distutils.dir_util import remove_tree
from distutils.command.sdist import sdist
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try:
import numpy
except:
raise 'Cannot build iw without numpy'
sys.exit()
# --------------------------------------------------------------------
# Clean target redefinition - force clean everything supprimer de la liste '^core\.*$',
relist = ['^.*~$', '^#.*#$', '^.*\.aux$', '^.*\.pyc$', '^.*\.o$']
reclean = []
USE_COPYRIGHT = True
try:
from copyright import writeStamp, eraseStamp
except ImportError:
USE_COPYRIGHT = False
###################
# Get Multimodal version
####################
def get_version():
v_text = open('VERSION').read().strip()
v_text_formted = '{"' + v_text.replace('\n', '","').replace(':', '":"')
v_text_formted += '"}'
v_dict = eval(v_text_formted)
return v_dict["multimodal"]
########################
# Set Multimodal __version__
########################
def set_version(multimodal_dir, version):
filename = os.path.join(multimodal_dir, '__init__.py')
buf = ""
for line in open(filename, "rb"):
if not line.decode("utf8").startswith("__version__ ="):
buf += line.decode("utf8")
f = open(filename, "wb")
f.write(buf.encode("utf8"))
f.write(('__version__ = "%s"\n' % version).encode("utf8"))
for restring in relist:
reclean.append(re.compile(restring))
def wselect(args, dirname, names):
for n in names:
for rev in reclean:
if (rev.match(n)):
os.remove("%s/%s" %(dirname, n))
break
######################
# Custom clean command
######################
class clean(_clean):
def walkAndClean(self):
os.walk("..", wselect, [])
pass
def run(self):
clean.run(self)
if os.path.exists('build'):
shutil.rmtree('build')
for dirpath, dirnames, filenames in os.walk('iw'):
for filename in filenames:
if (filename.endswith('.so') or
filename.endswith('.pyd') or
filename.endswith('.dll') or
filename.endswith('.pyc')):
os.unlink(os.path.join(dirpath, filename))
for dirname in dirnames:
if dirname == '__pycache__':
shutil.rmtree(os.path.join(dirpath, dirname))
##############################
# Custom sdist command
##############################
class m_sdist(sdist):
""" Build source package
WARNING : The stamping must be done on an default utf8 machine !
"""
def run(self):
if USE_COPYRIGHT:
writeStamp()
sdist.run(self)
# eraseStamp()
else:
sdist.run(self)
def setup_package():
"""Setup function"""
name = 'scikit-multimodallearn'
version = get_version()
multimodal_dir = 'multimodal'
set_version(multimodal_dir, 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 and Sokol Koço and Florent Jaillet and Riikka Huusari ' \
'and Baptiste Bauvin and Cécile Capponi and Hachem Kadri'
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',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Operating System :: Microsoft :: Windows',
'Operating System :: MacOS'],
keywords = ('machine learning, supervised learning, classification, '
'ensemble methods, boosting, kernel')
packages = find_packages(exclude=['*.tests'])
install_requires = ['scikit-learn>=0.24.2', 'numpy', 'scipy', 'cvxopt' ]
'doc': ['sphinx', 'numpydoc', 'sphinx_gallery', 'matplotlib', "sphinx_rtd_theme"]}
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()