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#!/usr/bin/env python
# Copyright (C) 2011-2020 Alexandre Gramfort
# <alexandre.gramfort@inria.fr>
import os
import os.path as op
from setuptools import setup
def parse_requirements_file(fname):
requirements = list()
with open(fname, 'r') as fid:
for line in fid:
req = line.strip()
if req.startswith('#'):
continue
# strip end-of-line comments
req = req.split('#', maxsplit=1)[0].strip()
requirements.append(req)
return requirements
# get the version (don't import mne here, so dependencies are not needed)
version = None
with open(op.join('mne', '_version.py'), 'r') as fid:
for line in (line.strip() for line in fid):
if line.startswith('__version__'):
version = line.split('=')[1].strip().strip('\'')
break
if version is None:
raise RuntimeError('Could not determine version')
DISTNAME = 'mne'
DESCRIPTION = 'MNE-Python project for MEG and EEG data analysis.'
MAINTAINER = 'Alexandre Gramfort'
MAINTAINER_EMAIL = 'alexandre.gramfort@inria.fr'
URL = 'https://mne.tools/dev/'
LICENSE = 'BSD-3-Clause'
DOWNLOAD_URL = 'http://github.com/mne-tools/mne-python'
VERSION = version
def package_tree(pkgroot):
"""Get the submodule list."""
# Adapted from VisPy
path = op.dirname(__file__)
subdirs = [op.relpath(i[0], path).replace(op.sep, '.')
for i in os.walk(op.join(path, pkgroot))
if '__init__.py' in i[2]]
return sorted(subdirs)
if __name__ == "__main__":
if op.exists('MANIFEST'):
os.remove('MANIFEST')
with open('README.rst', 'r') as fid:
long_description = fid.read()
# data_dependencies is empty, but let's leave them so that we don't break
# people's workflows who did `pip install mne[data]`
install_requires = parse_requirements_file('requirements_base.txt')
data_requires = []
hdf5_requires = parse_requirements_file('requirements_hdf5.txt')
test_requires = (parse_requirements_file('requirements_testing.txt') +
parse_requirements_file('requirements_testing_extra.txt'))
setup(name=DISTNAME,
maintainer=MAINTAINER,
include_package_data=True,
maintainer_email=MAINTAINER_EMAIL,
description=DESCRIPTION,
license=LICENSE,
url=URL,
version=VERSION,
download_url=DOWNLOAD_URL,
long_description=long_description,
long_description_content_type='text/x-rst',
zip_safe=False, # the package can run out of an .egg file
classifiers=['Intended Audience :: Science/Research',
'Intended Audience :: Developers',
'License :: OSI Approved',
'Programming Language :: Python',
'Topic :: Software Development',
'Topic :: Scientific/Engineering',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX',
'Operating System :: Unix',
'Operating System :: MacOS',
'Programming Language :: Python :: 3',
],
keywords='neuroscience neuroimaging MEG EEG ECoG fNIRS brain',
project_urls={
'Documentation': 'https://mne.tools/',
'Source': 'https://github.com/mne-tools/mne-python/',
'Tracker': 'https://github.com/mne-tools/mne-python/issues/',
},
platforms='any',
python_requires='>=3.7',
install_requires=install_requires,
extras_require={
'data': data_requires,
'hdf5': hdf5_requires,
'test': test_requires,
},
packages=package_tree('mne'),
package_data={'mne': [
op.join('data', 'eegbci_checksums.txt'),
op.join('data', '*.sel'),
op.join('data', 'icos.fif.gz'),
op.join('data', 'coil_def*.dat'),
op.join('data', 'helmets', '*.fif.gz'),
op.join('data', 'FreeSurferColorLUT.txt'),
op.join('data', 'image', '*gif'),
op.join('data', 'image', '*lout'),
op.join('data', 'fsaverage', '*.fif'),
op.join('channels', 'data', 'layouts', '*.lout'),
op.join('channels', 'data', 'layouts', '*.lay'),
op.join('channels', 'data', 'montages', '*.sfp'),
op.join('channels', 'data', 'montages', '*.txt'),
op.join('channels', 'data', 'montages', '*.elc'),
op.join('channels', 'data', 'neighbors', '*.mat'),
op.join('datasets', 'sleep_physionet', 'SHA1SUMS'),
op.join('datasets', '_fsaverage', '*.txt'),
op.join('datasets', '_infant', '*.txt'),
op.join('datasets', '_phantom', '*.txt'),
op.join('html', '*.js'),
op.join('html', '*.css'),
op.join('html_templates', 'repr', '*.jinja'),
op.join('html_templates', 'report', '*.jinja'),
op.join('icons', '*.svg'),
op.join('icons', '*.png'),
op.join('io', 'artemis123', 'resources', '*.csv'),
op.join('io', 'edf', 'gdf_encodes.txt')
]},
entry_points={'console_scripts': [
'mne = mne.commands.utils:main',
]})
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