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{bio}[foss/2023a] Cellformer v20240917 w/ R 4.3.2 #21621

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Original file line number Diff line number Diff line change
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easyblock = 'Tarball'

name = 'Cellformer'
version = '20240917'
versionsuffix = '-R-%(rver)s'
local_commit = '99a1165'

homepage = 'https://github.com/elo-nsrb/Cellformer'
description = '''An implementation of Cellformer from our publication: Berson et al.
"Whole genome deconvolution unveils Alzheimer’s resilient epigenetic signature"'''

toolchain = {'name': 'foss', 'version': '2023a'}

source_urls = ['https://github.com/elo-nsrb/Cellformer/archive/']
sources = [{'download_filename': '%s.tar.gz' % local_commit, 'filename': '%(name)s-%(version)s.tar.gz'}]
checksums = ['7cbddad75a4d47dfc0a39cd660ef20fe4e3cb755631b1b96136c1c3d5226c914']

dependencies = [
('Python', '3.11.3'),
('PyTorch', '2.1.2'),
('PyTorch-bundle', '2.1.2'),
('scikit-learn', '1.3.1'),
('PyTorch-Lightning', '2.2.1'),
('anndata', '0.10.5.post1'),
('h5py', '3.9.0'),
('SciPy-bundle', '2023.07'),
('Seaborn', '0.13.2'),
('tensorboard', '2.15.1'),
('tensorboardX', '2.6.2.2'),
('torchvision', '0.16.0'),
('tqdm', '4.66.1'),
('scanpy', '1.9.8'),
('pretty-yaml', '24.7.0'),
('Arrow', '14.0.1'),
('R', '4.3.2'),
('R-bundle-CRAN', '2023.12'),
('R-bundle-Bioconductor', '3.18', versionsuffix),
('ArchR', '1.0.2', versionsuffix),
('typing-extensions', '4.9.0'),
('einops', '0.7.0'),
]

exts_defaultclass = 'PythonPackage'
exts_default_options = {
'source_urls': [PYPI_SOURCE],
'download_dep_fail': True,
'use_pip': True,
'sanity_pip_check': True,
'installopts': '',
}

exts_list = [
('asteroid_filterbanks', '0.4.0', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['4932ac8b6acc6e08fb87cbe8ece84215b5a74eee284fe83acf3540a72a02eaf5'],
}),
('huggingface_hub', '0.25.2', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['1897caf88ce7f97fe0110603d8f66ac264e3ba6accdf30cd66cc0fed5282ad25'],
}),
('julius', '0.2.7', {
'checksums': ['3c0f5f5306d7d6016fcc95196b274cae6f07e2c9596eed314e4e7641554fbb08'],
}),
('cached_property', '1.5.2', {
'source_tmpl': SOURCE_WHL,
'checksums': ['df4f613cf7ad9a588cc381aaf4a512d26265ecebd5eb9e1ba12f1319eb85a6a0'],
}),
('mir_eval', '0.7', {
'checksums': ['e1febaa5766c65a7545c2a170b241490f47a98987370b1e06742424c5debe65e'],
}),
('pesq', '0.0.4', {
'checksums': ['b724b28f73fb638522982bd68e8c3c0957e2f45210639a460233b17aa7fc890b'],
}),
('pb_bss_eval', '0.0.2', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['a72c2fd04c9f4a4e734cf615029c3877e6e4536225eeaaae05bb0cf014b3af1b'],
}),
('soundfile', '0.12.1', {
'source_tmpl': SOURCE_WHL,
'checksums': ['828a79c2e75abab5359f780c81dccd4953c45a2c4cd4f05ba3e233ddf984b882'],
}),
('pytorch_ranger', '0.1.1', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['1e69156c9cc8439185cb8ba4725b18c91947fbe72743e25aca937da8aeb0c8ec'],
}),
('torch_optimizer', '0.1.0', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['b7adaed38b66a5c5105a59b30a71c4ab7c9954baf0acabd969fee3dac954657d'],
}),
('pystoi', '0.4.1', {
'source_tmpl': SOURCE_WHL,
'checksums': ['e277b671663d26d35a2416c9c8010a74084e6c3970354506398051a554896939'],
}),
('torch_stoi', '0.2.3', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['6eee85e33b42fe843a2150de46000f72e7b87cbeb19ae6ab9bbd94b6ec6b3cd2'],
}),
('torchmetrics', '1.4.3', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['76e67490231acef7f70cf36ab129df72fb2b0256dada7051001ab3b9f8699bf4'],
}),
('asteroid', '0.7.0', {
# requirement too strict
'preinstallopts': "sed -i 's/torchmetrics<=0.11.4/torchmetrics/g' setup.py && ",
'checksums': ['0326f28c5342495cb08ba0520efd0e21e39435dfd78854837fdd5a6c9c9ca410'],
}),
('everett', '3.1.0', {
'source_tmpl': SOURCE_WHL,
'checksums': ['db13891b849e45e54faea93ee79881d12458c5378f5b9b7f806eeff03ce1de3c'],
}),
('configobj', '5.0.9', {
'checksums': ['03c881bbf23aa07bccf1b837005975993c4ab4427ba57f959afdd9d1a2386848'],
}),
('python_box', '6.1.0', {
'modulename': 'box',
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['bdec0a5f5a17b01fc538d292602a077aa8c641fb121e1900dff0591791af80e8'],
}),
('sentry_sdk', '2.15.0', {
'source_tmpl': SOURCE_WHL,
'checksums': ['8fb0d1a4e1a640172f31502e4503543765a1fe8a9209779134a4ac52d4677303'],
}),
('wurlitzer', '3.1.1', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['0b2749c2cde3ef640bf314a9f94b24d929fe1ca476974719a6909dfc568c3aac'],
}),
('comet_ml', '3.47.0', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['81062bbef2d0758c8e77d8a469824d2c20ec13b09855c78b51b078203628b8c2'],
}),
('fast_histogram', '0.14', {
'checksums': ['390973b98af22bda85c29dcf6f008ba0d626321e9bd3f5a9d7a43e5690ea69ea'],
}),
('mpl_scatter_density', '0.7', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['721b4efeafcbc0ba4a5c1ecd8f401dc2d1aa6a372445c5b49e1da34e70a95ead'],
}),
('tensorboard_data_server', '0.7.0', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['753d4214799b31da7b6d93837959abebbc6afa86e69eacf1e9a317a48daa31eb'],
}),
('tensorboard_plugin_wit', '1.8.1', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['ff26bdd583d155aa951ee3b152b3d0cffae8005dc697f72b44a8e8c2a77a8cbe'],
}),
('torchmetrics', '1.4.2', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['87b9eca51ff6f93985a0f9db509f646cb45425b016f4d2f383d8c28d40dde5b6'],
}),
('torchmetrics', '0.11.4', {
'source_tmpl': SOURCE_PY3_WHL,
'checksums': ['45f892f3534e91f3ad9e2488d1b05a93b7cb76b7d037969435a41a1f24750d9a'],
}),
]

modextrapaths = {
'PATH': '',
'PYTHONPATH': 'lib/python%(pyshortver)s/site-packages',
}

fix_python_shebang_for = [
'src/*/*.py',
'src/*/*/*.py',
'src/*/*/*/*.py',
]

local_scripts = [
'createPeakMatrix.sh',
'createDataset.sh',
'deconvolution.sh',
'trainModel.sh',
'validation.sh',
]

postinstallcmds = [
"sed -i 's|python |python %(installdir)s/|g' %(installdir)s/*.sh"
] + ['chmod a+rx %%(installdir)s/%s' % script for script in local_scripts]

sanity_check_paths = {
'files': local_scripts,
'dirs': ['lib/python%(pyshortver)s/site-packages'],
}

sanity_check_commands = ["%s --help | grep '^Usage:'" % script for script in local_scripts]

moduleclass = 'bio'
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