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new file: a/alchemlyb/alchemlyb-0.1.0-Py-2.7.eb new file: g/gperftools/gperftools-2.7.eb new file: h/HDF5/HDF5-1.10.4-gompi-2019.02-parallel.eb new file: h/HDF5/HDF5-1.10.4-intel-2018a-parallel.eb new file: h/h5py/h5py-2.9.0-intel-2018a-Py-2.7.eb new file: l/LAMMPS/LAMMPS-20181212-intel-2017c.eb new file: m/mpi4py/mpi4py-3.0.0-intel-2018a-Py-2.7.eb new file: p/pandas/pandas-0.23.4-Py-2.7.eb new file: p/pkgconfig/pkgconfig-1.3.1-intel-2018a-Py-2.7.eb new file: p/pmx/pmx-20190115-Py-2.7.eb new file: p/pymbar/pymbar-3.0.3-Py-2.7.eb new file: p/pytz/pytz-2018.9-Py-2.7.eb modified: q/QMCPACK/QMCPACK-3.6.0-intel-2018a.eb new file: s/scikit-learn/scikit-learn-0.20.2-Py-2.7.eb new file: t/tbb/tbb-2018_U5-intel-2017c.eb modified: x/X11/X11-20170314.eb
28 lines
689 B
Plaintext
28 lines
689 B
Plaintext
# IT4Innovations 2019
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easyblock = 'PythonPackage'
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name = 'pmx'
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version = '20190115'
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homepage = 'https://github.com/alchemistry/alchemlyb/'
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description = """alchemlyb is an attempt to make alchemical free energy calculations easier to do by leveraging the full power and flexibility of the PyData stack"""
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toolchain = {'name': 'Py', 'version': '2.7'}
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source_urls = ['https://github.com/deGrootLab/pmx/archive/']
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sources = ['2016da08c4cea33bbca9ccd1f2094014110b7c6a.zip']
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dependencies = [
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('numpy', '1.13.3'),
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('scipy', '1.0.0'),
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('matplotlib', '2.1.1'),
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]
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sanity_check_paths = {
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'files': [],
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'dirs': ['lib/python2.7/site-packages/pmx'],
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}
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moduleclass = 'python'
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