easyblock = 'MakeCp'

name = 'MPI-LIBLINEAR'
version = '2.1-1'

homepage = 'https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/distributed-liblinear/mpi/'
description = """MPI LIBLINEAR is an extension of LIBLINEAR on distributed environments. The usage and the data format are the same as LIBLINEAR.
It supports L2-regularized logistic regression, L2-regularized logistic regression, L2-regularized L2-loss linear SVM (primal trust-region Newton),
L2-regularized L1-loss linear SVM (dual), L2-regularized logistic regression (primal limited common directions),
L2-regularized L2-loss linear SVM (primal limited common directions). Module created by the PERMON Team (http://permon.it4i.cz)."""

toolchain = {'name': 'intel', 'version': '2017a'}

source_urls = [homepage]
sources = [SOURCELOWER_ZIP]

patches = ['INTEL_parallel-make.patch']

files_to_copy = [(['train', 'predict', 'split.py'], 'bin')]

sanity_check_paths = {
    'files': ['bin/%s' % x for x in ['train', 'predict', 'split.py']],
    'dirs': [],
}

modextrapaths = {
    'PATH': ['bin'],
}

moduleclass = 'numlib'