Commit 4ca6ab55 authored by Josef Hrabal's avatar Josef Hrabal

new file: a/alchemical-analysis/alchemical-analysis-1.0.1-Py-2.7.eb

	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
parent f26759fb
Pipeline #5739 passed with stage
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# IT4Innovations 2019
easyblock = 'PythonPackage'
name = 'alchemical-analysis'
version = '1.0.1'
homepage = 'https://github.com/MobleyLab/alchemical-analysis'
description = """An open tool implementing some recommended practices for analyzing alchemical free energy calculations"""
toolchain = {'name': 'Py', 'version': '2.7'}
source_urls = ['https://github.com/MobleyLab/alchemical-analysis/archive/']
sources = ['v%(version)s.tar.gz']
dependencies = [
('pymbar', '3.0.3'),
]
sanity_check_paths = {
'files': [],
'dirs': ['bin', 'lib/python2.7/site-packages/alchemical_analysis-%(version)s-py2.7.egg/'],
}
moduleclass = 'python'
# IT4Innovations 2019
easyblock = 'PythonPackage'
name = 'alchemlyb'
version = '0.1.0'
homepage = 'https://github.com/alchemistry/alchemlyb/'
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"""
toolchain = {'name': 'Py', 'version': '2.7'}
source_urls = ['https://github.com/alchemistry/alchemlyb/archive/']
sources = ['%(version)s.tar.gz']
dependencies = [
('numpy', '1.13.3'),
('scipy', '1.0.0'),
('pandas', '0.23.4'),
('pymbar', '3.0.3'),
]
sanity_check_paths = {
'files': [],
'dirs': ['bin', 'lib/python2.7/site-packages/'],
}
moduleclass = 'python'
# IT4Innovations 2019
easyblock = 'ConfigureMake'
name = 'gperftools'
version = '2.7'
homepage = 'http://github.com/gperftools/gperftools'
description = """gperftools are for use by developers so that they can create more robust applications.
Especially of use to those developing multi-threaded applications in C++ with templates.
Includes TCMalloc, heap-checker, heap-profiler and cpu-profiler."""
toolchain = {'name': 'dummy', 'version': ''}
source_urls = [
'https://github.com/gperftools/gperftools/releases/download/%(namelower)s-%(version)s']
sources = [SOURCE_TAR_GZ]
dependencies = [('libunwind', '1.2.1', '', True)]
configopts = '--enable-libunwind'
sanity_check_paths = {
'files': [
'bin/pprof',
'lib/libprofiler.a',
'lib/libprofiler.%s' %
SHLIB_EXT,
'lib/libtcmalloc.a',
'lib/libtcmalloc.%s' %
SHLIB_EXT],
'dirs': []}
modextrapaths = {'LD_PRELOAD': 'lib/libtcmalloc_minimal.so.4'}
moduleclass = 'tools'
# IT4Innovations 2019
name = 'HDF5'
version = '1.10.4'
versionsuffix = '-parallel'
homepage = 'http://www.hdfgroup.org/HDF5/'
description = """HDF5 is a unique technology suite that makes possible the management of
extremely large and complex data collections."""
toolchain = {'name': 'gompi', 'version': '2019.02'}
toolchainopts = {'pic': True}
source_urls = [
'https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-%(version_major_minor)s/hdf5-%(version)s/src']
sources = [SOURCELOWER_TAR_GZ]
configopts = " --enable-parallel --enable-shared "
configopts += " --enable-static --enable-fortran "
configopts += " --enable-hl --with-zlib=$EBROOTZLIB"
dependencies = [
('zlib', '1.2.11', '', True),
('Szip', '2.1', '', True),
]
moduleclass = 'data'
# IT4Innovations 2019
name = 'HDF5'
version = '1.10.4'
versionsuffix = '-parallel'
homepage = 'http://www.hdfgroup.org/HDF5/'
description = """HDF5 is a unique technology suite that makes possible the management of
extremely large and complex data collections."""
toolchain = {'name': 'intel', 'version': '2018a'}
toolchainopts = {'pic': True, 'usempi': True}
source_urls = [
'https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-%(version_major_minor)s/hdf5-%(version)s/src']
sources = [SOURCELOWER_TAR_GZ]
dependencies = [
('zlib', '1.2.11', '', True),
('Szip', '2.1', '', True),
]
moduleclass = 'data'
# IT4Innovations 2019
easyblock = 'PythonPackage'
name = 'h5py'
version = '2.9.0'
versionsuffix = '-Py-2.7'
homepage = 'http://www.h5py.org/'
description = """HDF5 for Python (h5py) is a general-purpose Python interface to the Hierarchical Data Format library,
version 5. HDF5 is a versatile, mature scientific software library designed for the fast, flexible storage of enormous
amounts of data."""
toolchain = {'name': 'intel', 'version': '2018a'}
toolchainopts = {'usempi': True}
source_urls = ['https://files.pythonhosted.org/packages/43/27/a6e7dcb8ae20a4dbf3725321058923fec262b6f7835179d78ccc8d98deec/']
sources = ['h5py-2.9.0.tar.gz']
dependencies = [
('HDF5', '1.10.4', '-parallel'),
('numpy', '1.15.4', '-Py-2.7', True),
('mpi4py', '3.0.0', '-Py-2.7'), # required for MPI support
('six', '1.11.0', '-Py-2.7', True),
('pkgconfig', '1.3.1', '-Py-2.7'),
('Cython', '0.27.3', '-Py-2.7', True),
]
prebuildopts = 'python setup.py configure --mpi --hdf5=$EBROOTHDF5 && '
sanity_check_paths = {
'files': [],
'dirs': ['lib/python2.7/site-packages/h5py-2.9.0-py2.7-linux-x86_64.egg'],
}
moduleclass = 'python'
# IT4Innovations 2017
easyblock = 'CmdCp'
name = 'LAMMPS'
version = '20181212'
homepage = 'http://lammps.sandia.gov'
description = """LAMMPS is a classical molecular dynamics code,
and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator.
Has potentials for solid-state materials (metals, semiconductors) and soft
matter (biomolecules, polymers) and coarse-grained or mesoscopic systems.
It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic,
meso, or continuum scale.
"""
toolchain = {'name': 'intel', 'version': '2017c'}
source_urls = ['https://github.com/lammps/lammps/archive']
sources = ['patch_22Jun2018.tar.gz']
dependencies = [
('tbb', '2017.6.196', '', True),
('gperftools', '2.7', '', True),
]
builddependencies = [
('Python', '2.7.13', '-base', True),
('CMake', '3.5.2', '', True),
]
commands = "cd src && make yes-kokkos && "
commands += "make yes-user-phonon && make yes-misc && "
commands += "make lib-reax args='-m ifort' && make yes-reax && "
commands += "make yes-kspace && make yes-manybody && make yes-molecule && "
commands += "make yes-qeq && make yes-rigid && make yes-user-misc && "
commands += "make yes-user-reaxc && make yes-user-omp && "
commands += "make -j 16 intel_cpu_intelmpi && mv lmp_intel_cpu_intelmpi lammps"
cmds_map = [('.*', commands)]
files_to_copy = [
(['src/lammps'], 'bin'),
]
sanity_check_paths = {
'files': ['bin/lammps'],
'dirs': [''],
}
moduleclass = 'chem'
# IT4Innovations 2018
easyblock = 'PythonPackage'
name = 'mpi4py'
version = '3.0.0'
versionsuffix = '-Py-2.7'
homepage = 'http://mpi4py.scipy.org/docs'
description = """MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for
the Python programming language, allowing any Python program to exploit multiple processors."""
toolchain = {'name': 'intel', 'version': '2018a'}
source_urls = [PYPI_SOURCE]
sources = [SOURCE_TAR_GZ]
dependencies = [
('Py', '2.7', '', True),
]
sanity_check_paths = {
'files': [],
'dirs': ['lib/python2.7/site-packages/mpi4py'],
}
moduleclass = 'python'
# IT4Innovations 2019
easyblock = "PythonPackage"
name = 'pandas'
version = '0.23.4'
homepage = 'https://pypi.python.org/pypi/pandas'
description = 'Powerful data structures for data analysis, time series,and statistics.'
toolchain = {'name': 'Py', 'version': '2.7'}
source_urls = [PYPI_SOURCE]
sources = [SOURCE_TAR_GZ]
dependencies = [
('numpy', '1.13.3'),
('pytz', '2018.9'),
('python-dateutil', '2.6.1'),
]
sanity_check_paths = {
'files': [],
'dirs': ['lib/python2.7/site-packages/%(name)s-%(version)s-py2.7-linux-x86_64.egg'], }
moduleclass = 'python'
# IT4Innovations 2019
easyblock = 'PythonPackage'
name = 'pkgconfig'
version = '1.3.1'
versionsuffix = '-Py-2.7'
homepage = 'http://github.com/matze/pkgconfig'
description = """pkgconfig is a Python module to interface with the pkg-config command line tool"""
toolchain = {'name': 'intel', 'version': '2018a'}
toolchainopts = {'usempi': True}
source_urls = [PYPI_SOURCE]
sources = [SOURCE_TAR_GZ]
checksums = ['0bc77e955a5990b466b7277234a88dc6a62f1f4388ac1e95469051c82a17fd80']
dependencies = [
('Py', '2.7', '', True),
('pkg-config', '0.29.2', '', True),
]
sanity_check_paths = {
'files': [],
'dirs': ['lib/python2.7/site-packages/'],
}
moduleclass = 'devel'
# IT4Innovations 2019
easyblock = 'PythonPackage'
name = 'pmx'
version = '20190115'
homepage = 'https://github.com/alchemistry/alchemlyb/'
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"""
toolchain = {'name': 'Py', 'version': '2.7'}
source_urls = ['https://github.com/deGrootLab/pmx/archive/']
sources = ['2016da08c4cea33bbca9ccd1f2094014110b7c6a.zip']
dependencies = [
('numpy', '1.13.3'),
('scipy', '1.0.0'),
('matplotlib', '2.1.1'),
]
sanity_check_paths = {
'files': [],
'dirs': ['lib/python2.7/site-packages/pmx'],
}
moduleclass = 'python'
# IT4Innovations 2019
easyblock = 'PythonPackage'
name = 'pymbar'
version = '3.0.3'
homepage = 'https://github.com/MobleyLab/alchemical-analysis'
description = """An open tool implementing some recommended practices for analyzing alchemical free energy calculations"""
toolchain = {'name': 'Py', 'version': '2.7'}
source_urls = ['https://github.com/choderalab/pymbar/archive/']
sources = ['%(version)s.tar.gz']
dependencies = [
('numpy', '1.13.3'),
('six' , '1.11.0'),
('scipy', '1.0.0'),
]
sanity_check_paths = {
'files': [],
'dirs': ['lib/python2.7/site-packages/'],
}
moduleclass = 'python'
# IT4Innovations 2019
easyblock = "PythonPackage"
name = 'pytz'
version = '2018.9'
homepage = 'http://pytz.sourceforge.net/'
description = """pytz brings the Olson tz database into Python. This library allows
accurate and cross platform timezone calculations using Python 2.4 or higher."""
toolchain = {'name': 'Py', 'version': '2.7'}
source_urls = ['https://files.pythonhosted.org/packages/af/be/6c59e30e208a5f28da85751b93ec7b97e4612268bb054d0dff396e758a90/']
sources = ['%(name)s-%(version)s.tar.gz']
sanity_check_paths = {
'files': ['lib/python2.7/site-packages/%(name)s-%(version)s-py2.7.egg'],
'dirs': [],
}
moduleclass = 'python'
......@@ -19,13 +19,21 @@ dependencies = [
('CMake', '3.13.1', '', True),
('libxml2', '2.9.4', '', True),
('Boost', '1.68.0', '-serial'),
('HDF5', '1.10.4', '-serial')
('HDF5', '1.10.4', '-parallel'),
('h5py', '2.9.0', '-Py-2.7'),
]
separate_build_dir = True
configopts = ' -DENABLE_SOA=1 '
#preinstallopts = [
# #'cp %(builddir)s/easybuild_obj/ %(installdir)s/build -R',
# 'cd %(builddir)s/easybuild_obj/ && ',
# 'ctest -R deterministic -LE unstable && ',
# 'ctest -R short -LE unstable && '
#]
sanity_check_paths = {
'files': ['bin/qmcpack'],
'dirs': ['bin'],
......
# IT4Innovations 2019
easyblock = 'PythonPackage'
name = 'scikit-learn'
version = '0.20.2'
homepage = 'http://scikit-learn.org/stable/index.html'
description = """Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world,
building upon numpy, scipy, and matplotlib. As a machine-learning module,
it provides versatile tools for data mining and analysis in any field of science and engineering.
It strives to be simple and efficient, accessible to everybody, and reusable in various contexts."""
toolchain = {'name': 'Py', 'version': '2.7'}
source_urls = [PYPI_SOURCE]
sources = [SOURCE_TAR_GZ]
dependencies = [
('matplotlib', '2.1.1'),
('numpy', '1.13.3'),
('scipy', '1.0.0'),
('scikit-image', '0.14.1'),
('Tk', '8.6.6', '', True),
]
options = {'modulename': 'sklearn'}
sanity_check_paths = {
'files': [],
'dirs': ['lib/python3.6/site-packages/sklearn'],
}
moduleclass = 'python'
# IT4Innovations 2019
name = 'tbb'
version = '2018_U5'
homepage = 'https://01.org/tbb/'
description = """Intel(R) Threading Building Blocks (Intel(R) TBB) lets you easily write parallel C++ programs that
take full advantage of multicore performance, that are portable, composable and have future-proof scalability."""
toolchain = {'name': 'intel', 'version': '2017c'}
source_urls = ['https://github.com/01org/tbb/archive/']
sources = ['%(version)s.tar.gz']
checksums = ['c4c2896af527392496c5e01ef8579058a71b6eebbd695924cd138841c13f07be']
builddependencies = [
('binutils', '2.31.1', '', True)
]
moduleclass = 'lib'
......@@ -18,7 +18,7 @@ source_urls = [
dependencies = [
('bzip2', '1.0.6'),
('fontconfig', '2.13.0', '-libpng-1.6.34'),
('fontconfig', '2.13.0'),
('freetype', '2.9.1', '-libpng-1.6.34'),
('zlib', '1.2.11'),
]
......
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