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# Copyright 2013-2018 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
import platform
class PyNumpy(PythonPackage):
"""NumPy is the fundamental package for scientific computing with Python.
It contains among other things: a powerful N-dimensional array object,
sophisticated (broadcasting) functions, tools for integrating C/C++ and
Fortran code, and useful linear algebra, Fourier transform, and random
number capabilities"""
homepage = "http://www.numpy.org/"
url = "https://pypi.io/packages/source/n/numpy/numpy-1.15.1.zip"
install_time_test_callbacks = ['install_test', 'import_module_test']
import_modules = [
'numpy', 'numpy.compat', 'numpy.core', 'numpy.distutils', 'numpy.doc',
'numpy.f2py', 'numpy.fft', 'numpy.lib', 'numpy.linalg', 'numpy.ma',
'numpy.matrixlib', 'numpy.polynomial', 'numpy.random', 'numpy.testing',
'numpy.distutils.command', 'numpy.distutils.fcompiler'
]
version('1.15.2', sha256='27a0d018f608a3fe34ac5e2b876f4c23c47e38295c47dd0775cc294cd2614bc1')
version('1.15.1', '898004d5be091fde59ae353e3008fe9b')
version('1.14.3', '97416212c0a172db4bc6b905e9c4634b')
version('1.14.2', '080f01a19707cf467393e426382c7619')
version('1.14.1', 'b8324ef90ac9064cd0eac46b8b388674')
version('1.14.0', 'c12d4bf380ac925fcdc8a59ada6c3298')
version('1.13.3', '300a6f0528122128ac07c6deb5c95917')
version('1.13.1', '2c3c0f4edf720c3a7b525dacc825b9ae')
version('1.13.0', 'fd044f0b8079abeaf5e6d2e93b2c1d03')
version('1.12.1', 'c75b072a984028ac746a6a332c209a91')
version('1.12.0', '33e5a84579f31829bbbba084fe0a4300')
version('1.11.2', '8308cc97be154d2f64a2387ea863c2ac')
version('1.11.1', '5caa3428b24aaa07e72c79d115140e46')
version('1.11.0', '19ce5c4eb16d663a0713daf0018a3021')
version('1.10.4', '510ffc322c635511e7be95d225b6bcbb')
version('1.9.2', 'e80c19d2fb25af576460bb7dac31c59a')
version('1.9.1', '223532d8e1bdaff5d30936439701d6e1')
variant('blas', default=True, description='Build with BLAS support')
variant('lapack', default=True, description='Build with LAPACK support')
depends_on('python@2.7:2.8,3.4:', type=('build', 'run'))
depends_on('py-setuptools', type='build')
depends_on('blas', when='+blas')
depends_on('lapack', when='+lapack')
depends_on('py-nose@1.0.0:', when='@:1.14', type='test')
depends_on('py-pytest', when='@1.15:', type='test')
def setup_dependent_package(self, module, dependent_spec):
python_version = self.spec['python'].version.up_to(2)
self.spec.include = join_path(
self.prefix.lib,
'python{0}'.format(python_version),
'site-packages',
'numpy/core/include')
def patch(self):
spec = self.spec
# for build notes see http://www.scipy.org/scipylib/building/linux.html
lapackblas = LibraryList('')
if '+lapack' in spec:
lapackblas += spec['lapack'].libs
if '+blas' in spec:
lapackblas += spec['blas'].libs
if '+blas' in spec or '+lapack' in spec:
# note that one should not use [blas_opt] and [lapack_opt], see
# https://github.com/numpy/numpy/commit/ffd4332262ee0295cb942c94ed124f043d801eb6
with open('site.cfg', 'w') as f:
# Unfortunately, numpy prefers to provide each BLAS/LAPACK
# differently.
names = ','.join(lapackblas.names)
dirs = ':'.join(lapackblas.directories)
# Special treatment for some (!) BLAS/LAPACK. Note that
# in this case library_dirs can not be specified within [ALL].
if '^openblas' in spec:
f.write('[openblas]\n')
f.write('libraries=%s\n' % names)
elif '^mkl' in spec:
# numpy does not expect system libraries needed for MKL
# here.
# names = [x for x in names if x.startswith('mkl')]
# FIXME: as of @1.11.2, numpy does not work with separately
# specified threading and interface layers. A workaround is
# a terribly bad idea to use mkl_rt. In this case Spack
# will no longer be able to guarantee that one and the
# same variant of Blas/Lapack (32/64bit, threaded/serial)
# is used within the DAG. This may lead to a lot of
# hard-to-debug segmentation faults on user's side. Users
# may also break working installation by (unconsciously)
# setting environment variable to switch between different
# interface and threading layers dynamically. From this
# perspective it is no different from throwing away RPATH's
# and using LD_LIBRARY_PATH throughout Spack.
f.write('[mkl]\n')
f.write('mkl_libs=%s\n' % 'mkl_rt')
elif '^atlas' in spec:
f.write('[atlas]\n')
f.write('atlas_libs=%s\n' % names)
else:
# The section title for the defaults changed in @1.10, see
# https://github.com/numpy/numpy/blob/master/site.cfg.example
if spec.satisfies('@:1.9.2'):
f.write('[DEFAULT]\n')
else:
f.write('[ALL]\n')
f.write('libraries=%s\n' % names)
f.write('library_dirs=%s\n' % dirs)
if not ((platform.system() == "Darwin") and
(platform.mac_ver()[0] == '10.12')):
f.write('rpath=%s\n' % dirs)
def build_args(self, spec, prefix):
args = []
# From NumPy 1.10.0 on it's possible to do a parallel build.
if self.version >= Version('1.10.0'):
# But Parallel build in Python 3.5+ is broken. See:
# https://github.com/spack/spack/issues/7927
# https://github.com/scipy/scipy/issues/7112
if spec['python'].version < Version('3.5'):
args = ['-j', str(make_jobs)]
return args
def setup_environment(self, spack_env, run_env):
python_version = self.spec['python'].version.up_to(2)
include_path = join_path(
self.prefix.lib,
'python{0}'.format(python_version),
'site-packages',
'numpy/core/include')
run_env.prepend_path('CPATH', include_path)
def test(self):
# `setup.py test` is not supported. Use one of the following
# instead:
#
# - `python runtests.py` (to build and test)
# - `python runtests.py --no-build` (to test installed numpy)
# - `>>> numpy.test()` (run tests for installed numpy
# from within an interpreter)
pass
def install_test(self):
# Change directories due to the following error:
#
# ImportError: Error importing numpy: you should not try to import
# numpy from its source directory; please exit the numpy
# source tree, and relaunch your python interpreter from there.
with working_dir('spack-test', create=True):
python('-c', 'import numpy; numpy.test("full", verbose=2)')
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