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-rw-r--r--var/spack/repos/builtin/packages/py-numexpr3/package.py48
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+##############################################################################
+# Copyright (c) 2013-2018, Lawrence Livermore National Security, LLC.
+# Produced at the Lawrence Livermore National Laboratory.
+#
+# This file is part of Spack.
+# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
+# LLNL-CODE-647188
+#
+# For details, see https://github.com/spack/spack
+# Please also see the NOTICE and LICENSE files for our notice and the LGPL.
+#
+# This program is free software; you can redistribute it and/or modify
+# it under the terms of the GNU Lesser General Public License (as
+# published by the Free Software Foundation) version 2.1, February 1999.
+#
+# This program is distributed in the hope that it will be useful, but
+# WITHOUT ANY WARRANTY; without even the IMPLIED WARRANTY OF
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the terms and
+# conditions of the GNU Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this program; if not, write to the Free Software
+# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
+##############################################################################
+from spack import *
+
+
+class PyNumexpr3(PythonPackage):
+ """Numexpr3 is a fast numerical expression evaluator for NumPy. With it,
+ expressions that operate on arrays (like "3*a+4*b") are accelerated and
+ use less memory than doing the same calculation in Python.
+ In addition, its multi-threaded capabilities can make use of all your
+ cores, which may accelerate computations, most specially if they are not
+ memory-bounded (e.g. those using transcendental functions).
+ Compared to NumExpr 2.6, functions have been re-written in a fashion such
+ that gcc can auto-vectorize them with SIMD instruction sets such as
+ SSE2 or AVX2, if your processor supports them. Use of a newer version of
+ gcc such as 5.4 is strongly recommended."""
+ homepage = "https://github.com/pydata/numexpr/tree/numexpr-3.0"
+ url = "https://pypi.io/packages/source/n/numexpr3/numexpr3-3.0.1a1.tar.gz"
+
+ version('3.0.1.a1', '9fa8dc59b149aa1956fc755f982a78ad')
+ # TODO: Add CMake build system for better control of passing flags related
+ # to CPU ISA.
+
+ depends_on('python@2.6:2.8,3.3:', type=('build', 'run'))
+ depends_on('py-numpy@1.7:', type=('build', 'run'))
+ depends_on('py-setuptools@18.2:', type='build')