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pkgsrc/math/py-numpy/Makefile

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Use python correctly.
2011-04-19 15:14:28 +02:00
# $NetBSD: Makefile,v 1.13 2011/04/19 13:14:28 roy Exp $
Initial import of py-numpy 1.1.0 NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Pkgsrc issue: if the package build happens to find a fortran it prefers over the one pkgsrc is using it will try to use it and the wrong thing will happen.
2008-12-19 23:04:36 +01:00
#
Update to 1.4.1. From Wen Heping in PR pkg/43204. This minor release removes datetime support, which fixes the binary incompatibility issues with SciPy and other packages. It also includes several bug fixes. No new features are introduced. Bugs fixed ---------- - #1336: Fix for 1299 exposes Bus error on Sparc - #1379: CPU ID not set correctly on PARISC - #1388: frombuffer calls PyErr_Format without throwing an error - log1p - kaiser for M=1 - paver execution on Windows 7 for Python 2.6 - several fixes to Chebyshev and Polynomial
2010-04-24 19:13:55 +02:00
DISTNAME= numpy-1.4.1
Use python correctly.
2011-04-19 15:14:28 +02:00
PKGREVISION= 1
Update to 1.4.1. From Wen Heping in PR pkg/43204. This minor release removes datetime support, which fixes the binary incompatibility issues with SciPy and other packages. It also includes several bug fixes. No new features are introduced. Bugs fixed ---------- - #1336: Fix for 1299 exposes Bus error on Sparc - #1379: CPU ID not set correctly on PARISC - #1388: frombuffer calls PyErr_Format without throwing an error - log1p - kaiser for M=1 - paver execution on Windows 7 for Python 2.6 - several fixes to Chebyshev and Polynomial
2010-04-24 19:13:55 +02:00
PKGNAME= ${PYPKGPREFIX}-numpy-1.4.1
Initial import of py-numpy 1.1.0 NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Pkgsrc issue: if the package build happens to find a fortran it prefers over the one pkgsrc is using it will try to use it and the wrong thing will happen.
2008-12-19 23:04:36 +01:00
CATEGORIES= math python
MASTER_SITES= ${MASTER_SITE_SOURCEFORGE:=numpy/}
MAINTAINER= pkgsrc-users@NetBSD.org
HOMEPAGE= http://numpy.scipy.org/
COMMENT= Array processing for numbers, strings, records, and objects
Added LICENSE information.
2010-01-30 17:27:59 +01:00
LICENSE= modified-bsd
Initial import of py-numpy 1.1.0 NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Pkgsrc issue: if the package build happens to find a fortran it prefers over the one pkgsrc is using it will try to use it and the wrong thing will happen.
2008-12-19 23:04:36 +01:00
user-destdir support.
2008-12-19 23:09:55 +01:00
PKG_DESTDIR_SUPPORT= user-destdir
Initial import of py-numpy 1.1.0 NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Pkgsrc issue: if the package build happens to find a fortran it prefers over the one pkgsrc is using it will try to use it and the wrong thing will happen.
2008-12-19 23:04:36 +01:00
PYDISTUTILSPKG= yes
"fortran" -> "fortran77" except where it is clear that it isn't F77. "fortran" is alias of "fortran77" for now, but it will change later.
2010-07-30 12:36:22 +02:00
USE_LANGUAGES+= c fortran77
Initial import of py-numpy 1.1.0 NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Pkgsrc issue: if the package build happens to find a fortran it prefers over the one pkgsrc is using it will try to use it and the wrong thing will happen.
2008-12-19 23:04:36 +01:00
PLIST_SUBST+= PYVERSSUFFIX=${PYVERSSUFFIX}
MAKE_ENV+= ATLAS=None
Use python correctly.
2011-04-19 15:14:28 +02:00
REPLACE_PYTHON+= *.py */*.py */*/*.py */*/*/*.py */*/*/*/*.py
SUBST_CLASSES+= numpy
SUBST_STAGE.numpy= post-patch
SUBST_FILES.numpy= numpy/f2py/setup.py numpy/f2py/setupscons.py
SUBST_SED.numpy= -e 's:/usr/bin/env %s:${PYTHONBIN}:'
SUBST_SED.numpy+= -e 's:%(os.path.basename(sys.executable))::'
Add a few REPLACE_PYTHON. Bump PKGREVISION.
2009-09-10 21:03:26 +02:00
Avoid picking up other fortran compilers when they are installed. Fixes build when lang/g95 is present on the system.
2009-10-24 16:22:49 +02:00
# XXX Avoid picking up other compilers when installed
.include "../../mk/compiler.mk"
Fix so works again with non-default values of PKGSRC_FORTRAN.
2009-12-04 22:23:22 +01:00
.if defined(PKGSRC_FORTRAN) && !empty(PKGSRC_FORTRAN:Mg95)
PYSETUPBUILDARGS+= --fcompiler=g95
.elif defined(PKGSRC_FORTRAN) && !empty(PKGSRC_FORTRAN:Mgfortran)
PYSETUPBUILDARGS+= --fcompiler=gnu95
.elif !empty(PKGSRC_COMPILER:Mgcc)
Avoid picking up other fortran compilers when they are installed. Fixes build when lang/g95 is present on the system.
2009-10-24 16:22:49 +02:00
PYSETUPBUILDARGS+= --fcompiler=gnu
.endif
update to 1.4.0 changes: - Faster import time - Extended array wrapping mechanism for ufuncs - New Neighborhood iterator (C-level only) - C99-like complex functions in npymath, and a lot of portability fixes for basic floating point math functions
2010-01-27 21:48:20 +01:00
# needs devel/py-nose
#do-test:
# ${PYTHONBIN} -c "import numpy; numpy.test()"
Add a few REPLACE_PYTHON. Bump PKGREVISION.
2009-09-10 21:03:26 +02:00
.include "../../lang/python/application.mk"
Initial import of py-numpy 1.1.0 NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Pkgsrc issue: if the package build happens to find a fortran it prefers over the one pkgsrc is using it will try to use it and the wrong thing will happen.
2008-12-19 23:04:36 +01:00
.include "../../lang/python/extension.mk"
.include "../../math/blas/buildlink3.mk"
.include "../../math/lapack/buildlink3.mk"
.include "../../mk/bsd.pkg.mk"
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