Upgraded to 1.8.1 so I could build with OpenBLAS.
Fixed a typo while I was here.
---
testing/py-numpy/APKBUILD | 17 +++--testing/py-numpy/site.cfg | 157 ++++++++++++++++++++++++++++++++++++++++++++++
2 files changed, 168 insertions(+), 6 deletions(-)
create mode 100644 testing/py-numpy/site.cfg
diff --git a/testing/py-numpy/APKBUILD b/testing/py-numpy/APKBUILD
index a590ba1..db7f1f8 100644
--- a/testing/py-numpy/APKBUILD+++ b/testing/py-numpy/APKBUILD
@@ -2,7 +2,7 @@
# Maintainer: Francesco Colista <francesco.colista@gmail.com>
pkgname=py-numpy
_pkgname=numpy
-pkgver=1.7.1+pkgver=1.8.1pkgrel=0
pkgdesc="Scientific tools for Python"
url="http://numpy.scipy.org/"
@@ -13,7 +13,8 @@ depends_dev="python-dev"
makedepends="$depends_dev"
install=""
subpackages="$pkgname-dev $pkgname-doc"
-source="http://downloads.sourceforge.net/$_pkgname/$_pkgname-$pkgver.tar.gz"+source="http://downloads.sourceforge.net/$_pkgname/$_pkgname-$pkgver.tar.gz+ site.cfg"_builddir="$srcdir"/$_pkgname-$pkgver
prepare() {
@@ -22,13 +23,14 @@ prepare() {
for i in $source; do
case $i in
*.patch) msg $i; patch -p1 -i "$srcdir"/$i || return 1;;
+ site.cfg) msg $i; cp "$srcdir"/$i ./ || return 1;; esac
done
}
build() {
cd "$_builddir"
- export Atles=None+ export Atlas=None LDFLAGS="$LDFLAGS -shared"
python setup.py build config_fc --fcompiler=gnu95 || return 1
}
@@ -41,6 +43,9 @@ package() {
install -m644 LICENSE.txt "$pkgdir"/usr/share/licenses/custom/$pkgname/LICENSE
}
-md5sums="0ab72b3b83528a7ae79c6df9042d61c6 numpy-1.7.1.tar.gz"-sha256sums="5525019a3085c3d860e6cfe4c0a30fb65d567626aafc50cf1252a641a418084a numpy-1.7.1.tar.gz"-sha512sums="d58177f3971b6d07baf6f81a2088ba371c7e43ea64ee7ada261da97c6d725b4bd4927122ac373c55383254e4e31691939276dab08a79a238bfa55172a3eff684 numpy-1.7.1.tar.gz"+md5sums="be95babe263bfa3428363d6db5b64678 numpy-1.8.1.tar.gz+6f15bb8fe3d12faa8983a9e18bbea2a9 site.cfg"+sha256sums="3d722fc3ac922a34c50183683e828052cd9bb7e9134a95098441297d7ea1c7a9 numpy-1.8.1.tar.gz+8aa71c1aec2a9fdf6ab6167c92e86bdaf27f9a263b6b9849097ec7dcdf6d91a3 site.cfg"+sha512sums="39ef9e13f8681a2c2ba3d74ab96fd28c5669e653308fd1549f262921814fa7c276ce6d9fb65ef135006584c608bdf3db198d43f66c9286fc7b3c79803dbc1f57 numpy-1.8.1.tar.gz+21ca8db304cbbf5949f07702f2a42bb5e5a0d641921e36649555a41b0e48f04e96f53760417823177ac27f6de24b2191e6e1d5f0eb393beafa29f7484e23284f site.cfg"
diff --git a/testing/py-numpy/site.cfg b/testing/py-numpy/site.cfg
new file mode 100644
index 0000000..effb46f
--- /dev/null+++ b/testing/py-numpy/site.cfg
@@ -0,0 +1,157 @@
+# This file provides configuration information about non-Python dependencies for+# numpy.distutils-using packages. Create a file like this called "site.cfg" next+# to your package's setup.py file and fill in the appropriate sections. Not all+# packages will use all sections so you should leave out sections that your+# package does not use.++# To assist automatic installation like easy_install, the user's home directory+# will also be checked for the file ~/.numpy-site.cfg .++# The format of the file is that of the standard library's ConfigParser module.+#+# http://www.python.org/doc/current/lib/module-ConfigParser.html+#+# Each section defines settings that apply to one particular dependency. Some of+# the settings are general and apply to nearly any section and are defined here.+# Settings specific to a particular section will be defined near their section.+#+# libraries+# Comma-separated list of library names to add to compile the extension+# with. Note that these should be just the names, not the filenames. For+# example, the file "libfoo.so" would become simply "foo".+# libraries = lapack,f77blas,cblas,atlas+#+# library_dirs+# List of directories to add to the library search path when compiling+# extensions with this dependency. Use the character given by os.pathsep+# to separate the items in the list. Note that this character is known to+# vary on some unix-like systems; if a colon does not work, try a comma.+# This also applies to include_dirs and src_dirs (see below).+# On UN*X-type systems (OS X, most BSD and Linux systems):+# library_dirs = /usr/lib:/usr/local/lib+# On Windows:+# library_dirs = c:\mingw\lib,c:\atlas\lib+# On some BSD and Linux systems:+# library_dirs = /usr/lib,/usr/local/lib+#+# include_dirs+# List of directories to add to the header file earch path.+# include_dirs = /usr/include:/usr/local/include+#+# src_dirs +# List of directories that contain extracted source code for the+# dependency. For some dependencies, numpy.distutils will be able to build+# them from source if binaries cannot be found. The FORTRAN BLAS and+# LAPACK libraries are one example. However, most dependencies are more+# complicated and require actual installation that you need to do+# yourself.+# src_dirs = /home/rkern/src/BLAS_SRC:/home/rkern/src/LAPACK_SRC+#+# search_static_first+# Boolean (one of (0, false, no, off) for False or (1, true, yes, on) for+# True) to tell numpy.distutils to prefer static libraries (.a) over+# shared libraries (.so). It is turned off by default.+# search_static_first = false++# Defaults+# ========+# The settings given here will apply to all other sections if not overridden.+# This is a good place to add general library and include directories like+# /usr/local/{lib,include}+#+#[DEFAULT]+#library_dirs = /usr/local/lib+#include_dirs = /usr/local/include++# Atlas+# -----+# Atlas is an open source optimized implementation of the BLAS and Lapack+# routines. Numpy will try to build against Atlas by default when available in+# the system library dirs. To build numpy against a custom installation of+# Atlas you can add an explicit section such as the following. Here we assume+# that Atlas was configured with ``prefix=/opt/atlas``.+#+# [atlas]+# library_dirs = /opt/atlas/lib+# include_dirs = /opt/atlas/include++# OpenBLAS+# --------+# OpenBLAS is another open source optimized implementation of BLAS and Lapack+# and can be seen as an alternative to Atlas. To build numpy against OpenBLAS+# instead of Atlas, use this section instead of the above, adjusting as needed+# for your configuration (in the following example we installed OpenBLAS with+# ``make install PREFIX=/opt/OpenBLAS``.+#+# **Warning**: OpenBLAS, by default, is built in multithreaded mode. Due to the+# way Python's multiprocessing is implemented, a multithreaded OpenBLAS can+# cause programs using both to hang as soon as a worker process is forked on+# POSIX systems (Linux, Mac).+# This is fixed in Openblas 0.2.9 for the pthread build, the OpenMP build using+# GNU openmp is as of gcc-4.9 not fixed yet.+# Python 3.4 will introduce a new feature in multiprocessing, called the+# "forkserver", which solves this problem. For older versions, make sure+# OpenBLAS is built using pthreads or use Python threads instead of+# multiprocessing.+# (This problem does not exist with multithreaded ATLAS.)+#+# http://docs.python.org/3.4/library/multiprocessing.html#contexts-and-start-methods+# https://github.com/xianyi/OpenBLAS/issues/294+#+[openblas]+libraries = openblas+library_dirs = /usr/lib+include_dirs = /usr/include++# MKL+#----+# MKL is Intel's very optimized yet proprietary implementation of BLAS and+# Lapack.+# For recent (9.0.21, for example) mkl, you need to change the names of the+# lapack library. Assuming you installed the mkl in /opt, for a 32 bits cpu:+# [mkl]+# library_dirs = /opt/intel/mkl/9.1.023/lib/32/+# lapack_libs = mkl_lapack+#+# For 10.*, on 32 bits machines:+# [mkl]+# library_dirs = /opt/intel/mkl/10.0.1.014/lib/32/+# lapack_libs = mkl_lapack+# mkl_libs = mkl, guide++# UMFPACK+# -------+# The UMFPACK library is used in scikits.umfpack to factor large sparse matrices. +# It, in turn, depends on the AMD library for reordering the matrices for+# better performance. Note that the AMD library has nothing to do with AMD+# (Advanced Micro Devices), the CPU company.+#+# UMFPACK is not needed for numpy or scipy.+#+# http://www.cise.ufl.edu/research/sparse/umfpack/+# http://www.cise.ufl.edu/research/sparse/amd/+# http://scikits.appspot.com/umfpack+#+#[amd]+#amd_libs = amd+#+#[umfpack]+#umfpack_libs = umfpack++# FFT libraries+# -------------+# There are two FFT libraries that we can configure here: FFTW (2 and 3) and djbfft.+# Note that these libraries are not needed for numpy or scipy.+#+# http://fftw.org/+# http://cr.yp.to/djbfft.html+#+# Given only this section, numpy.distutils will try to figure out which version+# of FFTW you are using.+#[fftw]+#libraries = fftw3+#+# For djbfft, numpy.distutils will look for either djbfft.a or libdjbfft.a . +#[djbfft]+#include_dirs = /usr/local/djbfft/include+#library_dirs = /usr/local/djbfft/lib
--
2.1.0
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---
[alpine-devel] Re: [PATCH 2/2] testing/py-numpy: upgrade, use OpenBLAS
On Thu, Aug 28, 2014 at 08:53:57AM -0700, Isaac Dunham wrote:
> Upgraded to 1.8.1 so I could build with OpenBLAS.> Fixed a typo while I was here.
I made this change so I could build SciPy (it requires a BLAS implementation
and a LAPACK implementation; ATLAS is extremely difficult to build, while
OpenBLAS is trivial to build.)
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On Thu, Aug 28, 2014 at 08:53:56AM -0700, Isaac Dunham wrote:
> I've added a couple bugfixes cherry-picked from the development branch.> ---> +#USE_OPENMP=0: see GCC bug 60035> +#NO_AFFINITY: don't expect to work on musl, also breaks R> + make USE_OPENMP=0 NO_LAPACK=0 NUM_THREADS=2 MAJOR_VERSION=3 \> + NO_AFFINITY=1 TARGET=ATOM PREFIX=/usr || return 1
^^^^^^^^^^^
Argh! I thought I'd changed that, but I guess I hadn't.
It isn't ready to apply, which means the next patch needs to wait.
Whats's the minimum x86 version we support? i486, i586, i686, PIII?
Thanks,
Isaac Dunham
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