[Numpy-discussion] new mingw-w64 based numpy and scipy wheel (still experimental)

Carl Kleffner cmkleffner at gmail.com
Fri Jan 23 03:25:05 EST 2015


All tests for the 64bit builds passed.

Carl

2015-01-23 0:11 GMT+01:00 Sturla Molden <sturla.molden at gmail.com>:

> Were there any failures with the 64 bit build, or did all tests pass?
>
> Sturla
>
>
> On 22/01/15 22:29, Carl Kleffner wrote:
> > I took time to create mingw-w64 based wheels of numpy-1.9.1 and
> > scipy-0.15.1 source distributions and put them on
> > https://bitbucket.org/carlkl/mingw-w64-for-python/downloads as well as
> > on binstar.org <http://binstar.org>. The test matrix is python-2.7 and
> > 3.4 for both 32bit and 64bit.
> >
> > Feedback is welcome.
> >
> > The wheels can be pip installed with:
> >
> > pip install -i https://pypi.binstar.org/carlkl/simple numpy
> > pip install -i https://pypi.binstar.org/carlkl/simple scipy
> >
> > Some technical details: the binaries are build upon OpenBLAS as
> > accelerated BLAS/Lapack. OpenBLAS itself is build with dynamic kernels
> > (similar to MKL) and automatic runtime selection depending on the CPU.
> > The minimal requested feature supplied by the CPU is SSE2. SSE1 and
> > non-SSE CPUs are not supported with this builds. This is the default for
> > 64bit binaries anyway.
> >
> > OpenBLAS is deployed as part of the numpy wheel. That said, the scipy
> > wheels mentioned above are dependant on the installation of the OpenBLAS
> > based numpy and won't work i.e. with an installed  numpy-MKL.
> >
> > For the numpy 32bit builds there are 3 failures for special FP value
> > tests, due to a bug in mingw-w64 that is still present. All scipy
> > versions show up 7 failures with some numerical noise, that could be
> > ignored (or corrected with relaxed asserts in the test code).
> >
> > PR's for numpy and scipy are in preparation. The mingw-w64 compiler used
> > for building can be found at
> > https://bitbucket.org/carlkl/mingw-w64-for-python/downloads.
> >
> >
> >
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> >
>
>
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