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

[Sturla Molden]

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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