On Mon, Jan 27, 2014 at 8:04 PM, Julian Taylor <
jtaylor.deb...@googlemail.com> wrote:
> hi,
> numpys no-C99 fallback keeps turning up issues in corner cases, e.g.
> hypot https://github.com/numpy/numpy/issues/2385
> log1p https://github.com/numpy/numpy/issues/4225
>
> these only seem to happen on
Julian Taylor wrote:
> Are our binary builds for windows not correct or does windows just not
> support C99 math?
Microsoft's C compiler does not support C99.
It is not an OS issue. Use gcc, clang or Intel icc instead, and C99 is
supported.
Sturla
_
On Mon, Jan 27, 2014 at 3:43 PM, Charles G. Waldman wrote:
> Hi Numpy folks.
>
> I just noticed that comparing an array of type 'object' to None does
> not behave as I expected. Is this a feature or a bug? (I can take a
> stab at fixing it if it's a bug, as I believe it is).
>
> >>> np.version.f
Hi Numpy folks.
I just noticed that comparing an array of type 'object' to None does
not behave as I expected. Is this a feature or a bug? (I can take a
stab at fixing it if it's a bug, as I believe it is).
>>> np.version.full_version
'1.8.0'
>>> a = np.array(['Frank', None, 'Nancy'])
>>> a
a
Just a guess as I don't make those binaries, but I think they are done
with Visual Studio and it only support C89... We need to back port
some of our c code for windows for GPU as nvcc use VS and it don't
support C99.
Fred
On Mon, Jan 27, 2014 at 3:04 PM, Julian Taylor
wrote:
> hi,
> numpys no-C
hi,
numpys no-C99 fallback keeps turning up issues in corner cases, e.g.
hypot https://github.com/numpy/numpy/issues/2385
log1p https://github.com/numpy/numpy/issues/4225
these only seem to happen on windows, on linux and mac it seems to use
the C99 math library just fine.
Are our binary builds f
On Sun, Jan 26, 2014 at 6:06 PM, Stéfan van der Walt wrote:
> On Sun, 26 Jan 2014 16:40:44 +0200, Pauli Virtanen wrote:
> > The Numpy Windows binaries distributed in the numpy project at
> > sourceforge.net are compiled with ATLAS, which should count as an
> > optimized BLAS. I don't recall what's
a similar SIMD based library for transcendental function ist SLEEF
http://shibatch.sourceforge.net/ . An inclompete wrapper can be found here:
https://github.com/nikolaynag/avxmath
I suppose that Intels VML has a better coverage over YEPPP or SLEEF.
Carl
2014-01-27 Neal Becker
> http://www.y
http://www.yeppp.info/
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Not really. numexpr is mostly about element-wise operations in dense
matrices. You should look to another package for that.
Francesc
On 1/27/14, 10:18 AM, Dinesh Vadhia wrote:
> Francesc: Does numexpr support scipy sparse matrices?
>
> ___
> NumPy
Did you consider to check the experimental binaries on
https://code.google.com/p/mingw-w64-static/ for Python-2.7? These binaries
has been build with with a customized mingw-w64 toolchain. These builds are
fully statically build and are link against the MSVC90 runtime libraries
(gcc runtime is link
Francesc: Does numexpr support scipy sparse matrices?
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