[Numpy-discussion] ANN: Numpy 1.8.0 beta 1 release

[Chris Barker - NOAA Federal]

FWIW,

You all may know this already, but a "long" is 64 bit on most 64 bit
platforms, but 32 bit on Windows.

Can we start using stdint.h and int32_t and friends?

-CHB

On Sep 3, 2013, at 5:18 PM, Charles R Harris <charlesr.harris at gmail.com>
wrote:




On Tue, Sep 3, 2013 at 6:09 PM, Christoph Gohlke <cgohlke at uci.edu> wrote:

> On 9/3/2013 4:45 PM, Charles R Harris wrote:
> >
> >
> >
> > On Tue, Sep 3, 2013 at 5:40 PM, Christoph Gohlke <cgohlke at uci.edu
> > <mailto:cgohlke at uci.edu>> wrote:
> >
> >     On 9/3/2013 2:51 PM, Charles R Harris wrote:
> >     >
> >     >
> >     >
> >     > On Tue, Sep 3, 2013 at 3:23 PM, Christoph Gohlke <cgohlke at uci.edu<mailto:
> cgohlke at uci.edu>
> >     > <mailto:cgohlke at uci.edu <mailto:cgohlke at uci.edu>>> wrote:
> >     >
> >     >     On 9/1/2013 9:54 AM, Charles R Harris wrote:
> >     >
> >     >         Hi all,
> >     >
> >     >         I'm happy to announce the first beta release of Numpy
> 1.8.0.
> >     >         Please try
> >     >         this beta and report any issues on the numpy-dev mailing
> list.
> >     >
> >     >         Source tarballs and release notes can be found at
> >     >https://sourceforge.net/__projects/numpy/files/NumPy/1.__8.0b1/
> >     >         <
> https://sourceforge.net/projects/numpy/files/NumPy/1.8.0b1/>.
> >     >         The Windows
> >     >         and OS X installers will follow when the infrastructure
> issues
> >     >         are dealt
> >     >         with.
> >     >
> >     >         Chuck
> >     >
> >     >
> >     >     Hello,
> >     >
> >     >     I tried numpy-1.8.0.dev-86a6e6c with msvc9 and MKL 11.1 on
> >     >     win-amd64-py2.7. It builds OK but there are 23 test errors and
> 6
> >     >     failures (attached).
> >     >
> >     >     Some 3rd party packages (e.g. scipy, numexpr, pytables,
> bottleneck,
> >     >     pandas and matplotlib) that were built against numpy-MKL 1.7
> fail
> >     >     tests when used with numpy-MKL 1.8. Other packages test OK
> (e.g.
> >     >     skimage, sklearn, statsmodels, mahotas, pygame). See
> >     >     <
> http://www.lfd.uci.edu/~__gohlke/pythonlibs/tests/__20130902-win-amd64-py2.7-__numpy-1.8.0.dev-86a6e6c/
> >     <
> http://www.lfd.uci.edu/%7E__gohlke/pythonlibs/tests/__20130902-win-amd64-py2.7-__numpy-1.8.0.dev-86a6e6c/
> >
> >     >     <
> http://www.lfd.uci.edu/%7Egohlke/pythonlibs/tests/20130902-win-amd64-py2.7-numpy-1.8.0.dev-86a6e6c/
> >>
> >     >     compared to
> >     >     <
> http://www.lfd.uci.edu/~__gohlke/pythonlibs/tests/__20130902-win-amd64-py2.7/
> >     <
> http://www.lfd.uci.edu/%7E__gohlke/pythonlibs/tests/__20130902-win-amd64-py2.7/
> >
> >     >     <
> http://www.lfd.uci.edu/%7Egohlke/pythonlibs/tests/20130902-win-amd64-py2.7/
> >>.
> >     >
> >     >
> >     >     I have not looked in more detail or at other Python versions
> yet.
> >     >
> >     >
> >     > Thanks Christoph,
> >     >
> >     > Looks like some work to do. I wonder what is different between
> windows
> >     > and linux here?
> >     >
> >     > Chuck
> >     >
> >
> >     Looks like the fundamental PyArray_PyIntAsIntp function is broken on
> 64
> >     bit Windows. 64 bit PyLong values are intermediately stored in a 32
> bit
> >     C long variable. But maybe I am missing something...
> >     <
> https://github.com/numpy/numpy/blob/maintenance/1.8.x/numpy/core/src/multiarray/conversion_utils.c#L729
> >
> >     <
> https://github.com/numpy/numpy/blob/maintenance/1.8.x/numpy/core/src/multiarray/conversion_utils.c#L767
> >
> >
> > My, that does look suspicious. That function is new in 1.8 I believe.
> > Looks like it needs fixing whatever else it fixes.
> >
> > Chuck
> >
>
> In fact, using a npy_longlong instead of npy_long fixes all numpy test
> errors and failures. But it probably foils the recent optimizations.
>

Great! I think the function is not used for numeric things so I'm not sure
what optimizations could be affected. I'll put up a PR and backport it.

Chuck

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