On Tue, Sep 3, 2013 at 6:18 PM, Charles R Harris <[email protected]>wrote:
> > > > On Tue, Sep 3, 2013 at 6:09 PM, Christoph Gohlke <[email protected]> wrote: > >> On 9/3/2013 4:45 PM, Charles R Harris wrote: >> > >> > >> > >> > On Tue, Sep 3, 2013 at 5:40 PM, Christoph Gohlke <[email protected] >> > <mailto:[email protected]>> wrote: >> > >> > On 9/3/2013 2:51 PM, Charles R Harris wrote: >> > > >> > > >> > > >> > > On Tue, Sep 3, 2013 at 3:23 PM, Christoph Gohlke >> > <[email protected]<mailto: >> [email protected]> >> > > <mailto:[email protected] <mailto:[email protected]>>> 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. > > Looks like there are several errors in that function. Chuck
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