The one pandas test failure that is valid: ERROR: test_interp_regression (pandas.tests.test_generic.TestSeries)
has been fixed in pandas master / 0.14.1 (prob releasing in 1 month). (the other test failures are for clipboard / network issues) On Mon, Jun 9, 2014 at 7:21 PM, Christoph Gohlke <cgoh...@uci.edu> wrote: > On 6/8/2014 1:34 PM, Julian Taylor wrote: > >> Hello, >> >> I'm happy to announce the fist beta release of Numpy 1.9.0. >> 1.9.0 will be a new feature release supporting Python 2.6 - 2.7 and 3.2 >> - 3.4. >> Due to low demand windows binaries for the beta are only available for >> Python 2.7, 3.3 and 3.4. >> Please try it and report any issues to the numpy-discussion mailing list >> or on github. >> >> The 1.9 release will consists of mainly of many small improvements and >> bugfixes. The highlights are: >> >> * Addition of __numpy_ufunc__ to allow overriding ufuncs in ndarray >> subclasses. Please note that there are still some known issues with this >> mechanism which we hope to resolve before the final release (e.g. #4753) >> * Numerous performance improvements in various areas, most notably >> indexing and operations on small arrays are significantly faster. >> Indexing operations now also release the GIL. >> * Addition of nanmedian and nanpercentile rounds out the nanfunction set. >> >> The changes involve a lot of small changes that might affect some >> applications, please read the release notes for the full details on all >> changes: >> https://github.com/numpy/numpy/blob/maintenance/1.9.x/ >> doc/release/1.9.0-notes.rst >> Please also take special note of the future changes section which will >> apply to the following release 1.10.0 and make sure to check if your >> applications would be affected by them. >> >> Source tarballs, windows installers and release notes can be found at >> https://sourceforge.net/projects/numpy/files/NumPy/1.9.0b1 >> >> Cheers, >> Julian Taylor >> >> > Hello, > > I tested numpy-MKL-1.9.0b1 (msvc9, Intel MKL build) on win-amd64-py2.7 > against a few other packages that were built against numpy-MKL-1.8.x. > > While numpy and scipy pass all tests, some other packages (matplotlib, > statsmodels, skimage, pandas, pytables, sklearn...) show a few new test > failures (compared to testing with numpy-MKL-1.8.1). Many test errors are > of kind: > > ValueError: shape mismatch: value array of shape (24,) could not be > broadcast to indexing result of shape (8,3) > > I have attached a list of failing tests. The full test results are at < > http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/20140609-win-amd64-py2.7- > numpy-1.9.0b1/> (compare to <http://www.lfd.uci.edu/~ > gohlke/pythonlibs/tests/20140609-win-amd64-py2.7/>) > > I have not investigated any further... > > Christoph > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
