[Numpy-discussion] ANN: NumPy 1.9.0 beta release

[Charles R Harris]

On Mon, Jun 9, 2014 at 6:10 PM, Charles R Harris <charlesr.harris at gmail.com>
wrote:

>
>
>
> On Mon, Jun 9, 2014 at 5:21 PM, Christoph Gohlke <cgohlke at 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...
>>
>
> One of the matplotlib failures, and I suspect the others, comes from the
> assignment
>
> found_index[refi_triangles[ancestor_mask, :]
>                             ] = np.repeat(ancestors[ancestor_mask], 3)
>
> This fails with the error
>
> ValueError: shape mismatch: value array of shape (13824,)
>
>     could not be broadcast to indexing result of shape (4608,3)
>
> I confess I find the construction odd, but the error probably results from
> stricter indexing rules. Indeed,  (13824,) does not broadcast to  (4608,3).
> Apart from considerations of backward compatibility, should it?
>
>
Other errors are of the type:

TypeError: NumPy boolean array indexing assignment requires a 0 or
1-dimensionalinput, input has 2 dimensions

 This one looks to arise is from stricter rules for boolean indexing.

Chuck
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