[Numpy-discussion] NumPy 1.11.0b3 released.

Tue Feb 16 00:13:28 EST 2016

On Tue, Feb 16, 2016 at 12:09 AM, <josef.pktd at gmail.com> wrote:

>
>
> On Mon, Feb 15, 2016 at 11:31 PM, Charles R Harris <
> charlesr.harris at gmail.com> wrote:
>
>>
>>
>> On Mon, Feb 15, 2016 at 9:15 PM, <josef.pktd at gmail.com> wrote:
>>
>>>
>>>
>>> On Mon, Feb 15, 2016 at 11:05 PM, Charles R Harris <
>>> charlesr.harris at gmail.com> wrote:
>>>
>>>>
>>>>
>>>> On Mon, Feb 15, 2016 at 8:50 PM, <josef.pktd at gmail.com> wrote:
>>>>
>>>>>
>>>>>
>>>>> On Mon, Feb 15, 2016 at 10:46 PM, <josef.pktd at gmail.com> wrote:
>>>>>
>>>>>
>>>>>>
>>>>>> On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum <
>>>>>> nathan12343 at gmail.com> wrote:
>>>>>>
>>>>>>>
>>>>>>> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst
>>>>>>>
>>>>>>> On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller <t3kcit at gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Hi.
>>>>>>>> Where can I find the changelog?
>>>>>>>> It would be good for us to know which changes are done one purpos
>>>>>>>> without hunting through the issue tracker.
>>>>>>>>
>>>>>>>> Thanks,
>>>>>>>> Andy
>>>>>>>>
>>>>>>>>
>>>>>>>> On 02/09/2016 09:09 PM, Charles R Harris wrote:
>>>>>>>>
>>>>>>>> Hi All,
>>>>>>>>
>>>>>>>> I'm pleased to announce the release of NumPy 1.11.0b3. This beta
>>>>>>>> contains additional bug fixes as well as limiting the number of
>>>>>>>> FutureWarnings raised by assignment to masked array slices. One issue that
>>>>>>>> remains to be decided is whether or not to postpone raising an error for
>>>>>>>> floats used as indexes. Sources may be found on Sourceforge
>>>>>>>> <https://sourceforge.net/projects/numpy/files/NumPy/1.11.0b3/> and
>>>>>>>> both sources and OS X wheels are availble on pypi. Please test, hopefully
>>>>>>>> this will be that last beta needed.
>>>>>>>>
>>>>>>>> As a note on problems encountered, twine uploads continue to fail
>>>>>>>> for me, but there are still variations to try. The wheeluploader downloaded
>>>>>>>> wheels as it should, but could not upload them, giving the error message
>>>>>>>> "HTTPError: 413 Client Error: Request Entity Too Large for url:
>>>>>>>> <https://www.python.org/pypi>https://www.python.org/pypi". Firefox
>>>>>>>> also complains that http://wheels.scipy.org is incorrectly
>>>>>>>> configured with an invalid certificate.
>>>>>>>>
>>>>>>>> Enjoy,
>>>>>>>>
>>>>>>>> Chuck
>>>>>>>>
>>>>>>>>
>>>>>>>> _______________________________________________
>>>>>>>> NumPy-Discussion mailing listNumPy-Discussion at scipy.orghttps://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> _______________________________________________
>>>>>>>> NumPy-Discussion mailing list
>>>>>>>> NumPy-Discussion at scipy.org
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>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>> _______________________________________________
>>>>>>> NumPy-Discussion mailing list
>>>>>>> NumPy-Discussion at scipy.org
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>>>>>>>
>>>>>>>
>>>>>>
>>>>> (try to send again)
>>>>>
>>>>>
>>>>>>
>>>>>> another indexing question:  (not covered by unit test but showed up
>>>>>> in examples in statsmodels)
>>>>>>
>>>>>>
>>>>>> This works in numpy at least 1.9.2 and 1.6.1   (python 2.7, and
>>>>>> python 3.4)
>>>>>>
>>>>>> >>> list(range(5))[np.array([0])]
>>>>>> 0
>>>>>>
>>>>>>
>>>>>>
>>>>>> on numpy 0.11.0b2   (I'm not yet at b3)   (python 3.4)
>>>>>>
>>>>>> I get the same exception as here but even if there is just one element
>>>>>>
>>>>>>
>>>>>> >>> list(range(5))[np.array([0, 1])]
>>>>>> Traceback (most recent call last):
>>>>>>   File "<pyshell#7>", line 1, in <module>
>>>>>>     list(range(5))[np.array([0, 1])]
>>>>>> TypeError: only integer arrays with one element can be converted to
>>>>>> an index
>>>>>>
>>>>>
>>>> Looks like a misleading error message. Apparently it requires scalar
>>>> arrays (ndim == 0)
>>>>
>>>> In [3]: list(range(5))[np.array(0)]
>>>> Out[3]: 0
>>>>
>>>
>>>
>>> We have a newer version of essentially same function a second time that
>>> uses squeeze and that seems to work fine.
>>>
>>> Just to understand
>>>
>>> Why does this depend on the numpy version?  I would have understood that
>>> this always failed, but this code worked for several years.
>>> https://github.com/statsmodels/statsmodels/issues/2817
>>>
>>
>> It's part of the indexing cleanup.
>>
>> In [2]: list(range(5))[np.array([0])]
>> /home/charris/.local/bin/ipython:1: VisibleDeprecationWarning: converting
>> an array with ndim > 0 to an index will result in an error in the future
>>   #!/usr/bin/python
>> Out[2]: 0
>>
>> The use of multidimensional arrays as indexes is likely a coding error.
>> Or so we hope...
>>
>
> Thanks for the explanation
>
>
> Or, it forces everyone to watch out for the color of the ducks :)
>
> It's just a number, whether it's python scalar, numpy scalar, 1D or 2D.
> And once we squeeze, we cannot iterate over it anymore.
>
>
> This looks like the last problem with have in statsmodels master.
> Part of the reason that 0.10 hurt quite a bit is that we are using in
> statsmodels some of the grey zones so we don't have to commit to a specific
> usage. Even if a user or developer tries a "weird" case, it works for most
> of the results, but breaks in some unknown places.
>
>
I meant 1.11 here.

> (In the current case a cryptic exception would be raised if the user has
> two constant columns in the regression. Which is fine for some usecases but
> not for every result.)
>
> Josef
>
>
>>
>> Chuck
>>
>> _______________________________________________
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>>
>>
>
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