[SciPy-Dev] np.any(), np.all()

[Benny Malengier]

Sorry, I see you mention that issue. Anyway, I would suggest going for a
cython or C workaround at the moment and commenting on the tickets. As
Phillip says, a separate method would be needed as any and all do a reduce.
Some methods like firstnotvalue and firstvalue, returning index of a
difference from value or the value, so like
https://pypi.org/project/py_find_1st/  mentioned in the ticket.

For multidim arrays, as this operates on 1D arrays, perhaps the firstvalue
applied per axis...

Op wo 4 jul. 2018 om 09:43 schreef Benny Malengier <
benny.malengier at gmail.com>:

> There is an open issue for this since 2012:
> https://github.com/numpy/numpy/issues/2269
>
> Some python and c solutions are suggested in that thread.
>
> Op wo 4 jul. 2018 om 06:44 schreef Phillip Feldman <
> phillip.m.feldman at gmail.com>:
>
>> Performing a test (to determine whether the loop should be aborted) after
>> looking at each element would cause `np.any` to run slower if all elements
>> are zero, or if the first non-zero element is near the end of the array.
>> Possibly a separate method that operates in this fashion is needed?
>>
>> Phillip
>>
>>
>> On Mon, Jul 2, 2018 at 11:03 AM, Dieter Werthmüller <
>> dieter at werthmuller.org> wrote:
>>
>>> Dear devs,
>>>
>>> Sorry for posting a numpy-issue on the scipy-list. I am not (yet)
>>> subscribed to the numpy list, but I believe that the two community have a
>>> big enough overlap so it shouldn't matter too much where I post it.
>>>
>>> I recently encountered the issue that I found that np.any(x) is sort of
>>> veeeery slow for big arrays, even if every element has a non-zero value and
>>> I only need a True/False response. So my thinking was that if np.any(x)
>>> encounters the first non-zero value it should simply return True, which
>>> should take basically no time at all if every element in the array is
>>> non-zero.
>>>
>>> Searching for it I found the following two old issues on numpy:
>>>
>>> 1. https://github.com/numpy/numpy/issues/2269
>>>
>>> It is an issue from 2010, but got some traffic again in 2016 and 2017.
>>>
>>>
>>> 2. https://github.com/numpy/numpy/issues/3446
>>>
>>> This is a related issue from 2013, reporting a potential performance
>>> regression between numpy 1.6.2 and 1.7.0, that got some traffic in 2016
>>> again as well.
>>>
>>>
>>> I just wanted to ask about the opinions of devs more familiar with these
>>> two functions (np.all(), np.any()). Would there be better ways to check if
>>> any element in a big (1D or higher dimensions)-array is non-zero (or the
>>> reverse with np.all)?
>>>
>>>
>>> Thanks,
>>> Dieter
>>>
>>> _______________________________________________
>>> SciPy-Dev mailing list
>>> SciPy-Dev at python.org
>>> https://mail.python.org/mailman/listinfo/scipy-dev
>>>
>>
>> _______________________________________________
>> SciPy-Dev mailing list
>> SciPy-Dev at python.org
>> https://mail.python.org/mailman/listinfo/scipy-dev
>>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scipy-dev/attachments/20180704/d0a52c0d/attachment-0001.html>