[Numpy-discussion] Short-circuiting equivalent of np.any or np.all?

[Hameer Abbasi]

Ah, in that case, if exotic platforms aren’t important for you, Numba can
do the trick quite well.

Best regards,
Hameer Abbasi
Sent from Astro <https://www.helloastro.com> for Mac

On Apr 26, 2018 at 18:58, Nathan Goldbaum <nathan12343 at gmail.com> wrote:




On Thu, Apr 26, 2018 at 11:52 AM Hameer Abbasi <einstein.edison at gmail.com>
wrote:

> Hi Nathan,
>
> np.any and np.all call np.or.reduce and np.and.reduce respectively, and
> unfortunately the underlying function (ufunc.reduce) has no way of
> detecting that the value isn’t going to change anymore. It’s also used for
> (for example) np.sum (np.add.reduce), np.prod (np.multiply.reduce),
> np.min(np.minimum.reduce), np.max(np.maximum.reduce).
>
> You can find more information about this on the ufunc doc page
> <https://docs.scipy.org/doc/numpy/reference/ufuncs.html>. I don’t think
> it’s worth it to break this machinery for any and all, as it has numerous
> other advantages (such as being able to override in duck arrays, etc)
>

Sure, I'm not saying that numpy should change, more trying to see if
there's an alternate way to get what I want in NumPy or some other package.


>
> Best regards,
> Hameer Abbasi
> Sent from Astro <https://www.helloastro.com> for Mac
>
> On Apr 26, 2018 at 18:45, Nathan Goldbaum <nathan12343 at gmail.com> wrote:
>
>
> Hi all,
>
> I was surprised recently to discover that both np.any and np.all() do not
> have a way to exit early:
>
> In [1]: import numpy as np
>
> In [2]: data = np.arange(1e6)
>
> In [3]: print(data[:10])
> [0. 1. 2. 3. 4. 5. 6. 7. 8. 9.]
>
> In [4]: %timeit np.any(data)
> 724 us +- 42.4 us per loop (mean +- std. dev. of 7 runs, 1000 loops each)
>
> In [5]: data = np.zeros(int(1e6))
>
> In [6]: %timeit np.any(data)
> 732 us +- 52.9 us per loop (mean +- std. dev. of 7 runs, 1000 loops each)
>
> I don't see any discussions about this on the NumPy issue tracker but
> perhaps I'm missing something.
>
> I'm curious if there's a way to get a fast early-terminating search in
> NumPy? Perhaps there's another package I can depend on that does this? I
> guess I could also write a bit of cython code that does this but so far
> this project is pure python and I don't want to deal with the packaging
> headache of getting wheels built and conda-forge packages set up on all
> platforms.
>
> Thanks for your help!
>
> -Nathan
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>

_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion at python.org
https://mail.python.org/mailman/listinfo/numpy-discussion
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20180426/8c65705c/attachment.html>