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

[Dieter Werthmüller]

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