I think a separate ndenumerate() in the masked array namespace would make a lot of sense. This is much less risky than changing np.ndenumerate().
On Wed, Nov 17, 2021 at 11:54 AM Andras Deak <deak.and...@gmail.com> wrote: > On Wed, Nov 17, 2021 at 8:35 PM Sebastian Berg <sebast...@sipsolutions.net> > wrote: > >> On Wed, 2021-11-17 at 19:49 +0100, Andras Deak wrote: >> > On Wed, Nov 17, 2021 at 7:39 PM Sebastian Berg >> > <sebast...@sipsolutions.net> >> > wrote: >> > >> > > Hi all, >> > > >> > > the `np.ndenumerate` does not work well for masked arrays (like >> > > many >> > > main namespace functions, it simply ignores/drops the mask). >> > > >> > > There is a PR (https://github.com/numpy/numpy/pull/20020) to add a >> > > version of it to `np.ma` (masked array specific). And we thought >> > > it >> > > seemed reasonable and were planning on putting it in. >> > > >> > > This version skips all masked elements. An alternative could be to >> > > return `np.ma.masked` for masked elements? >> > > >> > > So if anyone thinks that may be the better solution, please send a >> > > brief mail. >> > > >> > >> > Would it be a bad idea to add a kwarg that specifies this behaviour >> > (i.e. >> > offering both alternatives)? Assuming people might need the masked >> > items to >> > be there under certain circumstances. Perhaps when zipping masked >> > data with >> > dense data? >> > >> >> Sure, if you agree the default should be skipping, I guess we are OK >> with adding it? ;) >> > > I don't actually use masked arrays myself, nor ndenumerate, so I'm very > forgiving in this matter... > But if both use cases are plausible (_if_, although I can indeed imagine > that this is the case), supporting both seems straightforward. Considering > the pure python implementation it wouldn't be a problem to expose both > functionalities. > > András > > > >> Cheers, >> >> Sebastian >> >> >> > András >> > >> > >> > >> > > (Personally, I don't have opinions on masked arrays for the most >> > > part.) >> > > >> > > Cheers, >> > > >> > > Sebastian >> > > _______________________________________________ >> > > NumPy-Discussion mailing list -- numpy-discussion@python.org >> > > To unsubscribe send an email to numpy-discussion-le...@python.org >> > > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >> > > Member address: deak.and...@gmail.com >> > > >> > _______________________________________________ >> > NumPy-Discussion mailing list -- numpy-discussion@python.org >> > To unsubscribe send an email to numpy-discussion-le...@python.org >> > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >> > Member address: sebast...@sipsolutions.net >> >> _______________________________________________ >> NumPy-Discussion mailing list -- numpy-discussion@python.org >> To unsubscribe send an email to numpy-discussion-le...@python.org >> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >> Member address: deak.and...@gmail.com >> > _______________________________________________ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: sho...@gmail.com >
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