Disclaimer : this is a user's point of view. I never commited a line in numpy.
In my usage, missing values happen or the need for some kind of mask, such as sea/land. I've been told, here, that using MA is superior to using NaNs, and indeed, I found a couple case where other libraries (matplotlib, ...) behaved better with MA than with NaNs in simple ndarrays. Thus, I fear moving masked arrays to a separate package would give them a second-class status, have them look as optional, and lower their support by third-party libraries. And I view a as a bad idea any suggestion to deprecate MaskedArray before any replacement is designed an implemented. Bruno. 2018-05-24 17:40 GMT+02:00 Hameer Abbasi <einstein.edi...@gmail.com>: > I also somewhat like the idea of taking it out (once we have a first > replacement) in the case that we have a plan to do a better/lower level > replacement at a later point within numpy. > Removal generally has its merits, but if a (mid term) replacement will > come in any case, it would be nice to get those started first if > possible. > Otherwise downstream might end up having to fix up things twice. > > - Sebastian > > > I also like the idea of designing a replacement first (using modern array > protocols, perhaps in a separate repository) and then deprecating > MaskedArray second. Deprecating an entire class in NumPy seems > counterproductive, although I will admit I’ve never found use from it. From > this thread, it’s clear that others have, though. > > Sent from Astro <https://www.helloastro.com> for Mac > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > >
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
