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ENH: Add support for complex weights in np.bincount
#23641
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03003a4
Add support for complex weights
alex-gregory-ds 66ae571
Add support for integers
alex-gregory-ds c9ef986
Switch to unsigned integers for the weights
alex-gregory-ds 2cfe3a7
Change to npy_uintp to reflect type at initialization
alex-gregory-ds 6ee969c
Initialise weights for the complex case
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This is cast is wrong. You should stick with
intp
everywhere.EDIT: Ops, that is unclear. The cast is wrong, not all integers are
uintp
(in fact it looks like you make it double here?). Theintp
comment is thatuintp
isn't the correct type unless you are preserving user input, you shouldn't change that.One reason I haven't looked at this much yet is that I am not sure how far we actually want to go here, since
np.add.at
is faster now and is often a work-around (it doesn't auto-resize create/resize the result mainly).Expanding this to more than just complex requires either proper templating (moving to
c.src
format orC++
) or figuring out how to re-use theufunc.at
logic (which may well be easier, since that has fast loops now; but that needs some new logic like chunking the index to resize, which might affect performance, although I doubt much).@mattip do you have a tought about this?