Would it make sense to just make the output type large enough to hold the
cumulative sum of the weights?
- Joseph Fox-Rabinovitz
------ Original message------From: Jaime Fernández del RíoDate: Sat, Mar 26,
2016 16:16To: Discussion of Numerical Python;Subject:[Numpy-discussion] Make
np.bincount output same dtype as weightsHi all,
I have just submitted a PR (#7464) that fixes an enhancement request (#6854),
making np.bincount return an array of the same type as the weights parameter.
This is an important deviation from current behavior, which always casts
weights to double, and always returns a double array, so I would like to hear
what others think about the worthiness of this. Main discussion
points:np.bincount now works with complex weights (yay!), I guess this should
be a pretty uncontroversial enhancement.The return is of the same type as
weights, which means that small integers are very likely to overflow. This is
exactly what #6854 requested, but perhaps we should promote the output for
integers to a long, as we do in np.sum?Boolean arrays stay boolean, and OR,
rather than sum, the weights. Is this what one would want? If we decide that
integer promotion is the way to go, perhaps booleans should go in the same
pack?This new implementation currently supports all of the reasonable native
types, but has no fallback for user defined types. I guess we should attempt
to cast the array to double as before if no native loop can be found? It would
be good to have a way of testing this though, any thoughts on how to go about
this?Does a behavior change like this require some deprecation period? What
would that look like?I have also added broadcasting of weights to the full size
of list, so that one can do e.g. np.bincount([1, 2, 3], weights=2j) without
having to tile the single weight to the size of the bins list.
Any other thoughts are very welcome as well!
Jaime
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