[Numpy-discussion] Make np.bincount output same dtype as weights

[Juan Nunez-Iglesias]

Thanks for clarifying, Jaime, and fwiw I agree with Josef: I would expect
np.bincount to behave like np.sum with regards to promoting weights dtypes.
Including bool.

On Sun, Mar 27, 2016 at 1:58 PM, <josef.pktd at gmail.com> wrote:

> On Sat, Mar 26, 2016 at 9:54 PM, Joseph Fox-Rabinovitz
> <jfoxrabinovitz at gmail.com> wrote:
> > 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 Río
> >
> > Date: Sat, Mar 26, 2016 16:16
> >
> > To: Discussion of Numerical Python;
> >
> > Subject:[Numpy-discussion] Make np.bincount output same dtype as weights
> >
> > Hi 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?
>
> I always thought of bincount with weights just as a group-by sum. So
> it would be easier to remember and have fewer surprises if it matches
> the behavior of 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?
>
> Isn't this calculating the sum, i.e. count of True by group, already?
> Based on a quick example with numpy 1.9.2, I don't think I ever used
> bool weights before.
>
>
> > 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!
>
> (2-D weights ?)
>
>
> Josef
>
>
> >
> > Jaime
> >
> > --
> > (__/)
> > ( O.o)
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> planes de
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> >
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