Have modified the PR to do the "promote integers to at least long" we do in np.sum.
Jaime On Mon, Mar 28, 2016 at 9:55 PM, CJ Carey <perimosocord...@gmail.com> wrote: > Another +1 for Josef's interpretation from me. Consistency with np.sum > seems like the best option. > > On Sat, Mar 26, 2016 at 11:12 PM, Juan Nunez-Iglesias <jni.s...@gmail.com> > wrote: > >> 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.p...@gmail.com> wrote: >> >>> On Sat, Mar 26, 2016 at 9:54 PM, Joseph Fox-Rabinovitz >>> <jfoxrabinov...@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) >>> > ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus >>> planes de >>> > dominación mundial. >>> > >>> > _______________________________________________ >>> > NumPy-Discussion mailing list >>> > NumPy-Discussion@scipy.org >>> > https://mail.scipy.org/mailman/listinfo/numpy-discussion >>> > >>> _______________________________________________ >>> NumPy-Discussion mailing list >>> NumPy-Discussion@scipy.org >>> https://mail.scipy.org/mailman/listinfo/numpy-discussion >>> >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> https://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > -- (\__/) ( O.o) ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes de dominación mundial.
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