[Numpy-discussion] Make np.bincount output same dtype as weights
CJ Carey
perimosocordiae at gmail.com
Mon Mar 28 15:55:14 EDT 2016
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.soma at 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.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)
>> > ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus
>> planes de
>> > dominación mundial.
>> >
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