[Numpy-discussion] Behavior of .reduceat()

[Feng Yu]

Hi Marten,

As a user of reduceat I seriously like your new proposal!

I notice that in your current proposal, each element in the 'at' list
shall be interpreted asif they are parameters to `slice`.

I wonder if it is meaningful to define reduceat on other `fancy` indexing types?

Cheers,

- Yu

On Sun, May 22, 2016 at 12:15 PM, Marten van Kerkwijk
<m.h.vankerkwijk at gmail.com> wrote:
> Hi Jaime,
>
> Very belated reply, but only with the semester over I seem to have regained
> some time to think.
>
> The behaviour of reduceat always has seemed a bit odd to me, logical for
> dividing up an array into irregular but contiguous pieces, but illogical for
> more random ones (where one effectively passes in pairs of points, only to
> remove the unwanted calculations after the fact by slicing with [::2];
> indeed, the very first example in the documentation does exactly this [1]).
> I'm not sure any of your proposals helps all that much for the latter case,
> while it risks breaking existing code in unexpected ways.
>
> For me, for irregular pieces, it would be much nicer to simply pass in pairs
> of points. I think this can be quite easily done in the current API, by
> expanding it to recognize multidimensional index arrays (with last dimension
> of 2; maybe 3 for step as well?). These numbers would just be the equivalent
> of start, end (and step?) of `slice`, so I think one can allow any integer
> with negative values having the usual meaning and clipping at 0 and length.
> So, specifically, the first example in the documentation would change from:
>
> np.add.reduceat(np.arange(8),[0,4, 1,5, 2,6, 3,7])[::2]
>
> to
>
> np.add.reduceat(np.arange(8),[(0, 4), (1, 5), (2, 6), (3,7)])
>
> (Or an equivalent ndarray. Note how horrid the example is: really, you'd
> want 4,8 as a pair too, but in the current API, you'd get that by adding a
> 4.)
>
> What do you think? Would this also be easy to implement?
>
> All the best,
>
> Marten
>
> [1]
> http://docs.scipy.org/doc/numpy/reference/generated/numpy.ufunc.reduceat.html
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>