I am not sure how I feel about this. If I understand correctly, the
issue started as a corner case when the indices were incorrect, and
grew to dealing with initial values, and then added a desire for
piecewise reducat with multiple segements. Is that correct? Could you
give a better summary of the issue the PR is trying to solve? The
examples look magic to me, it took me a long time to understand that
the `[1, 3, 5]` correspond to start indices and `[2, -1, 0]`
correspond to stop indices. Perhaps we should require kwarg use
instead of positional to make the code more readable.
Matti

On Sun, Nov 24, 2024 at 3:13 AM Marten van Kerkwijk
<m...@astro.utoronto.ca> wrote:
>
> Hi All,
>
> This discussion about updating reduceat went silent, but recently I came
> back to my PR to allow `indices` to be a 2-dimensional array of start
> and stop values (or a tuple of separate start and stop arrays).  I
> thought a bit more about it and think it is the easiest way to extend
> the present definition.  So, I have added some tests and documentation
> and would now like to open it for proper discussion.  See
>
> https://github.com/numpy/numpy/pull/25476
>
> >From the examples there:
> ```
> a = np.arange(12)
> np.add.reduceat(a, ([1, 3, 5], [2, -1, 0]))
> # array([ 1, 52,  0])
> np.minimum.reduceat(a, ([1, 3, 5], [2, -1, 0]), initial=10)
> # array([ 1,  3, 10])
> np.minimum.reduceat(a, ([1, 3, 5], [2, -1, 0]))
> # ValueError: empty slice encountered with reduceat operation for 'minimum', 
> which does not have an identity. Specify 'initial'.
> ```
> Let me know what you all think,
>
> Marten
>
> p.s.  Rereading the thread, I see we discussed initial vs default values
> in some detail. This is interesting, but somewhat orthogonal to the PR,
> since it just copies behaviour already present for reduce.
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