[Numpy-discussion] Why does fancy indexing work like this?

[Aaron Meurer]

Ah, so I guess I caught this issue right as it got fixed. There are no
warnings in 1.19.0, but I can confirm I get the warnings in numpy
master. 1.19.1 isn't on conda yet, but I tried building it and didn't
get the warning there. So I guess I need to wait for 0.19.2.

How long do deprecation cycles like this tend to last (I'm also
curious when the warnings for things like a[[[0, 1], [0, 1]]] will go
away)?

Aaron Meurer

On Wed, Jul 22, 2020 at 4:32 PM Sebastian Berg
<sebastian at sipsolutions.net> wrote:
>
> On Wed, 2020-07-22 at 16:23 -0600, Aaron Meurer wrote:
> > Why does fancy indexing have this behavior?
> >
> > > > > a = np.empty((0, 1, 2))
> > > > > b = np.empty((1, 1, 2))
> > > > > a[np.array([10, 10])]
> > Traceback (most recent call last):
> >   File "<stdin>", line 1, in <module>
> > IndexError: index 10 is out of bounds for axis 0 with size 0
> > > > > a[:, np.array([10, 10])]
> > array([], shape=(0, 2, 2), dtype=float64)
> > > > > a[:, :, np.array([10, 10])]
> > array([], shape=(0, 1, 2), dtype=float64)
> > > > > b[np.array([10, 10])]
> > Traceback (most recent call last):
> >   File "<stdin>", line 1, in <module>
> > IndexError: index 10 is out of bounds for axis 0 with size 1
> > > > > b[:, np.array([10, 10])]
> > Traceback (most recent call last):
> >   File "<stdin>", line 1, in <module>
> > IndexError: index 10 is out of bounds for axis 1 with size 1
> > > > > b[:, :, np.array([10, 10])]
> > Traceback (most recent call last):
> >   File "<stdin>", line 1, in <module>
> > IndexError: index 10 is out of bounds for axis 2 with size 2
> >
> > As far as I can tell, the behavior is that if an array has a 0
> > dimension and an integer array index indexes an axis that isn't 0,
> > there are no bounds checks. Why does it do this? It seems to be
> > inconsistent with the behavior of shape () fancy indices (integer
> > indices). I couldn't find any reference to this behavior in
> > https://numpy.org/doc/stable/reference/arrays.indexing.html.
> >
>
> The reason is because we used to not do this when there are *two*
> advanced indices:
>
>    arr = np.ones((5, 6))
>    arr[[], [10, 10]]
>
> giving an empty result.  If you check on master (and maybe on 1.19.x, I
> am not sure). You should see that all of your examples give a
> deprecation warning to be turned into an error (except the example I
> gave above, which can be argued to be correct).
>
> - Sebastian
>
>
> > Aaron Meurer
> > _______________________________________________
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> > NumPy-Discussion at python.org
> > https://mail.python.org/mailman/listinfo/numpy-discussion
> >
>
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