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 <sebast...@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 > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
