On Mon, 2020-08-24 at 15:31 -0600, Aaron Meurer wrote: > On Wed, Aug 19, 2020 at 8:18 PM Sebastian Berg > <sebast...@sipsolutions.net> wrote: > > On Wed, 2020-08-19 at 19:37 -0600, Aaron Meurer wrote: > > > These cases don't give any deprecation warnings in NumPy master: > > > > > > > > > np.arange(0)[np.array([0]), False] > > > array([], dtype=int64) > > > > > > np.arange(0).reshape((0, 0))[np.array([0]), np.array([], > > > > > > dtype=int)] > > > array([], dtype=int64) > > > > > > Is that intentional? > > > > I guess it follows from `np.array([[1]])[[], [10]]` also not > > failing > > currently. > > Sure, I think that's the same thing (sorry if my example is "too > trivial". I was copy-pasting a hypothesis shrunk example). > > > And that was intentional not to deprecate when out-of-bound indices > > broadcast away. But I am not sure I actually think that was the > > better > > choice. My initial choice was that this would be an error as well, > > and > > I still slightly prefer it, but don't feel it matters much. > > There's an inconsistency here, which is that out-of-bounds indices > that are broadcast away are not bounds checked unless they are scalar > indices, in which case they are. > > > > > a = np.empty((1, 1)) > > > > a[np.array([], dtype=int), np.array([10])] > array([], dtype=float64) > > > > a[np.array([], dtype=int), 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 > > > > np.broadcast_arrays(np.array([], dtype=int), np.array([10])) > [array([], dtype=int64), array([], dtype=int64)] > > > > np.broadcast_arrays(np.array([], dtype=int), 10) > [array([], dtype=int64), array([], dtype=int64)] > > This breaks the rule that scalar integer indices have the same > semantics as integer arrays with shape (). >
Good observation. I agree, that is a subtle inconsistency for 0-D objects! (To be precise, I expect 0-D arrays behave identically to integers, since they will be optimized out of the "advanced index" part of the indexing operation). I suppose this may be an argument for always checking indices even when they are broadcast away? I am not certain how straight forward, or even desirable, it is to fix it so that 0-D integer arrays/integers can be "broadcast away". - Sebastian > Aaron Meurer > > > - Sebastian > > > > > Aaron Meurer > > > > > > On Thu, Jul 23, 2020 at 12:18 PM Aaron Meurer <asmeu...@gmail.com > > > > > > > wrote: > > > > > After writing this, I realized that I actually remember the > > > > > *opposite* > > > > > discussion occurring before. I think in some of the equality > > > > > deprecations, we actually raise the new error due to an > > > > > internal > > > > > try/except clause. And there was a complaint that its > > > > > confusing > > > > > that a > > > > > non-deprecation-warning is raised when the error will only > > > > > happen > > > > > with > > > > > DeprecationWarnings being set to error. > > > > > > > > > > - Sebastian > > > > > > > > I noticed that warnings.catch_warnings does the right thing > > > > with > > > > warnings that are raised alongside an exception (although it is > > > > a > > > > bit > > > > clunky to use). > > > > > > > > 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 >
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