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 (). 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
