Just for completeness: this is *not* an issue for ndarray subclasses, but only for people attempting to write duck arrays. One might want to start by mimicking `empty_like` - not too different from `np.positive(a, where=False)`. Will note that that is 50 times slower for small arrays since it actually does the copying - it just doesn't store the results. It is comparable in time to np.zeros_like and np.ones_like, suggesting that a ufunc implementation is not necessarily a bad thing.
As I noted above, the main problem I see is that the ufunc mechanism doesn't easily work with strings and voids/structured dtypes. -- Marten _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
