Just curious, how much faster is it compared to currently recommended `reduce` approach? DG
On 2 Feb 2024, at 17:31, Marten van Kerkwijk <mhvk@astro.utoronto.ca> wrote:
For my own work, I required the intersect1d function to work on multiple arrays while returning the indices (using `return_indizes=True`). Consequently I changed the function in numpy and now I am seeking feedback from the community.
This is the corresponding PR: https://github.com/numpy/numpy/pull/25688
<snip>
To me this looks like a very sensible generalization. In terms of numpy API, the only real change is that, effectively, the assume_unique and return_indices arguments become keyword-only, i.e., in the unlikely case that someone passed those as positional, a trivial backward-compatible change will fix it.
-- Marten _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-leave@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: dom.grigonis@gmail.com