Just curious, how much faster is it compared to currently recommended `reduce` approach?
DG > On 2 Feb 2024, at 17:31, Marten van Kerkwijk <m...@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-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: dom.grigo...@gmail.com _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
