๐Long time numpy user, and big fan of all your work TL; DR - there's a `bit_count` method on numpy scalars, and Python ints, I'm advocating for a `ufunc` `bit_count` as has been implemented in this PR:
https://github.com/numpy/numpy/pull/21429 A number of people have requested this as a numpy feature and there's a lot of great discussion at this issue https://github.com/numpy/numpy/issues/16325 A bit count comes up in certain similarity situations (like hamming distance). This involves an xor with numpy arrays and a bit count, where the bit count is currently the bottleneck by a few orders of magnitude in my local benchmarking. Currently there's a number of not particularly fast, workarounds for doing this with numpy arrays, like the bit-twiddling solutions here https://stackoverflow.com/a/68943135/8123 https://stackoverflow.com/a/109025/8123 So I'd love to be able to continue the work of bit_count -> numpy array ufunc to get performance gains at the array level ๐ _______________________________________________ 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
