Dear Community,
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://gith
Dear Dom,
thanks for bringing up the possible constriction. I agree that this
would be serious argument against the change.
However, as you said the overlapping/non-overlapping indices would
become ambiguous with more than two arrays. And calling the fucntion
with only two arrays at a time w
Dear Dom,
just check, and on my computer the new version is ~factor 2 faster
compared to the reduce approach if arrays are shuffled. For sorted
arrays, the the new version is factor 3.4. faster:
from functools import reduce
idss = [np.random.permutation(np.arange(a*100, int(1e5)+a*100, 1)) f
