efficient loop over numpy array

Question

Versions of this question have already been asked but I have not found a satisfactory answer.

Problem: given a large numpy vector, find indices of t

Answer 1

This runs in 8 ms compared to 18 s for your code and doesn't use any strange libraries. It's similar to the approach by @vs0, but I like defaultdict more. It should be approximately O(N).

from collections import defaultdict
dupl = []
counter = 0
indexes = defaultdict(list)
for i, e in enumerate(vect):
    indexes[e].append(i)
    if len(indexes[e]) > 1:
        dupl.append(i)
        counter += 1