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

The obvious question is why you want to do this in this way. NumPy arrays are intended to be opaque data structures – by this I mean NumPy arrays are intended to be created inside the NumPy system and then operations sent in to the NumPy subsystem to deliver a result. i.e. NumPy should be a black box into which you throw requests and out come results.

So given the code above I am not at all suprised that NumPy performance is worse than dreadful.

The following should be effectively what you want, I believe, but done the NumPy way:

import numpy as np

N = 10000
vect = np.arange(float(N))
vect[N/2] = 1
vect[N/4] = 1

print([np.where(a == vect)[0] for a in vect][1])

# Delivers [1, 2500, 5000]