Numpy equivalent of list.index

Question

In a low-level function that is called many times, I need to do the equivalent of python\'s list.index, but with a numpy array. The function needs to return when it finds the f

Answer 1

See my comment on the OP's question for caveats, but in general, I would do the following:

import numpy as np
a = np.array([1, 2, 3])
np.min(np.nonzero(a == 2)[0])

if the value you are looking for is not in the array, you'll get a ValueError due to:

ValueError: zero-size array to ufunc.reduce without identity

because you are trying to take the min value of an empty array.

I would profile this code and see if it is an actual bottleneck, because in general when numpy searches through an entire array using a built-in function rather than an explicit python loop, it is relatively fast. An insistence on halting the search when it finds the first value may be functionally irrelevant.