numpy._core._multiarray_umath:where

Summary

Return elements chosen from x or y depending on condition.

condition : array_like, bool: Where True, yield x, otherwise yield y.
x, y : array_like: Values from which to choose. x, y and condition need to be broadcastable to some shape.

out : ndarray: An array with elements from x where condition is True, and elements from y elsewhere.

If all the arrays are 1-D, where is equivalent to

[xv if c else yv
 for c, xv, yv in zip(condition, x, y)]

import numpy as np
a = np.arange(10)
a
np.where(a < 5, a, 10*a)

This can be used on multidimensional arrays too:

np.where([[True, False], [True, True]],
         [[1, 2], [3, 4]],
         [[9, 8], [7, 6]])

The shapes of x, y, and the condition are broadcast together:

x, y = np.ogrid[:3, :4]
np.where(x < y, x, 10 + y)  # both x and 10+y are broadcast

a = np.array([[0, 1, 2],
              [0, 2, 4],
              [0, 3, 6]])
np.where(a < 4, a, -1)  # -1 is broadcast