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_ArrayFunctionDispatcher

numpy:where

Summary

Return elements chosen from x or y depending on condition.

Extended Summary

Parameters

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.

Returns

out : ndarray

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

Notes

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)]

Examples

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

See also

choose
nonzero

The function that is called when x and y are omitted

Aliases

  • numpy.where