Syntax:
numpy.where(condition[, x, y])
If both x and y are specified, the output array contains elements of x where condition is True, and elements from y elsewhere:
>>> x = 3
>>> np.where(x > 0, 42, 41)
array(42)
>>>
>>>
>>> np.where([[True, False, True], [True, True, False]],
... [[12, 24, 66], [22, 24, 26]],
... [[11,13,15], [23, 25, 27]])
array([[12, 13, 66],
[22, 24, 27]])
>>> a = np.array([3, 12, 14, 9])
>>> b = np.array([11, 13, 15, 19])
>>> c = np.array([23,25,27,29])
>>>
>>>
>>> np.where(a < 10, b, c)
array([11, 25, 27, 19]) >>>