numpy.select#

numpy.select(condlist, choicelist, default=0)[source]#

Return an array drawn from elements in choicelist, depending on conditions.

Parameters:

condlistlist of bool ndarrays: The list of conditions which determine from which array in choicelist the output elements are taken. When multiple conditions are satisfied, the first one encountered in condlist is used.
choicelistlist of ndarrays: The list of arrays from which the output elements are taken. It has to be of the same length as condlist.
defaultscalar, optional: The element inserted in output when all conditions evaluate to False.

Returns:

outputndarray: The output at position m is the m-th element of the array in choicelist where the m-th element of the corresponding array in condlist is True.

See also

where: Return elements from one of two arrays depending on condition.
take, choose, compress, diag, diagonal

Examples

>>> import numpy as np

Beginning with an array of integers from 0 to 5 (inclusive), elements less than 3 are negated, elements greater than 3 are squared, and elements not meeting either of these conditions (exactly 3) are replaced with a default value of 42.

>>> x = np.arange(6)
>>> condlist = [x<3, x>3]
>>> choicelist = [x, x**2]
>>> np.select(condlist, choicelist, 42)
array([ 0,  1,  2, 42, 16, 25])

When multiple conditions are satisfied, the first one encountered in condlist is used.

>>> condlist = [x<=4, x>3]
>>> choicelist = [x, x**2]
>>> np.select(condlist, choicelist, 55)
array([ 0,  1,  2,  3,  4, 25])