dpnp.select

dpnp.select(condlist, choicelist, default=0)[source]

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

For full documentation refer to numpy.select.

Parameters:

condlist (list of bool dpnp.ndarray or usm_ndarray) -- 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.
choicelist (list of dpnp.ndarray or usm_ndarray) -- The list of arrays from which the output elements are taken. It has to be of the same length as condlist.
default ({scalar, dpnp.ndarray, usm_ndarray}, optional) -- The element inserted in output when all conditions evaluate to False. Default: 0.

Returns:

out -- 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.

Return type:

dpnp.ndarray

See also

dpnp.where: Return elements from one of two arrays depending on condition.
dpnp.take: Take elements from an array along an axis.
dpnp.choose: Construct an array from an index array and a set of arrays to choose from.
dpnp.compress: Return selected slices of an array along given axis.
dpnp.diag: Extract a diagonal or construct a diagonal array.
dpnp.diagonal: Return specified diagonals.

Examples

>>> import dpnp 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])