dpnp.power

dpnp.power(x1, x2, /, out=None, *, order='K', where=True, dtype=None, subok=True, **kwargs)

First array elements raised to powers from second array, element-wise.

An integer type (of either negative or positive value, but not zero) raised to a negative integer power will return an array of zeroes.

For full documentation refer to numpy.power.

Returns:

out – The bases in x1 raised to the exponents in x2.

Return type:

dpnp.ndarray

Limitations

Parameters x1 and x2 are supported as either scalar, dpnp.ndarray or dpctl.tensor.usm_ndarray, but both x1 and x2 can not be scalars at the same time. Parameters where, dtype and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise the function will be executed sequentially on CPU. Input array data types are limited by supported DPNP Data types.

See also

dpnp.fmax

Element-wise maximum of array elements.

dpnp.fmin

Element-wise minimum of array elements.

dpnp.fmod

Calculate the element-wise remainder of division.

Examples

>>> import dpnp as dp
>>> a = dp.arange(6)
>>> dp.power(a, 3)
array([  0,   1,   8,  27,  64, 125])

Raise the bases to different exponents.

>>> b = dp.array([1.0, 2.0, 3.0, 3.0, 2.0, 1.0])
>>> dp.power(a, b)
array([ 0.,  1.,  8., 27., 16.,  5.])

The effect of broadcasting.

>>> c = dp.array([[1, 2, 3, 3, 2, 1], [1, 2, 3, 3, 2, 1]])
>>> dp.power(a, c)
array([[ 0,  1,  8, 27, 16,  5],
       [ 0,  1,  8, 27, 16,  5]])

The ** operator can be used as a shorthand for power on dpnp.ndarray.

>>> b = dp.array([1, 2, 3, 3, 2, 1])
>>> a = dp.arange(6)
>>> a ** b
array([ 0,  1,  8, 27, 16,  5])

Negative values raised to a non-integral value will result in nan.

>>> d = dp.array([-1.0, -4.0])
>>> dp.power(d, 1.5)
array([nan, nan])