power

Description

Use each element in the first input as the base and each element in the second input as the exponent, and calculate the result, that is, $\text{[math]}$ .

x1 and x2 must be broadcastable to the same shape. If x1[i] contains integers and x2[i] contains negative integers, the ValueError exception is thrown. If x1[i]<0 and elements in x2[i] are not integers, NaN is returned. To return a complex number, you need to convert the type of input data to complex or specify dtype=complex.

Mandatory Input Parameters

Parameter	Type	Description
x1	array_like	Base, which is an input array or scalar
x2	array_like	Exponent, which is an input array or scalar If x1.shape!=x2.shape, they must be broadcastable to a common shape.

Optional Input Parameters

Parameter	Type	Default Value	Description
out	ndarray/ndarray tuple	None	Location where the calculation result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided, a freshly-allocated array is returned.
where	array_like	None	This condition is broadcast over the input. At locations where the condition is true, the out array stores the result. Elsewhere, the out array retains its original value.
**kwargs	-	-	Other keyword arguments. Refer to the NumPy official document Universal functions (ufunc).

Return Value

Type	Description
ndarray/scalar	Result of the bases in x1 raised to the exponents in x2

Examples

>>> import numpy as np
>>> np.power(3, 2)
9
>>> x1 = np.arange(6)
>>> x1
array([0, 1, 2, 3, 4, 5])
>>> np.power(x1, 3)
array([  0,   1,   8,  27,  64, 125])
>>> 
>>> x2 = [1.0, 2.0, 3.0, 3.0, 2.0, 1.0]
>>> np.power(x1, x2)
array([ 0.,  1.,  8., 27., 16.,  5.])
>>>

Parent topic: Basic Operation Functions