The numpy.float_power()
function in NumPy is used to return a result, such that each element of an array x1
is raised to the power of each element of another array x2
.
numpy.float_power
numpy.float_power(x1, x2, /, out=None, *, where=True)
The numpy.float_power()
function takes the following parameter values:
x1
: This represents an input array whose elements are the bases. This is a required parameter value.x2
: This represents an array whose elements are the exponents. This is a required parameter value.out
: This represents the location where the result is stored. This is an optional parameter value.where
: This is the condition over which the input is being broadcast. At a given location where this condition is True
, the resulting array will be set to the ufunc
result. Otherwise, the resulting array will retain its original value. This is an optional parameter value.**kwargs
: This represents the other keyword arguments. This is an optional parameter value.import numpy as np# creating input arraysx1 = np.array([1.1, 2.2, 3.6])x2 = np.array([2.1, 1.1, 2.5])# implementing the float_power() functionmyarray = np.float_power(x1, x2)print(x1)print(x2)print("The float_power values are: ", myarray)
numpy
module.x1
and x2\
, using the array()
function.numpy.float_power()
function on the input arrays. We assign the result to a variable called myarray
.x1
and x2
to the console.myarray
to the console.