Numpy MaskedArray.power()函数| Python

numpy.MaskedArray.power()函数用于计算从第二个数组提升到幂的元素基础数组。它将 arr1 中的每个碱基提高到 arr2 中的位置对应幂。 arr1 和 arr2 必须可广播到相同的形状。请注意，整数类型的负整数幂将引发ValueError 。

Syntax : numpy.ma.power(arr1, arr2, third=None)

Parameters:
arr1 : [ array_like ] The base masked array.
arr2 :[ array_like ] The exponents masked array.
third : [ndarray, optional] A location into which the result is stored.
  -> If provided, it must have a shape that the inputs broadcast to.
  -> If not provided or None, a freshly-allocated array is returned.

Return : [ ndarray] The bases in arr1 raised to the exponents in arr2.

代码#1：

# Python program explaining
# numpy.MaskedArray.power() method 
     
# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 
     
# creating base array 
base_arr = geek.array([0, 1, 2, 3, 4, 5]) 
print ("Input base array : ", base_arr)
      
# Now we are creating a base masked array. 
# by making one entry as invalid.  
base_mask_arr = ma.masked_array(base_arr, mask =[ 0, 0, 0, 0, 1, 0]) 
print ("Base Masked array : ", base_mask_arr) 
  
# creating exponent array 
exp_arr = geek.array([0, 2, 1, 4, 2, 3]) 
print ("Input exponent array : ", exp_arr)
      
# Now we are creating a exponent masked array. 
# by making one entry as invalid.  
exp_mask_arr = ma.masked_array(exp_arr, mask =[ 0, 1, 0, 0, 1, 0]) 
print ("Exponent Masked array : ", exp_mask_arr) 
     
# applying MaskedArray.power methods 
# to masked array
out_arr = ma.power(base_mask_arr, exp_mask_arr) 
print ("Output masked array : ", out_arr)

输出：

Input base array :  [0 1 2 3 4 5]
Base Masked array :  [0 1 2 3 -- 5]
Input exponent array :  [0 2 1 4 2 3]
Exponent Masked array :  [0 -- 1 4 -- 3]
Output masked array :  [1 -- 2 81 -- 125]