Numpy MaskedArray.power() function | Python

numpy.MaskedArray.power() function is used to compute element-wise base array raised to power from second array. It raise each base in arr1 to the positionally-corresponding power in arr2. arr1 and arr2 must be broadcastable to the same shape. Note that an integer type raised to a negative integer power will raise a 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.

Code #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)

Output:

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]