numpy.bitwise_xor() in Python

Syntax : numpy.bitwise_xor(arr1, arr2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, ufunc ‘bitwise_xor’) Parameters : arr1 : [array_like] Input array. arr2 : [array_like] Input array. out : [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. **kwargs : Allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function. where : [array_like, optional] True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone. Return : [ndarray or scalar] Result. This is a scalar if both x1 and x2 are scalars.

# Python program explaining
# bitwise_xor() function

import numpy as geek
in_num1 = 10
in_num2 = 11

print ("Input  number1 : ", in_num1)
print ("Input  number2 : ", in_num2) 
  
out_num = geek.bitwise_xor(in_num1, in_num2) 
print ("bitwise_xor of 10 and 11 : ", out_num) 

Input  number1 :  10
Input  number2 :  11
bitwise_xor of 10 and 11 :  1

# Python program explaining
# bitwise_xor() function

import numpy as geek

in_arr1 = [2, 8, 125]
in_arr2 = [3, 3, 115]
 
print ("Input array1 : ", in_arr1) 
print ("Input array2 : ", in_arr2)
  
out_arr = geek.bitwise_xor(in_arr1, in_arr2) 
print ("Output array after bitwise_xor: ", out_arr) 

Input array1 :  [2, 8, 125]
Input array2 :  [3, 3, 115]
Output array after bitwise_xor:  [ 1 11 14]

# Python program explaining
# bitwise_xor() function

import numpy as geek

in_arr1 = [True, False, True, False]
in_arr2 = [False, False, True, True]
 
print ("Input array1 : ", in_arr1) 
print ("Input array2 : ", in_arr2)
  
out_arr = geek.bitwise_xor(in_arr1, in_arr2) 
print ("Output array after bitwise_xor: ", out_arr) 

Input array1 :  [True, False, True, False]
Input array2 :  [False, False, True, True]
Output array after bitwise_xor:  [ True False False  True]