numpy.logical_xor () in Python

Parameters :

arr1: [array_like] Input array.
arr2: [array_like] Input array.

out: [ndarray, optional] Output array with same dimensions as Input array, placed with result.

** 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:

 An array with Boolean results of arr1  XOR  arr2 element-wise (of the same shape). 

Code 1: Working

# Python program explaining
# logic_xor () function

import numpy as np

 
# login

arr1 = [ 1 , 3 , False , 0 ]

arr2 = [ 3 , 0 , True , False ]

 
# exit

out_arr = np.logical_xor (arr1, arr2)

  

print ( " Output Array: " , out_arr)

Output:

 Output Array: [False True True False] 

Code 2: Value error if input arrays have different shapes

# Python program explaining
# logic_xor ( ) function

imp ort numpy as np

 
#input

arr1 = [ 8 , 2 , False , 4 ]

arr2 = [ 3 , 0 , False , False , 8 ]

  
# exit

out_arr = np.logical_xor (arr1, arr2)

 

print ( "Output Array:" , out_arr)

Output:

  ValueError:  operands could not be broadcast together with shapes (4,) (5,) 

Code 3: Can check status

# Python program explaining
# logic_xor () function

import numpy as np

 
# login

arr1 = np.arange ( 8 )

print ( " arr1: " , arr1)

 

print ( "arr1 & gt; 3:" , arr1 & gt; 3 )

print ( "arr1 & lt; 6:" , arr1 & lt; 6 )

 

print ( " XOR Value : " , np.logical_xor (arr1 & gt; 3 , arr1 & lt; 6 ))

Exit :

 arr1: [0 1 2 3 4 5 6 7] arr1 & gt; 3: [False False False False True True True True] arr1 & lt; 6: [True True True True True True False False] XOR Value: [True True True True False False True True] 

Links:
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.logical_xor.html#numpy .logical_xor
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