numpy.bitwise_xor() function is used to Compute the bit-wise XOR of two array element-wise. This function computes the bit-wise XOR of the underlying binary representation of the integers in the input arrays.
Syntax : numpy.bitwise_xor(arr1, arr2, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, ufunc ‘bitwise_xor’)
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.
Code #1 : Working
Input number1 : 10 Input number2 : 11 bitwise_xor of 10 and 11 : 1
Code #2 :
Input array1 : [2, 8, 125] Input array2 : [3, 3, 115] Output array after bitwise_xor: [ 1 11 14]
Code #3 :
Input array1 : [True, False, True, False] Input array2 : [False, False, True, True] Output array after bitwise_xor: [ True False False True]
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