numpy.logical_xor(x1, x2[, out]) = <ufunc 'logical_xor'>

Compute the truth value of x1 XOR x2, element-wise.

Parameters :

x1, x2 : array_like

Logical XOR is applied to the elements of x1 and x2. They must be broadcastable to the same shape.

Returns :

y : bool or ndarray of bool

Boolean result of the logical XOR operation applied to the elements of x1 and x2; the shape is determined by whether or not broadcasting of one or both arrays was required.


>>> np.logical_xor(True, False)
>>> np.logical_xor([True, True, False, False], [True, False, True, False])
array([False,  True,  True, False], dtype=bool)
>>> x = np.arange(5)
>>> np.logical_xor(x < 1, x > 3)
array([ True, False, False, False,  True], dtype=bool)

Simple example showing support of broadcasting

>>> np.logical_xor(0, np.eye(2))
array([[ True, False],
       [False,  True]], dtype=bool)

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