bitwise_xor(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Some inconsistencies with the Dask version may exist.

Compute the bit-wise XOR of two arrays element-wise.

Computes the bit-wise XOR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ^ .

Parameters

x1, x2 : array_like

Only integer and boolean types are handled. If x1.shape != x2.shape , they must be broadcastable to a common shape (which becomes the shape of the output).

out : ndarray, None, or tuple of ndarray and None, 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. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

where : array_like, optional

This condition is broadcast over the input. At locations where the condition is True, the :None:None:`out` array will be set to the ufunc result. Elsewhere, the :None:None:`out` array will retain its original value. Note that if an uninitialized :None:None:`out` array is created via the default out=None , locations within it where the condition is False will remain uninitialized.

**kwargs :

For other keyword-only arguments, see the ufunc docs <ufuncs.kwargs> .

Returns

out : ndarray or scalar

Result. This is a scalar if both :None:None:`x1` and :None:None:`x2` are scalars.

This docstring was copied from numpy.bitwise_xor.

See Also

binary_repr

Return the binary representation of the input number as a string.

bitwise_and

bitwise_or

logical_xor

Examples

The number 13 is represented by 00001101 . Likewise, 17 is represented by 00010001 . The bit-wise XOR of 13 and 17 is therefore 00011100 , or 28:

This example is valid syntax, but we were not able to check execution

>>> np.bitwise_xor(13, 17)  # doctest: +SKIP
28

This example is valid syntax, but we were not able to check execution

>>> np.binary_repr(28)  # doctest: +SKIP
'11100'

This example is valid syntax, but we were not able to check execution

>>> np.bitwise_xor(31, 5)  # doctest: +SKIP
26

This example is valid syntax, but we were not able to check execution

>>> np.bitwise_xor([31,3], 5)  # doctest: +SKIP
array([26,  6])

This example is valid syntax, but we were not able to check execution

>>> np.bitwise_xor([31,3], [5,6])  # doctest: +SKIP
array([26,  5])

This example is valid syntax, but we were not able to check execution

>>> np.bitwise_xor([True, True], [False, True])  # doctest: +SKIP
array([ True, False])

The ^ operator can be used as a shorthand for np.bitwise_xor on ndarrays.

This example is valid syntax, but we were not able to check execution

>>> x1 = np.array([True, True])  # doctest: +SKIP
... x2 = np.array([False, True])  # doctest: +SKIP
... x1 ^ x2  # doctest: +SKIP
array([ True, False])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.ufunc.bitwise_or dask.array.ufunc.logical_xor dask.array.ufunc.invert dask.array.ufunc.bitwise_and

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