numpy.invert(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'invert'>
Compute bitwise inversion, or bitwise NOT, elementwise.
Computes the bitwise NOT of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ~
.
For signed integer inputs, the two’s complement is returned. In a two’scomplement system negative numbers are represented by the two’s complement of the absolute value. This is the most common method of representing signed integers on computers [1]. A Nbit two’scomplement system can represent every integer in the range to .
Parameters: 


Returns: 

See also
bitwise_and
, bitwise_or
, bitwise_xor
, logical_not
binary_repr
bitwise_not
is an alias for invert
:
>>> np.bitwise_not is np.invert True
[1]  Wikipedia, “Two’s complement”, https://en.wikipedia.org/wiki/Two’s_complement 
We’ve seen that 13 is represented by 00001101
. The invert or bitwise NOT of 13 is then:
>>> x = np.invert(np.array(13, dtype=np.uint8)) >>> x 242 >>> np.binary_repr(x, width=8) '11110010'
The result depends on the bitwidth:
>>> x = np.invert(np.array(13, dtype=np.uint16)) >>> x 65522 >>> np.binary_repr(x, width=16) '1111111111110010'
When using signed integer types the result is the two’s complement of the result for the unsigned type:
>>> np.invert(np.array([13], dtype=np.int8)) array([14], dtype=int8) >>> np.binary_repr(14, width=8) '11110010'
Booleans are accepted as well:
>>> np.invert(np.array([True, False])) array([False, True])
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Licensed under the 3clause BSD License.
https://docs.scipy.org/doc/numpy1.17.0/reference/generated/numpy.invert.html