numpy.invert#

numpy.invert(x,/,out=None,*,where=True,casting='same_kind',order='K',dtype=None,subok=True[,signature])=<ufunc'invert'>#

Compute bit-wise inversion, or bit-wise NOT, element-wise.

Computes the bit-wise NOT of the underlying binary representation ofthe integers in the input arrays. This ufunc implements the C/Pythonoperator~.

For signed integer inputs, the bit-wise NOT of the absolute value isreturned. In a two’s-complement system, this operation effectively flipsall the bits, resulting in a representation that corresponds to thenegative of the input plus one. This is the most common method ofrepresenting signed integers on computers[1]. A N-bit two’s-complementsystem can represent every integer in the range\(-2^{N-1}\) to\(+2^{N-1}-1\).

Parameters:
xarray_like

Only integer and boolean types are handled.

outndarray, None, or tuple of ndarray and None, optional

A location into which the result is stored. If provided, it must havea shape that the inputs broadcast to. If not provided or None,a freshly-allocated array is returned. A tuple (possible only as akeyword argument) must have length equal to the number of outputs.

wherearray_like, optional

This condition is broadcast over the input. At locations where thecondition is True, theout array will be set to the ufunc result.Elsewhere, theout array will retain its original value.Note that if an uninitializedout array is created via the defaultout=None, locations within it where the condition is False willremain uninitialized.

**kwargs

For other keyword-only arguments, see theufunc docs.

Returns:
outndarray or scalar

Result.This is a scalar ifx is a scalar.

See also

bitwise_and,bitwise_or,bitwise_xor
logical_not
binary_repr

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

Notes

numpy.bitwise_not is an alias forinvert:

>>>np.bitwise_notisnp.invertTrue

References

[1]

Wikipedia, “Two’s complement”,https://en.wikipedia.org/wiki/Two’s_complement

Examples

>>>importnumpyasnp

We’ve seen that 13 is represented by00001101.The invert or bit-wise NOT of 13 is then:

>>>x=np.invert(np.array(13,dtype=np.uint8))>>>xnp.uint8(242)>>>np.binary_repr(x,width=8)'11110010'

The result depends on the bit-width:

>>>x=np.invert(np.array(13,dtype=np.uint16))>>>xnp.uint16(65522)>>>np.binary_repr(x,width=16)'1111111111110010'

When using signed integer types, the result is the bit-wise NOT ofthe unsigned type, interpreted as a signed integer:

>>>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])

The~ operator can be used as a shorthand fornp.invert onndarrays.

>>>x1=np.array([True,False])>>>~x1array([False,  True])
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