nums.numpy.invert
-
nums.numpy.
invert
(x, out=None, where=True, **kwargs)[source] Compute bit-wise inversion, or bit-wise NOT, element-wise.
This docstring was copied from numpy.invert.
Some inconsistencies with the NumS version may exist.
Computes the bit-wise 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’s-complement 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 N-bit two’s-complement system can represent every integer in the range \(-2^{N-1}\) to \(+2^{N-1}-1\).
- Parameters
x (BlockArray) – Only integer and boolean types are handled.
out (BlockArray, None, or 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 (BlockArray, optional) – This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized 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.
- Returns
out – Result.
- Return type
BlockArray or scalar
See also
bitwise_and
,bitwise_or
,bitwise_xor
,logical_not
binary_repr
Return the binary representation of the input number as a string.
References
- 1
Wikipedia, “Two’s complement”, https://en.wikipedia.org/wiki/Two’s_complement
Examples
We’vThe doctests shown below are copied from NumPy. They won’t show the correct result until you operate
get()
.e seen that 13 is represented by
00001101
. The invert or bit-wise NOT of 13 is then:>>> x = nps.invert(nps.array(13, dtype=nps.uint8)) >>> x.get() array(242, dtype=uint8)
When using signed integer types the result is the two’s complement of the result for the unsigned type:
>>> nps.invert(nps.array([13], dtype=nps.int8)).get() array([-14], dtype=int8)
Booleans are accepted as well:
>>> nps.invert(nps.array([True, False])).get() array([False, True])