# mars.tensor.invert¶

mars.tensor.invert(x, out=None, where=None, **kwargs)[source]

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

Computes the bit-wise NOT of the underlying binary representation of the integers in the input tensors. 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 . A N-bit two’s-complement system can represent every integer in the range $$-2^{N-1}$$ to $$+2^{N-1}-1$$.

x : array_like
Only integer and boolean types are handled.
out : Tensor, None, or tuple of Tensor 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 tensor is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.

**kwargs

out : array_like
Result.

bitwise_and, bitwise_or, bitwise_xor logical_not

bitwise_not is an alias for invert:

>>> import mars.tensor as mt

>>> mt.bitwise_not is mt.invert
True

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

We’ve seen that 13 is represented by 00001101. The invert or bit-wise NOT of 13 is then:

>>> mt.invert(mt.array(, dtype=mt.uint8)).execute()
array(, dtype=uint8)


The result depends on the bit-width:

>>> mt.invert(mt.array(, dtype=mt.uint16)).execute()
array(, dtype=uint16)


When using signed integer types the result is the two’s complement of the result for the unsigned type:

>>> mt.invert(mt.array(, dtype=mt.int8)).execute()
array([-14], dtype=int8)


Booleans are accepted as well:

>>> mt.invert(mt.array([True, False])).execute()
array([False,  True])