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# 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 of the integers in the input arrays. This ufunc implements the C/Python operator `~`.

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

  Parameters:
    x array_like

      Only integer and boolean types are handled.

    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 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 ndarray or scalar

      Result. This is a scalar if x 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 for `invert`:

      >>> np.bitwise_not is np.invert
      True

  References

  [1]

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

  Examples

      >>> import numpy as np

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

      >>> x = np.invert(np.array(13, dtype=np.uint8))
      >>> x
      np.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))
      >>> x
      np.uint16(65522)
      >>> np.binary_repr(x, width=16)
      '1111111111110010'

  When using signed integer types, the result is the bit-wise NOT of the 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 for `np.invert` on ndarrays.

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