# numpy.packbits

numpy.packbits(a, /, axis=None, bitorder='big')

  Packs the elements of a binary-valued array into bits in a uint8 array.

  The result is padded to full bytes by inserting zero bits at the end.

  Parameters:
    a array_like

      An array of integers or booleans whose elements should be packed to bits.

    axis int, optional

      The dimension over which bit-packing is done. `None` implies packing the flattened array.

    bitorder{‘big’, ‘little’}, optional

      The order of the input bits. ‘big’ will mimic bin(val), `[0, 0, 0, 0, 0, 0, 1, 1] => 3 = 0b00000011`, ‘little’ will reverse the order so `[1, 1, 0, 0, 0, 0, 0, 0] => 3`. Defaults to ‘big’.

      New in version 1.17.0.

  Returns:
    packed ndarray

      Array of type uint8 whose elements represent bits corresponding to the logical (0 or nonzero) value of the input elements. The shape of packed has the same number of dimensions as the input (unless axis is None, in which case the output is 1-D).

  See also

  `unpackbits`

    Unpacks elements of a uint8 array into a binary-valued output array.

  Examples

      >>> a = np.array([[[1,0,1],
      ...                [0,1,0]],
      ...               [[1,1,0],
      ...                [0,0,1]]])
      >>> b = np.packbits(a, axis=-1)
      >>> b
      array([[[160],
              [ 64]],
             [[192],
              [ 32]]], dtype=uint8)

  Note that in binary 160 = 1010 0000, 64 = 0100 0000, 192 = 1100 0000, and 32 = 0010 0000.