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# numpy.bitwise_or

`numpy.``bitwise_or`(x1, x2[, out]) = <ufunc 'bitwise_or'>

  Compute the bit-wise OR of two arrays element-wise.

  Computes the bit-wise OR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator `|`.

  Parameters: | x1, x2 : array_like Only integer and boolean types are handled. out : ndarray, optional Array into which the output is placed. Its type is preserved and it must be of the right shape to hold the output. See doc.ufuncs.
  Returns: | out : array_like Result.

  See also

  `logical_or`, `bitwise_and`, `bitwise_xor`

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

  Examples

  The number 13 has the binaray representation `00001101`. Likewise, 16 is represented by `00010000`. The bit-wise OR of 13 and 16 is then `000111011`, or 29:

      >>> np.bitwise_or(13, 16)
      29
      >>> np.binary_repr(29)
      '11101'

      >>> np.bitwise_or(32, 2)
      34
      >>> np.bitwise_or([33, 4], 1)
      array([33,  5])
      >>> np.bitwise_or([33, 4], [1, 2])
      array([33,  6])

      >>> np.bitwise_or(np.array([2, 5, 255]), np.array([4, 4, 4]))
      array([  6,   5, 255])
      >>> np.array([2, 5, 255]) | np.array([4, 4, 4])
      array([  6,   5, 255])
      >>> np.bitwise_or(np.array([2, 5, 255, 2147483647L], dtype=np.int32),
      ...               np.array([4, 4, 4, 2147483647L], dtype=np.int32))
      array([         6,          5,        255, 2147483647])
      >>> np.bitwise_or([True, True], [False, True])
      array([ True,  True], dtype=bool)