# numpy.ma.mask_or

ma.mask_or(m1, m2, copy=False, shrink=True)

  Combine two masks with the `logical_or` operator.

  The result may be a view on m1 or m2 if the other is `nomask` (i.e. False).

  Parameters
    m1, m2 array_like

      Input masks.

    copy bool, optional

      If copy is False and one of the inputs is `nomask`, return a view of the other input mask. Defaults to False.

    shrink bool, optional

      Whether to shrink the output to `nomask` if all its values are False. Defaults to True.

  Returns
    mask output mask

      The result masks values that are masked in either m1 or m2.

  Raises
    ValueError

      If m1 and m2 have different flexible dtypes.

  Examples

      >>> m1 = np.ma.make_mask([0, 1, 1, 0])
      >>> m2 = np.ma.make_mask([1, 0, 0, 0])
      >>> np.ma.mask_or(m1, m2)
      array([ True,  True,  True, False])

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