numpy.ma.mask_or#
- ma.mask_or(m1, m2, copy=False, shrink=True)[source]#
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:
- Returns:
- maskoutput 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])