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

m1, m2array_like

Input masks.

copybool, optional

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

shrinkbool, optional

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

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])