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numpy.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
orm2
if the other isnomask
(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
orm2
.Raises: ValueError
If
m1
andm2
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], dtype=bool)
numpy.ma.mask_or()
2017-01-10 18:15:38
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