numpy.ma.mask_or()

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 or m2 if the other is nomask (i.e. False).

Parameters:

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.

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], dtype=bool)

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.ma.mask_or.html

doc_NumPy

2025-01-10 15:47:30

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