numpy.ma.is_mask¶

ma.is_mask(m)[source]¶

Return True if m is a valid, standard mask.

This function does not check the contents of the input, only that the type is MaskType. In particular, this function returns False if the mask has a flexible dtype.

Parameters

marray_like: Array to test.

Returns

resultbool: True if m.dtype.type is MaskType, False otherwise.

See also

ma.isMaskedArray: Test whether input is an instance of MaskedArray.

Examples

>>> import numpy.ma as ma
>>> m = ma.masked_equal([0, 1, 0, 2, 3], 0)
>>> m
masked_array(data=[--, 1, --, 2, 3],
             mask=[ True, False,  True, False, False],
       fill_value=0)
>>> ma.is_mask(m)
False
>>> ma.is_mask(m.mask)
True

Input must be an ndarray (or have similar attributes) for it to be considered a valid mask.

>>> m = [False, True, False]
>>> ma.is_mask(m)
False
>>> m = np.array([False, True, False])
>>> m
array([False,  True, False])
>>> ma.is_mask(m)
True

Arrays with complex dtypes don’t return True.

>>> dtype = np.dtype({'names':['monty', 'pithon'],
...                   'formats':[bool, bool]})
>>> dtype
dtype([('monty', '|b1'), ('pithon', '|b1')])
>>> m = np.array([(True, False), (False, True), (True, False)],
...              dtype=dtype)
>>> m
array([( True, False), (False,  True), ( True, False)],
      dtype=[('monty', '?'), ('pithon', '?')])
>>> ma.is_mask(m)
False

numpy.ma.is_masked numpy.ma.isMaskedArray