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