numpy.ma.is_mask — NumPy v1.15 Manual (original) (raw)

numpy.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.

See also

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=999999) 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', '|b1'), ('pithon', '|b1')]) ma.is_mask(m) False