Function is_mask

numpy/ma/core.py:1528–1594

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 ---------- m : array_like Array to test.

(m)

def is_mask(m):
    """
    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
    ----------
    m : array_like
        Array to test.

    Returns
    -------
    result : bool
        True if `m.dtype.type` is MaskType, False otherwise.

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

    Examples
    --------
    >>> import numpy as np
    >>> 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)],