numpy.ma.unique#

ma.unique(ar1, return_index=False, return_inverse=False)[source]#

Finds the unique elements of an array.

Masked values are considered the same element (masked). The output array is always a masked array. See numpy.unique for more details.

See also

numpy.unique: Equivalent function for ndarrays.

Examples

>>> a = [1, 2, 1000, 2, 3]
>>> mask = [0, 0, 1, 0, 0]
>>> masked_a = np.ma.masked_array(a, mask)
>>> masked_a
masked_array(data=[1, 2, --, 2, 3],
            mask=[False, False,  True, False, False],
    fill_value=999999)
>>> np.ma.unique(masked_a)
masked_array(data=[1, 2, 3, --],
            mask=[False, False, False,  True],
    fill_value=999999)
>>> np.ma.unique(masked_a, return_index=True)
(masked_array(data=[1, 2, 3, --],
            mask=[False, False, False,  True],
    fill_value=999999), array([0, 1, 4, 2]))
>>> np.ma.unique(masked_a, return_inverse=True)
(masked_array(data=[1, 2, 3, --],
            mask=[False, False, False,  True],
    fill_value=999999), array([0, 1, 3, 1, 2]))
>>> np.ma.unique(masked_a, return_index=True, return_inverse=True)
(masked_array(data=[1, 2, 3, --],
            mask=[False, False, False,  True],
    fill_value=999999), array([0, 1, 4, 2]), array([0, 1, 3, 1, 2]))