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# numpy.ma.unique

ma.unique(ar1, return_index=False, return_inverse=False)

  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

      >>> import numpy as np
      >>> 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]))