Calculate combinatorial distance between a select group of
        trajectories, indicated by indices

        Arguments
        ---------
        indices : tuple
        distance_matrix : numpy.ndarray (M,M)

        Returns
        -------
        numpy.ndarray

        Notes
        -----
        This function can perhaps be quickened by calculating the sum of the
        distances. The calculated distances, as they are right now,
        are only used in a relative way. Purely summing distances would lead
        to the same result, at a perhaps quicker rate.

def sum_distances(self, indices, distance_matrix):
        """Calculate combinatorial distance between a select group of
        trajectories, indicated by indices

        Arguments
        ---------
        indices : tuple
        distance_matrix : numpy.ndarray (M,M)

        Returns
        -------
        numpy.ndarray

        Notes
        -----
        This function can perhaps be quickened by calculating the sum of the
        distances. The calculated distances, as they are right now,
        are only used in a relative way. Purely summing distances would lead
        to the same result, at a perhaps quicker rate.
        """
        combs_tup = np.array(tuple(combinations(indices, 2)))

        # Put indices from tuples into two-dimensional array.
        combs = np.array([[i[0] for i in combs_tup],
                          [i[1] for i in combs_tup]])

        # Calculate distance (vectorized)
        dist = np.sqrt(
            np.sum(np.square(distance_matrix[combs[0], combs[1]]), axis=0))

        return dist