def get_tau_matrix(self):
        """Get tau matrix for adjacent pairs.

        Returns:
            :param tau: tau matrix for the current tree
            :type tau: np.ndarray
        """
        num_edges = len(self.edges)
        tau = np.empty([num_edges, num_edges])

        for i in range(num_edges):
            edge = self.edges[i]
            for j in edge.neighbors:
                if self.level == 1:
                    left_u = self.u_matrix[:, edge.L]
                    right_u = self.u_matrix[:, edge.R]

                else:
                    left_parent, right_parent = edge.parents
                    left_u, right_u = Edge.get_conditional_uni(left_parent, right_parent)

                tau[i, j], pvalue = scipy.stats.kendalltau(left_u, right_u)

        return tau
Get tau matrix for adjacent pairs.

        Returns:
            :param tau: tau matrix for the current tree
            :type tau: np.ndarray