def extract_cluster_amount(self, radius):
amount_clusters = <NUM_LIT:1><EOL>cluster_start = False<EOL>cluster_pick = False<EOL>total_similarity = True<EOL>previous_cluster_distance = None<EOL>previous_distance = None<EOL>cluster_borders = []<EOL>for index_ordering in range(len(self.__ordering)):<EOL><INDENT>distance = self.__ordering[index_ordering]<EOL>if distance >= radius:<EOL><INDENT>if cluster_start is False:<EOL><INDENT>cluster_start = True<EOL>amount_clusters += <NUM_LIT:1><EOL>if index_ordering != <NUM_LIT:0>:<EOL><INDENT>cluster_borders.append(index_ordering)<EOL><DEDENT><DEDENT>else:<EOL><INDENT>if (distance < previous_cluster_distance) and (cluster_pick is False):<EOL><INDENT>cluster_pick = True<EOL><DEDENT>elif (distance > previous_cluster_distance) and (cluster_pick is True):<EOL><INDENT>cluster_pick = False<EOL>amount_clusters += <NUM_LIT:1><EOL>if index_ordering != <NUM_LIT:0>:<EOL><INDENT>cluster_borders.append(index_ordering)<EOL><DEDENT><DEDENT><DEDENT>previous_cluster_distance = distance<EOL><DEDENT>else:<EOL><INDENT>cluster_start = False<EOL>cluster_pick = False<EOL><DEDENT>if (previous_distance is not None) and (distance != previous_distance):<EOL><INDENT>total_similarity = False<EOL><DEDENT>previous_distance = distance<EOL><DEDENT>if (total_similarity is True) and (previous_distance > radius):<EOL><INDENT>amount_clusters = <NUM_LIT:0><EOL><DEDENT>return amount_clusters, cluster_borders<EOL>
!
        @brief Obtains amount of clustering that can be allocated by using specified radius for ordering diagram and borders between them.
        @details When growth of reachability-distances is detected than it is considered as a start point of cluster, 
                 than pick is detected and after that recession is observed until new growth (that means end of the
                 current cluster and start of a new one) or end of diagram.

        @param[in] radius (double): connectivity radius that is used for cluster allocation.

        @return (unit, list) Amount of clusters that can be allocated by the connectivity radius on ordering diagram and borders between them using indexes
                 from ordering diagram (amount_clusters, border_clusters).