annoviko / pyclustering

        @return (list) Updated clusters.

        """

        bypass = None;

        if (available_indexes is None):

            bypass = range(len(self.__pointer_data));

        else:

            bypass = available_indexes;

        clusters = [[] for i in range(len(centers))];

        for index_point in bypass:

            index_optim = -1;

            dist_optim = 0.0;

            for index in range(len(centers)):

                # dist = euclidean_distance(data[index_point], centers[index]);         # Slow solution

                dist = euclidean_distance_sqrt(self.__pointer_data[index_point], centers[index]);      # Fast solution

                if ( (dist < dist_optim) or (index is 0)):

                    index_optim = index;

                    dist_optim = dist;

            clusters[index_optim].append(index_point);

        return clusters;

        for index_point in range(len(self.__pointer_data)):

            index_optim = -1;

            dist_optim = 0.0;

            for index in range(len(self.__centers)):

                # dist = euclidean_distance(data[index_point], centers[index]);         # Slow solution

                dist = euclidean_distance_sqrt(self.__pointer_data[index_point], self.__centers[index]);      # Fast solution

                if ( (dist < dist_optim) or (index is 0)):

                    index_optim = index;

                    dist_optim = dist;

            clusters[index_optim].append(index_point);

        # If cluster is not able to capture object it should be removed

        clusters = [cluster for cluster in clusters if len(cluster) > 0];

        return clusters;

    def __update_centers(self):

        """!

        @brief Calculate centers of clusters in line with contained objects.

        @return (list) Updated centers as list of centers.