* Get the number of edges * @return total number of edges */

* Get the number of vertices * @return total number of vertices */

Assignment operator definiton */

* Subdivide the list of points by a plane perpendicular on axe corresponding * to the 'cutfeat' dimension at 'cutval' position. * * On ret

Query for the \a num_closest closest points to a given point (entered as * query_point[0:dim-1]). Note that this is a short-cut method for * ind

* Find all the neighbors to \a query_point[0:dim-1] within a maximum radius. * The output is given as a vector of pairs, of which the first elemen

* Find all the neighbors to \a query_point[0:dim-1] within a maximum radius. * The output is given as a vector of pairs, of which the first elemen

* Remove the edge between two vertices. * @param [in] vertex_1 one vertex of the edge * @param [in] vertex_2 another vertex of the edge */

Remove a point from the set (Lazy Deletion) */

* Reserve space for complete graph. A complete undirected graph should have N*(N-1)/2 edges * @param num_vertices */

Stores the index in a binary file. * IMPORTANT NOTE: The set of data points is NOT stored in the file, so when * loading the index object it m

Stores the index in a binary file. * IMPORTANT NOTE: The set of data points is NOT stored in the file, so when * loading the index object it m

* @brief save precomputed covariance matrix to one binary file * * @param fout out stream * @param matrix_vector covariance matrix to be saved * @

* @brief search for neighboring voxels * @param polar_index, polar diameter index * @param pitch_index, pitch angular index * @param az

(Ground Removal + Sub Clustering) * Ground Removal + Subclustering * @param pcPtr */

* Set the rotation estimator used. * * Note: due to the fact that rotation estimator takes in a noise bound that * is dependent on the

* Set the scale estimator used * @param estimator */

* Set the translation estimator used. * @param estimator */

capacity

Returns number of points in dataset */