CGAL::Orthogonal_k_neighbor_search<Traits, OrthogonalDistance, Splitter, SpatialTree>

Definition

The class Orthogonal_k_neighbor_search<Traits, OrthogonalDistance, Splitter, SpatialTree> implements approximate $$k-nearest and $$k-furthest neighbor searching on a tree using an orthogonal distance class.

#include <CGAL/Orthogonal_k_neighbor_search.h>

Parameters

Expects for the first template argument an implementation of the concept SearchTraits, for example CGAL::Search_traits_2<CGAL::Cartesian<double> >.

Expects for the second template argument a model of the concept GeneralDistance. The default type is CGAL::Euclidean_distance<Traits>.

Expects for third template argument a model of the concept Splitter. The default type is CGAL::Sliding_midpoint<Traits>.

Expects for fourth template argument an implementation of the concept SpatialTree. The default type is CGAL::Kd_tree<Traits, Splitter, CGAL::Tag_true>. The template argument must be CGAL::Tag_true because orthogonal search needs extended kd tree nodes.

Types

Traits::Point_d	Point_d;	Point type.
Traits::FT	FT;	Number type.
GeneralDistance::Query_item
	Query_item;	Query item.
std::pair<Point_d,FT>
	Point_with_transformed_distance;
		Pair of point and transformed distance.

Orthogonal_k_neighbor_search<Traits, OrthogonalDistance, Splitter, SpatialTree>::iterator
	Bidirectional iterator with value type Point_with_transformed_distance for enumerating approximate neighbors.

SpatialTree

Tree;

The tree type.

Operations

Orthogonal_k_neighbor_search<Traits, OrthogonalDistance, Splitter, SpatialTree> s ( SpatialTree tree, Query_item query, int k=1, FT eps=FT(0.0), bool search_nearest=true, OrthogonalDistance d=OrthogonalDistance());
	Constructor for searching approximately $$k neighbors of the query item query in the points stored in tree using distance d and approximation factor eps.

iterator	s.begin ()	Returns an iterator to the approximate neighbors.
iterator	s.end ()	Past-the-end iterator.

advanced

std::ostream&	s.statistics ( std::ostream& s)
		Inserts statistics of the search process into the output stream s.

advanced

See Also

CGAL::K_neighbor_search<Traits, GeneralDistance, Splitter, SpatialTree>.