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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>
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. If Traits is CGAL::Search_traits_adapter<Key,PointPropertyMap,BaseTraits> the default type is CGAL::Distance_adapter<Key,PointPropertyMap,CGAL::Euclidean_distance<Traits> >, and CGAL::Euclidean_distance<Traits> otherwise.
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.
| Traits::Point_d | Point_d; | Point type. |
| Traits::FT | FT; | Number type. |
| OrthogonalDistance | Distance; | Distance type. |
| GeneralDistance::Query_item | Query_item; | Query item. |
| std::pair<Point_d,FT> | Point_with_transformed_distance; | Pair of point and transformed distance. |
| SpatialTree | Tree; | The tree type. |
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Constructor for searching approximately k neighbors of the query item query
in the points stored in tree using
distance d and approximation factor eps.sorted indicates
if the computed sequence of k-nearest neighbors needs to be sorted.
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| iterator | s.begin () const | Returns a const iterator to the approximate nearest or furthest neighbor. |
| iterator | s.end () const | Returns the appropriate past-the-end const iterator. |
| std::ostream& | s.statistics ( std::ostream& s) | Inserts statistics of the search process into the output stream s. |
CGAL::K_neighbor_search<Traits, GeneralDistance, Splitter, SpatialTree>