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The class K_neighbor_search<Traits, GeneralDistance, Splitter, SpatialTree> implements approximate k-nearest and k-furthest neighbor searching using standard search on a tree using a general distance class. The tree may be built with extended or unextended nodes.
#include <CGAL/K_neighbor_search.h>
Expects for the first template argument an implementation of the concept SearchTraits, for example CGAL::Cartesian_d<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_for_point_adapter<Key,PointPropertyMap,CGAL::Euclidean_distance<Traits> >, and CGAL::Euclidean_distance<Traits> otherwise.
Expects for fourth template argument an implementation of the concept SpatialTree. The default type is CGAL::Kd_tree<Traits, Splitter, CGAL::Tag_false>. The template argument CGAL::Tag_false makes that the tree is built with unextended nodes.
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| Point type. |
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| Number type. |
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| Distance type. |
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| Pair of point and transformed distance. |
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Bidirectional iterator with value type Point_with_distance
for enumerating approximate neighbors.
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| Query item type. |
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| The tree type. |
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Constructor for searching approximately k neighbors of the query item q
in the points stored in tree using
distance class d and approximation factor eps. sorted indicates
if the computed sequence of k-nearest neighbors needs to be sorted.
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| Returns an iterator to the approximate neighbors. |
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| Past-the-end iterator. |
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| Inserts statistics of the search process into the output stream s. |
CGAL::Orthogonal_k_neighbor_search<Traits, OrthogonalDistance, Splitter, SpatialTree>.