#include <CGAL/K_neighbor_search.h>
template<typename Traits, typename GeneralDistance, typename Splitter, typename SpatialTree>
class CGAL::K_neighbor_search< Traits, GeneralDistance, Splitter, SpatialTree >
The class K_neighbor_search 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.
- Template Parameters
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- See also
CGAL::Orthogonal_k_neighbor_search<Traits, OrthogonalDistance, Splitter, SpatialTree>
- Examples
- Spatial_searching/general_neighbor_searching.cpp.
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| iterator | begin () const |
| | Returns a const iterator to the approximate nearest or furthest neighbor. More...
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| iterator | end () const |
| | Returns the appropriate past-the-end const iterator. More...
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| std::ostream & | statistics (std::ostream &s) |
| | Inserts statistics of the search process into the output stream s. More...
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◆ Distance
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
◆ FT
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
◆ iterator
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
Bidirectional const iterator with value type Point_with_distance for enumerating approximate neighbors.
◆ Point_d
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
◆ Point_with_transformed_distance
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
Pair of point and transformed distance.
◆ Query_item
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
◆ Tree
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
◆ K_neighbor_search()
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
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.
◆ begin()
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
Returns a const iterator to the approximate nearest or furthest neighbor.
◆ end()
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
Returns the appropriate past-the-end const iterator.
◆ statistics()
template<typename Traits , typename GeneralDistance , typename Splitter , typename SpatialTree >
Inserts statistics of the search process into the output stream s.