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69 lines
1.4 KiB
Plaintext
69 lines
1.4 KiB
Plaintext
/** @file
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* @brief Representation of the optimized k-d tree.
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* @author Andreas Nuechter. Institute of Computer Science, University of Osnabrueck, Germany.
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* @author Kai Lingemann. Institute of Computer Science, University of Osnabrueck, Germany.
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* @author Thomas Escher
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*/
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#ifndef __KD_H__
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#define __KD_H__
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#include "slam6d/kdparams.h"
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#include "slam6d/searchTree.h"
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#include "slam6d/kdTreeImpl.h"
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#ifdef _MSC_VER
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#if !defined _OPENMP && defined OPENMP
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#define _OPENMP
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#endif
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#endif
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#ifdef _OPENMP
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#include <omp.h>
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#endif
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struct Void { };
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struct PtrAccessor {
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inline double *operator() (Void, double* indices) {
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return indices;
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}
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};
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/**
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* @brief The optimized k-d tree.
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*
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* A kD tree for points, with limited
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* capabilities (find nearest point to
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* a given point, or to a ray).
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**/
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class KDtree : public SearchTree, private KDTreeImpl<Void, double*, PtrAccessor>
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{
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public:
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KDtree(double **pts, int n);
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virtual ~KDtree();
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virtual double *FindClosest(double *_p,
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double maxdist2,
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int threadNum = 0) const;
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virtual double *FindClosestAlongDir(double *_p,
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double *_dir,
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double maxdist2,
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int threadNum = 0) const;
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virtual vector<Point> kNearestNeighbors(double *_p,
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int k,
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double sqRad2,
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int threadNum = 0) const;
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virtual vector<Point> fixedRangeSearch(double *_p,
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double sqRad2,
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int threadNum = 0) const;
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};
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#endif
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