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138 lines
3.4 KiB
Plaintext
138 lines
3.4 KiB
Plaintext
/** @file
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* @brief Representation of the optimized k-d tree. MetaScan variant.
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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_META_H__
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#define __KD_META_H__
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#include "kdparams.h"
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#include "searchTree.h"
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#include "data_types.h"
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#include <boost/thread/mutex.hpp>
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#include <boost/thread/locks.hpp>
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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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class Scan;
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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 KDtreeMeta : public SearchTree {
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protected:
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class Index {
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public:
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unsigned int s, i;
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inline void set(unsigned int _s, unsigned int _i) { s = _s; i = _i; }
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};
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public:
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KDtreeMeta();
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virtual ~KDtreeMeta();
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void create(const DataXYZ* const* pts, Index* indices, unsigned int n);
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virtual double *FindClosest(double *_p, double maxdist2, int threadNum = 0) const { return 0; }
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protected:
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/**
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* storing the parameters of the k-d tree, i.e., the current closest point,
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* the distance to the current closest point and the point itself.
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* These global variable are needed in this search.
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*
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* Padded in the parallel case.
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*/
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#ifdef _OPENMP
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#ifdef __INTEL_COMPILER
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__declspec (align(16)) static KDParams params[MAX_OPENMP_NUM_THREADS];
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#else
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static KDParams params[MAX_OPENMP_NUM_THREADS];
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#endif //__INTEL_COMPILER
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#else
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static KDParams params[MAX_OPENMP_NUM_THREADS];
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#endif
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/**
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* number of points. If this is 0: intermediate node. If nonzero: leaf.
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*/
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int npts;
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/**
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* Cue the standard rant about anon unions but not structs in C++
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*/
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union {
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/**
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* in case of internal node...
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*/
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struct {
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double center[3]; ///< storing the center of the voxel (R^3)
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double dx, ///< defining the voxel itself
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dy, ///< defining the voxel itself
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dz, ///< defining the voxel itself
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r2; ///< defining the voxel itself
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int splitaxis; ///< defining the kind of splitaxis
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KDtreeMeta *child1; ///< pointers to the childs
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KDtreeMeta *child2; ///< pointers to the childs
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} node;
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/**
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* in case of leaf node ...
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*/
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struct {
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//! Content is an array of indices to be put into the dynamically aquired data array
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Index* p;
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} leaf;
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};
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inline double* point(const DataXYZ* const* pts, const Index& i) const {
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return (*pts[i.s])[i.i];
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}
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void _FindClosest(const DataXYZ* const* pts, int threadNum) const;
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};
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class KDtreeMetaManaged : public KDtreeMeta {
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public:
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KDtreeMetaManaged(const vector<Scan*>& scans);
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virtual ~KDtreeMetaManaged();
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virtual void lock();
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virtual void unlock();
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//! Aquires cached data first to pass on to the usual KDtree to process
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virtual double* FindClosest(double *_p, double maxdist2, int threadNum = 0) const;
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private:
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Scan** m_scans;
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DataXYZ** m_data;
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unsigned int m_size;
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//! Mutex for safely reducing points just once in a multithreaded environment
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boost::mutex m_mutex_locking;
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volatile unsigned int m_count_locking;
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// constructor initializer list hacks
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Index* m_temp_indices;
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Index* prepareTempIndices(const vector<Scan*>& scans);
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unsigned int getPointsSize(const vector<Scan*>& scans);
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};
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#endif
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