3dpcp/.svn/pristine/19/190354f7a521759c16264773d5c896b468f0a276.svn-base
2012-09-16 14:33:11 +02:00

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