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133 lines
3.4 KiB
C++
133 lines
3.4 KiB
C++
/*
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* kdMeta implementation
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*
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* Copyright (C) Andreas Nuechter, Kai Lingemann, Thomas Escher
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*
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* Released under the GPL version 3.
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*
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*/
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/** @file
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* @brief An optimized k-d tree implementation. 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. Institute of Computer Science, University of Osnabrueck, Germany.
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*/
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#ifdef _MSC_VER
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#define _USE_MATH_DEFINES
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#endif
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#include "slam6d/kdMeta.h"
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#include "slam6d/globals.icc"
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#include "slam6d/scan.h"
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#include <iostream>
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using std::cout;
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using std::cerr;
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using std::endl;
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#include <algorithm>
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using std::swap;
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#include <cmath>
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#include <cstring>
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// KDtree class static variables
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template<class PointData, class AccessorData, class AccessorFunc>
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KDParams KDTreeImpl<PointData, AccessorData, AccessorFunc>::params[MAX_OPENMP_NUM_THREADS];
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KDtreeMetaManaged::KDtreeMetaManaged(const vector<Scan*>& scans) :
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m_count_locking(0)
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{
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// create scan pointer and data pointer arrays
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m_size = scans.size();
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m_scans = new Scan*[m_size];
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for(unsigned int i = 0; i < m_size; ++i)
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m_scans[i] = scans[i];
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m_data = new DataXYZ*[m_size];
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lock();
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create(m_data, prepareTempIndices(scans), getPointsSize(scans));
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unlock();
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// allocate in prepareTempIndices, deleted here
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delete[] m_temp_indices;
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}
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KDtreeMetaManaged::~KDtreeMetaManaged()
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{
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delete[] m_scans;
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delete[] m_data;
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}
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Index* KDtreeMetaManaged::prepareTempIndices(const vector<Scan*>& scans)
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{
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unsigned int n = getPointsSize(scans);
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m_temp_indices = new Index[n];
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unsigned int s = 0, j = 0;
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unsigned int scansize = scans[s]->size<DataXYZ>("xyz reduced");
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for(unsigned int i = 0; i < n; ++i) {
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m_temp_indices[i].set(s, j++);
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// switch to next scan
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if(j >= scansize) {
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++s;
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j = 0;
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if(s < scans.size())
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scansize = scans[s]->size<DataXYZ>("xyz reduced");
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}
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}
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return m_temp_indices;
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}
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unsigned int KDtreeMetaManaged::getPointsSize(const vector<Scan*>& scans)
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{
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unsigned int n = 0;
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for(vector<Scan*>::const_iterator it = scans.begin(); it != scans.end(); ++it) {
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n += (*it)->size<DataXYZ>("xyz reduced");
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}
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return n;
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}
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double* KDtreeMetaManaged::FindClosest(double *_p, double maxdist2, int threadNum) const
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{
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params[threadNum].closest = 0;
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params[threadNum].closest_d2 = maxdist2;
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params[threadNum].p = _p;
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_FindClosest(m_data, threadNum);
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return params[threadNum].closest;
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}
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double* KDtreeMetaManaged::FindClosestAlongDir(double *_p, double *_dir, double maxdist2, int threadNum) const
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{
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params[threadNum].closest = NULL;
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params[threadNum].closest_d2 = maxdist2;
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params[threadNum].p = _p;
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params[threadNum].dir = _dir;
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_FindClosestAlongDir(m_data, threadNum);
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return params[threadNum].closest;
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}
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void KDtreeMetaManaged::lock()
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{
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boost::lock_guard<boost::mutex> lock(m_mutex_locking);
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if(m_count_locking == 0) {
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// lock all the contained scans, metascan uses the transformed points
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for(unsigned int i = 0; i < m_size; ++i) {
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m_data[i] = new DataXYZ(m_scans[i]->get("xyz reduced"));
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}
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}
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++m_count_locking;
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}
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void KDtreeMetaManaged::unlock()
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{
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boost::lock_guard<boost::mutex> lock(m_mutex_locking);
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--m_count_locking;
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if(m_count_locking == 0) {
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// delete each locking object
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for(unsigned int i = 0; i < m_size; ++i) {
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delete m_data[i];
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}
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}
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}
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