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C++

/*
* kd implementation
*
* Copyright (C) Andreas Nuechter, Kai Lingemann, Thomas Escher
*
* Released under the GPL version 3.
*
*/
/** @file
* @brief An optimized k-d tree implementation
* @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 Institute of Computer Science, University of Osnabrueck, Germany.
*/
#ifdef _MSC_VER
#define _USE_MATH_DEFINES
#endif
#include "slam6d/kd.h"
#include "slam6d/globals.icc"
#include <iostream>
using std::cout;
using std::cerr;
using std::endl;
#include <algorithm>
using std::swap;
#include <cmath>
#include <cstring>
// KDtree class static variables
KDParams KDtree::params[MAX_OPENMP_NUM_THREADS];
/**
* Constructor
*
* Create a KD tree from the points pointed to by the array pts
*
* @param pts 3D array of points
* @param n number of points
*/
KDtree::KDtree(double **pts, int n)
{
// Find bbox
double xmin = pts[0][0], xmax = pts[0][0];
double ymin = pts[0][1], ymax = pts[0][1];
double zmin = pts[0][2], zmax = pts[0][2];
for (int i = 1; i < n; i++) {
xmin = min(xmin, pts[i][0]);
xmax = max(xmax, pts[i][0]);
ymin = min(ymin, pts[i][1]);
ymax = max(ymax, pts[i][1]);
zmin = min(zmin, pts[i][2]);
zmax = max(zmax, pts[i][2]);
}
// Leaf nodes
if ((n > 0) && (n <= 10)) {
npts = n;
leaf.p = new double*[n];
memcpy(leaf.p, pts, n * sizeof(double *));
return;
}
// Else, interior nodes
npts = 0;
node.center[0] = 0.5 * (xmin+xmax);
node.center[1] = 0.5 * (ymin+ymax);
node.center[2] = 0.5 * (zmin+zmax);
node.dx = 0.5 * (xmax-xmin);
node.dy = 0.5 * (ymax-ymin);
node.dz = 0.5 * (zmax-zmin);
node.r2 = sqr(node.dx) + sqr(node.dy) + sqr(node.dz);
// Find longest axis
if (node.dx > node.dy) {
if (node.dx > node.dz) {
node.splitaxis = 0;
} else {
node.splitaxis = 2;
}
} else {
if (node.dy > node.dz) {
node.splitaxis = 1;
} else {
node.splitaxis = 2;
}
}
// Partition
double splitval = node.center[node.splitaxis];
if ( fabs(max(max(node.dx,node.dy),node.dz)) < 0.01 ) {
npts = n;
leaf.p = new double*[n];
memcpy(leaf.p, pts, n * sizeof(double *));
return;
}
double **left = pts, **right = pts + n - 1;
while (1) {
while ((*left)[node.splitaxis] < splitval)
left++;
while ((*right)[node.splitaxis] >= splitval)
right--;
if (right < left)
break;
swap(*left, *right);
}
// Build subtrees
int i;
#ifdef WITH_OPENMP_KD // does anybody know the reason why this is slower ?? --Andreas
omp_set_num_threads(OPENMP_NUM_THREADS);
#pragma omp parallel for schedule(dynamic)
#endif
for (i = 0; i < 2; i++) {
if (i == 0) node.child1 = new KDtree(pts, left-pts);
if (i == 1) node.child2 = new KDtree(left, n-(left-pts));
}
}
KDtree::~KDtree()
{
if (!npts) {
#ifdef WITH_OPENMP_KD
omp_set_num_threads(OPENMP_NUM_THREADS);
#pragma omp parallel for schedule(dynamic)
#endif
for (int i = 0; i < 2; i++) {
if (i == 0 && node.child1) delete node.child1;
if (i == 1 && node.child2) delete node.child2;
}
} else {
if (leaf.p) delete [] leaf.p;
}
}
/**
* Finds the closest point within the tree,
* wrt. the point given as first parameter.
* @param _p point
* @param maxdist2 maximal search distance.
* @param threadNum Thread number, for parallelization
* @return Pointer to the closest point
*/
double *KDtree::FindClosest(double *_p, double maxdist2, int threadNum) const
{
params[threadNum].closest = 0;
params[threadNum].closest_d2 = maxdist2;
params[threadNum].p = _p;
_FindClosest(threadNum);
return params[threadNum].closest;
}
/**
* Wrapped function
*/
void KDtree::_FindClosest(int threadNum) const
{
// Leaf nodes
if (npts) {
for (int i = 0; i < npts; i++) {
double myd2 = Dist2(params[threadNum].p, leaf.p[i]);
if (myd2 < params[threadNum].closest_d2) {
params[threadNum].closest_d2 = myd2;
params[threadNum].closest = leaf.p[i];
}
}
return;
}
// Quick check of whether to abort
double approx_dist_bbox = max(max(fabs(params[threadNum].p[0]-node.center[0])-node.dx,
fabs(params[threadNum].p[1]-node.center[1])-node.dy),
fabs(params[threadNum].p[2]-node.center[2])-node.dz);
if (approx_dist_bbox >= 0 && sqr(approx_dist_bbox) >= params[threadNum].closest_d2)
return;
// Recursive case
double myd = node.center[node.splitaxis] - params[threadNum].p[node.splitaxis];
if (myd >= 0.0) {
node.child1->_FindClosest(threadNum);
if (sqr(myd) < params[threadNum].closest_d2) {
node.child2->_FindClosest(threadNum);
}
} else {
node.child2->_FindClosest(threadNum);
if (sqr(myd) < params[threadNum].closest_d2) {
node.child1->_FindClosest(threadNum);
}
}
}