//--------------------------------------------------------------
void testApp::updateNearestNeighbors(){
float *ptsx = &positionx[0];
float *ptsy = &positiony[0];
for (int i=0; i<nParticles; i++){
dataPts[i][0] = *ptsx++;
dataPts[i][1] = *ptsy++;
}
IppiSize roiAllNeighbors = {nParticles, nNearestNeighborsK};
ippiSet_32s_C1R(-1, kNeighbors, particleStep32s, roiAllNeighbors);
annMaxPtsVisit(nMaxPointsToVisit);
kdTree = new ANNkd_tree(
dataPts, // point array
nParticles, // number of points
nDimensions, // dimension of space
nBucketSize, // bucket size
ANN_KD_SUGGEST); // splitting rule
int indexa, indexb, indexc;
float xa,ya,xb,yb;
float dist = 0;
RS.Clear();
for (indexa =0; indexa < nParticles; indexa++){
queryPt = dataPts[indexa];
kdTree->annkSearch( // search
queryPt, // query point
nNearestNeighborsK, // number of near neighbors
nnIdx, // nearest neighbors (returned)
dists, // distance (returned)
searchError); // error bound
for (int i=1; i<nNearestNeighborsK; i++) {
indexb = nnIdx[i];
if (indexb > indexa){
dist = sqrt(dists[i]); // unsquare distance
RS.Push(dist);
indexc = maxNParticles*i + indexa;
kNeighbors[indexc] = indexb;
kDistances[indexc] = dist;
}
}
}
averageInterParticleDistance = RS.Mean();
stdevInterParticleDistance = RS.StandardDeviation();
delete kdTree;
}
void AnnPairAssignment::setMaxVisitPoints(unsigned int visitPoints)
{
annMaxPtsVisit(visitPoints);
}
