vector<Int_t> * Tracks::getConflictingTracksFromTrack(Int_t trackIdx) {
Int_t nClusters, nClustersReal;
Cluster * conflictCluster = nullptr;
Clusters * conflictClusters = nullptr;
vector<Int_t> * conflictingTracks = new vector<Int_t>;
vector<Int_t> * possibleTracks = nullptr;
conflictingTracks->reserve(5);
Track * trackA = At(trackIdx);
if (!trackA) { return conflictingTracks; }
conflictClusters = trackA->getConflictClusters();
nClusters = conflictClusters->GetEntriesFast();
nClustersReal = conflictClusters->GetEntries();
for (Int_t i=0; i<nClusters; i++) {
conflictCluster = conflictClusters->At(i);
if (!conflictCluster) continue;
possibleTracks = getTracksFromCluster(conflictCluster);
for (UInt_t j=0; j<possibleTracks->size(); j++) {
if (!isItemInVector(possibleTracks->at(j), conflictingTracks)) {
conflictingTracks->push_back(possibleTracks->at(j));
}
}
}
return conflictingTracks;
}
Clusters * getClusters(Int_t Runs, Int_t dataType, Int_t frameType, Float_t energy) {
run_energy = energy;
DataInterface * di = new DataInterface();
Int_t nClusters = kEventsPerRun * 5 * nLayers;
Int_t nHits = kEventsPerRun * 50;
Int_t nTracks = kEventsPerRun * 2;
Bool_t breakSignal = false;
CalorimeterFrame *cf = new CalorimeterFrame();
Clusters * clusters = new Clusters(nClusters);
Clusters * trackerClusters = new Clusters(nClusters);
Clusters * allClusters = new Clusters(nClusters * Runs);
Hits * hits = new Hits(nHits);
Hits * eventIDs = new Hits(kEventsPerRun * sizeOfEventID);
Int_t eventID = -1;
Hits * trackerHits = new Hits(nHits);
TRandom3 * gRandom = new TRandom3(0);
for (Int_t i=0; i<Runs; i++) {
cout << "Finding clusters " << i*kEventsPerRun << "->" << (i+1)*kEventsPerRun << " of " << Runs * kEventsPerRun << endl;
if (dataType == kMC) {
eventID = di->getMCFrame(i, cf);
di->getEventIDs(i, eventIDs);
cf->diffuseFrame(gRandom);
hits = cf->findHits(eventID);
clusters = hits->findClustersFromHits(); // badly optimized
clusters->removeSmallClusters(2);
clusters->matchWithEventIDs(eventIDs);
eventIDs->Clear();
}
else if (dataType == kData) {
di->getDataFrame(i, cf, energy);
hits = cf->findHits();
clusters = hits->findClustersFromHits();
clusters->removeSmallClusters(2);
clusters->removeAllClustersAfterLayer(8); // bad data in layer 10 and 11
}
clusters->Compress();
if (clusters->GetEntriesFast() == 0) breakSignal = kTRUE; // to stop running
for (Int_t j=0; j<clusters->GetEntriesFast(); j++) {
allClusters->appendCluster(clusters->At(j));
}
cf->Reset();
hits->clearHits();
trackerHits->clearHits();
clusters->clearClusters();
trackerClusters->clearClusters();
if (breakSignal) break;
}
delete cf;
delete clusters;
delete trackerClusters;
delete hits;
delete trackerHits;
delete di;
return allClusters;
}
