/**
* 1. Data sample : pp200 W->e nu with pile-up corresponding to 1 MHz min. bias
* events, 50 K event y2011, 10 K event y2012.
*
* 2. Proof of principal: no pile-up for both PPV and KFV
*
* a. Reconstructed primary track multiplicity versus corresponding MC
* "reconstructable" (i.e. in n STAR acceptance,no. TPC MC hits >= 15) tracks
* multiplicity.
*
* b. Corrected reconstructed primary track multiplicity (i.e. multiplied by
* QA/100.) versus corresponding MC "reconstructable" (i.e. in n STAR
* acceptance,no. TPC MC hits >= 15) tracks multiplicity.
*
* c. Efficiency primary vertex reconstruction versus MC "reconstructable"
* tracks multiplicity.
*
* 3. With pileup. repeat above (a-c) with old ranking scheme for
*
* I. Any reconstructed primary vertex which is matched with MC trigger
* vertex (MC = 1)
*
* II. The best (in sense of ranking) reconstructed primary vertex which is
* matched with MC trigger vertex (MC = 1)
*
* III. The best (in sense of ranking) reconstructed primary vertex which is
* not matched with MC trigger vertex (MC != 1)
*
* 4. With pileup. repeat above (a-c) with new ranking scheme for cases I-III
*/
void MuMcPrVKFV2012(Long64_t nevent, const char *file, const std::string& outFile, bool fillNtuple)
{
#ifdef __TMVA__
boost::replace_last(outFile, ".root", "");
outFile += ".TMVArank.root";
// create a set of variables and declare them to the reader
// - the variable names must corresponds in name and type to
// those given in the weight file(s) that you use
TString separator(":");
TString Vnames(vnames);
TObjArray *array = Vnames.Tokenize(separator);
std::vector<std::string> inputVars;
TIter next(array);
TObjString *objs;
while ((objs = (TObjString *) next())) {
std::cout << objs->GetString() << std::endl;
}
inputVars.push_back("beam");
inputVars.push_back("postx");
inputVars.push_back("prompt");
inputVars.push_back("cross");
inputVars.push_back("tof");
inputVars.push_back("notof");
inputVars.push_back("EEMC");
inputVars.push_back("noEEMC");
inputVars.push_back("chi2");
std::vector<double> *inputVec = new std::vector<double>( inputVars.size() );
IClassifierReader *classReader = new ReadBDT( inputVars );
#endif /* __TMVA__ */
TFile *fOut = TFile::Open(outFile.c_str(), "recreate");
data_t data;
// Book histograms
const int nMcRecMult = 75;
TArrayD xMult(nMcRecMult + 1);
xMult[0] = -0.5;
for (int i = 1; i <= nMcRecMult; i++) {
if (xMult[i - 1] < 50) xMult[i] = xMult[i - 1] + 1; // 1 - 50
else if (xMult[i - 1] < 100) xMult[i] = xMult[i - 1] + 2; // 51 - 75
else if (xMult[i - 1] < 200) xMult[i] = xMult[i - 1] + 10; // 76 - 85
else xMult[i] = xMult[i - 1] + 100; // 86 -100
}
TH1D *McRecMulT = new TH1D("McRecMulT", "Reconstructable multiplicity for trigger Mc Vertex", nMcRecMult, xMult.GetArray());
struct Name_t {
const Char_t *Name;
const Char_t *Title;
};
const Name_t HCases[3] = {
{"Any", "Any vertex matched with MC == 1"},
{"Good", "The best rank vertex with MC == 1"},
{"Bad", "The best rank vertex with MC != 1"}
};
const Name_t Plots[4] = {
{"Mult" , "the reconstructed (uncorrected) track multiplicity versus Reconstructable multiplicity"},
{"MultQA" , "the reconstructed (corrected for QA) track multiplicity versus Reconstructable multiplicity"},
{"McRecMul", "Reconstructable multiplicity"},
{"YvsX" , "Bad versus Good value"}
};
/* h p */
TH1 *hists[3][4];
for (int h = 0; h < 3; h++) {
for (int p = 0; p < 4; p++) {
TString Name(Plots[p].Name); Name += HCases[h].Name;
TString Title(Plots[p].Title); Title += " for "; Title += HCases[h].Title; Title += " vertex";
if (p < 2) hists[h][p] = new TH2D(Name, Title, nMcRecMult, xMult.GetArray(), nMcRecMult, xMult.GetArray());
else if (p == 2) hists[h][p] = new TH1D(Name, Title, nMcRecMult, xMult.GetArray());
}
}
TNtuple *VertexG = new TNtuple("VertexG", "good vertex & global params info", vnames);
TNtuple *VertexB = new TNtuple("VertexB", "bad vertex & global params info", vnames);
// ----------------------------------------------
StMuDstMaker *maker = new StMuDstMaker(0, 0, "", file, "st:MuDst.root", 1e9); // set up maker in read mode
// 0,0 this mean read mode
// dir read all files in this directory
// file bla.lis real all file in this list, if (file!="") dir is ignored
// filter apply filter to filenames, multiple filters are separated by ':'
// 10 maximum number of file to read
maker->SetStatus("*", 0);
std::vector<std::string> activeBranchNames = {
"MuEvent",
"PrimaryVertices",
"StStMuMcVertex",
"StStMuMcTrack"
};
// Set Active braches
for (const auto& branchName : activeBranchNames)
maker->SetStatus(branchName.c_str(), 1);
TChain *tree = maker->chain();
Long64_t nentries = tree->GetEntries();
nevent = TMath::Min(nevent, nentries);
std::cout << nentries << " events in chain " << nevent << " will be read." << std::endl;
tree->SetCacheSize(-1); //by setting the read cache to -1 we set it to the AutoFlush value when writing
tree->SetCacheLearnEntries(1); //one entry is sufficient to learn
tree->SetCacheEntryRange(0, nevent);
for (Long64_t ev = 0; ev < nevent; ev++) {
if (maker->Make()) break;
StMuDst *muDst = maker->muDst(); // get a pointer to the StMuDst class, the class that points to all the data
StMuEvent *muEvent = muDst->event(); // get a pointer to the class holding event-wise information
int referenceMultiplicity = muEvent->refMult(); // get the reference multiplicity
TClonesArray *PrimaryVertices = muDst->primaryVertices();
int nPrimaryVertices = PrimaryVertices->GetEntriesFast();
TClonesArray *MuMcVertices = muDst->mcArray(0);
int nMuMcVertices = MuMcVertices->GetEntriesFast();
TClonesArray *MuMcTracks = muDst->mcArray(1);
int nMuMcTracks = MuMcTracks->GetEntriesFast();
if ( nevent >= 10 && ev % int(nevent*0.1) == 0 )
{
std::cout << "Event #" << ev << "\tRun\t" << muEvent->runId()
<< "\tId: " << muEvent->eventId()
<< " refMult= " << referenceMultiplicity
<< "\tPrimaryVertices " << nPrimaryVertices
<< "\t" << " " << nMuMcVertices
<< "\t" << " " << nMuMcTracks
<< std::endl;
}
// const Double_t field = muEvent->magneticField()*kilogauss;
if (! nMuMcVertices || ! nMuMcTracks || nPrimaryVertices <= 0) {
std::cout << "Ev. " << ev << " has no MC information ==> skip it" << std::endl;
std::cout << "OR no reconstructed verticies found" << std::endl;
continue;
}
// Count number of MC tracks at a vertex with TPC reconstructable tracks
std::multimap<int, int> Mc2McHitTracks;
for (int m = 0; m < nMuMcTracks; m++) {
StMuMcTrack *McTrack = (StMuMcTrack *) MuMcTracks->UncheckedAt(m);
if (McTrack->No_tpc_hit() < 15) continue;
Mc2McHitTracks.insert(std::pair<int, int>(McTrack->IdVx(), McTrack->Id()));
}
// This is the "reconstructable" track multiplicity
int nMcTracksWithHits = Mc2McHitTracks.count(1);
// Let's skip events in which we do not expect to reconstruct any tracks
// (and thus vertex) from the primary vertex
if (nMcTracksWithHits <= 0) continue;
// This is our denominator histogram for efficiencies
McRecMulT->Fill(nMcTracksWithHits);
// ============= Build map between Rc and Mc vertices
std::map<StMuPrimaryVertex *, StMuMcVertex *> reco2McVertices;
TArrayF vertexRanks(nPrimaryVertices);
int mcMatchedVertexIndex = -1; // any vertex with MC==1 and highest reconstrated multiplicity.
int vertexMaxMultiplicity = -1;
// First loop over all verticies in this event. There is at least one
// must be available
for (int recoVertexIndex = 0; recoVertexIndex < nPrimaryVertices; recoVertexIndex++)
{
vertexRanks[recoVertexIndex] = -1e10;
StMuPrimaryVertex *recoVertex = (StMuPrimaryVertex *) PrimaryVertices->UncheckedAt(recoVertexIndex);
if ( !AcceptVX(recoVertex) ) continue;
// Check Mc
if (recoVertex->idTruth() < 0 || recoVertex->idTruth() > nMuMcVertices) {
std::cout << "ERROR: Illegal idTruth " << recoVertex->idTruth() << " The track is ignored" << std::endl;
continue;
}
StMuMcVertex *mcVertex = (StMuMcVertex *) MuMcVertices->UncheckedAt(recoVertex->idTruth() - 1);
if (mcVertex->Id() != recoVertex->idTruth()) {
std::cout << "ERROR: Mismatched idTruth " << recoVertex->idTruth() << " and mcVertex Id " << mcVertex->Id()
<< " The vertex is ignored" << std::endl;
continue;
}
reco2McVertices[recoVertex] = mcVertex;
vertexRanks[recoVertexIndex] = recoVertex->ranking();
if (recoVertex->idTruth() == 1 && recoVertex->noTracks() > vertexMaxMultiplicity)
{
mcMatchedVertexIndex = recoVertexIndex;
vertexMaxMultiplicity = recoVertex->noTracks();
}
FillData(data, recoVertex);
#ifdef __TMVA__
Float_t *dataArray = &data.beam;
for (size_t j = 0; j < inputVec->size(); j++)
(*inputVec)[j] = dataArray[j];
vertexRanks[recoVertexIndex] = classReader->GetMvaValue( *inputVec );
#endif
}
// If we reconstructed a vertex which matches the MC one we fill the
// numerator of the "Any" efficiency histogram
if (mcMatchedVertexIndex != -1) {
StMuPrimaryVertex *recoVertexMatchedMc = (StMuPrimaryVertex*) PrimaryVertices->UncheckedAt(mcMatchedVertexIndex);
double nTracks = recoVertexMatchedMc->noTracks();
double nTracksQA = nTracks * recoVertexMatchedMc->qaTruth() / 100.;
hists[0][0]->Fill(nMcTracksWithHits, nTracks);
hists[0][1]->Fill(nMcTracksWithHits, nTracksQA);
hists[0][2]->Fill(nMcTracksWithHits);
}
// Now deal with the highest rank vertex
int maxRankVertexIndex = TMath::LocMax(nPrimaryVertices, vertexRanks.GetArray());
StMuPrimaryVertex *recoVertexMaxRank = (StMuPrimaryVertex*) PrimaryVertices->UncheckedAt(maxRankVertexIndex);
StMuMcVertex *mcVertex = reco2McVertices[recoVertexMaxRank];
double nTracks = recoVertexMaxRank->noTracks();
double nTracksQA = nTracks * recoVertexMaxRank->qaTruth() / 100.;
// Fill numerator for "good" and "bad" efficiencies
int h = ( mcVertex && mcVertex->Id() == 1) ? 1 : 2;
hists[h][0]->Fill(nMcTracksWithHits, nTracks);
hists[h][1]->Fill(nMcTracksWithHits, nTracksQA);
hists[h][2]->Fill(nMcTracksWithHits);
// Proceed with filling ntuple only if requested by the user
if ( !fillNtuple ) continue;
// Second loop over all verticies in this event
for (int recoVertexIndex = 0; recoVertexIndex < nPrimaryVertices; recoVertexIndex++)
{
StMuPrimaryVertex *recoVertex = (StMuPrimaryVertex *) PrimaryVertices->UncheckedAt(recoVertexIndex);
if ( !AcceptVX(recoVertex) ) continue;
StMuMcVertex *mcVertex = reco2McVertices[recoVertex];
if ( !mcVertex ) {
std::cout << "No Match from RC to MC" << std::endl;
continue;
}
if (vtxeval::gDebugFlag) {
std::cout << Form("Vx[%3i]", recoVertexIndex) << *recoVertex << " " << *mcVertex;
int nMcTracksWithHitsatL = Mc2McHitTracks.count(recoVertex->idTruth());
std::cout << Form("Number of McTkHit %4i rank %8.3f", nMcTracksWithHitsatL, vertexRanks[recoVertexIndex]);
}
int IdPar = mcVertex->IdParTrk();
if (IdPar > 0 && IdPar <= nMuMcTracks) {
StMuMcTrack *mcTrack = (StMuMcTrack *) MuMcTracks->UncheckedAt(IdPar - 1);
if (mcTrack && vtxeval::gDebugFlag) std::cout << " " << mcTrack->GeName();
}
FillData(data, recoVertex);
double nTracks = recoVertex->noTracks();
if (mcVertex->Id() == 1 && nTracks == vertexMaxMultiplicity) {// good
VertexG->Fill(&data.beam);
}
else { // bad
VertexB->Fill(&data.beam);
}
}
if ( !gROOT->IsBatch() ) {
if (vtxeval::ask_user()) return;
}
else { vtxeval::gDebugFlag = false; }
}
fOut->Write();
}
