void QAvertex(const Char_t *fdata, const Char_t *fmc)
{
style();
TFile *fdtin = TFile::Open(fdata);
TList *ldtin = (TList *)fdtin->Get("clist");
TH2 *hdtin = (TH2 *)ldtin->FindObject("zv");
TH1 *hdt = (TH1 *)ldtin->FindObject("zvNoSel");
SetHistoStyle(hdt, 20, kRed+1);
hdt->Scale(1. / hdt->Integral());
TH1 *hdt0010 = hdtin->ProjectionX("hdt0010", 1, 4);
SetHistoStyle(hdt0010, 20, kRed+1);
hdt0010->Scale(1. / hdt0010->Integral());
TH1 *hdt7080 = hdtin->ProjectionX("hdt7080", 11, 11);
SetHistoStyle(hdt7080, 25, kAzure-3);
hdt7080->Scale(1. / hdt7080->Integral());
TFile *fmcin = TFile::Open(fmc);
TList *lmcin = (TList *)fmcin->Get("clist");
TH1 *hmc = (TH1 *)lmcin->FindObject("zvNoSel");
SetHistoStyle(hmc, 25, kAzure-3);
hmc->Scale(1. / hmc->Integral());
TCanvas *c = new TCanvas("cVertex", "cVertex", 800, 800);
TH1 * hfr = c->DrawFrame(-20., 0., 20., 0.1);
hfr->SetTitle(";#it{z}_{vtx};");
hdt0010->Draw("same");
hdt7080->Draw("same");
TLegend *legend = new TLegend(0.20, 0.18+0.60, 0.50, 0.30+0.60);
legend->SetFillColor(0);
legend->SetBorderSize(0);
legend->SetTextFont(42);
legend->SetTextSize(0.04);
legend->AddEntry(hdt0010, "0-10%", "p");
legend->AddEntry(hdt7080, "70-80%", "p");
legend->Draw("same");
c->SaveAs(canvasPrefix+"vertex.pdf");
TCanvas *c1 = new TCanvas("cVertexDataMC", "cVertexDataMC", 800, 800);
hfr = c1->DrawFrame(-20., 0., 20., 0.1);
hfr->SetTitle(";#it{z}_{vtx};");
hdt->Draw("same");
hmc->Draw("same");
legend = new TLegend(0.20, 0.18+0.60, 0.50, 0.30+0.60);
legend->SetFillColor(0);
legend->SetBorderSize(0);
legend->SetTextFont(42);
legend->SetTextSize(0.04);
legend->AddEntry(hdt, "data", "p");
legend->AddEntry(hmc, "Monte Carlo", "p");
legend->Draw("same");
c1->SaveAs(canvasPrefix+"vertexDataMC.pdf");
//return 0;
}
void QAcentrality(const Char_t *fdata)
{
style();
TFile *fin = TFile::Open(fdata);
TList *lin = (TList *)fin->Get("clist");
lin->ls();
TH1 *hin = (TH1 *)lin->FindObject("EvCentrDist");
Float_t sum = 1.2 * hin->Integral(hin->FindBin(0.1), hin->FindBin(79.9));
hin->Scale(1. / sum);
SetHistoStyle(hin, 20, kRed+1);
TCanvas *c = new TCanvas("cQAcentrality", "cQAcentrality", 800, 800);
TH1 * hfr = c->DrawFrame(0., 0.005, 100., 0.015);
hfr->SetTitle(";centrality percentile;events");
hin->Draw("same");
c->SaveAs(canvasPrefix+"centrality.pdf");
TH2 *hinv0 = (TH2 *)lin->FindObject("V0");
TCanvas *cv0 = new TCanvas("cQAcentralityV0", "cQAcentralityV0", 800, 800);
cv0->SetLogx();
cv0->SetLogz();
// TH1 * hfrv0 = cv0->DrawFrame(100., -0.5, 50000., 10.5);
// DrawBinLabelsY(hfrv0, kTRUE);
// hfrv0->SetTitle(";V0 signal;");
//hinv0->Draw("same,col");
hinv0->Draw("col");
cv0->SaveAs(canvasPrefix+"centralityV0.pdf");
}
int main(int argc, char** argv)
{
// Set style options
setTDRStyle();
gStyle->SetPadTickX(1);
gStyle->SetPadTickY(1);
gStyle->SetOptTitle(0);
gStyle->SetOptStat(1110);
gStyle->SetOptFit(1);
// Set fitting options
TVirtualFitter::SetDefaultFitter("Fumili2");
//-----------------
// Input parameters
std::cout << "\n***************************************************************************************************************************" << std::endl;
std::cout << "arcg: " << argc << std::endl;
char* EBEE = argv[1];
int evtsPerPoint = atoi(argv[2]);
int useRegression = atoi(argv[3]);
std::string dayMin = "";
std::string dayMax = "";
std::string dayMinLabel = "";
std::string dayMaxLabel = "";
float absEtaMin = -1.;
float absEtaMax = -1.;
int IetaMin = -1;
int IetaMax = -1;
int IphiMin = -1;
int IphiMax = -1;
if(argc >= 5)
{
dayMin = std::string(argv[4])+" "+std::string(argv[5])+" "+std::string(argv[6]);
dayMax = std::string(argv[7])+" "+std::string(argv[8])+" "+std::string(argv[9]);
dayMinLabel = std::string(argv[4])+"_"+std::string(argv[5])+"_"+std::string(argv[6]);
dayMaxLabel = std::string(argv[7])+"_"+std::string(argv[8])+"_"+std::string(argv[9]);
t1 = dateToInt(dayMin);
t2 = dateToInt(dayMax);
}
if(argc >= 11)
{
yMIN = atof(argv[10]);
yMAX = atof(argv[11]);
}
if(argc >= 13)
{
absEtaMin = atof(argv[12]);
absEtaMax = atof(argv[13]);
}
if(argc >= 15)
{
IetaMin = atoi(argv[14]);
IetaMax = atoi(argv[15]);
IphiMin = atoi(argv[16]);
IphiMax = atoi(argv[17]);
}
std::cout << "EBEE: " << EBEE << std::endl;
std::cout << "evtsPerPoint: " << evtsPerPoint << std::endl;
std::cout << "useRegression: " << useRegression << std::endl;
std::cout << "dayMin: " << dayMin << std::endl;
std::cout << "dayMax: " << dayMax << std::endl;
std::cout << "yMin: " << yMIN << std::endl;
std::cout << "yMax: " << yMAX << std::endl;
std::cout << "absEtaMin: " << absEtaMin << std::endl;
std::cout << "absEtaMax: " << absEtaMax << std::endl;
std::cout << "IetaMin: " << IetaMin << std::endl;
std::cout << "IetaMax: " << IetaMax << std::endl;
std::cout << "IphiMin: " << IphiMin << std::endl;
std::cout << "IphiMax: " << IphiMax << std::endl;
//-------------------
// Define in/outfiles
std::string folderName = std::string(EBEE) + "_" + dayMinLabel + "_" + dayMaxLabel;
if( (absEtaMin != -1.) && (absEtaMax != -1.) )
{
char absEtaBuffer[50];
sprintf(absEtaBuffer,"_%.2f-%.2f",absEtaMin,absEtaMax);
folderName += std::string(absEtaBuffer);
}
if( (IetaMin != -1.) && (IetaMax != -1.) && (IphiMin != -1.) && (IphiMax != -1.) )
{
char absEtaBuffer[50];
sprintf(absEtaBuffer,"_Ieta_%d-%d_Iphi_%d-%d",IetaMin,IetaMax,IphiMin,IphiMax);
folderName += std::string(absEtaBuffer);
}
gSystem->mkdir(folderName.c_str());
TFile* o = new TFile((folderName+"/"+folderName+"_histos.root").c_str(),"RECREATE");
// Get trees
std::cout << std::endl;
TChain* ntu_DA = new TChain("simpleNtupleEoverP/SimpleNtupleEoverP");
FillChain(ntu_DA,"inputDATA.txt");
std::cout << " DATA: " << std::setw(8) << ntu_DA->GetEntries() << " entries" << std::endl;
TChain* ntu_MC = new TChain("simpleNtupleEoverP/SimpleNtupleEoverP");
FillChain(ntu_MC,"inputMC.txt");
std::cout << "REFERENCE: " << std::setw(8) << ntu_MC->GetEntries() << " entries" << std::endl;
if (ntu_DA->GetEntries() == 0 || ntu_MC->GetEntries() == 0 )
{
std::cout << "Error: At least one file is empty" << std::endl;
return -1;
}
// Set branch addresses
int runId;
int timeStampHigh;
int PV_n;
float scLaserCorr, seedLaserAlpha, EoP, scEta, scPhi, scE, ES, P;
int seedIeta, seedIphi, seedIx, seedIy, seedZside;
ntu_DA->SetBranchStatus("*",0);
ntu_DA->SetBranchStatus("runId",1);
ntu_DA->SetBranchStatus("timeStampHigh",1);
ntu_DA->SetBranchStatus("PV_n",1);
ntu_DA->SetBranchStatus("ele1_scLaserCorr",1);
ntu_DA->SetBranchStatus("ele1_seedLaserAlpha",1);
ntu_DA->SetBranchStatus("ele1_EOverP",1);
ntu_DA->SetBranchStatus("ele1_scEta",1);
ntu_DA->SetBranchStatus("ele1_scPhi",1);
ntu_DA->SetBranchStatus("ele1_scE",1);
ntu_DA->SetBranchStatus("ele1_scE_regression",1);
ntu_DA->SetBranchStatus("ele1_scE",1);
ntu_DA->SetBranchStatus("ele1_es",1);
ntu_DA->SetBranchStatus("ele1_tkP",1);
ntu_DA->SetBranchStatus("ele1_seedIeta",1);
ntu_DA->SetBranchStatus("ele1_seedIphi",1);
ntu_DA->SetBranchStatus("ele1_seedIx",1);
ntu_DA->SetBranchStatus("ele1_seedIy",1);
ntu_DA->SetBranchStatus("ele1_seedZside",1);
ntu_DA->SetBranchAddress("runId", &runId);
ntu_DA->SetBranchAddress("timeStampHigh", &timeStampHigh);
ntu_DA->SetBranchAddress("PV_n", &PV_n);
ntu_DA->SetBranchAddress("ele1_scLaserCorr", &scLaserCorr);
ntu_DA->SetBranchAddress("ele1_seedLaserAlpha", &seedLaserAlpha);
ntu_DA->SetBranchAddress("ele1_EOverP", &EoP);
ntu_DA->SetBranchAddress("ele1_scEta", &scEta);
ntu_DA->SetBranchAddress("ele1_scPhi", &scPhi);
if( useRegression < 1 )
ntu_DA->SetBranchAddress("ele1_scE", &scE);
else
ntu_DA->SetBranchAddress("ele1_scE_regression", &scE);
ntu_DA->SetBranchAddress("ele1_scE", &scE);
ntu_DA->SetBranchAddress("ele1_es", &ES);
ntu_DA->SetBranchAddress("ele1_tkP", &P);
ntu_DA->SetBranchAddress("ele1_seedIeta", &seedIeta);
ntu_DA->SetBranchAddress("ele1_seedIphi", &seedIphi);
ntu_DA->SetBranchAddress("ele1_seedIx", &seedIx);
ntu_DA->SetBranchAddress("ele1_seedIy", &seedIy);
ntu_DA->SetBranchAddress("ele1_seedZside", &seedZside);
ntu_MC->SetBranchStatus("*",0);
ntu_MC->SetBranchStatus("runId",1);
ntu_MC->SetBranchStatus("PV_n",1);
ntu_MC->SetBranchStatus("ele1_scEta",1);
ntu_MC->SetBranchStatus("ele1_EOverP",1);
ntu_MC->SetBranchStatus("ele1_scE",1);
ntu_MC->SetBranchStatus("ele1_scE_regression",1);
ntu_MC->SetBranchStatus("ele1_es",1);
ntu_MC->SetBranchStatus("ele1_tkP",1);
ntu_MC->SetBranchStatus("ele1_seedIeta",1);
ntu_MC->SetBranchStatus("ele1_seedIphi",1);
ntu_MC->SetBranchStatus("ele1_seedIx",1);
ntu_MC->SetBranchStatus("ele1_seedIy",1);
ntu_MC->SetBranchStatus("ele1_seedZside",1);
ntu_MC->SetBranchAddress("runId", &runId);
ntu_MC->SetBranchAddress("PV_n", &PV_n);
ntu_MC->SetBranchAddress("ele1_scEta", &scEta);
ntu_MC->SetBranchAddress("ele1_EOverP", &EoP);
if( useRegression < 1 )
ntu_MC->SetBranchAddress("ele1_scE", &scE);
else
ntu_MC->SetBranchAddress("ele1_scE_regression", &scE);
ntu_MC->SetBranchAddress("ele1_es", &ES);
ntu_MC->SetBranchAddress("ele1_tkP", &P);
ntu_MC->SetBranchAddress("ele1_seedIeta", &seedIeta);
ntu_MC->SetBranchAddress("ele1_seedIphi", &seedIphi);
ntu_MC->SetBranchAddress("ele1_seedIx", &seedIx);
ntu_MC->SetBranchAddress("ele1_seedIy", &seedIy);
ntu_MC->SetBranchAddress("ele1_seedZside", &seedZside);
//--------------------------------------------------------
// Define PU correction (to be used if useRegression == 0)
// corr = p0 + p1 * PV_n
float p0_EB;
float p1_EB;
float p0_EE;
float p1_EE;
if( useRegression == 0 )
{
//2012 EB
p0_EB = 0.9991;
p1_EB = 0.0001635;
//2012 EE
p0_EE = 0.9968;
p1_EE = 0.001046;
}
else
{
//2012 EB
p0_EB = 1.001;
p1_EB = -0.000143;
//2012 EE
p0_EE = 1.00327;
p1_EE = -0.000432;
}
float p0 = -1.;
float p1 = -1.;
if( strcmp(EBEE,"EB") == 0 )
{
p0 = p0_EB;
p1 = p1_EB;
}
else
{
p0 = p0_EE;
p1 = p1_EE;
}
//---------------------------------
// Build the reference distribution
std::cout << std::endl;
std::cout << "***** Build reference for " << EBEE << " *****" << std::endl;
TH1F* h_template = new TH1F("template", "", 2000, 0., 5.);
for(int ientry = 0; ientry < ntu_MC->GetEntries(); ++ientry)
{
if( (ientry%100000 == 0) ) std::cout << "reading MC entry " << ientry << "\r" << std::flush;
ntu_MC->GetEntry(ientry);
// selections
if( (strcmp(EBEE,"EB") == 0) && (fabs(scEta) > 1.45) ) continue; // barrel
if( (strcmp(EBEE,"EE") == 0) && (fabs(scEta) < 1.47 || fabs(scEta)>2.7) ) continue; // endcap
if( (absEtaMin != -1.) && (absEtaMax != -1.) )
{
if( (fabs(scEta) < absEtaMin) || (fabs(scEta) > absEtaMax) ) continue;
}
if( (IetaMin != -1.) && (IetaMax != -1.) && (IphiMin != -1.) && (IphiMax != -1.) )
{
if( (seedIeta < IetaMin) || (seedIeta > IetaMax) ) continue;
if( (seedIphi < IphiMin) || (seedIphi > IphiMax) ) continue;
}
// PU correction
float PUCorr = (p0 + p1*PV_n);
//std::cout << "p0: " << p0 << " p1: " << p1 << " PV_n: " << PV_n << std::endl;
// fill the template histogram
h_template -> Fill( (scE-ES)/(P-ES) / PUCorr );
}
std::cout << "Reference built for " << EBEE << " - " << h_template->GetEntries() << " events" << std::endl;
//---------------------
// Loop and sort events
std::cout << std::endl;
std::cout << "***** Sort events and define bins *****" << std::endl;
int nEntries = ntu_DA -> GetEntriesFast();
int nSavePts = 0;
std::vector<bool> isSavedEntries(nEntries);
std::vector<Sorter> sortedEntries;
std::vector<int> timeStampFirst;
for(int ientry = 0; ientry < nEntries; ++ientry)
{
ntu_DA -> GetEntry(ientry);
isSavedEntries.at(ientry) = false;
// selections
if( (strcmp(EBEE,"EB") == 0) && (fabs(scEta) > 1.45) ) continue; // barrel
if( (strcmp(EBEE,"EE") == 0) && (fabs(scEta) < 1.47 || fabs(scEta)>2.7) ) continue; // endcap
if( (absEtaMin != -1.) && (absEtaMax != -1.) )
{
if( (fabs(scEta) < absEtaMin) || (fabs(scEta) > absEtaMax) ) continue;
}
if( (IetaMin != -1.) && (IetaMax != -1.) && (IphiMin != -1.) && (IphiMax != -1.) )
{
if( (seedIeta < IetaMin) || (seedIeta > IetaMax) ) continue;
if( (seedIphi < IphiMin) || (seedIphi > IphiMax) ) continue;
}
if( timeStampHigh < t1 ) continue;
if( timeStampHigh > t2 ) continue;
if( scLaserCorr <= 0. ) continue;
isSavedEntries.at(ientry) = true;
// fill sorter
Sorter dummy;
dummy.time = timeStampHigh;
dummy.entry = ientry;
sortedEntries.push_back(dummy);
++nSavePts;
}
// sort events
std::sort(sortedEntries.begin(),sortedEntries.end(),Sorter());
std::cout << "Data sorted in " << EBEE << " - " << nSavePts << " events" << std::endl;
std::map<int,int> antiMap;
for(unsigned int iSaved = 0; iSaved < sortedEntries.size(); ++iSaved)
antiMap[sortedEntries.at(iSaved).entry] = iSaved;
//---------------------
// Loop and define bins
// "wide" bins - find events with time separation bigger than 1 day
int nWideBins = 1;
std::vector<int> wideBinEntryMax;
int timeStampOld = -1;
wideBinEntryMax.push_back(0);
for(int iSaved = 0; iSaved < nSavePts; ++iSaved)
{
if( iSaved%100000 == 0 ) std::cout << "reading saved entry " << iSaved << "\r" << std::flush;
ntu_DA->GetEntry(sortedEntries[iSaved].entry);
if( iSaved == 0 )
{
timeStampOld = timeStampHigh;
continue;
}
if( (timeStampHigh-timeStampOld)/3600. > timeLapse )
{
++nWideBins;
wideBinEntryMax.push_back(iSaved-1);
}
timeStampOld = timeStampHigh;
}
std::cout << std::endl;
wideBinEntryMax.push_back(nSavePts);
// bins with approximatively evtsPerPoint events per bin
int nBins = 0;
std::vector<int> binEntryMax;
binEntryMax.push_back(0);
for(int wideBin = 0; wideBin < nWideBins; ++wideBin)
{
int nTempBins = std::max(1,int( (wideBinEntryMax.at(wideBin+1)-wideBinEntryMax.at(wideBin))/evtsPerPoint ));
int nTempBinEntries = int( (wideBinEntryMax.at(wideBin+1)-wideBinEntryMax.at(wideBin))/nTempBins );
for(int tempBin = 0; tempBin < nTempBins; ++tempBin)
{
++nBins;
if( tempBin < nTempBins - 1 )
binEntryMax.push_back( wideBinEntryMax.at(wideBin) + (tempBin+1)*nTempBinEntries );
else
binEntryMax.push_back( wideBinEntryMax.at(wideBin+1) );
}
}
std::cout << "nBins = " << nBins << std::endl;
//for(int bin = 0; bin < nBins; ++bin)
// std::cout << "bin: " << bin
// << " entry min: " << setw(6) << binEntryMax.at(bin)
// << " entry max: " << setw(6) << binEntryMax.at(bin+1)
// << " events: " << setw(6) << binEntryMax.at(bin+1)-binEntryMax.at(bin)
// << std::endl;
//---------------------
// histogram definition
TH1F* h_scOccupancy_eta = new TH1F("h_scOccupancy_eta","", 298, -2.6, 2.6);
TH1F* h_scOccupancy_phi = new TH1F("h_scOccupancy_phi","", 363, -3.1765, 3.159);
SetHistoStyle(h_scOccupancy_eta);
SetHistoStyle(h_scOccupancy_phi);
TH2F* h_seedOccupancy_EB = new TH2F("h_seedOccupancy_EB","", 171, -85., 86., 361, 0.,361.);
TH2F* h_seedOccupancy_EEp = new TH2F("h_seedOccupancy_EEp","", 101, 0.,101., 100, 0.,101.);
TH2F* h_seedOccupancy_EEm = new TH2F("h_seedOccupancy_EEm","", 101, 0.,101., 100, 0.,101.);
SetHistoStyle(h_seedOccupancy_EB);
SetHistoStyle(h_seedOccupancy_EEp);
SetHistoStyle(h_seedOccupancy_EEm);
TH1F* h_EoP_spread = new TH1F("h_EoP_spread","",100,yMIN,yMAX);
TH1F* h_EoC_spread = new TH1F("h_EoC_spread","",100,yMIN,yMAX);
TH1F* h_EoP_spread_run = new TH1F("h_EoP_spread_run","",100,yMIN,yMAX);
TH1F* h_EoC_spread_run = new TH1F("h_EoC_spread_run","",100,yMIN,yMAX);
SetHistoStyle(h_EoP_spread,"EoP");
SetHistoStyle(h_EoC_spread,"EoC");
SetHistoStyle(h_EoP_spread_run,"EoP");
SetHistoStyle(h_EoC_spread_run,"EoC");
TH1F* h_EoP_chi2 = new TH1F("h_EoP_chi2","",50,0.,5.);
TH1F* h_EoC_chi2 = new TH1F("h_EoC_chi2","",50,0.,5.);
SetHistoStyle(h_EoP_chi2,"EoP");
SetHistoStyle(h_EoC_chi2,"EoC");
TH1F** h_EoP = new TH1F*[nBins];
TH1F** h_EoC = new TH1F*[nBins];
TH1F** h_Las = new TH1F*[nBins];
TH1F** h_Tsp = new TH1F*[nBins];
TH1F** h_Cvl = new TH1F*[nBins];
for(int i = 0; i < nBins; ++i)
{
char histoName[80];
sprintf(histoName, "EoP_%d", i);
h_EoP[i] = new TH1F(histoName, histoName, 2000, 0., 5.);
SetHistoStyle(h_EoP[i],"EoP");
sprintf(histoName, "EoC_%d", i);
h_EoC[i] = new TH1F(histoName, histoName, 2000, 0., 5.);
SetHistoStyle(h_EoC[i],"EoC");
sprintf(histoName, "Las_%d", i);
h_Las[i] = new TH1F(histoName, histoName, 500, 0.5, 1.5);
sprintf(histoName, "Tsp_%d", i);
h_Tsp[i] = new TH1F(histoName, histoName, 500, 0.5, 1.5);
}
// function definition
TF1** f_EoP = new TF1*[nBins];
TF1** f_EoC = new TF1*[nBins];
// graphs definition
TGraphAsymmErrors* g_fit = new TGraphAsymmErrors();
TGraphAsymmErrors* g_c_fit = new TGraphAsymmErrors();
TGraphAsymmErrors* g_fit_run = new TGraphAsymmErrors();
TGraphAsymmErrors* g_c_fit_run = new TGraphAsymmErrors();
TGraph* g_las = new TGraph();
TGraphErrors* g_LT = new TGraphErrors();
g_fit->GetXaxis()->SetTimeFormat("%d/%m%F1970-01-01 00:00:00");
g_fit->GetXaxis()->SetTimeDisplay(1);
g_c_fit->GetXaxis()->SetTimeFormat("%d/%m%F1970-01-01 00:00:00");
g_c_fit->GetXaxis()->SetTimeDisplay(1);
g_las->GetXaxis()->SetTimeFormat("%d/%m%F1970-01-01 00:00:00");
g_las->GetXaxis()->SetTimeDisplay(1);
g_LT->GetXaxis()->SetTimeFormat("%d/%m%F1970-01-01 00:00:00");
g_LT->GetXaxis()->SetTimeDisplay(1);
//------------------------------------
// loop on the saved and sorted events
std::cout << std::endl;
std::cout << "***** Fill and fit histograms *****" << std::endl;
std::vector<int> Entries(nBins);
std::vector<double> AveTime(nBins);
std::vector<int> MinTime(nBins);
std::vector<int> MaxTime(nBins);
std::vector<double> AveRun(nBins);
std::vector<int> MinRun(nBins);
std::vector<int> MaxRun(nBins);
std::vector<double> AveLT(nBins);
std::vector<double> AveLT2(nBins);
int iSaved = -1;
for(int ientry = 0; ientry < nEntries; ++ientry)
{
if( (ientry%100000 == 0) ) std::cout << "reading entry " << ientry << "\r" << std::flush;
if( isSavedEntries.at(ientry) == false ) continue;
++iSaved;
int iSaved = antiMap[ientry];
int bin = -1;
for(bin = 0; bin < nBins; ++bin)
if( iSaved >= binEntryMax.at(bin) && iSaved < binEntryMax.at(bin+1) )
break;
//std::cout << "bin = " << bin << " iSaved = "<< iSaved << std::endl;
ntu_DA->GetEntry(ientry);
Entries[bin] += 1;
if( iSaved == binEntryMax.at(bin)+1 ) MinTime[bin] = timeStampHigh;
if( iSaved == binEntryMax.at(bin+1)-1 ) MaxTime[bin] = timeStampHigh;
AveTime[bin] += timeStampHigh;
if( iSaved == binEntryMax.at(bin)+1 ) MinRun[bin] = runId;
if( iSaved == binEntryMax.at(bin+1)-1 ) MaxRun[bin] = runId;
AveRun[bin] += runId;
float LT = (-1. / seedLaserAlpha * log(scLaserCorr));
AveLT[bin] += LT;
AveLT2[bin] += LT*LT;
// PU correction
float PUCorr = (p0 + p1*PV_n);
// fill the histograms
(h_EoP[bin]) -> Fill( (scE-ES)/(P-ES) / scLaserCorr / PUCorr);
(h_EoC[bin]) -> Fill( (scE-ES)/(P-ES) / PUCorr );
(h_Las[bin]) -> Fill(scLaserCorr);
(h_Tsp[bin]) -> Fill(1./scLaserCorr);
h_scOccupancy_eta -> Fill(scEta);
h_scOccupancy_phi -> Fill(scPhi);
if(seedZside == 0)
h_seedOccupancy_EB -> Fill(seedIeta,seedIphi);
if(seedZside > 0)
h_seedOccupancy_EEp -> Fill(seedIx,seedIy);
if(seedZside < 0)
h_seedOccupancy_EEm -> Fill(seedIx,seedIy);
}
for(int bin = 0; bin < nBins; ++bin)
{
AveTime[bin] = 1. * AveTime[bin] / (binEntryMax.at(bin+1)-binEntryMax.at(bin));
AveRun[bin] = 1. * AveRun[bin] / (binEntryMax.at(bin+1)-binEntryMax.at(bin));
AveLT[bin] = 1. * AveLT[bin] / (binEntryMax.at(bin+1)-binEntryMax.at(bin));
AveLT2[bin] = 1. * AveLT2[bin] / (binEntryMax.at(bin+1)-binEntryMax.at(bin));
//std::cout << date << " " << AveTime[i] << " " << MinTime[i] << " " << MaxTime[i] << std::endl;
}
int rebin = 2;
if( strcmp(EBEE,"EE") == 0 ) rebin *= 2;
h_template -> Rebin(rebin);
float EoP_scale = 0.;
float EoP_err = 0.;
int EoP_nActiveBins = 0;
float EoC_scale = 0.;
float EoC_err = 0.;
int EoC_nActiveBins = 0;
float LCInv_scale = 0;
std::vector<int> validBins;
for(int i = 0; i < nBins; ++i)
{
bool isValid = true;
h_EoP[i] -> Rebin(rebin);
h_EoC[i] -> Rebin(rebin);
//------------------------------------
// Fill the graph for uncorrected data
// define the fitting function
// N.B. [0] * ( [1] * f( [1]*(x-[2]) ) )
//o -> cd();
char convolutionName[50];
sprintf(convolutionName,"h_convolution_%d",i);
//h_Cvl[i] = ConvoluteTemplate(std::string(convolutionName),h_template,h_Las[i],32768,-5.,5.);
h_Cvl[i] = MellinConvolution(std::string(convolutionName),h_template,h_Tsp[i]);
histoFunc* templateHistoFunc = new histoFunc(h_template);
histoFunc* templateConvolutedHistoFunc = new histoFunc(h_Cvl[i]);
char funcName[50];
sprintf(funcName,"f_EoP_%d",i);
if( strcmp(EBEE,"EB") == 0 )
f_EoP[i] = new TF1(funcName, templateConvolutedHistoFunc, 0.8*(h_Tsp[i]->GetMean()), 1.4*(h_Tsp[i]->GetMean()), 3, "histoFunc");
else
f_EoP[i] = new TF1(funcName, templateConvolutedHistoFunc, 0.75*(h_Tsp[i]->GetMean()), 1.5*(h_Tsp[i]->GetMean()), 3, "histoFunc");
f_EoP[i] -> SetParName(0,"Norm");
f_EoP[i] -> SetParName(1,"Scale factor");
f_EoP[i] -> SetLineWidth(1);
f_EoP[i] -> SetNpx(10000);
double xNorm = h_EoP[i]->GetEntries()/h_template->GetEntries() *
h_EoP[i]->GetBinWidth(1)/h_template->GetBinWidth(1);
f_EoP[i] -> FixParameter(0, xNorm);
f_EoP[i] -> SetParameter(1, 1.);
f_EoP[i] -> FixParameter(2, 0.);
f_EoP[i] -> SetLineColor(kRed+2);
int fStatus = 0;
int nTrials = 0;
TFitResultPtr rp;
rp = h_EoP[i] -> Fit(funcName, "QERLS+");
while( (fStatus != 0) && (nTrials < 10) )
{
rp = h_EoP[i] -> Fit(funcName, "QERLS+");
fStatus = rp;
if(fStatus == 0) break;
++nTrials;
}
// fill the graph
double eee = f_EoP[i]->GetParError(1);
//float k = f_EoP[i]->GetParameter(1);
float k = f_EoP[i]->GetParameter(1) / h_Tsp[i]->GetMean(); //needed when using mellin's convolution
if( (h_EoP[i]->GetEntries() > 3) && (fStatus == 0) && (eee > 0.05*h_template->GetRMS()/sqrt(evtsPerPoint)) )
{
float date = (float)AveTime[i];
float dLow = (float)(AveTime[i]-MinTime[i]);
float dHig = (float)(MaxTime[i]-AveTime[i]);
float run = (float)AveRun[i];
float rLow = (float)(AveRun[i]-MinRun[i]);
float rHig = (float)(MaxRun[i]-AveRun[i]);
g_fit -> SetPoint(i, date , 1./k);
g_fit -> SetPointError(i, dLow , dHig, eee/k/k, eee/k/k);
g_fit_run -> SetPoint(i, run , 1./k);
g_fit_run -> SetPointError(i, rLow , rHig, eee/k/k, eee/k/k);
h_EoP_chi2 -> Fill(f_EoP[i]->GetChisquare()/f_EoP[i]->GetNDF());
EoP_scale += 1./k;
EoP_err += eee/k/k;
++EoP_nActiveBins;
}
else
{
std::cout << "Fitting uncorrected time bin: " << i << " Fail status: " << fStatus << " sigma: " << eee << std::endl;
isValid = false;
}
//----------------------------------
// Fill the graph for corrected data
// define the fitting function
// N.B. [0] * ( [1] * f( [1]*(x-[2]) ) )
sprintf(funcName,"f_EoC_%d",i);
if( strcmp(EBEE,"EB") == 0 )
f_EoC[i] = new TF1(funcName, templateHistoFunc, 0.8, 1.4, 3, "histoFunc");
else
f_EoC[i] = new TF1(funcName, templateHistoFunc, 0.75, 1.5, 3, "histoFunc");
f_EoC[i] -> SetParName(0,"Norm");
f_EoC[i] -> SetParName(1,"Scale factor");
f_EoC[i] -> SetLineWidth(1);
f_EoC[i] -> SetNpx(10000);
xNorm = h_EoC[i]->GetEntries()/h_template->GetEntries() *
h_EoC[i]->GetBinWidth(1)/h_template->GetBinWidth(1);
f_EoC[i] -> FixParameter(0, xNorm);
f_EoC[i] -> SetParameter(1, 0.99);
f_EoC[i] -> FixParameter(2, 0.);
f_EoC[i] -> SetLineColor(kGreen+2);
rp = h_EoC[i] -> Fit(funcName, "QERLS+");
fStatus = rp;
nTrials = 0;
while( (fStatus != 0) && (nTrials < 10) )
{
rp = h_EoC[i] -> Fit(funcName, "QERLS+");
fStatus = rp;
if(fStatus == 0) break;
++nTrials;
}
// fill the graph
k = f_EoC[i]->GetParameter(1);
eee = f_EoC[i]->GetParError(1);
if( (h_EoC[i]->GetEntries() > 10) && (fStatus == 0) && (eee > 0.05*h_template->GetRMS()/sqrt(evtsPerPoint)) )
{
float date = (float)AveTime[i];
float dLow = (float)(AveTime[i]-MinTime[i]);
float dHig = (float)(MaxTime[i]-AveTime[i]);
float run = (float)AveRun[i];
float rLow = (float)(AveRun[i]-MinRun[i]);
float rHig = (float)(MaxRun[i]-AveRun[i]);
g_c_fit -> SetPoint(i, date , 1./k);
g_c_fit -> SetPointError(i, dLow , dHig , eee/k/k, eee/k/k);
g_c_fit_run -> SetPoint(i, run , 1./k);
g_c_fit_run -> SetPointError(i, rLow , rHig, eee/k/k, eee/k/k);
h_EoC_chi2 -> Fill(f_EoC[i]->GetChisquare()/f_EoP[i]->GetNDF());
EoC_scale += 1./k;
EoC_err += eee/k/k;
++EoC_nActiveBins;
}
else
{
std::cout << "Fitting corrected time bin: " << i << " Fail status: " << fStatus << " sigma: " << eee << std::endl;
isValid = false;
}
if( isValid == true ) validBins.push_back(i);
}
EoP_scale /= EoP_nActiveBins;
EoP_err /= EoP_nActiveBins;
EoC_scale /= EoC_nActiveBins;
EoC_err /= EoC_nActiveBins;
//----------------------------------------
// Fill the graph for avg laser correction
//fede
for(unsigned int itr = 0; itr < validBins.size(); ++itr)
{
int i = validBins.at(itr);
g_las -> SetPoint(itr, (float)AveTime[i], h_Tsp[i]->GetMean() );
g_LT -> SetPoint(itr, (float)AveTime[i], AveLT[i] );
g_LT -> SetPointError(itr, 0., sqrt(AveLT2[i]-AveLT[i]*AveLT[i]) / sqrt(Entries[i]) );
LCInv_scale += h_Tsp[i]->GetMean();
}
LCInv_scale /= validBins.size();
//---------------
// Rescale graphs
float yscale = 1.;
//float yscale = 1./EoC_scale;
for(unsigned int itr = 0; itr < validBins.size(); ++itr)
{
double x,y;
g_fit -> GetPoint(itr,x,y);
g_fit -> SetPoint(itr,x,y*yscale);
if ( (x > t1) && (x < t2) ) h_EoP_spread -> Fill(y*yscale);
g_c_fit -> GetPoint(itr,x,y);
g_c_fit -> SetPoint(itr,x,y*yscale);
if ( (x > t1) && (x < t2) ) h_EoC_spread -> Fill(y*yscale);
g_fit_run -> GetPoint(itr,x,y);
g_fit_run -> SetPoint(itr,x,y*yscale);
if ( (x > t1) && (x < t2) ) h_EoP_spread_run -> Fill(y*yscale);
g_c_fit_run -> GetPoint(itr,x,y);
g_c_fit_run -> SetPoint(itr,x,y*yscale);
if ( (x > t1) && (x < t2) ) h_EoC_spread_run -> Fill(y*yscale);
g_las -> GetPoint(itr,x,y);
g_las -> SetPoint(itr,x,y*yscale*EoP_scale/LCInv_scale);
}
TF1 EoC_pol0("EoC_pol0","pol0",t1,t2);
EoC_pol0.SetLineColor(kGreen+2);
EoC_pol0.SetLineWidth(2);
EoC_pol0.SetLineStyle(2);
g_c_fit -> Fit("EoC_pol0","QNR");
//----------------------------
// Print out global quantities
std::cout << std::endl;
std::cout << "***** Mean scales and errors *****" << std::endl;
std::cout << std::fixed;
std::cout << std::setprecision(4);
std::cout << "Mean EoP scale: " << std::setw(6) << EoP_scale << " mean EoP error: " << std::setw(8) << EoP_err << std::endl;
std::cout << "Mean EoC scale: " << std::setw(6) << EoC_scale << " mean EoC error: " << std::setw(8) << EoC_err << std::endl;
std::cout << "Mean 1/LC scale: " << std::setw(6) << LCInv_scale << std::endl;
//-----------------
// Occupancy plots
//-----------------
TCanvas* c_scOccupancy = new TCanvas("c_scOccupancy","SC occupancy",0,0,1000,500);
c_scOccupancy -> Divide(2,1);
c_scOccupancy -> cd(1);
h_scOccupancy_eta -> GetXaxis() -> SetTitle("sc #eta");
h_scOccupancy_eta -> GetYaxis() -> SetTitle("events");
h_scOccupancy_eta -> Draw();
c_scOccupancy -> cd(2);
h_scOccupancy_phi -> GetXaxis() -> SetTitle("sc #phi");
h_scOccupancy_phi -> GetYaxis() -> SetTitle("events");
h_scOccupancy_phi -> Draw();
TCanvas* c_seedOccupancy = new TCanvas("c_seedOccupancy","seed occupancy",0,0,1500,500);
c_seedOccupancy -> Divide(3,1);
c_seedOccupancy -> cd(1);
h_seedOccupancy_EB -> GetXaxis() -> SetTitle("seed i#eta");
h_seedOccupancy_EB -> GetYaxis() -> SetTitle("seed i#phi");
h_seedOccupancy_EB -> Draw("COLZ");
c_seedOccupancy -> cd(2);
h_seedOccupancy_EEp -> GetXaxis() -> SetTitle("seed ix");
h_seedOccupancy_EEp -> GetYaxis() -> SetTitle("seed iy");
h_seedOccupancy_EEp -> Draw("COLZ");
c_seedOccupancy -> cd(3);
h_seedOccupancy_EEm -> GetXaxis() -> SetTitle("seed ix");
h_seedOccupancy_EEm -> GetYaxis() -> SetTitle("seed iy");
h_seedOccupancy_EEm -> Draw("COLZ");
//-----------
// Chi2 plots
//-----------
TCanvas* c_chi2 = new TCanvas("c_chi2","fit chi2",0,0,500,500);
c_chi2 -> cd();
h_EoC_chi2 -> GetXaxis() -> SetTitle("#chi^{2}/N_{dof}");
h_EoC_chi2 -> Draw("");
gPad -> Update();
TPaveStats* s_EoC = new TPaveStats;
s_EoC = (TPaveStats*)(h_EoC_chi2->GetListOfFunctions()->FindObject("stats"));
s_EoC -> SetStatFormat("1.4g");
s_EoC -> SetTextColor(kGreen+2);
s_EoC->SetY1NDC(0.59);
s_EoC->SetY2NDC(0.79);
s_EoC -> Draw("sames");
gPad -> Update();
h_EoP_chi2 -> GetXaxis() -> SetTitle("#chi^{2}/N_{dof}");
h_EoP_chi2 -> Draw("sames");
gPad -> Update();
TPaveStats* s_EoP = new TPaveStats;
s_EoP = (TPaveStats*)(h_EoP_chi2->GetListOfFunctions()->FindObject("stats"));
s_EoP -> SetStatFormat("1.4g");
s_EoP -> SetTextColor(kRed+2);
s_EoP->SetY1NDC(0.79);
s_EoP->SetY2NDC(0.99);
s_EoP -> Draw("sames");
gPad -> Update();
//-------------------
// Final plot vs date
//-------------------
TCanvas* cplot = new TCanvas("cplot", "history plot vs date",100,100,1000,500);
cplot->cd();
TPad *cLeft = new TPad("pad_0","pad_0",0.00,0.00,0.75,1.00);
TPad *cRight = new TPad("pad_1","pad_1",0.75,0.00,1.00,1.00);
cLeft->SetLeftMargin(0.15);
cLeft->SetRightMargin(0.025);
cRight->SetLeftMargin(0.025);
cLeft->Draw();
cRight->Draw();
float tYoffset = 1.0;
float labSize = 0.05;
float labSize2 = 0.06;
cLeft->cd();
cLeft->SetGridx();
cLeft->SetGridy();
TH1F *hPad = (TH1F*)gPad->DrawFrame(t1,0.9,t2,1.05);
hPad->GetXaxis()->SetTimeFormat("%d/%m%F1970-01-01 00:00:00");
hPad->GetXaxis()->SetTimeDisplay(1);
hPad->GetXaxis() -> SetRangeUser(MinTime[0]-43200,MaxTime[nBins-1]+43200);
hPad->GetXaxis()->SetTitle("date (day/month)");
if( strcmp(EBEE,"EB") == 0 )
hPad->GetYaxis()->SetTitle("Relative E/p scale");
else
hPad->GetYaxis()->SetTitle("Relative E/p scale");
hPad->GetYaxis()->SetTitleOffset(tYoffset);
hPad->GetXaxis()->SetLabelSize(labSize);
hPad->GetXaxis()->SetTitleSize(labSize2);
hPad->GetYaxis()->SetLabelSize(labSize);
hPad->GetYaxis()->SetTitleSize(labSize2);
hPad -> SetMinimum(yMIN);
hPad -> SetMaximum(yMAX);
// draw history plot
g_fit -> SetMarkerStyle(24);
g_fit -> SetMarkerSize(0.7);
g_fit -> SetMarkerColor(kRed+2);
g_fit -> SetLineColor(kRed+2);
g_fit -> Draw("P");
g_c_fit -> SetMarkerStyle(20);
g_c_fit -> SetMarkerColor(kGreen+2);
g_c_fit -> SetLineColor(kGreen+2);
g_c_fit -> SetMarkerSize(0.7);
g_c_fit -> Draw("P,same");
g_las -> SetLineColor(kAzure-2);
g_las -> SetLineWidth(2);
g_las -> Draw("L,same");
TLegend* legend = new TLegend(0.60,0.78,0.90,0.94);
legend -> SetLineColor(kWhite);
legend -> SetLineWidth(0);
legend -> SetFillColor(kWhite);
legend -> SetFillStyle(0);
legend -> SetTextFont(42);
legend -> SetTextSize(0.04);
legend -> AddEntry(g_c_fit,"with LM correction","PL");
legend -> AddEntry(g_fit, "without LM correction","PL");
legend -> AddEntry(g_las, "1 / LM correction","L");
legend -> Draw("same");
char latexBuffer[250];
sprintf(latexBuffer,"CMS 2012 Preliminary");
TLatex* latex = new TLatex(0.18,0.89,latexBuffer);
latex -> SetNDC();
latex -> SetTextFont(62);
latex -> SetTextSize(0.05);
latex -> Draw("same");
//sprintf(latexBuffer,"#sqrt{s} = 8 TeV L = 3.95 fb^{-1}");
sprintf(latexBuffer,"#sqrt{s} = 8 TeV");
TLatex* latex2 = new TLatex(0.18,0.84,latexBuffer);
latex2 -> SetNDC();
latex2 -> SetTextFont(42);
latex2 -> SetTextSize(0.05);
latex2 -> Draw("same");
if( strcmp(EBEE,"EB") == 0 )
sprintf(latexBuffer,"ECAL Barrel");
else
sprintf(latexBuffer,"ECAL Endcap");
TLatex* latex3 = new TLatex(0.18,0.19,latexBuffer);
latex3 -> SetNDC();
latex3 -> SetTextFont(42);
latex3 -> SetTextSize(0.05);
latex3 -> Draw("same");
//sprintf(latexBuffer,"%.2E events",1.*nSavePts);
//TLatex* latex4 = new TLatex(0.18,0.24,latexBuffer);
//latex4 -> SetNDC();
//latex4 -> SetTextFont(42);
//latex4 -> SetTextSize(0.04);
//latex4 -> Draw("same");
//
//sprintf(latexBuffer,"%d events/bin - %d bins",evtsPerPoint,nBins);
//TLatex* latex5 = new TLatex(0.18,0.19,latexBuffer);
//latex5 -> SetNDC();
//latex5 -> SetTextFont(42);
//latex5 -> SetTextSize(0.04);
//latex5 -> Draw("same");
cRight -> cd();
TPaveStats* s_EoP_spread = new TPaveStats();
TPaveStats* s_EoC_spread = new TPaveStats();
h_EoC_spread -> SetFillStyle(3001);
h_EoC_spread -> SetFillColor(kGreen+2);
h_EoC_spread->GetYaxis()->SetLabelSize(0.09);
h_EoC_spread->GetYaxis()->SetLabelOffset(-0.03);
h_EoC_spread->GetYaxis()->SetTitleSize(0.08);
h_EoC_spread->GetYaxis()->SetNdivisions(505);
h_EoC_spread->GetXaxis()->SetLabelOffset(1000);
h_EoC_spread -> Draw("hbar");
gPad -> Update();
s_EoC_spread = (TPaveStats*)(h_EoC_spread->GetListOfFunctions()->FindObject("stats"));
s_EoC_spread -> SetStatFormat("1.4g");
s_EoC_spread->SetX1NDC(0.06); //new x start position
s_EoC_spread->SetX2NDC(0.71); //new x end position
s_EoC_spread->SetY1NDC(0.93); //new x start position
s_EoC_spread->SetY2NDC(0.84); //new x end position
s_EoC_spread -> SetOptStat(1100);
s_EoC_spread ->SetTextColor(kGreen+2);
s_EoC_spread ->SetTextSize(0.08);
s_EoC_spread -> Draw("sames");
h_EoP_spread -> SetFillStyle(3001);
h_EoP_spread -> SetFillColor(kRed+2);
h_EoP_spread -> Draw("hbarsames");
gPad -> Update();
s_EoP_spread = (TPaveStats*)(h_EoP_spread->GetListOfFunctions()->FindObject("stats"));
s_EoP_spread -> SetStatFormat("1.4g");
s_EoP_spread->SetX1NDC(0.06); //new x start position
s_EoP_spread->SetX2NDC(0.71); //new x end position
s_EoP_spread->SetY1NDC(0.83); //new x start position
s_EoP_spread->SetY2NDC(0.74); //new x end position
s_EoP_spread ->SetOptStat(1100);
s_EoP_spread ->SetTextColor(kRed+2);
s_EoP_spread ->SetTextSize(0.08);
s_EoP_spread -> Draw("sames");
/*
h_EoP_spread -> SetFillStyle(3001);
h_EoP_spread -> SetFillColor(kRed+2);
h_EoP_spread -> Draw("hbarsame");
gPad -> Update();
*/
//------------------
// Final plot vs run
//------------------
TCanvas* cplot_run = new TCanvas("cplot_run", "history plot vs run",100,100,1000,500);
cplot_run->cd();
cLeft = new TPad("pad_0_run","pad_0_run",0.00,0.00,0.75,1.00);
cRight = new TPad("pad_1_run","pad_1_run",0.75,0.00,1.00,1.00);
cLeft->SetLeftMargin(0.15);
cLeft->SetRightMargin(0.025);
cRight->SetLeftMargin(0.025);
cLeft->Draw();
cRight->Draw();
tYoffset = 1.5;
labSize = 0.04;
labSize2 = 0.07;
cLeft->cd();
cLeft->SetGridx();
cLeft->SetGridy();
hPad = (TH1F*)gPad->DrawFrame(MinRun[0]-1000,0.9,MaxRun[nBins-1]+1000,1.05);
hPad->GetXaxis()->SetTitle("run");
if( strcmp(EBEE,"EB") == 0 )
hPad->GetYaxis()->SetTitle("Relative E/p scale");
else
hPad->GetYaxis()->SetTitle("Relative E/p scale");
hPad->GetYaxis()->SetTitleOffset(tYoffset);
hPad->GetXaxis()->SetLabelSize(labSize);
hPad->GetXaxis()->SetTitleSize(labSize);
hPad->GetYaxis()->SetLabelSize(labSize);
hPad->GetYaxis()->SetTitleSize(labSize);
hPad -> SetMinimum(yMIN);
hPad -> SetMaximum(yMAX);
// draw history plot
g_fit_run -> SetMarkerStyle(20);
g_fit_run -> SetMarkerSize(0.7);
g_fit_run -> SetMarkerColor(kRed+2);
g_fit_run -> SetLineColor(kRed+2);
g_fit_run -> Draw("P");
g_c_fit_run -> SetMarkerStyle(20);
g_c_fit_run -> SetMarkerColor(kGreen+2);
g_c_fit_run -> SetLineColor(kGreen+2);
g_c_fit_run -> SetMarkerSize(0.7);
g_c_fit_run -> Draw("P,same");
cRight -> cd();
s_EoP_spread = new TPaveStats();
s_EoC_spread = new TPaveStats();
h_EoC_spread_run -> SetFillStyle(3001);
h_EoC_spread_run -> SetFillColor(kGreen+2);
h_EoC_spread_run->GetYaxis()->SetLabelSize(labSize2);
h_EoC_spread_run->GetYaxis()->SetTitleSize(labSize2);
h_EoC_spread_run->GetYaxis()->SetNdivisions(505);
h_EoC_spread_run->GetYaxis()->SetLabelOffset(-0.02);
h_EoC_spread_run->GetXaxis()->SetLabelOffset(1000);
h_EoC_spread_run -> Draw("hbar");
gPad -> Update();
s_EoC_spread = (TPaveStats*)(h_EoC_spread_run->GetListOfFunctions()->FindObject("stats"));
s_EoC_spread ->SetTextColor(kGreen+2);
s_EoC_spread ->SetTextSize(0.06);
s_EoC_spread->SetX1NDC(0.49); //new x start position
s_EoC_spread->SetX2NDC(0.99); //new x end position
s_EoC_spread->SetY1NDC(0.875); //new x start position
s_EoC_spread->SetY2NDC(0.990); //new x end position
s_EoC_spread -> SetOptStat(1100);
s_EoC_spread -> Draw("sames");
h_EoP_spread_run -> SetFillStyle(3001);
h_EoP_spread_run -> SetFillColor(kRed+2);
h_EoP_spread_run -> Draw("hbarsames");
gPad -> Update();
s_EoP_spread = (TPaveStats*)(h_EoP_spread_run->GetListOfFunctions()->FindObject("stats"));
s_EoP_spread->SetX1NDC(0.49); //new x start position
s_EoP_spread->SetX2NDC(0.99); //new x end position
s_EoP_spread->SetY1NDC(0.750); //new x start position
s_EoP_spread->SetY2NDC(0.875); //new x end position
s_EoP_spread ->SetOptStat(1100);
s_EoP_spread ->SetTextColor(kRed+2);
s_EoP_spread ->SetTextSize(0.06);
s_EoP_spread -> Draw("sames");
c_chi2 -> Print((folderName+"/"+folderName+"_fitChi2.png").c_str(),"png");
c_scOccupancy -> Print((folderName+"/"+folderName+"_scOccupancy.png").c_str(),"png");
c_seedOccupancy -> Print((folderName+"/"+folderName+"_seedOccupancy.png").c_str(),"png");
cplot -> Print((folderName+"/"+folderName+"_history_vsTime.png").c_str(),"png");
cplot_run -> Print((folderName+"/"+folderName+"_history_vsRun.png").c_str(),"png");
c_chi2 -> Print((folderName+"/"+folderName+"_fitChi2.pdf").c_str(),"pdf");
c_scOccupancy -> Print((folderName+"/"+folderName+"_scOccupancy.pdf").c_str(),"pdf");
c_seedOccupancy -> Print((folderName+"/"+folderName+"_seedOccupancy.pdf").c_str(),"pdf");
cplot -> Print((folderName+"/"+folderName+"_history_vsTime.pdf").c_str(),"pdf");
cplot_run -> Print((folderName+"/"+folderName+"_history_vsRun.pdf").c_str(),"pdf");
cplot -> SaveAs((folderName+"/"+folderName+"_history_vsTime.C").c_str());
cplot_run -> SaveAs((folderName+"/"+folderName+"_history_vsRun.C").c_str());
o -> cd();
h_template -> Write();
h_scOccupancy_eta -> Write();
h_scOccupancy_phi -> Write();
h_seedOccupancy_EB -> Write();
h_seedOccupancy_EEp -> Write();
h_seedOccupancy_EEm -> Write();
g_fit -> Write("g_fit");
g_c_fit -> Write("g_c_fit");
g_fit_run -> Write("g_fit_run");
g_c_fit_run -> Write("g_c_fit_run");
g_las -> Write("g_las");
g_LT -> Write("g_LT");
h_EoP_chi2 -> Write();
h_EoC_chi2 -> Write();
//for(int i = 0; i < nBins; ++i)
//{
// h_EoP[i] -> GetXaxis() -> SetTitle("E/p");
// h_EoP[i] -> Write();
//
// h_EoC[i] -> GetXaxis() -> SetTitle("E/p");
// h_EoC[i] -> Write();
//
// h_Tsp[i] -> Write();
//
// h_Cvl[i] -> Write();
//}
o -> Close();
}