TGraphAsymmErrors *plotEffPt(RooDataSet *a, int aa) {
const RooArgSet *set = a->get();
RooRealVar *xAx = (RooRealVar*)set->find("pt");
RooRealVar *eff = (RooRealVar*)set->find("efficiency");
const int nbins = xAx->getBinning().numBins();
double tx[nbins], txhi[nbins], txlo[nbins];
double ty[nbins], tyhi[nbins], tylo[nbins];
for (int i=0; i<nbins; i++) {
a->get(i);
ty[i] = eff->getVal();
tx[i] = xAx->getVal();
txhi[i] = fabs(xAx->getErrorHi());
txlo[i] = fabs(xAx->getErrorLo());
tyhi[i] = fabs(eff->getErrorHi());
tylo[i] = fabs(eff->getErrorLo());
}
cout<<"NBins : "<<nbins<<endl;
const double *x = tx;
const double *xhi = txhi;
const double *xlo = txlo;
const double *y = ty;
const double *yhi = tyhi;
const double *ylo = tylo;
TGraphAsymmErrors *b = new TGraphAsymmErrors();
if(aa == 1) {
*b = TGraphAsymmErrors(nbins,x,y,xlo,xhi,ylo,yhi);
}
if(aa == 0) {
*b = TGraphAsymmErrors(nbins,x,y,0,0,ylo,yhi);
}
b->SetMaximum(1.1);
b->SetMinimum(0.0);
b->SetMarkerStyle(20);
b->SetMarkerColor(kRed+2);
b->SetMarkerSize(1.0);
b->SetTitle("");
b->GetXaxis()->SetTitleSize(0.05);
b->GetYaxis()->SetTitleSize(0.05);
b->GetXaxis()->SetTitle("p_{T} [GeV/c]");
b->GetYaxis()->SetTitle("Efficiency");
b->GetXaxis()->CenterTitle();
//b->Draw("apz");
for (int i=0; i<nbins; i++) {
cout << x[i] << " " << y[i] << " " << yhi[i] << " " << ylo[i] << endl;
}
return b;
}
pair<double,double> bkgEvPerGeV(RooWorkspace *work, int m_hyp, int cat, int spin=false){
RooRealVar *mass = (RooRealVar*)work->var("CMS_hgg_mass");
if (spin) mass = (RooRealVar*)work->var("mass");
mass->setRange(100,180);
RooAbsPdf *pdf = (RooAbsPdf*)work->pdf(Form("pdf_data_pol_model_8TeV_cat%d",cat));
RooAbsData *data = (RooDataSet*)work->data(Form("data_mass_cat%d",cat));
RooPlot *tempFrame = mass->frame();
data->plotOn(tempFrame,Binning(80));
pdf->plotOn(tempFrame);
RooCurve *curve = (RooCurve*)tempFrame->getObject(tempFrame->numItems()-1);
double nombkg = curve->Eval(double(m_hyp));
RooRealVar *nlim = new RooRealVar(Form("nlim%d",cat),"",0.,0.,1.e5);
//double lowedge = tempFrame->GetXaxis()->GetBinLowEdge(FindBin(double(m_hyp)));
//double upedge = tempFrame->GetXaxis()->GetBinUpEdge(FindBin(double(m_hyp)));
//double center = tempFrame->GetXaxis()->GetBinUpCenter(FindBin(double(m_hyp)));
nlim->setVal(nombkg);
mass->setRange("errRange",m_hyp-0.5,m_hyp+0.5);
RooAbsPdf *epdf = 0;
epdf = new RooExtendPdf("epdf","",*pdf,*nlim,"errRange");
RooAbsReal *nll = epdf->createNLL(*data,Extended(),NumCPU(4));
RooMinimizer minim(*nll);
minim.setStrategy(0);
minim.setPrintLevel(-1);
minim.migrad();
minim.minos(*nlim);
double error = (nlim->getErrorLo(),nlim->getErrorHi())/2.;
data->Print();
return pair<double,double>(nombkg,error);
}
TH2F *plotEff2D(RooDataSet *a, TString b) {
const RooArgSet *set = a->get();
RooRealVar *yAx = (RooRealVar*)set->find("pt");
RooRealVar *xAx = (RooRealVar*)set->find("eta");
RooRealVar *eff = (RooRealVar*)set->find("efficiency");
// const int xnbins = xAx->getBinning().numBins();
// const int ynbins = yAx->getBinning().numBins();
//double xbins[] = {-2.4, -1.6, -0.8, 0.0, 0.8, 1.6, 2.4};
//double ybins[] = {0, 2, 3, 5, 8, 10, 20};
const double *xvbins = xAx->getBinning().array();
const double *yvbins = yAx->getBinning().array();
TH2F* h = new TH2F(b, "", xAx->getBinning().numBins(), xvbins, yAx->getBinning().numBins(), yvbins);
gStyle->SetPaintTextFormat("5.2f");
gStyle->SetPadRightMargin(0.12);
gStyle->SetPalette(1);
h->SetOption("colztexte");
h->GetZaxis()->SetRangeUser(-0.001,1.001);
h->SetStats(kFALSE);
h->GetYaxis()->SetTitle("p_{T} [GeV/c]");
h->GetXaxis()->SetTitle("#eta");
h->GetXaxis()->CenterTitle();
h->GetYaxis()->CenterTitle();
h->GetXaxis()->SetTitleSize(0.05);
h->GetYaxis()->SetTitleSize(0.05);
h->GetYaxis()->SetTitleOffset(0.8);
h->GetXaxis()->SetTitleOffset(0.9);
for(int i=0; i<a->numEntries(); i++) {
a->get(i);
h->SetBinContent(h->FindBin(xAx->getVal(), yAx->getVal()), eff->getVal());
h->SetBinError(h->FindBin(xAx->getVal(), yAx->getVal()), (eff->getErrorHi()-eff->getErrorLo())/2.);
}
return h;
}
vector<Double_t*> simFit(bool makeSoupFit_ = false,
const string tnp_ = "etoTauMargLooseNoCracks70",
const string category_ = "tauAntiEMVA",
const string bin_ = "abseta<1.5",
const float binCenter_ = 0.75,
const float binWidth_ = 0.75,
const float xLow_=60,
const float xHigh_=120,
bool SumW2_ = false,
bool verbose_ = true){
vector<Double_t*> out;
//return out;
//TFile *test = new TFile( outFile->GetName(),"UPDATE");
// output file
TFile *test = new TFile( Form("EtoTauPlotsFit_%s_%s_%f.root",tnp_.c_str(),category_.c_str(),binCenter_),"RECREATE");
test->mkdir(Form("bin%f",binCenter_));
TCanvas *c = new TCanvas("fitCanvas",Form("fitCanvas_%s_%s",tnp_.c_str(),bin_.c_str()),10,30,650,600);
c->SetGrid(0,0);
c->SetFillStyle(4000);
c->SetFillColor(10);
c->SetTicky();
c->SetObjectStat(0);
TCanvas *c2 = new TCanvas("fitCanvasTemplate",Form("fitCanvasTemplate_%s_%s",tnp_.c_str(),bin_.c_str()),10,30,650,600);
c2->SetGrid(0,0);
c2->SetFillStyle(4000);
c2->SetFillColor(10);
c2->SetTicky();
c2->SetObjectStat(0);
// input files
TFile fsup("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup.root");
TFile fbkg("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup_bkg.root");
TFile fsgn("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup_sgn.root");
TFile fdat("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_Data.root");
// data from 2iter:
//TFile fdat("/data_CMS/cms/lbianchini/35pb/testNewWriteFromPAT_Data.root");
//********************** signal only tree *************************/
TTree *fullTreeSgn = (TTree*)fsgn.Get((tnp_+"/fitter_tree").c_str());
TH1F* hSall = new TH1F("hSall","",1,0,150);
TH1F* hSPall = new TH1F("hSPall","",1,0,150);
TH1F* hS = new TH1F("hS","",1,0,150);
TH1F* hSP = new TH1F("hSP","",1,0,150);
fullTreeSgn->Draw("mass>>hS",Form("weight*(%s && mass>%f && mass<%f && mcTrue && signalPFChargedHadrCands<1.5)",bin_.c_str(),xLow_,xHigh_));
fullTreeSgn->Draw("mass>>hSall",Form("weight*(%s && mass>%f && mass<%f)",bin_.c_str(),xLow_,xHigh_));
float SGNtrue = hS->Integral();
float SGNall = hSall->Integral();
fullTreeSgn->Draw("mass>>hSP",Form("weight*(%s && %s>0 && mass>%f && mass<%f && mcTrue && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
fullTreeSgn->Draw("mass>>hSPall",Form("weight*(%s && %s>0 && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
float SGNtruePass = hSP->Integral();
float SGNallPass = hSPall->Integral();
//********************** background only tree *************************//
TTree *fullTreeBkg = (TTree*)fbkg.Get((tnp_+"/fitter_tree").c_str());
TH1F* hB = new TH1F("hB","",1,0,150);
TH1F* hBP = new TH1F("hBP","",1,0,150);
fullTreeBkg->Draw("mass>>hB",Form("weight*(%s && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),xLow_,xHigh_));
float BKG = hB->Integral();
float BKGUnWeighted = hB->GetEntries();
fullTreeBkg->Draw("mass>>hBP",Form("weight*(%s && %s>0 && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
float BKGPass = hBP->Integral();
float BKGUnWeightedPass = hBP->GetEntries();
float BKGFail = BKG-BKGPass;
cout << "*********** BKGFail " << BKGFail << endl;
//********************** soup tree *************************//
TTree *fullTreeSoup = (TTree*)fsup.Get((tnp_+"/fitter_tree").c_str());
//********************** data tree *************************//
TTree *fullTreeData = (TTree*)fdat.Get((tnp_+"/fitter_tree").c_str());
//********************** workspace ***********************//
RooWorkspace *w = new RooWorkspace("w","w");
// tree variables to be imported
w->factory("mass[30,120]");
w->factory("weight[0,10000]");
w->factory("abseta[0,2.5]");
w->factory("pt[0,200]");
w->factory("mcTrue[0,1]");
w->factory("signalPFChargedHadrCands[0,10]");
w->factory((category_+"[0,1]").c_str());
// background pass pdf for MC
w->factory("RooExponential::McBackgroundPdfP(mass,McCP[0,-10,10])");
// background fail pdf for MC
w->factory("RooExponential::McBackgroundPdfF(mass,McCF[0,-10,10])");
// background pass pdf for Data
w->factory("RooExponential::DataBackgroundPdfP(mass,DataCP[0,-10,10])");
// background fail pdf for Data
w->factory("RooExponential::DataBackgroundPdfF(mass,DataCF[0,-10,10])");
// fit parameters for background
w->factory("McEfficiency[0.04,0,1]");
w->factory("McNumSgn[0,1000000]");
w->factory("McNumBkgP[0,100000]");
w->factory("McNumBkgF[0,100000]");
w->factory("expr::McNumSgnP('McEfficiency*McNumSgn',McEfficiency,McNumSgn)");
w->factory("expr::McNumSgnF('(1-McEfficiency)*McNumSgn',McEfficiency,McNumSgn)");
w->factory("McPassing[pass=1,fail=0]");
// fit parameters for data
w->factory("DataEfficiency[0.1,0,1]");
w->factory("DataNumSgn[0,1000000]");
w->factory("DataNumBkgP[0,1000000]");
w->factory("DataNumBkgF[0,10000]");
w->factory("expr::DataNumSgnP('DataEfficiency*DataNumSgn',DataEfficiency,DataNumSgn)");
w->factory("expr::DataNumSgnF('(1-DataEfficiency)*DataNumSgn',DataEfficiency,DataNumSgn)");
w->factory("DataPassing[pass=1,fail=0]");
RooRealVar *weight = w->var("weight");
RooRealVar *abseta = w->var("abseta");
RooRealVar *pt = w->var("pt");
RooRealVar *mass = w->var("mass");
mass->setRange(xLow_,xHigh_);
RooRealVar *mcTrue = w->var("mcTrue");
RooRealVar *cut = w->var( category_.c_str() );
RooRealVar *signalPFChargedHadrCands = w->var("signalPFChargedHadrCands");
// build the template for the signal pass sample:
RooDataSet templateP("templateP","dataset for signal-pass template", RooArgSet(*mass,*weight,*abseta,*pt,*cut,*mcTrue,*signalPFChargedHadrCands), Import( *fullTreeSgn ), /*WeightVar( *weight ),*/ Cut( Form("(mcTrue && %s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()) ) );
// build the template for the signal fail sample:
RooDataSet templateF("templateF","dataset for signal-fail template", RooArgSet(*mass,*weight,*abseta,*pt,*cut,*mcTrue,*signalPFChargedHadrCands), Import( *fullTreeSgn ), /*WeightVar( *weight ),*/ Cut( Form("(mcTrue && %s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()) ) );
mass->setBins(24);
RooDataHist templateHistP("templateHistP","",RooArgSet(*mass), templateP, 1.0);
RooHistPdf TemplateSignalPdfP("TemplateSignalPdfP","",RooArgSet(*mass),templateHistP);
w->import(TemplateSignalPdfP);
mass->setBins(24);
RooDataHist templateHistF("templateHistF","",RooArgSet(*mass),templateF,1.0);
RooHistPdf TemplateSignalPdfF("TemplateSignalPdfF","",RooArgSet(*mass),templateHistF);
w->import(TemplateSignalPdfF);
mass->setBins(10000,"fft");
RooPlot* TemplateFrameP = mass->frame(Bins(24),Title("Template passing"));
templateP.plotOn(TemplateFrameP);
w->pdf("TemplateSignalPdfP")->plotOn(TemplateFrameP);
RooPlot* TemplateFrameF = mass->frame(Bins(24),Title("Template failing"));
templateF.plotOn(TemplateFrameF);
w->pdf("TemplateSignalPdfF")->plotOn(TemplateFrameF);
//w->factory("RooFFTConvPdf::McSignalPdfP(mass,TemplateSignalPdfP,RooTruthModel::McResolModP(mass))");
//w->factory("RooFFTConvPdf::McSignalPdfF(mass,TemplateSignalPdfF,RooTruthModel::McResolModF(mass))");
// FOR GREGORY: PROBLEM WHEN TRY TO USE THE PURE TEMPLATE =>
RooHistPdf McSignalPdfP("McSignalPdfP","McSignalPdfP",RooArgSet(*mass),templateHistP);
RooHistPdf McSignalPdfF("McSignalPdfF","McSignalPdfF",RooArgSet(*mass),templateHistF);
w->import(McSignalPdfP);
w->import(McSignalPdfF);
// FOR GREGORY: FOR DATA, CONVOLUTION IS OK =>
w->factory("RooFFTConvPdf::DataSignalPdfP(mass,TemplateSignalPdfP,RooGaussian::DataResolModP(mass,DataMeanResP[0.0,-5.,5.],DataSigmaResP[0.5,0.,10]))");
w->factory("RooFFTConvPdf::DataSignalPdfF(mass,TemplateSignalPdfF,RooGaussian::DataResolModF(mass,DataMeanResF[-5.,-10.,10.],DataSigmaResF[0.5,0.,10]))");
//w->factory("RooCBShape::DataSignalPdfF(mass,DataMeanF[91.2,88,95.],DataSigmaF[3,0.5,8],DataAlfaF[1.8,0.,10],DataNF[1.0,1e-06,10])");
//w->factory("RooFFTConvPdf::DataSignalPdfF(mass,RooVoigtian::DataVoigF(mass,DataMeanF[85,80,95],DataWidthF[2.49],DataSigmaF[3,0.5,10]),RooCBShape::DataResolModF(mass,DataMeanResF[0.5,0.,10.],DataSigmaResF[0.5,0.,10],DataAlphaResF[0.5,0.,10],DataNResF[1.0,1e-06,10]))");
//w->factory("SUM::DataSignalPdfF(fVBP[0.5,0,1]*RooBifurGauss::bifF(mass,DataMeanResF[91.2,80,95],sigmaLF[10,0.5,40],sigmaRF[0.]), RooVoigtian::voigF(mass, DataMeanResF, widthF[2.49], sigmaVoigF[5,0.1,10]) )" );
// composite model pass for MC
w->factory("SUM::McModelP(McNumSgnP*McSignalPdfP,McNumBkgP*McBackgroundPdfP)");
w->factory("SUM::McModelF(McNumSgnF*McSignalPdfF,McNumBkgF*McBackgroundPdfF)");
// composite model pass for data
w->factory("SUM::DataModelP(DataNumSgnP*DataSignalPdfP,DataNumBkgP*DataBackgroundPdfP)");
w->factory("SUM::DataModelF(DataNumSgnF*DataSignalPdfF,DataNumBkgF*DataBackgroundPdfF)");
// simultaneous fir for MC
w->factory("SIMUL::McModel(McPassing,pass=McModelP,fail=McModelF)");
// simultaneous fir for data
w->factory("SIMUL::DataModel(DataPassing,pass=DataModelP,fail=DataModelF)");
w->Print("V");
w->saveSnapshot("clean", w->allVars());
w->loadSnapshot("clean");
/****************** sim fit to soup **************************/
///////////////////////////////////////////////////////////////
TFile *f = new TFile("dummySoup.root","RECREATE");
TTree* cutTreeSoupP = fullTreeSoup->CopyTree(Form("(%s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
TTree* cutTreeSoupF = fullTreeSoup->CopyTree(Form("(%s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
RooDataSet McDataP("McDataP","dataset pass for the soup", RooArgSet(*mass), Import( *cutTreeSoupP ) );
RooDataSet McDataF("McDataF","dataset fail for the soup", RooArgSet(*mass), Import( *cutTreeSoupF ) );
RooDataHist McCombData("McCombData","combined data for the soup", RooArgSet(*mass), Index(*(w->cat("McPassing"))), Import("pass", *(McDataP.createHistogram("histoP",*mass)) ), Import("fail",*(McDataF.createHistogram("histoF",*mass)) ) ) ;
RooPlot* McFrameP = 0;
RooPlot* McFrameF = 0;
RooRealVar* McEffFit = 0;
if(makeSoupFit_){
cout << "**************** N bins in mass " << w->var("mass")->getBins() << endl;
RooFitResult* ResMcCombinedFit = w->pdf("McModel")->fitTo(McCombData, Extended(1), Minos(1), Save(1), SumW2Error( SumW2_ ), Range(xLow_,xHigh_), NumCPU(4) /*, ExternalConstraints( *(w->pdf("ConstrainMcNumBkgF")) )*/ );
test->cd(Form("bin%f",binCenter_));
ResMcCombinedFit->Write("McFitResults_Combined");
RooArgSet McFitParam(ResMcCombinedFit->floatParsFinal());
McEffFit = (RooRealVar*)(&McFitParam["McEfficiency"]);
RooRealVar* McNumSigFit = (RooRealVar*)(&McFitParam["McNumSgn"]);
RooRealVar* McNumBkgPFit = (RooRealVar*)(&McFitParam["McNumBkgP"]);
RooRealVar* McNumBkgFFit = (RooRealVar*)(&McFitParam["McNumBkgF"]);
McFrameP = mass->frame(Bins(24),Title("MC: passing sample"));
McCombData.plotOn(McFrameP,Cut("McPassing==McPassing::pass"));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McSignalPdfP"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McBackgroundPdfP"), LineColor(kGreen),Range(xLow_,xHigh_));
McFrameF = mass->frame(Bins(24),Title("MC: failing sample"));
McCombData.plotOn(McFrameF,Cut("McPassing==McPassing::fail"));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McSignalPdfF"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McBackgroundPdfF"), LineColor(kGreen),Range(xLow_,xHigh_));
}
///////////////////////////////////////////////////////////////
/****************** sim fit to data **************************/
///////////////////////////////////////////////////////////////
TFile *f2 = new TFile("dummyData.root","RECREATE");
TTree* cutTreeDataP = fullTreeData->CopyTree(Form("(%s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
TTree* cutTreeDataF = fullTreeData->CopyTree(Form("(%s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
RooDataSet DataDataP("DataDataP","dataset pass for the soup", RooArgSet(*mass), Import( *cutTreeDataP ) );
RooDataSet DataDataF("DataDataF","dataset fail for the soup", RooArgSet(*mass), Import( *cutTreeDataF ) );
RooDataHist DataCombData("DataCombData","combined data for the soup", RooArgSet(*mass), Index(*(w->cat("DataPassing"))), Import("pass",*(DataDataP.createHistogram("histoDataP",*mass))),Import("fail",*(DataDataF.createHistogram("histoDataF",*mass)))) ;
RooFitResult* ResDataCombinedFit = w->pdf("DataModel")->fitTo(DataCombData, Extended(1), Minos(1), Save(1), SumW2Error( SumW2_ ), Range(xLow_,xHigh_), NumCPU(4));
test->cd(Form("bin%f",binCenter_));
ResDataCombinedFit->Write("DataFitResults_Combined");
RooArgSet DataFitParam(ResDataCombinedFit->floatParsFinal());
RooRealVar* DataEffFit = (RooRealVar*)(&DataFitParam["DataEfficiency"]);
RooRealVar* DataNumSigFit = (RooRealVar*)(&DataFitParam["DataNumSgn"]);
RooRealVar* DataNumBkgPFit = (RooRealVar*)(&DataFitParam["DataNumBkgP"]);
RooRealVar* DataNumBkgFFit = (RooRealVar*)(&DataFitParam["DataNumBkgF"]);
RooPlot* DataFrameP = mass->frame(Bins(24),Title("Data: passing sample"));
DataCombData.plotOn(DataFrameP,Cut("DataPassing==DataPassing::pass"));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataSignalPdfP"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataBackgroundPdfP"), LineColor(kGreen),LineStyle(kDashed),Range(xLow_,xHigh_));
RooPlot* DataFrameF = mass->frame(Bins(24),Title("Data: failing sample"));
DataCombData.plotOn(DataFrameF,Cut("DataPassing==DataPassing::fail"));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataSignalPdfF"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataBackgroundPdfF"), LineColor(kGreen),LineStyle(kDashed),Range(xLow_,xHigh_));
///////////////////////////////////////////////////////////////
if(makeSoupFit_) c->Divide(2,2);
else c->Divide(2,1);
c->cd(1);
DataFrameP->Draw();
c->cd(2);
DataFrameF->Draw();
if(makeSoupFit_){
c->cd(3);
McFrameP->Draw();
c->cd(4);
McFrameF->Draw();
}
c->Draw();
test->cd(Form("bin%f",binCenter_));
c->Write();
c2->Divide(2,1);
c2->cd(1);
TemplateFrameP->Draw();
c2->cd(2);
TemplateFrameF->Draw();
c2->Draw();
test->cd(Form("bin%f",binCenter_));
c2->Write();
// MINOS errors, otherwise HESSE quadratic errors
float McErrorLo = 0;
float McErrorHi = 0;
if(makeSoupFit_){
McErrorLo = McEffFit->getErrorLo()<0 ? McEffFit->getErrorLo() : (-1)*McEffFit->getError();
McErrorHi = McEffFit->getErrorHi()>0 ? McEffFit->getErrorHi() : McEffFit->getError();
}
float DataErrorLo = DataEffFit->getErrorLo()<0 ? DataEffFit->getErrorLo() : (-1)*DataEffFit->getError();
float DataErrorHi = DataEffFit->getErrorHi()>0 ? DataEffFit->getErrorHi() : DataEffFit->getError();
float BinomialError = TMath::Sqrt(SGNtruePass/SGNtrue*(1-SGNtruePass/SGNtrue)/SGNtrue);
Double_t* truthMC = new Double_t[6];
Double_t* tnpMC = new Double_t[6];
Double_t* tnpData = new Double_t[6];
truthMC[0] = binCenter_;
truthMC[1] = binWidth_;
truthMC[2] = binWidth_;
truthMC[3] = SGNtruePass/SGNtrue;
truthMC[4] = BinomialError;
truthMC[5] = BinomialError;
if(makeSoupFit_){
tnpMC[0] = binCenter_;
tnpMC[1] = binWidth_;
tnpMC[2] = binWidth_;
tnpMC[3] = McEffFit->getVal();
tnpMC[4] = (-1)*McErrorLo;
tnpMC[5] = McErrorHi;
}
tnpData[0] = binCenter_;
tnpData[1] = binWidth_;
tnpData[2] = binWidth_;
tnpData[3] = DataEffFit->getVal();
tnpData[4] = (-1)*DataErrorLo;
tnpData[5] = DataErrorHi;
out.push_back(truthMC);
out.push_back(tnpData);
if(makeSoupFit_) out.push_back(tnpMC);
test->Close();
//delete c; delete c2;
if(verbose_) cout << "returning from bin " << bin_ << endl;
return out;
}
void fit_mass(TString fileN="") {//suffix added before file extension, e.g., '.pdf'
TString placeholder;//to add strings before using them, e.g., for saving text files
gROOT->SetBatch(kTRUE);
gROOT->ProcessLine(".x /afs/cern.ch/user/m/mwilkins/cmtuser/src/lhcbStyle.C");
// gStyle->SetPadTickX(1);
// gStyle->SetPadTickY(1);
// gStyle->SetPadLeftMargin(0.15);
// gStyle->SetTextSize(0.3);
// //open file and get histogram
// TFile *inHistos = new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/data/histos_data.root", "READ");
// TH1F * h100 = (TH1F*)inHistos->Get("h70");
// cout<<"data histogram gotten"<<endl;
//unbinned
TFile *hastree = new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/data/cutfile_Optimized.root", "READ");
TTree * h100 = (TTree*)hastree->Get("mytree");
cout<<"tree gotten"<<endl;
TFile *SMChistos= new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/MC/withKScut/histos_SMCfile_fullMC.root", "READ");
cout<<"SMC file opened"<<endl;
TH1F *SMCh = (TH1F*)SMChistos->Get("h00");
cout<<"SMC hist gotten"<<endl;
RooRealVar *mass = new RooRealVar("Bs_LOKI_MASS_JpsiConstr","m(J/#psi #Lambda)",4100,6100,"MeV");
mass->setRange("bkg1",4300,4800);
mass->setRange("bkg2",5700,5950);
mass->setRange("bkg3",4300,5500);
mass->setRange("bkg4",5100,5500);
mass->setRange("L",5350,5950);
mass->setRange("tot",4300,5950);
cout<<"mass declared"<<endl;
// RooDataHist *data = new RooDataHist("data","1D",RooArgList(*mass),h100);
//unbinned
RooDataSet *data = new RooDataSet("data","1D",h100,*mass);
cout<<"data declared"<<endl;
RooDataHist *SMC = new RooDataHist("SMC","1D",RooArgList(*mass),SMCh);
cout<<"SMC hist assigned to RooDataHist"<<endl;
// Construct Pdf Model
// /\0
//gaussian
RooRealVar mean1L("mean1L","/\\ gaus 1: mean",5621.103095,5525,5700);
RooRealVar sig1L("sig1L","/\\ gaus 1: sigma",6.898126,0,100);
RooGaussian gau1L("gau1L","#Lambda signal: gaussian 1",*mass,mean1L,sig1L);
RooFormulaVar mean2L("mean2L","@0",mean1L);
RooRealVar sig2L("sig2L","/\\ gaus 2: sigma",14.693117,0,100);
RooGaussian gau2L("gau2L","#Lambda signal: gaussian 2",*mass,mean2L,sig2L);
RooRealVar f1L("f1L","/\\ signal: fraction gaussian 1",0.748776,0,1);
RooAddPdf sigL("sigL","#Lambda signal",RooArgList(gau1L,gau2L),RooArgList(f1L));
// //CB
// RooRealVar mean3L("mean3L","/\\ CB: mean",5621.001,5525,5700);
// RooRealVar sig3L("sig3L","/\\ CB: sigma",5.161,0,100);
// RooRealVar alphaL3("alphaL3","/\\ CB: alpha",2.077,0,1000);
// RooRealVar nL3("nL1","/\\ CB: n",0.286,0,1000);
// RooCBShape CBL("CBL","#Lambda signal: CB",*mass,mean3L,sig3L,alphaL3,nL3);
// RooRealVar mean4L("mean4L","/\\ gaus: mean",5621.804,5525,5700);
// RooRealVar sig4L("sig4L","/\\ gaus: sigma",10.819,0,100);
// RooGaussian gauL("gauL","#Lambda signal: gaussian",*mass,mean4L,sig4L);
// RooRealVar f1L("f1L","/\\ signal: fraction CB",0.578,0,1);
// RooAddPdf sigL("sigL","#Lambda signal",RooArgList(CBL,gauL),RooArgList(f1L));
// sigma0
//using RooHistPdf from MC--no need to build pdf here
RooHistPdf sigS = makeroohistpdf(SMC,mass,"sigS","#Sigma^{0} signal (RooHistPdf)");
// /\*
cout<<"Lst stuff"<<endl;
RooRealVar meanLst1("meanLst1","/\\*(misc.): mean1",5011.031237,4900,5100);
RooRealVar sigLst1("sigLst1","/\\*(misc.): sigma1",70.522092,0,100);
RooRealVar meanLst2("mean5Lst2","/\\*(1405): mean2",5245.261703,5100,5350);
RooRealVar sigLst2("sigLst2","/\\*(1405): sigma2",64.564763,0,100);
RooRealVar alphaLst2("alphaLst2","/\\*(1405): alpha2",29.150301);
RooRealVar nLst2("nLst2","/\\*(1405): n2",4.615817,0,50);
RooGaussian gauLst1("gauLst1","#Lambda*(misc.), gaus",*mass,meanLst1,sigLst1);
RooCBShape gauLst2("gauLst2","#Lambda*(1405), CB",*mass,meanLst2,sigLst2,alphaLst2,nLst2);
// RooRealVar fLst1("fLst1","/\\* bkg: fraction gaus 1",0.743,0,1);
// RooAddPdf bkgLst("bkgLst","#Lambda* signal",RooArgList(gauLst1,gauLst2),RooArgList(fLst1));
//Poly func BKG mass
// RooRealVar b0("b0","Background: Chebychev b0",-1.071,-10000,10000);
RooRealVar b1("b1","Background: Chebychev b1",-1.323004,-10,-0.00000000000000000000001);
RooRealVar b2("b2","Background: Chebychev b2",0.145494,0,10);
RooRealVar b3("b3","Background: Chebychev b3",-0.316,-10000,10000);
RooRealVar b4("b4","Background: Chebychev b4",0.102,-10000,10000);
RooRealVar b5("b5","Background: Chebychev b5",0.014,-10000,10000);
RooRealVar b6("b6","Background: Chebychev b6",-0.015,-10000,10000);
RooRealVar b7("b7","Background: Chebychev b7",0.012,-10000,10000);
RooArgList bList(b1,b2);
RooChebychev bkg("bkg","Background", *mass, bList);
// TF1 *ep = new TF1("ep","[2]*exp([0]*x+[1]*x*x)",4300,5950);
// ep->SetParameter(0,1);
// ep->SetParameter(1,-1);
// ep->SetParameter(2,2000);
// ep->SetParName(0,"a");
// ep->SetParName(1,"b");
// ep->SetParName(2,"c");
// RooRealVar a("a","Background: Coefficent of x",1,-10000,10000);
// RooRealVar b("b","Background: Coefficent of x*x",-1,-10000,10000);
// RooRealVar c("c","Background: Coefficent of exp()",2000,-10000,10000);
// RooTFnPdfBinding bkg("ep","ep",ep,RooArgList(*mass,a,b));
//number of each shape
RooRealVar nbkg("nbkg","N bkg",2165.490249,0,100000000);
RooRealVar nsigL("nsigL","N /\\",1689.637290,0,1000000000);
RooRealVar nsigS("nsigS","N sigma",0.000002,0,10000000000);
RooRealVar ngauLst1("ngauLst1","N /\\*(misc.)",439.812103,0,10000000000);
RooRealVar ngauLst2("ngauLst2","N /\\*(1405)",152.061617,0,10000000000);
RooRealVar nbkgLst("nbkgLst","N /\\*",591.828,0,1000000000);
//add shapes and their number to a totalPdf
RooArgList shapes;
RooArgList yields;
shapes.add(sigL); yields.add(nsigL);
shapes.add(sigS); yields.add(nsigS);
// shapes.add(bkgLst); yields.add(nbkgLst);
shapes.add(gauLst1); yields.add(ngauLst1);
shapes.add(gauLst2); yields.add(ngauLst2);
shapes.add(bkg); yields.add(nbkg);
RooAddPdf totalPdf("totalPdf","totalPdf",shapes,yields);
//fit the totalPdf
RooAbsReal * nll = totalPdf.createNLL(*data,Extended(kTRUE),Range("tot"));
RooMinuit m(*nll);
m.setVerbose(kFALSE);
m.migrad();
m.minos();
m.minos();
//display and save information
ofstream textfile;//create text file to hold data
placeholder = "plots/fit"+fileN+".txt";
textfile.open(placeholder);
TString outputtext;//for useful text
//plot things
RooPlot *framex = mass->frame();
framex->GetYaxis()->SetTitle("Events/(5 MeV)");
data->plotOn(framex,Name("Hist"),MarkerColor(kBlack),LineColor(kBlack),DataError(RooAbsData::SumW2));
totalPdf.plotOn(framex,Name("curvetot"),LineColor(kBlue));
RooArgSet* totalPdfComponents = totalPdf.getComponents();
TIterator* itertPC = totalPdfComponents->createIterator();
RooAddPdf* vartPC = (RooAddPdf*) itertPC->Next();
vartPC = (RooAddPdf*) itertPC->Next();//skip totalPdf
int i=0;//color index
TLegend *leg = new TLegend(0.2, 0.02, .4, .42);
leg->SetTextSize(0.06);
leg->AddEntry(framex->findObject("curvetot"),"Total PDF","l");
while(vartPC){//loop over compotents of totalPdf
TString vartPCtitle = vartPC->GetTitle();
TIterator* itercompPars;//forward declare so it persists outside the if statement
RooRealVar* varcompPars;
if(!(vartPCtitle.Contains(":")||vartPCtitle.Contains("@"))){//only for non-sub-shapes
while(i==0||i==10||i==4||i==1||i==5||(i>=10&&i<=27))i++;//avoid white and blue and black and yellow and horribleness
RooArgSet* compPars = vartPC->getParameters(data);//set of the parameters of the component the loop is on
itercompPars = compPars->createIterator();
varcompPars = (RooRealVar*) itercompPars->Next();
while(varcompPars){//write and print mean, sig, etc. of sub-shapes
TString vartitle = varcompPars->GetTitle();
double varval = varcompPars->getVal();
TString varvalstring = Form("%f",varval);
double hi = varcompPars->getErrorHi();
TString varerrorstring = "[exact]";
if(hi!=-1){
double lo = varcompPars->getErrorLo();
double varerror = TMath::Max(fabs(lo),hi);
varerrorstring = Form("%E",varerror);
}
outputtext = vartitle+" = "+varvalstring+" +/- "+varerrorstring;
textfile<<outputtext<<endl;
cout<<outputtext<<endl;
varcompPars = (RooRealVar*) itercompPars->Next();
}
totalPdf.plotOn(framex,Name(vartPC->GetName()),LineStyle(kDashed),LineColor(i),Components(vartPC->GetName()));
leg->AddEntry(framex->findObject(vartPC->GetName()),vartPCtitle,"l");
i++;
}
vartPC = (RooAddPdf*) itertPC->Next();
itercompPars->Reset();//make sure it's ready for the next vartPC
}
// Calculate chi2/ndf
RooArgSet *floatpar = totalPdf.getParameters(data);
int floatpars = (floatpar->selectByAttrib("Constant",kFALSE))->getSize();
Double_t chi2 = framex->chiSquare("curvetot","Hist",floatpars);
TString chi2string = Form("%f",chi2);
//create text box to list important parameters on the plot
// TPaveText* txt = new TPaveText(0.1,0.5,0.7,0.9,"NBNDC");
// txt->SetTextSize(0.06);
// txt->SetTextColor(kBlack);
// txt->SetBorderSize(0);
// txt->SetFillColor(0);
// txt->SetFillStyle(0);
outputtext = "#chi^{2}/N_{DoF} = "+chi2string;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
// txt->AddText(outputtext);
// Print stuff
TIterator* iteryields = yields.createIterator();
RooRealVar* varyields = (RooRealVar*) iteryields->Next();//only inherits things from TObject unless class specified
vector<double> Y, E;//holds yields and associated errors
vector<TString> YS, ES;//holds strings of the corresponding yields
int j=0;//count vector position
int jS=0, jL=0;//these hold the position of the S and L results;initialized in case there is no nsigS or nsigL
while(varyields){//loop over yields
TString varname = varyields->GetName();
TString vartitle = varyields->GetTitle();
double varval = varyields->getVal();
Y.push_back(varval);
double lo = varyields->getErrorLo();
double hi = varyields->getErrorHi();
E.push_back(TMath::Max(fabs(lo),hi));
YS.push_back(Form("%f",Y[j]));
ES.push_back(Form("%f",E[j]));
if(varname=="nsigS") jS=j;
if(varname=="nsigL") jL=j;
outputtext = vartitle+" = "+YS[j]+" +/- "+ES[j];
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
varyields = (RooRealVar*) iteryields->Next();
j++;
}
//S/L
double result = Y[jS]/Y[jL];
cout<<"result declared"<<endl;
double E_result = TMath::Abs(result)*sqrt(pow(E[jS]/Y[jS],2)+pow(E[jL]/Y[jL],2));
cout<<"E_result declared"<<endl;
TString resultstring = Form("%E",result);
TString E_resultstring = Form("%E",E_result);
outputtext = "Y_{#Sigma^{0}}/Y_{#Lambda} = "+resultstring+" +/- "+E_resultstring;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
double resultlimit = (Y[jS]+E[jS])/(Y[jL]-E[jL]);
outputtext = Form("%E",resultlimit);
outputtext = "limit = "+outputtext;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
// Create canvas and pads, set style
TCanvas *c1 = new TCanvas("c1","data fits",1200,800);
TPad *pad1 = new TPad("pad1","pad1",0.0,0.3,1.0,1.0);
TPad *pad2 = new TPad("pad2","pad2",0.0,0.0,1.0,0.3);
pad1->SetBottomMargin(0);
pad2->SetTopMargin(0);
pad2->SetBottomMargin(0.5);
pad2->SetBorderMode(0);
pad1->SetBorderMode(0);
c1->SetBorderMode(0);
pad2->Draw();
pad1->Draw();
pad1->cd();
framex->SetMinimum(1);
framex->SetMaximum(3000);
framex->addObject(leg);//add legend to frame
//framex->addObject(txt);//add text to frame
gPad->SetTopMargin(0.06);
pad1->SetLogy();
// pad1->Range(4100,0,6100,0.0005);
pad1->Update();
framex->Draw();
// Pull distribution
RooPlot *framex2 = mass->frame();
RooHist* hpull = framex->pullHist("Hist","curvetot");
framex2->addPlotable(hpull,"P");
hpull->SetLineColor(kBlack);
hpull->SetMarkerColor(kBlack);
framex2->SetTitle(0);
framex2->GetYaxis()->SetTitle("Pull");
framex2->GetYaxis()->SetTitleSize(0.15);
framex2->GetYaxis()->SetLabelSize(0.15);
framex2->GetXaxis()->SetTitleSize(0.2);
framex2->GetXaxis()->SetLabelSize(0.15);
framex2->GetYaxis()->CenterTitle();
framex2->GetYaxis()->SetTitleOffset(0.45);
framex2->GetXaxis()->SetTitleOffset(1.1);
framex2->GetYaxis()->SetNdivisions(505);
framex2->GetYaxis()->SetRangeUser(-8.8,8.8);
pad2->cd();
framex2->Draw();
c1->cd();
placeholder = "plots/fit"+fileN+".eps";
c1->Print(placeholder);
placeholder = "plots/fit"+fileN+".C";
c1->SaveAs(placeholder);
textfile.close();
}
vector<float*> simFit(
const string tnp_ = "elecTnP",
const string category_ = "elecID80",
double cutValue_ = 0.5,
const string bin_ = "abseta>1.5",
const float binCenter_ = 0.75,
const float binWidth_ = 0.75,
const float xLow_ = 40,
const float xHigh_ = 120,
const float nBins_ = 24,
bool doBinned_ = true,
float deltaAlpha_ = 0.0,
float deltaN_ = 0.0,
float scale_ = 0.0
)
{
vector<float*> out;
TFile fSgn("../prod/ElecTnP/treeElecTnP_DYJets-50-madgraph-PUS4-TnP.root");
TTree *fullTreeSgn = (TTree*)fSgn.Get((tnp_+"/fitter_tree").c_str());
fSgn.cd("allEventsFilter");
TH1F* totalEventsSgn = (TH1F*)gDirectory->Get("totalEvents");
float readEventsSgn = totalEventsSgn->GetBinContent(1);
// data
TFile fdat("../prod/ElecTnP/treeElecTnP_DYJets-50-madgraph-PUS4-TnP.root");
TTree *fullTreeData = (TTree*)fdat.Get((tnp_+"/fitter_tree").c_str());
TH1F* hS = new TH1F("hS","",1,0,150);
TH1F* hSP = new TH1F("hSP","",1,0,150);
fullTreeSgn->Draw("mass>>hS",Form("tag_puMCWeight*(%s && mass>%f && mass<%f && mcTrue && tag_genDecay==23*11 && tag_pfRelIso<0.1 && pair_tnpCharge==0 && event_met_pfmet<25 && tag_pt>35)",bin_.c_str(),xLow_,xHigh_));
float SGNtrue = hS->Integral();
fullTreeSgn->Draw("mass>>hSP",Form("tag_puMCWeight*(%s && %s>=%f && mass>%f && mass<%f && mcTrue && tag_genDecay==23*11 && tag_pfRelIso<0.1 && pair_tnpCharge==0 && event_met_pfmet<25 && tag_pt>35)",bin_.c_str(),category_.c_str(),cutValue_,xLow_,xHigh_));
float SGNtruePass = hSP->Integral();
float McTruthEff = SGNtruePass/SGNtrue;
float BinomialError = TMath::Sqrt(SGNtruePass/SGNtrue*(1-SGNtruePass/SGNtrue)/SGNtrue);
cout << bin_.c_str() << " ==> MCTRUTH: " << McTruthEff << " +/- " << BinomialError << endl;
delete hS; delete hSP;
// file to copy the trees
TFile *templFile = new TFile(Form("dummyTempl_bin%.2f.root",binCenter_),"RECREATE");
TTree* fullTreeSgnCutP = fullTreeSgn->CopyTree( Form("(%s>=%f && %s && pair_tnpCharge==0 && event_met_pfmet<25 && mcTrue && tag_genDecay==23*11 && tag_pfRelIso<0.1 && tag_pt>35)",category_.c_str(),cutValue_,bin_.c_str()) );
TTree* fullTreeSgnCutF = fullTreeSgn->CopyTree( Form("(%s< %f && %s && pair_tnpCharge==0 && event_met_pfmet<25 && mcTrue && tag_genDecay==23*11 && tag_pfRelIso<0.1 && tag_pt>35)",category_.c_str(),cutValue_,bin_.c_str()) );
RooRealVar mass("mass","m_{tp} (GeV/c^{2})",xLow_,xHigh_);
mass.setBins( 10000, "fft" );
mass.setBins( nBins_ );
RooRealVar meanBkgP("meanBkgP","",59,30,100);
RooRealVar sigmaBkgP("sigmaBkgP","",11,0,50);
//RooLandau bkgPdfP("bkgPdfP","",mass,meanBkgP,sigmaBkgP);
RooRealVar DataCP("DataCP","",0);
RooExponential bkgPdfP("bkgPdfP","",mass,DataCP);
RooRealVar meanBkgF("meanBkgF","",59,30,100);
RooRealVar sigmaBkgF("sigmaBkgF","",11,0,50);
//RooLandau bkgPdfF("bkgPdfF","",mass,meanBkgF,sigmaBkgF);
RooRealVar DataCF("DataCF","",0,-10,10);
RooExponential bkgPdfF("bkgPdfF","",mass,DataCF);
TCanvas *c0 = new TCanvas("fitCanvas","canvas",10,30,650,600);
c0->SetGrid(0,0);
c0->SetFillStyle(4000);
c0->SetFillColor(10);
c0->SetTicky();
c0->SetObjectStat(0);
mass.setBins( 50 );
/////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////
// passing:
RooDataSet sgnDataSetP("sgnDataSetP","dataset for signal", RooArgSet(mass), Import( *fullTreeSgnCutP ) );
RooDataHist sgnDataHistP("sgnDataHistP","",RooArgSet(mass),sgnDataSetP, 1.0);
//RooHistPdf sgnTemplatePdfP("sgnTemplatePdfP","",RooArgSet(mass),sgnDataHistP);
RooKeysPdf sgnTemplatePdfP("sgnTemplatePdfP","",mass,sgnDataSetP);
// Breit-Wigner
RooRealVar meanSgnP("meanSgnP","mean",91.19,85,100);
RooRealVar widthSgnP("widthSgnP","width",2.49,0.,10);
RooBreitWigner bwSgnP("bwSgnP","bw",mass,meanSgnP,widthSgnP);
// Crystall Ball
RooRealVar m1SgnP("m1SgnP","m1",0,-20,20);
RooRealVar sigmaSgnP("sigmaSgnP","sigma",0.5,0,20);
RooRealVar alfaSgnP("alfaSgnP","alfa", 0.5,-10,10);
RooRealVar nSgnP("nSgnP","n", 1,1e-06,50);
RooCBShape cbSgnP("cbSgnP","",mass,m1SgnP,sigmaSgnP,alfaSgnP,nSgnP);
mass.setBins( 1000 , "fft");
// BW (X) CB
RooFFTConvPdf bvcbSgnP("bvcbSgnP","",mass,bwSgnP, cbSgnP);
RooFitResult* ResSgnFitP = bvcbSgnP.fitTo(sgnDataSetP, Minos(1), Save(1), NumCPU(4) );
RooArgSet FitParamSgnP(ResSgnFitP->floatParsFinal());
RooRealVar* m1SgnFitP = (RooRealVar*)(&FitParamSgnP["m1SgnP"]);
RooRealVar* sigmaSgnFitP = (RooRealVar*)(&FitParamSgnP["sigmaSgnP"]);
RooRealVar* alfaSgnFitP = (RooRealVar*)(&FitParamSgnP["alfaSgnP"]);
RooRealVar* nSgnFitP = (RooRealVar*)(&FitParamSgnP["nSgnP"]);
RooRealVar* nMeanSgnFitP = (RooRealVar*)(&FitParamSgnP["meanSgnP"]);
RooRealVar* nWidthSgnFitP= (RooRealVar*)(&FitParamSgnP["widthSgnP"]);
RooRealVar m1SgnP_C("m1SgnP_C","m1",m1SgnFitP->getVal(),-10,10);
RooRealVar sigmaSgnP_C("sigmaSgnP_C","sigma",sigmaSgnFitP->getVal(),0,20);
// choose to let it float or not
RooRealVar meanSgnP_C("meanSgnP_C","mean", nMeanSgnFitP->getVal() ,80,120);
RooRealVar widthSgnP_C("widthSgnP_C","width",nWidthSgnFitP->getVal() /*,0.,10*/);
RooRealVar alfaSgnP_C("alfaSgnP_C","alfa",alfaSgnFitP->getVal()*(1+deltaAlpha_)/*,0,20*/);
RooRealVar nSgnP_C("nSgnP_C","n",nSgnFitP->getVal()*(1+deltaN_)/*,0,50*/);
RooCBShape cbSgnP_C("cbSgnP_C","",mass,m1SgnP_C,sigmaSgnP_C,alfaSgnP_C,nSgnP_C);
RooLognormal alfaSgnP_CPdf("alfaSgnP_CPdf","",alfaSgnP_C,RooConst(alfaSgnFitP->getVal()),RooConst(1.5));
RooLognormal nSgnP_CPdf("nSgnP_CPdf","",nSgnP_C,RooConst(nSgnFitP->getVal()), RooConst(1.5));
RooLognormal meanSgnP_CPdf("meanSgnP_CPdf","",meanSgnP_C,RooConst(nMeanSgnFitP->getVal()),RooConst(1.5));
RooLognormal widthSgnP_CPdf("widthSgnP_CPdf","",widthSgnP_C,RooConst(nWidthSgnFitP->getVal()),RooConst(1.5));
// fitted BW (X) CB
RooBreitWigner bwSgnP_C("bwSgnP_C","bw",mass,meanSgnP_C,widthSgnP_C);
RooFFTConvPdf sgnPdfP("sgnPdfP","",mass,bwSgnP_C, cbSgnP_C);
RooRealVar sgnMeanResP("sgnMeanResP","",0,-10,10);
RooRealVar sgnSigmaResP("sgnSigmaResP","",0.5,0,10);
RooGaussian resolModP("sgnResolModP","",mass,sgnMeanResP,sgnSigmaResP);
mass.setBins(nBins_);
//return;
/////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////
// failing:
RooDataSet sgnDataSetF("sgnDataSetF","dataset for signal", RooArgSet(mass), Import( *fullTreeSgnCutF ) );
RooDataHist sgnDataHistF("sgnDataHistF","",RooArgSet(mass),sgnDataSetF, 1.0);
//RooHistPdf sgnTemplatePdfF("sgnTemplatePdfF","",RooArgSet(mass),sgnDataHistF);
RooKeysPdf sgnTemplatePdfF("sgnTemplatePdfF","",mass,sgnDataSetF);
// Breit-Wigner
RooRealVar meanSgnF("meanSgnF","mean",91.19,85,100);
RooRealVar widthSgnF("widthSgnF","width",2.49,0.,10);
RooBreitWigner bwSgnF("bwSgnF","bw",mass,meanSgnF,widthSgnF);
// Crystall Ball
RooRealVar m1SgnF("m1SgnF","m1",0,-20,20);
RooRealVar sigmaSgnF("sigmaSgnF","sigma",0.5,0,20);
RooRealVar alfaSgnF("alfaSgnF","alfa", 0.5,-10,10);
RooRealVar nSgnF("nSgnF","n", 1,1e-06,50);
RooCBShape cbSgnF("cbSgnF","",mass,m1SgnF,sigmaSgnF,alfaSgnF,nSgnF);
// BW (X) CB
RooFFTConvPdf bvcbSgnF("bvcbSgnF","",mass,bwSgnF, cbSgnF);
RooFitResult* ResSgnFitF = bvcbSgnF.fitTo(sgnDataSetF, Minos(1), Save(1), NumCPU(4) );
RooArgSet FitParamSgnF(ResSgnFitF->floatParsFinal());
RooRealVar* m1SgnFitF = (RooRealVar*)(&FitParamSgnF["m1SgnF"]);
RooRealVar* sigmaSgnFitF = (RooRealVar*)(&FitParamSgnF["sigmaSgnF"]);
RooRealVar* alfaSgnFitF = (RooRealVar*)(&FitParamSgnF["alfaSgnF"]);
RooRealVar* nSgnFitF = (RooRealVar*)(&FitParamSgnF["nSgnF"]);
RooRealVar* nMeanSgnFitF = (RooRealVar*)(&FitParamSgnF["meanSgnF"]);
RooRealVar* nWidthSgnFitF= (RooRealVar*)(&FitParamSgnF["widthSgnF"]);
RooRealVar m1SgnF_C("m1SgnF_C","m1",m1SgnFitF->getVal(),-10,10);
RooRealVar sigmaSgnF_C("sigmaSgnF_C","sigma",sigmaSgnFitF->getVal(),0,20);
// choose to let it float or not
RooRealVar meanSgnF_C("meanSgnF_C","mean", nMeanSgnFitF->getVal() ,80,120);
RooRealVar widthSgnF_C("widthSgnF_C","width",nWidthSgnFitF->getVal() /*,0.,10*/);
RooRealVar alfaSgnF_C("alfaSgnF_C","alfa",alfaSgnFitF->getVal()*(1+deltaAlpha_)/*,0,20*/);
RooRealVar nSgnF_C("nSgnF_C","n",nSgnFitF->getVal()*(1+deltaN_)/*,0,50*/);
RooCBShape cbSgnF_C("cbSgnF_C","",mass,m1SgnF_C,sigmaSgnF_C,alfaSgnF_C,nSgnF_C);
RooLognormal alfaSgnF_CPdf("alfaSgnF_CPdf","",alfaSgnF_C,RooConst(alfaSgnFitF->getVal()),RooConst(1.5));
RooLognormal nSgnF_CPdf("nSgnF_CPdf","",nSgnF_C,RooConst(nSgnFitF->getVal()), RooConst(1.5));
RooLognormal meanSgnF_CPdf("meanSgnF_CPdf","",meanSgnF_C,RooConst(nMeanSgnFitF->getVal()),RooConst(1.5));
RooLognormal widthSgnF_CPdf("widthSgnF_CPdf","",widthSgnF_C,RooConst(nWidthSgnFitF->getVal()),RooConst(1.5));
// fitted BW (X) CB
RooBreitWigner bwSgnF_C("bwSgnF_C","bw",mass,meanSgnF_C,widthSgnF_C);
RooFFTConvPdf sgnPdfF("sgnPdfF","",mass,bwSgnF_C, cbSgnF_C);
RooRealVar sgnMeanResF("sgnMeanResF","",0,-10,10);
RooRealVar sgnSigmaResF("sgnSigmaResF","",0.5,0,10);
RooGaussian resolModF("sgnResolModF","",mass,sgnMeanResF,sgnSigmaResF);
mass.setBins(nBins_);
//return;
// Fit
RooCategory category("category","category") ;
category.defineType("pass") ;
category.defineType("fail") ;
RooRealVar DataNumBkgF("DataNumBkgF","",0,10000000);
RooRealVar DataNumBkgP("DataNumBkgP","",0,10000000);
RooRealVar DataNumSgn("DataNumSgn","", 0,10000000);
RooRealVar DataEfficiency("DataEfficiency","",0.5,0,1);
RooFormulaVar DataNumSgnP("DataNumSgnP","DataEfficiency*DataNumSgn", RooArgSet(DataEfficiency,DataNumSgn));
RooFormulaVar DataNumSgnF("DataNumSgnF","(1-DataEfficiency)*DataNumSgn",RooArgSet(DataEfficiency,DataNumSgn));
RooAddPdf DataModelP("DataModelP","",RooArgList(sgnPdfP,bkgPdfP),RooArgList(DataNumSgnP,DataNumBkgP));
RooAddPdf DataModelF("DataModelF","",RooArgList(sgnPdfF,bkgPdfF),RooArgList(DataNumSgnF,DataNumBkgF));
TFile* dummyData = new TFile("dummyData.root","RECREATE");
TTree* fullTreeDataCutP = fullTreeData->CopyTree( Form("(%s>=%f && %s && tag_pfRelIso<0.1 && pair_tnpCharge==0 && event_met_pfmet<25 && (tag_hlt1==1 || tag_hlt2==1) && tag_pt>35)",category_.c_str(),cutValue_,bin_.c_str()) );
TTree* fullTreeDataCutF = fullTreeData->CopyTree( Form("(%s <%f && %s && tag_pfRelIso<0.1 && pair_tnpCharge==0 && event_met_pfmet<25 && (tag_hlt1==1 || tag_hlt2==1) && tag_pt>35)",category_.c_str(),cutValue_,bin_.c_str()) );
mass.setBins(nBins_);
RooDataSet DataDataSetP("DataDataSetP","dataset for Data pass", RooArgSet(mass), Import( *fullTreeDataCutP ) );
std::cout << "data dataset Pass " << DataDataSetP.numEntries() << " " << std::endl;
//return out;
RooDataHist DataDataHistP("DataDataHistP","",RooArgSet(mass),DataDataSetP, 1.0);
RooDataSet DataDataSetF("DataDataSetF","dataset for Data fail", RooArgSet(mass), Import( *fullTreeDataCutF ) );
std::cout << "data dataset Fail " << DataDataSetF.numEntries() << " " << std::endl;
RooDataHist DataDataHistF("DataDataHistF","",RooArgSet(mass),DataDataSetF, 1.0);
RooRealVar DataNumSgnP_("DataNumSgnP_","",0,10000);
RooAddPdf DataModelP_("DataModelP_","",RooArgList(sgnPdfP,bkgPdfP),RooArgList(DataNumSgnP_,DataNumBkgP));
DataModelP_.fitTo(DataDataSetP, Extended(1), Minos(1), Save(1), NumCPU(4),SumW2Error(1) /*,ExternalConstraints( RooArgSet(meanSgn_CPdf,widthSgn_CPdf) )*/);
RooPlot* frame2 = mass.frame(Title("template"));
DataDataSetP.plotOn(frame2);
DataModelP_.plotOn(frame2, LineColor(kBlue), LineStyle(kSolid));
DataModelP_.plotOn(frame2, Components("sgnPdfP"), LineColor(kRed), LineStyle(kSolid));
DataModelP_.plotOn(frame2, Components("bkgPdfP"), LineColor(kGreen), LineStyle(kSolid));
frame2->Draw();
//return;
// binned combined dataset
RooDataHist DataCombData("DataCombData","combined data",mass,Index(category),Import("pass", *(DataDataSetP.createHistogram("histoDataP",mass)) ) ,Import("fail", *(DataDataSetF.createHistogram("histoDataF",mass))), Weight(0.5) ) ;
std::cout << "data dataHist Comb " << DataCombData.sumEntries() << " " << std::endl;
std::cout << "+++++++++++++++++++++++++++++++++++++++++++++" << std::endl;
// unbinned combined dataset
RooDataSet DataCombDataUnBinned("DataCombDataUnBinned","combined data",mass,Index(category),Import("pass", DataDataSetP ) ,Import("fail",DataDataSetF), Weight(0.5) ) ;
std::cout << "data dataset Comb " << DataCombDataUnBinned.numEntries() << " " << std::endl;
std::cout << "+++++++++++++++++++++++++++++++++++++++++++++" << std::endl;
//return out;
RooSimultaneous DataSimPdf("DataSimPdf","simultaneous pdf",category) ;
DataSimPdf.addPdf(DataModelP,"pass") ;
DataSimPdf.addPdf(DataModelF,"fail") ;
//mass.setBins( 10000, "fft" );
mass.setBins( nBins_ );
RooFitResult* ResDataCombinedFit = 0;
if(doBinned_) ResDataCombinedFit = DataSimPdf.fitTo(DataCombData , Extended(1), Minos(1), Save(1), NumCPU(4), /*ExternalConstraints( RooArgSet(alfaSgn_CPdf,nSgn_CPdf) )*/ SumW2Error(1));
else ResDataCombinedFit = DataSimPdf.fitTo(DataCombDataUnBinned , Extended(1), Minos(1), Save(1), NumCPU(4), /*ExternalConstraints( RooArgSet(alfaSgn_CPdf,nSgn_CPdf) )*/ SumW2Error(1));
RooArgSet DataFitParam(ResDataCombinedFit->floatParsFinal());
RooRealVar* DataEffFit = (RooRealVar*)(&DataFitParam["DataEfficiency"]);
RooRealVar* DataNumSigFit = (RooRealVar*)(&DataFitParam["DataNumSgn"]);
RooPlot* DataFrameP = mass.frame(Bins(40),Title("CMS Preliminary 2011 #sqrt{s}=7 TeV L=XXX pb^{-1}: passing probe"));
DataCombData.plotOn(DataFrameP,Cut("category==category::pass"));
DataSimPdf.plotOn(DataFrameP,Slice(category,"pass"), ProjWData(category,DataCombData), LineColor(kBlue));
DataSimPdf.plotOn(DataFrameP,Slice(category,"pass"), ProjWData(category,DataCombData), Components("sgnPdfP"), LineColor(kRed), LineStyle(kSolid));
DataSimPdf.plotOn(DataFrameP,Slice(category,"pass"), ProjWData(category,DataCombData), Components("bkgPdfP"), LineColor(kMagenta), LineStyle(kDashed));
RooPlot* DataFrameF = mass.frame(Bins(40),Title("CMS Preliminary 2011 #sqrt{s}=7 TeV L=XXX pb^{-1}: failing probe"));
DataCombData.plotOn(DataFrameF,Cut("category==category::fail"));
DataSimPdf.plotOn(DataFrameF,Slice(category,"fail"), ProjWData(category,DataCombData), LineColor(kBlue));
DataSimPdf.plotOn(DataFrameF,Slice(category,"fail"), ProjWData(category,DataCombData), Components("sgnPdfF"), LineColor(kRed), LineStyle(kSolid));
DataSimPdf.plotOn(DataFrameF,Slice(category,"fail"), ProjWData(category,DataCombData), Components("bkgPdfF"), LineColor(kMagenta), LineStyle(kDashed));
TCanvas *cPass = new TCanvas("fitCanvasP","canvas",10,30,650,600);
cPass->SetGrid(0,0);
cPass->SetFillStyle(4000);
cPass->SetFillColor(10);
cPass->SetTicky();
cPass->SetObjectStat(0);
cPass->cd();
DataFrameP->Draw();
string fileNameP = "fitCanvasPassElecTnP_"+tnp_+"_"+category_;
cPass->SaveAs(Form("%s_%.2f.png",fileNameP.c_str(), binCenter_));
TCanvas *cFail = new TCanvas("fitCanvasF","canvas",10,30,650,600);
cFail->SetGrid(0,0);
cFail->SetFillStyle(4000);
cFail->SetFillColor(10);
cFail->SetTicky();
cFail->SetObjectStat(0);
cFail->cd();
DataFrameF->Draw();
string fileNameF = "fitCanvasFailElecTnP_"+tnp_+"_"+category_;
cFail->SaveAs(Form("%s_%.2f.png",fileNameF.c_str(), binCenter_));
ResDataCombinedFit->printArgs(std::cout);
cout << endl;
ResDataCombinedFit->printValue(std::cout);
cout << endl;
float DataErrorLo = DataEffFit->getErrorLo()<0 ? DataEffFit->getErrorLo() : (-1)*DataEffFit->getError();
float DataErrorHi = DataEffFit->getErrorHi()>0 ? DataEffFit->getErrorHi() : DataEffFit->getError();
cout << DataEffFit->getVal() << " +/- " << DataEffFit->getError() << " ( " << DataErrorLo << ", " << DataErrorHi << ")" << endl;
float* out1 = new float[6];
float* out2 = new float[6];
out1[0]=(binCenter_);
out1[1]=(binWidth_);
out1[2]=(binWidth_);
out1[3]=(McTruthEff);
out1[4]=(BinomialError);
out1[5]=(BinomialError);
out2[0]=(binCenter_);
out2[1]=(binWidth_);
out2[2]=(binWidth_);
out2[3]=(DataEffFit->getVal());
out2[4]=((-1)*DataErrorLo);
out2[5]=(DataErrorHi);
out.push_back(out1);
out.push_back(out2);
return out;
}
void ZeeGammaMassFitSystematicStudy(string workspaceFile, const Int_t seed = 1234,
Int_t Option = 0, Int_t NToys = 1) {
//--------------------------------------------------------------------------------------------------------------
// Settings
//==============================================================================================================
TRandom3 *randomnumber = new TRandom3(seed);
// RooRealVar m("m","mass",60,130);
RooCategory sample("sample","");
sample.defineType("Pass",1);
sample.defineType("Fail",2);
//--------------------------------------------------------------------------------------------------------------
//Load Workspace
//==============================================================================================================
TFile *f = new TFile (workspaceFile.c_str(), "READ");
RooWorkspace *w = (RooWorkspace*)f->Get("MassFitWorkspace");
//--------------------------------------------------------------------------------------------------------------
//Setup output tree
//==============================================================================================================
TFile *outputfile = new TFile (Form("EffToyResults_Option%d_Seed%d.root",Option, seed), "RECREATE");
float varEff = 0;
float varEffErrL = 0;
float varEffErrH = 0;
TTree *outTree = new TTree("eff","eff");
outTree->Branch("eff",&varEff, "eff/F");
outTree->Branch("efferrl",&varEffErrL, "efferrl/F");
outTree->Branch("efferrh",&varEffErrH, "efferrh/F");
//--------------------------------------------------------------------------------------------------------------
//Load Model
//==============================================================================================================
RooSimultaneous *totalPdf = (RooSimultaneous*)w->pdf("totalPdf");
RooRealVar *m_default = (RooRealVar*)w->var("m");
m_default->setRange("signalRange",85, 95);
//get default models
RooAddPdf *modelPass_default = (RooAddPdf*)w->pdf("modelPass");
RooAddPdf *modelFail_default = (RooAddPdf*)w->pdf("modelFail");
//get variables
RooRealVar *Nsig = (RooRealVar*)w->var("Nsig");
RooRealVar *eff = (RooRealVar*)w->var("eff");
RooRealVar *NbkgFail = (RooRealVar*)w->var("NbkgFail");
RooFormulaVar NsigPass("NsigPass","eff*Nsig",RooArgList(*eff,*Nsig));
RooFormulaVar NsigFail("NsigFail","(1.0-eff)*Nsig",RooArgList(*eff,*Nsig));
//get number of expected events
Double_t npass = 100;
Double_t nfail = 169;
//*************************************************************************************
//make alternative model
//*************************************************************************************
RooRealVar *tFail_default = (RooRealVar*)w->var("tFail");
RooRealVar *fracFail_default = (RooRealVar*)w->var("fracFail");
RooRealVar *meanFail_default = (RooRealVar*)w->var("meanFail");
RooRealVar *sigmaFail_default = (RooRealVar*)w->var("sigmaFail");
RooHistPdf *bkgFailTemplate_default = (RooHistPdf*)w->pdf("bkgHistPdfFail");
RooFFTConvPdf *sigFail_default = (RooFFTConvPdf*)w->pdf("signalFail");
RooFFTConvPdf *bkgFail_default = (RooFFTConvPdf*)w->pdf("bkgConvPdfFail");
RooExtendPdf *esignalFail_default = (RooExtendPdf *)w->pdf("esignalFail");
RooExtendPdf *ebackgroundFail_default = (RooExtendPdf *)w->pdf("ebackgroundFail");
RooExponential *bkgexpFail_default = (RooExponential*)w->pdf("bkgexpFail");
RooAddPdf *backgroundFail_default = (RooAddPdf*)w->pdf("backgroundFail");
RooGaussian *bkggausFail_default = (RooGaussian*)w->pdf("bkggausFail");
//shifted mean
RooRealVar *meanFail_shifted = new RooRealVar("meanFail_shifted","meanFail_shifted", 0, -5, 5);
meanFail_shifted->setVal(meanFail_default->getVal());
if (Option == 1) meanFail_shifted->setVal(meanFail_default->getVal()-1.0);
else if (Option == 2) meanFail_shifted->setVal(meanFail_default->getVal()+1.0);
else if (Option == 11) meanFail_shifted->setVal(meanFail_default->getVal()-2.0);
else if (Option == 12) meanFail_shifted->setVal(meanFail_default->getVal()+2.0);
RooRealVar *sigmaFail_shifted = new RooRealVar("sigmaFail_shifted","sigmaFail_shifted", 0, -5, 5);
sigmaFail_shifted->setVal(sigmaFail_default->getVal());
if (Option == 3) sigmaFail_shifted->setVal(sigmaFail_default->getVal()*1.2);
else if (Option == 4) sigmaFail_shifted->setVal(sigmaFail_default->getVal()*0.8);
CMCBkgTemplateConvGaussianPlusExp *bkgFailModel = new CMCBkgTemplateConvGaussianPlusExp(*m_default,bkgFailTemplate_default,false,meanFail_shifted,sigmaFail_shifted, "shifted");
bkgFailModel->t->setVal(tFail_default->getVal());
bkgFailModel->frac->setVal(fracFail_default->getVal());
cout << "mean : " << meanFail_default->getVal() << " - " << meanFail_shifted->getVal() << endl;
cout << "sigma : " << sigmaFail_default->getVal() << " - " << sigmaFail_shifted->getVal() << endl;
cout << "t: " << tFail_default->getVal() << " - " << bkgFailModel->t->getVal() << endl;
cout << "frac: " << fracFail_default->getVal() << " - " << bkgFailModel->frac->getVal() << endl;
cout << "eff: " << eff->getVal() << " : " << NsigPass.getVal() << " / " << (NsigPass.getVal() + NsigFail.getVal()) << endl;
cout << "NbkgFail: " << NbkgFail->getVal() << endl;
//make alternative fail model
RooAddPdf *modelFail=0;
RooExtendPdf *esignalFail=0, *ebackgroundFail=0;
ebackgroundFail = new RooExtendPdf("ebackgroundFail_shifted","ebackgroundFail_shifted",*(bkgFailModel->model),*NbkgFail,"signalRange");
modelFail = new RooAddPdf("modelFail","Model for FAIL sample", RooArgList(*esignalFail_default,*ebackgroundFail));
cout << "*************************************\n";
ebackgroundFail->Print();
cout << "*************************************\n";
ebackgroundFail_default->Print();
cout << "*************************************\n";
modelFail->Print();
cout << "*************************************\n";
modelFail_default->Print();
cout << "*************************************\n";
TCanvas *cv = new TCanvas("cv","cv",800,600);
RooPlot *mframeFail_default = m_default->frame(Bins(Int_t(130-60)/2));
modelFail_default->plotOn(mframeFail_default);
modelFail_default->plotOn(mframeFail_default,Components("ebackgroundFail"),LineStyle(kDashed),LineColor(kRed));
modelFail_default->plotOn(mframeFail_default,Components("bkgexpFail"),LineStyle(kDashed),LineColor(kGreen+2));
mframeFail_default->GetYaxis()->SetTitle("");
mframeFail_default->GetYaxis()->SetTitleOffset(1.2);
mframeFail_default->GetXaxis()->SetTitle("m_{ee#gamma} [GeV/c^{2}]");
mframeFail_default->GetXaxis()->SetTitleOffset(1.05);
mframeFail_default->SetTitle("");
mframeFail_default->Draw();
cv->SaveAs("DefaultModel.gif");
RooPlot *mframeFail = m_default->frame(Bins(Int_t(130-60)/2));
modelFail->plotOn(mframeFail);
modelFail->plotOn(mframeFail,Components("ebackgroundFail_shifted"),LineStyle(kDashed),LineColor(kRed));
modelFail->plotOn(mframeFail,Components("bkgexpFail_shifted"),LineStyle(kDashed),LineColor(kGreen+2));
mframeFail->GetYaxis()->SetTitle("");
mframeFail->GetYaxis()->SetTitleOffset(1.2);
mframeFail->GetXaxis()->SetTitle("m_{ee#gamma} [GeV/c^{2}]");
mframeFail->GetXaxis()->SetTitleOffset(1.05);
mframeFail->SetTitle("");
mframeFail->Draw();
cv->SaveAs(Form("ShiftedModel_%d.gif",Option));
//*************************************************************************************
//Do Toys
//*************************************************************************************
for(uint t=0; t < NToys; ++t) {
RooDataSet *pseudoData_pass = modelPass_default->generate(*m_default, randomnumber->Poisson(npass));
RooDataSet *pseudoData_fail = 0;
pseudoData_fail = modelFail->generate(*m_default, randomnumber->Poisson(nfail));
RooDataSet *pseudoDataCombined = new RooDataSet("pseudoDataCombined","pseudoDataCombined",RooArgList(*m_default),
RooFit::Index(sample),
RooFit::Import("Pass",*pseudoData_pass),
RooFit::Import("Fail",*pseudoData_fail));
pseudoDataCombined->write(Form("toy%d.txt",t));
RooFitResult *fitResult=0;
fitResult = totalPdf->fitTo(*pseudoDataCombined,
RooFit::Extended(),
RooFit::Strategy(2),
//RooFit::Minos(RooArgSet(eff)),
RooFit::Save());
cout << "\n\n";
cout << "Eff Fit: " << eff->getVal() << " -" << fabs(eff->getErrorLo()) << " +" << eff->getErrorHi() << endl;
//Fill Tree
varEff = eff->getVal();
varEffErrL = fabs(eff->getErrorLo());
varEffErrH = eff->getErrorHi();
outTree->Fill();
// //*************************************************************************************
// //Plot Toys
// //*************************************************************************************
// TCanvas *cv = new TCanvas("cv","cv",800,600);
// char pname[50];
// char binlabelx[100];
// char binlabely[100];
// char yield[50];
// char effstr[100];
// char nsigstr[100];
// char nbkgstr[100];
// char chi2str[100];
// //
// // Plot passing probes
// //
// RooPlot *mframeFail_default = m.frame(Bins(Int_t(130-60)/2));
// modelFail_default->plotOn(mframeFail_default);
// modelFail_default->plotOn(mframeFail_default,Components("ebackgroundFail"),LineStyle(kDashed),LineColor(kRed));
// modelFail_default->plotOn(mframeFail_default,Components("bkgexpFail"),LineStyle(kDashed),LineColor(kGreen+2));
// mframeFail_default->Draw();
// cv->SaveAs("DefaultModel.gif");
// RooPlot *mframeFail = m.frame(Bins(Int_t(130-60)/2));
// modelFail->plotOn(mframeFail);
// modelFail->plotOn(mframeFail,Components("ebackgroundFail_shifted"),LineStyle(kDashed),LineColor(kRed));
// modelFail->plotOn(mframeFail,Components("bkgexpFail_shifted"),LineStyle(kDashed),LineColor(kGreen+2));
// sprintf(yield,"%u Events",(Int_t)passTree->GetEntries());
// sprintf(nsigstr,"N_{sig} = %.1f #pm %.1f",NsigPass.getVal(),NsigPass.getPropagatedError(*fitResult));
// plotPass.AddTextBox(yield,0.21,0.76,0.51,0.80,0,kBlack,-1);
// plotPass.AddTextBox(effstr,0.70,0.85,0.94,0.90,0,kBlack,-1);
// plotPass.AddTextBox(0.70,0.73,0.94,0.83,0,kBlack,-1,1,nsigstr);//,chi2str);
// mframeFail->Draw();
// cv->SaveAs(Form("ShiftedModel_%d.gif",Option));
// //
// // Plot failing probes
// //
// sprintf(pname,"fail%s_%i",name.Data(),ibin);
// sprintf(yield,"%u Events",(Int_t)failTree->GetEntries());
// sprintf(nsigstr,"N_{sig} = %.1f #pm %.1f",NsigFail.getVal(),NsigFail.getPropagatedError(*fitResult));
// sprintf(nbkgstr,"N_{bkg} = %.1f #pm %.1f",NbkgFail.getVal(),NbkgFail.getPropagatedError(*fitResult));
// sprintf(chi2str,"#chi^{2}/DOF = %.3f",mframePass->chiSquare(nflfail));
// CPlot plotFail(pname,mframeFail,"Failing probes","tag-probe mass [GeV/c^{2}]","Events / 2.0 GeV/c^{2}");
// plotFail.AddTextBox(binlabelx,0.21,0.85,0.51,0.90,0,kBlack,-1);
// if((name.CompareTo("etapt")==0) || (name.CompareTo("etaphi")==0)) {
// plotFail.AddTextBox(binlabely,0.21,0.80,0.51,0.85,0,kBlack,-1);
// plotFail.AddTextBox(yield,0.21,0.76,0.51,0.80,0,kBlack,-1);
// } else {
// plotFail.AddTextBox(yield,0.21,0.81,0.51,0.85,0,kBlack,-1);
// }
// plotFail.AddTextBox(effstr,0.70,0.85,0.94,0.90,0,kBlack,-1);
// plotFail.AddTextBox(0.70,0.68,0.94,0.83,0,kBlack,-1,2,nsigstr,nbkgstr);//,chi2str);
// plotFail.Draw(cfail,kTRUE,format);
} //for loop over all toys
//*************************************************************************************
//Save To File
//*************************************************************************************
outputfile->WriteTObject(outTree, outTree->GetName(), "WriteDelete");
}
void fitbkgdataCard(TString configCard="template.config",
bool dobands = true, // create baerror bands for BG models
bool dosignal = false, // plot the signal model (needs to be present)
bool blinded = true, // blind the data in the plots?
bool verbose = true ) {
gROOT->Macro("MitStyle.C");
gStyle->SetErrorX(0);
gStyle->SetOptStat(0);
gROOT->ForceStyle();
TString projectDir;
std::vector<TString> catdesc;
std::vector<TString> catnames;
std::vector<int> polorder;
double massmin = -1.;
double massmax = -1.;
double theCMenergy = -1.;
bool readStatus = readFromConfigCard( configCard,
projectDir,
catnames,
catdesc,
polorder,
massmin,
massmax,
theCMenergy
);
if( !readStatus ) {
std::cerr<<" ERROR: Could not read from card > "<<configCard.Data()<<" <."<<std::endl;
return;
}
TFile *fdata = new TFile(TString::Format("%s/CMS-HGG-data.root",projectDir.Data()),"READ");
if( !fdata ) {
std::cerr<<" ERROR: Could not open file "<<projectDir.Data()<<"/CMS-HGG-data.root."<<std::endl;
return;
}
if( !gSystem->cd(TString::Format("%s/databkg/",projectDir.Data())) ) {
std::cerr<<" ERROR: Could not change directory to "<<TString::Format("%s/databkg/",projectDir.Data()).Data()<<"."<<std::endl;
return;
}
// ----------------------------------------------------------------------
// load the input workspace....
RooWorkspace* win = (RooWorkspace*)fdata->Get("cms_hgg_workspace_data");
if( !win ) {
std::cerr<<" ERROR: Could not load workspace > cms_hgg_workspace_data < from file > "<<TString::Format("%s/CMS-HGG-data.root",projectDir.Data()).Data()<<" <."<<std::endl;
return;
}
RooRealVar *intLumi = win->var("IntLumi");
RooRealVar *hmass = win->var("CMS_hgg_mass");
if( !intLumi || !hmass ) {
std::cerr<<" ERROR: Could not load needed variables > IntLumi < or > CMS_hgg_mass < forom input workspace."<<std::endl;
return;
}
//win->Print();
hmass->setRange(massmin,massmax);
hmass->setBins(4*(int)(massmax-massmin));
hmass->SetTitle("m_{#gamma#gamma}");
hmass->setUnit("GeV");
hmass->setRange("fitrange",massmin,massmax);
hmass->setRange("blind1",100.,110.);
hmass->setRange("blind2",150.,180.);
// ----------------------------------------------------------------------
// some auxiliray vectro (don't know the meaning of all of them ... yet...
std::vector<RooAbsData*> data_vec;
std::vector<RooAbsPdf*> pdfShape_vec; // vector to store the NOT-EXTENDED PDFs (aka pdfshape)
std::vector<RooAbsPdf*> pdf_vec; // vector to store the EXTENDED PDFs
std::vector<RooAbsReal*> normu_vec; // this holds the normalization vars for each Cat (needed in bands for combined cat)
RooArgList normList; // list of range-limityed normalizations (needed for error bands on combined category)
//std::vector<RooRealVar*> coeffv;
//std::vector<RooAbsReal*> normu_vecv; // ???
// ----------------------------------------------------------------------
// define output works
RooWorkspace *wOut = new RooWorkspace("wbkg","wbkg") ;
// util;ities for the combined fit
RooCategory finalcat ("finalcat", "finalcat") ;
RooSimultaneous fullbkgpdf("fullbkgpdf","fullbkgpdf",finalcat);
RooDataSet datacomb ("datacomb", "datacomb", RooArgList(*hmass,finalcat)) ;
RooDataSet *datacombcat = new RooDataSet("data_combcat","",RooArgList(*hmass)) ;
// add the 'combcat' to the list...if more than one cat
if( catnames.size() > 1 ) {
catnames.push_back("combcat");
catdesc.push_back("Combined");
}
for (UInt_t icat=0; icat<catnames.size(); ++icat) {
TString catname = catnames.at(icat);
finalcat.defineType(catname);
// check if we're in a sub-cat or the comb-cat
RooDataSet *data = NULL;
RooDataSet *inData = NULL;
if( icat < (catnames.size() - 1) || catnames.size() == 1) { // this is NOT the last cat (which is by construction the combination)
inData = (RooDataSet*)win->data(TString("data_mass_")+catname);
if( !inData ) {
std::cerr<<" ERROR: Could not find dataset > data_mass_"<<catname.Data()<<" < in input workspace."<<std::endl;
return;
}
data = new RooDataSet(TString("data_")+catname,"",*hmass,Import(*inData)); // copy the dataset (why?)
// append the data to the combined data...
RooDataSet *datacat = new RooDataSet(TString("datacat")+catname,"",*hmass,Index(finalcat),Import(catname,*data)) ;
datacomb.append(*datacat);
datacombcat->append(*data);
// normalization for this category
RooRealVar *nbkg = new RooRealVar(TString::Format("CMS_hgg_%s_bkgshape_norm",catname.Data()),"",800.0,0.0,25e3);
// we keep track of the normalizario vars only for N-1 cats, naming convetnions hystoric...
if( catnames.size() > 2 && icat < (catnames.size() - 2) ) {
RooRealVar* cbkg = new RooRealVar(TString::Format("cbkg%s",catname.Data()),"",0.0,0.0,1e3);
cbkg->removeRange();
normu_vec.push_back(cbkg);
normList.add(*cbkg);
}
/// generate the Bernstrin polynomial (FIX-ME: add possibility ro create other models...)
fstBernModel* theBGmodel = new fstBernModel(hmass, polorder[icat], icat, catname); // using my dedicated class...
std::cout<<" model name is "<<theBGmodel->getPdf()->GetName()<<std::endl;
RooAbsPdf* bkgshape = theBGmodel->getPdf(); // the BG shape
RooAbsPdf* bkgpdf = new RooExtendPdf(TString("bkgpdf")+catname,"",*bkgshape,*nbkg); // the extended PDF
// add the extedned PDF to the RooSimultaneous holding all models...
fullbkgpdf.addPdf(*bkgpdf,catname);
// store the NON-EXTENDED PDF for usgae to compute the error bands later..
pdfShape_vec.push_back(bkgshape);
pdf_vec .push_back(bkgpdf);
data_vec .push_back(data);
} else {
data = datacombcat; // we're looking at the last cat (by construction the combination)
data_vec.push_back(data);
// sum up all the cts PDFs for combined PDF
RooArgList subpdfs;
for (int ipdf=0; ipdf<pdf_vec.size(); ++ipdf) {
subpdfs.add(*pdf_vec.at(ipdf));
}
RooAddPdf* bkgpdf = new RooAddPdf(TString("bkgpdf")+catname,"",subpdfs);
pdfShape_vec.push_back(bkgpdf);
pdf_vec .push_back(bkgpdf); // I don't think this is really needed though....
}
// generate the binned dataset (to be put into the workspace... just in case...)
RooDataHist *databinned = new RooDataHist(TString("databinned_")+catname,"",*hmass,*data);
wOut->import(*data);
wOut->import(*databinned);
}
std::cout<<" ***************** "<<std::endl;
// fit the RooSimultaneous to the combined dataset -> (we could also fit each cat separately)
fullbkgpdf.fitTo(datacomb,Strategy(1),Minos(kFALSE),Save(kTRUE));
RooFitResult *fullbkgfitres = fullbkgpdf.fitTo(datacomb,Strategy(2),Minos(kFALSE),Save(kTRUE));
// in principle we're done now, so store the results in the output workspace
wOut->import(datacomb);
wOut->import(fullbkgpdf);
wOut->import(*fullbkgfitres);
std::cout<<" ***************** "<<std::endl;
if( verbose ) wOut->Print();
std::cout<<" ***************** "<<std::endl;
wOut->writeToFile("bkgdatawithfit.root") ;
if( verbose ) {
printf("IntLumi = %5f\n",intLumi->getVal());
printf("ndata:\n");
for (UInt_t icat=0; icat<catnames.size(); ++icat) {
printf("%i ",data_vec.at(icat)->numEntries());
}
printf("\n");
}
// --------------------------------------------------------------------------------------------
// Now comesd the plotting
// chage the Statistics style...
gStyle->SetOptStat(1110);
// we want to plot in 1GeV bins (apparently...)
UInt_t nbins = (UInt_t) (massmax-massmin);
// here we'll store the curves for the bands...
std::vector<RooCurve*> fitcurves;
// loop again over the cats
TCanvas **canbkg = new TCanvas*[catnames.size()];
RooPlot** plot = new RooPlot*[catnames.size()];
TLatex** lat = new TLatex*[catnames.size()];
TLatex** lat2 = new TLatex*[catnames.size()];
std::cout<<" beofre plotting..."<<std::endl;
for (UInt_t icat=0; icat<catnames.size(); ++icat) {
TString catname = catnames.at(icat);
std::cout<<" trying to plot #"<<icat<<std::endl;
// plot the data and the fit
canbkg[icat] = new TCanvas;
plot [icat] = hmass->frame(Bins(nbins),Range("fitrange"));
std::cout<<" trying to plot #"<<icat<<std::endl;
// first plot the data invisibly... and put the fitted BG model on top...
data_vec .at(icat)->plotOn(plot[icat],RooFit::LineColor(kWhite),MarkerColor(kWhite),Invisible());
pdfShape_vec.at(icat)->plotOn(plot[icat],RooFit::LineColor(kRed),Range("fitrange"),NormRange("fitrange"));
std::cout<<" trying to plot #"<<icat<<std::endl;
// if toggled on, plot also the Data visibly
if( !blinded ) {
data_vec.at(icat)->plotOn(plot[icat]);
}
std::cout<<" trying to plot #"<<icat<<std::endl;
// some cosmetics...
plot[icat]->SetTitle("");
plot[icat]->SetMinimum(0.0);
plot[icat]->SetMaximum(1.40*plot[icat]->GetMaximum());
plot[icat]->GetXaxis()->SetTitle("m_{#gamma#gamma} (GeV/c^{2})");
plot[icat]->Draw();
std::cout<<" trying to plot #"<<icat<<std::endl;
// legend....
TLegend *legmc = new TLegend(0.68,0.70,0.97,0.90);
legmc->AddEntry(plot[icat]->getObject(2),"Data","LPE");
legmc->AddEntry(plot[icat]->getObject(1),"Bkg Model","L");
// this part computes the 1/2-sigma bands.
TGraphAsymmErrors *onesigma = NULL;
TGraphAsymmErrors *twosigma = NULL;
std::cout<<" trying *** to plot #"<<icat<<std::endl;
RooAddition* sumcatsnm1 = NULL;
if ( dobands ) { //&& icat == (catnames.size() - 1) ) {
onesigma = new TGraphAsymmErrors();
twosigma = new TGraphAsymmErrors();
// get the PDF for this cat from the vector
RooAbsPdf *thisPdf = pdfShape_vec.at(icat);
// get the nominal fir curve
RooCurve *nomcurve = dynamic_cast<RooCurve*>(plot[icat]->getObject(1));
fitcurves.push_back(nomcurve);
bool iscombcat = ( icat == (catnames.size() - 1) && catnames.size() > 1);
RooAbsData *datanorm = ( iscombcat ? &datacomb : data_vec.at(icat) );
// this si the nornmalization in the 'sliding-window' (i.e. per 'test-bin')
RooRealVar *nlim = new RooRealVar(TString::Format("nlim%s",catnames.at(icat).Data()),"",0.0,0.0,10.0);
nlim->removeRange();
if( iscombcat ) {
// ----------- HISTORIC NAMING ----------------------------------------
sumcatsnm1 = new RooAddition("sumcatsnm1","",normList); // summing all normalizations epect the last Cat
// this is the normlization of the last Cat
RooFormulaVar *nlast = new RooFormulaVar("nlast","","TMath::Max(0.1,@0-@1)",RooArgList(*nlim,*sumcatsnm1));
// ... and adding it ot the list of norms
normu_vec.push_back(nlast);
}
//if (icat == 1 && catnames.size() == 2) continue; // only 1 cat, so don't need combination
for (int i=1; i<(plot[icat]->GetXaxis()->GetNbins()+1); ++i) {
// this defines the 'binning' we use for the error bands
double lowedge = plot[icat]->GetXaxis()->GetBinLowEdge(i);
double upedge = plot[icat]->GetXaxis()->GetBinUpEdge(i);
double center = plot[icat]->GetXaxis()->GetBinCenter(i);
// get the nominal value at the center of the bin
double nombkg = nomcurve->interpolate(center);
nlim->setVal(nombkg);
hmass->setRange("errRange",lowedge,upedge);
// this is the new extended PDF whith the normalization restricted to the bin-area
RooAbsPdf *extLimPdf = NULL;
if( iscombcat ) {
extLimPdf = new RooSimultaneous("epdf","",finalcat);
// loop over the cats and generate temporary extended PDFs
for (int jcat=0; jcat<(catnames.size()-1); ++jcat) {
RooRealVar *rvar = dynamic_cast<RooRealVar*>(normu_vec.at(jcat));
if (rvar) rvar->setVal(fitcurves.at(jcat)->interpolate(center));
RooExtendPdf *ecpdf = new RooExtendPdf(TString::Format("ecpdf%s",catnames.at(jcat).Data()),"",*pdfShape_vec.at(jcat),*normu_vec.at(jcat),"errRange");
static_cast<RooSimultaneous*>(extLimPdf)->addPdf(*ecpdf,catnames.at(jcat));
}
} else
extLimPdf = new RooExtendPdf("extLimPdf","",*thisPdf,*nlim,"errRange");
RooAbsReal *nll = extLimPdf->createNLL(*datanorm,Extended(),NumCPU(1));
RooMinimizer minim(*nll);
minim.setStrategy(0);
double clone = 1.0 - 2.0*RooStats::SignificanceToPValue(1.0);
double cltwo = 1.0 - 2.0*RooStats::SignificanceToPValue(2.0);
if (iscombcat) minim.setStrategy(2);
minim.migrad();
if (!iscombcat) {
minim.minos(*nlim);
}
else {
minim.hesse();
nlim->removeAsymError();
}
if( verbose )
printf("errlo = %5f, errhi = %5f\n",nlim->getErrorLo(),nlim->getErrorHi());
onesigma->SetPoint(i-1,center,nombkg);
onesigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());
// to get the 2-sigma bands...
minim.setErrorLevel(0.5*pow(ROOT::Math::normal_quantile(1-0.5*(1-cltwo),1.0), 2)); // the 0.5 is because qmu is -2*NLL
// eventually if cl = 0.95 this is the usual 1.92!
if (!iscombcat) {
minim.migrad();
minim.minos(*nlim);
}
else {
nlim->setError(2.0*nlim->getError());
nlim->removeAsymError();
}
twosigma->SetPoint(i-1,center,nombkg);
twosigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());
// for memory clean-up
delete nll;
delete extLimPdf;
}
hmass->setRange("errRange",massmin,massmax);
if( verbose )
onesigma->Print("V");
// plot[icat] the error bands
twosigma->SetLineColor(kGreen);
twosigma->SetFillColor(kGreen);
twosigma->SetMarkerColor(kGreen);
twosigma->Draw("L3 SAME");
onesigma->SetLineColor(kYellow);
onesigma->SetFillColor(kYellow);
onesigma->SetMarkerColor(kYellow);
onesigma->Draw("L3 SAME");
plot[icat]->Draw("SAME");
// and add the error bands to the legend
legmc->AddEntry(onesigma,"#pm1 #sigma","F");
legmc->AddEntry(twosigma,"#pm2 #sigma","F");
}
std::cout<<" trying ***2 to plot #"<<icat<<std::endl;
// rest of the legend ....
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
lat[icat] = new TLatex(103.0,0.9*plot[icat]->GetMaximum(),TString::Format("#scale[0.7]{#splitline{CMS preliminary}{#sqrt{s} = %.1f TeV L = %.2f fb^{-1}}}",theCMenergy,intLumi->getVal()));
lat2[icat] = new TLatex(103.0,0.75*plot[icat]->GetMaximum(),catdesc.at(icat));
lat[icat] ->Draw();
lat2[icat]->Draw();
// -------------------------------------------------------
// save canvas in different formats
canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".pdf"));
canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".eps"));
canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".root"));
}
return;
}
void performFit(string inputDir, string inputParameterFile, string label,
string PassInputDataFilename, string FailInputDataFilename,
string PassSignalTemplateHistName, string FailSignalTemplateHistName)
{
gBenchmark->Start("fitZCat");
//--------------------------------------------------------------------------------------------------------------
// Settings
//==============================================================================================================
const Double_t mlow = 60;
const Double_t mhigh = 120;
const Int_t nbins = 24;
TString effType = inputDir;
// The fit variable - lepton invariant mass
RooRealVar* rooMass_ = new RooRealVar("Mass","m_{ee}",mlow, mhigh, "GeV/c^{2}");
RooRealVar Mass = *rooMass_;
Mass.setBins(nbins);
// Make the category variable that defines the two fits,
// namely whether the probe passes or fails the eff criteria.
RooCategory sample("sample","") ;
sample.defineType("Pass", 1) ;
sample.defineType("Fail", 2) ;
RooDataSet *dataPass = RooDataSet::read((inputDir+PassInputDataFilename).c_str(),RooArgList(Mass));
RooDataSet *dataFail = RooDataSet::read((inputDir+FailInputDataFilename).c_str(),RooArgList(Mass));
RooDataSet *dataCombined = new RooDataSet("dataCombined","dataCombined", RooArgList(Mass), RooFit::Index(sample),
RooFit::Import("Pass",*dataPass),
RooFit::Import("Fail",*dataFail));
//*********************************************************************************************
//Define Free Parameters
//*********************************************************************************************
RooRealVar* ParNumSignal = LoadParameters(inputParameterFile, label,"ParNumSignal");
RooRealVar* ParNumBkgPass = LoadParameters(inputParameterFile, label,"ParNumBkgPass");
RooRealVar* ParNumBkgFail = LoadParameters(inputParameterFile, label, "ParNumBkgFail");
RooRealVar* ParEfficiency = LoadParameters(inputParameterFile, label, "ParEfficiency");
RooRealVar* ParPassBackgroundExpCoefficient = LoadParameters(inputParameterFile, label, "ParPassBackgroundExpCoefficient");
RooRealVar* ParFailBackgroundExpCoefficient = LoadParameters(inputParameterFile, label, "ParFailBackgroundExpCoefficient");
RooRealVar* ParPassSignalMassShift = LoadParameters(inputParameterFile, label, "ParPassSignalMassShift");
RooRealVar* ParFailSignalMassShift = LoadParameters(inputParameterFile, label, "ParFailSignalMassShift");
RooRealVar* ParPassSignalResolution = LoadParameters(inputParameterFile, label, "ParPassSignalResolution");
RooRealVar* ParFailSignalResolution = LoadParameters(inputParameterFile, label, "ParFailSignalResolution");
// new RooRealVar ("ParPassSignalMassShift","ParPassSignalMassShift",-2.6079e-02,-10.0, 10.0); //ParPassSignalMassShift->setConstant(kTRUE);
// RooRealVar* ParFailSignalMassShift = new RooRealVar ("ParFailSignalMassShift","ParFailSignalMassShift",7.2230e-01,-10.0, 10.0); //ParFailSignalMassShift->setConstant(kTRUE);
// RooRealVar* ParPassSignalResolution = new RooRealVar ("ParPassSignalResolution","ParPassSignalResolution",6.9723e-01,0.0, 10.0); ParPassSignalResolution->setConstant(kTRUE);
// RooRealVar* ParFailSignalResolution = new RooRealVar ("ParFailSignalResolution","ParFailSignalResolution",1.6412e+00,0.0, 10.0); ParFailSignalResolution->setConstant(kTRUE);
//*********************************************************************************************
//
//Load Signal PDFs
//
//*********************************************************************************************
TFile *Zeelineshape_file = new TFile("res/photonEfffromZee.dflag1.eT1.2.gT40.mt15.root", "READ");
TH1* histTemplatePass = (TH1D*) Zeelineshape_file->Get(PassSignalTemplateHistName.c_str());
TH1* histTemplateFail = (TH1D*) Zeelineshape_file->Get(FailSignalTemplateHistName.c_str());
//Introduce mass shift coordinate transformation
// RooFormulaVar PassShiftedMass("PassShiftedMass","@0-@1",RooArgList(Mass,*ParPassSignalMassShift));
// RooFormulaVar FailShiftedMass("FailShiftedMass","@0-@1",RooArgList(Mass,*ParFailSignalMassShift));
RooGaussian *PassSignalResolutionFunction = new RooGaussian("PassSignalResolutionFunction","PassSignalResolutionFunction",Mass,*ParPassSignalMassShift,*ParPassSignalResolution);
RooGaussian *FailSignalResolutionFunction = new RooGaussian("FailSignalResolutionFunction","FailSignalResolutionFunction",Mass,*ParFailSignalMassShift,*ParFailSignalResolution);
RooDataHist* dataHistPass = new RooDataHist("dataHistPass","dataHistPass", RooArgSet(Mass), histTemplatePass);
RooDataHist* dataHistFail = new RooDataHist("dataHistFail","dataHistFail", RooArgSet(Mass), histTemplateFail);
RooHistPdf* signalShapePassTemplatePdf = new RooHistPdf("signalShapePassTemplatePdf", "signalShapePassTemplatePdf", Mass, *dataHistPass, 1);
RooHistPdf* signalShapeFailTemplatePdf = new RooHistPdf("signalShapeFailTemplatePdf", "signalShapeFailTemplatePdf", Mass, *dataHistFail, 1);
RooFFTConvPdf* signalShapePassPdf = new RooFFTConvPdf("signalShapePassPdf","signalShapePassPdf" , Mass, *signalShapePassTemplatePdf,*PassSignalResolutionFunction,2);
RooFFTConvPdf* signalShapeFailPdf = new RooFFTConvPdf("signalShapeFailPdf","signalShapeFailPdf" , Mass, *signalShapeFailTemplatePdf,*FailSignalResolutionFunction,2);
// Now define some efficiency/yield variables
RooFormulaVar* NumSignalPass = new RooFormulaVar("NumSignalPass", "ParEfficiency*ParNumSignal", RooArgList(*ParEfficiency,*ParNumSignal));
RooFormulaVar* NumSignalFail = new RooFormulaVar("NumSignalFail", "(1.0-ParEfficiency)*ParNumSignal", RooArgList(*ParEfficiency,*ParNumSignal));
//*********************************************************************************************
//
// Create Background PDFs
//
//*********************************************************************************************
RooExponential* bkgPassPdf = new RooExponential("bkgPassPdf","bkgPassPdf",Mass, *ParPassBackgroundExpCoefficient);
RooExponential* bkgFailPdf = new RooExponential("bkgFailPdf","bkgFailPdf",Mass, *ParFailBackgroundExpCoefficient);
//*********************************************************************************************
//
// Create Total PDFs
//
//*********************************************************************************************
RooAddPdf pdfPass("pdfPass","pdfPass",RooArgList(*signalShapePassPdf,*bkgPassPdf), RooArgList(*NumSignalPass,*ParNumBkgPass));
RooAddPdf pdfFail("pdfFail","pdfFail",RooArgList(*signalShapeFailPdf,*bkgFailPdf), RooArgList(*NumSignalFail,*ParNumBkgFail));
// PDF for simultaneous fit
RooSimultaneous totalPdf("totalPdf","totalPdf", sample);
totalPdf.addPdf(pdfPass,"Pass");
// totalPdf.Print();
totalPdf.addPdf(pdfFail,"Fail");
totalPdf.Print();
//*********************************************************************************************
//
// Perform Fit
//
//*********************************************************************************************
RooFitResult *fitResult = 0;
// ********* Fix with Migrad first ********** //
fitResult = totalPdf.fitTo(*dataCombined, RooFit::Save(true),
RooFit::Extended(true), RooFit::PrintLevel(-1));
fitResult->Print("v");
// // ********* Fit With Minos ********** //
// fitResult = totalPdf.fitTo(*dataCombined, RooFit::Save(true),
// RooFit::Extended(true), RooFit::PrintLevel(-1), RooFit::Minos());
// fitResult->Print("v");
// // ********* Fix Mass Shift and Fit For Resolution ********** //
// ParPassSignalMassShift->setConstant(kTRUE);
// ParFailSignalMassShift->setConstant(kTRUE);
// ParPassSignalResolution->setConstant(kFALSE);
// ParFailSignalResolution->setConstant(kFALSE);
// fitResult = totalPdf.fitTo(*dataCombined, RooFit::Save(true),
// RooFit::Extended(true), RooFit::PrintLevel(-1));
// fitResult->Print("v");
// // ********* Do Final Fit ********** //
// ParPassSignalMassShift->setConstant(kFALSE);
// ParFailSignalMassShift->setConstant(kFALSE);
// ParPassSignalResolution->setConstant(kTRUE);
// ParFailSignalResolution->setConstant(kTRUE);
// fitResult = totalPdf.fitTo(*dataCombined, RooFit::Save(true),
// RooFit::Extended(true), RooFit::PrintLevel(-1));
// fitResult->Print("v");
double nSignalPass = NumSignalPass->getVal();
double nSignalFail = NumSignalFail->getVal();
double denominator = nSignalPass + nSignalFail;
printf("\nFit results:\n");
if( fitResult->status() != 0 ){
std::cout<<"ERROR: BAD FIT STATUS"<<std::endl;
}
printf(" Efficiency = %.4f +- %.4f\n",
ParEfficiency->getVal(), ParEfficiency->getPropagatedError(*fitResult));
cout << "Signal Pass: "******"Signal Fail: " << nSignalFail << endl;
cout << "*********************************************************************\n";
cout << "Final Parameters\n";
cout << "*********************************************************************\n";
PrintParameter(ParNumSignal, label,"ParNumSignal");
PrintParameter(ParNumBkgPass, label,"ParNumBkgPass");
PrintParameter(ParNumBkgFail, label, "ParNumBkgFail");
PrintParameter(ParEfficiency , label, "ParEfficiency");
PrintParameter(ParPassBackgroundExpCoefficient , label, "ParPassBackgroundExpCoefficient");
PrintParameter(ParFailBackgroundExpCoefficient , label, "ParFailBackgroundExpCoefficient");
PrintParameter(ParPassSignalMassShift , label, "ParPassSignalMassShift");
PrintParameter(ParFailSignalMassShift , label, "ParFailSignalMassShift");
PrintParameter(ParPassSignalResolution , label, "ParPassSignalResolution");
PrintParameter(ParFailSignalResolution , label, "ParFailSignalResolution");
cout << endl << endl;
//--------------------------------------------------------------------------------------------------------------
// Make plots
//==============================================================================================================
TFile *canvasFile = new TFile("Efficiency_FitResults.root", "UPDATE");
RooAbsData::ErrorType errorType = RooAbsData::Poisson;
Mass.setBins(NBINSPASS);
TString cname = TString((label+"_Pass").c_str());
TCanvas *c = new TCanvas(cname,cname,800,600);
RooPlot* frame1 = Mass.frame();
frame1->SetMinimum(0);
dataPass->plotOn(frame1,RooFit::DataError(errorType));
pdfPass.plotOn(frame1,RooFit::ProjWData(*dataPass),
RooFit::Components(*bkgPassPdf),RooFit::LineColor(kRed));
pdfPass.plotOn(frame1,RooFit::ProjWData(*dataPass));
frame1->Draw("e0");
TPaveText *plotlabel = new TPaveText(0.23,0.87,0.43,0.92,"NDC");
plotlabel->SetTextColor(kBlack);
plotlabel->SetFillColor(kWhite);
plotlabel->SetBorderSize(0);
plotlabel->SetTextAlign(12);
plotlabel->SetTextSize(0.03);
plotlabel->AddText("CMS Preliminary 2010");
TPaveText *plotlabel2 = new TPaveText(0.23,0.82,0.43,0.87,"NDC");
plotlabel2->SetTextColor(kBlack);
plotlabel2->SetFillColor(kWhite);
plotlabel2->SetBorderSize(0);
plotlabel2->SetTextAlign(12);
plotlabel2->SetTextSize(0.03);
plotlabel2->AddText("#sqrt{s} = 7 TeV");
TPaveText *plotlabel3 = new TPaveText(0.23,0.75,0.43,0.80,"NDC");
plotlabel3->SetTextColor(kBlack);
plotlabel3->SetFillColor(kWhite);
plotlabel3->SetBorderSize(0);
plotlabel3->SetTextAlign(12);
plotlabel3->SetTextSize(0.03);
char temp[100];
sprintf(temp, "%.4f", LUMINOSITY);
plotlabel3->AddText((string("#int#font[12]{L}dt = ") +
temp + string(" pb^{ -1}")).c_str());
TPaveText *plotlabel4 = new TPaveText(0.6,0.82,0.8,0.87,"NDC");
plotlabel4->SetTextColor(kBlack);
plotlabel4->SetFillColor(kWhite);
plotlabel4->SetBorderSize(0);
plotlabel4->SetTextAlign(12);
plotlabel4->SetTextSize(0.03);
double nsig = ParNumSignal->getVal();
double nErr = ParNumSignal->getError();
double e = ParEfficiency->getVal();
double eErr = ParEfficiency->getError();
double corr = fitResult->correlation(*ParEfficiency, *ParNumSignal);
double err = ErrorInProduct(nsig, nErr, e, eErr, corr);
sprintf(temp, "Signal = %.2f #pm %.2f", NumSignalPass->getVal(), err);
plotlabel4->AddText(temp);
TPaveText *plotlabel5 = new TPaveText(0.6,0.77,0.8,0.82,"NDC");
plotlabel5->SetTextColor(kBlack);
plotlabel5->SetFillColor(kWhite);
plotlabel5->SetBorderSize(0);
plotlabel5->SetTextAlign(12);
plotlabel5->SetTextSize(0.03);
sprintf(temp, "Bkg = %.2f #pm %.2f", ParNumBkgPass->getVal(), ParNumBkgPass->getError());
plotlabel5->AddText(temp);
TPaveText *plotlabel6 = new TPaveText(0.6,0.87,0.8,0.92,"NDC");
plotlabel6->SetTextColor(kBlack);
plotlabel6->SetFillColor(kWhite);
plotlabel6->SetBorderSize(0);
plotlabel6->SetTextAlign(12);
plotlabel6->SetTextSize(0.03);
plotlabel6->AddText("Passing probes");
TPaveText *plotlabel7 = new TPaveText(0.6,0.72,0.8,0.77,"NDC");
plotlabel7->SetTextColor(kBlack);
plotlabel7->SetFillColor(kWhite);
plotlabel7->SetBorderSize(0);
plotlabel7->SetTextAlign(12);
plotlabel7->SetTextSize(0.03);
sprintf(temp, "Eff = %.3f #pm %.3f", ParEfficiency->getVal(), ParEfficiency->getErrorHi());
plotlabel7->AddText(temp);
TPaveText *plotlabel8 = new TPaveText(0.6,0.72,0.8,0.66,"NDC");
plotlabel8->SetTextColor(kBlack);
plotlabel8->SetFillColor(kWhite);
plotlabel8->SetBorderSize(0);
plotlabel8->SetTextAlign(12);
plotlabel8->SetTextSize(0.03);
sprintf(temp, "#chi^{2}/DOF = %.3f", frame1->chiSquare());
plotlabel8->AddText(temp);
plotlabel4->Draw();
plotlabel5->Draw();
plotlabel6->Draw();
plotlabel7->Draw();
plotlabel8->Draw();
// c->SaveAs( cname + TString(".eps"));
c->SaveAs( cname + TString(".gif"));
canvasFile->WriteTObject(c, c->GetName(), "WriteDelete");
Mass.setBins(NBINSFAIL);
cname = TString((label+"_Fail").c_str());
TCanvas* c2 = new TCanvas(cname,cname,800,600);
RooPlot* frame2 = Mass.frame();
frame2->SetMinimum(0);
dataFail->plotOn(frame2,RooFit::DataError(errorType));
pdfFail.plotOn(frame2,RooFit::ProjWData(*dataFail),
RooFit::Components(*bkgFailPdf),RooFit::LineColor(kRed));
pdfFail.plotOn(frame2,RooFit::ProjWData(*dataFail));
frame2->Draw("e0");
plotlabel = new TPaveText(0.23,0.87,0.43,0.92,"NDC");
plotlabel->SetTextColor(kBlack);
plotlabel->SetFillColor(kWhite);
plotlabel->SetBorderSize(0);
plotlabel->SetTextAlign(12);
plotlabel->SetTextSize(0.03);
plotlabel->AddText("CMS Preliminary 2010");
plotlabel2 = new TPaveText(0.23,0.82,0.43,0.87,"NDC");
plotlabel2->SetTextColor(kBlack);
plotlabel2->SetFillColor(kWhite);
plotlabel2->SetBorderSize(0);
plotlabel2->SetTextAlign(12);
plotlabel2->SetTextSize(0.03);
plotlabel2->AddText("#sqrt{s} = 7 TeV");
plotlabel3 = new TPaveText(0.23,0.75,0.43,0.80,"NDC");
plotlabel3->SetTextColor(kBlack);
plotlabel3->SetFillColor(kWhite);
plotlabel3->SetBorderSize(0);
plotlabel3->SetTextAlign(12);
plotlabel3->SetTextSize(0.03);
sprintf(temp, "%.4f", LUMINOSITY);
plotlabel3->AddText((string("#int#font[12]{L}dt = ") +
temp + string(" pb^{ -1}")).c_str());
plotlabel4 = new TPaveText(0.6,0.82,0.8,0.87,"NDC");
plotlabel4->SetTextColor(kBlack);
plotlabel4->SetFillColor(kWhite);
plotlabel4->SetBorderSize(0);
plotlabel4->SetTextAlign(12);
plotlabel4->SetTextSize(0.03);
err = ErrorInProduct(nsig, nErr, 1.0-e, eErr, corr);
sprintf(temp, "Signal = %.2f #pm %.2f", NumSignalFail->getVal(), err);
plotlabel4->AddText(temp);
plotlabel5 = new TPaveText(0.6,0.77,0.8,0.82,"NDC");
plotlabel5->SetTextColor(kBlack);
plotlabel5->SetFillColor(kWhite);
plotlabel5->SetBorderSize(0);
plotlabel5->SetTextAlign(12);
plotlabel5->SetTextSize(0.03);
sprintf(temp, "Bkg = %.2f #pm %.2f", ParNumBkgFail->getVal(), ParNumBkgFail->getError());
plotlabel5->AddText(temp);
plotlabel6 = new TPaveText(0.6,0.87,0.8,0.92,"NDC");
plotlabel6->SetTextColor(kBlack);
plotlabel6->SetFillColor(kWhite);
plotlabel6->SetBorderSize(0);
plotlabel6->SetTextAlign(12);
plotlabel6->SetTextSize(0.03);
plotlabel6->AddText("Failing probes");
plotlabel7 = new TPaveText(0.6,0.72,0.8,0.77,"NDC");
plotlabel7->SetTextColor(kBlack);
plotlabel7->SetFillColor(kWhite);
plotlabel7->SetBorderSize(0);
plotlabel7->SetTextAlign(12);
plotlabel7->SetTextSize(0.03);
sprintf(temp, "Eff = %.3f #pm %.3f", ParEfficiency->getVal(), ParEfficiency->getErrorHi(), ParEfficiency->getErrorLo());
plotlabel7->AddText(temp);
plotlabel8 = new TPaveText(0.6,0.72,0.8,0.66,"NDC");
plotlabel8->SetTextColor(kBlack);
plotlabel8->SetFillColor(kWhite);
plotlabel8->SetBorderSize(0);
plotlabel8->SetTextAlign(12);
plotlabel8->SetTextSize(0.03);
sprintf(temp, "#chi^{2}/DOF = %.3f", frame2->chiSquare());
plotlabel8->AddText(temp);
// plotlabel->Draw();
// plotlabel2->Draw();
// plotlabel3->Draw();
plotlabel4->Draw();
plotlabel5->Draw();
plotlabel6->Draw();
plotlabel7->Draw();
plotlabel8->Draw();
c2->SaveAs( cname + TString(".gif"));
// c2->SaveAs( cname + TString(".eps"));
// c2->SaveAs( cname + TString(".root"));
canvasFile->WriteTObject(c2, c2->GetName(), "WriteDelete");
canvasFile->Close();
effTextFile.width(40);
effTextFile << label;
effTextFile.width(20);
effTextFile << setiosflags(ios::fixed) << setprecision(4) << left << ParEfficiency->getVal() ;
effTextFile.width(20);
effTextFile << left << ParEfficiency->getErrorHi();
effTextFile.width(20);
effTextFile << left << ParEfficiency->getErrorLo();
effTextFile.width(14);
effTextFile << setiosflags(ios::fixed) << setprecision(2) << left << nSignalPass ;
effTextFile.width(14);
effTextFile << left << nSignalFail << endl;
}
