void PEs(RooAbsPdf *iGen,RooAbsPdf *iFit,int iN,int iNEvents,RooRealVar &iVar,RooRealVar &iSig,RooRealVar &iMean, RooRealVar &iScale,RooRealVar &iRes) { double iM0 = iMean.getVal(); double iS0 = iSig.getVal(); //iScale.setVal(iMeanScale); iRes.setVal(iSigScale); TRandom1 *lRand = new TRandom1(0xDEADBEEF); TNtuple * lDN= new TNtuple( "xxx","xxx","ntot:m_r:m:merr:sig_r:sig:sigerr"); for(int i0=0;i0<iN;i0++){ if(i0 % 10 == 0) cout << "+++++++++++++++++++++++++++ running ======> " << i0 << endl; int lN = lRand->Poisson(iNEvents); RooDataSet * lSignal = iGen->generate(iVar,lN); iMean.setVal(iM0); iSig.setVal(iS0); iFit->fitTo(*lSignal,Strategy(1));//,Save(kTRUE),PrintLevel(1)); if(iMean.getError() < 0.05) iFit->fitTo(*lSignal,Strategy(2)); Float_t values[]={ (Float_t) lN, (Float_t) 90.78/iScale.getVal(), (Float_t) iMean.getVal(), (Float_t) iMean.getError(), (Float_t) iSig.getVal(), (Float_t) iSig.getVal(), (Float_t) iSig.getError() }; lDN->Fill(values); } TFile *lF = new TFile("XXX.root","RECREATE"); lDN->Write(); lF->Close(); }
void Plot(RooAbsPdf *iGen,RooAbsPdf *iFit,int iN,int iNEvents,RooRealVar &iVar,RooRealVar &iSig,RooRealVar &iMean, RooRealVar &iScale,RooRealVar &iRes,RooDataSet *iData=0) { TRandom1 *lRand = new TRandom1(0xDEADBEEF); RooDataSet * lSignal = iGen->generate(iVar,iNEvents); if(iData == 0) { iFit->fitTo(*lSignal,Strategy(1)); if(iMean.getError() < 0.05) iFit->fitTo(*lSignal,Strategy(2)); } else { iFit->fitTo(*iData,Strategy(1)); if(iMean.getError() < 0.05) iFit->fitTo(*iData,Strategy(2)); } iVar.setBins(30); RooPlot *lFrame1 = iVar.frame(RooFit::Title("XXX")) ; if(iData == 0) lSignal->plotOn(lFrame1); if(iData != 0) iData->plotOn(lFrame1); iFit->plotOn(lFrame1); TCanvas *iC =new TCanvas("A","A",800,600); iC->cd(); lFrame1->Draw(); iC->SaveAs("Crap.png"); if(iData != 0) { RooPlot *lFrame2 = iVar.frame(RooFit::Title("XXX")) ; iData->plotOn(lFrame2); iGen->plotOn(lFrame2); TCanvas *iC1 =new TCanvas("B","B",800,600); iC1->cd(); lFrame2->Draw(); iC1->SaveAs("Crap.png"); } }
void FitterUtils::initiateParams(int nGenSignalZeroGamma, int nGenSignalOneGamma, int nGenSignalTwoGamma, RooRealVar const& expoConstGen, RooRealVar& nSignal, RooRealVar& nPartReco, RooRealVar& nComb, RooRealVar& fracZero, RooRealVar& fracOne, RooRealVar& expoConst, RooRealVar& nJpsiLeak, bool constPartReco, RooRealVar const& fracPartRecoSigma) { TRandom rand; rand.SetSeed(); int nGenSignal = nGenSignalZeroGamma + nGenSignalOneGamma + nGenSignalTwoGamma; double nGenSignal2; double nGenPartReco2; if(!constPartReco) { nGenSignal2 = rand.Uniform(nGenSignal-5*sqrt(nGenSignal), nGenSignal+5*sqrt(nGenSignal)); nGenPartReco2 = rand.Uniform(nGenPartReco-5*sqrt(nGenPartReco), nGenPartReco+5*sqrt(nGenPartReco)); } if(constPartReco) { double nGenSigPartReco( nGenSignal+nGenPartReco ); double nGenSigPartReco2( rand.Uniform( nGenSigPartReco-5*sqrt(nGenSigPartReco), nGenSigPartReco+5*sqrt(nGenSigPartReco) ) ); double fracPartReco1( nGenPartReco/(1.*nGenSignal)); double fracPartReco2( rand.Uniform(fracPartReco1-5*fracPartRecoSigma.getVal(), fracPartReco1+5*fracPartRecoSigma.getVal()) ); nGenPartReco2 = fracPartReco2*nGenSigPartReco2 / (1+fracPartReco2); nGenSignal2 = nGenSigPartReco2 / (1+fracPartReco2); } double nGenComb2 = rand.Uniform(nGenComb-5*sqrt(nGenComb), nGenComb+5*sqrt(nGenComb)); double nGenJpsiLeak2 = rand.Uniform(nGenJpsiLeak-5*sqrt(nGenJpsiLeak), nGenJpsiLeak+5*sqrt(nGenJpsiLeak)); nSignal.setVal(nGenSignal2); nSignal.setRange(TMath::Max(0.,nGenSignal2-10.*sqrt(nGenSignal)) , nGenSignal2+10*sqrt(nGenSignal)); nPartReco.setVal(nGenPartReco2); nPartReco.setRange(TMath::Max(0.,nGenPartReco2-10.*sqrt(nGenPartReco)), nGenPartReco2+10*sqrt(nGenPartReco)); nComb.setVal(nGenComb2); nComb.setRange(TMath::Max(0.,nGenComb2-10.*sqrt(nGenComb)), nGenComb2+10*sqrt(nGenComb)); nJpsiLeak.setVal(nGenJpsiLeak2); nJpsiLeak.setRange(TMath::Max(0., nGenJpsiLeak2-10*sqrt(nGenJpsiLeak)), nGenJpsiLeak2+10*sqrt(nGenJpsiLeak)); double fracGenZero(nGenSignalZeroGamma/(1.*nGenSignal)); double fracGenOne(nGenSignalOneGamma/(1.*nGenSignal)); fracZero.setVal(rand.Gaus(fracGenZero, sqrt(nGenSignalZeroGamma)/(1.*nGenSignal))) ; fracZero.setRange(0., 1.); fracOne.setVal(rand.Gaus(fracGenOne, sqrt(nGenSignalOneGamma)/(1.*nGenSignal))) ; fracOne.setRange(0., 1.); expoConst.setVal(rand.Uniform( expoConstGen.getVal() - 5*expoConstGen.getError(), expoConstGen.getVal() + 5*expoConstGen.getError() ) ); expoConst.setRange( expoConstGen.getVal() - 10*expoConstGen.getError(), expoConstGen.getVal() + 10*expoConstGen.getError() ); }
MakeBiasStudy::MakeBiasStudy() { int Nmodels = 8; //RooRealVar* mass = ws->var("mass"); RooRealVar *mass = new RooRealVar("mass","mass", 100,180); RooRealVar *nBkgTruth = new RooRealVar("TruthNBkg","", 0,1e9); // RooAbsData* realData = ws->data("Data_Combined")->reduce( Form("evtcat==evtcat::%s",cat.Data()) ); double Bias[Nmodels][Nmodels]; double BiasE[Nmodels][Nmodels]; MakeAICFits MakeAIC_Fits; for(int truthType = 0; truthType < Nmodels; truthType++){ RooAbsPdf *truthPdf = MakeAIC_Fits.getBackgroundPdf(truthType,mass); RooExtendPdf *truthExtendedPdf = new RooExtendPdf("truthExtendedPdf","",*truthPdf,*nBkgTruth); //truthExtendedPdf.fitTo(*realData,RooFit::Strategy(0),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE)); //truthExtendedPdf.fitTo(*realData,RooFit::Strategy(2),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE)); double BiasWindow = 2.00; mass->setRange("biasRegion", mh-BiasWindow, mh+BiasWindow); double TruthFrac = truthExtendedPdf->createIntegral(mass,RooFit::Range("biasRegion"),RooFit::NormSet(*mass))->getVal(); double NTruth = TruthFrac * nBkgTruth->getVal(); double NTruthE = TruthFrac * nBkgTruth->getError(); RooDataSet* truthbkg = truthPdf->generate(RooArgSet(*mass),nBkgTruth); for(int modelType = 0; modelType < Nmodels; modelType++){ RooAbsPdf* ModelShape = MakeAIC_Fits.getBackgroundPdf(modelType,mass); RooRealVar *nBkgFit = new RooRealVar("FitNBkg", "", 0, 1e9); RooExtendPdf ModelExtendedPdf = new RooExtendPdf("ModelExtendedPdf", "",*ModelShape, *nBkgFit); ModelExtendedPdf.fitTo(truthbkg, RooFit::Strategy(0),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE)); ModelExtendedPdf.fitTo(truthbkg, RooFit::Strategy(2),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE)); double FitFrac = ModelExtendedPdf.createIntegral(mass,RooFit::Range("biasRegion"),RooFit::NormSet(mass))->getVal(); double NFit = FitFrac * nBkgFit->getVal(); double NFitE = FitFrac * nBkgFit->getError(); Bias[truthType][modelType] = fabs(NFit - NTruth); BiasE[truthType][modelType] = fabs(NFitE - NTruthE); } } for(int i = 0; i < Nmodels; i++) { std::cout << "===== Truth Model : " << MakeBiasStudy::Category(i) << " ===== " << std::endl; for (int j = 0; j < Nmodels; j++) { std::cout << "Fit Model: " << MakeBiasStudy::Category(j) << " , Bias = " << Bias[i][j] << " +/- " << BiasE[i][j] << std::endl; } } }
double getSigmaError(RooWorkspace *w) { using namespace RooFit; // Access saved Sigma CB values and error from WorkSpace RooRealVar *mySavedSigma = w->var("sigma_{CB}"); RooRealVar *mySavedDeltaM = w->var("#Deltam_{CB}"); Double_t sigma = mySavedSigma->getVal(); Double_t sigmaerror = mySavedSigma->getError(); Double_t DeltaM = mySavedDeltaM->getVal(); Double_t DeltaMerror = mySavedDeltaM->getError(); Double_t Sigpercent = 100 * sigma / (91.187 + DeltaM); Double_t Sigpercenterror = 100 * pow(pow(sigmaerror / (91.198 + DeltaM), 2) + pow((sigma * DeltaMerror) / pow(DeltaM + 91.198, 2), 2), .5); return Sigpercenterror; } // plotFitOn(..)
void simplePrintResults() { vector<string> filenames; filenames.push_back("Output/Test2/result/FIT_DATA_Psi2SJpsi_PPPrompt_Bkg_SecondOrderChebychev_pt65300_rap016_cent0200_262620_263757.root"); const char* parname = "N_Jpsi_PP"; vector<string>::iterator it = filenames.begin(); for (it; it<filenames.end(); it++) { TFile *f = new TFile(it->c_str()); if (!f) { cout << "Error, " << *it << " not found" << endl; continue; } RooWorkspace *ws = (RooWorkspace*) f->Get("workspace"); if (!ws) { cout << "Error, workspace not found in " << *it << endl; continue; } RooRealVar *var = ws->var(parname); if (!ws) { cout << "Error, variable " << parname << " not found in " << *it << endl; continue; } cout << *it << " " << var->getVal() << " +- " << var->getError() << endl; } }
void PDF_GLWADS_Dpi_K3pi::setUncertainties(config c) { switch(c) { case lumi1fb: { obsErrSource = "1fb-1, ExpNll/sept2012K3PIResult.root"; TString File = this->dir+"/ExpNll/sept2012K3PIResult.root"; TFile *fr = TFile::Open(File); RooFitResult *r = (RooFitResult*)fr->Get("fitresult_model_reducedData_binned"); assert(r); for ( int i=0; i<nObs; i++ ) { RooRealVar* pObs = (RooRealVar*)((RooArgList*)observables)->at(i); RooRealVar* pRes = (RooRealVar*)r->floatParsFinal().find(obsTmkToMalcolm(pObs->GetName())); assert(pRes); StatErr[i] = pRes->getError(); } SystErr[0] = 0.010; // afav_dpi_obs SystErr[1] = 0.00011; // rp_dpi_obs SystErr[2] = 0.00011; // rm_dpi_obs fr->Close(); delete r; delete fr; break; } default: cout << "PDF_GLWADS_Dpi_K3pi::setUncertainties() : ERROR : config "+ConfigToTString(c)+" not found." << endl; exit(1); } }
void checkBestFitPoint(std::string workspace, std::string fitFile, bool splusb){ // Open the ws file... TFile *fd_=0; TFile *fw_=0; gSystem->Load("$CMSSW_BASE/lib/$SCRAM_ARCH/libHiggsAnalysisCombinedLimit.so"); gROOT->SetBatch(true); gStyle->SetOptFit(0); gStyle->SetOptStat(0); gStyle->SetPalette(1,0); fw_ = TFile::Open(workspace.c_str()); w = (RooWorkspace*) fw_->Get("w"); w->Print(); RooDataSet *data = (RooDataSet*) w->data("data_obs"); if (splusb) { mc_s = (RooStats::ModelConfig*)w->genobj("ModelConfig"); } else { mc_s = (RooStats::ModelConfig*)w->genobj("ModelConfig_bonly"); } std::cout << "make nll"<<std::endl; nll = mc_s->GetPdf()->createNLL( *data,RooFit::Constrain(*mc_s->GetNuisanceParameters()) ,RooFit::Extended(mc_s->GetPdf()->canBeExtended())); // Now get the best fit result fd_ = TFile::Open(fitFile.c_str()); RooFitResult *fit; if (splusb) { fit =(RooFitResult*)fd_->Get("fit_s"); } else { fit =(RooFitResult*)fd_->Get("fit_b"); } RooArgSet fitargs = fit->floatParsFinal(); std::cout << "Got the best fit values" <<std::endl; w->saveSnapshot("bestfitall",fitargs,true); TString filename; if (splusb) { filename = "minimum_s.pdf"; } else { filename = "minimum_b.pdf"; } // Now make the plots! TCanvas *c = new TCanvas("c","",600,600); c->SaveAs((filename+"[")); TIterator* iter(fitargs->createIterator()); for (TObject *a = iter->Next(); a != 0; a = iter->Next()) { RooRealVar *rrv = dynamic_cast<RooRealVar *>(a); std::string name = rrv->GetName(); TGraph *gr = graphLH(name,rrv->getError()); gr->Draw("ALP"); c->SaveAs((filename+"[")); } c->SaveAs((filename+"]")); }
// grab the initial parameters and errors for making pull distributions: // Take these from a fit file to the data themselves void fillInitialParams(RooArgSet *args, std::map<std::string, std::pair<double,double> > &vals){ TIterator* iter(args->createIterator()); for (TObject *a = iter->Next(); a != 0; a = iter->Next()) { RooRealVar *rrv = dynamic_cast<RooRealVar *>(a); std::string name = rrv->GetName(); std::pair<double,double> valE(rrv->getVal(),rrv->getError()); vals.insert( std::pair<std::string,std::pair<double ,double> > (name,valE)) ; } }
void FitterUtilsSimultaneousExpOfPolyTimesX::initiateParams(int nGenSignalZeroGamma, int nGenSignalOneGamma, int nGenSignalTwoGamma, RooRealVar& nKemu, RooRealVar& nSignal, RooRealVar& nPartReco, RooRealVar& nComb, RooRealVar& fracZero, RooRealVar& fracOne, RooRealVar& nJpsiLeak, bool constPartReco, RooRealVar const& fracPartRecoSigma, RooRealVar& l1Kee, RooRealVar& l2Kee, RooRealVar& l3Kee, RooRealVar& l4Kee, RooRealVar& l5Kee, RooRealVar& l1Kemu, RooRealVar& l2Kemu, RooRealVar& l3Kemu, RooRealVar& l4Kemu, RooRealVar& l5Kemu, RooRealVar const& l1KeeGen, RooRealVar const& l2KeeGen, RooRealVar const& l3KeeGen, RooRealVar const& l4KeeGen, RooRealVar const& l5KeeGen ) { FitterUtilsExpOfPolyTimesX::initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma, nSignal, nPartReco, nComb, fracZero, fracOne, nJpsiLeak, constPartReco, fracPartRecoSigma, l1Kee, l2Kee, l3Kee, l4Kee, l5Kee, l1KeeGen, l2KeeGen, l3KeeGen, l4KeeGen, l5KeeGen ); TRandom rand; rand.SetSeed(); nKemu.setVal(rand.Uniform(nGenKemu-5*sqrt(nGenKemu), nGenKemu+5*sqrt(nGenKemu))); nKemu.setRange(nGenKemu-10*sqrt(nGenKemu), nGenKemu+10*sqrt(nGenKemu)); l1Kemu.setVal(rand.Uniform( l1KeeGen.getVal() - 5*l1KeeGen.getError(), l1KeeGen.getVal() + 5*l1KeeGen.getError() ) ); l1Kemu.setRange( l1KeeGen.getVal() - 10*l1KeeGen.getError(), l1KeeGen.getVal() + 10*l1KeeGen.getError() ); l2Kemu.setVal(rand.Uniform( l2KeeGen.getVal() - 5*l2KeeGen.getError(), l2KeeGen.getVal() + 5*l2KeeGen.getError() ) ); l2Kemu.setRange( l2KeeGen.getVal() - 10*l2KeeGen.getError(), l2KeeGen.getVal() + 10*l2KeeGen.getError() ); l3Kemu.setVal(rand.Uniform( l3KeeGen.getVal() - 5*l3KeeGen.getError(), l3KeeGen.getVal() + 5*l3KeeGen.getError() ) ); l3Kemu.setRange( l3KeeGen.getVal() - 10*l3KeeGen.getError(), l3KeeGen.getVal() + 10*l3KeeGen.getError() ); l4Kemu.setVal(rand.Uniform( l4KeeGen.getVal() - 5*l4KeeGen.getError(), l4KeeGen.getVal() + 5*l4KeeGen.getError() ) ); l4Kemu.setRange( l4KeeGen.getVal() - 10*l4KeeGen.getError(), l4KeeGen.getVal() + 10*l4KeeGen.getError() ); l5Kemu.setVal(rand.Uniform( l5KeeGen.getVal() - 5*l5KeeGen.getError(), l5KeeGen.getVal() + 5*l5KeeGen.getError() ) ); l5Kemu.setRange( l5KeeGen.getVal() - 10*l5KeeGen.getError(), l5KeeGen.getVal() + 10*l5KeeGen.getError() ); }
void MakeSpinPlots::MakeChannelComp(const char* mcType){ TGraphErrors graph(catNames.size()); RooRealVar mu("mu","",-50,50); float exp = ws->data(Form("%s_Combined",mcType))->sumEntries();///total * 607*lumi/12.; TH1F frame("frame","",catNames.size(),0,catNames.size()); //graph.GetXaxis()->SetNdivisions(catNames.size()); float min=99999,max=-99999; for(int i=0;i<catNames.size();i++){ RooRealVar *ind = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcType, catNames.at(i).Data()) ); RooRealVar *f = ws->var( Form("Data_%s_FULLFIT_%s_fsig",mcType, catNames.at(i).Data()) ); float mu = ind->getVal()/exp/f->getVal(); float muE = ind->getError()/exp/f->getVal(); graph.SetPoint(i,i+0.5,mu); graph.SetPointError(i,0,muE); if(mu-muE < min) min = mu-muE; if(mu+muE > max) max = mu+muE; //graph.GetXaxis()->SetBinLabel(i+1,catNames.at(i)); } TF1 fit("fit","[0]",0+0.5,catNames.size()+0.5); graph.Fit(&fit,"MNE"); float mean = fit.GetParameter(0); float meanE = fit.GetParError(0); frame.SetAxisRange(min-1.5,max+0.5,"Y"); frame.SetYTitle("Fitted #sigma/#sigma_{SM}"); frame.SetXTitle("Category"); TCanvas cv; frame.Draw(); TBox err(0,mean-meanE,catNames.size(),mean+meanE); err.SetFillColor(kGreen); frame.Draw(); err.Draw("SAME"); TLine mLine(0,mean,catNames.size(),mean); mLine.Draw("SAME"); graph.Draw("PSAME"); cv.SaveAs(basePath+Form("/ChannelComp_%s_%s.png",mcType,outputTag.Data())); cv.SaveAs(basePath+Form("/ChannelComp_%s_%s.pdf",mcType,outputTag.Data())); }
void MakeSpinPlots::printYields(const char* mcType){ RooRealVar * tot = ws->var(Form("Data_%s_FULLFIT_Nsig",mcType)); if(tot==0) return; cout << "Total Yield: " << tot->getVal() << " +- " << tot->getError() <<endl; cout << "Category Yields: CONSTRAINED FIT " << endl; for(int i=0;i<catNames.size();i++){ RooRealVar *f = ws->var( Form("Data_%s_FULLFIT_%s_fsig",mcType, catNames.at(i).Data()) ); cout << "\t" << catNames.at(i) <<": " << tot->getVal()*f->getVal() << " +- " << tot->getError()*f->getVal() <<endl; } cout << "\nCategory Yields: INDEPENDENT FIT " << endl; for(int i=0;i<catNames.size();i++){ RooRealVar *ind = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcType, catNames.at(i).Data()) ); if(ind==0) continue; cout << "\t" << catNames.at(i) <<": " << ind->getVal() << " +- " << ind->getError() <<endl; } float exp = ws->data(Form("%s_Combined",mcType))->sumEntries();///total * 607*lumi/12.; cout << endl << "Expected Events: " << exp << endl; cout << "Expected Yields Per Category: " <<endl; for(int i=0;i<catNames.size();i++){ RooRealVar *f = ws->var( Form("Data_%s_FULLFIT_%s_fsig",mcType, catNames.at(i).Data()) ); cout << "\t" << catNames.at(i) <<": " << exp*f->getVal() <<endl; } cout << "mu: " << tot->getVal()/exp << " +- " << tot->getError()/exp <<endl; for(int i=0;i<catNames.size();i++){ RooRealVar *ind = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcType, catNames.at(i).Data()) ); if(ind==0) continue; RooRealVar *f = ws->var( Form("Data_%s_FULLFIT_%s_fsig",mcType, catNames.at(i).Data()) ); cout << "\t" << catNames.at(i) <<": " << ind->getVal()/(exp*f->getVal()) << " +- " << ind->getError()/(exp*f->getVal()) <<endl; } MakeChannelComp(mcType); }
void logStatisticsPar(std::ostream& out, RooDataSet *dataSet, RooRealVar *realVar, int nBins, double chi2, const RooArgList &variables) { TH1 *histogram = dataSet->createHistogram(Form("h%s", dataSet->GetName()), *realVar, RooFit::Binning(nBins)); // Create the TeX file out << "\\documentclass[10pt]{article}" << std::endl; out << "\\usepackage[usenames]{color} %used for font color" << std::endl; out << "\\usepackage{fontspec}" << std::endl; out << "\\usepackage{xunicode}" << std::endl; out << "\\usepackage{xltxtra}" << std::endl; out << "\\defaultfontfeatures{Scale=MatchLowercase}" << std::endl; out << "\\setromanfont[Mapping=tex-text]{Myriad Pro}" << std::endl; out << "\\setsansfont[Mapping=tex-text]{Myriad Pro}" << std::endl; out << "\\setmonofont{Monaco}" << std::endl; out << "\\begin{document}" << std::endl; out << "\\thispagestyle{empty}" << std::endl; out << "\\setlength{\\tabcolsep}{1ex}" << std::endl; out << "\\setlength{\\fboxsep}{0ex}" << std::endl; out << "{\\fontsize{7pt}{0.9em}\\selectfont" << std::endl; out << "\\framebox{\\begin{tabular*}{60pt}{l@{\\extracolsep{\\fill}}r}" << std::endl; // This is the particular info for the histogram out << "Entries & " ; formatNumber(histogram->GetEntries(), out) << " \\\\" << std::endl; out << "Mean & " ; formatNumber(histogram->GetMean(), out) << " \\\\" << std::endl; out << "RMS & " ; formatNumber(histogram->GetRMS(), out) << " \\\\" << std::endl; if (chi2 > 0.0) { out << "Fit $\\chi^{2}$ & " ; formatNumber(chi2, out) << " \\\\" << std::endl; } RooRealVar *theVariable; for (int index = 0; index < variables.getSize(); index++) { theVariable = dynamic_cast<RooRealVar*>(variables.find(variables[index].GetName())); out << theVariable->GetTitle() << " & $\\textrm{" ; formatNumber(theVariable->getValV(), out) << "} \\pm \\textrm{" ; formatNumber(theVariable->getError(), out) << "}$ \\\\" << std::endl; } out << "\\end{tabular*}}}" << std::endl; out << "\\end{document}" << std::endl; histogram->Delete(); }
bool extractParameter(string fileName, const char* parName, pair<double,double>& value) { TFile *f = new TFile( fileName.c_str() ); if (!f) { cout << "[Error] " << fileName << " not found" << endl; return false; } RooWorkspace *ws = (RooWorkspace*) f->Get("workspace"); if (!ws) { cout << "[ERROR] Workspace not found in " << fileName << endl; return false; } RooRealVar *var = ws->var(parName); if (!var) { value = make_pair( -999.9 , -999.9 ); return true; } value = make_pair( var->getValV() , var->getError() ); return true; }
RooDataSet * getDataAndFrac(TString name, TString q2name, TreeReader * mydata, TCut cut, RooRealVar * MM, double * frac, Str2VarMap jpsiPars, double *outnsig) { RooRealVar * cosThetaL = new RooRealVar("cosThetaL","cosThetaL",0.,-1.,1.); RooRealVar * cosThetaB = new RooRealVar("cosThetaB","cosThetaB",0.,-1.,1.); TCut massCut = "Lb_MassConsLambda > 5590 && Lb_MassConsLambda < 5650"; Analysis * ana = new Analysis(name+"_mass"+q2name,"Lb",mydata,&cut,MM); ana->AddVariable("J_psi_1S_MM"); ana->AddVariable(cosThetaL); ana->AddVariable(cosThetaB); RooAbsPdf * mysig = stringToPdf("Gauss","sig",MM,jpsiPars); RooAbsPdf * mybkg = stringToPdf("Exp","bkgM",MM); RooRealVar * mynsig = new RooRealVar("mynsig","mynsig",50,0,100000); RooRealVar * mynbkg = new RooRealVar("mynbkg","mynbkg",10,0,100000); RooAbsPdf * Mmodel = new RooAddPdf("MassModel","MassModel",RooArgSet(*mysig,*mybkg),RooArgSet(*mynsig,*mynbkg)); ana->applyCuts(&cut); RooDataSet * data = ana->GetDataSet("-recalc"); Mmodel->fitTo(*data,Extended(kTRUE)); double sigBkg = mybkg->createIntegral(*MM,NormSet(*MM),Range("Signal"))->getVal(); double sig = mysig->createIntegral(*MM,NormSet(*MM),Range("Signal"))->getVal(); double nsig = mynsig->getVal(); double nbkg = mynbkg->getVal(); if(frac) { frac[0] = nsig*sig/(nsig*sig+nbkg*sigBkg); frac[1] = frac[0]*TMath::Sqrt( TMath::Power(mynsig->getError()/nsig,2) + TMath::Power(mynbkg->getError()/nbkg,2) ); } TCut mycut = cut + massCut; ana->applyCuts(&mycut); TCanvas * cc = new TCanvas(); GetFrame(MM,Mmodel,data,"-nochi2-plotAllComp",30,NULL,0,"cos#theta_{#Lambda}")->Draw(); cc->Print("M_"+name+"_"+q2name+".pdf"); if(*outnsig) *outnsig = nsig; return ana->GetDataSet("-recalc"); }
// internal routine to run the inverter HypoTestInverterResult * RooStats::HypoTestInvTool::RunInverter(RooWorkspace * w, const char * modelSBName, const char * modelBName, const char * dataName, int type, int testStatType, bool useCLs, int npoints, double poimin, double poimax, int ntoys, bool useNumberCounting, const char * nuisPriorName ){ std::cout << "Running HypoTestInverter on the workspace " << w->GetName() << std::endl; w->Print(); RooAbsData * data = w->data(dataName); if (!data) { Error("StandardHypoTestDemo","Not existing data %s",dataName); return 0; } else std::cout << "Using data set " << dataName << std::endl; if (mUseVectorStore) { RooAbsData::setDefaultStorageType(RooAbsData::Vector); data->convertToVectorStore() ; } // get models from WS // get the modelConfig out of the file ModelConfig* bModel = (ModelConfig*) w->obj(modelBName); ModelConfig* sbModel = (ModelConfig*) w->obj(modelSBName); if (!sbModel) { Error("StandardHypoTestDemo","Not existing ModelConfig %s",modelSBName); return 0; } // check the model if (!sbModel->GetPdf()) { Error("StandardHypoTestDemo","Model %s has no pdf ",modelSBName); return 0; } if (!sbModel->GetParametersOfInterest()) { Error("StandardHypoTestDemo","Model %s has no poi ",modelSBName); return 0; } if (!sbModel->GetObservables()) { Error("StandardHypoTestInvDemo","Model %s has no observables ",modelSBName); return 0; } if (!sbModel->GetSnapshot() ) { Info("StandardHypoTestInvDemo","Model %s has no snapshot - make one using model poi",modelSBName); sbModel->SetSnapshot( *sbModel->GetParametersOfInterest() ); } // case of no systematics // remove nuisance parameters from model if (noSystematics) { const RooArgSet * nuisPar = sbModel->GetNuisanceParameters(); if (nuisPar && nuisPar->getSize() > 0) { std::cout << "StandardHypoTestInvDemo" << " - Switch off all systematics by setting them constant to their initial values" << std::endl; RooStats::SetAllConstant(*nuisPar); } if (bModel) { const RooArgSet * bnuisPar = bModel->GetNuisanceParameters(); if (bnuisPar) RooStats::SetAllConstant(*bnuisPar); } } if (!bModel || bModel == sbModel) { Info("StandardHypoTestInvDemo","The background model %s does not exist",modelBName); Info("StandardHypoTestInvDemo","Copy it from ModelConfig %s and set POI to zero",modelSBName); bModel = (ModelConfig*) sbModel->Clone(); bModel->SetName(TString(modelSBName)+TString("_with_poi_0")); RooRealVar * var = dynamic_cast<RooRealVar*>(bModel->GetParametersOfInterest()->first()); if (!var) return 0; double oldval = var->getVal(); var->setVal(0); bModel->SetSnapshot( RooArgSet(*var) ); var->setVal(oldval); } else { if (!bModel->GetSnapshot() ) { Info("StandardHypoTestInvDemo","Model %s has no snapshot - make one using model poi and 0 values ",modelBName); RooRealVar * var = dynamic_cast<RooRealVar*>(bModel->GetParametersOfInterest()->first()); if (var) { double oldval = var->getVal(); var->setVal(0); bModel->SetSnapshot( RooArgSet(*var) ); var->setVal(oldval); } else { Error("StandardHypoTestInvDemo","Model %s has no valid poi",modelBName); return 0; } } } // check model has global observables when there are nuisance pdf // for the hybrid case the globobs are not needed if (type != 1 ) { bool hasNuisParam = (sbModel->GetNuisanceParameters() && sbModel->GetNuisanceParameters()->getSize() > 0); bool hasGlobalObs = (sbModel->GetGlobalObservables() && sbModel->GetGlobalObservables()->getSize() > 0); if (hasNuisParam && !hasGlobalObs ) { // try to see if model has nuisance parameters first RooAbsPdf * constrPdf = RooStats::MakeNuisancePdf(*sbModel,"nuisanceConstraintPdf_sbmodel"); if (constrPdf) { Warning("StandardHypoTestInvDemo","Model %s has nuisance parameters but no global observables associated",sbModel->GetName()); Warning("StandardHypoTestInvDemo","\tThe effect of the nuisance parameters will not be treated correctly "); } } } // run first a data fit const RooArgSet * poiSet = sbModel->GetParametersOfInterest(); RooRealVar *poi = (RooRealVar*)poiSet->first(); std::cout << "StandardHypoTestInvDemo : POI initial value: " << poi->GetName() << " = " << poi->getVal() << std::endl; // fit the data first (need to use constraint ) TStopwatch tw; bool doFit = initialFit; if (testStatType == 0 && initialFit == -1) doFit = false; // case of LEP test statistic if (type == 3 && initialFit == -1) doFit = false; // case of Asymptoticcalculator with nominal Asimov double poihat = 0; if (minimizerType.size()==0) minimizerType = ROOT::Math::MinimizerOptions::DefaultMinimizerType(); else ROOT::Math::MinimizerOptions::SetDefaultMinimizer(minimizerType.c_str()); Info("StandardHypoTestInvDemo","Using %s as minimizer for computing the test statistic", ROOT::Math::MinimizerOptions::DefaultMinimizerType().c_str() ); if (doFit) { // do the fit : By doing a fit the POI snapshot (for S+B) is set to the fit value // and the nuisance parameters nominal values will be set to the fit value. // This is relevant when using LEP test statistics Info( "StandardHypoTestInvDemo"," Doing a first fit to the observed data "); RooArgSet constrainParams; if (sbModel->GetNuisanceParameters() ) constrainParams.add(*sbModel->GetNuisanceParameters()); RooStats::RemoveConstantParameters(&constrainParams); tw.Start(); RooFitResult * fitres = sbModel->GetPdf()->fitTo(*data,InitialHesse(false), Hesse(false), Minimizer(minimizerType.c_str(),"Migrad"), Strategy(0), PrintLevel(mPrintLevel), Constrain(constrainParams), Save(true) ); if (fitres->status() != 0) { Warning("StandardHypoTestInvDemo","Fit to the model failed - try with strategy 1 and perform first an Hesse computation"); fitres = sbModel->GetPdf()->fitTo(*data,InitialHesse(true), Hesse(false),Minimizer(minimizerType.c_str(),"Migrad"), Strategy(1), PrintLevel(mPrintLevel+1), Constrain(constrainParams), Save(true) ); } if (fitres->status() != 0) Warning("StandardHypoTestInvDemo"," Fit still failed - continue anyway....."); poihat = poi->getVal(); std::cout << "StandardHypoTestInvDemo - Best Fit value : " << poi->GetName() << " = " << poihat << " +/- " << poi->getError() << std::endl; std::cout << "Time for fitting : "; tw.Print(); //save best fit value in the poi snapshot sbModel->SetSnapshot(*sbModel->GetParametersOfInterest()); std::cout << "StandardHypoTestInvo: snapshot of S+B Model " << sbModel->GetName() << " is set to the best fit value" << std::endl; } // print a message in case of LEP test statistics because it affects result by doing or not doing a fit if (testStatType == 0) { if (!doFit) Info("StandardHypoTestInvDemo","Using LEP test statistic - an initial fit is not done and the TS will use the nuisances at the model value"); else Info("StandardHypoTestInvDemo","Using LEP test statistic - an initial fit has been done and the TS will use the nuisances at the best fit value"); } // build test statistics and hypotest calculators for running the inverter SimpleLikelihoodRatioTestStat slrts(*sbModel->GetPdf(),*bModel->GetPdf()); // null parameters must includes snapshot of poi plus the nuisance values RooArgSet nullParams(*sbModel->GetSnapshot()); if (sbModel->GetNuisanceParameters()) nullParams.add(*sbModel->GetNuisanceParameters()); if (sbModel->GetSnapshot()) slrts.SetNullParameters(nullParams); RooArgSet altParams(*bModel->GetSnapshot()); if (bModel->GetNuisanceParameters()) altParams.add(*bModel->GetNuisanceParameters()); if (bModel->GetSnapshot()) slrts.SetAltParameters(altParams); // ratio of profile likelihood - need to pass snapshot for the alt RatioOfProfiledLikelihoodsTestStat ropl(*sbModel->GetPdf(), *bModel->GetPdf(), bModel->GetSnapshot()); ropl.SetSubtractMLE(false); if (testStatType == 11) ropl.SetSubtractMLE(true); ropl.SetPrintLevel(mPrintLevel); ropl.SetMinimizer(minimizerType.c_str()); ProfileLikelihoodTestStat profll(*sbModel->GetPdf()); if (testStatType == 3) profll.SetOneSided(true); if (testStatType == 4) profll.SetSigned(true); profll.SetMinimizer(minimizerType.c_str()); profll.SetPrintLevel(mPrintLevel); profll.SetReuseNLL(mOptimize); slrts.SetReuseNLL(mOptimize); ropl.SetReuseNLL(mOptimize); if (mOptimize) { profll.SetStrategy(0); ropl.SetStrategy(0); ROOT::Math::MinimizerOptions::SetDefaultStrategy(0); } if (mMaxPoi > 0) poi->setMax(mMaxPoi); // increase limit MaxLikelihoodEstimateTestStat maxll(*sbModel->GetPdf(),*poi); NumEventsTestStat nevtts; AsymptoticCalculator::SetPrintLevel(mPrintLevel); // create the HypoTest calculator class HypoTestCalculatorGeneric * hc = 0; if (type == 0) hc = new FrequentistCalculator(*data, *bModel, *sbModel); else if (type == 1) hc = new HybridCalculator(*data, *bModel, *sbModel); // else if (type == 2 ) hc = new AsymptoticCalculator(*data, *bModel, *sbModel, false, mAsimovBins); // else if (type == 3 ) hc = new AsymptoticCalculator(*data, *bModel, *sbModel, true, mAsimovBins); // for using Asimov data generated with nominal values else if (type == 2 ) hc = new AsymptoticCalculator(*data, *bModel, *sbModel, false ); else if (type == 3 ) hc = new AsymptoticCalculator(*data, *bModel, *sbModel, true ); // for using Asimov data generated with nominal values else { Error("StandardHypoTestInvDemo","Invalid - calculator type = %d supported values are only :\n\t\t\t 0 (Frequentist) , 1 (Hybrid) , 2 (Asymptotic) ",type); return 0; } // set the test statistic TestStatistic * testStat = 0; if (testStatType == 0) testStat = &slrts; if (testStatType == 1 || testStatType == 11) testStat = &ropl; if (testStatType == 2 || testStatType == 3 || testStatType == 4) testStat = &profll; if (testStatType == 5) testStat = &maxll; if (testStatType == 6) testStat = &nevtts; if (testStat == 0) { Error("StandardHypoTestInvDemo","Invalid - test statistic type = %d supported values are only :\n\t\t\t 0 (SLR) , 1 (Tevatron) , 2 (PLR), 3 (PLR1), 4(MLE)",testStatType); return 0; } ToyMCSampler *toymcs = (ToyMCSampler*)hc->GetTestStatSampler(); if (toymcs && (type == 0 || type == 1) ) { // look if pdf is number counting or extended if (sbModel->GetPdf()->canBeExtended() ) { if (useNumberCounting) Warning("StandardHypoTestInvDemo","Pdf is extended: but number counting flag is set: ignore it "); } else { // for not extended pdf if (!useNumberCounting ) { int nEvents = data->numEntries(); Info("StandardHypoTestInvDemo","Pdf is not extended: number of events to generate taken from observed data set is %d",nEvents); toymcs->SetNEventsPerToy(nEvents); } else { Info("StandardHypoTestInvDemo","using a number counting pdf"); toymcs->SetNEventsPerToy(1); } } toymcs->SetTestStatistic(testStat); if (data->isWeighted() && !mGenerateBinned) { Info("StandardHypoTestInvDemo","Data set is weighted, nentries = %d and sum of weights = %8.1f but toy generation is unbinned - it would be faster to set mGenerateBinned to true\n",data->numEntries(), data->sumEntries()); } toymcs->SetGenerateBinned(mGenerateBinned); toymcs->SetUseMultiGen(mOptimize); if (mGenerateBinned && sbModel->GetObservables()->getSize() > 2) { Warning("StandardHypoTestInvDemo","generate binned is activated but the number of ovservable is %d. Too much memory could be needed for allocating all the bins",sbModel->GetObservables()->getSize() ); } // set the random seed if needed if (mRandomSeed >= 0) RooRandom::randomGenerator()->SetSeed(mRandomSeed); } // specify if need to re-use same toys if (reuseAltToys) { hc->UseSameAltToys(); } if (type == 1) { HybridCalculator *hhc = dynamic_cast<HybridCalculator*> (hc); assert(hhc); hhc->SetToys(ntoys,ntoys/mNToysRatio); // can use less ntoys for b hypothesis // remove global observables from ModelConfig (this is probably not needed anymore in 5.32) bModel->SetGlobalObservables(RooArgSet() ); sbModel->SetGlobalObservables(RooArgSet() ); // check for nuisance prior pdf in case of nuisance parameters if (bModel->GetNuisanceParameters() || sbModel->GetNuisanceParameters() ) { // fix for using multigen (does not work in this case) toymcs->SetUseMultiGen(false); ToyMCSampler::SetAlwaysUseMultiGen(false); RooAbsPdf * nuisPdf = 0; if (nuisPriorName) nuisPdf = w->pdf(nuisPriorName); // use prior defined first in bModel (then in SbModel) if (!nuisPdf) { Info("StandardHypoTestInvDemo","No nuisance pdf given for the HybridCalculator - try to deduce pdf from the model"); if (bModel->GetPdf() && bModel->GetObservables() ) nuisPdf = RooStats::MakeNuisancePdf(*bModel,"nuisancePdf_bmodel"); else nuisPdf = RooStats::MakeNuisancePdf(*sbModel,"nuisancePdf_sbmodel"); } if (!nuisPdf ) { if (bModel->GetPriorPdf()) { nuisPdf = bModel->GetPriorPdf(); Info("StandardHypoTestInvDemo","No nuisance pdf given - try to use %s that is defined as a prior pdf in the B model",nuisPdf->GetName()); } else { Error("StandardHypoTestInvDemo","Cannnot run Hybrid calculator because no prior on the nuisance parameter is specified or can be derived"); return 0; } } assert(nuisPdf); Info("StandardHypoTestInvDemo","Using as nuisance Pdf ... " ); nuisPdf->Print(); const RooArgSet * nuisParams = (bModel->GetNuisanceParameters() ) ? bModel->GetNuisanceParameters() : sbModel->GetNuisanceParameters(); RooArgSet * np = nuisPdf->getObservables(*nuisParams); if (np->getSize() == 0) { Warning("StandardHypoTestInvDemo","Prior nuisance does not depend on nuisance parameters. They will be smeared in their full range"); } delete np; hhc->ForcePriorNuisanceAlt(*nuisPdf); hhc->ForcePriorNuisanceNull(*nuisPdf); } } else if (type == 2 || type == 3) { if (testStatType == 3) ((AsymptoticCalculator*) hc)->SetOneSided(true); if (testStatType != 2 && testStatType != 3) Warning("StandardHypoTestInvDemo","Only the PL test statistic can be used with AsymptoticCalculator - use by default a two-sided PL"); } else if (type == 0 || type == 1) ((FrequentistCalculator*) hc)->SetToys(ntoys,ntoys/mNToysRatio); // Get the result RooMsgService::instance().getStream(1).removeTopic(RooFit::NumIntegration); HypoTestInverter calc(*hc); calc.SetConfidenceLevel(0.95); calc.UseCLs(useCLs); calc.SetVerbose(true); // can speed up using proof-lite if (mUseProof && mNWorkers > 1) { ProofConfig pc(*w, mNWorkers, "", kFALSE); toymcs->SetProofConfig(&pc); // enable proof } if (npoints > 0) { if (poimin > poimax) { // if no min/max given scan between MLE and +4 sigma poimin = int(poihat); poimax = int(poihat + 4 * poi->getError()); } std::cout << "Doing a fixed scan in interval : " << poimin << " , " << poimax << std::endl; calc.SetFixedScan(npoints,poimin,poimax); } else { //poi->setMax(10*int( (poihat+ 10 *poi->getError() )/10 ) ); std::cout << "Doing an automatic scan in interval : " << poi->getMin() << " , " << poi->getMax() << std::endl; } tw.Start(); HypoTestInverterResult * r = calc.GetInterval(); std::cout << "Time to perform limit scan \n"; tw.Print(); if (mRebuild) { calc.SetCloseProof(1); tw.Start(); SamplingDistribution * limDist = calc.GetUpperLimitDistribution(true,mNToyToRebuild); std::cout << "Time to rebuild distributions " << std::endl; tw.Print(); if (limDist) { std::cout << "expected up limit " << limDist->InverseCDF(0.5) << " +/- " << limDist->InverseCDF(0.16) << " " << limDist->InverseCDF(0.84) << "\n"; //update r to a new updated result object containing the rebuilt expected p-values distributions // (it will not recompute the expected limit) if (r) delete r; // need to delete previous object since GetInterval will return a cloned copy r = calc.GetInterval(); } else std::cout << "ERROR : failed to re-build distributions " << std::endl; } return r; }
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; }
int main(int argc, char **argv) { bool printSw = true; //TString massModel = "Gauss-m[5622]"; string massModel = "DCB-m[5622]"; TString effbase = "/afs/cern.ch/user/p/pluca/work/Lb/Lmumu/results/"; bool printeff = false; TString dodata = "data"; bool fitsingle = false; TString wstr = "physRate_polp006"; TString decayToDo = "Lb2Lmumu"; if(dodata=="genMC") wstr += "_noDecay"; gROOT->ProcessLine(".x lhcbStyle.C"); RooRealVar * cosThetaL = new RooRealVar("cosThetaL","cosThetaL",0.,-1.,1.); RooRealVar * cosThetaB = new RooRealVar("cosThetaB","cosThetaB",0.,-1.,1.); RooRealVar * nsig_sw = new RooRealVar("nsig_sw","nsig_sw",1,-1.e6,1.e6); RooRealVar * MCweight = new RooRealVar(wstr,wstr,1.,-1.e10,1.e10); RooRealVar * MM = new RooRealVar("Lb_MassConsLambda","Lb_MassConsLambda",5620.,5500.,5900.); TString datafilename = "/afs/cern.ch/user/p/pluca/work/Lb/Lmumu/candLb.root"; if(dodata=="MC") datafilename = "/afs/cern.ch/user/p/pluca/work/Lb/Lmumu/candLb_MC.root"; if(dodata=="genMC") datafilename = "/afs/cern.ch/work/p/pluca/weighted/Lmumu/"+(string)decayToDo+"_geomMC_Pythia8_NBweighted.root"; TreeReader * data; if(dodata!="genMC") data = new TreeReader("cand"+decayToDo); else data = new TreeReader("MCtree"); data->AddFile(datafilename); TFile * histFile = new TFile("Afb_hist.root","recreate"); RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR); int nbins = 1;//CutsDef::nq2bins; double q2min[] = {15.,11.0,15,16,18};//&CutsDef::q2min_highfirst[0]; double q2max[] = {20.,12.5,16,18,20};//&CutsDef::q2max_highfirst[0]; //int nbins = CutsDef::nq2bins //double *q2min = &CutsDef::q2min[0]; //double *q2max = &CutsDef::q2max[0]; TGraphErrors * Afb_vs_q2 = new TGraphErrors(); TGraphErrors * AfbB_vs_q2 = new TGraphErrors(); TGraphErrors * fL_vs_q2 = new TGraphErrors(); TCanvas * ceff = new TCanvas(); RooCategory * samples = new RooCategory("samples","samples"); samples->defineType("DD"); samples->defineType("LL"); RooRealVar * afb = new RooRealVar("afb","afb",0.,-100,100); RooRealVar * fL = new RooRealVar("fL","fL",0.7,-1.,10.); //RooRealVar * afb = new RooRealVar("afb","afb",0.,-1.,1.); //RooRealVar * fL = new RooRealVar("fL","fL",0.7,0.,1.); RooRealVar * origafb = new RooRealVar("afb","afb",0.,-1.,1.); RooRealVar * origfL = new RooRealVar("fL","fL",0.7,-1.,10.); TString afbLpdf = "((3./8.)*(1.-fL)*(1 + TMath::Power(cosThetaL,2)) + afb*cosThetaL + (3./4.)*fL*(1 - TMath::Power(cosThetaL,2)))"; RooRealVar * afbB = new RooRealVar("afbB","afbB",0.,-100,100); //RooRealVar * afbB = new RooRealVar("afbB","afbB",0.,-1.,1.); RooRealVar * origafbB = new RooRealVar("afbB","afbB",0.,-1.,1.); TString afbBpdf = "(1 + 2*afbB*cosThetaB)"; vector< vector< double > > afb_errs, afbB_errs, fL_errs; TList * LLlist = new TList, * DDlist = new TList; TCanvas * cDD = new TCanvas(); TCanvas * cLL = new TCanvas(); TCanvas * cDDB = new TCanvas(); TCanvas * cLLB = new TCanvas(); for(int i = 0; i < nbins; i++) { //if(q2min[i] < 8) continue; TString q2name = ((TString)Form("q2_%4.2f_%4.2f",q2min[i],q2max[i])).ReplaceAll(".",""); TString curq2cut = Form("TMath::Power(J_psi_1S_MM/1000,2) >= %e && TMath::Power(J_psi_1S_MM/1000,2) < %e",q2min[i],q2max[i]); //TString curq2cut = Form("TMath::Power(J_psi_1S_MM/1000,2) >= %e && TMath::Power(J_psi_1S_MM/1000,2) < %e && (Lb_MassConsLambda > 5680 || Lb_MassConsLambda < 5590)",q2min[i],q2max[i]); cout << "------------------- q2 bin: " << q2min[i] << " - " << q2max[i] << " -----------------------" << endl; TFile * effFile = NULL; TH1F * effDD = NULL, * effLL = NULL, * effLLB = NULL, * effDDB = NULL; if(q2min[i] == 15 && q2max[i] == 20) { effFile = TFile::Open(effbase+"LbeffvscosThetaL_DD.root"); effDD = (TH1F *)effFile->Get("htoteff"); effFile = TFile::Open(effbase+"LbeffvscosThetaL_LL.root"); effLL = (TH1F *)effFile->Get("htoteff"); effFile = TFile::Open(effbase+"LbeffvscosThetaB_DD.root"); effDDB = (TH1F *)effFile->Get("htot_nodet_eff"); effFile = TFile::Open(effbase+"LbeffvscosThetaB_LL.root"); effLLB = (TH1F *)effFile->Get("htot_nodet_eff"); } else { effFile = TFile::Open(effbase+"Lbeff2D_cosThetaL_vs_q2_DD.root"); TH2F * effDD2D = (TH2F *)effFile->Get("htot_eff"); effDD = (TH1F*)GetSliceX(effDD2D,(q2max[i]+q2min[i])/2.); effFile = TFile::Open(effbase+"Lbeff2D_cosThetaL_vs_q2_LL.root"); TH2F * effLL2D = (TH2F *)effFile->Get("htot_eff"); effLL = (TH1F*)GetSliceX(effLL2D,(q2max[i]+q2min[i])/2.); effFile = TFile::Open(effbase+"Lbeff2D_cosThetaB_vs_q2_DD.root"); TH2F * effDDB2D = (TH2F *)effFile->Get("hupper_eff"); effDDB = (TH1F*)GetSliceX(effDDB2D,(q2max[i]+q2min[i])/2.); effFile = TFile::Open(effbase+"Lbeff2D_cosThetaB_vs_q2_LL.root"); TH2F * effLLB2D = (TH2F *)effFile->Get("hupper_eff"); effLLB = (TH1F*)GetSliceX(effLLB2D,(q2max[i]+q2min[i])/2.); } ceff->cd(); /** FIT EFFICIENCY **/ RooDataHist * hLL = new RooDataHist("hLL","hLL",*cosThetaL,effLL); RooDataHist * hDD = new RooDataHist("hDD","hDD",*cosThetaL,effDD); RooRealVar * c1LL = new RooRealVar("c1LL","",0.,-1.,1); RooRealVar * c1DD = new RooRealVar("c1DD","",0.,-1.,1); RooRealVar * c2LL = new RooRealVar("c2LL","",0.,-1.,1); RooRealVar * c2DD = new RooRealVar("c2DD","",0.,-1.,1); TString effLLstr = "(1 + c1LL*cosThetaL + c2LL*TMath::Power(cosThetaL,2))"; TString effDDstr = "(1 + c1DD*cosThetaL + c2DD*TMath::Power(cosThetaL,2))"; RooAbsPdf * effLLpdf = new RooGenericPdf("effLLpdf", "", effLLstr, RooArgSet(*cosThetaL, *c1LL, *c2LL)); RooAbsPdf * effDDpdf = new RooGenericPdf("effDDpdf", "", effDDstr, RooArgSet(*cosThetaL, *c1DD, *c2DD)); effLLpdf->fitTo(*hLL,PrintLevel(-1)); effDDpdf->fitTo(*hDD,PrintLevel(-1)); fixParams(effLLpdf,cosThetaL); fixParams(effDDpdf,cosThetaL); RooDataHist * hLLB = new RooDataHist("hLLB","hLLB",*cosThetaB,effLLB); RooDataHist * hDDB = new RooDataHist("hDDB","hDDB",*cosThetaB,effDDB); RooRealVar * cB1LL = new RooRealVar("cB1LL","",0,-1.,1); RooRealVar * cB1DD = new RooRealVar("cB1DD","",0,-1.,1); RooRealVar * cB2LL = new RooRealVar("cB2LL","",0,-1.,1); RooRealVar * cB2DD = new RooRealVar("cB2DD","",0,-1.,1); TString effLLBstr = "(1 + cB1LL*cosThetaB + cB2LL*TMath::Power(cosThetaB,2))"; TString effDDBstr = "(1 + cB1DD*cosThetaB + cB2DD*TMath::Power(cosThetaB,2))"; RooAbsPdf * effLLpdfB = new RooGenericPdf("effLLpdfB", "", effLLBstr, RooArgSet(*cosThetaB, *cB1LL, *cB2LL)); RooAbsPdf * effDDpdfB = new RooGenericPdf("effDDpdfB", "", effDDBstr, RooArgSet(*cosThetaB, *cB1DD, *cB2DD)); effLLpdfB->fitTo(*hLLB,PrintLevel(-1)); effDDpdfB->fitTo(*hDDB,PrintLevel(-1)); fixParams(effLLpdfB,cosThetaB); fixParams(effDDpdfB,cosThetaB); //cout << q2min[i] << " - " << q2max[i] << " LL cosThetaL -> " << c1LL->getVal() << " " << c2LL->getVal() << endl; //cout << q2min[i] << " - " << q2max[i] << " DD cosThetaL -> " << c1DD->getVal() << " " << c2DD->getVal() << endl; //cout << q2min[i] << " - " << q2max[i] << " LL cosThetaB -> " << cB1LL->getVal() << " " << cB2LL->getVal() << endl; //cout << q2min[i] << " - " << q2max[i] << " DD cosThetaB -> " << cB1DD->getVal() << " " << cB2DD->getVal() << endl; if(printeff) { GetFrame(cosThetaL, hLL,effLLpdf,"-nochi2",0,NULL,0,"cos#theta_{l}","Tot. eff.")->Draw(); ceff->Print("DDeffFit"+q2name+".pdf"); GetFrame(cosThetaL, hDD,effDDpdf,"-nochi2",0,NULL,0,"cos#theta_{l}","Tot. eff.")->Draw(); ceff->Print("LLeffFit"+q2name+".pdf"); GetFrame(cosThetaB, hLLB,effLLpdfB,"-nochi2",0,NULL,0,"cos#theta_{#Lambda}","Tot. eff.")->Draw(); ceff->Print("DDeffFitB"+q2name+".pdf"); GetFrame(cosThetaB, hDDB,effDDpdfB,"-nochi2",0,NULL,0,"cos#theta_{#Lambda}","Tot. eff.")->Draw(); ceff->Print("LLeffFitB"+q2name+".pdf"); } /** FIT AFB **/ afb->setVal(0); afbB->setVal(0); fL->setVal(0.7); TString LLnorm = "1./( 1. + (2./3.)*afb*c1LL + (2./5.)*c2LL - (1./5.)*c2LL*fL )*"+effLLstr; TString DDnorm = "1./( 1. + (2./3.)*afb*c1DD + (2./5.)*c2DD - (1./5.)*c2DD*fL )*"+effDDstr; RooAbsPdf * corrPdfLL = new RooGenericPdf(Form("corrPdfLL_%i",i),LLnorm+"*"+afbLpdf,RooArgSet(*cosThetaL, *afb, *fL, *c1LL, *c2LL) ); RooAbsPdf * corrPdfDD = new RooGenericPdf(Form("corrPdfDD_%i",i),DDnorm+"*"+afbLpdf,RooArgSet(*cosThetaL, *afb, *fL, *c1DD, *c2DD) ); TString LLnormB = "1./( (2./3.)*( 2*afbB*cB1LL + cB2LL + 3.) )*"+effLLBstr; TString DDnormB = "1./( (2./3.)*( 2*afbB*cB1DD + cB2DD + 3.) )*"+effDDBstr; RooAbsPdf * corrPdfLLB = new RooGenericPdf(Form("corrPdfLLB_%i",i),LLnormB+"*"+afbBpdf,RooArgSet(*cosThetaB, *afbB, *cB1LL, *cB2LL) ); RooAbsPdf * corrPdfDDB = new RooGenericPdf(Form("corrPdfDDB_%i",i),DDnormB+"*"+afbBpdf,RooArgSet(*cosThetaB, *afbB, *cB1DD, *cB2DD) ); TCut cutLL = CutsDef::LLcut + (TCut)curq2cut; TCut cutDD = CutsDef::DDcut + (TCut)curq2cut; if(dodata=="genMC") { corrPdfLLB = new RooGenericPdf("corrPdfLL",afbBpdf,RooArgSet(*cosThetaB, *afbB, *cB1LL, *cB2LL) ); corrPdfDDB = new RooGenericPdf("corrPdfDD",afbBpdf,RooArgSet(*cosThetaB, *afbB, *cB1DD, *cB2DD) ); corrPdfLL = new RooGenericPdf("corrPdfLL",afbLpdf,RooArgSet(*cosThetaL, *afb, *fL, *c1LL, *c2LL) ); corrPdfDD = new RooGenericPdf("corrPdfDD",afbLpdf,RooArgSet(*cosThetaL, *afb, *fL, *c1DD, *c2DD) ); cutLL = (TCut)curq2cut; cutDD = (TCut)curq2cut; } Analysis * anaLL = new Analysis(Form("LL_mass_%i",i),"Lb",data,&cutLL,MM); anaLL->AddVariable(cosThetaL); anaLL->AddVariable(cosThetaB); anaLL->AddVariable("J_psi_1S_MM"); if(dodata!="data") anaLL->SetWeight(wstr); RooDataSet * dataLL = anaLL->GetDataSet("-recalc-docuts"); Analysis * anaDD = new Analysis(Form("DD_mass_%i",i),"Lb",data,&cutDD,MM); anaDD->AddVariable(cosThetaL); anaDD->AddVariable(cosThetaB); anaDD->AddVariable("J_psi_1S_MM"); if(dodata!="data") anaDD->SetWeight(wstr); RooDataSet * dataDD = anaDD->GetDataSet("-recalc-docuts"); RooDataSet * sdataDD, * sdataLL; if(dodata=="data") { sdataLL = anaLL->CalcSweight("",massModel.c_str(),"Exp"); if(printSw) { GetFrame(MM,NULL,sdataLL,"-nochi2",30,NULL,0,"M(#Lambda#mu#mu) (MeV/c^{2})")->Draw(); ceff->Print("Mass_LL_sWeighted"+q2name+".pdf"); GetFrame(cosThetaL,NULL,sdataLL,"-nochi2",6,NULL,0,"cos#theta_{l}")->Draw(); ceff->Print("cosThetaL_LL_sWeighted"+q2name+".pdf"); GetFrame(cosThetaL,NULL,dataLL,"-nochi2",6,NULL,0,"cos#theta_{l}")->Draw(); ceff->Print("cosThetaL_LL_"+q2name+".pdf"); } sdataDD = anaDD->CalcSweight("",massModel.c_str(),"Exp"); if(printSw) { GetFrame(MM,NULL,sdataDD,"-nochi2",30,NULL,0,"M(#Lambda#mu#mu) (MeV/c^{2})")->Draw(); ceff->Print("Mass_DD_sWeighted"+q2name+".pdf"); GetFrame(cosThetaL,NULL,sdataDD,"-nochi2",10,NULL,0,"cos#theta_{l}")->Draw(); ceff->Print("cosThetaL_DD_sWeighted"+q2name+".pdf"); GetFrame(cosThetaL,NULL,dataDD,"-nochi2",10,NULL,0,"cos#theta_{l}")->Draw(); ceff->Print("cosThetaL_DD_"+q2name+".pdf"); } } else { sdataLL = dataLL; sdataDD = dataDD; } histFile->cd(); TTree * LLTree = (TTree*)sdataLL->tree(); LLTree->SetName(Form("treeLL_%i",i)); LLlist->Add(LLTree); TTree * DDTree = (TTree*)sdataDD->tree(); DDTree->SetName(Form("treeDD_%i",i)); DDlist->Add(DDTree); // CREATE COMBINED DATASET RooDataSet * combData; if(dodata=="data") combData = new RooDataSet(Form("combData_%i",i),"combined data",RooArgSet(*cosThetaL,*cosThetaB,*nsig_sw),Index(*samples),Import("DD",*sdataDD),Import("LL",*sdataLL),WeightVar("nsig_sw")); else combData = new RooDataSet(Form("combData_%i",i),"combined data",RooArgSet(*cosThetaL,*cosThetaB,*MCweight),Index(*samples),Import("DD",*sdataDD),Import("LL",*sdataLL),WeightVar(wstr)); // FIT COS LEPTON RooSimultaneous * combModel = new RooSimultaneous(Form("combModel_%i",i),"",*samples); combModel->addPdf(*corrPdfLL,"LL"); combModel->addPdf(*corrPdfDD,"DD"); combModel->fitTo(*combData,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE)); if(fitsingle) corrPdfLL->fitTo(*sdataLL,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE)); GetFrame(cosThetaL,corrPdfLL,sdataLL,"-sumW2err-nochi2-noCost",6,NULL,0,"cos#theta_{l}")->Draw(); ceff->Print("Afb_LL_"+q2name+".pdf"); if(fitsingle) corrPdfDD->fitTo(*sdataDD,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE)); GetFrame(cosThetaL,corrPdfDD,sdataDD,"-sumW2err-nochi2-noCost",10,NULL,0,"cos#theta_{l}")->Draw(); ceff->Print("Afb_DD_"+q2name+".pdf"); Afb_vs_q2->SetPoint(i,(q2max[i] + q2min[i])/2.,afb->getVal()); Afb_vs_q2->SetPointError(i,(q2max[i] - q2min[i])/2.,afb->getError()); fL_vs_q2->SetPoint(i,(q2max[i] + q2min[i])/2.,fL->getVal()); fL_vs_q2->SetPointError(i,(q2max[i] - q2min[i])/2.,fL->getError()); // FIT COS HADRON RooSimultaneous * combModelB = new RooSimultaneous(Form("combModelB_%i",i),"",*samples); combModelB->addPdf(*corrPdfLLB,"LL"); combModelB->addPdf(*corrPdfDDB,"DD"); combModelB->fitTo(*combData,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE)); if(fitsingle) corrPdfLLB->fitTo(*sdataLL,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE)); GetFrame(cosThetaB,corrPdfLLB,sdataLL,"-sumW2err-nochi2-noCost",6,NULL,0,"cos#theta_{#Lambda}")->Draw(); ceff->Print("AfbB_LL_"+q2name+".pdf"); if(fitsingle) corrPdfDDB->fitTo(*sdataDD,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE)); GetFrame(cosThetaB,corrPdfDDB,sdataDD,"-sumW2err-nochi2-noCost",10,NULL,0,"cos#theta_{#Lambda}")->Draw(); ceff->Print("AfbB_DD_"+q2name+".pdf"); AfbB_vs_q2->SetPoint(i,(q2max[i] + q2min[i])/2.,afbB->getVal()); AfbB_vs_q2->SetPointError(i,(q2max[i] - q2min[i])/2.,afbB->getError()); cout << endl << fixed << setprecision(6) << "AfbB = " << afbB->getVal() << " +/- " << afbB->getError() << endl; cout << "Afb = " << afb->getVal() << " +/- " << afb->getError() << endl; cout << "fL = " << fL->getVal() << " +/- " << fL->getError() << endl; cout << endl; cout << "------------------------ FELDMAN AND COUSINS ------------------------" << endl; vector < RooDataSet * > datas; vector < RooAbsPdf * > pdfs, pdfsB; vector < TString > cat; cat.push_back("LL"); cat.push_back("DD"); datas.push_back(sdataLL); datas.push_back(sdataDD); RooArgSet * origPars = new RooArgSet(); origPars->add(*origafb); origPars->add(*origfL); pdfs.push_back(corrPdfLL); pdfs.push_back(corrPdfDD); vector< double > afb_err, afbB_err, fL_err; /* double fLval = fL->getVal(), fLerr = fL->getError(); FeldmanCousins * FC = new FeldmanCousins(q2name,cat,datas,pdfs,cosThetaL,afb,"nsig_sw"); //FC->SetNPointsToScan(20); //FC->SetNExp(1000); if(q2min[i]==18) afb_err = FC->ExtractLimits(origPars,-0.3,0.3); else if( (afb->getVal()-1.4*afb->getError()) > -1 && (afb->getVal()+1.4*afb->getError()) < 1 ) afb_err = FC->ExtractLimits(origPars,afb->getVal()-1.4*afb->getError(),afb->getVal()+1.4*afb->getError()); else afb_err = FC->ExtractLimits(origPars,-0.4,0.4); //FeldmanCousins * FCfL = new FeldmanCousins(q2name,cat,datas,pdfs,cosThetaL,fL,"nsig_sw"); //if(q2min[i]==11) fL_err = FCfL->ExtractLimits(origPars,0.,0.6); //else if (q2min[i]==18) fL_err = FCfL->ExtractLimits(origPars,0.75,0.992); //( (fLval-1.3*fLerr) > 0 && (fLval+1.3*fLerr) <= 1 ) //else fL_err = FCfL->ExtractLimits(origPars,fLval-1.3*fLerr,fLval+1.3*fLerr); afb_errs.push_back(afb_err); //fL_errs.push_back(fL_err); RooArgSet * origParsB = new RooArgSet(); origParsB->add(*origafbB); pdfsB.push_back(corrPdfLLB); pdfsB.push_back(corrPdfDDB); FeldmanCousins * FCB = new FeldmanCousins(q2name,cat,datas,pdfsB,cosThetaB,afbB,"nsig_sw"); if( (afbB->getVal()-1.5*afbB->getError()) > -1 && (afbB->getVal()+1.5*afbB->getError()) < 1 ) afbB_err = FCB->ExtractLimits(origParsB,afbB->getVal()-1.5*afbB->getError(),afbB->getVal()+1.5*afbB->getError()); else afbB_err = FCB->ExtractLimits(origParsB,-0.4,0.4); afbB_errs.push_back(afbB_err); */ delete effDD; delete effLL; delete effLLB; delete effDDB; } cDD->Print("DDeff.pdf"); cLL->Print("LLeff.pdf"); cDDB->Print("DDBeff.pdf"); cLLB->Print("LLBeff.pdf"); Afb_vs_q2->GetXaxis()->SetTitle("q^{2}"); Afb_vs_q2->GetYaxis()->SetTitle("Afb"); Afb_vs_q2->SetMaximum(1); Afb_vs_q2->SetMinimum(-1); Afb_vs_q2->Draw("AP"); ceff->Print("Afb_vs_q2.pdf"); AfbB_vs_q2->GetXaxis()->SetTitle("q^{2}"); AfbB_vs_q2->GetYaxis()->SetTitle("AfbB"); AfbB_vs_q2->SetMaximum(1); AfbB_vs_q2->SetMinimum(-1); AfbB_vs_q2->Draw("AP"); ceff->Print("AfbB_vs_q2.pdf"); fL_vs_q2->GetXaxis()->SetTitle("q^{2}"); fL_vs_q2->GetYaxis()->SetTitle("fL"); fL_vs_q2->Draw("AP"); ceff->Print("fL_vs_q2.pdf"); for(int bb = 0; bb < Afb_vs_q2->GetN(); bb++) { double qq, qqerr, afbv, afbBv, fLv; Afb_vs_q2->GetPoint(bb,qq,afbv); qqerr = Afb_vs_q2->GetErrorX(bb); AfbB_vs_q2->GetPoint(bb,qq,afbBv); fL_vs_q2->GetPoint(bb,qq,fLv); cout << fixed << setprecision(1) << qq-qqerr << " - " << qq+qqerr; cout << fixed << setprecision(4); //cout << " & $" << afbv << "_{-" << TMath::Abs(afb_errs[bb][0] - afbv) << "}^{+" << TMath::Abs(afb_errs[bb][1] - afbv) << "} \\text{(stat)} \\pm \\text{(sys)}$ "; //cout << " & $" << afbBv << "_{-" << TMath::Abs(afbB_errs[bb][0] - afbBv) << "}^{+" << TMath::Abs(afbB_errs[bb][1]-afbBv) << "} \\text{(stat)} \\pm \\text{(sys)}$ " ; //cout << " & $" << fLv << "_{-" << TMath::Abs(fL_errs[bb][0] - fLv) << "}^{+" << TMath::Abs(fL_errs[bb][1] - fLv) << "} \\text{(stat)} \\pm \\text{(sys)}$ "; cout << " \\\\ " << endl; } histFile->cd(); TTree * finalLLtree = (TTree*)TTree::MergeTrees(LLlist); TTree * finalDDtree = (TTree*)TTree::MergeTrees(DDlist); finalLLtree->SetName("LL_data"); finalDDtree->SetName("DD_data"); finalLLtree->Write(); finalDDtree->Write(); delete ceff; histFile->Write(); delete histFile; }
void FitBias(TString CAT,TString CUT,float SIG,float BKG,int NTOYS) { gROOT->ForceStyle(); RooMsgService::instance().setSilentMode(kTRUE); RooMsgService::instance().setStreamStatus(0,kFALSE); RooMsgService::instance().setStreamStatus(1,kFALSE); // ----------------------------------------- TFile *fTemplates = TFile::Open("templates_"+CUT+"_"+CAT+"_workspace.root"); RooWorkspace *wTemplates = (RooWorkspace*)fTemplates->Get("w"); RooRealVar *x = (RooRealVar*)wTemplates->var("mTop"); RooAbsPdf *pdf_signal = (RooAbsPdf*)wTemplates->pdf("ttbar_pdf_Nominal"); RooAbsPdf *pdf_bkg = (RooAbsPdf*)wTemplates->pdf("qcdCor_pdf"); TRandom *rnd = new TRandom(); rnd->SetSeed(0); x->setBins(250); RooPlot *frame; TFile *outf; if (NTOYS > 1) { outf = TFile::Open("FitBiasToys_"+CUT+"_"+CAT+".root","RECREATE"); } float nSigInj,nBkgInj,nSigFit,nBkgFit,eSigFit,eBkgFit,nll; TTree *tr = new TTree("toys","toys"); tr->Branch("nSigInj",&nSigInj,"nSigInj/F"); tr->Branch("nSigFit",&nSigFit,"nSigFit/F"); tr->Branch("nBkgInj",&nBkgInj,"nBkgInj/F"); tr->Branch("nBkgFit",&nBkgFit,"nBkgFit/F"); tr->Branch("eSigFit",&eSigFit,"eSigFit/F"); tr->Branch("eBkgFit",&eBkgFit,"eBkgFit/F"); tr->Branch("nll" ,&nll ,"nll/F"); for(int itoy=0;itoy<NTOYS;itoy++) { // generate pseudodataset nSigInj = rnd->Poisson(SIG); nBkgInj = rnd->Poisson(BKG); RooRealVar *nSig = new RooRealVar("nSig","nSig",nSigInj); RooRealVar *nBkg = new RooRealVar("nBkg","nBkg",nBkgInj); RooAddPdf *model = new RooAddPdf("model","model",RooArgList(*pdf_signal,*pdf_bkg),RooArgList(*nSig,*nBkg)); RooDataSet *data = model->generate(*x,nSigInj+nBkgInj); RooDataHist *roohist = new RooDataHist("roohist","roohist",RooArgList(*x),*data); // build fit model RooRealVar *nFitSig = new RooRealVar("nFitSig","nFitSig",SIG,0,10*SIG); RooRealVar *nFitBkg = new RooRealVar("nFitBkg","nFitBkg",BKG,0,10*BKG); RooAddPdf *modelFit = new RooAddPdf("modelFit","modelFit",RooArgList(*pdf_signal,*pdf_bkg),RooArgList(*nFitSig,*nFitBkg)); // fit the pseudo dataset RooFitResult *res = modelFit->fitTo(*roohist,RooFit::Save(),RooFit::Extended(kTRUE)); //res->Print(); nSigFit = nFitSig->getVal(); nBkgFit = nFitBkg->getVal(); eSigFit = nFitSig->getError(); eBkgFit = nFitBkg->getError(); nll = res->minNll(); tr->Fill(); if (itoy % 100 == 0) { cout<<"Toy #"<<itoy<<": injected = "<<nSigInj<<", fitted = "<<nSigFit<<", error = "<<eSigFit<<endl; } if (NTOYS == 1) { frame = x->frame(); roohist->plotOn(frame); model->plotOn(frame); } } if (NTOYS == 1) { TCanvas *can = new TCanvas("Toy","Toy",900,600); frame->Draw(); } else { outf->cd(); tr->Write(); outf->Close(); fTemplates->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; }
int main(int argc, char **argv) { bool printeff = true; string fc = "none"; gROOT->ProcessLine(".x lhcbStyle.C"); if(argc > 1) { for(int a = 1; a < argc; a++) { string arg = argv[a]; string str = arg.substr(2,arg.length()-2); if(arg.find("-E")!=string::npos) fc = str; if(arg=="-peff") printeff = true; } } int nexp = 100; int nbins = 6; double q2min[] = {8.,15.,11.0,15,16,18}; double q2max[] = {11.,20.,12.5,16,18,20}; TString datafilename = "/afs/cern.ch/work/p/pluca/weighted/Lmumu/candLb.root"; TreeReader * data = new TreeReader("candLb2Lmumu"); data->AddFile(datafilename); TreeReader * datajpsi = new TreeReader("candLb2JpsiL"); datajpsi->AddFile(datafilename); TFile * histFile = new TFile("Afb_bkgSys.root","recreate"); string options = "-quiet-noPlot-lin-stdAxis-XM(#Lambda#mu#mu) (MeV/c^{2})-noCost-noParams"; Analysis::SetPrintLevel("s"); RooRealVar * cosThetaL = new RooRealVar("cosThetaL","cosThetaL",0.,-1.,1.); RooRealVar * cosThetaB = new RooRealVar("cosThetaB","cosThetaB",0.,-1.,1.); RooRealVar * MM = new RooRealVar("Lb_MassConsLambda","Lb_MassConsLambda",5621.,5400.,6000.); MM->setRange("Signal",5600,5640); RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR); //TGraphAsymmErrors * fL_vs_q2 = new TGraphAsymmErrors(); //TCanvas * ceff = new TCanvas(); RooCategory * samples = new RooCategory("samples","samples"); samples->defineType("DD"); samples->defineType("LL"); RooRealVar * afb = new RooRealVar("afb","afb",0.,-0.75,0.75); RooRealVar * fL = new RooRealVar("fL","fL",0.6,0.,1.); TString afbLpdf = "((3./8.)*(1.-fL)*(1 + TMath::Power(cosThetaL,2)) + afb*cosThetaL + (3./4.)*fL*(1 - TMath::Power(cosThetaL,2)))"; RooRealVar * afbB = new RooRealVar("afbB","afbB",0.,-0.5,0.5); TString afbBpdf = "(1 + 2*afbB*cosThetaB)"; RooAbsPdf * teoPdf = new RooGenericPdf("teoPdf",afbLpdf,RooArgSet(*cosThetaL,*afb,*fL)); RooAbsPdf * teoPdfB = new RooGenericPdf("teoPdfB",afbBpdf,RooArgSet(*cosThetaB,*afbB)); TreeReader * mydata = datajpsi; Str2VarMap jpsiParsLL = getJpsiPars("LL", CutsDef::LLcut, histFile); Str2VarMap jpsiParsDD = getJpsiPars("DD", CutsDef::DDcut, histFile); vector<TH1 *> fLsysh, afbsysh, afbBsysh, fLsysh_frac, afbsysh_frac, afbBsysh_frac; for(int i = 0; i < nbins; i++) { TString q2name = ((TString)Form("q2_%4.2f_%4.2f",q2min[i],q2max[i])).ReplaceAll(".",""); if(i>0) { mydata = data; MM->setRange(5400,6000); } else { q2name = "jpsi"; MM->setRange(5500,5850); } TString curq2cut = Form("TMath::Power(J_psi_1S_MM/1000,2) >= %e && TMath::Power(J_psi_1S_MM/1000,2) < %e",q2min[i],q2max[i]); cout << "------------------- q2 bin: " << q2min[i] << " - " << q2max[i] << " -----------------------" << endl; /** GET AND FIT EFFICIENCIES **/ RooAbsPdf * effDDpdf = NULL, * effLLpdf = NULL, * effLLBpdf = NULL, * effDDBpdf = NULL; getEfficiencies(q2min[i],q2max[i],&effLLpdf,&effDDpdf,&effLLBpdf,&effDDBpdf,printeff); cout << "Efficiencies extracted" << endl; histFile->cd(); /** FIT AFB **/ afb->setVal(0); afbB->setVal(-0.37); fL->setVal(0.6); RooAbsPdf * corrPdfLL = new RooProdPdf("sigPdfLL"+q2name,"corrPdfLL",*teoPdf,*effLLpdf); RooAbsPdf * corrPdfDD = new RooProdPdf("sigPdfDD"+q2name,"corrPdfDD",*teoPdf,*effDDpdf); RooAbsPdf * corrPdfLLB = new RooProdPdf("sigPdfLLB"+q2name,"corrPdfLLB",*teoPdfB,*effLLBpdf); RooAbsPdf * corrPdfDDB = new RooProdPdf("sigPdfDDB"+q2name,"corrPdfDDB",*teoPdfB,*effDDBpdf); TCut baseCut = ""; TCut cutLL = CutsDef::LLcut + (TCut)curq2cut + baseCut; TCut cutDD = CutsDef::DDcut + (TCut)curq2cut + baseCut; histFile->cd(); double fracDDv[2], fracLLv[2]; double nsigDD, nsigLL; RooDataSet * dataLL = getDataAndFrac("LL",q2name,mydata,cutLL,MM,&fracLLv[0],jpsiParsLL,&nsigLL); RooDataSet * dataDD = getDataAndFrac("DD",q2name,mydata,cutDD,MM,&fracDDv[0],jpsiParsDD,&nsigDD); double nevts = nsigDD+nsigLL; cout << fixed << setprecision(3) << fracDDv[0] << " " << fracDDv[1] << endl; RooRealVar * fracLL = new RooRealVar("fracLL","fracLL",fracLLv[0]); RooRealVar * fracDD = new RooRealVar("fracDD","fracDD",fracDDv[0]); RooAbsPdf * bkgLL = NULL, * bkgLLB = NULL, * bkgDD = NULL, * bkgDDB = NULL; buildBkgPdfs(q2min[i],q2max[i],"LL",CutsDef::LLcut,&bkgLL,&bkgLLB); buildBkgPdfs(q2min[i],q2max[i],"DD",CutsDef::DDcut,&bkgDD,&bkgDDB); cout << "Backgrounds extracted" << endl; RooAbsPdf * modelLL = new RooAddPdf("modelLL","modelLL",RooArgSet(*corrPdfLL,*bkgLL),*fracLL); RooAbsPdf * modelDD = new RooAddPdf("modelDD","modelDD",RooArgSet(*corrPdfDD,*bkgDD),*fracDD); RooAbsPdf * modelLLB = new RooAddPdf("modelLLB","modelLLB",RooArgSet(*corrPdfLLB,*bkgLLB),*fracLL); RooAbsPdf * modelDDB = new RooAddPdf("modelDDB","modelDDB",RooArgSet(*corrPdfDDB,*bkgDDB),*fracDD); // CREATE COMBINED DATASET RooDataSet * combData = new RooDataSet(Form("combData_%i",i),"combined data",RooArgSet(*MM,*cosThetaL,*cosThetaB),Index(*samples),Import("DD",*dataDD),Import("LL",*dataLL)); Str2VarMap params; params["fL"] = fL; params["afb"] = afb; Str2VarMap paramsB; paramsB["afbB"] = afbB; // FIT COS LEPTON RooSimultaneous * combModel = new RooSimultaneous(Form("combModel_%i",i),"",*samples); combModel->addPdf(*modelLL,"LL"); combModel->addPdf(*modelDD,"DD"); RooFitResult * res = safeFit(combModel,combData,params,&isInAllowedArea); // FIT COS HADRON RooSimultaneous * combModelB = new RooSimultaneous(Form("combModelB_%i",i),"",*samples); combModelB->addPdf(*modelLLB,"LL"); combModelB->addPdf(*modelDDB,"DD"); RooFitResult * resB = safeFit(combModelB,combData,paramsB,&isInAllowedAreaB); cout << endl << fixed << setprecision(6) << "AfbB = " << afbB->getVal() << " +/- " << afbB->getError() << endl; cout << "Afb = " << afb->getVal() << " +/- " << afb->getError() << endl; cout << "fL = " << fL->getVal() << " +/- " << fL->getError() << endl; cout << endl; cout << "lepton: " << res->edm() << " " << res->covQual() << endl; cout << "baryon: " << resB->edm() << " " << resB->covQual() << endl; cout << endl; TH1F * fLsys = new TH1F(Form("fLsys_%i",i),"fLsys",40,-1,1); TH1F * afbsys = new TH1F(Form("afbsys_%i",i),"afbsys",40,-1,1); TH1F * afbBsys = new TH1F(Form("afbBsys_%i",i),"afbBsys",40,-1,1); TH1F * fLsys_frac = new TH1F(Form("fLsys_frac%i",i),"fLsys",40,-1,1); TH1F * afbsys_frac = new TH1F(Form("afbsys_frac%i",i),"afbsys",40,-1,1); TH1F * afbBsys_frac = new TH1F(Form("afbBsys_frac%i",i),"afbBsys",40,-1,1); RooAbsPdf * mybkgDD_2 = NULL, * mybkgDDB_2 = NULL; buildBkgPdfs(q2min[i],q2max[i],"DD",CutsDef::DDcut,&mybkgDD_2,&mybkgDDB_2,"RooKeyPdf"); //cout << nevts << endl; //TRandom3 r(0); for(int e = 0; e < nexp; e++) { histFile->cd(); RooAbsPdf * toypdf = (RooAbsPdf *)modelDD->Clone(); Analysis * toy = new Analysis("toy",cosThetaL,modelDD,nevts); RooAbsPdf * toypdfB = (RooAbsPdf *)modelDDB->Clone(); Analysis * toyB = new Analysis("toyB",cosThetaB,modelDDB,nevts); afb->setVal(0); afbB->setVal(-0.37); fL->setVal(0.6); safeFit(toypdf,toy->GetDataSet("-recalc"),params,&isInAllowedArea); safeFit(toypdfB,toyB->GetDataSet("-recalc"),paramsB,&isInAllowedAreaB); double def_afb = afb->getVal(); double def_fL = fL->getVal(); double def_afbB = afbB->getVal(); afb->setVal(0); afbB->setVal(-0.37); fL->setVal(0.6); RooAbsPdf * modelDD_2 = new RooAddPdf("modelDD_2","modelDD",RooArgSet(*corrPdfDD,*mybkgDD_2),*fracDD); RooAbsPdf * modelDDB_2 = new RooAddPdf("modelDDB_2","modelDDB",RooArgSet(*corrPdfDDB,*mybkgDDB_2),*fracDD); safeFit(modelDD_2,toy->GetDataSet("-recalc"),params,&isInAllowedArea); safeFit(modelDDB_2,toyB->GetDataSet("-recalc"),paramsB,&isInAllowedAreaB); double oth_afb = afb->getVal(); double oth_fL = fL->getVal(); double oth_afbB = afbB->getVal(); fLsys->Fill(oth_fL-def_fL); afbsys->Fill(oth_afb-def_afb); afbBsys->Fill(oth_afbB-def_afbB); afb->setVal(0.); afbB->setVal(-0.37); fL->setVal(0.6); //double rdm_frac = r.Gaus(fracDDv[0],fracDDv[1]); double rdm_frac = fracDDv[0] + fracDDv[1]; RooRealVar * fracDD_2 = new RooRealVar("fracDD_2","fracDD_2",rdm_frac); RooAbsPdf * modelDD_3 = new RooAddPdf("modelDD_3","modelDD",RooArgSet(*corrPdfDD,*bkgDD),*fracDD_2); RooAbsPdf * modelDDB_3 = new RooAddPdf("modelDDB_3","modelDDB",RooArgSet(*corrPdfDDB,*bkgDDB),*fracDD_2); safeFit(modelDD_3,toy->GetDataSet("-recalc"),params,&isInAllowedArea); safeFit(modelDDB_3,toyB->GetDataSet("-recalc"),paramsB,&isInAllowedAreaB); double frc_afb = afb->getVal(); double frc_fL = fL->getVal(); double frc_afbB = afbB->getVal(); fLsys_frac->Fill(frc_fL-def_fL); afbsys_frac->Fill(frc_afb-def_afb); afbBsys_frac->Fill(frc_afbB-def_afbB); } afbsysh.push_back(afbsys); afbBsysh.push_back(afbBsys); fLsysh.push_back(fLsys); afbsysh_frac.push_back(afbsys_frac); afbBsysh_frac.push_back(afbBsys_frac); fLsysh_frac.push_back(fLsys_frac); } for(int q = 0; q < nbins; q++) { cout << fixed << setprecision(2) << "-------- Bin " << q2min[q] << "-" << q2max[q] << endl; cout << fixed << setprecision(5) << "fL sys = " << fLsysh[q]->GetMean() << " +/- " << fLsysh[q]->GetMeanError() << endl; cout << "Afb sys = " << afbsysh[q]->GetMean() << " +/- " << afbsysh[q]->GetMeanError() << endl; cout << "AfbB sys = " << afbBsysh[q]->GetMean() << " +/- " << afbBsysh[q]->GetMeanError() << endl; } cout << "#################################################################" << endl; for(int q = 0; q < nbins; q++) { cout << fixed << setprecision(2) << "-------- Bin " << q2min[q] << "-" << q2max[q] << endl; cout << fixed << setprecision(5) << "fL sys = " << fLsysh_frac[q]->GetMean() << " +/- " << fLsysh_frac[q]->GetMeanError() << endl; cout << "Afb sys = " << afbsysh_frac[q]->GetMean() << " +/- " << afbsysh_frac[q]->GetMeanError() << endl; cout << "AfbB sys = " << afbBsysh_frac[q]->GetMean() << " +/- " << afbBsysh_frac[q]->GetMeanError() << endl; } cout << "#################################################################" << endl; for(int q = 0; q < nbins; q++) { cout << fixed << setprecision(2) << "-------- Bin " << q2min[q] << "-" << q2max[q] << endl; cout << fixed << setprecision(5) << "fL sys = " << TMath::Sqrt(TMath::Power(fLsysh_frac[q]->GetMean(),2) + TMath::Power(fLsysh[q]->GetMean(),2) ) << endl; cout << "Afb sys = " << TMath::Sqrt(TMath::Power(afbsysh_frac[q]->GetMean(),2) + TMath::Power(afbsysh[q]->GetMean(),2) ) << endl; cout << "AfbB sys = " << TMath::Sqrt(TMath::Power(afbBsysh_frac[q]->GetMean(),2) + TMath::Power(afbBsysh[q]->GetMean(),2) ) << endl; } }
void computeLimits( const char* ACTag, // ACTag: where to look for combined workspaces in Limits/CombinedWorkspaces/ bool doSyst= false, double CL=0.95, // Confidence Level for limits computation int calculatorType = 2, int testStatType = 2, bool useCLs = false ) // define calc type and test stat type: // // calculatorType = 0 Freq calculator // calculatorType = 1 Hybrid calculator // calculatorType = 2 Asymptotic calculator // calculatorType = 3 Asymptotic calculator using nominal Asimov data sets (not using fitted parameter values but nominal ones) // // testStatType = 0 LEP // = 1 Tevatron // = 2 Profile Likelihood two sided // = 3 Profile Likelihood one sided (i.e. = 0 if mu < mu_hat) // = 4 Profile Likelihood signed ( pll = -pll if mu < mu_hat) // = 5 Max Likelihood Estimate as test statistic // = 6 Number of observed event as test statistic // // 0,3,true for frequentist CLs; 2,3,true for asymptotic CLs; 0,2,false for FC { // list of files vector<TString> theFiles = combFileList(ACTag, doSyst ? "wSyst" : "woSyst"); if ( theFiles.empty() ) { cout << "# [Error]: No combined workspaces found" << endl; return; } // File to save results ostringstream strs; strs << CL; string str = strs.str(); TString sCL(str); sCL.Remove(0,sCL.First('.')+1); string limitsFileName = string("csv/") + "cLimits_" + string(sCL) + "_" + string(ACTag); if ( calculatorType == 0 ) limitsFileName = limitsFileName + "_Freq"; else if ( calculatorType == 1 ) limitsFileName = limitsFileName + "_Hybr"; else if ( calculatorType == 2 ) limitsFileName = limitsFileName + "_Asym"; else if ( calculatorType == 3 ) limitsFileName = limitsFileName + "_AsymAsi"; if ( testStatType == 0 ) limitsFileName = limitsFileName + "_LEP"; else if ( testStatType == 1 ) limitsFileName = limitsFileName + "_Tev"; else if ( testStatType == 2 ) limitsFileName = limitsFileName + "_2SPL"; else if ( testStatType == 3 ) limitsFileName = limitsFileName + "_1SPL"; else if ( testStatType == 4 ) limitsFileName = limitsFileName + "_SPL"; else if ( testStatType == 5 ) limitsFileName = limitsFileName + "_MaxL"; else if ( testStatType == 6 ) limitsFileName = limitsFileName + "_NOE"; if ( doSyst ) limitsFileName = limitsFileName + "_wSyst.csv"; else limitsFileName = limitsFileName + "_woSyst.csv"; ofstream file(limitsFileName.c_str()); file << CL << endl; // Confidence interval computation int cnt=1; for (vector<TString>::const_iterator it=theFiles.begin(); it!=theFiles.end(); it++) { cout << ">>>>>>> Computing " << CL*100 << "% " << "limits for analysis bin " << cnt << endl; cout << "Using combined PbPb-PP workspace " << cnt << " / " << theFiles.size() << ": " << *it << endl; anabin thebin = binFromFile(*it); // if (thebin != anabin(1.6,2.4,3,30,40,80)) continue; if (!usebatch) { pair<double,double> lims = runLimit_RaaNS_Workspace(*it, "RFrac2Svs1S_PbPbvsPP_P", "simPdf", "workspace", "dOS_DATA", ACTag, CL, calculatorType, testStatType, useCLs); file << thebin.rapbin().low() << ", " << thebin.rapbin().high() << ", " << thebin.ptbin().low() << ", " << thebin.ptbin().high() << ", " << thebin.centbin().low() << ", " << thebin.centbin().high() << ", " << lims.first << ", " << lims.second << endl; } else { TString exports; exports += Form("export it=%s; ",it->Data()); exports += Form("export ACTag=%s; ",ACTag); exports += Form("export CL=%f; ",CL); exports += Form("export calculatorType=%i; ",calculatorType); exports += Form("export testStatType=%i; ",testStatType); exports += Form("export useCLs=%i; ",useCLs); exports += Form("export pwd_=%s; ", gSystem->pwd()); if (calculatorType==0) { // special case of frequentist limits: submit more jobs TFile *f = TFile::Open(*it); RooWorkspace *ws = (RooWorkspace*) f->Get("workspace"); ws->loadSnapshot("SbHypo_poiAndNuisance_snapshot"); RooRealVar *theVar = (RooRealVar*) ws->var("RFrac2Svs1S_PbPbvsPP_P"); double val = theVar->getVal(); double err = theVar->getError(); f->Close(); if (ws) delete ws; double nsigma = sqrt(2)*TMath::ErfcInverse(1-CL); // double poimin = max(0.,0.5*(val - nsigma*err)); // double poimax = 1.5*(val + nsigma*err); double poimin = max(0.,val + 0.9*nsigma*err); double poimax = val + 1.1*nsigma*err; int npoints = 5; double dpoi = (poimax-poimin)/npoints; for (int ipoi=0; ipoi<npoints; ipoi++) for (int irnd=0; irnd<50; irnd++) { TString exports2 = exports + Form("export poival=%f; ",poimin+ipoi*dpoi); exports2 += Form("export rndseed=%i; ",irnd+1); TString command("qsub -k oe -q cms@llrt3 -p -500 "); // -p option: lower the priority since we're submitting many jobs... command += Form("-N limits_bin%i_ipoi%i_%i ",cnt,ipoi,irnd+1); command += "-V "; command += Form("-o %s ", gSystem->pwd()); command += Form("-v it,ACTag,CL,calculatorType,testStatType,useCLs,pwd_,poival,rndseed "); command += "runbatch_limits_4WS.sh"; TString command_full = exports2 + command; cout << command_full.Data() << endl; int njobs = atoi(exec("qstat -u $USER cms@llrt3 | wc -l").c_str()); int njobs_queue = atoi(exec("qstat cms@llrt3 | grep \" Q \" | wc -l").c_str()); while (njobs_queue>0 && njobs >= maxjobs) { system("sleep 60"); njobs = atoi(exec("qstat -u $USER cms@llrt3 | wc -l").c_str()); njobs_queue = atoi(exec("qstat cms@llrt3 | grep \" Q \" | wc -l").c_str()); } system(command_full.Data()); } } else { exports += Form("export poival=%f; ",-1.); exports += Form("export rndseed=%i; ",-1); TString command("qsub -k oe -q cms@llrt3 -l nodes=1:ppn=23 "); command += Form("-N limits_bin%i ",cnt); command += "-V "; command += Form("-o %s ", gSystem->pwd()); command += Form("-v it,ACTag,CL,calculatorType,testStatType,useCLs,pwd_,poival,rndseed "); command += "runbatch_limits_4WS.sh"; TString command_full = exports + command; cout << command_full.Data() << endl; system(command_full.Data()); } system("sleep 1"); } cnt++; } // loop on the files file.close(); cout << "Closed " << limitsFileName << endl << endl; }
void StandardBayesianNumericalDemo(const char* infile = "", const char* workspaceName = "combined", const char* modelConfigName = "ModelConfig", const char* dataName = "obsData") { // option definitions double confLevel = optBayes.confLevel; TString integrationType = optBayes.integrationType; int nToys = optBayes.nToys; bool scanPosterior = optBayes.scanPosterior; int nScanPoints = optBayes.nScanPoints; int intervalType = optBayes.intervalType; int maxPOI = optBayes.maxPOI; double nSigmaNuisance = optBayes.nSigmaNuisance; ///////////////////////////////////////////////////////////// // First part is just to access a user-defined file // or create the standard example file if it doesn't exist //////////////////////////////////////////////////////////// const char* filename = ""; if (!strcmp(infile,"")) { filename = "results/example_combined_GaussExample_model.root"; bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code // if file does not exists generate with histfactory if (!fileExist) { #ifdef _WIN32 cout << "HistFactory file cannot be generated on Windows - exit" << endl; return; #endif // Normally this would be run on the command line cout <<"will run standard hist2workspace example"<<endl; gROOT->ProcessLine(".! prepareHistFactory ."); gROOT->ProcessLine(".! hist2workspace config/example.xml"); cout <<"\n\n---------------------"<<endl; cout <<"Done creating example input"<<endl; cout <<"---------------------\n\n"<<endl; } } else filename = infile; // Try to open the file TFile *file = TFile::Open(filename); // if input file was specified byt not found, quit if(!file ){ cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl; return; } ///////////////////////////////////////////////////////////// // Tutorial starts here //////////////////////////////////////////////////////////// // get the workspace out of the file RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName); if(!w){ cout <<"workspace not found" << endl; return; } // get the modelConfig out of the file ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName); // get the modelConfig out of the file RooAbsData* data = w->data(dataName); // make sure ingredients are found if(!data || !mc){ w->Print(); cout << "data or ModelConfig was not found" <<endl; return; } ///////////////////////////////////////////// // create and use the BayesianCalculator // to find and plot the 95% credible interval // on the parameter of interest as specified // in the model config // before we do that, we must specify our prior // it belongs in the model config, but it may not have // been specified RooUniform prior("prior","",*mc->GetParametersOfInterest()); w->import(prior); mc->SetPriorPdf(*w->pdf("prior")); // do without systematics //mc->SetNuisanceParameters(RooArgSet() ); if (nSigmaNuisance > 0) { RooAbsPdf * pdf = mc->GetPdf(); assert(pdf); RooFitResult * res = pdf->fitTo(*data, Save(true), Minimizer(ROOT::Math::MinimizerOptions::DefaultMinimizerType().c_str()), Hesse(true), PrintLevel(ROOT::Math::MinimizerOptions::DefaultPrintLevel()-1) ); res->Print(); RooArgList nuisPar(*mc->GetNuisanceParameters()); for (int i = 0; i < nuisPar.getSize(); ++i) { RooRealVar * v = dynamic_cast<RooRealVar*> (&nuisPar[i] ); assert( v); v->setMin( TMath::Max( v->getMin(), v->getVal() - nSigmaNuisance * v->getError() ) ); v->setMax( TMath::Min( v->getMax(), v->getVal() + nSigmaNuisance * v->getError() ) ); std::cout << "setting interval for nuisance " << v->GetName() << " : [ " << v->getMin() << " , " << v->getMax() << " ]" << std::endl; } } BayesianCalculator bayesianCalc(*data,*mc); bayesianCalc.SetConfidenceLevel(confLevel); // 95% interval // default of the calculator is central interval. here use shortest , central or upper limit depending on input // doing a shortest interval might require a longer time since it requires a scan of the posterior function if (intervalType == 0) bayesianCalc.SetShortestInterval(); // for shortest interval if (intervalType == 1) bayesianCalc.SetLeftSideTailFraction(0.5); // for central interval if (intervalType == 2) bayesianCalc.SetLeftSideTailFraction(0.); // for upper limit if (!integrationType.IsNull() ) { bayesianCalc.SetIntegrationType(integrationType); // set integrationType bayesianCalc.SetNumIters(nToys); // set number of ietrations (i.e. number of toys for MC integrations) } // in case of toyMC make a nnuisance pdf if (integrationType.Contains("TOYMC") ) { RooAbsPdf * nuisPdf = RooStats::MakeNuisancePdf(*mc, "nuisance_pdf"); cout << "using TOYMC integration: make nuisance pdf from the model " << std::endl; nuisPdf->Print(); bayesianCalc.ForceNuisancePdf(*nuisPdf); scanPosterior = true; // for ToyMC the posterior is scanned anyway so used given points } // compute interval by scanning the posterior function if (scanPosterior) bayesianCalc.SetScanOfPosterior(nScanPoints); RooRealVar* poi = (RooRealVar*) mc->GetParametersOfInterest()->first(); if (maxPOI != -999 && maxPOI > poi->getMin()) poi->setMax(maxPOI); SimpleInterval* interval = bayesianCalc.GetInterval(); // print out the iterval on the first Parameter of Interest cout << "\n>>>> RESULT : " << confLevel*100 << "% interval on " << poi->GetName()<<" is : ["<< interval->LowerLimit() << ", "<< interval->UpperLimit() <<"] "<<endl; // make a plot // since plotting may take a long time (it requires evaluating // the posterior in many points) this command will speed up // by reducing the number of points to plot - do 50 // ignore errors of PDF if is zero RooAbsReal::setEvalErrorLoggingMode(RooAbsReal::Ignore) ; cout << "\nDrawing plot of posterior function....." << endl; // always plot using numer of scan points bayesianCalc.SetScanOfPosterior(nScanPoints); RooPlot * plot = bayesianCalc.GetPosteriorPlot(); plot->Draw(); }
int DiagnosisMacro(int Nbins = 10, int Nsigma = 10, int CPUused = 1, TString Filename = "FIT_DATA_Psi2SJpsi_PPPrompt_Bkg_SecondOrderChebychev_pt65300_rap016_cent0200_262620_263757.root", TString Outputdir = "./") //Nbins: Number of points for which to calculate profile likelihood. Time required is about (1/CPU) minutes per point per parameter. 0 means do plain likelihood only //Nsigma: The range in which the scan is performed (value-Nsigma*sigma, value+Nsigma*sigma) //CPUused: anything larger than 1 causes weird fit results on my laptop, runs fine on lxplus with more (16) { // R e a d w o r k s p a c e f r o m f i l e // ----------------------------------------------- // Open input file with workspace //Filename = "FIT_DATA_Psi2SJpsi_PP_Jpsi_DoubleCrystalBall_Psi2S_DoubleCrystalBall_Bkg_Chebychev2_pt6590_rap016_cent0200.root"; //Filename = "FIT_DATA_Psi2SJpsi_PbPb_Jpsi_DoubleCrystalBall_Psi2S_DoubleCrystalBall_Bkg_Chebychev1_pt6590_rap016_cent0200.root"; TFile *f = new TFile(Filename); // Retrieve workspace from file RooWorkspace* w = (RooWorkspace*)f->Get("workspace"); // Retrieve x,model and data from workspace RooRealVar* x = w->var("invMass"); RooAbsPdf* model = w->pdf("simPdf_syst"); if (model == 0) { model = w->pdf("simPdf"); } if (model == 0) { model = w->pdf("pdfMASS_Tot_PP"); } if (model == 0) { model = w->pdf("pdfMASS_Tot_PbPb"); } if (model == 0) { cout << "[ERROR] pdf failed to load from the workspace" << endl; return false; } RooAbsData* data = w->data("dOS_DATA"); if (data == 0) { data = w->data("dOS_DATA_PP"); } if (data == 0) { data = w->data("dOS_DATA_PbPb"); } if (data == 0) { cout << "[ERROR] data failed to load from the workspace" << endl; return false; } // Print structure of composite p.d.f. model->Print("t"); /* // P l o t m o d e l // --------------------------------------------------------- // Plot data and PDF overlaid RooPlot* xframe = x->frame(Title("J/psi Model and Data")); data->plotOn(xframe); model->plotOn(xframe); // Draw the frame on the canvas TCanvas* c2 = new TCanvas("PlotModel", "PlotModel", 1000, 1000); gPad->SetLeftMargin(0.15); xframe->GetYaxis()->SetTitleOffset(2.0); xframe->Draw();//*/ ///// Check parameters RooArgSet* paramSet1 = model->getDependents(data); paramSet1->Print("v"); // Just check RooArgSet* paramSet2 = model->getParameters(data); paramSet2->Print("v"); int Nparams = paramSet2->getSize(); cout << "Number of parameters: " << Nparams<<endl<<endl; // C o n s t r u c t p l a i n l i k e l i h o o d // --------------------------------------------------- // Construct unbinned likelihood RooAbsReal* nll = model->createNLL(*data, NumCPU(CPUused)); // Minimize likelihood w.r.t all parameters before making plots RooMinuit(*nll).migrad(); ////////////////////////////////////////////////////// /////////////////// L O O P O V E R P A R A M E T E R S ///////////////////////////////////////////////////// /// Set up loop over parameters TString ParamName; double ParamValue; double ParamError; double ParamLimitLow; double ParamLimitHigh; double FitRangeLow; double FitRangeHigh; RooRealVar* vParam; int counter = 0; // Loop start TIterator* iter = paramSet2->createIterator(); TObject* var = iter->Next(); while (var != 0) { counter++; ParamName = var->GetName(); vParam = w->var(ParamName); ParamValue = vParam->getVal(); ParamError = vParam->getError(); ParamLimitLow = vParam->getMin(); ParamLimitHigh = vParam->getMax(); cout << ParamName << " has value " << ParamValue << " with error: " << ParamError << " and limits: " << ParamLimitLow << " to " << ParamLimitHigh << endl << endl; if (ParamError == 0) { //Skipping fixed parameters cout << "Parameter was fixed, skipping its fitting" << endl; cout << endl << "DONE WITH " << counter << " PARAMETER OUT OF " << Nparams << endl << endl; var = iter->Next(); continue; } // determining fit range: Nsigma sigma on each side unless it would be outside of parameter limits if ((ParamValue - Nsigma * ParamError) > ParamLimitLow) { FitRangeLow = (ParamValue - Nsigma * ParamError); } else { FitRangeLow = ParamLimitLow; } if ((ParamValue + Nsigma * ParamError) < ParamLimitHigh) { FitRangeHigh = (ParamValue + Nsigma * ParamError); } else { FitRangeHigh = ParamLimitHigh; } // P l o t p l a i n l i k e l i h o o d a n d C o n s t r u c t p r o f i l e l i k e l i h o o d // --------------------------------------------------- RooPlot* frame1; RooAbsReal* pll=NULL; if (Nbins != 0) { frame1 = vParam->frame(Bins(Nbins), Range(FitRangeLow, FitRangeHigh), Title(TString::Format("LL and profileLL in %s", ParamName.Data()))); nll->plotOn(frame1, ShiftToZero()); pll = nll->createProfile(*vParam); // Plot the profile likelihood pll->plotOn(frame1, LineColor(kRed), RooFit::Precision(-1)); } else { //Skip profile likelihood frame1 = vParam->frame(Bins(10), Range(FitRangeLow, FitRangeHigh), Title(TString::Format("LL and profileLL in %s", ParamName.Data()))); nll->plotOn(frame1, ShiftToZero()); } // D r a w a n d s a v e p l o t s // ----------------------------------------------------------------------- // Adjust frame maximum for visual clarity frame1->SetMinimum(0); frame1->SetMaximum(20); TCanvas* c = new TCanvas("CLikelihoodResult", "CLikelihoodResult", 800, 600); c->cd(1); gPad->SetLeftMargin(0.15); frame1->GetYaxis()->SetTitleOffset(1.4); frame1->Draw(); TLegend* leg = new TLegend(0.70, 0.70, 0.95, 0.88, ""); leg->SetFillColor(kWhite); leg->SetBorderSize(0); leg->SetTextSize(0.035); TLegendEntry *le1 = leg->AddEntry(nll, "Plain likelihood", "l"); le1->SetLineColor(kBlue); le1->SetLineWidth(3); TLegendEntry *le2 = leg->AddEntry(pll, "Profile likelihood", "l"); le2->SetLineColor(kRed); le2->SetLineWidth(3); leg->Draw("same"); //Save plot TString StrippedName = TString(Filename(Filename.Last('/')+1,Filename.Length())); StrippedName = StrippedName.ReplaceAll(".root",""); cout << StrippedName << endl; gSystem->mkdir(Form("%s/root/%s", Outputdir.Data(), StrippedName.Data()), kTRUE); c->SaveAs(Form("%s/root/%s/Likelihood_scan_%s.root", Outputdir.Data(), StrippedName.Data(), ParamName.Data())); gSystem->mkdir(Form("%s/pdf/%s", Outputdir.Data(), StrippedName.Data()), kTRUE); c->SaveAs(Form("%s/pdf/%s/Likelihood_scan_%s.pdf", Outputdir.Data(), StrippedName.Data(), ParamName.Data())); gSystem->mkdir(Form("%s/png/%s", Outputdir.Data(), StrippedName.Data()), kTRUE); c->SaveAs(Form("%s/png/%s/Likelihood_scan_%s.png", Outputdir.Data(), StrippedName.Data(), ParamName.Data())); delete c; delete frame1; if (pll) delete pll; cout << endl << "DONE WITH " << counter << " PARAMETER OUT OF " << Nparams << endl << endl; //if (counter == 2){ break; } //Exit - for testing var = iter->Next(); } // End of the loop return true; }
// internal routine to run the inverter HypoTestInverterResult * RunInverter(RooWorkspace * w, const char * modelSBName, const char * modelBName, const char * dataName, int type, int testStatType, int npoints, double poimin, double poimax, int ntoys, bool useCls ) { std::cout << "Running HypoTestInverter on the workspace " << w->GetName() << std::endl; w->Print(); RooAbsData * data = w->data(dataName); if (!data) { Error("RA2bHypoTestDemo","Not existing data %s",dataName); return 0; } else std::cout << "Using data set " << dataName << std::endl; // get models from WS // get the modelConfig out of the file ModelConfig* bModel = (ModelConfig*) w->obj(modelBName); ModelConfig* sbModel = (ModelConfig*) w->obj(modelSBName); if (!sbModel) { Error("RA2bHypoTestDemo","Not existing ModelConfig %s",modelSBName); return 0; } // check the model if (!sbModel->GetPdf()) { Error("RA2bHypoTestDemo","Model %s has no pdf ",modelSBName); return 0; } if (!sbModel->GetParametersOfInterest()) { Error("RA2bHypoTestDemo","Model %s has no poi ",modelSBName); return 0; } if (!sbModel->GetParametersOfInterest()) { Error("RA2bHypoTestInvDemo","Model %s has no poi ",modelSBName); return 0; } if (!sbModel->GetSnapshot() ) { Info("RA2bHypoTestInvDemo","Model %s has no snapshot - make one using model poi",modelSBName); sbModel->SetSnapshot( *sbModel->GetParametersOfInterest() ); } if (!bModel || bModel == sbModel) { Info("RA2bHypoTestInvDemo","The background model %s does not exist",modelBName); Info("RA2bHypoTestInvDemo","Copy it from ModelConfig %s and set POI to zero",modelSBName); bModel = (ModelConfig*) sbModel->Clone(); bModel->SetName(TString(modelSBName)+TString("_with_poi_0")); RooRealVar * var = dynamic_cast<RooRealVar*>(bModel->GetParametersOfInterest()->first()); if (!var) return 0; double oldval = var->getVal(); var->setVal(0); bModel->SetSnapshot( RooArgSet(*var) ); var->setVal(oldval); } else { if (!bModel->GetSnapshot() ) { Info("RA2bHypoTestInvDemo","Model %s has no snapshot - make one using model poi and 0 values ",modelBName); RooRealVar * var = dynamic_cast<RooRealVar*>(bModel->GetParametersOfInterest()->first()); if (var) { double oldval = var->getVal(); var->setVal(0); bModel->SetSnapshot( RooArgSet(*var) ); var->setVal(oldval); } else { Error("RA2bHypoTestInvDemo","Model %s has no valid poi",modelBName); return 0; } } } SimpleLikelihoodRatioTestStat slrts(*sbModel->GetPdf(),*bModel->GetPdf()); if (sbModel->GetSnapshot()) slrts.SetNullParameters(*sbModel->GetSnapshot()); if (bModel->GetSnapshot()) slrts.SetAltParameters(*bModel->GetSnapshot()); // ratio of profile likelihood - need to pass snapshot for the alt RatioOfProfiledLikelihoodsTestStat ropl(*sbModel->GetPdf(), *bModel->GetPdf(), bModel->GetSnapshot()); ropl.SetSubtractMLE(false); //MyProfileLikelihoodTestStat profll(*sbModel->GetPdf()); ProfileLikelihoodTestStat profll(*sbModel->GetPdf()); if (testStatType == 3) profll.SetOneSided(1); if (optimize) profll.SetReuseNLL(true); TestStatistic * testStat = &slrts; if (testStatType == 1) testStat = &ropl; if (testStatType == 2 || testStatType == 3) testStat = &profll; HypoTestCalculatorGeneric * hc = 0; if (type == 0) hc = new FrequentistCalculator(*data, *bModel, *sbModel); else hc = new HybridCalculator(*data, *bModel, *sbModel); ToyMCSampler *toymcs = (ToyMCSampler*)hc->GetTestStatSampler(); //=== DEBUG ///// toymcs->SetWS( w ) ; //=== DEBUG toymcs->SetNEventsPerToy(1); toymcs->SetTestStatistic(testStat); if (optimize) toymcs->SetUseMultiGen(true); if (type == 1) { HybridCalculator *hhc = (HybridCalculator*) hc; hhc->SetToys(ntoys,ntoys); // check for nuisance prior pdf if (bModel->GetPriorPdf() && sbModel->GetPriorPdf() ) { hhc->ForcePriorNuisanceAlt(*bModel->GetPriorPdf()); hhc->ForcePriorNuisanceNull(*sbModel->GetPriorPdf()); } else { if (bModel->GetNuisanceParameters() || sbModel->GetNuisanceParameters() ) { Error("RA2bHypoTestInvDemo","Cannnot run Hybrid calculator because no prior on the nuisance parameter is specified"); return 0; } } } else ((FrequentistCalculator*) hc)->SetToys(ntoys,ntoys); // Get the result RooMsgService::instance().getStream(1).removeTopic(RooFit::NumIntegration); TStopwatch tw; tw.Start(); const RooArgSet * poiSet = sbModel->GetParametersOfInterest(); RooRealVar *poi = (RooRealVar*)poiSet->first(); // fit the data first sbModel->GetPdf()->fitTo(*data); double poihat = poi->getVal(); HypoTestInverter calc(*hc); calc.SetConfidenceLevel(0.95); calc.UseCLs(useCls); calc.SetVerbose(true); // can speed up using proof-lite if (useProof && nworkers > 1) { ProofConfig pc(*w, nworkers, "", kFALSE); toymcs->SetProofConfig(&pc); // enable proof } printf(" npoints = %d, poimin = %7.2f, poimax = %7.2f\n\n", npoints, poimin, poimax ) ; cout << flush ; if ( npoints==1 ) { std::cout << "Evaluating one point : " << poimax << std::endl; calc.RunOnePoint(poimax); } else if (npoints > 0) { if (poimin >= poimax) { // if no min/max given scan between MLE and +4 sigma poimin = int(poihat); poimax = int(poihat + 4 * poi->getError()); } std::cout << "Doing a fixed scan in interval : " << poimin << " , " << poimax << std::endl; calc.SetFixedScan(npoints,poimin,poimax); } else { //poi->setMax(10*int( (poihat+ 10 *poi->getError() )/10 ) ); std::cout << "Doing an automatic scan in interval : " << poi->getMin() << " , " << poi->getMax() << std::endl; } cout << "\n\n right before calc.GetInterval(), ntoys = " << ntoys << " \n\n" << flush ; HypoTestInverterResult * r = calc.GetInterval(); return r; }
void FitterUtils::fit(bool wantplot, bool constPartReco, double fracPartReco_const, ofstream& out, TTree* t, bool update, string plotsfile) { //***************Get the PDFs from the workspace TFile fw(workspacename.c_str()); RooWorkspace* workspace = (RooWorkspace*)fw.Get("workspace"); RooRealVar *B_plus_M = workspace->var("B_plus_M"); RooRealVar *misPT = workspace->var("misPT"); RooRealVar *T = workspace->var("T"); RooRealVar *n = workspace->var("n"); RooRealVar *expoConst = workspace->var("expoConst"); RooRealVar *trueExp = workspace->var("trueExp"); RooRealVar *fractionalErrorJpsiLeak = workspace->var("fractionalErrorJpsiLeak"); cout<<"VALUE OF T IN FIT: "<<T->getVal()<<" +- "<<T->getError()<<endl; cout<<"VALUE OF n IN FIT: "<<n->getVal()<<" +- "<<n->getError()<<endl; RooHistPdf *histPdfSignalZeroGamma = (RooHistPdf *) workspace->pdf("histPdfSignalZeroGamma"); RooHistPdf *histPdfSignalOneGamma = (RooHistPdf *) workspace->pdf("histPdfSignalOneGamma"); RooHistPdf *histPdfSignalTwoGamma = (RooHistPdf *) workspace->pdf("histPdfSignalTwoGamma"); RooHistPdf *histPdfPartReco = (RooHistPdf *) workspace->pdf("histPdfPartReco"); RooHistPdf *histPdfJpsiLeak(0); if(nGenJpsiLeak>0) histPdfJpsiLeak = (RooHistPdf *) workspace->pdf("histPdfJpsiLeak"); RooAbsPdf *combPDF; if (fit2D) { combPDF = new RooPTMVis("combPDF", "combPDF", *misPT, *B_plus_M, *T, *n, *expoConst); } else { combPDF = new RooExponential("combPDF", "combPDF", *B_plus_M, *expoConst); } expoConst->setVal(trueExp->getVal()); RooWorkspace* workspaceGen = (RooWorkspace*)fw.Get("workspaceGen"); RooDataSet* dataGenSignalZeroGamma = (RooDataSet*)workspaceGen->data("dataGenSignalZeroGamma"); RooDataSet* dataGenSignalOneGamma = (RooDataSet*)workspaceGen->data("dataGenSignalOneGamma"); RooDataSet* dataGenSignalTwoGamma = (RooDataSet*)workspaceGen->data("dataGenSignalTwoGamma"); RooDataSet* dataGenPartReco = (RooDataSet*)workspaceGen->data("dataGenPartReco"); RooDataSet* dataGenComb = (RooDataSet*)workspaceGen->data("dataGenComb"); RooDataSet* dataGenJpsiLeak(0); if(nGenJpsiLeak>0) dataGenJpsiLeak = (RooDataSet*)workspaceGen->data("dataGenJpsiLeak"); if(wantplot) { //**************Must get the datasets RooDataSet* dataSetSignalZeroGamma = (RooDataSet*)workspace->data("dataSetSignalZeroGamma"); RooDataSet* dataSetSignalOneGamma = (RooDataSet*)workspace->data("dataSetSignalOneGamma"); RooDataSet* dataSetSignalTwoGamma = (RooDataSet*)workspace->data("dataSetSignalTwoGamma"); RooDataSet* dataSetPartReco = (RooDataSet*)workspace->data("dataSetPartReco"); RooDataSet* dataSetComb = (RooDataSet*)workspace->data("dataSetComb"); RooDataSet* dataSetJpsiLeak = (RooDataSet*)workspace->data("dataSetJpsiLeak"); //**************Plot all the different components cout<<"dataGenSignalZeroGamma: "<<dataGenSignalZeroGamma<<endl; PlotShape(*dataSetSignalZeroGamma, *dataGenSignalZeroGamma, *histPdfSignalZeroGamma, plotsfile, "cSignalZeroGamma", *B_plus_M, *misPT); PlotShape(*dataSetSignalOneGamma, *dataGenSignalOneGamma, *histPdfSignalOneGamma, plotsfile, "cSignalOneGamma", *B_plus_M, *misPT); PlotShape(*dataSetSignalTwoGamma, *dataGenSignalTwoGamma, *histPdfSignalTwoGamma, plotsfile, "cSignalTwoGamma", *B_plus_M, *misPT); PlotShape(*dataSetPartReco, *dataGenPartReco, *histPdfPartReco, plotsfile, "cPartReco", *B_plus_M, *misPT); PlotShape(*dataSetComb, *dataGenComb, *combPDF, plotsfile, "cComb", *B_plus_M, *misPT); if(nGenJpsiLeak>1) PlotShape(*dataSetJpsiLeak, *dataGenJpsiLeak, *histPdfJpsiLeak, plotsfile, "cJpsiLeak", *B_plus_M, *misPT); } //***************Merge datasets RooDataSet* dataGenTot(dataGenPartReco); dataGenTot->append(*dataGenSignalZeroGamma); dataGenTot->append(*dataGenSignalOneGamma); dataGenTot->append(*dataGenSignalTwoGamma); dataGenTot->append(*dataGenComb); if(nGenJpsiLeak>0) dataGenTot->append(*dataGenJpsiLeak); //**************Prepare fitting function RooRealVar nSignal("nSignal", "#signal events", 1.*nGenSignal, nGenSignal-7*sqrt(nGenSignal), nGenSignal+7*sqrt(nGenSignal)); RooRealVar nPartReco("nPartReco", "#nPartReco", 1.*nGenPartReco, nGenPartReco-7*sqrt(nGenPartReco), nGenPartReco+7*sqrt(nGenPartReco)); RooRealVar nComb("nComb", "#nComb", 1.*nGenComb, nGenComb-7*sqrt(nGenComb), nGenComb+7*sqrt(nGenComb)); RooRealVar nJpsiLeak("nJpsiLeak", "#nJpsiLeak", 1.*nGenJpsiLeak, nGenJpsiLeak-7*sqrt(nGenJpsiLeak), nGenJpsiLeak+7*sqrt(nGenJpsiLeak)); RooRealVar fracZero("fracZero", "fracZero",0.5,0,1); RooRealVar fracOne("fracOne", "fracOne",0.5, 0,1); RooFormulaVar fracPartReco("fracPartReco", "nPartReco/nSignal", RooArgList(nPartReco,nSignal)); RooFormulaVar fracOneRec("fracOneRec", "(1-fracZero)*fracOne", RooArgList(fracZero, fracOne)); RooAddPdf histPdfSignal("histPdfSignal", "histPdfSignal", RooArgList(*histPdfSignalZeroGamma, *histPdfSignalOneGamma, *histPdfSignalTwoGamma), RooArgList(fracZero, fracOneRec)); RooArgList pdfList(histPdfSignal, *histPdfPartReco, *combPDF); RooArgList yieldList(nSignal, nPartReco, nComb); if(nGenJpsiLeak>0) { pdfList.add(*histPdfJpsiLeak); yieldList.add(nJpsiLeak); } RooAddPdf totPdf("totPdf", "totPdf", pdfList, yieldList); //**************** Constrain the fraction of zero and one photon int nGenSignalZeroGamma(floor(nGenFracZeroGamma*nGenSignal)); int nGenSignalOneGamma(floor(nGenFracOneGamma*nGenSignal)); int nGenSignalTwoGamma(floor(nGenSignal-nGenSignalZeroGamma-nGenSignalOneGamma)); RooRealVar fracZeroConstMean("fracZeroConstMean", "fracZeroConstMean", nGenSignalZeroGamma*1./nGenSignal); RooRealVar fracZeroConstSigma("fracZeroConstSigma", "fracZeroConstSigma", sqrt(nGenSignalZeroGamma)/nGenSignal); RooGaussian fracZeroConst("fracZeroConst", "fracZeroConst", fracZero, fracZeroConstMean, fracZeroConstSigma); RooRealVar fracOneConstMean("fracOneConstMean", "fracOneConstMean", nGenSignalOneGamma*1./nGenSignal/(1-fracZeroConstMean.getVal())); RooRealVar fracOneConstSigma("fracOneConstSigma", "fracOneConstSigma", sqrt(nGenSignalOneGamma)/nGenSignal/(1-fracZeroConstMean.getVal())); RooGaussian fracOneConst("fracOneConst", "fracOneConst", fracOne, fracOneConstMean, fracOneConstSigma); RooRealVar fracPartRecoMean("fracPartRecoMean", "fracPartRecoMean", nGenPartReco/(1.*nGenSignal)); RooRealVar fracPartRecoSigma("fracPartRecoSigma", "fracPartRecoSigma", fracPartReco_const*fracPartRecoMean.getVal()); RooGaussian fracPartRecoConst("fracPartRecoConst", "fracPartRecoConst", fracPartReco, fracPartRecoMean, fracPartRecoSigma); RooRealVar JpsiLeakMean("JpsiLeakMean", "JpsiLeakMean", nGenJpsiLeak); RooRealVar JpsiLeakSigma("JpsiLeakSigma", "JpsiLeakSigma", nGenJpsiLeak*fractionalErrorJpsiLeak->getVal()); RooGaussian JpsiLeakConst("JpsiLeakConst", "JpsiLeakConst", nJpsiLeak, JpsiLeakMean, JpsiLeakSigma); //Extra TEST CONSTRAINT //RooRealVar combConstMean("combConstMean", "combConstMean", nGenComb); //RooRealVar combConstSigma("combConstSigma", "combConstSigma", 7.7); //RooGaussian combConst("combConst", "combConst", nComb, combConstMean, combConstSigma); //**************** fit RooAbsReal::defaultIntegratorConfig()->setEpsAbs(1e-8) ; RooAbsReal::defaultIntegratorConfig()->setEpsRel(1e-8) ; RooArgSet *par_set = totPdf.getParameters(dataGenTot); initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma, *trueExp, nSignal, nPartReco, nComb, fracZero, fracOne, *expoConst, nJpsiLeak, constPartReco, fracPartRecoSigma); RooArgSet constraints(fracZeroConst, fracOneConst); if (constPartReco) constraints.add(fracPartRecoConst); if(nGenJpsiLeak>0) constraints.add(JpsiLeakConst); RooAbsReal* nll = totPdf.createNLL(*dataGenTot, Extended(), ExternalConstraints(constraints)); RooMinuit minuit(*nll); minuit.setStrategy(2); int migradRes(1); int hesseRes(4); vector<int> migradResVec; vector<int> hesseResVec; double edm(10); int nrefit(0); RooFitResult* fitRes(0); vector<RooFitResult*> fitResVec; bool hasConverged(false); for(int i(0); (i<10) && !hasConverged ; ++i) { initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma, *trueExp, nSignal, nPartReco, nComb, fracZero, fracOne, *expoConst, nJpsiLeak, constPartReco, fracPartRecoSigma); cout<<"FITTING: starting with nsignal = "<<nSignal.getValV()<<" refit nbr. "<<i<<endl; //if(fitRes != NULL && fitRes != 0) delete fitRes; migradRes = minuit.migrad(); hesseRes = minuit.hesse(); fitRes = minuit.save(); edm = fitRes->edm(); fitResVec.push_back(fitRes); migradResVec.push_back(migradRes); hesseResVec.push_back(hesseRes); if( migradRes == 0 && hesseRes == 0 && edm < 1e-4 ) hasConverged = true; ++nrefit; cout<<"Fitting nbr "<<i<<" done. Hesse: "<<hesseRes<<" migrad: "<<migradRes<<" edm: "<<edm<<" minNll: "<<fitRes->minNll()<<endl; } if(!hasConverged) { double minNll(1e20); int minIndex(-1); for(unsigned int i(0); i<fitResVec.size(); ++i) { if( fitResVec.at(i)->minNll() < minNll) { minIndex = i; minNll = fitResVec[i]->minNll(); } } migradRes = migradResVec.at(minIndex); hesseRes = hesseResVec.at(minIndex); cout<<"Fit not converged, choose fit "<<minIndex<<". Hesse: "<<hesseRes<<" migrad: "<<migradRes<<" edm: "<<edm<<" minNll: "<<fitRes->minNll()<<endl; } fillTreeResult(t, fitRes, update, migradRes, hesseRes, hasConverged); for(unsigned int i(0); i<fitResVec.size(); ++i) delete fitResVec.at(i); //totPdf.fitTo(*dataGenTot, Extended(), Save(), Warnings(false)); //*************** output fit status int w(12); out<<setw(w)<<migradRes<<setw(w)<<hesseRes<<setw(w)<<edm<<setw(w)<<nrefit<<endl; if(wantplot) plot_fit_result(plotsfile, totPdf, *dataGenTot); fw.Close(); //delete and return delete nll; delete par_set; delete workspace; delete workspaceGen; delete combPDF; }
void FitterUtils::generate() { //***************Get the PDFs from the workspace TFile fw(workspacename.c_str(), "UPDATE"); RooWorkspace* workspace = (RooWorkspace*)fw.Get("workspace"); RooRealVar *B_plus_M = workspace->var("B_plus_M"); RooRealVar *misPT = workspace->var("misPT"); RooRealVar *T = workspace->var("T"); RooRealVar *n = workspace->var("n"); RooRealVar *expoConst = workspace->var("expoConst"); RooRealVar *trueExp = workspace->var("trueExp"); RooRealVar *fractionalErrorJpsiLeak = workspace->var("fractionalErrorJpsiLeak"); cout<<"VALUE OF T IN GENERATE: "<<T->getVal()<<" +- "<<T->getError()<<endl; cout<<"VALUE OF n IN GENERATE: "<<n->getVal()<<" +- "<<n->getError()<<endl; RooHistPdf *histPdfSignalZeroGamma = (RooHistPdf *) workspace->pdf("histPdfSignalZeroGamma"); RooHistPdf *histPdfSignalOneGamma = (RooHistPdf *) workspace->pdf("histPdfSignalOneGamma"); RooHistPdf *histPdfSignalTwoGamma = (RooHistPdf *) workspace->pdf("histPdfSignalTwoGamma"); RooHistPdf *histPdfPartReco = (RooHistPdf *) workspace->pdf("histPdfPartReco"); RooHistPdf *histPdfJpsiLeak(0); if(nGenJpsiLeak>1) histPdfJpsiLeak = (RooHistPdf *) workspace->pdf("histPdfJpsiLeak"); RooAbsPdf *combPDF; if (fit2D) { combPDF = new RooPTMVis("combPDF", "combPDF", *misPT, *B_plus_M, *T, *n, *expoConst); } else { combPDF = new RooExponential("combPDF", "combPDF", *B_plus_M, *expoConst); } double trueExpConst(trueExp->getValV()); expoConst->setVal(trueExpConst); //***************Prepare generation int nGenSignalZeroGamma(floor(nGenFracZeroGamma*nGenSignal)); int nGenSignalOneGamma(floor(nGenFracOneGamma*nGenSignal)); int nGenSignalTwoGamma(floor(nGenSignal-nGenSignalZeroGamma-nGenSignalOneGamma)); RooArgSet argset2(*B_plus_M); if (fit2D) argset2.add(*misPT); cout<<"Preparing the generation of events 1"; RooRandom::randomGenerator()->SetSeed(); RooAbsPdf::GenSpec* GenSpecSignalZeroGamma = histPdfSignalZeroGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalZeroGamma)); cout<<" 2 "; RooAbsPdf::GenSpec* GenSpecSignalOneGamma = histPdfSignalOneGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalOneGamma)); cout<<" 3 "; RooAbsPdf::GenSpec* GenSpecSignalTwoGamma = histPdfSignalTwoGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalTwoGamma)); cout<<" 4 "; RooAbsPdf::GenSpec* GenSpecPartReco = histPdfPartReco->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenPartReco)); cout<<" 5 "<<endl; RooAbsPdf::GenSpec* GenSpecComb = combPDF->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenComb)); RooAbsPdf::GenSpec* GenSpecJpsiLeak(0); if(nGenJpsiLeak>1) GenSpecJpsiLeak = histPdfJpsiLeak->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenJpsiLeak)); cout<<"Variable loaded:"<<endl; B_plus_M->Print(); expoConst->Print(); //B_plus_DTFM_M_zero->Print(); if (fit2D) misPT->Print(); //***************Generate some datasets cout<<"Generating signal Zero Photon"<<endl; RooDataSet* dataGenSignalZeroGamma = histPdfSignalZeroGamma->generate(*GenSpecSignalZeroGamma);//(argset, 250, false, true, "", false, true); dataGenSignalZeroGamma->SetName("dataGenSignalZeroGamma"); dataGenSignalZeroGamma->SetTitle("dataGenSignalZeroGamma"); cout<<"Generating signal One Photon"<<endl; RooDataSet* dataGenSignalOneGamma = histPdfSignalOneGamma->generate(*GenSpecSignalOneGamma);//(argset, 250, false, true, "", false, true); dataGenSignalOneGamma->SetName("dataGenSignalOneGamma"); dataGenSignalOneGamma->SetTitle("dataGenSignalOneGamma"); cout<<"Generating signal two Photons"<<endl; RooDataSet* dataGenSignalTwoGamma = histPdfSignalTwoGamma->generate(*GenSpecSignalTwoGamma);//(argset, 250, false, true, "", false, true); dataGenSignalTwoGamma->SetName("dataGenSignalTwoGamma"); dataGenSignalTwoGamma->SetTitle("dataGenSignalTwoGamma"); cout<<"Generating combinatorial"<<endl; RooDataSet* dataGenComb = combPDF->generate(*GenSpecComb);//(argset, 100, false, true, "", false, true); dataGenComb->SetName("dataGenComb"); dataGenComb->SetTitle("dataGenComb"); cout<<"Generating PartReco"<<endl; RooDataSet* dataGenPartReco = histPdfPartReco->generate(*GenSpecPartReco);//argset, 160, false, true, "", false, true); dataGenPartReco->SetName("dataGenPartReco"); dataGenPartReco->SetTitle("dataGenPartReco"); RooDataSet* dataGenJpsiLeak(0); if(nGenJpsiLeak>1) { cout<<"Generating Leaking JPsi"<<endl; dataGenJpsiLeak = histPdfJpsiLeak->generate(*GenSpecJpsiLeak);//argset, 160, false, true, "", false, true); dataGenJpsiLeak->SetName("dataGenJpsiLeak"); dataGenJpsiLeak->SetTitle("dataGenJpsiLeak"); } //*************Saving the generated datasets in a workspace RooWorkspace workspaceGen("workspaceGen", "workspaceGen"); workspaceGen.import(*dataGenSignalZeroGamma); workspaceGen.import(*dataGenSignalOneGamma); workspaceGen.import(*dataGenSignalTwoGamma); workspaceGen.import(*dataGenComb); workspaceGen.import(*dataGenPartReco); if(nGenJpsiLeak>1) workspaceGen.import(*dataGenJpsiLeak); workspaceGen.Write("", TObject::kOverwrite); //delete workspace; fw.Close(); delete dataGenSignalZeroGamma; delete dataGenSignalOneGamma; delete dataGenSignalTwoGamma; delete dataGenComb; delete dataGenPartReco; if(nGenJpsiLeak>1) delete dataGenJpsiLeak; delete GenSpecSignalZeroGamma; delete GenSpecSignalOneGamma; delete GenSpecSignalTwoGamma; delete GenSpecComb; delete GenSpecPartReco; delete combPDF; if(nGenJpsiLeak>1) delete GenSpecJpsiLeak; delete histPdfSignalZeroGamma; delete histPdfSignalOneGamma; delete histPdfSignalTwoGamma; delete histPdfPartReco; if(nGenJpsiLeak>1) delete histPdfJpsiLeak; }
int compute(RooFitResult* fit, int nbdata, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin, double et_plateau, double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin, bool draw, bool verbose) { // Extract fit parameters // std::cout<<"erereo4"<<std::endl; RooArgList param = fit->floatParsFinal() ; std::cout<<"erereo6"<<std::endl; double err[5] ; double mu[5] ; for(Int_t i = 0; i < param.getSize(); i++) { RooRealVar* var = ( dynamic_cast<RooRealVar*>( param.at(i) ) ); //var->Print() ; mu[i] = var->getVal() ; err[i] = var->getError() ; } std::cout<<"erereo5"<<std::endl; double min, max; min = mu[0]-5*err[0] ; if (mu[0]-5*err[0]<0) min = 0. ; RooRealVar alpha("alpha","#alpha",mu[0],min,mu[0]+5*err[0]); min = mu[1]-5*err[1] ; if (mu[1]-5*err[1]<5) min = 5. ; RooRealVar mean("mean","mean",mu[1],min,mu[1]+5*err[1]); min = mu[2]-5*err[2] ; if (mu[2]-5*err[2]<1) min = 1. ; RooRealVar n("n","n",mu[2],min,mu[2]+5*err[2]); min = mu[3]-5*err[3] ; if (mu[3]-5*err[3]<0.6) min = 0.6 ; max = mu[3]+5*err[3] ; if (mu[3]+5*err[3]>1.) max = 1. ; RooRealVar norm("norm","N",mu[3],min,max); min = mu[4]-5*err[4] ; if (mu[4]-5*err[4]<0.) min = 0. ; RooRealVar sigma("sigma","#sigma",mu[4],min,mu[4]+5*err[4]); RooRealVar xaxis("x","x",0,150) ; // Create PDF and generate nbdata sets of CB parameters RooAbsPdf* parabPdf = fit->createHessePdf(RooArgSet(norm,alpha,n,mean,sigma)) ; RooDataSet* data = parabPdf->generate(RooArgSet(norm,alpha,n,mean,sigma),nbdata) ; // Generate histo to extract error bar on efficiency(xaxis) xaxis = et_plateau ; cout << "Generate histo to extract error bars" << endl; genHisto(nbdata, data, nEff, eff, et, et_errmax, et_errmin, eff_plateau, eff_plateau_errmax, eff_plateau_errmin, xaxis, mean, sigma, alpha, n, norm, draw, verbose); /* int genHisto(int nbdata, RooDataSet* data, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin, double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin, RooRealVar xaxis, RooRealVar mean, RooRealVar sigma, RooRealVar alpha, RooRealVar n, RooRealVar norm, bool draw, bool verbose) int compute(RooFitResult* fit, int nbdata, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin, double et_plateau, double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin, bool draw, bool verbose) */ return 1; }
void printMassFrom2DParameters(RooWorkspace myws, TPad* Pad, bool isPbPb, string pdfName, bool isWeighted) { Pad->cd(); TLatex *t = new TLatex(); t->SetNDC(); t->SetTextSize(0.026); float dy = 0.025; RooArgSet* Parameters = (RooArgSet*)myws.pdf(pdfName.c_str())->getParameters(RooArgSet(*myws.var("invMass"), *myws.var("ctau"), *myws.var("ctauErr")))->selectByAttrib("Constant",kFALSE); TIterator* parIt = Parameters->createIterator(); for (RooRealVar* it = (RooRealVar*)parIt->Next(); it!=NULL; it = (RooRealVar*)parIt->Next() ) { stringstream ss(it->GetName()); string s1, s2, s3, label; getline(ss, s1, '_'); getline(ss, s2, '_'); getline(ss, s3, '_'); // Parse the parameter's labels if(s1=="invMass" || s1=="ctauErr" || s1=="ctau"){continue;} else if(s1=="MassRatio"){continue;} else if(s1=="One"){continue;} else if(s1=="mMin"){continue;} else if(s1=="mMax"){continue;} if(s1=="RFrac2Svs1S"){ s1="R_{#psi(2S)/J/#psi}"; } else if(s1=="rSigma21"){ s1="(#sigma_{2}/#sigma_{1})"; } else if(s1.find("sigma")!=std::string::npos || s1.find("lambda")!=std::string::npos || s1.find("alpha")!=std::string::npos){ s1=Form("#%s",s1.c_str()); } if(s2=="PbPbvsPP") { s2="PbPb/PP"; } else if(s2=="Jpsi") { s2="J/#psi"; } else if(s2=="Psi2S") { s2="#psi(2S)"; } else if(s2=="Bkg") { s2="bkg"; } else if(s2=="CtauRes") { continue; } else if(s2=="JpsiNoPR") { continue; } else if(s2=="JpsiPR") { continue; } else if(s2=="Psi2SNoPR"){ continue; } else if(s2=="Psi2SPR") { continue; } else if(s2=="BkgNoPR") { continue; } else if(s2=="BkgPR") { continue; } else if(s2=="Bkg" && (s1=="N" || s1=="b")) { continue; } else {continue;} if(s3!=""){ label=Form("%s_{%s}^{%s}", s1.c_str(), s2.c_str(), s3.c_str()); } else { label=Form("%s^{%s}", s1.c_str(), s2.c_str()); } // Print the parameter's results if(s1=="N"){ t->DrawLatex(0.20, 0.76-dy, Form((isWeighted?"%s = %.6f#pm%.6f ":"%s = %.0f#pm%.0f "), label.c_str(), it->getValV(), it->getError())); dy+=0.045; } else if(s1.find("#sigma_{2}/#sigma_{1}")!=std::string::npos){ t->DrawLatex(0.20, 0.76-dy, Form("%s = %.3f#pm%.3f ", label.c_str(), it->getValV(), it->getError())); dy+=0.045; } else if(s1.find("sigma")!=std::string::npos){ t->DrawLatex(0.20, 0.76-dy, Form("%s = %.2f#pm%.2f MeV/c^{2}", label.c_str(), it->getValV()*1000., it->getError()*1000.)); dy+=0.045; } else if(s1.find("lambda")!=std::string::npos){ t->DrawLatex(0.20, 0.76-dy, Form("%s = %.4f#pm%.4f", label.c_str(), it->getValV(), it->getError())); dy+=0.045; } else if(s1.find("m")!=std::string::npos){ t->DrawLatex(0.20, 0.76-dy, Form("%s = %.5f#pm%.5f GeV/c^{2}", label.c_str(), it->getValV(), it->getError())); dy+=0.045; } else { t->DrawLatex(0.20, 0.76-dy, Form("%s = %.4f#pm%.4f", label.c_str(), it->getValV(), it->getError())); dy+=0.045; } } };
void bfractionVsCent(char *tagger="discr_ssvHighEff", double workingPoint=2., int fixCL=0, char *taggerName="ssvHighEff", float ptlo=80, float pthi=100, float etalo=0., float etahi=2.) { gStyle->SetOptStat(0); gStyle->SetOptTitle(0); gStyle->SetLabelFont(43,"xyz"); gStyle->SetLabelSize(20,"xyz"); gStyle->SetTitleFont(43,"xyz"); gStyle->SetTitleSize(26,"xyz"); gStyle->SetTitleOffset(1.0,"xy"); gROOT->ForceStyle(1); int doLTJP=1; int doLTCSV=0; const int nBins = 2; double centBin[nBins+1] = {0,30,100}; //const int nBins = 3; //double centBin[nBins+1] = {0,20,50,100}; Double_t bPurMC, bPurData, bEffMC, bEffDataLTJP, bEffDataLTCSV, taggedFracData, bFracMC, bFracData, bFracDataLTJP, bFracDataLTCSV, bFracJPdirect; Double_t bPurMCError, bPurDataError, bEffMCError, bEffDataLTJPError, bEffDataLTCSVError, taggedFracDataError, bFracMCError, bFracDataError, bFracDataLTJPError, bFracDataLTCSVError, bFracJPdirectError; Enumerations numbers; TH1D *hBPurityData = new TH1D("hBPurityData","hBPurityData;Centrality;B-Tagging purity",nBins,centBin); TH1D *hBPurityMC = new TH1D("hBPurityMC","hBPurityMC;Centrality;B-Tagging purity",nBins,centBin); TH1D *hBEfficiencyMC = new TH1D("hBEfficiencyMC","hBEfficiencyMC;Centrality;B-Tagging efficiency",nBins,centBin); TH1D *hBEfficiencyDataLTJP = new TH1D("hBEfficiencyDataLTJP","hBEfficiencyDataLTJP;Centrality;B-Tagging efficiency",nBins,centBin); TH1D *hBEfficiencyDataLTCSV = new TH1D("hBEfficiencyDataLTCSV","hBEfficiencyDataLTCSV;Centrality;B-Tagging efficiency",nBins,centBin); TH1D *hBFractionMC = new TH1D("hBFractionMC","hBFractionMC;Centrality;B-jet fraction",nBins,centBin); TH1D *hBFractionData = new TH1D("hBFractionData","hBFractionData;Centrality;B-jet fraction",nBins,centBin); TH1D *hBFractionDataLTJP = new TH1D("hBFractionDataLTJP","hBFractionDataLTJP;Centrality;B-jet fraction",nBins,centBin); TH1D *hBFractionDataLTCSV = new TH1D("hBFractionDataLTCSV","hBFractionDataLTCSV;Centrality;B-jet fraction",nBins,centBin); TH1D *hBFractionJPdirect = new TH1D("hBFractionJPdirect","hBFractionJPdirect;Centrality;B-jet fraction",nBins,centBin); int ncol=1; int nrow=1; if(nBins==3||nBins==2){ ncol=nBins; } if(nBins==4){ ncol=nBins/2; nrow=nBins/2; } TCanvas *c1=new TCanvas("c1","c1",1200,600); //c1->Divide(ncol,nrow,0,0); c1->Divide(ncol,nrow); TCanvas *c2=new TCanvas("c2","c2",1200,600); //c2->Divide(ncol,nrow,0,0); c2->Divide(ncol,nrow); TCanvas *c3=new TCanvas("c3","c3",1200,600); //c3->Divide(ncol,nrow,0,0); c3->Divide(ncol,nrow); TCanvas *c4=new TCanvas("c4","c4",1200,600); //c4->Divide(ncol,nrow,0,0); c4->Divide(ncol,nrow); TCanvas *cCount = new TCanvas("cCount","cCount",600,600); for (int n=0;n<nBins;n++) { cout<<"Processing jet centrality bin ["<<centBin[n]<<","<<centBin[n+1]<<"] ..."<<endl; cCount->cd(); cout<<"centBin[n]: "<<centBin[n]<<" centBin[n+1]: "<<centBin[n+1]<<" tagger: "<<tagger<<" workingPoint: "<<workingPoint<<" ptlo: "<<ptlo<<" pthi: "<<pthi<<" etalo: "<<etalo<<" etahi: "<<etahi<<endl; numbers = count(centBin[n],centBin[n+1],tagger,workingPoint,ptlo,pthi,etalo,etahi); c1->cd(n+1); c1->GetPad(n+1)->SetLogy(); RooRealVar fitSvtxmTag = bfractionFit(fixCL,"svtxm",0,6,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,workingPoint,6,"b-tagged sample (SSVHE > 2)",9e3); //RooRealVar fitSvtxmTag = bfractionFit(fixCL,"svtxm",0,6,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,workingPoint,10,Form("b-tagged sample (%s at %.1f)",taggerName,workingPoint)); //RooRealVar fitJpDirect = bfractionFit(fixCL,"discr_prob",0,3,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,-2,10,"inclusive sample",5e4); c2->cd(n+1); c2->GetPad(n+1)->SetLogy(); RooRealVar fitJpDirect = bfractionFit(fixCL,"discr_prob",0.0,3.,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,"discr_prob",0.,3.,"inclusive sample",4e5); if (doLTJP) { c3->cd(n+1); c3->GetPad(n+1)->SetLogy(); RooRealVar fitJpBeforetag = bfractionFit(fixCL,"discr_prob",0.0,3.,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,"discr_prob",0,3.,"jets with JP info",4e5); c4->cd(n+1); c4->GetPad(n+1)->SetLogy(); RooRealVar fitJpTag = bfractionFit(fixCL,"discr_prob",0.0,3.,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,workingPoint,6,"b-tagged sample (SSVHE > 2)",4e5); } if (doLTCSV) { RooRealVar fitCsvBeforetag = bfractionFit(fixCL,"discr_csvSimple",0,1,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,-2,10,"jets with CSV info",4e5); RooRealVar fitCsvTag = bfractionFit(fixCL,"discr_csvSimple",0,1,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,workingPoint,10,"b-tagged sample (SSVHE > 2)",4e5); } taggedFracData = numbers.nTaggedJetsData / (numbers.nTaggedJetsData+numbers.nUntaggedJetsData); taggedFracDataError = fracError(numbers.nTaggedJetsData,numbers.nUntaggedJetsData,numbers.nTaggedJetsDataError,numbers.nUntaggedJetsDataError); //* --- b-tagging purity --- bPurMC = numbers.nTaggedBjetsMC / numbers.nTaggedJetsMC; cout<<" bPurMC "<<bPurMC<<" numbers.nTaggedBjetsMC "<<numbers.nTaggedBjetsMC<<" numbers.nTaggedJetsMC "<<numbers.nTaggedJetsMC<<endl; bPurMCError = fracError(numbers.nTaggedBjetsMC,numbers.nTaggedNonBjetsMC,numbers.nTaggedBjetsMCError,numbers.nTaggedNonBjetsMCError); bPurData = fitSvtxmTag.getVal(); bPurDataError = fitSvtxmTag.getError(); hBPurityMC->SetBinContent(n+1,bPurMC); hBPurityMC->SetBinError(n+1,bPurMCError); hBPurityData->SetBinContent(n+1,bPurData); hBPurityData->SetBinError(n+1,bPurDataError); //*/ //* --- b-tagging efficiency --- bEffMC = numbers.nTaggedBjetsMC / numbers.nBjetsMC; bEffMCError = fracError(numbers.nTaggedBjetsMC,numbers.nUntaggedBjetsMC,numbers.nTaggedBjetsMCError,numbers.nUntaggedBjetsMCError); hBEfficiencyMC->SetBinContent(n+1,bEffMC); hBEfficiencyMC->SetBinError(n+1,bEffMCError); if (doLTJP) { bEffDataLTJP = taggedFracData * numbers.cbForJP * fitJpTag.getVal() / fitJpBeforetag.getVal(); bEffDataLTJPError = prodError(taggedFracData,fitJpTag.getVal(),taggedFracDataError,fitJpTag.getError()) * numbers.cbForJP / fitJpBeforetag.getVal(); hBEfficiencyDataLTJP->SetBinContent(n+1,bEffDataLTJP); hBEfficiencyDataLTJP->SetBinError(n+1,bEffDataLTJPError); } if (doLTCSV) { bEffDataLTCSV = taggedFracData * numbers.cbForCSV * fitCsvTag.getVal() / fitCsvBeforetag.getVal(); bEffDataLTCSVError = prodError(taggedFracData,fitCsvTag.getVal(),taggedFracDataError,fitCsvTag.getError()) * numbers.cbForCSV / fitCsvBeforetag.getVal(); hBEfficiencyDataLTCSV->SetBinContent(n+1,bEffDataLTCSV); hBEfficiencyDataLTCSV->SetBinError(n+1,bEffDataLTCSVError); } //* --- b fraction --- bFracMC = numbers.nBjetsMC / numbers.nJetsMC; //bFracMC = numbers.nTaggedJetsMC * bPurMC / (bEffMC * numbers.nJetsMC); // for check : same as previous bFracMCError = fracError(numbers.nBjetsMC,numbers.nNonBjetsMC,numbers.nBjetsMCError,numbers.nNonBjetsMCError); hBFractionMC->SetBinContent(n+1,bFracMC); hBFractionMC->SetBinError(n+1,bFracMCError); bFracData = taggedFracData * bPurData / bEffMC; // efficiency from MC bFracDataError = prodError(taggedFracData,bPurData,taggedFracDataError,bPurDataError) / bEffMC; // stat.error from purity and tagged-fraction (assumed independent) //bFracDataError = bFracData * bPurDataError / bPurData; // stat.error only from purity hBFractionData->SetBinContent(n+1,bFracData); hBFractionData->SetBinError(n+1,bFracDataError); if (doLTJP) { bFracDataLTJP = taggedFracData * bPurData / bEffDataLTJP ; // efficiency from LTJP method bFracDataLTJPError = prodError(taggedFracData,bPurData,taggedFracDataError,bPurDataError) / bEffDataLTJP; // stat.error from purity and tagged-fraction (assumed independent) //bFracDataLTJPError = bFracDataLTJP * bPurDataError / bPurData; // stat.error only from purity hBFractionDataLTJP->SetBinContent(n+1,bFracDataLTJP); hBFractionDataLTJP->SetBinError(n+1,bFracDataLTJPError); } if (doLTCSV) { bFracDataLTCSV = taggedFracData * bPurData / bEffDataLTCSV; // efficiency from LTCSV method bFracDataLTCSVError = prodError(taggedFracData,bPurData,taggedFracDataError,bPurDataError) / bEffDataLTCSV; // stat.error from purity and tagged-fraction (assumed independent) //bFracDataLTCSVError = bFracDataLTCSV * bPurDataError / bPurData; // stat.error only from purity hBFractionDataLTCSV->SetBinContent(n+1,bFracDataLTCSV); hBFractionDataLTCSV->SetBinError(n+1,bFracDataLTCSVError); } bFracJPdirect = fitJpDirect.getVal(); bFracJPdirectError = fitJpDirect.getError(); hBFractionJPdirect->SetBinContent(n+1,bFracJPdirect); hBFractionJPdirect->SetBinError(n+1,bFracJPdirectError); //*/ //* cout<<"nTaggedJetsMC "<<numbers.nTaggedJetsMC<<endl; cout<<"nUntaggedJetsMC "<<numbers.nUntaggedJetsMC<<endl; cout<<"nJetsMC "<<numbers.nJetsMC<<endl; cout<<"nTaggedBjetsMC "<<numbers.nTaggedBjetsMC<<endl; cout<<"nUntaggedBjetsMC "<<numbers.nUntaggedBjetsMC<<endl; cout<<"nBjetsMC "<<numbers.nBjetsMC<<endl; cout<<"nNonBjetsMC "<<numbers.nNonBjetsMC<<endl; cout<<"nTaggedNonBjetsMC "<<numbers.nTaggedNonBjetsMC<<endl; cout<<"nTaggedJetsData "<<numbers.nTaggedJetsData<<endl; cout<<"nUntaggedJetsData "<<numbers.nUntaggedJetsData<<endl; cout<<"bPurMC "<<bPurMC<<endl; cout<<"bPurData "<<bPurData<<endl; cout<<"bEffMC "<<bEffMC<<endl; cout<<"CbForJP "<<numbers.cbForJP<<endl; cout<<"bEffDataLTJP "<<bEffDataLTJP<<endl; cout<<"CbForCSV "<<numbers.cbForCSV<<endl; cout<<"bEffDataLTCSV "<<bEffDataLTCSV<<endl; cout<<"bFracMC "<<bFracMC<<endl; cout<<"bFracData "<<bFracData<<endl; cout<<"bFracDataLTJP "<<bFracDataLTJP<<endl; cout<<"bFracDataLTCSV "<<bFracDataLTCSV<<endl; cout<<"bFracJPdirect "<<bFracJPdirect<<endl; cout<<endl; //*/ } TLegend *legPur = new TLegend(0.4,0.15,0.85,0.3,Form("Purity of b-tagged sample (%s at %.1f)",taggerName,workingPoint)); legPur->SetBorderSize(0); //legPur->SetFillColor(kGray); legPur->SetFillStyle(0); legPur->AddEntry(hBPurityMC,"MC Input","pl"); legPur->AddEntry(hBPurityData,"Data","pl"); TCanvas *cBPurity = new TCanvas("cBPurity","b purity",600,600); hBPurityMC->SetAxisRange(0,1,"Y"); hBPurityMC->SetTitleOffset(1.3,"Y"); hBPurityMC->SetLineColor(2); hBPurityMC->SetMarkerColor(2); hBPurityMC->SetMarkerStyle(21); hBPurityMC->Draw(); hBPurityData->SetLineColor(1); hBPurityData->SetMarkerColor(1); hBPurityData->SetMarkerStyle(20); hBPurityData->Draw("same"); legPur->Draw(); //cBPurity->SaveAs("purity.gif"); TLegend *legEff = new TLegend(0.4,0.65,0.85,0.8,Form("Efficiency for tagging b-jets (%s at %.1f)",taggerName,workingPoint)); legEff->SetBorderSize(0); //legEff->SetFillColor(kGray); legEff->SetFillStyle(0); legEff->AddEntry(hBEfficiencyMC,"MC Efficiency","pl"); if (doLTJP) legEff->AddEntry(hBEfficiencyDataLTJP,"LT method (JP)","pl"); if (doLTCSV) legEff->AddEntry(hBEfficiencyDataLTCSV,"LT method (CSV)","pl"); TCanvas *cBEfficiency = new TCanvas("cBEfficiency","B-Tagging efficiency",600,600); hBEfficiencyMC->SetAxisRange(0,1,"Y"); hBEfficiencyMC->SetTitleOffset(1.3,"Y"); hBEfficiencyMC->SetLineColor(2); hBEfficiencyMC->SetMarkerColor(2); hBEfficiencyMC->SetMarkerStyle(21); hBEfficiencyMC->Draw(); if (doLTJP) { hBEfficiencyDataLTJP->SetLineColor(8); hBEfficiencyDataLTJP->SetMarkerColor(8); hBEfficiencyDataLTJP->SetMarkerStyle(20); hBEfficiencyDataLTJP->Draw("same"); } if (doLTCSV) { hBEfficiencyDataLTCSV->SetLineColor(7); hBEfficiencyDataLTCSV->SetMarkerColor(7); hBEfficiencyDataLTCSV->SetMarkerStyle(20); hBEfficiencyDataLTCSV->Draw("same"); } legEff->Draw(); //cBEfficiency->SaveAs("efficiency.gif"); TLegend *legFrac = new TLegend(0.25,0.15,0.85,0.3); legFrac->SetBorderSize(0); //legFrac->SetFillColor(kGray); legFrac->SetFillStyle(0); legFrac->AddEntry(hBFractionMC,"MC Input","pl"); legFrac->AddEntry(hBFractionData,Form("%s at %.1f + pur. from SV mass + eff. from MC",taggerName,workingPoint),"pl"); if (doLTJP) legFrac->AddEntry(hBFractionDataLTJP,Form("%s at %.1f + pur. from SV mass + eff. from LT (JP)",taggerName,workingPoint),"pl"); if (doLTCSV) legFrac->AddEntry(hBFractionDataLTCSV,Form("%s at %.1f + pur. from SV mass + eff. from LT (CSV)",taggerName,workingPoint),"pl"); legFrac->AddEntry(hBFractionJPdirect,"Direct fit to JP","pl"); TCanvas *cBFraction = new TCanvas("cBFraction","B-jet fraction",600,600); hBFractionMC->SetAxisRange(0,0.03,"Y"); hBFractionMC->SetTitleOffset(1.8,"Y"); hBFractionMC->SetLineColor(2); hBFractionMC->SetMarkerColor(2); hBFractionMC->SetMarkerStyle(21); hBFractionMC->Draw(); hBFractionData->SetLineColor(1); hBFractionData->SetMarkerColor(1); hBFractionData->SetMarkerStyle(20); hBFractionData->Draw("same"); if (doLTJP) { hBFractionDataLTJP->SetLineColor(8); hBFractionDataLTJP->SetMarkerColor(8); hBFractionDataLTJP->SetMarkerStyle(20); hBFractionDataLTJP->Draw("same"); } if (doLTCSV) { hBFractionDataLTCSV->SetLineColor(7); hBFractionDataLTCSV->SetMarkerColor(7); hBFractionDataLTCSV->SetMarkerStyle(20); hBFractionDataLTCSV->Draw("same"); } hBFractionJPdirect->SetLineColor(4); hBFractionJPdirect->SetMarkerColor(4); hBFractionJPdirect->SetMarkerStyle(20); hBFractionJPdirect->Draw("same"); legFrac->Draw(); //cBFraction->SaveAs("bfraction.gif"); TFile *fout = new TFile(Form("output/bFractionMerged_%sat%.1fFixCL%d_centDep.root",taggerName,workingPoint,fixCL),"recreate"); hBFractionMC->Write(); hBFractionData->Write(); if (doLTJP) hBFractionDataLTJP->Write(); if (doLTCSV) hBFractionDataLTCSV->Write(); hBFractionJPdirect->Write(); fout->Close(); //c1->SaveAs(Form("gifs/svtxMassFit_%s.gif",fixCL?"CLfixed":"CLfree")); //c2->SaveAs(Form("gifs/jpDirectFit_%s.gif",fixCL?"CLfixed":"CLfree")); //c3->SaveAs(Form("gifs/jpBeforeTag_%s.gif",fixCL?"CLfixed":"CLfree")); //c4->SaveAs(Form("gifs/jpAfterTag_%s.gif",fixCL?"CLfixed":"CLfree")); }