/// /// Perform a couple of consistency checks to make it easier /// to find bugs: /// - check if all observables end with '_obs' /// - check if all predicted observables end with '_th' /// - check if the 'observables' and 'theory' lists are correctly ordered /// bool PDF_Abs::checkConsistency() { if ( m_isCrossCorPdf ) return true; bool allOk = true; // check if all observables end with '_obs' TIterator* it = observables->createIterator(); while ( RooRealVar* p = (RooRealVar*)it->Next() ){ TString pObsName = p->GetName(); pObsName.ReplaceAll(uniqueID,""); if ( !pObsName.EndsWith("_obs") ){ cout << "PDF_Abs::checkConsistency() : " << name << " : observable " << p->GetName() << " doesn't end with '_obs'" << endl; allOk = false; } } // check if all predicted observables end with '_th' delete it; it = theory->createIterator(); while ( RooRealVar* p = (RooRealVar*)it->Next() ){ TString pThName = p->GetName(); pThName.ReplaceAll(uniqueID,""); if ( !pThName.EndsWith("_th") ){ cout << "PDF_Abs::checkConsistency() : " << name << " : theory " << p->GetName() << " doesn't end with '_th'" << endl; allOk = false; } } // check if the 'observables' and 'theory' lists are correctly ordered for ( int i=0; i<nObs; i++ ){ RooAbsArg* pTh = theory->at(i); TString base = pTh->GetName(); base.ReplaceAll("_th",""); base.ReplaceAll(uniqueID,""); TString pObsName = observables->at(i)->GetName(); pObsName.ReplaceAll(uniqueID,""); if ( pObsName != base+"_obs"){ cout << "PDF_Abs::checkConsistency() : " << name << " : " << pTh->GetName() << " doesn't match its observable." << endl; cout << " Expected '" << base+"_obs" << "'. Found '" << pObsName << "'." << endl; cout << " Check ordering of the 'theory' and 'observables' lists!" << endl; allOk = false; } } return allOk; }
RooWorkspace* makeInvertedANFit(TTree* tree, float forceSigma=-1, bool constrainMu=false, float forceMu=-1) { RooWorkspace *ws = new RooWorkspace("ws",""); std::vector< TString (*)(TString, RooRealVar&, RooWorkspace&) > bkgPdfList; bkgPdfList.push_back(makeSingleExp); bkgPdfList.push_back(makeDoubleExp); #if DEBUG==0 //bkgPdfList.push_back(makeTripleExp); bkgPdfList.push_back(makeModExp); bkgPdfList.push_back(makeSinglePow); bkgPdfList.push_back(makeDoublePow); bkgPdfList.push_back(makePoly2); bkgPdfList.push_back(makePoly3); #endif RooRealVar mgg("mgg","m_{#gamma#gamma}",103,160,"GeV"); mgg.setBins(38); mgg.setRange("sideband_low", 103,120); mgg.setRange("sideband_high",131,160); mgg.setRange("signal",120,131); RooRealVar MR("MR","",0,3000,"GeV"); MR.setBins(60); RooRealVar Rsq("t1Rsq","",0,1,"GeV"); Rsq.setBins(20); RooRealVar hem1_M("hem1_M","",-1,2000,"GeV"); hem1_M.setBins(40); RooRealVar hem2_M("hem2_M","",-1,2000,"GeV"); hem2_M.setBins(40); RooRealVar ptgg("ptgg","p_{T}^{#gamma#gamma}",0,500,"GeV"); ptgg.setBins(50); RooDataSet data("data","",tree,RooArgSet(mgg,MR,Rsq,hem1_M,hem2_M,ptgg)); RooDataSet* blind_data = (RooDataSet*)data.reduce("mgg<121 || mgg>130"); std::vector<TString> tags; //fit many different background models for(auto func = bkgPdfList.begin(); func != bkgPdfList.end(); func++) { TString tag = (*func)("bonly",mgg,*ws); tags.push_back(tag); ws->pdf("bonly_"+tag+"_ext")->fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE),RooFit::Range("sideband_low,sideband_high")); RooFitResult* bres = ws->pdf("bonly_"+tag+"_ext")->fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE),RooFit::Range("sideband_low,sideband_high")); bres->SetName(tag+"_bonly_fitres"); ws->import(*bres); //make blinded fit RooPlot *fmgg_b = mgg.frame(); blind_data->plotOn(fmgg_b,RooFit::Range("sideband_low,sideband_high")); TBox blindBox(121,fmgg_b->GetMinimum()-(fmgg_b->GetMaximum()-fmgg_b->GetMinimum())*0.015,130,fmgg_b->GetMaximum()); blindBox.SetFillColor(kGray); fmgg_b->addObject(&blindBox); ws->pdf("bonly_"+tag+"_ext")->plotOn(fmgg_b,RooFit::LineColor(kRed),RooFit::Range("Full"),RooFit::NormRange("sideband_low,sideband_high")); fmgg_b->SetName(tag+"_blinded_frame"); ws->import(*fmgg_b); delete fmgg_b; //set all the parameters constant RooArgSet* vars = ws->pdf("bonly_"+tag)->getVariables(); RooFIter iter = vars->fwdIterator(); RooAbsArg* a; while( (a = iter.next()) ){ if(string(a->GetName()).compare("mgg")==0) continue; static_cast<RooRealVar*>(a)->setConstant(kTRUE); } //make the background portion of the s+b fit (*func)("b",mgg,*ws); RooRealVar sigma(tag+"_s_sigma","",5,0,100); if(forceSigma!=-1) { sigma.setVal(forceSigma); sigma.setConstant(true); } RooRealVar mu(tag+"_s_mu","",126,120,132); if(forceMu!=-1) { mu.setVal(forceMu); mu.setConstant(true); } RooGaussian sig(tag+"_sig_model","",mgg,mu,sigma); RooRealVar Nsig(tag+"_sb_Ns","",5,0,100); RooRealVar Nbkg(tag+"_sb_Nb","",100,0,100000); RooRealVar HiggsMass("HiggsMass","",125.1); RooRealVar HiggsMassError("HiggsMassError","",0.24); RooGaussian HiggsMassConstraint("HiggsMassConstraint","",mu,HiggsMass,HiggsMassError); RooAddPdf fitModel(tag+"_sb_model","",RooArgList( *ws->pdf("b_"+tag), sig ),RooArgList(Nbkg,Nsig)); RooFitResult* sbres; RooAbsReal* nll; if(constrainMu) { fitModel.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint))); sbres = fitModel.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint))); nll = fitModel.createNLL(data,RooFit::NumCPU(4),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint))); } else { fitModel.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE)); sbres = fitModel.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE)); nll = fitModel.createNLL(data,RooFit::NumCPU(4),RooFit::Extended(kTRUE)); } sbres->SetName(tag+"_sb_fitres"); ws->import(*sbres); ws->import(fitModel); RooPlot *fmgg = mgg.frame(); data.plotOn(fmgg); fitModel.plotOn(fmgg); ws->pdf("b_"+tag+"_ext")->plotOn(fmgg,RooFit::LineColor(kRed),RooFit::Range("Full"),RooFit::NormRange("Full")); fmgg->SetName(tag+"_frame"); ws->import(*fmgg); delete fmgg; RooMinuit(*nll).migrad(); RooPlot *fNs = Nsig.frame(0,25); fNs->SetName(tag+"_Nsig_pll"); RooAbsReal *pll = nll->createProfile(Nsig); //nll->plotOn(fNs,RooFit::ShiftToZero(),RooFit::LineColor(kRed)); pll->plotOn(fNs); ws->import(*fNs); delete fNs; RooPlot *fmu = mu.frame(125,132); fmu->SetName(tag+"_mu_pll"); RooAbsReal *pll_mu = nll->createProfile(mu); pll_mu->plotOn(fmu); ws->import(*fmu); delete fmu; } RooArgSet weights("weights"); RooArgSet pdfs_bonly("pdfs_bonly"); RooArgSet pdfs_b("pdfs_b"); RooRealVar minAIC("minAIC","",1E10); //compute AIC stuff for(auto t = tags.begin(); t!=tags.end(); t++) { RooAbsPdf *p_bonly = ws->pdf("bonly_"+*t); RooAbsPdf *p_b = ws->pdf("b_"+*t); RooFitResult *sb = (RooFitResult*)ws->obj(*t+"_bonly_fitres"); RooRealVar k(*t+"_b_k","",p_bonly->getParameters(RooArgSet(mgg))->getSize()); RooRealVar nll(*t+"_b_minNll","",sb->minNll()); RooRealVar Npts(*t+"_b_N","",blind_data->sumEntries()); RooFormulaVar AIC(*t+"_b_AIC","2*@0+2*@1+2*@1*(@1+1)/(@2-@1-1)",RooArgSet(nll,k,Npts)); ws->import(AIC); if(AIC.getVal() < minAIC.getVal()) { minAIC.setVal(AIC.getVal()); } //aicExpSum+=TMath::Exp(-0.5*AIC.getVal()); //we will need this precomputed for the next step pdfs_bonly.add(*p_bonly); pdfs_b.add(*p_b); } ws->import(minAIC); //compute the AIC weight float aicExpSum=0; for(auto t = tags.begin(); t!=tags.end(); t++) { RooFormulaVar *AIC = (RooFormulaVar*)ws->obj(*t+"_b_AIC"); aicExpSum+=TMath::Exp(-0.5*(AIC->getVal()-minAIC.getVal())); //we will need this precomputed for the next step } std::cout << "aicExpSum: " << aicExpSum << std::endl; for(auto t = tags.begin(); t!=tags.end(); t++) { RooFormulaVar *AIC = (RooFormulaVar*)ws->obj(*t+"_b_AIC"); RooRealVar *AICw = new RooRealVar(*t+"_b_AICWeight","",TMath::Exp(-0.5*(AIC->getVal()-minAIC.getVal()))/aicExpSum); if( TMath::IsNaN(AICw->getVal()) ) {AICw->setVal(0);} ws->import(*AICw); std::cout << *t << ": " << AIC->getVal()-minAIC.getVal() << " " << AICw->getVal() << std::endl; weights.add(*AICw); } RooAddPdf bonly_AIC("bonly_AIC","",pdfs_bonly,weights); RooAddPdf b_AIC("b_AIC","",pdfs_b,weights); //b_AIC.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE),RooFit::Range("sideband_low,sideband_high")); //RooFitResult* bres = b_AIC.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE),RooFit::Range("sideband_low,sideband_high")); //bres->SetName("AIC_b_fitres"); //ws->import(*bres); //make blinded fit RooPlot *fmgg_b = mgg.frame(RooFit::Range("sideband_low,sideband_high")); blind_data->plotOn(fmgg_b,RooFit::Range("sideband_low,sideband_high")); TBox blindBox(121,fmgg_b->GetMinimum()-(fmgg_b->GetMaximum()-fmgg_b->GetMinimum())*0.015,130,fmgg_b->GetMaximum()); blindBox.SetFillColor(kGray); fmgg_b->addObject(&blindBox); bonly_AIC.plotOn(fmgg_b,RooFit::LineColor(kRed),RooFit::Range("Full"),RooFit::NormRange("sideband_low,sideband_high")); fmgg_b->SetName("AIC_blinded_frame"); ws->import(*fmgg_b); delete fmgg_b; #if 1 RooRealVar sigma("AIC_s_sigma","",5,0,100); if(forceSigma!=-1) { sigma.setVal(forceSigma); sigma.setConstant(true); } RooRealVar mu("AIC_s_mu","",126,120,132); if(forceMu!=-1) { mu.setVal(forceMu); mu.setConstant(true); } RooGaussian sig("AIC_sig_model","",mgg,mu,sigma); RooRealVar Nsig("AIC_sb_Ns","",5,0,100); RooRealVar Nbkg("AIC_sb_Nb","",100,0,100000); RooRealVar HiggsMass("HiggsMass","",125.1); RooRealVar HiggsMassError("HiggsMassError","",0.24); RooGaussian HiggsMassConstraint("HiggsMassConstraint","",mu,HiggsMass,HiggsMassError); RooAddPdf fitModel("AIC_sb_model","",RooArgList( b_AIC, sig ),RooArgList(Nbkg,Nsig)); RooFitResult* sbres; RooAbsReal *nll; if(constrainMu) { fitModel.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint))); sbres = fitModel.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint))); nll = fitModel.createNLL(data,RooFit::NumCPU(4),RooFit::Extended(kTRUE),RooFit::ExternalConstraints(RooArgSet(HiggsMassConstraint))); } else { fitModel.fitTo(data,RooFit::Strategy(0),RooFit::Extended(kTRUE)); sbres = fitModel.fitTo(data,RooFit::Strategy(2),RooFit::Save(kTRUE),RooFit::Extended(kTRUE)); nll = fitModel.createNLL(data,RooFit::NumCPU(4),RooFit::Extended(kTRUE)); } assert(nll!=0); sbres->SetName("AIC_sb_fitres"); ws->import(*sbres); ws->import(fitModel); RooPlot *fmgg = mgg.frame(); data.plotOn(fmgg); fitModel.plotOn(fmgg); ws->pdf("b_AIC")->plotOn(fmgg,RooFit::LineColor(kRed),RooFit::Range("Full"),RooFit::NormRange("Full")); fmgg->SetName("AIC_frame"); ws->import(*fmgg); delete fmgg; RooMinuit(*nll).migrad(); RooPlot *fNs = Nsig.frame(0,25); fNs->SetName("AIC_Nsig_pll"); RooAbsReal *pll = nll->createProfile(Nsig); //nll->plotOn(fNs,RooFit::ShiftToZero(),RooFit::LineColor(kRed)); pll->plotOn(fNs); ws->import(*fNs); delete fNs; RooPlot *fmu = mu.frame(125,132); fmu->SetName("AIC_mu_pll"); RooAbsReal *pll_mu = nll->createProfile(mu); pll_mu->plotOn(fmu); ws->import(*fmu); delete fmu; std::cout << "min AIC: " << minAIC.getVal() << std::endl; for(auto t = tags.begin(); t!=tags.end(); t++) { RooFormulaVar *AIC = (RooFormulaVar*)ws->obj(*t+"_b_AIC"); RooRealVar *AICw = ws->var(*t+"_b_AICWeight"); RooRealVar* k = ws->var(*t+"_b_k"); printf("%s & %0.0f & %0.2f & %0.2f \\\\\n",t->Data(),k->getVal(),AIC->getVal()-minAIC.getVal(),AICw->getVal()); //std::cout << k->getVal() << " " << AIC->getVal()-minAIC.getVal() << " " << AICw->getVal() << std::endl; } #endif return ws; }
exampleScript() { gSystem->CompileMacro("betaHelperFunctions.h" ,"kO") ; gSystem->CompileMacro("RooNormalFromFlatPdf.cxx" ,"kO") ; gSystem->CompileMacro("RooBetaInverseCDF.cxx" ,"kO") ; gSystem->CompileMacro("RooBetaPrimeInverseCDF.cxx" ,"kO") ; gSystem->CompileMacro("RooCorrelatedBetaGeneratorHelper.cxx" ,"kO") ; gSystem->CompileMacro("RooCorrelatedBetaPrimeGeneratorHelper.cxx" ,"kO") ; gSystem->CompileMacro("rooFitBetaHelperFunctions.h","kO") ; TFile betaTest("betaTest.root","RECREATE"); betaTest.cd(); RooWorkspace workspace("workspace"); TString correlatedName("testVariable"); TString observables("observables"); TString nuisances("nuisances"); RooAbsArg* betaOne = getCorrelatedBetaConstraint(workspace,"betaOne","", 0.5 , 0.1 , observables, nuisances, correlatedName ); printf("\n\n *** constraint name is %s from betaOne and %s\n\n", betaOne->GetName(), correlatedName.Data() ) ; RooAbsArg* betaTwo = getCorrelatedBetaConstraint(workspace,"betaTwo","", 0 , 0 , observables, nuisances, correlatedName ); RooAbsArg* betaThree = getCorrelatedBetaConstraint(workspace,"betaThree","", 0.2 , 0.01 , observables, nuisances, correlatedName ); RooAbsArg* betaFour = getCorrelatedBetaConstraint(workspace,"betaFour","", 0.7 , 0.1 , observables, nuisances, correlatedName ); RooAbsArg* betaFourC = getCorrelatedBetaConstraint(workspace,"betaFourC","", 0.7 , 0.1 , observables, nuisances, correlatedName, kTRUE ); RooAbsArg* betaPrimeOne = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeOne","", 1.0 , 0.5 , observables, nuisances, correlatedName ); RooAbsArg* betaPrimeOneC = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeOneC","", 1.0 , 0.5 , observables, nuisances, correlatedName, kTRUE ); RooAbsArg* betaPrimeTwo = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeTwo","", 0.7 , 0.5 , observables, nuisances, correlatedName ); RooAbsArg* betaPrimeThree = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeThree","", 0.1 , 0.05 , observables, nuisances, correlatedName ); RooAbsArg* betaPrimeFour = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeFour","", 7 , 1 , observables, nuisances, correlatedName ); RooRealVar* correlatedParameter = workspace.var(correlatedName); RooAbsPdf* normalFromFlat = workspace.pdf(correlatedName+"_Constraint"); RooDataSet* data = normalFromFlat->generate(RooArgSet(*correlatedParameter),1e5); data->addColumn(*normalFromFlat); data->addColumn(*betaOne); data->addColumn(*betaTwo); data->addColumn(*betaThree); data->addColumn(*betaFour); data->addColumn(*betaFourC); data->addColumn(*betaPrimeOne); data->addColumn(*betaPrimeTwo); data->addColumn(*betaPrimeThree); data->addColumn(*betaPrimeFour); data->addColumn(*betaPrimeOneC); data->Print("v"); workspace.Print() ; //Setup Plotting Kluges: RooRealVar normalPlotter (correlatedName+"_Constraint" , correlatedName+"_Constraint" ,0,1); RooPlot* normalPlot = normalPlotter.frame(); data->plotOn(normalPlot); RooRealVar betaOnePlotter ("betaOne_BetaInverseCDF" ,"betaOne_BetaInverseCDF" ,0,1); RooRealVar betaTwoPlotter ("betaTwo_BetaInverseCDF" ,"betaTwo_BetaInverseCDF" ,0,1); RooRealVar betaThreePlotter("betaThree_BetaInverseCDF","betaThree_BetaInverseCDF",0,1); RooRealVar betaFourPlotter ("betaFour_BetaInverseCDF" ,"betaFour_BetaInverseCDF" ,0,1); RooRealVar betaFourCPlotter ("betaFourC_BetaInverseCDF" ,"betaFourC_BetaInverseCDF" ,0,1); RooRealVar betaPrimeOnePlotter ("betaPrimeOne_BetaPrimeInverseCDF" ,"betaPrimeOne_BetaPrimeInverseCDF" ,0,4); RooRealVar betaPrimeOneCPlotter ("betaPrimeOneC_BetaPrimeInverseCDF" ,"betaPrimeOneC_BetaPrimeInverseCDF" ,0,4); RooRealVar betaPrimeTwoPlotter ("betaPrimeTwo_BetaPrimeInverseCDF" ,"betaPrimeTwo_BetaPrimeInverseCDF" ,0,4); RooRealVar betaPrimeThreePlotter("betaPrimeThree_BetaPrimeInverseCDF","betaPrimeThree_BetaPrimeInverseCDF",0,0.3); RooRealVar betaPrimeFourPlotter ("betaPrimeFour_BetaPrimeInverseCDF" ,"betaPrimeFour_BetaPrimeInverseCDF" ,4,12); RooPlot* betaOnePlot = betaOnePlotter .frame(); RooPlot* betaTwoPlot = betaTwoPlotter .frame(); RooPlot* betaThreePlot = betaThreePlotter.frame(); RooPlot* betaFourPlot = betaFourPlotter .frame(); RooPlot* betaFourCPlot = betaFourCPlotter .frame(); data->plotOn(betaOnePlot ); data->plotOn(betaTwoPlot ); data->plotOn(betaThreePlot); data->plotOn(betaFourPlot ); data->plotOn(betaFourCPlot ); RooPlot* betaPrimeOnePlot = betaPrimeOnePlotter .frame(); RooPlot* betaPrimeOneCPlot = betaPrimeOneCPlotter .frame(); RooPlot* betaPrimeTwoPlot = betaPrimeTwoPlotter .frame(); RooPlot* betaPrimeThreePlot = betaPrimeThreePlotter.frame(); RooPlot* betaPrimeFourPlot = betaPrimeFourPlotter .frame(); data->plotOn(betaPrimeOnePlot ); data->plotOn(betaPrimeOneCPlot ); data->plotOn(betaPrimeTwoPlot ); data->plotOn(betaPrimeThreePlot); data->plotOn(betaPrimeFourPlot ); TCanvas* underlyingVariable = new TCanvas("underlyingVariable","underlyingVariable",800,800); underlyingVariable->Divide(2,2); underlyingVariable->cd(1); RooPlot* underlyingPlot = correlatedParameter->frame(); data->plotOn(underlyingPlot); underlyingPlot->Draw(); underlyingVariable->cd(2); normalPlot->Draw(); underlyingVariable->cd(3); TH2F* underlying = data->createHistogram(*correlatedParameter,normalPlotter,50,50); underlying->Draw("col"); TH2F* legoUnderlying = (TH2F*)underlying->Clone(); underlyingVariable->cd(4); legoUnderlying->Draw("lego"); underlyingVariable->SaveAs("underlyingVariable.pdf"); TCanvas* betaCanvas = new TCanvas("betaCanvas","betaCanvas",800,800); betaCanvas->Divide(3,2); betaCanvas->cd(1); betaOnePlot->Draw(); betaCanvas->cd(2); betaTwoPlot->Draw(); betaCanvas->cd(3); betaThreePlot->Draw(); betaCanvas->cd(4); betaFourPlot->Draw(); betaCanvas->cd(5); betaFourCPlot->Draw(); betaCanvas->SaveAs("betaVariables.pdf"); TCanvas* betaPrimeCanvas = new TCanvas("betaPrimeCanvas","betaPrimeCanvas",1200,800); betaPrimeCanvas->Divide(3,2); betaPrimeCanvas->cd(1); betaPrimeOnePlot->Draw(); betaPrimeCanvas->cd(2); betaPrimeTwoPlot->Draw(); betaPrimeCanvas->cd(3); betaPrimeThreePlot->Draw(); betaPrimeCanvas->cd(4); betaPrimeFourPlot->Draw(); betaPrimeCanvas->cd(5); betaPrimeOneCPlot->Draw(); betaPrimeCanvas->SaveAs("betaPrimeVariables.pdf"); TCanvas* betaCorrelationsCanvas = new TCanvas("betaCorrelationsCanvas","betaCorrelationsCanvas",1600,800); betaCorrelationsCanvas->Divide(4,2); TH2F* oneTwo = data->createHistogram(betaOnePlotter,betaTwoPlotter,30,30); TH2F* oneThree = data->createHistogram(betaOnePlotter,betaThreePlotter,30,30); TH2F* oneFour = data->createHistogram(betaOnePlotter,betaFourPlotter,30,30); TH2F* twoThree = data->createHistogram(betaTwoPlotter,betaThreePlotter,30,30); TH2F* twoFour = data->createHistogram(betaTwoPlotter,betaFourPlotter,30,30); TH2F* threeFour = data->createHistogram(betaThreePlotter,betaFourPlotter,30,30); TH2F* twoFourC = data->createHistogram(betaTwoPlotter,betaFourCPlotter,30,30); TH2F* fourFourC = data->createHistogram(betaFourPlotter,betaFourCPlotter,30,30); betaCorrelationsCanvas->cd(1); oneTwo->DrawCopy("lego"); betaCorrelationsCanvas->cd(2); oneThree->DrawCopy("lego"); betaCorrelationsCanvas->cd(3); oneFour->DrawCopy("lego"); betaCorrelationsCanvas->cd(4); twoThree->DrawCopy("lego"); betaCorrelationsCanvas->cd(5); twoFour->DrawCopy("lego"); betaCorrelationsCanvas->cd(6); threeFour->DrawCopy("lego"); betaCorrelationsCanvas->cd(7); twoFourC->DrawCopy("lego"); betaCorrelationsCanvas->cd(8); fourFourC->DrawCopy("lego"); betaCorrelationsCanvas->SaveAs("betaCorrelations.pdf"); TCanvas* betaPrimeCorrelationsCanvas = new TCanvas("betaPrimeCorrelationsCanvas","betaPrimeCorrelationsCanvas",1600,800); betaPrimeCorrelationsCanvas->Divide(4,2); TH2F* oneTwo = data->createHistogram(betaPrimeOnePlotter,betaPrimeTwoPlotter,30,30); TH2F* oneThree = data->createHistogram(betaPrimeOnePlotter,betaPrimeThreePlotter,30,30); TH2F* oneFour = data->createHistogram(betaPrimeOnePlotter,betaPrimeFourPlotter,30,30); TH2F* twoThree = data->createHistogram(betaPrimeTwoPlotter,betaPrimeThreePlotter,30,30); TH2F* twoFour = data->createHistogram(betaPrimeTwoPlotter,betaPrimeFourPlotter,30,30); TH2F* threeFour = data->createHistogram(betaPrimeThreePlotter,betaPrimeFourPlotter,30,30); TH2F* oneOneC = data->createHistogram(betaPrimeOnePlotter,betaPrimeOneCPlotter,30,30); betaPrimeCorrelationsCanvas->cd(1); oneTwo->DrawCopy("lego"); betaPrimeCorrelationsCanvas->cd(2); oneThree->DrawCopy("lego"); betaPrimeCorrelationsCanvas->cd(3); oneFour->DrawCopy("lego"); betaPrimeCorrelationsCanvas->cd(4); twoThree->DrawCopy("lego"); betaPrimeCorrelationsCanvas->cd(5); twoFour->DrawCopy("lego"); betaPrimeCorrelationsCanvas->cd(6); threeFour->DrawCopy("lego"); betaPrimeCorrelationsCanvas->cd(7); oneOneC->DrawCopy("lego"); betaPrimeCorrelationsCanvas->SaveAs("betaPrimeCorrelations.pdf"); RooProdPdf totalPdf("totalPdf","totalPdf",workspace.allPdfs()); totalPdf.Print("v"); RooArgSet* observableSet = workspace.set("observables"); observableSet->Print(); RooDataSet* allDataOne = totalPdf.generate(*observableSet,1); allDataOne->Print("v"); correlatedParameter->setVal(0.25); RooDataSet* allDataTwo = totalPdf.generate(*observableSet,1); allDataTwo->Print("v"); correlatedParameter->setVal(0.75); RooDataSet* allDataThree = totalPdf.generate(*observableSet,1); allDataThree->Print("v"); //Testing for extreme values! for(int i = 0; i< 101; i++) { correlatedParameter->setVal((double)i/100.); cout << "Correlation parameter has value of " << correlatedParameter->getVal(); cout << " and the pdf has an unnormalized value of " << normalFromFlat->getVal() << endl; } }
void DrawChannelCompatibility(double rMin = -5,double rMax=5) { gROOT->ForceStyle(); TFile *inf = TFile::Open("higgsCombineZ.ChannelCompatibilityCheck.mH120.root"); RooFitResult *fit_nominal = (RooFitResult *)inf->Get("fit_nominal"); RooFitResult *fit_alternate = (RooFitResult *)inf->Get("fit_alternate"); RooRealVar *rFit = (RooRealVar*)fit_nominal->floatParsFinal().find("r"); TString prefix = TString::Format("_ChannelCompatibilityCheck_%s_","r"); int nChann = 0; TIterator *iter = fit_alternate->floatParsFinal().createIterator(); for (RooAbsArg *a = (RooAbsArg *) iter->Next(); a != 0; a = (RooAbsArg *) iter->Next()) { if (TString(a->GetName()).Index(prefix) == 0) nChann++; } TH2F *frame = new TH2F("frame",";best fit #sigma/#sigma_{SM};",1,rMin,rMax,nChann,0,nChann); iter->Reset(); int iChann = 0; TGraphAsymmErrors *points = new TGraphAsymmErrors(nChann); float chi2(0.0); for (RooAbsArg *a = (RooAbsArg *) iter->Next(); a != 0; a = (RooAbsArg *) iter->Next()) { if (TString(a->GetName()).Index(prefix) == 0) { RooRealVar *ri = (RooRealVar *) a; TString channel = a->GetName(); channel.ReplaceAll(prefix,""); points->SetPoint(iChann,ri->getVal(),iChann+0.5); cout<<channel<<" "<<ri->getVal()<<" "<<ri->getAsymErrorLo()<<" +"<<ri->getAsymErrorHi()<<endl; chi2 += pow((ri->getVal()-rFit->getVal())/ri->getError(),2); points->SetPointError(iChann,-ri->getAsymErrorLo(),ri->getAsymErrorHi(),0,0); //points->SetPointError(iChann,ri->getAsymErrorHi(),ri->getAsymErrorHi(),0,0); iChann++; frame->GetYaxis()->SetBinLabel(iChann, channel); } } cout<<"Combined fit: "<<rFit->getVal()<<" "<<rFit->getAsymErrorLo()<<" +"<<rFit->getAsymErrorHi()<<endl; cout<<"chi2 = "<<chi2<<endl; points->SetLineColor(kRed); points->SetLineWidth(3); points->SetMarkerStyle(21); TCanvas *can = new TCanvas("ChannelCompatibility_Z","ChannelCompatibility_Z",900,600); frame->GetXaxis()->SetNdivisions(505); frame->GetXaxis()->SetTitleSize(0.06); frame->GetXaxis()->SetTitleOffset(0.9); frame->GetXaxis()->SetLabelSize(0.05); frame->GetYaxis()->SetLabelSize(0.1); frame->Draw(); //gStyle->SetOptStat(0); TBox globalFitBand(rFit->getVal()+rFit->getAsymErrorLo(), 0, rFit->getVal()+rFit->getAsymErrorHi(), nChann); //TBox globalFitBand(rFit->getVal()-rFit->getAsymErrorHi(), 0, rFit->getVal()+rFit->getAsymErrorHi(), nChann); globalFitBand.SetFillStyle(3013); globalFitBand.SetFillColor(65); globalFitBand.SetLineStyle(0); globalFitBand.DrawClone(); TLine globalFitLine(rFit->getVal(), 0, rFit->getVal(), nChann); globalFitLine.SetLineWidth(4); globalFitLine.SetLineColor(214); globalFitLine.DrawClone(); points->Draw("P SAME"); gPad->Update(); TLine *ln0 = new TLine(1,gPad->GetFrame()->GetY1(),1,gPad->GetFrame()->GetY2()); ln0->SetLineColor(kBlack); ln0->SetLineWidth(1); ln0->SetLineStyle(2); ln0->Draw("same"); }