/// /// 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; }
RooAbsArg *cloneRecursiveRename(RooAbsArg *arg, const char *postfix) { RooAbsArg *clone = arg->cloneTree(); RooArgSet *clonecomps = clone->getComponents(); RooArgSet *clonevars = clone->getVariables(); RooArgList cloneargs; cloneargs.add(*clonecomps); cloneargs.add(*clonevars); delete clonecomps; delete clonevars; for (int iarg=0; iarg<cloneargs.getSize(); ++iarg) { cloneargs.at(iarg)->SetName(TString::Format("%s_%s",cloneargs.at(iarg)->GetName(),postfix)); } return clone; }
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 rf506_msgservice() { // C r e a t e p d f // -------------------- // Construct gauss(x,m,s) RooRealVar x("x","x",-10,10) ; RooRealVar m("m","m",0,-10,10) ; RooRealVar s("s","s",1,-10,10) ; RooGaussian gauss("g","g",x,m,s) ; // Construct poly(x,p0) RooRealVar p0("p0","p0",0.01,0.,1.) ; RooPolynomial poly("p","p",x,p0) ; // Construct model = f*gauss(x) + (1-f)*poly(x) RooRealVar f("f","f",0.5,0.,1.) ; RooAddPdf model("model","model",RooArgSet(gauss,poly),f) ; RooDataSet* data = model.generate(x,10) ; // P r i n t c o n f i g u r a t i o n o f m e s s a g e s e r v i c e // --------------------------------------------------------------------------- // Print streams configuration RooMsgService::instance().Print() ; cout << endl ; // A d d i n g I n t e g r a t i o n t o p i c t o e x i s t i n g I N F O s t r e a m // ----------------------------------------------------------------------------------------------- // Print streams configuration RooMsgService::instance().Print() ; cout << endl ; // Add Integration topic to existing INFO stream RooMsgService::instance().getStream(1).addTopic(Integration) ; // Construct integral over gauss to demonstrate new message stream RooAbsReal* igauss = gauss.createIntegral(x) ; igauss->Print() ; // Print streams configuration in verbose, which also shows inactive streams cout << endl ; RooMsgService::instance().Print() ; cout << endl ; // Remove stream RooMsgService::instance().getStream(1).removeTopic(Integration) ; // E x a m p l e s o f p d f v a l u e t r a c i n g s t r e a m // ----------------------------------------------------------------------- // Show DEBUG level message on function tracing, trace RooGaussian only RooMsgService::instance().addStream(DEBUG,Topic(Tracing),ClassName("RooGaussian")) ; // Perform a fit to generate some tracing messages model.fitTo(*data,Verbose(kTRUE)) ; // Reset message service to default stream configuration RooMsgService::instance().reset() ; // Show DEBUG level message on function tracing on all objects, redirect output to file RooMsgService::instance().addStream(DEBUG,Topic(Tracing),OutputFile("rf506_debug.log")) ; // Perform a fit to generate some tracing messages model.fitTo(*data,Verbose(kTRUE)) ; // Reset message service to default stream configuration RooMsgService::instance().reset() ; // E x a m p l e o f a n o t h e r d e b u g g i n g s t r e a m // --------------------------------------------------------------------- // Show DEBUG level messages on client/server link state management RooMsgService::instance().addStream(DEBUG,Topic(LinkStateMgmt)) ; RooMsgService::instance().Print("v") ; // Clone composite pdf g to trigger some link state management activity RooAbsArg* gprime = gauss.cloneTree() ; gprime->Print() ; // Reset message service to default stream configuration RooMsgService::instance().reset() ; }
/*********************************************************************** *********************************************************************** * CONSTRUCTOR MAKES ALLLLLLLL ******************************************************************* ************************************************* ***************************** ***** */ Tbroomfit(double xlow, double xhi, TH1 *h2, int npeak, double *peak, double *sigm, const char *chpol="p0"){ int iq=0; printf("constructor - %d %ld", iq++, (int64_t)h2 ); h2->Print(); /* * get global area, ranges for sigma, x */ npeaks=npeak; // class defined int // double areah2=h2->Integral( int(xlow), int(xhi) ); // WRONG - BINS min= h2->GetXaxis()->GetFirst(); printf("constructor - %d %f", iq++, min ); max= h2->GetXaxis()->GetLast(); printf("constructor - %d %f", iq++, max ); double areah2=h2->Integral( min, max ); printf("constructor - %d %f", iq++, areah2 ); min=xlow; max=xhi; double sigmamin=(max-min)/300; double sigmamax=(max-min)/4; double areamin=0; double areamax=2*areah2; printf("x:(%f,%f) s:(%f,%f) a:(%f,%f) \n", min,max,sigmamin, sigmamax,areamin, areamax ); /* * definition of variables.............. * */ RooRealVar x("x", "x", min, max); int MAXPEAKS=6; // later from 5 to 6 ??? printf("RooFit: npeaks=%d\n", npeaks ); // ABOVE: RooRealVar *msat[14][5]; // POINTERS TO ALL variables // 0 m Mean // 1 s Sigma // 2 a Area // 3 t Tail // 4 [0] nalpha // 5 [0] n1 for (int ii=0;ii<14;ii++){ for (int jj=0;jj<MAXPEAKS;jj++){ msat[ii][jj]=NULL; msat_values[ii][jj]=0.0; } //for for }// for for printf("delete fitresult, why crash?\n%s",""); fitresult=NULL; printf("delete fitresult, no crash?\n%s",""); RooRealVar mean1("mean1", "mean", 1*(max-min)/(npeaks+1)+min, min,max);msat[0][0]=&mean1; RooRealVar mean2("mean2", "mean", 2*(max-min)/(npeaks+1)+min, min,max);msat[0][1]=&mean2; RooRealVar mean3("mean3", "mean", 3*(max-min)/(npeaks+1)+min, min,max);msat[0][2]=&mean3; RooRealVar mean4("mean4", "mean", 4*(max-min)/(npeaks+1)+min, min,max);msat[0][3]=&mean4; RooRealVar mean5("mean5", "mean", 5*(max-min)/(npeaks+1)+min, min,max);msat[0][4]=&mean5; RooRealVar mean6("mean6", "mean", 6*(max-min)/(npeaks+1)+min, min,max);msat[0][5]=&mean6; RooRealVar sigma1("sigma1","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][0]=&sigma1; RooRealVar sigma2("sigma2","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][1]=&sigma2; RooRealVar sigma3("sigma3","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][2]=&sigma3; RooRealVar sigma4("sigma4","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][3]=&sigma4; RooRealVar sigma5("sigma5","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][4]=&sigma5; RooRealVar sigma6("sigma6","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][5]=&sigma6; RooRealVar area1("area1", "area", areah2/npeaks, areamin, areamax );msat[2][0]=&area1; RooRealVar area2("area2", "area", areah2/npeaks, areamin, areamax );msat[2][1]=&area2; RooRealVar area3("area3", "area", areah2/npeaks, areamin, areamax );msat[2][2]=&area3; RooRealVar area4("area4", "area", areah2/npeaks, areamin, areamax );msat[2][3]=&area4; RooRealVar area5("area5", "area", areah2/npeaks, areamin, areamax );msat[2][4]=&area5; RooRealVar area6("area6", "area", areah2/npeaks, areamin, areamax );msat[2][5]=&area6; RooRealVar bgarea("bgarea", "bgarea", areah2/5, 0, 2*areah2); double tailstart=-1.0;// tune the tails.... double tailmin=-1e+4; double tailmax=1e+4; RooRealVar tail1("tail1", "tail", tailstart, tailmin, tailmax );msat[3][0]=&tail1; RooRealVar tail2("tail2", "tail", tailstart, tailmin, tailmax );msat[3][1]=&tail2; RooRealVar tail3("tail3", "tail", tailstart, tailmin, tailmax );msat[3][2]=&tail3; RooRealVar tail4("tail4", "tail", tailstart, tailmin, tailmax );msat[3][3]=&tail4; RooRealVar tail5("tail5", "tail", tailstart, tailmin, tailmax );msat[3][4]=&tail5; RooRealVar tail6("tail6", "tail", tailstart, tailmin, tailmax );msat[3][5]=&tail6; // for CBShape RooRealVar nalpha1("nalpha1", "nalpha", 1.3, 0, 100 );msat[4][0]=&nalpha1; RooRealVar n1("n1", "n", 5.1, 0, 100 ); msat[5][0]=&n1; /* * initial values for peak positions................ */ if (npeaks>=1) {mean1=peak[0];sigma1=sigm[0];} if (npeaks>=2) {mean2=peak[1];sigma2=sigm[1];} if (npeaks>=3) {mean3=peak[2];sigma3=sigm[2];} if (npeaks>=4) {mean4=peak[3];sigma4=sigm[3];} if (npeaks>=5) {mean5=peak[4];sigma5=sigm[4];} if (npeaks>=6) {mean6=peak[5];sigma6=sigm[5];} /* * RooAbsPdf -> RooGaussian * RooNovosibirsk * RooLandau */ RooAbsPdf *pk[6]; // MAXIMUM PEAKS ==5 6 NOW!! RooAbsPdf *pk_dicto[14][6]; // ALL DICTIONARY OF PEAKS.......... // Abstract Class.... carrefuly RooGaussian gauss1("gauss1","gauss(x,mean,sigma)", x, mean1, sigma1);pk_dicto[0][0]=&gauss1; RooGaussian gauss2("gauss2","gauss(x,mean,sigma)", x, mean2, sigma2);pk_dicto[0][1]=&gauss2; RooGaussian gauss3("gauss3","gauss(x,mean,sigma)", x, mean3, sigma3);pk_dicto[0][2]=&gauss3; RooGaussian gauss4("gauss4","gauss(x,mean,sigma)", x, mean4, sigma4);pk_dicto[0][3]=&gauss4; RooGaussian gauss5("gauss5","gauss(x,mean,sigma)", x, mean5, sigma5);pk_dicto[0][4]=&gauss5; RooGaussian gauss6("gauss6","gauss(x,mean,sigma)", x, mean6, sigma6);pk_dicto[0][5]=&gauss6; RooNovosibirsk ns1("ns1","novosib(x,mean,sigma,tail)", x, mean1,sigma1, tail1 );pk_dicto[1][0]=&ns1; RooNovosibirsk ns2("ns2","novosib(x,mean,sigma,tail)", x, mean2,sigma2, tail2 );pk_dicto[1][1]=&ns2; RooNovosibirsk ns3("ns3","novosib(x,mean,sigma,tail)", x, mean3,sigma3, tail3 );pk_dicto[1][2]=&ns3; RooNovosibirsk ns4("ns4","novosib(x,mean,sigma,tail)", x, mean4,sigma4, tail4 );pk_dicto[1][3]=&ns4; RooNovosibirsk ns5("ns5","novosib(x,mean,sigma,tail)", x, mean5,sigma5, tail5 );pk_dicto[1][4]=&ns5; // BreitWiegner is Lorentzian...? RooBreitWigner bw1("bw1","BreitWigner(x,mean,sigma)", x, mean1, sigma1 );pk_dicto[2][0]=&bw1; RooBreitWigner bw2("bw2","BreitWigner(x,mean,sigma)", x, mean2, sigma2 );pk_dicto[2][1]=&bw2; RooBreitWigner bw3("bw3","BreitWigner(x,mean,sigma)", x, mean3, sigma3 );pk_dicto[2][2]=&bw3; RooBreitWigner bw4("bw4","BreitWigner(x,mean,sigma)", x, mean4, sigma4 );pk_dicto[2][3]=&bw4; RooBreitWigner bw5("bw5","BreitWigner(x,mean,sigma)", x, mean5, sigma5 );pk_dicto[2][4]=&bw5; RooCBShape cb1("cb1","CBShape(x,mean,sigma)", x, mean1, sigma1, nalpha1, n1 );pk_dicto[3][0]=&cb1; RooCBShape cb2("cb2","CBShape(x,mean,sigma)", x, mean2, sigma2, nalpha1, n1 );pk_dicto[3][1]=&cb2; RooCBShape cb3("cb3","CBShape(x,mean,sigma)", x, mean3, sigma3, nalpha1, n1 );pk_dicto[3][2]=&cb3; RooCBShape cb4("cb4","CBShape(x,mean,sigma)", x, mean4, sigma4, nalpha1, n1 );pk_dicto[3][3]=&cb4; RooCBShape cb5("cb5","CBShape(x,mean,sigma)", x, mean5, sigma5, nalpha1, n1 );pk_dicto[3][4]=&cb5; RooCBShape cb6("cb6","CBShape(x,mean,sigma)", x, mean6, sigma6, nalpha1, n1 );pk_dicto[3][5]=&cb6; /* * PEAK TYPES BACKGROUND TYPE ......... COMMAND BOX OPTIONS ...... */ /**************************************************************************** * PLAY WITH THE DEFINITION COMMANDLINE...................... POLYNOM + PEAKS */ // CALSS DECLARED TString s; s=chpol; /* * peaks+bg== ALL BEFORE ; or : (after ... it is a conditions/options) */ TString command; int comstart=s.Index(":"); if (comstart<0){ comstart=s.Index(";");} if (comstart<0){ command="";}else{ command=s(comstart+1, s.Length()-comstart -1 ); // without ; s=s(0,comstart); // without ; printf("COMMANDLINE : %s\n", command.Data() ); if (TPRegexp("scom").Match(command)!=0){ }// COMMANDS - }// there is some command /************************************************* * PLAY WITH peaks+bg.................. s */ s.Append("+"); s.Prepend("+"); s.ReplaceAll(" ","+"); s.ReplaceAll("++++","+"); s.ReplaceAll("+++","+"); s.ReplaceAll("++","+");s.ReplaceAll("++","+"); printf (" regextp = %s\n", s.Data() ); if (TPRegexp("\\+p[\\dn]\\+").Match(s)==0){ // no match printf("NO polynomial demanded =>: %s\n", "appending pn command" ); s.Append("pn+"); } TString spk=s; TString sbg=s; TPRegexp("\\+p[\\dn]\\+").Substitute(spk,"+"); // remove +p.+ TPRegexp(".+(p[\\dn]).+").Substitute(sbg,"$1"); // remove all but +p+ printf ("PEAKS=%s BG=%s\n", spk.Data() , sbg.Data() ); spk.ReplaceAll("+",""); // VARIANT 1 ------- EACH LETTER MEANS ONE PEAK /************************************************************************ * PREPARE PEAKS FOLLOWING THE COMMAND BOX................ */ //default PEAK types pk[0]=&gauss1; pk[1]=&gauss2; pk[2]=&gauss3; pk[3]=&gauss4; pk[4]=&gauss5; pk[5]=&gauss6; int maxi=spk.Length(); if (maxi>npeaks){maxi=npeaks;} for (int i=0;i<maxi;i++){ if (spk[i]=='n'){ pk[i]=pk_dicto[1][i];//novosibirsk printf("PEAK #%d ... Novosibirsk\n", i ); }else if(spk[i]=='b'){ pk[i]=pk_dicto[2][i];//BreitWiegner printf("PEAK #%d ... BreitWigner\n", i ); }else if(spk[i]=='c'){ pk[i]=pk_dicto[3][i];//CBShape printf("PEAK #%d ... CBShape\n", i ); }else if(spk[i]=='y'){ }else if(spk[i]=='z'){ }else{ pk[i]=pk_dicto[0][i]; //gauss printf("PEAK #%d ... Gaussian\n", i ); }// ELSE CHAIN }//i to maxi for (int i=0;i<npeaks;i++){ printf("Peak %d at %f s=%f: PRINT:\n " , i, peak[i], sigm[i] );pk[i]->Print();} /******************************************************** BACKGROUND pn-p4 * a0 == level - also skew * a1 == p2 * a2 == p3 */ // Build Chebychev polynomial p.d.f. // RooRealVar a0("a0","a0", 0.) ; RooRealVar a0("a0","a0", 0., -10, 10) ; RooRealVar a1("a1","a1", 0., -10, 10) ; RooRealVar a2("a2","a2", 0., -10, 10) ; RooRealVar a3("a3","a3", 0., -10, 10) ; RooArgSet setcheb; if ( sbg=="pn" ){ setcheb.add(a0); a0=0.; a0.setConstant(kTRUE);bgarea=0.; bgarea.setConstant(kTRUE);} if ( sbg=="p0" ){ setcheb.add(a0); a0=0.; a0.setConstant(kTRUE); } if ( sbg=="p1" ){ setcheb.add(a0); } if ( sbg=="p2" ){ setcheb.add(a1); setcheb.add(a0); } if ( sbg=="p3" ){ setcheb.add(a2); setcheb.add(a1); setcheb.add(a0); } if ( sbg=="p4" ){ setcheb.add(a3);setcheb.add(a2); setcheb.add(a1); setcheb.add(a0); } // RooChebychev bkg("bkg","Background",x,RooArgSet(a0,a1,a2,a3) ) ; RooChebychev bkg("bkg","Background",x, setcheb ) ; /********************************************************************** * MODEL */ RooArgList rl; if (npeaks>0)rl.add( *pk[0] ); if (npeaks>1)rl.add( *pk[1] ); if (npeaks>2)rl.add( *pk[2] ); if (npeaks>3)rl.add( *pk[3] ); if (npeaks>4)rl.add( *pk[4] ); if (npeaks>5)rl.add( *pk[5] ); rl.add( bkg ); RooArgSet rs; if (npeaks>0)rs.add( area1 ); if (npeaks>1)rs.add( area2 ); if (npeaks>2)rs.add( area3 ); if (npeaks>3)rs.add( area4 ); if (npeaks>4)rs.add( area5 ); if (npeaks>5)rs.add( area6 ); rs.add( bgarea ); RooAddPdf modelV("model","model", rl, rs ); /* * WITH CUSTOMIZER - I can change parameters inside. But * - then all is a clone and I dont know how to reach it */ RooCustomizer cust( modelV ,"cust"); /* * Possibility to fix all sigma or tails.... */ if (TPRegexp("scom").Match(command)!=0){//----------------------SCOM printf("all sigma have common values.....\n%s", ""); if (npeaks>1)cust.replaceArg(sigma2,sigma1) ; if (npeaks>2)cust.replaceArg(sigma3,sigma1) ; if (npeaks>3)cust.replaceArg(sigma4,sigma1) ; if (npeaks>4)cust.replaceArg(sigma5,sigma1) ; if (npeaks>5)cust.replaceArg(sigma6,sigma1) ; } if (TPRegexp("tcom").Match(command)!=0){//----------------------TCOM printf("all tails have common values.....\n%s", ""); if (npeaks>1)cust.replaceArg(tail2,tail1) ; if (npeaks>2)cust.replaceArg(tail3,tail1) ; if (npeaks>3)cust.replaceArg(tail4,tail1) ; if (npeaks>4)cust.replaceArg(tail5,tail1) ; if (npeaks>5)cust.replaceArg(tail6,tail1) ; } /* if (TPRegexp("tcom").Match(command)!=0){//----------------------TCOM Neni dalsi ACOM,NCOM pro CB... printf("all tails have common values.....\n%s", ""); if (npeaks>1)cust.replaceArg(tail2,tail1) ; if (npeaks>2)cust.replaceArg(tail3,tail1) ; if (npeaks>3)cust.replaceArg(tail4,tail1) ; if (npeaks>4)cust.replaceArg(tail5,tail1) ; } */ if (TPRegexp("p1fix").Match(command)!=0){//---------------------- mean1.setConstant();printf("position 1 set constant%s\n",""); } if (TPRegexp("p2fix").Match(command)!=0){//---------------------- mean2.setConstant();printf("position 2 set constant%s\n",""); } if (TPRegexp("p3fix").Match(command)!=0){//---------------------- mean3.setConstant();printf("position 3 set constant%s\n",""); } if (TPRegexp("p4fix").Match(command)!=0){//---------------------- mean4.setConstant();printf("position 4 set constant%s\n",""); } if (TPRegexp("p5fix").Match(command)!=0){//---------------------- mean5.setConstant();printf("position 5 set constant%s\n",""); } if (TPRegexp("p6fix").Match(command)!=0){//---------------------- mean6.setConstant();printf("position 6 set constant%s\n",""); } if (TPRegexp("s1fix").Match(command)!=0){//---------------------- sigma1.setConstant();printf("sigma 1 set constant%s\n",""); } if (TPRegexp("s2fix").Match(command)!=0){//---------------------- sigma2.setConstant();printf("sigma 2 set constant%s\n",""); } if (TPRegexp("s3fix").Match(command)!=0){//---------------------- sigma3.setConstant();printf("sigma 3 set constant%s\n",""); } if (TPRegexp("s4fix").Match(command)!=0){//---------------------- sigma4.setConstant();printf("sigma 4 set constant%s\n",""); } if (TPRegexp("s5fix").Match(command)!=0){//---------------------- sigma5.setConstant();printf("sigma 5 set constant%s\n",""); } if (TPRegexp("s6fix").Match(command)!=0){//---------------------- sigma6.setConstant();printf("sigma 6 set constant%s\n",""); } RooAbsPdf* model = (RooAbsPdf*) cust.build(kTRUE) ; //build a clone...comment on changes... // model->Print("t") ; //delete model ; // eventualy delete the model... /* * DISPLAY RESULTS >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */ TPad *orig_gpad=(TPad*)gPad; TCanvas *c; c=(TCanvas*)gROOT->GetListOfCanvases()->FindObject("fitresult"); if (c==NULL){ printf("making new canvas\n%s",""); c=new TCanvas("fitresult",h2->GetName(),1000,700); }else{ printf("using old canvas\n%s",""); c->SetTitle( h2->GetName() ); } c->Clear(); printf(" canvas cleared\n%s",""); c->Divide(1,2) ; printf(" canvas divided\n%s",""); c->Modified();c->Update(); RooDataHist datah("datah","datah with x",x,h2); RooPlot* xframe = x.frame(); datah.plotOn(xframe, DrawOption("logy") ); // return; if (TPRegexp("chi2").Match(command)!=0){//----------------------CHI2 //from lorenzo moneta // TH1 * h1 = datah.createHistogram(x); // TF1 * f = model->asTF(RooArgList(x) , parameters ); //??? // h2->Fit(f); //It will work but you need to create a THNSparse and fit it //or use directly the ROOT::Fit::BinData class to create a ROOT::Fit::Chi2Function to minimize. // THIS CANNOT DO ZERO BINS fitresult = model->chi2FitTo( datah , Save() ); }else{ // FIT FIT FIT FIT FIT FIT FIT FIT FIT FIT fitresult = model->fitTo( datah , Save() ); } fitresult->SetTitle( h2->GetName() ); // I PUT histogram name to global fitresult // will be done by printResult ... fitresult->Print("v") ; //duplicite fitresult->floatParsFinal().Print("s") ; // later - after parsfinale .... : printResult(); // model->Print(); // not interesting........ model->plotOn(xframe, LineColor(kRed), DrawOption("l0z") ); //,Minos(kFALSE) /* * Posledni nakreslena vec je vychodiskem pro xframe->resid...? * NA PORADI ZALEZI.... */ //unused RooHist* hresid = xframe->residHist() ; RooHist* hpull = xframe->pullHist() ; // RooPlot* xframe2 = x.frame(Title("Residual Distribution")) ; // xframe2->addPlotable(hresid,"P") ; // Construct a histogram with the pulls of the data w.r.t the curve RooPlot* xframe3 = x.frame(Title("Pull Distribution")) ; xframe3->addPlotable(hpull,"P") ; /* * plot components at the end.... PLOT >>>>>>>>>>>>>>>> */ int colorseq[10]={kRed,kGreen,kBlue,kYellow,kCyan,kMagenta,kViolet,kAzure,kGray,kOrange}; // RooArgSet* model_params = model->getParameters(x); // this returns all parameters RooArgSet* model_params = model->getComponents(); TIterator* iter = model_params->createIterator() ; RooAbsArg* arg ; int icomp=0, ipeak=0; // printf("ENTERING COMPONENT ITERATOR x%dx.....................\n", icomp ); while((arg=(RooAbsArg*)iter->Next())) { // printf("printing COMPONENT %d\n", icomp ); // arg->Print(); // printf("NAME==%s\n", arg->Class_Name() ); //This returns only RooAbsArg // printf("NAME==%s\n", arg->ClassName() ); //This RooGaussian RooChebychev if ( IsPeak( arg->ClassName() )==1 ){ pk[ipeak]=(RooAbsPdf*)arg; //? // pk[ipeak]->Print(); ipeak++; // printf("adresses ... %d - %d - %d\n", pk[0], pk[1], pk[2] ); }// yes peak. icomp++; }//iterations over all components model->plotOn(xframe, Components(bkg), LineColor(kRed), LineStyle(kDashed), DrawOption("l0z") ); for (int i=0;i<npeaks;i++){ // printf("plotting %d. peak, color %d\n", i, colorseq[i+1] ); // printf("adresses ... %d - %d - %d\n", pk[0], pk[1], pk[2] ); // pk[i]->Print(); model->plotOn(xframe, Components( RooArgSet(*pk[i],bkg) ), LineColor(colorseq[i+1]), LineStyle(kDashed), DrawOption("l0z") ); // DrawOption("pz"),DataError(RooAbsData::SumW2) );??? pz removes complains...warnings // model.plotOn(xframe, Components( RooArgSet(*pk[i],bkg) ), LineColor(colorseq[i+1]), LineStyle(kDashed)); } // WE SET THE 1st PAD in "fitresult" to LOGY.... 1 // ..... if the original window is LOGY..... :) // // printf("########### ORIGPAD LOGY==%d #########3\n", orig_gpad->GetLogy() ); c->cd(1); xframe->Draw(); gPad->SetLogy( orig_gpad->GetLogy() ); // c->cd(2); xframe2->Draw(); c->cd(2); xframe3->Draw(); c->Modified();c->Update(); orig_gpad->cd(); // printf("msat reference to peak 0 0 = %d, (%f)\n", msat[0][0] , msat[0][0]->getVal() ); for (int ii=0;ii<14;ii++){ for (int jj=0;jj<MAXPEAKS;jj++){ if ( msat[ii][jj]!=NULL){ msat_values[ii][jj]=msat[ii][jj]->getVal(); }//if } //for for }// for for printf("at the total end of the constructor....%s\n",""); // done in pirntResult .. fitresult->floatParsFinal().Print("s") ; printResult(); }; // constructor
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"); }