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; }
void makejpsifit(string inputFilename, string outFilename, Int_t ptBin, Int_t etaBin, double minMass, double maxMass, double mean_bw, double gamma_bw, double cutoff_cb, double power_cb, const char* plotOpt, const int nbins, Int_t isMC) { TStyle *mystyle = RooHZZStyle("ZZ"); mystyle->cd(); //Create Data Set RooRealVar mass("zmass","m(e^{+}e^{-})",minMass,maxMass,"GeV/c^{2}"); // Reading everything from root tree instead TFile *tfile = TFile::Open(inputFilename.c_str()); TTree *ttree = (TTree*)tfile->Get("zeetree/probe_tree"); hzztree *zeeTree = new hzztree(ttree); RooArgSet zMassArgSet(mass); RooDataSet* data = new RooDataSet("data", "ntuple parameters", zMassArgSet); for (int i = 0; i < zeeTree->fChain->GetEntries(); i++) { if(i%100000==0) cout << "Processing Event " << i << endl; zeeTree->fChain->GetEntry(i); //************************************************************************* //Electron Selection //************************************************************************* // already passed for this tree //************************************************************************* //Compute electron four vector; //************************************************************************* double ele1pt = zeeTree->l1pt; double ele2pt = zeeTree->l2pt; double ELECTRONMASS = 0.51e-3; TLorentzVector ele1FourVector; ele1FourVector.SetPtEtaPhiM(zeeTree->l1pt, zeeTree->l1eta, zeeTree->l1phi, ELECTRONMASS); TLorentzVector ele2FourVector; ele2FourVector.SetPtEtaPhiM(zeeTree->l2pt, zeeTree->l2eta, zeeTree->l2phi, ELECTRONMASS); //************************************************************************* //pt and eta cuts on electron //************************************************************************* if (! (ele1pt > 7 && ele2pt > 7 && fabs( zeeTree->l1eta) < 2.5 && fabs( zeeTree->l2eta) < 2.5 )) continue; //************************************************************************* //pt bins and eta bins //************************************************************************* Int_t Ele1PtBin = -1; Int_t Ele1EtaBin = -1; Int_t Ele2PtBin = -1; Int_t Ele2EtaBin = -1; if (ele1pt > 7 && ele1pt < 10) Ele1PtBin = 0; else if (ele1pt < 20) Ele1PtBin = 1; else Ele1PtBin = 2; if (ele2pt > 7 && ele2pt < 10) Ele2PtBin = 0; else if (ele2pt < 20) Ele2PtBin = 1; else Ele2PtBin = 2; if (fabs(zeeTree->l1sceta) < 1.479) Ele1EtaBin = 0; else Ele1EtaBin = 1; if (fabs(zeeTree->l2sceta) < 1.479) Ele2EtaBin = 0; else Ele2EtaBin = 1; if (!(Ele1PtBin == ptBin || Ele2PtBin == ptBin)) continue; if (!(Ele1EtaBin == etaBin && Ele2EtaBin == etaBin)) continue; //************************************************************************* // restrict range of mass //************************************************************************* double zMass = (ele1FourVector+ele2FourVector).M(); if (zMass < minMass || zMass > maxMass) continue; //************************************************************************* //set mass variable //************************************************************************* zMassArgSet.setRealValue("zmass", zMass); data->add(zMassArgSet); } // do binned fit to gain time... mass.setBins(nbins); RooDataHist *bdata = new RooDataHist("data_binned","data_binned", zMassArgSet, *data); cout << "dataset size: " << data->numEntries() << endl; // // Closing file // treeFile->Close(); //====================== Parameters=========================== //Crystal Ball parameters // RooRealVar cbBias ("#Deltam_{CB}", "CB Bias", -.01, -10, 10, "GeV/c^{2}"); // RooRealVar cbSigma("sigma_{CB}", "CB Width", 1.7, 0.8, 5.0, "GeV/c^{2}"); // RooRealVar cbCut ("a_{CB}","CB Cut", 1.05, 1.0, 3.0); // RooRealVar cbPower("n_{CB}","CB Order", 2.45, 0.1, 20.0); RooRealVar cbBias ("#Deltam_{CB}", "CB Bias", -.01, -10, 10, "GeV/c^{2}"); RooRealVar cbSigma("#sigma_{CB}", "CB Width", 1.5, 0.01, 5.0, "GeV/c^{2}"); RooRealVar cbCut ("a_{CB}","CB Cut", 1.0, 1.0, 3.0); RooRealVar cbPower("n_{CB}","CB Order", 2.5, 0.1, 20.0); cbCut.setVal(cutoff_cb); cbPower.setVal(power_cb); // Just checking //cbCut.Print(); //cbPower.Print(); //Breit_Wigner parameters RooRealVar bwMean("m_{JPsi}","BW Mean", 3.096916, "GeV/c^{2}"); bwMean.setVal(mean_bw); RooRealVar bwWidth("#Gamma_{JPsi}", "BW Width", 92.9e-6, "GeV/c^{2}"); bwWidth.setVal(gamma_bw); // Fix the Breit-Wigner parameters to PDG values bwMean.setConstant(kTRUE); bwWidth.setConstant(kTRUE); // Exponential Background parameters RooRealVar expRate("#lambda_{exp}", "Exponential Rate", -0.064, -1, 1); RooRealVar c0("c_{0}", "c0", 1., 0., 50.); //Number of Signal and Background events RooRealVar nsig("N_{S}", "# signal events", 524, 0.1, 10000000000.); RooRealVar nbkg("N_{B}", "# background events", 43, 1., 10000000.); //============================ P.D.F.s============================= // Mass signal for two decay electrons p.d.f. RooBreitWigner bw("bw", "bw", mass, bwMean, bwWidth); RooCBShape cball("cball", "Crystal Ball", mass, cbBias, cbSigma, cbCut, cbPower); RooFFTConvPdf BWxCB("BWxCB", "bw X crystal ball", mass, bw, cball); // Mass background p.d.f. RooExponential bg("bg", "exp. background", mass, expRate); // Mass model for signal electrons p.d.f. RooAddPdf model("model", "signal", RooArgList(BWxCB), RooArgList(nsig)); TStopwatch t ; t.Start() ; double fitmin, fitmax; if(isMC) { fitmin = (etaBin==0) ? 3.00 : 2.7; fitmax = (etaBin==0) ? 3.20 : 3.4; } else { fitmin = (etaBin==0) ? ( (ptBin>=2) ? 3.01 : 3.02 ) : 2.7; fitmax = (etaBin==0) ? ( (ptBin==3) ? 3.23 : 3.22 ) : 3.4; } RooFitResult *fitres = model.fitTo(*bdata,Range(fitmin,fitmax),Hesse(1),Minos(1),Timer(1),Save(1)); fitres->SetName("fitres"); t.Print() ; TCanvas* c = new TCanvas("c","Unbinned Invariant Mass Fit", 0,0,800,600); //========================== Plotting ============================ //Create a frame RooPlot* plot = mass.frame(Range(minMass,maxMass),Bins(nbins)); // Add data and model to canvas int col = (isMC ? kAzure+4 : kGreen+1); data->plotOn(plot); model.plotOn(plot,LineColor(col)); data->plotOn(plot); model.paramOn(plot, Format(plotOpt, AutoPrecision(1)), Parameters(RooArgSet(cbBias, cbSigma, cbCut, cbPower, bwMean, bwWidth, expRate, nsig, nbkg)), Layout(0.15,0.45,0.80)); plot->getAttText()->SetTextSize(.03); plot->SetTitle(""); plot->Draw(); // Print Fit Values TLatex *tex = new TLatex(); tex->SetNDC(); tex->SetTextSize(.1); tex->SetTextFont(132); // tex->Draw(); tex->SetTextSize(0.057); if(isMC) tex->DrawLatex(0.65, 0.75, "J/#psi #rightarrow e^{+}e^{-} MC"); else tex->DrawLatex(0.65, 0.75, "J/#psi #rightarrow e^{+}e^{-} data"); tex->SetTextSize(0.030); tex->DrawLatex(0.645, 0.65, Form("BW Mean = %.2f GeV/c^{2}", bwMean.getVal())); tex->DrawLatex(0.645, 0.60, Form("BW #sigma = %.2f GeV/c^{2}", bwWidth.getVal())); c->Update(); c->SaveAs((outFilename + ".pdf").c_str()); c->SaveAs((outFilename + ".png").c_str()); // tablefile << Form(Outfile + "& $ %f $ & $ %f $ & $ %f $\\ \hline",cbBias.getVal(), cbSigma.getVal(), cbCut.getVal()); // Output workspace with model and data RooWorkspace *w = new RooWorkspace("JPsieeMassScaleAndResolutionFit"); w->import(model); w->import(*bdata); w->writeToFile((outFilename + ".root").c_str()); TFile *tfileo = TFile::Open((outFilename + ".root").c_str(),"update"); fitres->Write(); tfileo->Close(); }