void AnalyzeToy::extract_signal() { calculate_yield(); MakeSpinSPlot splotter(toyData); splotter.addSpecies("signal",ws->pdf("model_signal_mass"),signalYield); splotter.addSpecies("background",ws->pdf("model_bkg_mass"),backgroundYield); splotter.addVariable(ws->var("mass")); splotter.calculate(); RooDataSet *sweights = splotter.getSWeightDataSet(); sweights->SetName("sweights"); RooRealVar weight("weight","",-5.,5.); RooArgSet event; event.add(*mass); event.add(*cosT); event.add(weight); extractedData = new RooDataSet("extractedData","",event,WeightVar("weight")); Long64_t nEntries = toyData->numEntries(); for(int i=0;i<nEntries;i++) { double weight_double=0; weight_double += sweights->get(i)->getRealValue("signal_sw"); // weight_double += sweights->get(i)->getRealValue("background_sw"); mass->setVal(toyData->get(i)->getRealValue("mass")); cosT->setVal(toyData->get(i)->getRealValue("cosT")); extractedData->add(event,weight_double); } delete toyData; }
/// /// Set all parameters to values found in /// a provided fit result. /// void PDF_Abs::loadExtParameters(RooFitResult *r) { RooArgSet *tmp = new RooArgSet(); tmp->add(r->floatParsFinal()); tmp->add(r->constPars()); setParameters(parameters, tmp); delete tmp; }
void makeDataset( TString fname, TString tname, TString outfname ) { RooWorkspace *w = new RooWorkspace("w","w"); w->factory( "Dst_M[1950.,2070.]" ); w->factory( "D0_M[1810.,1920.]" ); w->factory( "D0_LTIME_ps[0.00,5.]" ); RooArgSet *observables = new RooArgSet(); observables->add( *w->var("Dst_M") ); observables->add( *w->var("D0_M") ); observables->add( *w->var("D0_LTIME_ps") ); w->defineSet("observables", *observables); w->var("Dst_M")->setBins(240); w->var("D0_M")->setBins(220); w->var("D0_LTIME_ps")->setBins(200); double Dst_M = -999.; double D0_M = -999.; double D0_LTIME_ps = -999.; TFile *tf = TFile::Open(fname); TTree *tree = (TTree*)tf->Get(tname); tree->SetBranchAddress( "Dst_M", &Dst_M ); tree->SetBranchAddress( "D0_M" , &D0_M ); tree->SetBranchAddress( "D0_LTIME_ps", &D0_LTIME_ps ); RooDataSet *data = new RooDataSet("Data","Data",*observables); RooDataHist *dataH = new RooDataHist("DataHist","Data",*observables); for ( int ev=0; ev<tree->GetEntries(); ev++) { tree->GetEntry(ev); if ( ev%10000 == 0 ) cout << ev << " / " << tree->GetEntries() << endl; if ( Dst_M < w->var("Dst_M")->getMin() || Dst_M > w->var("Dst_M")->getMax() ) continue; if ( D0_M < w->var("D0_M")->getMin() || D0_M > w->var("D0_M")->getMax() ) continue; if ( D0_LTIME_ps < w->var("D0_LTIME_ps")->getMin() || D0_LTIME_ps > w->var("D0_LTIME_ps")->getMax() ) continue; w->var("Dst_M")->setVal(Dst_M); w->var("D0_M")->setVal(D0_M); w->var("D0_LTIME_ps")->setVal(D0_LTIME_ps); data->add( *observables ); dataH->add( *observables ); } tf->Close(); w->import(*data); w->import(*dataH); w->writeToFile(outfname); }
void defineDatasets( RooWorkspace *w ) { w->factory( "B_s0_DTF_B_s0_M [5000,5800]" ); w->factory( "eventNumber [0, 10e10]" ); w->factory( "DataCat[HadronTOS2011,GlobalTIS2011,HadronTOS2012,GlobalTIS2012]" ); w->var("B_s0_DTF_B_s0_M")->SetTitle("m(K^{+}#pi^{-}K^{-}#pi^{+})"); w->var("B_s0_DTF_B_s0_M")->setUnit("MeV"); RooArgSet *observables = new RooArgSet(); observables->add( *w->var("B_s0_DTF_B_s0_M") ); observables->add( *w->var("eventNumber") ); observables->add( *w->cat("DataCat") ); w->defineSet( "observables", *observables ); delete observables; RooArgSet *categories = new RooArgSet(); categories->add( *w->cat("DataCat") ); w->defineSet( "categories", *categories ); delete categories; vector<TString> dsets; dsets.push_back( "Data" ); dsets.push_back( "Data2011" ); dsets.push_back( "Data2012" ); dsets.push_back( "Data2011HadronTOS" ); dsets.push_back( "Data2011GlobalTIS" ); dsets.push_back( "Data2012HadronTOS" ); dsets.push_back( "Data2012GlobalTIS" ); dsets.push_back( "Bs2KstKst" ); dsets.push_back( "Bs2KstKst1430" ); dsets.push_back( "Bs2Kst1430Kst1430" ); dsets.push_back( "Bs2KpiKpiPhaseSpace" ); dsets.push_back( "Bd2KstKst" ); dsets.push_back( "Bd2PhiKst" ); dsets.push_back( "Bs2PhiKst" ); dsets.push_back( "Bd2RhoKst" ); dsets.push_back( "Lb2pKpipi" ); dsets.push_back( "Lb2ppipipi" ); for (int i=0; i<dsets.size(); i++) { RooDataSet *data = new RooDataSet( dsets[i], dsets[i], *w->set("observables") ); w->import( *data ); delete data; } }
void SetConstants(RooWorkspace * pWs, RooStats::ModelConfig * pMc){ // // Fix all variables in the PDF except observables, POI and // nuisance parameters. Note that global observables are fixed. // If you need global observables floated, you have to set them // to float separately. // pMc->SetWorkspace(*pWs); RooAbsPdf * pPdf = pMc->GetPdf(); // we do not own this RooArgSet * pVars = pPdf->getVariables(); // we do own this RooArgSet * pFloated = new RooArgSet(*pMc->GetObservables()); pFloated->add(*pMc->GetParametersOfInterest()); pFloated->add(*pMc->GetNuisanceParameters()); TIterator * pIter = pVars->createIterator(); // we do own this for(TObject * pObj = pIter->Next(); pObj; pObj = pIter->Next() ){ std::string _name = pObj->GetName(); RooRealVar * pFloatedObj = (RooRealVar *)pFloated->find(_name.c_str()); if (pFloatedObj){ ((RooRealVar *)pObj)->setConstant(kFALSE); } else{ ((RooRealVar *)pObj)->setConstant(kTRUE); } //pObj->Print(); } delete pIter; delete pVars; delete pFloated; return; }
void RA4WorkSpace::finalize () { // // check // if ( !hasEle_ && !hasMu_ ) { std::cout << "no channel has been defined" << std::endl; return; } // // combined model RooArgSet modelSet; if ( !constEff_ ) modelSet.add(*pdfMcEff_); if ( !constKappa_ ) modelSet.add(*pdfMcKappa_); if ( !constSCont_ ) modelSet.add(*pdfMcSCont_); // RooArgSet modelSet(*pdfMcEff_,*pdfMcKappa_,*pdfMcSCont_); if ( hasEle_ ) { for ( unsigned int i=0; i<4; ++i ) modelSet.add(*pdfReg_[i][0]); } if ( hasMu_ ) { for ( unsigned int i=0; i<4; ++i ) modelSet.add(*pdfReg_[i][1]); } RooProdPdf model("model","model",modelSet); wspace_->import(model); // // priors // wspace_->factory("Uniform::prior_poi({s})"); RooUniform priorNuis("prior_nuis","prior_nuis",*setNuis_); wspace_->import(priorNuis); wspace_->factory("PROD::prior(prior_poi,prior_nuis)"); wspace_->Print("v"); finalized_ = true; }
//#include <typeinfo.h> void addFlatNuisances(std::string fi){ gSystem->Load("libHiggsAnalysisCombinedLimit.so"); TFile *fin = TFile::Open(fi.c_str()); RooWorkspace *wspace = (RooWorkspace*)fin->Get("w_hmumu"); wspace->Print(""); RooStats::ModelConfig *mc = (RooStats::ModelConfig*)wspace->genobj("ModelConfig"); RooArgSet *nuis = (RooArgSet*) mc->GetNuisanceParameters(); std::cout << "Before...." << std::endl; nuis->Print(); RooRealVar *mgg = (RooRealVar*)wspace->var("mmm"); // Get all of the "flat" nuisances to be added to the nusiances: RooArgSet pdfs = (RooArgSet) wspace->allVars(); RooAbsReal *pdf; TIterator *it_pdf = pdfs.createIterator(); while ( (pdf=(RooAbsReal*)it_pdf->Next()) ){ if (!(std::string(pdf->GetName()).find("zmod") != std::string::npos )) { if (!(std::string(pdf->GetName()).find("__norm") != std::string::npos )) { continue; } } pdf->Print(); RooArgSet* pdfpars = (RooArgSet*)pdf->getParameters(RooArgSet(*mgg)); pdfpars->Print(); std::string newname_pdf = (std::string("unconst_")+std::string(pdf->GetName())); wspace->import(*pdf,RooFit::RenameVariable(pdf->GetName(),newname_pdf.c_str())); pdf->SetName(newname_pdf.c_str()); nuis->add(*pdf); } wspace->var("MH")->setVal(125.0); std::cout << "After..." << std::endl; nuis->Print(); mc->SetNuisanceParameters(*nuis); //RooWorkspace *wspace_new = wspace->Clone(); //mc->SetWorkspace(*wspace_new); //wspace_new->import(*mc,true); TFile *finew = new TFile((std::string(fin->GetName())+std::string("_unconst.root")).c_str(),"RECREATE"); //wspace_new->SetName("w"); finew->WriteTObject(wspace); finew->Close(); }
void dtfit_sigmc(){ TChain* tree = new TChain("TEvent"); tree->Add("/home/vitaly/B0toDh0/Tuples/b2dh_sigmc_s1.root"); tree->Add("/home/vitaly/B0toDh0/Tuples/b2dh_sigmc_s2.root"); RooArgSet argset; RooRealVar mbc("mbc","mbc",mbc_min,mbc_max,"GeV"); argset.add(mbc); RooRealVar de("de","#DeltaE",-0.15,0.3,"GeV"); argset.add(de); de.setRange("signal",de_min,de_max); RooRealVar md("md","md",DMass-md_cut,DMass+md_cut,"GeV"); argset.add(md); RooRealVar mk("mk","mk",KMass-mk_cut,KMass+mk_cut,"GeV"); argset.add(mk); RooRealVar mpi0("mpi0","mpi0",Pi0Mass-mpi0_cut,Pi0Mass+mpi0_cut,"GeV"); argset.add(mpi0); RooRealVar bdtgs("bdtgs","bdtgs",0.98,1.); argset.add(bdtgs); RooRealVar atckpi_max("atckpi_max","atckpi_max",0.,atckpi_cut); argset.add(atckpi_max); RooDataSet ds("ds","ds",tree,argset); ds.Print(); }
void SHyFT::fit(bool verbose) { if ( verbose ) cout << "Fitting" << endl; RooArgSet nllset; for(unsigned int i=0;i<bins_.size();++i) { nllset.add(*bins_[i]->nll()); } RooAddition nllsum("nllsum","nllsum",nllset); RooMinuit m(nllsum); if ( verbose ) m.setVerbose(kTRUE); else { m.setVerbose(kFALSE); m.setPrintLevel(-1); } m.migrad(); m.hesse(); // m.minos(); if ( verbose ) { RooFitResult * f = m.save(); f->Print("v"); } }
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; }
int main(int argc, char* argv[]) { doofit::builder::EasyPdf *epdf = new doofit::builder::EasyPdf(); epdf->Var("sig_yield"); epdf->Var("sig_yield").setVal(153000); epdf->Var("sig_yield").setConstant(false); //decay time epdf->Var("obsTime"); epdf->Var("obsTime").SetTitle("t_{#kern[-0.2]{B}_{#kern[-0.1]{ d}}^{#kern[-0.1]{ 0}}}"); epdf->Var("obsTime").setUnit("ps"); epdf->Var("obsTime").setRange(0.,16.); // tag, respectively the initial state of the produced B meson epdf->Cat("obsTag"); epdf->Cat("obsTag").defineType("B_S",1); epdf->Cat("obsTag").defineType("Bbar_S",-1); //finalstate epdf->Cat("catFinalState"); epdf->Cat("catFinalState").defineType("f",1); epdf->Cat("catFinalState").defineType("fbar",-1); epdf->Var("obsEtaOS"); epdf->Var("obsEtaOS").setRange(0.0,0.5); std::vector<double> knots; knots.push_back(0.07); knots.push_back(0.10); knots.push_back(0.138); knots.push_back(0.16); knots.push_back(0.23); knots.push_back(0.28); knots.push_back(0.35); knots.push_back(0.42); knots.push_back(0.44); knots.push_back(0.48); knots.push_back(0.5); // empty arg list for coefficients RooArgList* list = new RooArgList(); // create first coefficient RooRealVar* coeff_first = &(epdf->Var("parCSpline1")); coeff_first->setRange(0,10000); coeff_first->setVal(1); coeff_first->setConstant(false); list->add( *coeff_first ); for (unsigned int i=1; i <= knots.size(); ++i){ std::string number = boost::lexical_cast<std::string>(i); RooRealVar* coeff = &(epdf->Var("parCSpline"+number)); coeff->setRange(0,10000); coeff->setVal(1); coeff->setConstant(false); list->add( *coeff ); } // create last coefficient RooRealVar* coeff_last = &(epdf->Var("parCSpline"+boost::lexical_cast<std::string>(knots.size()))); coeff_last->setRange(0,10000); coeff_last->setVal(1); coeff_last->setConstant(false); list->add( *coeff_last ); list->Print(); doofit::roofit::pdfs::DooCubicSplinePdf splinePdf("splinePdf",epdf->Var("obsEtaOS"),knots,*list,0,0.5); //doofit::roofit::pdfs::DooCubicSplinePdf* splinePdf = new doofit::roofit::pdfs::DooCubicSplinePdf("splinePdf", epdf->Var("obsEtaOS"), knots, *list,0,0.5); //Koeffizienten DecRateCoeff *coeff_c = new DecRateCoeff("coef_cos","coef_cos",DecRateCoeff::CPOdd,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("C_f"),epdf->Var("C_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Var("obsEtaOS"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff")); DecRateCoeff *coeff_s = new DecRateCoeff("coef_sin","coef_sin",DecRateCoeff::CPOdd,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("S_f"),epdf->Var("S_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Var("obsEtaOS"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff")); DecRateCoeff *coeff_sh = new DecRateCoeff("coef_sinh","coef_sinh",DecRateCoeff::CPEven,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("f1_f"),epdf->Var("f1_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Var("obsEtaOS"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff")); DecRateCoeff *coeff_ch = new DecRateCoeff("coef_cosh","coef_cosh",DecRateCoeff::CPEven,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("f0_f"),epdf->Var("f0_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Var("obsEtaOS"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff")); epdf->AddRealToStore(coeff_ch); epdf->AddRealToStore(coeff_sh); epdf->AddRealToStore(coeff_c); epdf->AddRealToStore(coeff_s); ///////////////////Generiere PDF's///////////////////// //Zeit epdf->GaussModel("resTimeGauss",epdf->Var("obsTime"),epdf->Var("allTimeResMean"),epdf->Var("allTimeReso")); epdf->BDecay("pdfSigTime",epdf->Var("obsTime"),epdf->Var("tau"),epdf->Var("dgamma"),epdf->Real("coef_cosh"),epdf->Real("coef_sinh"),epdf->Real("coef_cos"),epdf->Real("coef_sin"),epdf->Var("deltaM"),epdf->Model("resTimeGauss")); //Zusammenfassen der Parameter in einem RooArgSet RooArgSet Observables; Observables.add(RooArgSet( epdf->Var("obsTime"),epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("obsEtaOS"))); epdf->Extend("pdfExtend", epdf->Pdf("pdfSigTime"),epdf->Real("sig_yield")); //Multipliziere Signal und Untergrund PDF mit ihrer jeweiligen Zerfalls PDF// //Untergrund * Zerfall /*epdf->Product("pdf_bkg", RooArgSet(epdf->Pdf("pdf_bkg_mass_expo"), epdf->Pdf("pdf_bkg_mass_time"))); //Signal * Zerfall epdf->Product("pdf_sig", RooArgSet(epdf->Pdf("pdf_sig_mass_gauss"),epdf->Pdf("pdfSigTime"))); //Addiere PDF's epdf->Add("pdf_total", RooArgSet(epdf->Pdf("pdf_sig_mass_gauss*pdf_sig_time_decay"), epdf->Pdf("pdf_bkg_mass*pdf_bkg_time_decay")), RooArgSet(epdf->Var("bkg_Yield"),epdf->Var("sig_Yield")));*/ RooWorkspace ws; ws.import(epdf->Pdf("pdfExtend")); ws.defineSet("Observables",Observables, true); ws.Print(); doofit::config::CommonConfig cfg_com("common"); cfg_com.InitializeOptions(argc, argv); doofit::toy::ToyFactoryStdConfig cfg_tfac("toyfac"); cfg_tfac.InitializeOptions(cfg_com); doofit::toy::ToyStudyStdConfig cfg_tstudy("toystudy"); cfg_tstudy.InitializeOptions(cfg_tfac); // set a previously defined workspace to get PDF from (not mandatory, but convenient) cfg_tfac.set_workspace(&ws); // Check for a set --help flag and if so, print help and exit gracefully // (recommended). cfg_com.CheckHelpFlagAndPrintHelp(); // More custom code, e.g. to set options internally. // Not required as configuration via command line/config file is enough. cfg_com.PrintAll(); // Print overview of all options (optional) // cfg_com.PrintAll(); // Initialize the toy factory module with the config objects and start // generating toy samples. doofit::toy::ToyFactoryStd tfac(cfg_com, cfg_tfac); doofit::toy::ToyStudyStd tstudy(cfg_com, cfg_tstudy); RooDataSet* data = tfac.Generate(); data->Print(); epdf->Pdf("pdfExtend").getParameters(data)->readFromFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-parameter_spline.txt"); epdf->Pdf("pdfExtend").getParameters(data)->writeToFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-parameter_spline.txt.new"); //epdf->Pdf("pdfExtend").fitTo(*data); //epdf->Pdf("pdfExtend").getParameters(data)->writeToFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-fit-result.txt"); RooFitResult* fit_result = epdf->Pdf("pdfExtend").fitTo(*data, RooFit::Save(true)); tstudy.StoreFitResult(fit_result); /*using namespace doofit::plotting; PlotConfig cfg_plot("cfg_plot"); cfg_plot.InitializeOptions(); cfg_plot.set_plot_directory("/net/lhcb-tank/home/chasenberg/Ergebnis/dootoycp_spline-lhcb/time/"); // plot PDF and directly specify components Plot myplot(cfg_plot, epdf->Var("obsTime"), *data, RooArgList(epdf->Pdf("pdfExtend"))); myplot.PlotItLogNoLogY(); PlotConfig cfg_plotEta("cfg_plotEta"); cfg_plotEta.InitializeOptions(); cfg_plotEta.set_plot_directory("/net/lhcb-tank/home/chasenberg/Ergebnis/dootoycp_spline-lhcb/eta/"); // plot PDF and directly specify components Plot myplotEta(cfg_plotEta, epdf->Var("obsEtaOS"), *data, RooArgList(splinePdf)); myplotEta.PlotIt();*/ }
// implementation void TwoBinInstructional( void ){ // let's time this example TStopwatch t; t.Start(); // set RooFit random seed for reproducible results RooRandom::randomGenerator()->SetSeed(4357); // make model RooWorkspace * pWs = new RooWorkspace("ws"); // derived from data pWs->factory("xsec[0.2,0,2]"); // POI pWs->factory("bg_b[10,0,50]"); // data driven nuisance // predefined nuisances pWs->factory("lumi[100,0,1000]"); pWs->factory("eff_a[0.2,0,1]"); pWs->factory("eff_b[0.05,0,1]"); pWs->factory("tau[0,1]"); pWs->factory("xsec_bg_a[0.05]"); // constant pWs->var("xsec_bg_a")->setConstant(1); // channel a (signal): lumi*xsec*eff_a + lumi*bg_a + tau*bg_b pWs->factory("prod::sig_a(lumi,xsec,eff_a)"); pWs->factory("prod::bg_a(lumi,xsec_bg_a)"); pWs->factory("prod::tau_bg_b(tau, bg_b)"); pWs->factory("Poisson::pdf_a(na[14,0,100],sum::mu_a(sig_a,bg_a,tau_bg_b))"); // channel b (control): lumi*xsec*eff_b + bg_b pWs->factory("prod::sig_b(lumi,xsec,eff_b)"); pWs->factory("Poisson::pdf_b(nb[11,0,100],sum::mu_b(sig_b,bg_b))"); // nuisance constraint terms (systematics) pWs->factory("Lognormal::l_lumi(lumi,nom_lumi[100,0,1000],sum::kappa_lumi(1,d_lumi[0.1]))"); pWs->factory("Lognormal::l_eff_a(eff_a,nom_eff_a[0.20,0,1],sum::kappa_eff_a(1,d_eff_a[0.05]))"); pWs->factory("Lognormal::l_eff_b(eff_b,nom_eff_b[0.05,0,1],sum::kappa_eff_b(1,d_eff_b[0.05]))"); pWs->factory("Lognormal::l_tau(tau,nom_tau[0.50,0,1],sum::kappa_tau(1,d_tau[0.05]))"); //pWs->factory("Lognormal::l_bg_a(bg_a,nom_bg_a[0.05,0,1],sum::kappa_bg_a(1,d_bg_a[0.10]))"); // complete model PDF pWs->factory("PROD::model(pdf_a,pdf_b,l_lumi,l_eff_a,l_eff_b,l_tau)"); // Now create sets of variables. Note that we could use the factory to // create sets but in that case many of the sets would be duplicated // when the ModelConfig objects are imported into the workspace. So, // we create the sets outside the workspace, and only the needed ones // will be automatically imported by ModelConfigs // observables RooArgSet obs(*pWs->var("na"), *pWs->var("nb"), "obs"); // global observables RooArgSet globalObs(*pWs->var("nom_lumi"), *pWs->var("nom_eff_a"), *pWs->var("nom_eff_b"), *pWs->var("nom_tau"), "global_obs"); // parameters of interest RooArgSet poi(*pWs->var("xsec"), "poi"); // nuisance parameters RooArgSet nuis(*pWs->var("lumi"), *pWs->var("eff_a"), *pWs->var("eff_b"), *pWs->var("tau"), "nuis"); // priors (for Bayesian calculation) pWs->factory("Uniform::prior_xsec(xsec)"); // for parameter of interest pWs->factory("Uniform::prior_bg_b(bg_b)"); // for data driven nuisance parameter pWs->factory("PROD::prior(prior_xsec,prior_bg_b)"); // total prior // create data pWs->var("na")->setVal(14); pWs->var("nb")->setVal(11); RooDataSet * pData = new RooDataSet("data","",obs); pData->add(obs); pWs->import(*pData); //pData->Print(); // signal+background model ModelConfig * pSbModel = new ModelConfig("SbModel"); pSbModel->SetWorkspace(*pWs); pSbModel->SetPdf(*pWs->pdf("model")); pSbModel->SetPriorPdf(*pWs->pdf("prior")); pSbModel->SetParametersOfInterest(poi); pSbModel->SetNuisanceParameters(nuis); pSbModel->SetObservables(obs); pSbModel->SetGlobalObservables(globalObs); // set all but obs, poi and nuisance to const SetConstants(pWs, pSbModel); pWs->import(*pSbModel); // background-only model // use the same PDF as s+b, with xsec=0 // POI value under the background hypothesis Double_t poiValueForBModel = 0.0; ModelConfig* pBModel = new ModelConfig(*(RooStats::ModelConfig *)pWs->obj("SbModel")); pBModel->SetName("BModel"); pBModel->SetWorkspace(*pWs); pWs->import(*pBModel); // find global maximum with the signal+background model // with conditional MLEs for nuisance parameters // and save the parameter point snapshot in the Workspace // - safer to keep a default name because some RooStats calculators // will anticipate it RooAbsReal * pNll = pSbModel->GetPdf()->createNLL(*pData); RooAbsReal * pProfile = pNll->createProfile(RooArgSet()); pProfile->getVal(); // this will do fit and set POI and nuisance parameters to fitted values RooArgSet * pPoiAndNuisance = new RooArgSet(); if(pSbModel->GetNuisanceParameters()) pPoiAndNuisance->add(*pSbModel->GetNuisanceParameters()); pPoiAndNuisance->add(*pSbModel->GetParametersOfInterest()); cout << "\nWill save these parameter points that correspond to the fit to data" << endl; pPoiAndNuisance->Print("v"); pSbModel->SetSnapshot(*pPoiAndNuisance); delete pProfile; delete pNll; delete pPoiAndNuisance; // Find a parameter point for generating pseudo-data // with the background-only data. // Save the parameter point snapshot in the Workspace pNll = pBModel->GetPdf()->createNLL(*pData); pProfile = pNll->createProfile(poi); ((RooRealVar *)poi.first())->setVal(poiValueForBModel); pProfile->getVal(); // this will do fit and set nuisance parameters to profiled values pPoiAndNuisance = new RooArgSet(); if(pBModel->GetNuisanceParameters()) pPoiAndNuisance->add(*pBModel->GetNuisanceParameters()); pPoiAndNuisance->add(*pBModel->GetParametersOfInterest()); cout << "\nShould use these parameter points to generate pseudo data for bkg only" << endl; pPoiAndNuisance->Print("v"); pBModel->SetSnapshot(*pPoiAndNuisance); delete pProfile; delete pNll; delete pPoiAndNuisance; // inspect workspace pWs->Print(); // save workspace to file pWs->writeToFile("ws_twobin.root"); // clean up delete pWs; delete pData; delete pSbModel; delete pBModel; } // ----- end of tutorial ----------------------------------------
void new_RA4(){ // let's time this challenging example TStopwatch t; t.Start(); // set RooFit random seed for reproducible results RooRandom::randomGenerator()->SetSeed(4357); // make model RooWorkspace* wspace = new RooWorkspace("wspace"); wspace->factory("Gaussian::sigCons(prime_SigEff[0,-5,5], nom_SigEff[0,-5,5], 1)"); wspace->factory("expr::SigEff('1.0*pow(1.20,@0)',prime_SigEff)"); // // 1+-20%, 1.20=exp(20%) wspace->factory("Poisson::on(non[0,50], sum::splusb(prod::SigUnc(s[0,0,50],SigEff),mainb[8.8,0,50],dilep[0.9,0,20],tau[2.3,0,20],QCD[0.,0,10],MC[0.1,0,4]))"); wspace->factory("Gaussian::mcCons(prime_rho[0,-5,5], nom_rho[0,-5,5], 1)"); wspace->factory("expr::rho('1.0*pow(1.39,@0)',prime_rho)"); // // 1+-39% wspace->factory("Poisson::off(noff[0,200], prod::rhob(mainb,rho,mu_plus_e[0.74,0.01,10],1.08))"); wspace->factory("Gaussian::mcCons2(mu_plus_enom[0.74,0.01,4], mu_plus_e, sigmatwo[.05])"); wspace->factory("Gaussian::dilep_pred(dilep_nom[0.9,0,20], dilep, sigma3[2.2])"); wspace->factory("Gaussian::tau_pred(tau_nom[2.3,0,20], tau, sigma4[0.5])"); wspace->factory("Gaussian::QCD_pred(QCD_nom[0.0,0,10], QCD, sigma5[1.0])"); wspace->factory("Gaussian::MC_pred(MC_nom[0.1,0.01,4], MC, sigma7[0.14])"); wspace->factory("PROD::model(on,off,mcCons,mcCons2,sigCons,dilep_pred,tau_pred,QCD_pred,MC_pred)"); RooArgSet obs(*wspace->var("non"), *wspace->var("noff"), *wspace->var("mu_plus_enom"), *wspace->var("dilep_nom"), *wspace->var("tau_nom"), "obs"); obs.add(*wspace->var("QCD_nom")); obs.add(*wspace->var("MC_nom")); RooArgSet globalObs(*wspace->var("nom_SigEff"), *wspace->var("nom_rho"), "global_obs"); // fix global observables to their nominal values wspace->var("nom_SigEff")->setConstant(); wspace->var("nom_rho")->setConstant(); RooArgSet poi(*wspace->var("s"), "poi"); RooArgSet nuis(*wspace->var("mainb"), *wspace->var("prime_rho"), *wspace->var("prime_SigEff"), *wspace->var("mu_plus_e"), *wspace->var("dilep"), *wspace->var("tau"), "nuis"); nuis.add(*wspace->var("QCD")); nuis.add(*wspace->var("MC")); wspace->factory("Uniform::prior_poi({s})"); wspace->factory("Uniform::prior_nuis({mainb,mu_plus_e,dilep,tau,QCD,MC})"); wspace->factory("PROD::prior(prior_poi,prior_nuis)"); wspace->var("non")->setVal(8); //observed //wspace->var("non")->setVal(12); //expected observation wspace->var("noff")->setVal(7); //observed events in control region wspace->var("mu_plus_enom")->setVal(0.74); wspace->var("dilep_nom")->setVal(0.9); wspace->var("tau_nom")->setVal(2.3); wspace->var("QCD")->setVal(0.0); wspace->var("MC")->setVal(0.1); RooDataSet * data = new RooDataSet("data","",obs); data->add(obs); wspace->import(*data); ///////////////////////////////////////////////////// // Now the statistical tests // model config ModelConfig* pSbModel = new ModelConfig("SbModel"); pSbModel->SetWorkspace(*wspace); pSbModel->SetPdf(*wspace->pdf("model")); pSbModel->SetPriorPdf(*wspace->pdf("prior")); pSbModel->SetParametersOfInterest(poi); pSbModel->SetNuisanceParameters(nuis); pSbModel->SetObservables(obs); pSbModel->SetGlobalObservables(globalObs); wspace->import(*pSbModel); // set all but obs, poi and nuisance to const SetConstants(wspace, pSbModel); wspace->import(*pSbModel); Double_t poiValueForBModel = 0.0; ModelConfig* pBModel = new ModelConfig(*(RooStats::ModelConfig *)wspace->obj("SbModel")); pBModel->SetName("BModel"); pBModel->SetWorkspace(*wspace); wspace->import(*pBModel); RooAbsReal * pNll = pSbModel->GetPdf()->createNLL(*data); RooAbsReal * pProfile = pNll->createProfile(RooArgSet()); pProfile->getVal(); // this will do fit and set POI and nuisance parameters to fitted values RooArgSet * pPoiAndNuisance = new RooArgSet(); //if(pSbModel->GetNuisanceParameters()) // pPoiAndNuisance->add(*pSbModel->GetNuisanceParameters()); pPoiAndNuisance->add(*pSbModel->GetParametersOfInterest()); cout << "\nWill save these parameter points that correspond to the fit to data" << endl; pPoiAndNuisance->Print("v"); pSbModel->SetSnapshot(*pPoiAndNuisance); delete pProfile; delete pNll; delete pPoiAndNuisance; pNll = pBModel->GetPdf()->createNLL(*data); pProfile = pNll->createProfile(poi); ((RooRealVar *)poi.first())->setVal(poiValueForBModel); pProfile->getVal(); // this will do fit and set nuisance parameters to profiled values pPoiAndNuisance = new RooArgSet(); //if(pBModel->GetNuisanceParameters()) // pPoiAndNuisance->add(*pBModel->GetNuisanceParameters()); pPoiAndNuisance->add(*pBModel->GetParametersOfInterest()); cout << "\nShould use these parameter points to generate pseudo data for bkg only" << endl; pPoiAndNuisance->Print("v"); pBModel->SetSnapshot(*pPoiAndNuisance); delete pProfile; delete pNll; delete pPoiAndNuisance; // inspect workspace wspace->Print(); // save workspace to file wspace->writeToFile("tight.root"); //wspace->writeToFile("tight_median.root"); // clean up delete wspace; delete data; delete pSbModel; delete pBModel; }
/* * Prepares the workspace to be used by the hypothesis test calculator */ void workspace_preparer(char *signal_file_name, char *signal_hist_name_in_file, char *background_file_name, char *background_hist_name_in_file, char *data_file_name, char *data_hist_name_in_file, char *config_file) { // Include the config_reader class. TString path = gSystem->GetIncludePath(); path.Append(" -I/home/max/cern/cls/mario"); gSystem->SetIncludePath(path); gROOT->LoadMacro("config_reader.cxx"); // RooWorkspace used to store values. RooWorkspace * pWs = new RooWorkspace("ws"); // Create a config_reader (see source for details) to read the config // file. config_reader reader(config_file, pWs); // Read MR and RR bounds from the config file. double MR_lower = reader.find_double("MR_lower"); double MR_upper = reader.find_double("MR_upper"); double RR_lower = reader.find_double("RR_lower"); double RR_upper = reader.find_double("RR_upper"); double MR_initial = (MR_lower + MR_upper)/2; double RR_initial = (RR_lower + RR_upper)/2; // Define the Razor Variables RooRealVar MR = RooRealVar("MR", "MR", MR_initial, MR_lower, MR_upper); RooRealVar RR = RooRealVar("RSQ", "RSQ", RR_initial, RR_lower, RR_upper); // Argument lists RooArgList pdf_arg_list(MR, RR, "input_args_list"); RooArgSet pdf_arg_set(MR, RR, "input_pdf_args_set"); /***********************************************************************/ /* PART 1: IMPORTING SIGNAL AND BACKGROUND HISTOGRAMS */ /***********************************************************************/ /* * Get the signal's unextended pdf by converting the TH2D in the file * into a RooHistPdf */ TFile *signal_file = new TFile(signal_file_name); TH2D *signal_hist = (TH2D *)signal_file->Get(signal_hist_name_in_file); RooDataHist *signal_RooDataHist = new RooDataHist("signal_roodatahist", "signal_roodatahist", pdf_arg_list, signal_hist); RooHistPdf *unextended_sig_pdf = new RooHistPdf("unextended_sig_pdf", "unextended_sig_pdf", pdf_arg_set, *signal_RooDataHist); /* * Repeat this process for the background. */ TFile *background_file = new TFile(background_file_name); TH2D *background_hist = (TH2D *)background_file->Get(background_hist_name_in_file); RooDataHist *background_RooDataHist = new RooDataHist("background_roodatahist", "background_roodatahist", pdf_arg_list, background_hist); RooHistPdf *unextended_bkg_pdf = new RooHistPdf("unextended_bkg_pdf", "unextended_bkg_pdf", pdf_arg_set, *background_RooDataHist); /* * Now, we want to create the bprime variable, which represents the * integral over the background-only sample. We will perform the * integral automatically (that's why this is the only nuisance * parameter declared in this file - its value can be determined from * the input histograms). */ ostringstream bprime_string; ostringstream bprime_pdf_string; bprime_string << "bprime[" << background_hist->Integral() << ", 0, 999999999]"; bprime_pdf_string << "Poisson::bprime_pdf(bprime, " << background_hist->Integral() << ")"; pWs->factory(bprime_string.str().c_str()); pWs->factory(bprime_pdf_string.str().c_str()); /* * This simple command will create all values from the config file * with 'make:' at the beginning and a delimiter at the end (see config * _reader if you don't know what a delimiter is). In other * words, the luminosity, efficiency, transfer factors, and their pdfs * are created from this command. The declarations are contained in the * config file to be changed easily without having to modify this code. */ reader.factory_all(); /* * Now, we want to create the extended pdfs from the unextended pdfs, as * well as from the S and B values we manufactured in the config file. * S and B are the values by which the signal and background pdfs, * respectively, are extended. Recall that they were put in the * workspace in the reader.facotry_all() command. */ RooAbsReal *S = pWs->function("S"); RooAbsReal *B = pWs->function("B"); RooExtendPdf *signalpart = new RooExtendPdf("signalpart", "signalpart", *unextended_sig_pdf, *S); RooExtendPdf *backgroundpart = new RooExtendPdf("backgroundpart", "backgroundpart", *unextended_bkg_pdf, *B); RooArgList *pdf_list = new RooArgList(*signalpart, *backgroundpart, "list"); // Add the signal and background pdfs to make a TotalPdf RooAddPdf *TotalPdf = new RooAddPdf("TotalPdf", "TotalPdf", *pdf_list); RooArgList *pdf_prod_list = new RooArgList(*TotalPdf, *pWs->pdf("lumi_pdf"), *pWs->pdf("eff_pdf"), *pWs->pdf("rho_pdf"), *pWs->pdf("bprime_pdf")); // This creates the final model pdf. RooProdPdf *model = new RooProdPdf("model", "model", *pdf_prod_list); /* * Up until now, we have been using the workspace pWs to contain all of * our values. Now, all of our values that we require are in use in the * RooProdPdf called "model". So, we need to import "model" into a * RooWorkspace. To avoid recopying values into the rooworkspace, when * the values may already be present (which can cause problems), we will * simply create a new RooWorkspace to avoid confusion and problems. The * new RooWorkspace is created here. */ RooWorkspace *newworkspace = new RooWorkspace("newws"); newworkspace->import(*model); // Immediately delete pWs, so we don't accidentally use it again. delete pWs; // Show off the newworkspace newworkspace->Print(); // observables RooArgSet obs(*newworkspace->var("MR"), *newworkspace->var("RSQ"), "obs"); // global observables RooArgSet globalObs(*newworkspace->var("nom_lumi"), *newworkspace->var("nom_eff"), *newworkspace->var("nom_rho")); //fix global observables to their nominal values newworkspace->var("nom_lumi")->setConstant(); newworkspace->var("nom_eff")->setConstant(); newworkspace->var("nom_rho")->setConstant(); //Set Parameters of interest RooArgSet poi(*newworkspace->var("sigma"), "poi"); //Set Nuisnaces RooArgSet nuis(*newworkspace->var("prime_lumi"), *newworkspace->var("prime_eff"), *newworkspace->var("prime_rho"), *newworkspace->var("bprime")); // priors (for Bayesian calculation) newworkspace->factory("Uniform::prior_signal(sigma)"); // for parameter of interest newworkspace->factory("Uniform::prior_bg_b(bprime)"); // for data driven nuisance parameter newworkspace->factory("PROD::prior(prior_signal,prior_bg_b)"); // total prior //Observed data is pulled from histogram. //TFile *data_file = new TFile(data_file_name); TFile *data_file = new TFile(data_file_name); TH2D *data_hist = (TH2D *)data_file->Get(data_hist_name_in_file); RooDataHist *pData = new RooDataHist("data", "data", obs, data_hist); newworkspace->import(*pData); // Now, we will draw our data from a RooDataHist. /*TFile *data_file = new TFile(data_file_name); TTree *data_tree = (TTree *) data_file->Get(data_hist_name_in_file); RooDataSet *pData = new RooDataSet("data", "data", data_tree, obs); newworkspace->import(*pData);*/ // Craft the signal+background model ModelConfig * pSbModel = new ModelConfig("SbModel"); pSbModel->SetWorkspace(*newworkspace); pSbModel->SetPdf(*newworkspace->pdf("model")); pSbModel->SetPriorPdf(*newworkspace->pdf("prior")); pSbModel->SetParametersOfInterest(poi); pSbModel->SetNuisanceParameters(nuis); pSbModel->SetObservables(obs); pSbModel->SetGlobalObservables(globalObs); // set all but obs, poi and nuisance to const SetConstants(newworkspace, pSbModel); newworkspace->import(*pSbModel); // background-only model // use the same PDF as s+b, with sig=0 // POI value under the background hypothesis // (We will set the value to 0 later) Double_t poiValueForBModel = 0.0; ModelConfig* pBModel = new ModelConfig(*(RooStats::ModelConfig *)newworkspace->obj("SbModel")); pBModel->SetName("BModel"); pBModel->SetWorkspace(*newworkspace); newworkspace->import(*pBModel); // find global maximum with the signal+background model // with conditional MLEs for nuisance parameters // and save the parameter point snapshot in the Workspace // - safer to keep a default name because some RooStats calculators // will anticipate it RooAbsReal * pNll = pSbModel->GetPdf()->createNLL(*pData); RooAbsReal * pProfile = pNll->createProfile(RooArgSet()); pProfile->getVal(); // this will do fit and set POI and nuisance parameters to fitted values RooArgSet * pPoiAndNuisance = new RooArgSet(); if(pSbModel->GetNuisanceParameters()) pPoiAndNuisance->add(*pSbModel->GetNuisanceParameters()); pPoiAndNuisance->add(*pSbModel->GetParametersOfInterest()); cout << "\nWill save these parameter points that correspond to the fit to data" << endl; pPoiAndNuisance->Print("v"); pSbModel->SetSnapshot(*pPoiAndNuisance); delete pProfile; delete pNll; delete pPoiAndNuisance; // Find a parameter point for generating pseudo-data // with the background-only data. // Save the parameter point snapshot in the Workspace pNll = pBModel->GetPdf()->createNLL(*pData); pProfile = pNll->createProfile(poi); ((RooRealVar *)poi.first())->setVal(poiValueForBModel); pProfile->getVal(); // this will do fit and set nuisance parameters to profiled values pPoiAndNuisance = new RooArgSet(); if(pBModel->GetNuisanceParameters()) pPoiAndNuisance->add(*pBModel->GetNuisanceParameters()); pPoiAndNuisance->add(*pBModel->GetParametersOfInterest()); cout << "\nShould use these parameter points to generate pseudo data for bkg only" << endl; pPoiAndNuisance->Print("v"); pBModel->SetSnapshot(*pPoiAndNuisance); delete pProfile; delete pNll; delete pPoiAndNuisance; // save workspace to file newworkspace->writeToFile("ws_twobin.root"); // clean up delete newworkspace; delete pData; delete pSbModel; delete pBModel; } // ----- end of tutorial ----------------------------------------
void ztonunu1() { // RooMsgService::instance().addStream(DEBUG,Topic(Tracing),ClassName("RooPoisson"),OutputFile("debug.log")) ; float acc_mm_mean( 0.98 ) ; float acc_mm_err( 0.02 ) ; float acc_ee_mean( 0.98 ) ; float acc_ee_err( 0.02 ) ; float eff_mm_mean( 0.77 ) ; float eff_mm_err( 0.08 ) ; float eff_ee_mean( 0.76 ) ; float eff_ee_err( 0.08 ) ; RooRealVar* rv_Nsbee = new RooRealVar( "Nsbee" ,"Nsbee" , 0., 100. ) ; RooRealVar* rv_Nsbmm = new RooRealVar( "Nsbmm" ,"Nsbmm" , 0., 100. ) ; RooRealVar* rv_Nsigee = new RooRealVar( "Nsigee" ,"Nsigee" , 0., 100. ) ; RooRealVar* rv_Nsigmm = new RooRealVar( "Nsigmm" ,"Nsigmm" , 0., 100. ) ; rv_Nsbee->setVal( 5 ) ; rv_Nsbmm->setVal( 3 ) ; rv_Nsigee->setVal( 4 ) ; rv_Nsigmm->setVal( 3 ) ; RooRealVar* rv_mu_Znnsb = new RooRealVar( "mu_Znnsb" , "mu_Znnsb" , 0., 100. ) ; RooRealVar* rv_mu_Znnsig = new RooRealVar( "mu_Znnsig" , "mu_Znnsig" , 0., 100. ) ; rv_mu_Znnsb->setVal( 37 ) ; // starting value rv_mu_Znnsig->setVal( 17. ) ; // starting value RooRealVar* rv_bfRatio = new RooRealVar( "bfRatio", "bfRatio", 0., 10. ) ; rv_bfRatio->setVal( 5.95 ) ; rv_bfRatio->setConstant( kTRUE ) ; RooRealVar* rv_acc_mm = new RooRealVar( "acc_mm", "acc_mm", 0.001, 1.000 ) ; RooRealVar* rv_acc_ee = new RooRealVar( "acc_ee", "acc_ee", 0.001, 1.000 ) ; RooRealVar* rv_eff_mm = new RooRealVar( "eff_mm", "eff_mm", 0.001, 1.000 ) ; RooRealVar* rv_eff_ee = new RooRealVar( "eff_ee", "eff_ee", 0.001, 1.000 ) ; rv_acc_mm->setVal( acc_mm_mean ) ; rv_acc_ee->setVal( acc_ee_mean ) ; rv_eff_mm->setVal( eff_mm_mean ) ; rv_eff_ee->setVal( eff_ee_mean ) ; RooRealVar* rv_lumi_ratio = new RooRealVar( "lumi_ratio", "lumi_ratio", 0., 10. ) ; rv_lumi_ratio -> setVal( 686./869. ) ; rv_lumi_ratio -> setConstant( kTRUE) ; RooFormulaVar* rv_mu_Zeesb = new RooFormulaVar( "mu_Zeesb", "mu_Znnsb * ( acc_ee * eff_ee / (bfRatio*lumi_ratio) )", RooArgSet( *rv_mu_Znnsb, *rv_acc_ee, *rv_eff_ee, *rv_bfRatio, *rv_lumi_ratio ) ) ; RooFormulaVar* rv_mu_Zmmsb = new RooFormulaVar( "mu_Zmmsb", "mu_Znnsb * ( acc_mm * eff_mm / (bfRatio*lumi_ratio) )", RooArgSet( *rv_mu_Znnsb, *rv_acc_mm, *rv_eff_mm, *rv_bfRatio, *rv_lumi_ratio ) ) ; RooFormulaVar* rv_mu_Zeesig = new RooFormulaVar( "mu_Zeesig", "mu_Znnsig * ( acc_ee * eff_ee / (bfRatio*lumi_ratio) )", RooArgSet( *rv_mu_Znnsig, *rv_acc_ee, *rv_eff_ee, *rv_bfRatio, *rv_lumi_ratio ) ) ; RooFormulaVar* rv_mu_Zmmsig = new RooFormulaVar( "mu_Zmmsig", "mu_Znnsig * ( acc_mm * eff_mm / (bfRatio*lumi_ratio) )", RooArgSet( *rv_mu_Znnsig, *rv_acc_mm, *rv_eff_mm, *rv_bfRatio, *rv_lumi_ratio ) ) ; RooFormulaVar* rv_n_sbee = new RooFormulaVar( "n_sbee" , "mu_Zeesb" , RooArgSet( *rv_mu_Zeesb ) ) ; RooFormulaVar* rv_n_sbmm = new RooFormulaVar( "n_sbmm" , "mu_Zmmsb" , RooArgSet( *rv_mu_Zmmsb ) ) ; RooFormulaVar* rv_n_sigee = new RooFormulaVar( "n_sigee" , "mu_Zeesig" , RooArgSet( *rv_mu_Zeesig ) ) ; RooFormulaVar* rv_n_sigmm = new RooFormulaVar( "n_sigmm" , "mu_Zmmsig" , RooArgSet( *rv_mu_Zmmsig ) ) ; RooGaussian* pdf_acc_mm = new RooGaussian( "pdf_acc_mm", "Gaussian pdf for Z to mumu acceptance", *rv_acc_mm, RooConst( acc_mm_mean ), RooConst( acc_mm_err ) ) ; RooGaussian* pdf_acc_ee = new RooGaussian( "pdf_acc_ee", "Gaussian pdf for Z to ee acceptance", *rv_acc_ee, RooConst( acc_ee_mean ), RooConst( acc_ee_err ) ) ; RooGaussian* pdf_eff_mm = new RooGaussian( "pdf_eff_mm", "Gaussian pdf for Z to mumu efficiency", *rv_eff_mm, RooConst( eff_mm_mean ), RooConst( eff_mm_err ) ) ; RooGaussian* pdf_eff_ee = new RooGaussian( "pdf_eff_ee", "Gaussian pdf for Z to ee efficiency", *rv_eff_ee, RooConst( eff_ee_mean ), RooConst( eff_ee_err ) ) ; RooPoisson* pdf_Nsbee = new RooPoisson( "pdf_Nsbee" , "Nsb , Z to ee Poisson PDF", *rv_Nsbee , *rv_n_sbee ) ; RooPoisson* pdf_Nsbmm = new RooPoisson( "pdf_Nsbmm" , "Nsb , Z to mm Poisson PDF", *rv_Nsbmm , *rv_n_sbmm ) ; RooPoisson* pdf_Nsigee = new RooPoisson( "pdf_Nsigee" , "Nsig, Z to ee Poisson PDF", *rv_Nsigee , *rv_n_sigee ) ; RooPoisson* pdf_Nsigmm = new RooPoisson( "pdf_Nsigmm" , "Nsig, Z to mm Poisson PDF", *rv_Nsigmm , *rv_n_sigmm ) ; RooArgSet pdflist ; pdflist.add( *pdf_acc_mm ) ; pdflist.add( *pdf_acc_ee ) ; pdflist.add( *pdf_eff_mm ) ; pdflist.add( *pdf_eff_ee ) ; pdflist.add( *pdf_Nsbee ) ; pdflist.add( *pdf_Nsbmm ) ; pdflist.add( *pdf_Nsigee ) ; pdflist.add( *pdf_Nsigmm ) ; RooProdPdf* znnLikelihood = new RooProdPdf( "znnLikelihood", "Z to nunu likelihood", pdflist ) ; RooArgSet observedParametersList ; observedParametersList.add( *rv_Nsbee ) ; observedParametersList.add( *rv_Nsbmm ) ; observedParametersList.add( *rv_Nsigee ) ; observedParametersList.add( *rv_Nsigmm ) ; RooDataSet* dsObserved = new RooDataSet( "ztonn_rds", "Z to nunu dataset", observedParametersList ) ; dsObserved->add( observedParametersList ) ; //// RooDataSet* dsObserved = znnLikelihood->generate( observedParametersList, 1) ; RooWorkspace* znnWorkspace = new RooWorkspace("ztonn_ws") ; znnWorkspace->import( *znnLikelihood ) ; znnWorkspace->import( *dsObserved ) ; znnWorkspace->Print() ; dsObserved->printMultiline(cout, 1, kTRUE, "") ; RooFitResult* fitResult = znnLikelihood->fitTo( *dsObserved, Verbose(true), Save(true) ) ; printf("\n\n----- Constant parameters:\n") ; RooArgList constPars = fitResult->constPars() ; for ( int pi=0; pi<constPars.getSize(); pi++ ) { constPars[pi].Print() ; } // pi. printf("\n\n----- Floating parameters:\n") ; RooArgList floatPars = fitResult->floatParsFinal() ; for ( int pi=0; pi<floatPars.getSize(); pi++ ) { floatPars[pi].Print() ; } // pi. printf("\n\n") ; ProfileLikelihoodCalculator plc_znn_sb( *dsObserved, *znnLikelihood, RooArgSet( *rv_mu_Znnsb ) ) ; ProfileLikelihoodCalculator plc_znn_sig( *dsObserved, *znnLikelihood, RooArgSet( *rv_mu_Znnsig ) ) ; plc_znn_sb.SetTestSize(0.32) ; plc_znn_sig.SetTestSize(0.32) ; ConfInterval* sb_znn_interval = plc_znn_sb.GetInterval() ; float sbZnnLow = ((LikelihoodInterval*) sb_znn_interval)->LowerLimit(*rv_mu_Znnsb) ; float sbZnnHigh = ((LikelihoodInterval*) sb_znn_interval)->UpperLimit(*rv_mu_Znnsb) ; printf("\n\n znn SB interval %6.1f to %6.1f\n", sbZnnLow, sbZnnHigh ) ; ConfInterval* sig_znn_interval = plc_znn_sig.GetInterval() ; float sigZnnLow = ((LikelihoodInterval*) sig_znn_interval)->LowerLimit(*rv_mu_Znnsig) ; float sigZnnHigh = ((LikelihoodInterval*) sig_znn_interval)->UpperLimit(*rv_mu_Znnsig) ; printf("\n\n znn SIG interval %6.1f to %6.1f\n", sigZnnLow, sigZnnHigh ) ; TCanvas* c_prof_sb = new TCanvas("c_prof_sb","SB Z to nunu profile") ; LikelihoodIntervalPlot plot_znn_sb((LikelihoodInterval*)sb_znn_interval) ; plot_znn_sb.Draw() ; c_prof_sb->SaveAs("znn_sb_profile.png") ; TCanvas* c_prof_sig = new TCanvas("c_prof_sig","sig Z to nunu profile") ; LikelihoodIntervalPlot plot_znn_sig((LikelihoodInterval*)sig_znn_interval) ; plot_znn_sig.Draw() ; c_prof_sig->SaveAs("znn_sig_profile.png") ; }
void splitws(string inFolderName, double mass, string channel) { cout << "Splitting workspace in " << channel << endl; int flatInterpCode = 4; int shapeInterpCode = 4; bool do2011 = 0; if (inFolderName.find("2011") != string::npos) do2011 = 1; bool conditionalAsimov = 0; bool doData = 1; //if (inFolderName.find("_blind_") != string::npos) { //conditionalAsimov = 0; //} //else { //conditionalAsimov = 1; //} set<string> channelNames; if (channel == "01j") { channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":"")); } else if (channel == "0j") { channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":"")); } else if (channel == "1j") { channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":"")); } else if (channel == "OF01j") { channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_sscr_0j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_sscr_1j"+string(!do2011?"_2012":"")); } else if (channel == "OF0j") { channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_sscr_0j"+string(!do2011?"_2012":"")); } else if (channel == "OF1j") { channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_sscr_1j"+string(!do2011?"_2012":"")); } else if (channel == "SF01j") { channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":"")); } else if (channel == "SF0j") { channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":"")); } else if (channel == "SF1j") { channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":"")); } else if (channel == "2j") { channelNames.insert("em_signalLike1_2j"+string(!do2011?"_2012":"")); channelNames.insert("ee_signalLike1_2j"+string(!do2011?"_2012":"")); channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":"")); } else if (channel == "OF2j") { channelNames.insert("em_signalLike1_2j"+string(!do2011?"_2012":"")); channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":"")); } else if (channel == "SF2j") { channelNames.insert("ee_signalLike1_2j"+string(!do2011?"_2012":"")); channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":"")); } else if (channel == "OF") { channelNames.insert("em_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_0j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike1_1j"+string(!do2011?"_2012":"")); channelNames.insert("me_signalLike2_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":"")); channelNames.insert("em_signalLike1_2j"+string(!do2011?"_2012":"")); channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":"")); } else if (channel == "SF") { channelNames.insert("SF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_0j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_0j"+string(!do2011?"_2012":"")); channelNames.insert("SF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_AfrecSR_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_ASR_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("SF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CfrecZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_CZpeak_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_mainControl_1j"+string(!do2011?"_2012":"")); channelNames.insert("OF_topbox_1j"+string(!do2011?"_2012":"")); channelNames.insert("ee_signalLike1_2j"+string(!do2011?"_2012":"")); channelNames.insert("SF_topbox_2j"+string(!do2011?"_2012":"")); } else { cout << "Channel " << channel << " not defined. Please check!" << endl; exit(1); } // bool fix = 1; stringstream inFileName; inFileName << "workspaces/" << inFolderName << "/" << mass << ".root"; TFile f(inFileName.str().c_str()); RooWorkspace* w = (RooWorkspace*)f.Get("combWS"); if (!w) w = (RooWorkspace*)f.Get("combined"); RooDataSet* data = (RooDataSet*)w->data("combData"); if (!data) data = (RooDataSet*)w->data("obsData"); ModelConfig* mc = (ModelConfig*)w->obj("ModelConfig"); RooRealVar* weightVar = w->var("weightVar"); RooRealVar* mu = (RooRealVar*)mc->GetParametersOfInterest()->first(); if (!mu) mu = w->var("SigXsecOverSM"); const RooArgSet* mc_obs = mc->GetObservables(); const RooArgSet* mc_nuis = mc->GetNuisanceParameters(); const RooArgSet* mc_globs = mc->GetGlobalObservables(); const RooArgSet* mc_poi = mc->GetParametersOfInterest(); RooArgSet nuis = *mc_nuis; RooArgSet antiNuis = *mc_nuis; RooArgSet globs = *mc_globs; RooArgSet antiGlobs = *mc_globs; RooArgSet allParams; RooSimultaneous* simPdf = (RooSimultaneous*)mc->GetPdf(); RooCategory* cat = (RooCategory*)&simPdf->indexCat(); RooArgSet nuis_tmp = nuis; RooArgSet fullConstraints = *simPdf->getAllConstraints(*mc_obs,nuis_tmp,false); vector<string> foundChannels; vector<string> skippedChannels; cout << "Getting constraints" << endl; map<string, RooDataSet*> data_map; map<string, RooAbsPdf*> pdf_map; RooCategory* decCat = new RooCategory("dec_channel","dec_channel"); // int i = 0; TIterator* catItr = cat->typeIterator(); RooCatType* type; RooArgSet allConstraints; while ((type = (RooCatType*)catItr->Next())) { RooAbsPdf* pdf = simPdf->getPdf(type->GetName()); string typeName(type->GetName()); if (channelNames.size() && channelNames.find(typeName) == channelNames.end()) { skippedChannels.push_back(typeName); continue; } cout << "On channel " << type->GetName() << endl; foundChannels.push_back(typeName); decCat->defineType(type->GetName()); // pdf->getParameters(*data)->Print("v"); RooArgSet nuis_tmp1 = nuis; RooArgSet nuis_tmp2 = nuis; RooArgSet* constraints = pdf->getAllConstraints(*mc_obs, nuis_tmp1, true); constraints->Print(); allConstraints.add(*constraints); } catItr->Reset(); while ((type = (RooCatType*)catItr->Next())) { RooAbsPdf* pdf = simPdf->getPdf(type->GetName()); string typeName(type->GetName()); cout << "Considering type " << typeName << endl; if (channelNames.size() && channelNames.find(typeName) == channelNames.end()) continue; cout << "On channel " << type->GetName() << endl; RooArgSet nuis_tmp1 = nuis; RooArgSet nuis_tmp2 = nuis; RooArgSet* constraints = pdf->getAllConstraints(*mc_obs, nuis_tmp1, true); cout << "Adding pdf to map: " << typeName << " = " << pdf->GetName() << endl; pdf_map[typeName] = pdf; RooProdPdf prod("prod","prod",*constraints); RooArgSet* params = pdf->getParameters(*data); antiNuis.remove(*params); antiGlobs.remove(*params); allParams.add(*params); // cout << type->GetName() << endl; } // return; RooArgSet decNuis; TIterator* nuiItr = mc_nuis->createIterator(); TIterator* parItr = allParams.createIterator(); RooAbsArg* nui, *par; while ((par = (RooAbsArg*)parItr->Next())) { nuiItr->Reset(); while ((nui = (RooAbsArg*)nuiItr->Next())) { if (par == nui) decNuis.add(*nui); } } RooArgSet decGlobs; TIterator* globItr = mc_globs->createIterator(); parItr->Reset(); RooAbsArg* glob; while ((par = (RooAbsArg*)parItr->Next())) { globItr->Reset(); while ((glob = (RooAbsArg*)globItr->Next())) { if (par == glob) decGlobs.add(*glob); } } // antiNuis.Print(); // nuis.Print(); // globs.Print(); // i = 0; TList* datalist = data->split(*cat, true); TIterator* dataItr = datalist->MakeIterator(); RooAbsData* ds; while ((ds = (RooAbsData*)dataItr->Next())) { string typeName(ds->GetName()); if (channelNames.size() && channelNames.find(typeName) == channelNames.end()) continue; cout << "Adding dataset to map: " << ds->GetName() << endl; data_map[string(ds->GetName())] = (RooDataSet*)ds; cout << ds->GetName() << endl; } RooSimultaneous* decPdf = new RooSimultaneous("decPdf","decPdf",pdf_map,*decCat); RooArgSet decObs = *decPdf->getObservables(data); // decObs.add(*(RooAbsArg*)weightVar); decObs.add(*(RooAbsArg*)decCat); decObs.Print(); nuis.remove(antiNuis); globs.remove(antiGlobs); // nuis.Print("v"); RooDataSet* decData = new RooDataSet("obsData","obsData",RooArgSet(decObs,*(RooAbsArg*)weightVar),Index(*decCat),Import(data_map),WeightVar(*weightVar)); decData->Print(); RooArgSet poi(*(RooAbsArg*)mu); RooWorkspace decWS("combined"); ModelConfig decMC("ModelConfig",&decWS); decMC.SetPdf(*decPdf); decMC.SetObservables(decObs); decMC.SetNuisanceParameters(decNuis); decMC.SetGlobalObservables(decGlobs); decMC.SetParametersOfInterest(poi); decMC.Print(); decWS.import(*decPdf); decWS.import(decMC); decWS.import(*decData); // decWS.Print(); ModelConfig* mcInWs = (ModelConfig*)decWS.obj("ModelConfig"); decPdf = (RooSimultaneous*)mcInWs->GetPdf(); // setup(mcInWs); // return; mcInWs->GetNuisanceParameters()->Print("v"); mcInWs->GetGlobalObservables()->Print("v"); // decData->tree()->Scan("*"); // Make asimov data RooArgSet funcs = decWS.allFunctions(); TIterator* it = funcs.createIterator(); TObject* tempObj = 0; while((tempObj=it->Next())) { FlexibleInterpVar* flex = dynamic_cast<FlexibleInterpVar*>(tempObj); if(flex) { flex->setAllInterpCodes(flatInterpCode); } PiecewiseInterpolation* piece = dynamic_cast<PiecewiseInterpolation*>(tempObj); if(piece) { piece->setAllInterpCodes(shapeInterpCode); } } RooDataSet* dataInWs = (RooDataSet*)decWS.data("obsData"); makeAsimovData(mcInWs, conditionalAsimov && doData, &decWS, mcInWs->GetPdf(), dataInWs, 0); makeAsimovData(mcInWs, conditionalAsimov && doData, &decWS, mcInWs->GetPdf(), dataInWs, 1); makeAsimovData(mcInWs, conditionalAsimov && doData, &decWS, mcInWs->GetPdf(), dataInWs, 2); system(("mkdir -vp workspaces/"+inFolderName+"_"+channel).c_str()); stringstream outFileName; outFileName << "workspaces/" << inFolderName << "_" << channel << "/" << mass << ".root"; cout << "Exporting" << endl; decWS.writeToFile(outFileName.str().c_str()); cout << "\nIncluded the following channels: " << endl; for (int i=0;i<(int)foundChannels.size();i++) { cout << "-> " << foundChannels[i] << endl; } cout << "\nSkipping the following channels: " << endl; for (int i=0;i<(int)skippedChannels.size();i++) { cout << "-> " << skippedChannels[i] << endl; } cout << "Done" << endl; // decPdf->fitTo(*decData, Hesse(0), Minos(0), PrintLevel(0)); }
void MakeWorkspace( void ){ // // this function implements a RooFit model for a counting experiment // // create workspace RooWorkspace * pWs = new RooWorkspace("myWS"); // observable: number of events pWs->factory( "n[0.0]" ); // integrated luminosity with systematics pWs->factory( "lumi_nom[5000.0, 4000.0, 6000.0]" ); pWs->factory( "lumi_kappa[1.045]" ); pWs->factory( "cexpr::alpha_lumi('pow(lumi_kappa,beta_lumi)',lumi_kappa,beta_lumi[0,-5,5])" ); pWs->factory( "prod::lumi(lumi_nom,alpha_lumi)" ); pWs->factory( "Gaussian::constr_lumi(beta_lumi,glob_lumi[0,-5,5],1)" ); // cross section - parameter of interest pWs->factory( "xsec[0.001,0.0,0.1]" ); // selection efficiency * acceptance with systematics pWs->factory( "efficiency_nom[0.1, 0.05, 0.15]" ); pWs->factory( "efficiency_kappa[1.10]" ); pWs->factory( "cexpr::alpha_efficiency('pow(efficiency_kappa,beta_efficiency)',efficiency_kappa,beta_efficiency[0,-5,5])" ); pWs->factory( "prod::efficiency(efficiency_nom,alpha_efficiency)" ); pWs->factory( "Gaussian::constr_efficiency(beta_efficiency,glob_efficiency[0,-5,5],1)" ); // signal yield pWs->factory( "prod::nsig(lumi,xsec,efficiency)" ); // background yield with systematics pWs->factory( "nbkg_nom[10.0, 5.0, 15.0]" ); pWs->factory( "nbkg_kappa[1.10]" ); pWs->factory( "cexpr::alpha_nbkg('pow(nbkg_kappa,beta_nbkg)',nbkg_kappa,beta_nbkg[0,-5,5])" ); pWs->factory( "prod::nbkg(nbkg_nom,alpha_lumi,alpha_nbkg)" ); pWs->factory( "Gaussian::constr_nbkg(beta_nbkg,glob_nbkg[0,-5,5],1)" ); // full event yield pWs->factory("sum::yield(nsig,nbkg)"); // Core model: Poisson probability with mean signal+bkg pWs->factory( "Poisson::model_core(n,yield)" ); // define Bayesian prior PDF for POI pWs->factory( "Uniform::prior(xsec)" ); // model with systematics pWs->factory( "PROD::model(model_core,constr_lumi,constr_efficiency,constr_nbkg)" ); // create set of observables (will need it for datasets and ModelConfig later) RooRealVar * pObs = pWs->var("n"); // get the pointer to the observable RooArgSet obs("observables"); obs.add(*pObs); // create the dataset pObs->setVal(11); // this is your observed data: we counted ten events RooDataSet * data = new RooDataSet("data", "data", obs); data->add( *pObs ); // import dataset into workspace pWs->import(*data); // create set of global observables (need to be defined as constants) pWs->var("glob_lumi")->setConstant(true); pWs->var("glob_efficiency")->setConstant(true); pWs->var("glob_nbkg")->setConstant(true); RooArgSet globalObs("global_obs"); globalObs.add( *pWs->var("glob_lumi") ); globalObs.add( *pWs->var("glob_efficiency") ); globalObs.add( *pWs->var("glob_nbkg") ); // create set of parameters of interest (POI) RooArgSet poi("poi"); poi.add( *pWs->var("xsec") ); // create set of nuisance parameters RooArgSet nuis("nuis"); nuis.add( *pWs->var("beta_lumi") ); nuis.add( *pWs->var("beta_efficiency") ); nuis.add( *pWs->var("beta_nbkg") ); // create signal+background Model Config RooStats::ModelConfig sbHypo("SbHypo"); sbHypo.SetWorkspace( *pWs ); sbHypo.SetPdf( *pWs->pdf("model") ); sbHypo.SetObservables( obs ); sbHypo.SetGlobalObservables( globalObs ); sbHypo.SetParametersOfInterest( poi ); sbHypo.SetNuisanceParameters( nuis ); sbHypo.SetPriorPdf( *pWs->pdf("prior") ); // this is optional // fix all other variables in model: // everything except observables, POI, and nuisance parameters // must be constant pWs->var("lumi_nom")->setConstant(true); pWs->var("efficiency_nom")->setConstant(true); pWs->var("nbkg_nom")->setConstant(true); pWs->var("lumi_kappa")->setConstant(true); pWs->var("efficiency_kappa")->setConstant(true); pWs->var("nbkg_kappa")->setConstant(true); RooArgSet fixed("fixed"); fixed.add( *pWs->var("lumi_nom") ); fixed.add( *pWs->var("efficiency_nom") ); fixed.add( *pWs->var("nbkg_nom") ); fixed.add( *pWs->var("lumi_kappa") ); fixed.add( *pWs->var("efficiency_kappa") ); fixed.add( *pWs->var("nbkg_kappa") ); // set parameter snapshot that corresponds to the best fit to data RooAbsReal * pNll = sbHypo.GetPdf()->createNLL( *data ); RooAbsReal * pProfile = pNll->createProfile( globalObs ); // do not profile global observables pProfile->getVal(); // this will do fit and set POI and nuisance parameters to fitted values RooArgSet * pPoiAndNuisance = new RooArgSet("poiAndNuisance"); pPoiAndNuisance->add(*sbHypo.GetNuisanceParameters()); pPoiAndNuisance->add(*sbHypo.GetParametersOfInterest()); sbHypo.SetSnapshot(*pPoiAndNuisance); delete pProfile; delete pNll; delete pPoiAndNuisance; // import S+B ModelConfig into workspace pWs->import( sbHypo ); // create background-only Model Config from the S+B one RooStats::ModelConfig bHypo = sbHypo; bHypo.SetName("BHypo"); bHypo.SetWorkspace(*pWs); // set parameter snapshot for bHypo, setting xsec=0 // it is useful to understand how this block of code works // but you can also use it as a recipe to make a parameter snapshot pNll = bHypo.GetPdf()->createNLL( *data ); RooArgSet poiAndGlobalObs("poiAndGlobalObs"); poiAndGlobalObs.add( poi ); poiAndGlobalObs.add( globalObs ); pProfile = pNll->createProfile( poiAndGlobalObs ); // do not profile POI and global observables ((RooRealVar *)poi.first())->setVal( 0 ); // set xsec=0 here pProfile->getVal(); // this will do fit and set nuisance parameters to profiled values pPoiAndNuisance = new RooArgSet( "poiAndNuisance" ); pPoiAndNuisance->add( nuis ); pPoiAndNuisance->add( poi ); bHypo.SetSnapshot(*pPoiAndNuisance); delete pProfile; delete pNll; delete pPoiAndNuisance; // import model config into workspace pWs->import( bHypo ); // print out the workspace contents pWs->Print(); // save workspace to file pWs -> SaveAs("workspace.root"); return; }
void Back_2dFit(void){ TFile *ifile = TFile::Open("/home/vitaly/B0toDh0/TMVA/fil_b2dh_gen.root"); TTree *tree = (TTree*)ifile->Get("TEvent"); RooCategory b0f("b0f","b0f"); b0f.defineType("comb",-1); RooArgSet argset; const double mbcMin = 5.20; const double mbcMax = 5.29; const double deMin = -0.15; const double deMax = 0.3; RooRealVar mbc("mbc","M_{bc}",mbcMin,mbcMax,"GeV"); argset.add(mbc); mbc.setRange("Signal",mbc_min,mbc_max); mbc.setRange("mbcSignal",mbc_min,mbc_max); mbc.setRange("deSignal",mbcMin,mbcMax); RooRealVar de("de","#DeltaE",deMin,deMax,"GeV"); argset.add(de); de.setRange("Signal",de_min,de_max); de.setRange("mbcSignal",deMin,deMax); de.setRange("deSignal",de_min,de_max); RooRealVar md("md","md",DMass-md_cut,DMass+md_cut,"GeV"); argset.add(md); RooRealVar mk("mk","mk",KMass-mk_cut,KMass+mk_cut,"GeV"); argset.add(mk); RooRealVar mpi0("mpi0","mpi0",Pi0Mass-mpi0_cut,Pi0Mass+mpi0_cut,"GeV"); argset.add(mpi0); RooRealVar bdtgs("bdtgs","bdtgs",bdtgs_cut,1.); argset.add(bdtgs); RooRealVar atckpi_max("atckpi_max","atckpi_max",0.,atckpi_cut); argset.add(atckpi_max); argset.add(b0f); RooDataSet ds("ds","ds",tree,argset); RooDataSet* ds0 = ds.reduce(RooArgSet(de,mbc)); RooDataHist* dh = ds0->binnedClone(); ds.Print(); dh->Print(); //////////// // de pdf // //////////// // RooRealVar c1("c1","c1",mc_c1,-1.,0.); if(cComb) c1.setConstant(kTRUE); // RooRealVar c2("c2","c2",mc_c2,0.,0.1); if(cComb) c2.setConstant(kTRUE); RooRealVar c3("c3","c3",mc_c1,-1.,0.); if(cComb) c3.setConstant(kTRUE); RooRealVar c4("c4","c4",mc_c2,0.,0.1); if(cComb) c4.setConstant(kTRUE); RooChebychev pdf_de("pdf_de","pdf_de",de,RooArgSet(c3,c4)); ///////////// // mbc pdf // ///////////// RooRealVar argpar("argpar","argus shape parameter",mc_argpar,-100.,-1.); if(cComb) argpar.setConstant(kTRUE); RooRealVar argedge("argedge","argedge",mc_argedge,5.285,5.292); if(cComb) argedge.setConstant(kTRUE); RooArgusBG pdf_mbc("pdf_mbc","Argus PDF",mbc,argedge,argpar); ///////// // pdf // ///////// RooProdPdf pdf("pdf","pdf",RooArgList(pdf_de,pdf_mbc)); pdf.fitTo(*dh,Verbose(),Timer(true)); ///////////// // Plots // ///////////// // de // RooPlot* deFrame = de.frame(); ds.plotOn(deFrame,DataError(RooAbsData::SumW2),MarkerSize(1),MarkerColor(kGreen)); pdf.plotOn(deFrame,LineWidth(2),LineColor(kGreen)); ds.plotOn(deFrame,DataError(RooAbsData::SumW2),MarkerSize(1),CutRange("mbcSignal")); pdf.plotOn(deFrame,LineWidth(2),ProjectionRange("mbcSignal")); RooHist* hdepull = deFrame->pullHist(); RooPlot* dePull = de.frame(Title("#Delta E pull distribution")); dePull->addPlotable(hdepull,"P"); dePull->GetYaxis()->SetRangeUser(-5,5); TCanvas* cm = new TCanvas("#Delta E, Signal","#Delta E, Signal",600,700); cm->cd(); TPad *pad3 = new TPad("pad3","pad3",0.01,0.20,0.99,0.99); TPad *pad4 = new TPad("pad4","pad4",0.01,0.01,0.99,0.20); pad3->Draw(); pad4->Draw(); pad3->cd(); pad3->SetLeftMargin(0.15); pad3->SetFillColor(0); deFrame->GetXaxis()->SetTitleSize(0.05); deFrame->GetXaxis()->SetTitleOffset(0.85); deFrame->GetXaxis()->SetLabelSize(0.04); deFrame->GetYaxis()->SetTitleOffset(1.6); deFrame->Draw(); stringstream out; out.str(""); out << "#chi^{2}/n.d.f = " << deFrame->chiSquare(); TPaveText *pt = new TPaveText(0.6,0.8,0.98,0.9,"brNDC"); pt->SetFillColor(0); pt->SetTextAlign(12); pt->AddText(out.str().c_str()); pt->Draw(); TLine *de_line_RIGHT = new TLine(de_max,0,de_max,200); de_line_RIGHT->SetLineColor(kRed); de_line_RIGHT->SetLineStyle(1); de_line_RIGHT->SetLineWidth((Width_t)2.); de_line_RIGHT->Draw(); TLine *de_line_LEFT = new TLine(de_min,0,de_min,200); de_line_LEFT->SetLineColor(kRed); de_line_LEFT->SetLineStyle(1); de_line_LEFT->SetLineWidth((Width_t)2.); de_line_LEFT->Draw(); pad4->cd(); pad4->SetLeftMargin(0.15); pad4->SetFillColor(0); dePull->SetMarkerSize(0.05); dePull->Draw(); TLine *de_lineUP = new TLine(deMin,3,deMax,3); de_lineUP->SetLineColor(kBlue); de_lineUP->SetLineStyle(2); de_lineUP->Draw(); TLine *de_line = new TLine(deMin,0,deMax,0); de_line->SetLineColor(kBlue); de_line->SetLineStyle(1); de_line->SetLineWidth((Width_t)2.); de_line->Draw(); TLine *de_lineDOWN = new TLine(deMin,-3,deMax,-3); de_lineDOWN->SetLineColor(kBlue); de_lineDOWN->SetLineStyle(2); de_lineDOWN->Draw(); cm->Update(); // mbc // RooPlot* mbcFrame = mbc.frame(); ds.plotOn(mbcFrame,DataError(RooAbsData::SumW2),MarkerSize(1),MarkerColor(kGreen)); pdf.plotOn(mbcFrame,LineWidth(2),LineColor(kGreen)); ds.plotOn(mbcFrame,DataError(RooAbsData::SumW2),MarkerSize(1),CutRange("deSignal")); pdf.plotOn(mbcFrame,LineWidth(2),ProjectionRange("deSignal")); RooHist* hmbcpull = mbcFrame->pullHist(); RooPlot* mbcPull = mbc.frame(Title("#Delta E pull distribution")); mbcPull->addPlotable(hmbcpull,"P"); mbcPull->GetYaxis()->SetRangeUser(-5,5); TCanvas* cmmbc = new TCanvas("M_{bc}, Signal","M_{bc}, Signal",600,700); cmmbc->cd(); TPad *pad1 = new TPad("pad1","pad1",0.01,0.20,0.99,0.99); TPad *pad2 = new TPad("pad2","pad2",0.01,0.01,0.99,0.20); pad1->Draw(); pad2->Draw(); pad1->cd(); pad1->SetLeftMargin(0.15); pad1->SetFillColor(0); mbcFrame->GetXaxis()->SetTitleSize(0.05); mbcFrame->GetXaxis()->SetTitleOffset(0.85); mbcFrame->GetXaxis()->SetLabelSize(0.04); mbcFrame->GetYaxis()->SetTitleOffset(1.6); mbcFrame->Draw(); out.str(""); out << "#chi^{2}/n.d.f = " << mbcFrame->chiSquare(); TPaveText *ptmbc = new TPaveText(0.6,0.8,0.98,0.9,"brNDC"); ptmbc->SetFillColor(0); ptmbc->SetTextAlign(12); ptmbc->AddText(out.str().c_str()); ptmbc->Draw(); TLine *mbc_line_RIGHT = new TLine(mbc_max,0,mbc_max,150); mbc_line_RIGHT->SetLineColor(kRed); mbc_line_RIGHT->SetLineStyle(1); mbc_line_RIGHT->SetLineWidth((Width_t)2.); mbc_line_RIGHT->Draw(); TLine *mbc_line_LEFT = new TLine(mbc_min,0,mbc_min,150); mbc_line_LEFT->SetLineColor(kRed); mbc_line_LEFT->SetLineStyle(1); mbc_line_LEFT->SetLineWidth((Width_t)2.); mbc_line_LEFT->Draw(); pad2->cd(); pad2->SetLeftMargin(0.15); pad2->SetFillColor(0); mbcPull->SetMarkerSize(0.05); mbcPull->Draw(); TLine *mbc_lineUP = new TLine(mbcMin,3,mbcMax,3); mbc_lineUP->SetLineColor(kBlue); mbc_lineUP->SetLineStyle(2); mbc_lineUP->Draw(); TLine *mbc_line = new TLine(mbcMin,0,mbcMax,0); mbc_line->SetLineColor(kBlue); mbc_line->SetLineStyle(1); mbc_line->SetLineWidth((Width_t)2.); mbc_line->Draw(); TLine *mbc_lineDOWN = new TLine(mbcMin,-3,mbcMax,-3); mbc_lineDOWN->SetLineColor(kBlue); mbc_lineDOWN->SetLineStyle(2); mbc_lineDOWN->Draw(); TH2D* hh_pdf = pdf.createHistogram("hh_data",de,Binning(50,-0.15,0.1),YVar(mbc,Binning(50,5.26,5.30))); hh_pdf->SetLineColor(kBlue); TCanvas* hhc = new TCanvas("hhc","hhc",600,600); hhc->cd(); hh_pdf->Draw("SURF"); cmmbc->Update(); }
void dzRooFit(const int _mode = 1, const int _h0mode = 10,const int EXP = -1){ TFile *omegafile; switch(_mode){ case 1: omegafile = TFile::Open("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_sigPi0_s4_full.root"); break; case 2: omegafile = TFile::Open("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_sigEta_full.root"); break; case 3: omegafile = TFile::Open("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_sigOmega_s1_full.root"); break; } TTree *omegatree = (TTree*)omegafile->Get("TEvent"); const double dz_min = -1.5; const double dz_max = 1.5; RooArgSet argset; RooCategory b0f("b0f","b0f"); b0f.defineType("sig",1); b0f.defineType("badpi0",5); argset.add(b0f); RooCategory exp("exp","exp"); if(EXP>0){ exp.defineType("expNo",EXP); } if(EXP == -2 || EXP == -3){ exp.defineType("7",7); exp.defineType("9",9); exp.defineType("11",11); exp.defineType("13",13); exp.defineType("15",15); exp.defineType("17",17); exp.defineType("21",21); exp.defineType("23",23); exp.defineType("25",25); exp.defineType("27",27); } if(EXP == -1 || EXP == -3){ exp.defineType("31",31); exp.defineType("33",33); exp.defineType("35",35); exp.defineType("37",37); exp.defineType("39",39); exp.defineType("41",41); exp.defineType("43",43); exp.defineType("45",45); exp.defineType("47",47); exp.defineType("49",49); exp.defineType("51",51); exp.defineType("55",55); exp.defineType("61",61); exp.defineType("63",63); exp.defineType("65",65); } argset.add(exp); RooCategory nptag("nptag","nptag"); nptag.defineType("nonp",0); // argset.add(nptag); RooRealVar dz("dz","dz",dz_min,dz_max,"mm"); argset.add(dz); RooRealVar sz_asc("sz_asc","dz_asc",0.01,0.15); argset.add(sz_asc); RooRealVar sz_sig("sz_sig","dz_sig",0.01,0.15); argset.add(sz_sig); RooRealVar chisq_z_asc("chisq_z_asc","chisq_z_asc",0.,200); argset.add(chisq_z_asc); RooRealVar chisq_z_sig("chisq_z_sig","chisq_z_sig",0.,200); argset.add(chisq_z_sig); // RooDataSet pids("pids","pids",pitree,argset); RooDataSet omegads("omegads","omegads",omegatree,argset,"(dz>0 || dz<0) && sz_asc>0 && sz_sig>0 && chisq_z_asc>0 && chisq_z_sig>0"); // pids.Print(); omegads.Print(); RooRealVar tau("tau","tau",0.196,0.01,1,"mm"); tau.setConstant(kTRUE); RooRealVar dz0Om("dz0Om","dz0Om",0,-3.,3.,"mm"); dz0Om.setConstant(kTRUE); RooRealVar s01sigOm("s01sigOm","s01sigOm",2,0.1,5.); RooRealVar s02sigOm("s02sigOm","s02sigOm",13,0.1,27.); RooRealVar fsigOm("fsigOm","fsigOm",0.9,0.,1.); // RooGaussModel g1Om("g1Om","g1Om",dz,dz0Om,s01Om,sz); // RooGaussModel g2Om("g2Om","g2Om",dz,dz0Om,s02Om,sz); RooDecay dec1SigOm("dec1SigOm","dec1SigOm",dz,tau,g1sigOm,RooDecay::DoubleSided); RooDecay dec2SigOm("dec2SigOm","dec2SigOm",dz,tau,g2sigOm,RooDecay::DoubleSided); RooAddPdf pdfsigOm("pdfsigOm","pdfsigOm",RooArgList(dec1SigOm,dec2SigOm),RooArgSet(fsigOm)); if(EXP!=55 && EXP>0){ fsigOm.setVal(1.); fsigOm.setConstant(kTRUE); s02sigOm.setConstant(kTRUE); } // RooDecay pdfsigOm("pdfsigOm","pdpsigOm",z_sig,tau,g1sigOm,RooDecay::SingleSided); // pdfsigPi.fitTo(pids,ConditionalObservables(szSigPi)); RooFitResult* fitRes = pdfsigOm.fitTo(omegads,Verbose(),ConditionalObservables(sz_asc)); // fitRes->Print(); /////////// // Plots // /////////// RooPlot* zFrameSig = z_asc.frame(); omegads.plotOn(zFrameSig,DataError(RooAbsData::SumW2),MarkerSize(1)); pdfsigOm.plotOn(zFrameSig,LineColor(kRed),ProjWData(omegads)); TCanvas* z_cm_sig = new TCanvas("z_{sig}, cm","z_{sig}, mm",700,500); z_cm_sig->cd(); omegads.statOn(zFrameSig,Layout(0.6,0.98,0.9),What("MR"),Label("#omega^{0}"),Format("NE",AutoPrecision(1))); TPad *pad1 = new TPad("pad1","pad1",0.01,0.00,0.99,0.99); pad1->Draw(); pad1->cd(); pad1->SetLeftMargin(0.15); pad1->SetFillColor(0); zFrameSig->GetXaxis()->SetTitleOffset(0.75); zFrameSig->GetXaxis()->SetLabelSize(0.05); zFrameSig->GetXaxis()->SetTitleSize(0.06); zFrameSig->GetYaxis()->SetTitleOffset(1.6); zFrameSig->Draw(); z_cm_sig->Update(); stringstream out; out.str(""); out << "pics/zAscFit_Exp" << EXP << ".png"; z_cm_sig->Print(out.str().c_str()); out.str(""); out << "pics/zAscFit_Exp" << EXP << ".root"; z_cm_sig->Print(out.str().c_str()); return; }
void Purity_2d_fit_etagg_v2(bool data = false) { TChain* tree = new TChain("TEvent"); if(!data) tree->Add("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_gen_0-1_full.root"); else tree->Add("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_data.root"); const int _mode = 2; const int _h0mode = 10; const int _b0f = -1; // gROOT->ProcessLine(".L pdfs/RooRhoDeltaEPdf.cxx+"); RooCategory b0f("b0f","b0f"); b0f.defineType("signal",1); b0f.defineType("fsr",10); b0f.defineType("bad_pi0",5); b0f.defineType("peak1",3); b0f.defineType("peak2",4); b0f.defineType("peak3",11); b0f.defineType("peak4",20); b0f.defineType("comb",-1); RooArgSet argset; const double mbcMin = 5.20; const double mbcMax = 5.29; double deMin = -0.15; if(keysflag) deMin = -0.3; const double deMax = 0.3; const double elliscaleDe = TMath::Sqrt(4./TMath::Pi()); const double elliscaleMbc = TMath::Sqrt(4./TMath::Pi()); RooRealVar mbc_center("mbc_center","mbc_center",0.5*(mbc_min+mbc_max),mbc_min,mbc_max); mbc_center.setConstant(kTRUE); RooRealVar mbc_center_eq("mbc_center_eq","mbc_center_eq",mr_argedge_3-0.5*(mbc_max-mbc_min)*elliscaleMbc,mbc_min,mbc_max); mbc_center_eq.setConstant(kTRUE); RooRealVar de_center("de_center","de_center",0.5*(de_min+de_max),de_min,de_max); de_center.setConstant(kTRUE); RooRealVar mbc_radius("mbc_radius","mbc_radius",0.5*(mbc_max-mbc_min)*elliscaleMbc,0,0.5*(mbcMax-mbcMin)); mbc_radius.setConstant(kTRUE); RooRealVar de_radius("de_radius","de_radius",0.5*(de_max-de_min)*elliscaleDe,0.,0.5*(deMax-deMin)); de_radius.setConstant(kTRUE); RooRealVar mbc_radius1("mbc_radius1","mbc_radius1",0.5*(mbc_max-mbc_min),0,0.5*(mbcMax-mbcMin)); mbc_radius1.setConstant(kTRUE); RooRealVar de_radius1("de_radius1","de_radius1",0.5*(de_max-de_min),0.,0.5*(deMax-deMin)); de_radius1.setConstant(kTRUE); cout << 0.5*(mbc_min+mbc_max) << " " << 0.5*(mbc_max-mbc_min) << endl; cout << 0.5*(de_min+de_max) << " " << 0.5*(de_max-de_min) << endl; mbc_center.Print(); mbc_center_eq.Print(); const double BDTG_MIN = bdtg_cut_etagg; const double BDTG_MAX = 1; RooCategory mode("mode","mode"); mode.defineType("eta",2); RooCategory h0mode("h0mode","h0mode"); h0mode.defineType("gg",10); argset.add(mode); argset.add(h0mode); RooRealVar mbc("mbc","M_{bc}",0.5*(mbc_min+mbc_max),mbcMin,mbcMax,"GeV"); argset.add(mbc); mbc.setRange("Signal",mbc_min,mbc_max); mbc.setRange("mbcSignal",mbc_min,mbc_max); mbc.setRange("deSignal",mbcMin,mbcMax); RooRealVar de("de","#DeltaE",deMin,deMax,"GeV"); argset.add(de); de.setRange("Signal",de_min,de_max); de.setRange("mbcSignal",deMin,deMax); de.setRange("deSignal",de_min,de_max); RooRealVar md("md","md",DMass-md_cut,DMass+md_cut,"GeV"); argset.add(md); RooRealVar mk("mk","mk",KMass-mk_cut,KMass+mk_cut,"GeV"); argset.add(mk); RooRealVar mh0("mh0","mh0",EtaMass-meta_cut,EtaMass+meta_cut,"GeV"); argset.add(mh0); RooRealVar bdtg("bdtg","bdtg",BDTG_MIN,1.); argset.add(bdtg); RooRealVar atckpi_max("atckpi_max","atckpi_max",0.,atckpi_cut); argset.add(atckpi_max); if(!data) argset.add(b0f); RooDataSet ds("ds","ds",tree,argset,"mbc>0||mbc<=0"); // RooDataSet* ds0 = ds.reduce(RooArgSet(de,mbc)); stringstream out; if(!data) { out.str(""); out << "de<" << de_max << " && de>" << de_min; out << " && mbc>" << mbc_min << " && mbc<" << mbc_max; Roo1DTable* sigtable = ds.table(b0f,out.str().c_str()); sigtable->Print(); sigtable->Print("v"); Roo1DTable* fulltable = ds.table(b0f); fulltable->Print(); fulltable->Print("v"); } // RooDataHist* dh = ds0->binnedClone(); ds.Print(); //////////////// // Signal PDF // //////////////// //////////// // de pdf // //////////// if(!(_mode!=1 && _h0mode == 20 && _b0f == -1)) { RooRealVar de0("de0","de0",get_de0(_mode,_h0mode,_b0f),-0.2,0.1); if(cSIG) de0.setConstant(kTRUE); RooRealVar s1("s1","s1",get_s1(_mode,_h0mode,_b0f),0.,0.5); if(cSIG) s1.setConstant(kTRUE); RooGaussian g1("g1","g1",de,de0,s1); RooRealVar deCBl("deCBl","deCBl",get_deCBl(_mode,_h0mode,_b0f),-0.2,0.1); if(cSIG) deCBl.setConstant(kTRUE); RooRealVar sCBl("sCBl","sCBl",get_sCBl(_mode,_h0mode,_b0f),0.,0.5); if(cSIG) sCBl.setConstant(kTRUE); RooRealVar nl("nl","nl",get_nl(_mode,_h0mode,_b0f),0.,100.); if(cSIG) nl.setConstant(kTRUE); // RooRealVar nl("nl","nl",1.,0.,100.); nl.setConstant(kTRUE); RooRealVar alphal("alphal","alphal",get_alphal(_mode,_h0mode,_b0f),-10.,10.); if(cSIG) alphal.setConstant(kTRUE); RooRealVar deCBr("deCBr","deCBr",get_deCBr(_mode,_h0mode,_b0f),-0.2,0.1); if(cSIG) deCBr.setConstant(kTRUE); RooRealVar sCBr("sCBr","sCBr",get_sCBr(_mode,_h0mode,_b0f),0.,0.5); if(cSIG) sCBr.setConstant(kTRUE); RooRealVar nr("nr","nr",get_nr(_mode,_h0mode,_b0f),0.,100.); if(cSIG) nr.setConstant(kTRUE); RooRealVar alphar("alphar","alphar",get_alphar(_mode,_h0mode,_b0f),-10.,10.); if(cSIG) alphar.setConstant(kTRUE); RooCBShape CBl("CBl","CBl",de,deCBl,sCBl,alphal,nl); RooCBShape CBr("CBr","CBr",de,deCBr,sCBr,alphar,nr); RooRealVar fCBl("fCBl","fCBl",get_fCBl(_mode,_h0mode,_b0f),0.,1.); if(cSIG) fCBl.setConstant(kTRUE); RooRealVar fCBr("fCBr","fCBr",get_fCBr(_mode,_h0mode,_b0f),0.,1.); if(cSIG) fCBr.setConstant(kTRUE); RooAddPdf pdf_de_sig("pdf_de_sig","pdf_de_sig",RooArgList(CBl,CBr,g1),RooArgSet(fCBl,fCBr)); } if((_mode==3&&_h0mode == 20 || _mode==2) && _b0f == -1) { RooRealVar de0_201("de0_201","de0_201",get_de0(_mode,_h0mode,1),-0.1,0.1); de0_201.setConstant(kTRUE); RooRealVar s1_201("s1_201","s1_201",get_s1(_mode,_h0mode,1),0.,0.5); s1_201.setConstant(kTRUE); RooGaussian g1_201("g1_201","g1_201",de,de0_201,s1_201); RooRealVar deCBl_201("deCBl_201","deCBl_201",get_deCBl(_mode,_h0mode,1),-0.1,0.1); deCBl_201.setConstant(kTRUE); RooRealVar sCBl_201("sCBl_201","sCBl_201",get_sCBl(_mode,_h0mode,1),0.,0.5); sCBl_201.setConstant(kTRUE); RooRealVar nl_201("nl_201","nl_201",get_nl(_mode,_h0mode,1),0.,100.); nl_201.setConstant(kTRUE); RooRealVar alphal_201("alphal_201","alphal_201",get_alphal(_mode,_h0mode,1),-10.,10.); alphal_201.setConstant(kTRUE); RooRealVar deCBr_201("deCBr_201","deCBr_201",get_deCBr(_mode,_h0mode,1),-0.1,0.1); deCBr_201.setConstant(kTRUE); RooRealVar sCBr_201("sCBr_201","sCBr_201",get_sCBr(_mode,_h0mode,1),0.,0.5); sCBr_201.setConstant(kTRUE); RooRealVar nr_201("nr_201","nr_201",get_nr(_mode,_h0mode,1),0.,100.); nr_201.setConstant(kTRUE); RooRealVar alphar_201("alphar_201","alphar_201",get_alphar(_mode,_h0mode,1),-10.,10.); alphar_201.setConstant(kTRUE); RooCBShape CBl_201("CBl_201","CBl_201",de,deCBl_201,sCBl_201,alphal_201,nl_201); RooCBShape CBr_201("CBr_201","CBr_201",de,deCBr_201,sCBr_201,alphar_201,nr_201); RooRealVar fCBl_201("fCBl_201","fCBl_201",get_fCBl(_mode,_h0mode,1),0.,1.); fCBl_201.setConstant(kTRUE); RooRealVar fCBr_201("fCBr_201","fCBr_201",get_fCBr(_mode,_h0mode,1),0.,1.); fCBr_201.setConstant(kTRUE); RooAddPdf pdf_de_201("pdf_de_201","pdf_de_201",RooArgList(CBl_201,CBr_201,g1_201),RooArgSet(fCBl_201,fCBr_201)); RooRealVar de0_205("de0_205","de0_205",get_de0(_mode,_h0mode,5),-0.1,0.1); de0_205.setConstant(kTRUE); RooRealVar s1_205("s1_205","s1_205",get_s1(_mode,_h0mode,5),0.,0.5); s1_205.setConstant(kTRUE); RooGaussian g1_205("g1_205","g1_205",de,de0_205,s1_205); RooRealVar deCBl_205("deCBl_205","deCBl_205",get_deCBl(_mode,_h0mode,5),-0.1,0.1); deCBl_205.setConstant(kTRUE); RooRealVar sCBl_205("sCBl_205","sCBl_205",get_sCBl(_mode,_h0mode,5),0.,0.5); sCBl_205.setConstant(kTRUE); RooRealVar nl_205("nl_205","nl_205",get_nl(_mode,_h0mode,5),0.,100.); nl_205.setConstant(kTRUE); RooRealVar alphal_205("alphal_205","alphal_205",get_alphal(_mode,_h0mode,5),-10.,10.); alphal_205.setConstant(kTRUE); RooCBShape CBl_205("CBl_205","CBl_205",de,deCBl_205,sCBl_205,alphal_205,nl_205); RooRealVar fCBl_205("fCBl_205","fCBl_205",get_fCBl(_mode,_h0mode,5),0.,1.); fCBl_205.setConstant(kTRUE); RooAddPdf pdf_de_205("pdf_de_205","pdf_de_205",RooArgList(CBl_205,g1_205),RooArgSet(fCBl_205)); RooRealVar f_201("f_201","f_201",get_f201(_mode,_h0mode),0.,1.); if(cSIG) f_201.setConstant(kTRUE); RooAddPdf pdf_de_sig("pdf_de_sig","pdf_de_sig",RooArgList(pdf_de_201,pdf_de_205),RooArgSet(f_201)); } ///////////// // mbc pdf // ///////////// const bool cond_flag = false;//(b0f == 5); if(cond_flag) { RooRealVar cond("cond","cond",mr_cond_3,-0.1.,1.); if(cRHO) cond.setConstant(kTRUE); RooRealVar condr("condr","condr",mr_condr_3,-1000.,1.); if(cRHO) condr.setConstant(kTRUE); RooRealVar _sl("_sl","_sl",get_sl(_mode,_h0mode,_b0f),0.,0.5); if(cSIG) _sl.setConstant(kTRUE); RooRealVar _sr("_sr","_sr",get_sr(_mode,_h0mode,_b0f),0.0005,0.5); if(cSIG) _sr.setConstant(kTRUE); RooFormulaVar sl("sl","sl","@0+@1*@2",RooArgList(_sl,cond,de)); RooFormulaVar sr("sr","sr","@0+@1*@2",RooArgList(_sr,condr,de)); RooRealVar _sll("_sll","_sll",get_sll(_mode,_h0mode,_b0f),0.,0.5); if(cSIG) _sll.setConstant(kTRUE); RooRealVar _srr("_srr","_srr",get_srr(_mode,_h0mode,_b0f),0.0005,0.5); if(cSIG) _srr.setConstant(kTRUE); RooFormulaVar sll("sll","sll","@0+@1*@2",RooArgList(_sll,cond,de)); RooFormulaVar srr("srr","srr","@0+@1*@2",RooArgList(_srr,condr,de)); } else {
void BDT_cuts_norm(){ gROOT->ProcessLine(".L ~/cern/project/lhcbStyle.C"); lhcbStyle(); const std::string filename("/afs/cern.ch/work/a/apmorris/private/cern/ntuples/new_tuples/normalisation_samples/Lb2JpsipK_2011_2012_signal_withbdt.root"); const std::string treename = "withbdt"; const std::string filenameMC("/afs/cern.ch/work/a/apmorris/private/cern/ntuples/new_tuples/normalisation_samples/Lb2JpsipK_MC_2011_2012_norm_withbdt.root"); TFile* file = TFile::Open( filename.c_str() ); if( !file ) std::cout << "file " << filename << " does not exist" << std::endl; TTree* tree = (TTree*)file->Get( treename.c_str() ); if( !tree ) std::cout << "tree " << treename << " does not exist" << std::endl; TFile* fileMC = TFile::Open( filenameMC.c_str() ); if( !fileMC ) std::cout << "file " << filenameMC << " does not exist" << std::endl; TTree* treeMC = (TTree*)fileMC->Get( treename.c_str() ); if( !treeMC ) std::cout << "tree " << treename << " does not exist" << std::endl; // -- signal, mass shape RooRealVar Lambda_b0_DTF_MASS_constr1("Lambda_b0_DTF_MASS_constr1","m(J/#psi pK^{-})", 5550., 5700., "MeV/c^{2}"); RooRealVar Jpsi_M("Jpsi_M","m(#mu#mu)", 3000., 3200., "MeV/c^{2}"); RooRealVar chi_c_M("chi_c_M","m(J/#psi#gamma)", 3400., 3700., "MeV/c^{2}"); RooRealVar mean("mean","mean", 5630., 5610., 5650.); RooRealVar sigma1("sigma1","sigma1", 10., 1., 100.); RooRealVar sigma2("sigma2","sigma2", 30.0, 5.0, 300.0); RooRealVar alpha1("alpha1","alpha1", 1.0, 0.5, 5.0); RooRealVar n1("n1","n1", 1.8, 0.2, 15.0); RooRealVar alpha2("alpha2","alpha2", -0.5, -5.5, 0.0); RooRealVar n2("n2","n2", 0.7, 0.2, 10.0); //RooRealVar bkgcat_chic("bkgcat_chic","bkgcat_chic", 0, 100); RooRealVar bdtg3("bdtg3", "bdtg3", -1.0, 1.0); RooRealVar frac2("frac2","frac2", 0.3, 0., 1.); RooGaussian gauss1("gauss1","gauss1", Lambda_b0_DTF_MASS_constr1, mean, sigma1); RooGaussian gauss2("gauss2","gauss2", Lambda_b0_DTF_MASS_constr1, mean, sigma2); RooCBShape cb1("cb1","cb1", Lambda_b0_DTF_MASS_constr1, mean, sigma1, alpha1, n1); RooCBShape cb2("cb2","cb2", Lambda_b0_DTF_MASS_constr1, mean, sigma2, alpha2, n2); RooAddPdf sig("sig", "sig", RooArgList(cb1, cb2), RooArgList( frac2 )); RooRealVar cbRatio("cbRatio","cb Ratio", 0.8, 0.1, 1.0); RooRealVar sigYield("sigYield","sig Yield", 4e2, 1e0, 1e6); RooRealVar bgYield("bgYield","bg Yield", 1e4, 1e0, 1e6); //put in values from fit_MC here <<--- DON'T FORGET TO CHANGE THESE IF THE FIT CHANGES!!! /* EXT PARAMETER INTERNAL INTERNAL NO. NAME VALUE ERROR STEP SIZE VALUE 1 alpha1 2.18020e+00 2.85078e-02 1.38432e-04 -2.56034e-01 2 alpha2 -2.79102e+00 6.74385e-02 1.51818e-04 -1.49177e-02 3 cbRatio 3.07172e-01 1.49204e-02 1.72642e-04 -5.69984e-01 4 mean 5.61985e+03 9.58397e-03 5.56682e-05 -9.66293e-02 5 n1 1.49358e+00 8.14447e-02 2.09300e-04 -9.70542e-01 6 n2 1.45276e+00 1.09864e-01 2.59028e-04 -8.39538e-01 7 sigma1 8.46303e+00 1.32851e-01 2.86985e-05 -1.01453e+00 8 sigma2 4.93976e+00 3.42842e-02 5.03572e-06 -1.44512e+00 */ alpha1.setVal( 2.18020e+00 ); alpha2.setVal( -2.79102e+00 ); n1.setVal( 1.49358e+00 ); n2.setVal( 1.45276e+00 ); frac2.setVal( 3.07172e-01 ); sigma1.setVal( 8.46303e+00 ); sigma2.setVal( 4.93976e+00 ); alpha1.setConstant( true ); alpha2.setConstant( true ); frac2.setConstant( true ); n1.setConstant( true ); n2.setConstant( true ); sigma1.setConstant( true ); sigma2.setConstant( true ); // -- bg, mass shape RooRealVar a1("a1","a1", -0.1, -0.5, 0.5); RooChebychev comb("comb","comb", Lambda_b0_DTF_MASS_constr1, a1); RooRealVar mean3("mean3","mean3", 5560., 5500., 5600.); RooRealVar sigma3("sigma3","sigma3", 5., 1., 10.); RooRealVar frac3("frac3","frac", 0.2, 0.0, 0.3); RooGaussian gauss3("gauss3","gauss3", Lambda_b0_DTF_MASS_constr1, mean3, sigma3); //RooAddPdf bg("bg","bg", RooArgList(comb), RooArgList(frac3)); // -- add signal & bg RooAddPdf pdf("pdf", "pdf", RooArgList(sig, comb), RooArgList( sigYield, bgYield)); double efficiencies1[40]; double efficiencies1_error[40]; double bdt_cuts[40]; double efficiencies2[40]; double efficiencies2_error[40]; double sideband_bg_val[40]; double MC_pre = treeMC->GetEntries(); double effvals[40]; //loop starting here for(int i=0; i < 40; i=i+1) { double cut_val = -1.0 + i*0.05; //double cut_val = -1.0; // testing bdt_cuts[i] = cut_val; std::stringstream c; c << "bdtg3" << " >= " << cut_val; const std::string cut = c.str(); //std::cout << cut; RooArgSet obs; obs.add(Lambda_b0_DTF_MASS_constr1); //obs.add(chi_c_Mp); //obs.add(mass_pK); obs.add(Jpsi_M); obs.add(chi_c_M); obs.add(bdtg3); RooDataSet ds("ds","ds", obs, RooFit::Import(*tree), RooFit::Cut(cut.c_str())); RooPlot* plot = Lambda_b0_DTF_MASS_constr1.frame(); RooFitResult * result = pdf.fitTo( ds, RooFit::Extended() ); double sig_val = sigYield.getVal(); double bg_val = bgYield.getVal(); double sig_error = sigYield.getError(); double bg_error = bgYield.getError(); double efficiency1 = (sig_val)/(sqrt(sig_val + bg_val)); efficiencies1[i] = efficiency1; double efficiency1_error_sq = (pow(sig_error,2)/(sig_val+bg_val) + (pow(sig_val,2)*(pow(sig_error,2)+pow(bg_error,2))/(4*pow((sig_val+bg_val),3)))); double efficiency1_error = sqrt(efficiency1_error_sq); efficiencies1_error[i] = efficiency1_error; /* double MC_post = treeMC->GetEntries(cut.c_str()); double eff_val = MC_post/MC_pre; //something here to get the sideband background count Lambda_b0_DTF_MASS_constr1.setRange("R", 5650., 5700.); RooFitResult * sideband = bg.fitTo( ds, RooFit::Range("R") ); sideband->Print(); Lambda_b0_DTF_MASS_constr1.setRange("R", 5650., 5700.); RooAbsReal* integral = pdf.createIntegral(Lambda_b0_DTF_MASS_constr1, RooFit::Range("R")); //std::cout << integral->getVal() << std::endl; //std::cout << integral->getError() << std::endl; //Double_t sideband_bg_val = integral->getVal(); //double sideband_bg_error = integral->getError(); std::stringstream r; r << "bdtg3" << " >= " << cut_val << " && Lambda_b0_DTF_MASS_constr1 >= 5650 && Lambda_b0_DTF_MASS_constr1 <= 5700"; const std::string cut2 = r.str(); double integ = tree->GetEntries(cut2.c_str()); //double integ = integral->getVal(); double efficiency2 = eff_val/(5./2. + sqrt(integ)); efficiencies2[i] = efficiency2; effvals[i]=eff_val; std::cout << "\n" << integ << std::endl; std::cout << "\n" << eff_val << std::endl; std::cout << "\n" << efficiency2 << std::endl; */ //double efficiency2_error = efficiency2*sqrt(pow(eff_error/eff_val,2)+(1/(4*sideband_bg_val))*pow(sideband_bg_error/(5/2+sideband_bg_val),2)); //std::cout << "\n\n" << "BDT cut value = " << cut_val << "\n" ; //std::cout << "S = " << sig_val << " +/- " << sig_error << "\n" ; //std::cout << "B = " << bg_val << " +/- " << bg_error << "\n" ; //std::cout << "S/sqrt(S+B) = " << efficiency << " +/- " << efficiency_error << "\n\n" ; //ds.plotOn( plot ); //pdf.plotOn( plot ); //RooPlot* plotPullMass = mass.frame(); //plotPullMass->addPlotable( plot->pullHist() ); //plotPullMass->SetMinimum(); //plotPullMass->SetMaximum(); //std::cout << cut_val; } TCanvas *c1 = new TCanvas(); //double zeros[20]; //for (i=0, i<20, i++) zeros[i]=0.0; TGraphErrors* graph = new TGraphErrors(40, bdt_cuts, efficiencies1, 0, efficiencies1_error); graph->SetTitle("S/sqrt(S+B) vs BDTG3 cut"); //graph->SetMarkerColor(4); //graph->SetMarkerStyle(20); //graph->SetMarkerSize(1.0); graph->GetXaxis()->SetTitle("BDTG3 cut (>)"); graph->GetXaxis()->SetRangeUser(-1.0,1.0); graph->GetYaxis()->SetTitle("S/sqrt(S+B)"); //graph->Fit("pol5"); graph->Draw("AP"); c1->SaveAs("~/cern/plots/bdt_cuts_norm/Lb2JpsipK_2011_2012_BDTG3_cuts_S_sqrtS+B.pdf"); //return c1; //std::cout << efficiencies1_error[5] << std::endl; //gStyle->SetOptFit(1011); /*TCanvas *c2 = new TCanvas(); TGraph* graph2 = new TGraph(40, bdt_cuts, efficiencies2); graph2->SetTitle("eff/[5/2+sqrt(B)] vs BDTG3 cut"); graph2->SetMarkerColor(4); graph2->SetMarkerStyle(20); graph2->SetMarkerSize(1.0); graph2->GetXaxis()->SetTitle("BDTG3 cut (>)"); graph2->GetXaxis()->SetRangeUser(-1.0,1.0); graph2->GetYaxis()->SetTitle("eff/[5/2+sqrt(B)]"); //graph2->Fit("pol7"); graph2->Draw("AP"); c2->SaveAs("~/cern/plots/bdt_cuts_norm/Lb2JpsipK_2011_2012_BDTG3_cuts_Punzi.png"); //return c2; */ /* TCanvas* c = new TCanvas(); TPad* pad1 = new TPad("pad1","pad1", 0, 0.3, 1, 1.0); pad1->SetBottomMargin(0.1); pad1->SetTopMargin(0.1); pad1->Draw(); c->cd(); TPad* pad2 = new TPad("pad2","pad2", 0, 0, 1, 0.3); pad2->SetBottomMargin(0.1); pad2->SetTopMargin(0.0); pad2->Draw(); //pdf.plotOn( plot, RooFit::Components( DfbPdf ), RooFit::LineColor( kRed ), RooFit::LineStyle(kDashed) ); //pdf.plotOn( plot, RooFit::Components( promptPdf ), RooFit::LineColor( kBlue ), RooFit::LineStyle(kDotted) ); //pdf.plotOn( plot, RooFit::Components( bgPdf ), RooFit::LineColor( kOrange ), RooFit::LineStyle(kDashDotted) ); pad1->cd(); plot->Draw(); pad2->cd(); plotPullMass->Draw("AP"); c->SaveAs(out_file_mass); RooStats::SPlot* sData = new RooStats::SPlot("sData","An SPlot", ds, &pdf, RooArgList(sigYield, bgYield) ); RooDataSet * dataw_z = new RooDataSet(ds.GetName(),ds.GetTitle(),&ds,*(ds.get()),0,"sigYield_sw") ; */ /* TCanvas* d = new TCanvas(); RooPlot* w_mass_chicp = mass_chicp.frame(); dataw_z->plotOn(w_mass_chicp, RooFit::DataError(RooAbsData::SumW2), RooFit::Binning(20)) ; w_mass_chicp->Draw(); d->SaveAs("m_chicp_sweighted.png"); TCanvas* e = new TCanvas(); RooPlot* w_mass_pK = mass_pK.frame(); dataw_z->plotOn(w_mass_pK, RooFit::DataError(RooAbsData::SumW2), RooFit::Binning(20)) ; w_mass_pK->Draw(); e->SaveAs("m_pK_sweighted.png"); */ /* TCanvas* f = new TCanvas(); RooPlot* w_mass_Jpsi = mass_Jpsi.frame(); dataw_z->plotOn(w_mass_Jpsi, RooFit::DataError(RooAbsData::SumW2), RooFit::Binning(20)) ; w_mass_Jpsi->Draw(); f->SaveAs("m_Jpsi_sweighted.png"); TCanvas* g = new TCanvas(); RooPlot* w_mass_Chic = mass_Chic.frame(); dataw_z->plotOn(w_mass_Chic, RooFit::DataError(RooAbsData::SumW2), RooFit::Binning(20)) ; w_mass_Chic->Draw(); g->SaveAs("m_Chic_sweighted.png"); */ }
void BackSlice_fit(const int m_mode = 1, const bool bbflag = false){ // mode 1 -> pi0 // mode 2 -> eta -> gg // mode 3 -> eta -> pi+pi-pi0 // mode 4 -> omega // const bool projection_flag = true; // const bool save_flag = true; double BDTG_MIN = 0; double BDTG_MAX = 1; RooCategory mode("mode","mode"); RooCategory h0mode("h0mode","h0mode"); RooArgSet argset; switch(m_mode){ case 1: mode.defineType("pi0",1); h0mode.defineType("gg",10); BDTG_MIN = bdtg_cut_pi0; break; case 2: mode.defineType("eta",2); h0mode.defineType("gg",10); BDTG_MIN = bdtg_cut_etagg; break; case 3: mode.defineType("eta",2); h0mode.defineType("ppp",20); BDTG_MIN = bdtg_cut_etappp; break; case 4: mode.defineType("omega",3); h0mode.defineType("ppp",20); BDTG_MIN = bdtg_cut_omega; break; } argset.add(mode); argset.add(h0mode); TFile *ifile; if(!bbflag){ //ifile = TFile::Open("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_cont_0-1_full.root"); ifile = TFile::Open("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_gen_0-1_full.root"); } else{ ifile = TFile::Open("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_bb_0-1_full.root"); } TTree *tree = (TTree*)ifile->Get("TEvent"); // string cuts; RooCategory b0f("b0f","b0f"); b0f.defineType("comb",-1); argset.add(b0f); const double mbcMin = 5.20; const double mbcMax = 5.29; const double deMin = -0.3; const double deMax = 0.3; RooRealVar mbc("mbc","M_{bc}",mbcMin,mbcMax,"GeV"); argset.add(mbc); RooRealVar de("de","#DeltaE",deMin,deMax,"GeV"); argset.add(de); // RooRealVar md("md","md",DMass-md_cut,DMass+md_cut,"GeV"); argset.add(md); // RooRealVar mk("mk","mk",KMass-mk_cut,KMass+mk_cut,"GeV"); argset.add(mk); // RooRealVar mpi0("mpi0","mpi0",Pi0Mass-mpi0_cut,Pi0Mass+mpi0_cut,"GeV"); argset.add(mpi0); RooRealVar bdtg("bdtg","bdtg",BDTG_MIN,BDTG_MAX); argset.add(bdtg); // RooRealVar atckpi_max("atckpi_max","atckpi_max",0.,atckpi_cut); argset.add(atckpi_max); const int NSlices = 10; double c1_arr[NSlices], c1_arr_err[NSlices]; double c2_arr[NSlices], c2_arr_err[NSlices]; double mbc_arr[NSlices], mbc_arr_err[NSlices]; double chisq_arr[NSlices]; stringstream out; double dmbc = (mbcMax-mbcMin)/NSlices; RooDataSet ds("ds","ds",tree,argset); ds.Print(); ////////////// // Comb PDF // ////////////// //////////// // de pdf // //////////// RooRealVar c1("c1","c1",mc_c1,-10.,10.);// if(cComb && false) c1.setConstant(kTRUE); RooRealVar c2("c2","c2",0,-10.,10.);// c2.setConstant(kTRUE); RooChebychev pdf("pdf","pdf",de,RooArgSet(c1,c2)); RooDataSet* ds0; for(int i=0; i<NSlices; i++){ out.str(""); out << "mbc>" << mbcMin+i*dmbc << " && mbc<" << mbcMin+(i+1)*dmbc; ds0 = (RooDataSet*)ds.reduce(RooArgSet(de),out.str().c_str()); pdf.fitTo(*ds0,Verbose(),Timer(true)); c1_arr[i] = c1.getVal(); c1_arr_err[i] = c1.getError(); c2_arr[i] = c2.getVal(); c2_arr_err[i] = c2.getError(); mbc_arr[i] = mbcMin+(0.5+i)*dmbc; mbc_arr_err[i] = 0; RooPlot* deFrame = de.frame(); ds0->plotOn(deFrame,DataError(RooAbsData::SumW2),MarkerSize(1)); pdf.plotOn(deFrame,LineWidth(2)); // out.str(""); // out << "dE, Signal " << i; // TCanvas* cmmbc = new TCanvas(out.str().c_str(),out.str().c_str(),600,600); // cmmbc->cd(); // TPad *pad1 = new TPad("pad1","pad1",0.01,0.00,0.99,0.99); // pad1->Draw(); // pad1->cd(); // pad1->SetLeftMargin(0.15); // pad1->SetFillColor(0); // deFrame->GetXaxis()->SetTitleSize(0.05); // deFrame->GetXaxis()->SetTitleOffset(0.85); // deFrame->GetXaxis()->SetLabelSize(0.04); // deFrame->GetYaxis()->SetTitleOffset(1.6); // deFrame->Draw(); chisq_arr[i] = deFrame->chiSquare(); } for(int i=0; i<NSlices; i++){ cout << c1_arr[i] << " " << c2_arr[i] << " " << chisq_arr[i] << endl; } TGraphErrors* gr_c1 = new TGraphErrors(NSlices,mbc_arr,c1_arr,mbc_arr_err,c1_arr_err); gr_c1->SetTitle("c_{1}"); gr_c1->SetMarkerSize(1); gr_c1->SetMarkerColor(kBlue); gr_c1->SetMarkerStyle(21); TGraphErrors* gr_c2 = new TGraphErrors(NSlices,mbc_arr,c2_arr,mbc_arr_err,c2_arr_err); gr_c2->SetTitle("c_{2}"); gr_c2->SetMarkerSize(1); gr_c2->SetMarkerColor(kBlue); gr_c2->SetMarkerStyle(21); TGraphErrors* gr_chisq = new TGraphErrors(NSlices,mbc_arr,chisq_arr,mbc_arr_err,mbc_arr_err); gr_chisq->SetTitle("Chi2"); gr_chisq->SetMarkerSize(1); gr_chisq->SetMarkerColor(kBlue); gr_chisq->SetMarkerStyle(21); TCanvas* cm = new TCanvas("de","#Delta E, Cmb background",800,400); cm->cd(); TPad *pad1 = new TPad("pad1","pad1",0.01,0.01,0.49,0.99); TPad *pad2 = new TPad("pad2","pad2",0.51,0.01,0.99,0.99); pad1->Draw(); pad2->Draw(); pad1->cd(); pad1->SetGrid(); pad1->SetLeftMargin(0.15); pad1->SetFillColor(0); gr_c1->Draw("AP"); gr_c1->Fit("pol2"); pad2->cd(); pad2->SetGrid(); pad2->SetLeftMargin(0.15); pad2->SetFillColor(0); gr_c2->Draw("AP"); gr_c2->Fit("pol2"); cm->Update(); TCanvas* cm_chi2 = new TCanvas("chi2","#chi^{2}",400,400); cm_chi2->cd(); cm_chi2->SetLeftMargin(0.15); cm_chi2->SetFillColor(0); gr_chisq->Draw("AP"); cm_chi2->Update(); return; }
void Purity_1d_fit(int type = 0){ TChain* tree = new TChain("TEvent"); if(!type) tree->Add("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_gen_0-1_full.root"); else tree->Add("/home/vitaly/B0toDh0/TMVA/FIL_b2dh_data.root"); RooCategory b0f("b0f","b0f"); b0f.defineType("signal",1); b0f.defineType("fsr",10); b0f.defineType("bad_pi0",5); b0f.defineType("rho",3); b0f.defineType("comb",-1); RooArgSet argset; const double deMin = -0.15; const double deMax = 0.3; RooRealVar mbc("mbc","M_{bc}",mbc_min,mbc_max,"GeV"); argset.add(mbc); RooRealVar de("de","#DeltaE",deMin,deMax,"GeV"); argset.add(de); de.setRange("Signal",de_min,de_max); RooRealVar md("md","md",DMass-md_cut,DMass+md_cut,"GeV"); argset.add(md); RooRealVar mk("mk","mk",KMass-mk_cut,KMass+mk_cut,"GeV"); argset.add(mk); RooRealVar mpi0("mpi0","mpi0",Pi0Mass-mpi0_cut,Pi0Mass+mpi0_cut,"GeV"); argset.add(mpi0); RooRealVar bdtgs("bdtgs","bdtgs",bdtgs_cut,1.); argset.add(bdtgs); RooRealVar atckpi_max("atckpi_max","atckpi_max",0.,atckpi_cut); argset.add(atckpi_max); if(!type) argset.add(b0f); RooDataSet ds("ds","ds",tree,argset,"mbc>0||mbc<=0"); // RooDataSet* ds0 = ds.reduce(RooArgSet(de)); stringstream out; if(!type){ out.str(""); out << "de<" << de_max << " && de>" << de_min; Roo1DTable* sigtable = ds.table(b0f,out.str().c_str()); sigtable->Print(); sigtable->Print("v"); Roo1DTable* fulltable = ds.table(b0f); fulltable->Print(); fulltable->Print("v"); } // RooDataHist* dh = ds0->binnedClone(); // ds0->Print(); //////////////// // Signal PDF // //////////////// //////////// // de pdf // //////////// RooRealVar de0("de0","de0",m_de0,-0.1,0.1); if(cSig) de0.setConstant(kTRUE); RooRealVar s1("s1","s1",m_s1,0.,0.5); if(cSig) s1.setConstant(kTRUE); RooGaussian g1("g1","g1",de,de0,s1); RooRealVar deCBl("deCBl","deCBl",m_deCBl,-0.1,0.1); if(cSig) deCBl.setConstant(kTRUE); RooRealVar sCBl("sCBl","sCBl",m_sCBl,0.,0.5); if(cSig) sCBl.setConstant(kTRUE); RooRealVar nl("nl","nl",m_nl,0.,100.); if(cSig) nl.setConstant(kTRUE); RooRealVar alphal("alphal","alphal",m_alphal,-10.,10.); if(cSig) alphal.setConstant(kTRUE); RooRealVar deCBr("deCBr","deCBr",m_deCBr,-0.1,0.1); if(cSig) deCBr.setConstant(kTRUE); RooRealVar sCBr("sCBr","sCBr",m_sCBr,0.,0.5); if(cSig) sCBr.setConstant(kTRUE); RooRealVar nr("nr","nr",m_nr,0.,100.); if(cSig) nr.setConstant(kTRUE); RooRealVar alphar("alphar","alphar",m_alphar,-10.,10.); if(cSig) alphar.setConstant(kTRUE); RooCBShape CBl("CBl","CBl",de,deCBl,sCBl,alphal,nl); RooCBShape CBr("CBr","CBr",de,deCBr,sCBr,alphar,nr); RooRealVar fCBl("fCBl","fCBl",m_fCBl,0.,1.); if(cSig) fCBl.setConstant(kTRUE); RooRealVar fCBr("fCBr","fCBr",m_fCBr,0.,1.); if(cSig) fCBr.setConstant(kTRUE); RooAddPdf pdf_sig("pdf_sig","pdf_sig",RooArgList(CBl,CBr,g1),RooArgSet(fCBl,fCBr)); ////////////// // Comb PDF // ////////////// //////////// // de pdf // //////////// RooRealVar c1("c1","c1",mc_c1_1d,-10.,10.); if(cComb) c1.setConstant(kTRUE); RooRealVar c2("c2","c2",mc_c2_1d,-10.,10.); if(cComb) c2.setConstant(kTRUE); RooChebychev pdf_comb("pdf_comb","pdf_comb",de,RooArgSet(c1,c2)); ///////////// // Rho PDF // ///////////// //////////// // de pdf // //////////// if(de_rho_param == 0){ RooRealVar exppar("exppar","exppar",mr_exppar,-40.,-25.);// if(cRho) exppar.setConstant(kTRUE); RooExponential pdf_rho("pdf_rho","pdf_rho",de,exppar); } RooRealVar de0r("de0r","de0r",mr_de0r,-0.2,0.12); if(cRho) de0r.setConstant(kTRUE); if(de_rho_param == 1){ RooRealVar slopel("slopel","slopel",mr_slopel,-1000,-500.); if(cRho) slopel.setConstant(kTRUE); RooRealVar sloper("sloper","sloper",mr_sloper,-10000,0.); if(cRho) sloper.setConstant(kTRUE); RooRealVar steep("steep","steep",mr_steep,7.,9.); if(cRho) steep.setConstant(kTRUE); RooRealVar p5("p5","p5",mr_p5,0.01,1000.); if(cRho) p5.setConstant(kTRUE); RooRhoDeltaEPdf pdf_rho("pdf_rho","pdf_rho",de,de0r,slopel,sloper,steep,p5); } if(de_rho_param == -1){ RooRealVar x0("x0","x0",mr_x0_1d,-0.2,0.12); if(cRho) x0.setConstant(kTRUE); RooRealVar p1("p1","p1",mr_p1_1d,-1000.,100.); if(cRho) p1.setConstant(kTRUE); RooRealVar p2("p2","p2",mr_p2_1d,0.,100.); if(cRho) p2.setConstant(kTRUE); RooGenericPdf pdf_rho("pdf_rho","1+@0*@1-@2*TMath::Log(1+TMath::Exp(@2*(@0-@1)/@3))",RooArgSet(de,x0,p1,p2)); } ////////////////// // Complete PDF // ////////////////// RooRealVar Nsig("Nsig","Nsig",700,100.,1500.);// fsig.setConstant(kTRUE); RooRealVar Nrho("Nrho","Nrho",400,100,1500.);// frho.setConstant(kTRUE); RooRealVar Ncmb("Ncmb","Ncmb",1000,100,100000);// frho.setConstant(kTRUE); RooAddPdf pdf("pdf","pdf",RooArgList(pdf_sig,pdf_rho,pdf_comb),RooArgList(Nsig,Nrho,Ncmb)); pdf.fitTo(ds,Verbose(),Timer(true)); RooAbsReal* intSig = pdf_sig.createIntegral(RooArgSet(de),NormSet(RooArgSet(de)),Range("Signal")); RooAbsReal* intRho = pdf_rho.createIntegral(RooArgSet(de),NormSet(RooArgSet(de)),Range("Signal")); RooAbsReal* intCmb = pdf_comb.createIntegral(RooArgSet(de),NormSet(RooArgSet(de)),Range("Signal")); const double nsig = intSig->getVal()*Nsig.getVal(); const double nsig_err = intSig->getVal()*Nsig.getError(); const double nsig_err_npq = TMath::Sqrt(nsig*(Nsig.getVal()-nsig)/Nsig.getVal()); const double nsig_err_total = TMath::Sqrt(nsig_err*nsig_err+nsig_err_npq*nsig_err_npq); const double nrho = intRho->getVal()*Nrho.getVal(); const double nrho_err = intRho->getVal()*Nrho.getError(); const double nrho_err_npq = TMath::Sqrt(nrho*(Nrho.getVal()-nrho)/Nrho.getVal()); const double nrho_err_total = TMath::Sqrt(nrho_err*nrho_err+nrho_err_npq*nrho_err_npq); const double ncmb = intCmb->getVal()*Ncmb.getVal(); const double ncmb_err = intCmb->getVal()*Ncmb.getError(); const double ncmb_err_npq = TMath::Sqrt(ncmb*(Ncmb.getVal()-ncmb)/Ncmb.getVal()); const double ncmb_err_total = TMath::Sqrt(ncmb_err*ncmb_err+ncmb_err_npq*ncmb_err_npq); const double purity = nsig/(nsig+nrho+ncmb); const double purity_err = nsig_err_total/(nsig+nrho+ncmb); cout << "Nsig = " << nsig <<" +- " << nsig_err << endl; cout << "Nrho = " << nrho <<" +- " << nrho_err << endl; cout << "Ncmb = " << ncmb <<" +- " << ncmb_err << endl; ///////////// // Plots // ///////////// // de // RooPlot* deFrame = de.frame(); ds.plotOn(deFrame,DataError(RooAbsData::SumW2),MarkerSize(1)); pdf.plotOn(deFrame,Components(pdf_sig),LineStyle(kDashed)); pdf.plotOn(deFrame,Components(pdf_rho),LineStyle(kDashed)); pdf.plotOn(deFrame,Components(pdf_comb),LineStyle(kDashed)); pdf.plotOn(deFrame,LineWidth(2)); RooHist* hdepull = deFrame->pullHist(); RooPlot* dePull = de.frame(Title("#Delta E pull distribution")); dePull->addPlotable(hdepull,"P"); dePull->GetYaxis()->SetRangeUser(-5,5); TCanvas* cm = new TCanvas("Delta E","Delta E",600,700); cm->cd(); TPad *pad3 = new TPad("pad3","pad3",0.01,0.20,0.99,0.99); TPad *pad4 = new TPad("pad4","pad4",0.01,0.01,0.99,0.20); pad3->Draw(); pad4->Draw(); pad3->cd(); pad3->SetLeftMargin(0.15); pad3->SetFillColor(0); deFrame->GetXaxis()->SetTitleSize(0.05); deFrame->GetXaxis()->SetTitleOffset(0.85); deFrame->GetXaxis()->SetLabelSize(0.04); deFrame->GetYaxis()->SetTitleOffset(1.6); deFrame->Draw(); stringstream out1; TPaveText *pt = new TPaveText(0.6,0.75,0.98,0.9,"brNDC"); pt->SetFillColor(0); pt->SetTextAlign(12); out1.str(""); out1 << "#chi^{2}/n.d.f = " << deFrame->chiSquare(); pt->AddText(out1.str().c_str()); out1.str(""); out1 << "S: " << (int)(nsig+0.5) << " #pm " << (int)(nsig_err_total+0.5); pt->AddText(out1.str().c_str()); out1.str(""); out1 << "Purity: " << std::fixed << std::setprecision(2) << purity*100. << " #pm " << purity_err*100; pt->AddText(out1.str().c_str()); pt->Draw(); TLine *de_line_RIGHT = new TLine(de_max,0,de_max,50); de_line_RIGHT->SetLineColor(kRed); de_line_RIGHT->SetLineStyle(1); de_line_RIGHT->SetLineWidth((Width_t)2.); de_line_RIGHT->Draw(); TLine *de_line_LEFT = new TLine(de_min,0,de_min,50); de_line_LEFT->SetLineColor(kRed); de_line_LEFT->SetLineStyle(1); de_line_LEFT->SetLineWidth((Width_t)2.); de_line_LEFT->Draw(); pad4->cd(); pad4->SetLeftMargin(0.15); pad4->SetFillColor(0); dePull->SetMarkerSize(0.05); dePull->Draw(); TLine *de_lineUP = new TLine(deMin,3,deMax,3); de_lineUP->SetLineColor(kBlue); de_lineUP->SetLineStyle(2); de_lineUP->Draw(); TLine *de_line = new TLine(deMin,0,deMax,0); de_line->SetLineColor(kBlue); de_line->SetLineStyle(1); de_line->SetLineWidth((Width_t)2.); de_line->Draw(); TLine *de_lineDOWN = new TLine(deMin,-3,deMax,-3); de_lineDOWN->SetLineColor(kBlue); de_lineDOWN->SetLineStyle(2); de_lineDOWN->Draw(); cm->Update(); if(!type){ out.str(""); out << "de<" << de_max << " && de>" << de_min; Roo1DTable* sigtable = ds.table(b0f,out.str().c_str()); sigtable->Print(); sigtable->Print("v"); Roo1DTable* fulltable = ds.table(b0f); fulltable->Print(); fulltable->Print("v"); } cout << "Nsig = " << nsig <<" +- " << nsig_err << " +- " << nsig_err_npq << " (" << nsig_err_total << ")" << endl; cout << "Nrho = " << nrho <<" +- " << nrho_err << " +- " << nrho_err_npq << " (" << nrho_err_total << ")" << endl; cout << "Ncmb = " << ncmb <<" +- " << ncmb_err << " +- " << ncmb_err_npq << " (" << ncmb_err_total << ")" << endl; cout << "Pury = " << purity << " +- " << purity_err << endl; }
/// \brief Needed if the PDF has more than one observable /// The constructors only fill in one observable void AddObservable( RooRealVar * newobs ) { obs->add(*newobs); }
// 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; }
void fit_MC_norm(std::string input_file = "/afs/cern.ch/work/a/apmorris/private/cern/ntuples/new_tuples/normalisation_samples/reduced_Lb2JpsipK_MC_2011_2012_norm.root", std::string out_file_mass = "~/cern/plots/fitting/Lb2JpsipK_MC_2011_2012_cut_mass_fit.png"){ // gROOT->ProcessLine(".L ~/cern/scripts/lhcbStyle.C"); //lhcbStyle(); const std::string filename(input_file.c_str()); const std::string treename = "DecayTree"; TFile* file = TFile::Open( filename.c_str() ); if( !file ) std::cout << "file " << filename << " does not exist" << std::endl; TTree* tree = (TTree*)file->Get( treename.c_str() ); if( !tree ) std::cout << "tree " << treename << " does not exist" << std::endl; // -- signal, mass shape RooRealVar Lambda_b0_DTF_MASS_constr1("Lambda_b0_DTF_MASS_constr1","m(J/#psi pK^{-})", 5450., 5850., "MeV/c^{2}"); RooRealVar Jpsi_M("Jpsi_M","m(#mu#mu)", 3000., 3200., "MeV/c^{2}"); //RooRealVar chi_c_M("chi_c_M","m(J/#psi#gamma)", 3350., 3750., "MeV/c^{2}"); RooRealVar mean("mean","mean", 5620., 5595., 5650.); RooRealVar sigma1("sigma1","sigma1", 10., 1., 100.); RooRealVar sigma2("sigma2","sigma2", 100., 1., 1000.); RooRealVar alpha1("alpha1","alpha1", 1.0, 0.5, 5.0); RooRealVar n1("n1","n1", 1.8, 0.2, 15.0); RooRealVar alpha2("alpha2","alpha2", -0.5, -5.5, 0.0); RooRealVar n2("n2","n2", 0.7, 0.2, 10.0); //RooRealVar bkgcat_chic("bkgcat_chic","bkgcat_chic", 0, 100); RooGaussian gauss1("gauss1","gauss1", Lambda_b0_DTF_MASS_constr1, mean, sigma1); RooGaussian gauss2("gauss2","gauss2", Lambda_b0_DTF_MASS_constr1, mean, sigma2); RooCBShape cb1("cb1","cb1", Lambda_b0_DTF_MASS_constr1, mean, sigma1, alpha1, n1); RooCBShape cb2("cb2","cb2", Lambda_b0_DTF_MASS_constr1, mean, sigma2, alpha2, n2); /* // the chi_c2 component RooRealVar mean3("mean3","mean3", 5570., 5520., 5580.); RooRealVar sigma3("sigma3","sigma3", 10., 1., 20.); RooGaussian gauss3("gauss3","gauss3", Lambda_b0_DTF_MASS_constr1, mean3, sigma3); */ RooRealVar cbRatio("cbRatio","cbRatio", 0.8, 0.1, 1.0); RooRealVar frac2("frac2","frac2", 0.3, 0., 1.); /* alpha1.setVal( 2.1 ); alpha2.setVal( -4.9 ); n1.setVal( 3.2 ); n2.setVal( 7.9 ); cbRatio.setVal( 0.6808 ); alpha1.setConstant( true ); alpha2.setConstant( true ); cbRatio.setConstant( true ); n1.setConstant( true ); n2.setConstant( true ); */ // -- add signal & bg //RooAddPdf pdf("pdf", "pdf", RooArgList(gauss1, gauss2), RooArgList( frac2 )); RooAddPdf pdf("pdf", "pdf", RooArgList(cb1, cb2), RooArgList( cbRatio )); RooArgSet obs; obs.add(Lambda_b0_DTF_MASS_constr1); obs.add(Jpsi_M); //obs.add(chi_c_M); //obs.add(bkgcat_chic); RooDataSet ds("ds","ds", obs, RooFit::Import(*tree)); //RooFit::Cut("Lambda_b0_DTF_MASS_constr1 > 5580") RooPlot* plot = Lambda_b0_DTF_MASS_constr1.frame(); plot->SetAxisRange(5500., 5750.); pdf.fitTo( ds ); ds.plotOn( plot, RooFit::Binning(200) ); pdf.plotOn( plot ); //gauss3.plotOn( plot ); RooPlot* plotPullMass = Lambda_b0_DTF_MASS_constr1.frame(); plotPullMass->addPlotable( plot->pullHist() ); //plotPullMass->SetMinimum(); //plotPullMass->SetMaximum(); plotPullMass->SetAxisRange(5500., 5750.); TCanvas* c = new TCanvas(); c->cd(); TPad* pad1 = new TPad("pad1","pad1", 0, 0.3, 1, 1.0); pad1->SetBottomMargin(0.1); pad1->SetTopMargin(0.1); pad1->Draw(); //TPad* pad2 = new TPad("pad2","pad2", 0, 0.05, 1, 0.4); TPad* pad2 = new TPad("pad2","pad2", 0, 0, 1, 0.3); pad2->SetBottomMargin(0.1); pad2->SetTopMargin(0.0); pad2->Draw(); pdf.plotOn( plot, RooFit::Components( cb1 ), RooFit::LineColor( kRed ), RooFit::LineStyle(kDashed) ); pdf.plotOn( plot, RooFit::Components( cb2 ), RooFit::LineColor( kOrange ), RooFit::LineStyle(kDotted) ); //pdf.plotOn( plot, RooFit::Components( bgPdf ), RooFit::LineColor( kBlue ), RooFit::LineStyle(kDashDotted) ); pad1->cd(); //pad1->SetLogy(); plot->Draw(); pad2->cd(); plotPullMass->Draw("AP"); c->SaveAs(out_file_mass.c_str()); }
void Raa3S_Workspace(const char* name_pbpb="chad_ws_fits/centFits/ws_PbPbData_262548_263757_0cent10_0.0pt50.0_0.0y2.4.root", const char* name_pp="chad_ws_fits/centFits/ws_PPData_262157_262328_-1cent1_0.0pt50.0_0.0y2.4.root", const char* name_out="fitresult_combo.root"){ //TFile File(filename); //RooWorkspace * ws = test_combine(name_pbpb, name_pp); TFile *f = new TFile("fitresult_combo_333.root") ; RooWorkspace * ws1 = (RooWorkspace*) f->Get("wcombo"); //File.GetObject("wcombo", ws); ws1->Print(); RooAbsData * data = ws1->data("data"); //dataOS, dataSS // RooDataSet * US_data = (RooDataSet*) data->reduce( "QQsign == QQsign::PlusMinus"); // US_data->SetName("US_data"); // ws->import(* US_data); // RooDataSet * hi_data = (RooDataSet*) US_data->reduce("dataCat == dataCat::hi"); // hi_data->SetName("hi_data"); // ws->import(* hi_data); // hi_data->Print(); RooRealVar* raa3 = new RooRealVar("raa3","R_{AA}(#Upsilon (3S))",0.5,-1,1); RooRealVar* leftEdge = new RooRealVar("leftEdge","leftEdge",0); RooRealVar* rightEdge = new RooRealVar("rightEdge","rightEdge",1); RooGenericPdf step("step", "step", "(@0 >= @1) && (@0 < @2)", RooArgList(*raa3, *leftEdge, *rightEdge)); ws1->import(step); ws1->factory( "Uniform::flat(raa3)" ); //pp Luminosities, Taa and efficiency ratios Systematics ws1->factory( "Taa_hi[5.662e-9]" ); ws1->factory( "Taa_kappa[1.062]" ); // was 1.057 ws1->factory( "expr::alpha_Taa('pow(Taa_kappa,beta_Taa)',Taa_kappa,beta_Taa[0,-5,5])" ); ws1->factory( "prod::Taa_nom(Taa_hi,alpha_Taa)" ); ws1->factory( "Gaussian::constr_Taa(beta_Taa,glob_Taa[0,-5,5],1)" ); ws1->factory( "lumipp_hi[5.4]" ); ws1->factory( "lumipp_kappa[1.037]" ); // was 1.06 ws1->factory( "expr::alpha_lumipp('pow(lumipp_kappa,beta_lumipp)',lumipp_kappa,beta_lumipp[0,-5,5])" ); ws1->factory( "prod::lumipp_nom(lumipp_hi,alpha_lumipp)" ); ws1->factory( "Gaussian::constr_lumipp(beta_lumipp,glob_lumipp[0,-5,5],1)" ); // ws->factory( "effRat1[1]" ); // ws->factory( "effRat2[1]" ); ws1->factory( "effRat3_hi[0.95]" ); ws1->factory( "effRat_kappa[1.054]" ); ws1->factory( "expr::alpha_effRat('pow(effRat_kappa,beta_effRat)',effRat_kappa,beta_effRat[0,-5,5])" ); // ws->factory( "prod::effRat1_nom(effRat1_hi,alpha_effRat)" ); ws1->factory( "Gaussian::constr_effRat(beta_effRat,glob_effRat[0,-5,5],1)" ); // ws->factory( "prod::effRat2_nom(effRat2_hi,alpha_effRat)" ); ws1->factory( "prod::effRat3_nom(effRat3_hi,alpha_effRat)" ); // ws1->factory("Nmb_hi[1.161e9]"); ws1->factory("prod::denominator(Taa_nom,Nmb_hi)"); ws1->factory( "expr::lumiOverTaaNmbmodified('lumipp_nom/denominator',lumipp_nom,denominator)"); RooAbsReal *lumiOverTaaNmbmodified = ws1->function("lumiOverTaaNmbmodified"); //RooFormulaVar *lumiOverTaaNmbmodified = ws->function("lumiOverTaaNmbmodified"); // // RooRealVar *raa1 = ws->var("raa1"); // RooRealVar* nsig1_pp = ws->var("nsig1_pp"); // RooRealVar* effRat1 = ws->function("effRat1_nom"); // RooRealVar *raa2 = ws->var("raa2"); // RooRealVar* nsig2_pp = ws->var("nsig2_pp"); // RooRealVar* effRat2 = ws->function("effRat2_nom"); RooRealVar* nsig3_pp = ws1->var("R_{#frac{3S}{1S}}_pp"); //RooRealVar* nsig3_pp = ws->var("N_{#Upsilon(3S)}_pp"); cout << nsig3_pp << endl; RooAbsReal* effRat3 = ws1->function("effRat3_nom"); //RooRealVar* effRat3 = ws->function("effRat3_nom"); // // RooFormulaVar nsig1_hi_modified("nsig1_hi_modified", "@0*@1*@3/@2", RooArgList(*raa1, *nsig1_pp, *lumiOverTaaNmbmodified, *effRat1)); // ws->import(nsig1_hi_modified); // RooFormulaVar nsig2_hi_modified("nsig2_hi_modified", "@0*@1*@3/@2", RooArgList(*raa2, *nsig2_pp, *lumiOverTaaNmbmodified, *effRat2)); // ws->import(nsig2_hi_modified); RooFormulaVar nsig3_hi_modified("nsig3_hi_modified", "@0*@1*@3/@2", RooArgList(*raa3, *nsig3_pp, *lumiOverTaaNmbmodified, *effRat3)); ws1->import(nsig3_hi_modified); // // background yield with systematics ws1->factory( "nbkg_hi_kappa[1.10]" ); ws1->factory( "expr::alpha_nbkg_hi('pow(nbkg_hi_kappa,beta_nbkg_hi)',nbkg_hi_kappa,beta_nbkg_hi[0,-5,5])" ); ws1->factory( "SUM::nbkg_hi_nom(alpha_nbkg_hi*bkgPdf_hi)" ); ws1->factory( "Gaussian::constr_nbkg_hi(beta_nbkg_hi,glob_nbkg_hi[0,-5,5],1)" ); RooAbsPdf* sig1S_hi = ws1->pdf("sig1S_hi"); //RooAbsPdf* sig1S_hi = ws->pdf("cbcb_hi"); RooAbsPdf* sig2S_hi = ws1->pdf("sig2S_hi"); RooAbsPdf* sig3S_hi = ws1->pdf("sig3S_hi"); RooAbsPdf* LSBackground_hi = ws1->pdf("nbkg_hi_nom"); RooRealVar* nsig1_hi = ws1->var("N_{#Upsilon(1S)}_hi"); RooRealVar* nsig2_hi = ws1->var("R_{#frac{2S}{1S}}_hi"); RooAbsReal* nsig3_hi = ws1->function("nsig3_hi_modified"); //RooFormulaVar* nsig3_hi = ws->function("nsig3_hi_modified"); cout << nsig1_hi << " " << nsig2_hi << " " << nsig3_pp << endl; RooRealVar* norm_nbkg_hi = ws1->var("n_{Bkgd}_hi"); RooArgList pdfs_hi( *sig1S_hi,*sig2S_hi,*sig3S_hi, *LSBackground_hi); RooArgList norms_hi(*nsig1_hi,*nsig2_hi,*nsig3_hi, *norm_nbkg_hi); //////////////////////////////////////////////////////////////////////////////// ws1->factory( "nbkg_pp_kappa[1.03]" ); ws1->factory( "expr::alpha_nbkg_pp('pow(nbkg_pp_kappa,beta_nbkg_pp)',nbkg_pp_kappa,beta_nbkg_pp[0,-5,5])" ); ws1->factory( "SUM::nbkg_pp_nom(alpha_nbkg_pp*bkgPdf_pp)" ); ws1->factory( "Gaussian::constr_nbkg_pp(beta_nbkg_pp,glob_nbkg_pp[0,-5,5],1)" ); RooAbsPdf* sig1S_pp = ws1->pdf("sig1S_pp"); //RooAbsPdf* sig1S_pp = ws1->pdf("cbcb_pp"); RooAbsPdf* sig2S_pp = ws1->pdf("sig2S_pp"); RooAbsPdf* sig3S_pp = ws1->pdf("sig3S_pp"); RooAbsPdf* LSBackground_pp = ws1->pdf("nbkg_pp_nom"); RooRealVar* nsig1_pp = ws1->var("N_{#Upsilon(1S)}_pp"); RooRealVar* nsig2_pp = ws1->var("R_{#frac{2S}{1S}}_pp"); //RooRealVar* nsig2_pp = ws1->var("N_{#Upsilon(2S)}_pp"); // RooRealVar* nsig3_pp = ws1->var("N_{#Upsilon(3S)}_pp"); RooRealVar* norm_nbkg_pp = ws1->var("n_{Bkgd}_pp"); RooArgList pdfs_pp( *sig1S_pp,*sig2S_pp,*sig3S_pp, *LSBackground_pp); RooArgList norms_pp( *nsig1_pp,*nsig2_pp,*nsig3_pp,*norm_nbkg_pp); RooAddPdf model_num("model_num", "model_num", pdfs_hi,norms_hi); ws1->import(model_num); ws1->factory("PROD::model_hi(model_num, constr_nbkg_hi,constr_lumipp,constr_Taa,constr_effRat)"); RooAddPdf model_den("model_den", "model_den", pdfs_pp,norms_pp); ws1->import(model_den); ws1->factory("PROD::model_pp(model_den, constr_nbkg_pp)"); ws1->factory("SIMUL::joint(dataCat,hi=model_hi,pp=model_pp)"); ///////////////////////////////////////////////////////////////////// RooRealVar * pObs = ws1->var("invariantMass"); // get the pointer to the observable RooArgSet obs("observables"); obs.add(*pObs); obs.add( *ws1->cat("dataCat")); // ///////////////////////////////////////////////////////////////////// ws1->var("glob_lumipp")->setConstant(true); ws1->var("glob_Taa")->setConstant(true); ws1->var("glob_effRat")->setConstant(true); ws1->var("glob_nbkg_pp")->setConstant(true); ws1->var("glob_nbkg_hi")->setConstant(true); RooArgSet globalObs("global_obs"); globalObs.add( *ws1->var("glob_lumipp") ); globalObs.add( *ws1->var("glob_Taa") ); globalObs.add( *ws1->var("glob_effRat") ); globalObs.add( *ws1->var("glob_nbkg_hi") ); globalObs.add( *ws1->var("glob_nbkg_pp") ); cout << "66666" << endl; // ws1->Print(); RooArgSet poi("poi"); poi.add( *ws1->var("raa3") ); cout << "77777" << endl; // create set of nuisance parameters RooArgSet nuis("nuis"); nuis.add( *ws1->var("beta_lumipp") ); nuis.add( *ws1->var("beta_nbkg_hi") ); nuis.add( *ws1->var("beta_nbkg_pp") ); nuis.add( *ws1->var("beta_Taa") ); nuis.add( *ws1->var("beta_effRat") ); cout << "88888" << endl; ws1->var("#alpha_{CB}_hi")->setConstant(true); ws1->var("#alpha_{CB}_pp")->setConstant(true); ws1->var("#sigma_{CB1}_hi")->setConstant(true); ws1->var("#sigma_{CB1}_pp")->setConstant(true); ws1->var("#sigma_{CB2}/#sigma_{CB1}_hi")->setConstant(true); ws1->var("#sigma_{CB2}/#sigma_{CB1}_pp")->setConstant(true); //ws1->var("Centrality")->setConstant(true); //delete ws1->var("N_{#varUpsilon(1S)}_hi")->setConstant(true); ws1->var("N_{#varUpsilon(1S)}_pp")->setConstant(true); //ws1->var("N_{#Upsilon(2S)}_hi")->setConstant(true); //ws1->var("N_{#Upsilon(2S)}_pp")->setConstant(true); //ws1->var("N_{#Upsilon(3S)}_pp")->setConstant(true); ws1->var("R_{#frac{2S}{1S}}_hi")->setConstant(true); //new ws1->var("R_{#frac{2S}{1S}}_pp")->setConstant(true); //new ws1->var("R_{#frac{3S}{1S}}_hi")->setConstant(true); //new ws1->var("R_{#frac{3S}{1S}}_pp")->setConstant(true); //new ws1->var("Nmb_hi")->setConstant(true); // ws1->var("QQsign")->setConstant(true); ws1->var("Taa_hi")->setConstant(true); ws1->var("Taa_kappa")->setConstant(true); // ws1->var("beta_Taa")->setConstant(true); // ws1->var("beta_effRat")->setConstant(true); // ws1->var("beta_lumipp")->setConstant(true); // ws1->var("beta_nbkg_hi")->setConstant(true); // ws1->var("beta_nbkg_pp")->setConstant(true); // ws1->var("dataCat")->setConstant(true); ws1->var("decay_hi")->setConstant(true); ws1->var("decay_pp")->setConstant(true); ws1->var("effRat3_hi")->setConstant(true); ws1->var("effRat_kappa")->setConstant(true); // ws1->var("glob_Taa")->setConstant(true); // ws1->var("glob_effRat")->setConstant(true); // ws1->var("glob_lumipp")->setConstant(true); // ws1->var("glob_nbkg_hi")->setConstant(true); // ws1->var("glob_nbkg_pp")->setConstant(true); // ws1->var("invariantMass")->setConstant(true); ws1->var("leftEdge")->setConstant(true); ws1->var("lumipp_hi")->setConstant(true); ws1->var("lumipp_kappa")->setConstant(true); ws1->var("m_{ #varUpsilon(1S)}_hi")->setConstant(true); //ws1->var("mass1S_hi")->setConstant(true); ws1->var("m_{ #varUpsilon(1S)}_pp")->setConstant(true); //ws1->var("mass1S_pp")->setConstant(true); ws1->var("muMinusPt")->setConstant(true); ws1->var("muPlusPt")->setConstant(true); ws1->var("n_{Bkgd}_hi")->setConstant(true); ws1->var("n_{Bkgd}_pp")->setConstant(true); ws1->var("nbkg_hi_kappa")->setConstant(true); ws1->var("nbkg_pp_kappa")->setConstant(true); //ws1->var("n_{CB}")->setConstant(true); //ws1->var("n_{CB}")->setConstant(true); //ws1->var("npow")->setConstant(true); ws1->var("n_{CB}_hi")->setConstant(true); //ws1->var("n_{CB}")->setConstant(true); //ws1->var("npow")->setConstant(true); ws1->var("n_{CB}_pp")->setConstant(true); //ws1->var("n_{CB}")->setConstant(true); //ws1->var("npow")->setConstant(true); // ws1->var("raa3")->setConstant(true); ws1->var("rightEdge")->setConstant(true); ws1->var("sigmaFraction_hi")->setConstant(true); ws1->var("sigmaFraction_pp")->setConstant(true); ws1->var("turnOn_hi")->setConstant(true); ws1->var("turnOn_pp")->setConstant(true); ws1->var("dimuPt")->setConstant(true); //ws1->var("upsPt")->setConstant(true); ws1->var("dimuRapidity")->setConstant(true); //ws1->var("upsRapidity")->setConstant(true); ws1->var("vProb")->setConstant(true); ws1->var("width_hi")->setConstant(true); ws1->var("width_pp")->setConstant(true); // ws1->var("x3raw")->setConstant(true); // RooArgSet fixed_again("fixed_again"); // fixed_again.add( *ws1->var("leftEdge") ); // fixed_again.add( *ws1->var("rightEdge") ); // fixed_again.add( *ws1->var("Taa_hi") ); // fixed_again.add( *ws1->var("Nmb_hi") ); // fixed_again.add( *ws1->var("lumipp_hi") ); // fixed_again.add( *ws1->var("effRat1_hi") ); // fixed_again.add( *ws1->var("effRat2_hi") ); // fixed_again.add( *ws1->var("effRat3_hi") ); // fixed_again.add( *ws1->var("nsig3_pp") ); // fixed_again.add( *ws1->var("nsig1_pp") ); // fixed_again.add( *ws1->var("nbkg_hi") ); // fixed_again.add( *ws1->var("alpha") ); // fixed_again.add( *ws1->var("nbkg_kappa") ); // fixed_again.add( *ws1->var("Taa_kappa") ); // fixed_again.add( *ws1->var("lumipp_kappa") ); // fixed_again.add( *ws1->var("mean_hi") ); // fixed_again.add( *ws1->var("mean_pp") ); // fixed_again.add( *ws1->var("width_hi") ); // fixed_again.add( *ws1->var("turnOn_hi") ); // fixed_again.add( *ws1->var("bkg_a1_pp") ); // fixed_again.add( *ws1->var("bkg_a2_pp") ); // fixed_again.add( *ws1->var("decay_hi") ); // fixed_again.add( *ws1->var("raa1") ); // fixed_again.add( *ws1->var("raa2") ); // fixed_again.add( *ws1->var("nsig2_pp") ); // fixed_again.add( *ws1->var("sigma1") ); // fixed_again.add( *ws1->var("nbkg_pp") ); // fixed_again.add( *ws1->var("npow") ); // fixed_again.add( *ws1->var("muPlusPt") ); // fixed_again.add( *ws1->var("muMinusPt") ); // fixed_again.add( *ws1->var("mscale_hi") ); // fixed_again.add( *ws1->var("mscale_pp") ); // // ws1->Print(); cout << "99999" << endl; // create signal+background Model Config RooStats::ModelConfig sbHypo("SbHypo"); sbHypo.SetWorkspace( *ws1 ); sbHypo.SetPdf( *ws1->pdf("joint") ); sbHypo.SetObservables( obs ); sbHypo.SetGlobalObservables( globalObs ); sbHypo.SetParametersOfInterest( poi ); sbHypo.SetNuisanceParameters( nuis ); sbHypo.SetPriorPdf( *ws1->pdf("step") ); // this is optional // ws1->Print(); ///////////////////////////////////////////////////////////////////// RooAbsReal * pNll = sbHypo.GetPdf()->createNLL( *data,NumCPU(10) ); cout << "111111" << endl; RooMinuit(*pNll).migrad(); // minimize likelihood wrt all parameters before making plots cout << "444444" << endl; RooPlot *framepoi = ((RooRealVar *)poi.first())->frame(Bins(10),Range(0.,0.2),Title("LL and profileLL in raa3")); cout << "222222" << endl; pNll->plotOn(framepoi,ShiftToZero()); cout << "333333" << endl; RooAbsReal * pProfile = pNll->createProfile( globalObs ); // do not profile global observables pProfile->getVal(); // this will do fit and set POI and nuisance parameters to fitted values pProfile->plotOn(framepoi,LineColor(kRed)); framepoi->SetMinimum(0); framepoi->SetMaximum(3); TCanvas *cpoi = new TCanvas(); cpoi->cd(); framepoi->Draw(); cpoi->SaveAs("cpoi.pdf"); ((RooRealVar *)poi.first())->setMin(0.); RooArgSet * pPoiAndNuisance = new RooArgSet("poiAndNuisance"); // pPoiAndNuisance->add(*sbHypo.GetNuisanceParameters()); // pPoiAndNuisance->add(*sbHypo.GetParametersOfInterest()); pPoiAndNuisance->add( nuis ); pPoiAndNuisance->add( poi ); sbHypo.SetSnapshot(*pPoiAndNuisance); RooPlot* xframeSB = pObs->frame(Title("SBhypo")); data->plotOn(xframeSB,Cut("dataCat==dataCat::hi")); RooAbsPdf *pdfSB = sbHypo.GetPdf(); RooCategory *dataCat = ws1->cat("dataCat"); pdfSB->plotOn(xframeSB,Slice(*dataCat,"hi"),ProjWData(*dataCat,*data)); TCanvas *c1 = new TCanvas(); c1->cd(); xframeSB->Draw(); c1->SaveAs("c1.pdf"); delete pProfile; delete pNll; delete pPoiAndNuisance; ws1->import( sbHypo ); ///////////////////////////////////////////////////////////////////// RooStats::ModelConfig bHypo = sbHypo; bHypo.SetName("BHypo"); bHypo.SetWorkspace(*ws1); pNll = bHypo.GetPdf()->createNLL( *data,NumCPU(2) ); RooArgSet poiAndGlobalObs("poiAndGlobalObs"); poiAndGlobalObs.add( poi ); poiAndGlobalObs.add( globalObs ); pProfile = pNll->createProfile( poiAndGlobalObs ); // do not profile POI and global observables ((RooRealVar *)poi.first())->setVal( 0 ); // set raa3=0 here pProfile->getVal(); // this will do fit and set nuisance parameters to profiled values pPoiAndNuisance = new RooArgSet( "poiAndNuisance" ); pPoiAndNuisance->add( nuis ); pPoiAndNuisance->add( poi ); bHypo.SetSnapshot(*pPoiAndNuisance); RooPlot* xframeB = pObs->frame(Title("Bhypo")); data->plotOn(xframeB,Cut("dataCat==dataCat::hi")); RooAbsPdf *pdfB = bHypo.GetPdf(); pdfB->plotOn(xframeB,Slice(*dataCat,"hi"),ProjWData(*dataCat,*data)); TCanvas *c2 = new TCanvas(); c2->cd(); xframeB->Draw(); c2->SaveAs("c2.pdf"); delete pProfile; delete pNll; delete pPoiAndNuisance; // import model config into workspace bHypo.SetWorkspace(*ws1); ws1->import( bHypo ); ///////////////////////////////////////////////////////////////////// ws1->Print(); bHypo.Print(); sbHypo.Print(); // save workspace to file ws1 -> SaveAs(name_out); return; }
void OneSidedFrequentistUpperLimitWithBands_intermediate(const char* infile = "", const char* workspaceName = "combined", const char* modelConfigName = "ModelConfig", const char* dataName = "obsData"){ double confidenceLevel=0.95; // degrade/improve number of pseudo-experiments used to define the confidence belt. // value of 1 corresponds to default number of toys in the tail, which is 50/(1-confidenceLevel) double additionalToysFac = 1.; int nPointsToScan = 30; // number of steps in the parameter of interest int nToyMC = 100; // number of toys used to define the expected limit and band TStopwatch t; t.Start(); ///////////////////////////////////////////////////////////// // 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"; else filename = infile; // Check if example input file exists TFile *file = TFile::Open(filename); // if input file was specified byt not found, quit if(!file && strcmp(infile,"")){ cout <<"file not found" << endl; return; } // if default file not found, try to create it if(!file ){ // 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; } // now try to access the file again file = TFile::Open(filename); if(!file){ // if it is still not there, then we can't continue cout << "Not able to run hist2workspace to create example input" <<endl; return; } ///////////////////////////////////////////////////////////// // Now get the data and workspace //////////////////////////////////////////////////////////// // 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; } cout << "Found data and ModelConfig:" <<endl; mc->Print(); ///////////////////////////////////////////////////////////// // Now get the POI for convenience // you may want to adjust the range of your POI //////////////////////////////////////////////////////////// RooRealVar* firstPOI = (RooRealVar*) mc->GetParametersOfInterest()->first(); // firstPOI->setMin(0); // firstPOI->setMax(10); ///////////////////////////////////////////// // create and use the FeldmanCousins tool // to find and plot the 95% confidence interval // on the parameter of interest as specified // in the model config // REMEMBER, we will change the test statistic // so this is NOT a Feldman-Cousins interval FeldmanCousins fc(*data,*mc); fc.SetConfidenceLevel(confidenceLevel); fc.AdditionalNToysFactor(additionalToysFac); // improve sampling that defines confidence belt // fc.UseAdaptiveSampling(true); // speed it up a bit, but don't use for expectd limits fc.SetNBins(nPointsToScan); // set how many points per parameter of interest to scan fc.CreateConfBelt(true); // save the information in the belt for plotting ///////////////////////////////////////////// // Feldman-Cousins is a unified limit by definition // but the tool takes care of a few things for us like which values // of the nuisance parameters should be used to generate toys. // so let's just change the test statistic and realize this is // no longer "Feldman-Cousins" but is a fully frequentist Neyman-Construction. // ProfileLikelihoodTestStatModified onesided(*mc->GetPdf()); // fc.GetTestStatSampler()->SetTestStatistic(&onesided); // ((ToyMCSampler*) fc.GetTestStatSampler())->SetGenerateBinned(true); ToyMCSampler* toymcsampler = (ToyMCSampler*) fc.GetTestStatSampler(); ProfileLikelihoodTestStat* testStat = dynamic_cast<ProfileLikelihoodTestStat*>(toymcsampler->GetTestStatistic()); testStat->SetOneSided(true); // test speedups: testStat->SetReuseNLL(true); // toymcsampler->setUseMultiGen(true); // not fully validated // Since this tool needs to throw toy MC the PDF needs to be // extended or the tool needs to know how many entries in a dataset // per pseudo experiment. // In the 'number counting form' where the entries in the dataset // are counts, and not values of discriminating variables, the // datasets typically only have one entry and the PDF is not // extended. if(!mc->GetPdf()->canBeExtended()){ if(data->numEntries()==1) fc.FluctuateNumDataEntries(false); else cout <<"Not sure what to do about this model" <<endl; } // We can use PROOF to speed things along in parallel ProofConfig pc(*w, 4, "",false); if(mc->GetGlobalObservables()){ cout << "will use global observables for unconditional ensemble"<<endl; mc->GetGlobalObservables()->Print(); toymcsampler->SetGlobalObservables(*mc->GetGlobalObservables()); } toymcsampler->SetProofConfig(&pc); // enable proof // Now get the interval PointSetInterval* interval = fc.GetInterval(); ConfidenceBelt* belt = fc.GetConfidenceBelt(); // print out the iterval on the first Parameter of Interest cout << "\n95% interval on " <<firstPOI->GetName()<<" is : ["<< interval->LowerLimit(*firstPOI) << ", "<< interval->UpperLimit(*firstPOI) <<"] "<<endl; // get observed UL and value of test statistic evaluated there RooArgSet tmpPOI(*firstPOI); double observedUL = interval->UpperLimit(*firstPOI); firstPOI->setVal(observedUL); double obsTSatObsUL = fc.GetTestStatSampler()->EvaluateTestStatistic(*data,tmpPOI); // Ask the calculator which points were scanned RooDataSet* parameterScan = (RooDataSet*) fc.GetPointsToScan(); RooArgSet* tmpPoint; // make a histogram of parameter vs. threshold TH1F* histOfThresholds = new TH1F("histOfThresholds","", parameterScan->numEntries(), firstPOI->getMin(), firstPOI->getMax()); histOfThresholds->GetXaxis()->SetTitle(firstPOI->GetName()); histOfThresholds->GetYaxis()->SetTitle("Threshold"); // loop through the points that were tested and ask confidence belt // what the upper/lower thresholds were. // For FeldmanCousins, the lower cut off is always 0 for(Int_t i=0; i<parameterScan->numEntries(); ++i){ tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp"); double arMax = belt->GetAcceptanceRegionMax(*tmpPoint); double poiVal = tmpPoint->getRealValue(firstPOI->GetName()) ; histOfThresholds->Fill(poiVal,arMax); } TCanvas* c1 = new TCanvas(); c1->Divide(2); c1->cd(1); histOfThresholds->SetMinimum(0); histOfThresholds->Draw(); c1->cd(2); ///////////////////////////////////////////////////////////// // Now we generate the expected bands and power-constriant //////////////////////////////////////////////////////////// // First: find parameter point for mu=0, with conditional MLEs for nuisance parameters RooAbsReal* nll = mc->GetPdf()->createNLL(*data); RooAbsReal* profile = nll->createProfile(*mc->GetParametersOfInterest()); firstPOI->setVal(0.); profile->getVal(); // this will do fit and set nuisance parameters to profiled values RooArgSet* poiAndNuisance = new RooArgSet(); if(mc->GetNuisanceParameters()) poiAndNuisance->add(*mc->GetNuisanceParameters()); poiAndNuisance->add(*mc->GetParametersOfInterest()); w->saveSnapshot("paramsToGenerateData",*poiAndNuisance); RooArgSet* paramsToGenerateData = (RooArgSet*) poiAndNuisance->snapshot(); cout << "\nWill use these parameter points to generate pseudo data for bkg only" << endl; paramsToGenerateData->Print("v"); double CLb=0; double CLbinclusive=0; // Now we generate background only and find distribution of upper limits TH1F* histOfUL = new TH1F("histOfUL","",100,0,firstPOI->getMax()); histOfUL->GetXaxis()->SetTitle("Upper Limit (background only)"); histOfUL->GetYaxis()->SetTitle("Entries"); for(int imc=0; imc<nToyMC; ++imc){ // set parameters back to values for generating pseudo data w->loadSnapshot("paramsToGenerateData"); // in 5.30 there is a nicer way to generate toy data & randomize global obs RooAbsData* toyData = toymcsampler->GenerateToyData(*paramsToGenerateData); // get test stat at observed UL in observed data firstPOI->setVal(observedUL); double toyTSatObsUL = fc.GetTestStatSampler()->EvaluateTestStatistic(*toyData,tmpPOI); // toyData->get()->Print("v"); // cout <<"obsTSatObsUL " <<obsTSatObsUL << "toyTS " << toyTSatObsUL << endl; if(obsTSatObsUL < toyTSatObsUL) // (should be checked) CLb+= (1.)/nToyMC; if(obsTSatObsUL <= toyTSatObsUL) // (should be checked) CLbinclusive+= (1.)/nToyMC; // loop over points in belt to find upper limit for this toy data double thisUL = 0; for(Int_t i=0; i<parameterScan->numEntries(); ++i){ tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp"); double arMax = belt->GetAcceptanceRegionMax(*tmpPoint); firstPOI->setVal( tmpPoint->getRealValue(firstPOI->GetName()) ); double thisTS = fc.GetTestStatSampler()->EvaluateTestStatistic(*toyData,tmpPOI); if(thisTS<=arMax){ thisUL = firstPOI->getVal(); } else{ break; } } histOfUL->Fill(thisUL); delete toyData; } histOfUL->Draw(); c1->SaveAs("one-sided_upper_limit_output.pdf"); // if you want to see a plot of the sampling distribution for a particular scan point: // Now find bands and power constraint Double_t* bins = histOfUL->GetIntegral(); TH1F* cumulative = (TH1F*) histOfUL->Clone("cumulative"); cumulative->SetContent(bins); double band2sigDown=0, band1sigDown=0, bandMedian=0, band1sigUp=0,band2sigUp=0; for(int i=1; i<=cumulative->GetNbinsX(); ++i){ if(bins[i]<RooStats::SignificanceToPValue(2)) band2sigDown=cumulative->GetBinCenter(i); if(bins[i]<RooStats::SignificanceToPValue(1)) band1sigDown=cumulative->GetBinCenter(i); if(bins[i]<0.5) bandMedian=cumulative->GetBinCenter(i); if(bins[i]<RooStats::SignificanceToPValue(-1)) band1sigUp=cumulative->GetBinCenter(i); if(bins[i]<RooStats::SignificanceToPValue(-2)) band2sigUp=cumulative->GetBinCenter(i); } t.Stop(); t.Print(); cout << "-2 sigma band " << band2sigDown << endl; cout << "-1 sigma band " << band1sigDown << endl; cout << "median of band " << bandMedian << " [Power Constriant)]" << endl; cout << "+1 sigma band " << band1sigUp << endl; cout << "+2 sigma band " << band2sigUp << endl; // print out the iterval on the first Parameter of Interest cout << "\nobserved 95% upper-limit "<< interval->UpperLimit(*firstPOI) <<endl; cout << "CLb strict [P(toy>obs|0)] for observed 95% upper-limit "<< CLb <<endl; cout << "CLb inclusive [P(toy>=obs|0)] for observed 95% upper-limit "<< CLbinclusive <<endl; delete profile; delete nll; }
double ro_fit4( TH1F * h2, int p4,int p3,int p2,int p1 ){ TCanvas *chi=(TCanvas*)gROOT->GetListOfCanvases()->FindObject("c_hist"); if (chi!=NULL){ chi->cd(); } int npeaks=4; if (npeaks>NMAX){ printf("TOO MANY PEAKS\n",""); return 1;} TH1F *h2; double pk[NMAX]; double si[NMAX]; double ar[NMAX]; double al[NMAX]; double n1; double min=h2->GetXaxis()->GetFirst(), max=h2->GetXaxis()->GetLast(), smin=(max-min)/1000, smax=(max-min), amin=h2->Integral( min, max )/1000., amax=h2->Integral( min, max ), almin=0., almax=100., nmin=1.0, nmax=100.; pk[0]=p4; pk[1]=p3; pk[2]=p2; pk[3]=p1; for (int i=0;i<npeaks;i++){ // pk[i]=1.0*(i+1)/(1+npeaks)*(max-min) +min; si[i]=4.3.; ar[i]=1.0*(amax+amin)/npeaks/2; //area al[i]=1.3; } n1=5.1; smin=0.5* si[0]; smax=2.*si[0]; int tag=1; int i; printf("%d peaks : ", npeaks); for (i=0;i<npeaks;i++){ printf( "%8.2f ",pk[i] ); } printf("\n######### TAG %7d\n", tag++); //================ MAIN variable 1D ============== RooRealVar x("x", "x", min, max); /* * * CHEBYSHEV HERE */ char sbg="p1"; // 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, setcheb ) ; RooRealVar mean1("mean1", "mean_", pk[0], min,max); RooRealVar mean2("mean2", "mean_", pk[1], min,max); RooRealVar mean3("mean3", "mean_", pk[2], min,max); RooRealVar mean4("mean4", "mean_", pk[3], min,max); RooRealVar mean5("mean5", "mean_", pk[4], min,max); RooRealVar mean6("mean6", "mean_", pk[5], min,max); RooRealVar mean7("mean7", "mean_", pk[6], min,max); RooRealVar mean8("mean8", "mean_", pk[7], min,max); RooRealVar mean9("mean9", "mean_", pk[8], min,max); RooRealVar meana("meana", "mean_", pk[9], min,max); RooRealVar meanb("meanb", "mean_", pk[10], min,max); RooRealVar meanc("meanc", "mean_", pk[11], min,max); RooRealVar meand("meand", "mean_", pk[12], min,max); RooRealVar meane("meane", "mean_", pk[13], min,max); RooRealVar meanf("meanf", "mean_", pk[14], min,max); RooRealVar sigm1("sigm1", "sigma", si[0], smin, smax); RooRealVar sigm2("sigm2", "sigma", si[1], smin, smax); RooRealVar sigm3("sigm3", "sigma", si[2], smin, smax); RooRealVar sigm4("sigm4", "sigma", si[3], smin, smax); RooRealVar sigm5("sigm5", "sigma", si[4], smin, smax); RooRealVar sigm6("sigm6", "sigma", si[5], smin, smax); RooRealVar sigm7("sigm7", "sigma", si[6], smin, smax); RooRealVar sigm8("sigm8", "sigma", si[7], smin, smax); RooRealVar sigm9("sigm9", "sigma", si[8], smin, smax); RooRealVar sigma("sigma", "sigma", si[9], smin, smax); RooRealVar sigmb("sigmb", "sigma", si[10], smin, smax); RooRealVar sigmc("sigmc", "sigma", si[11], smin, smax); RooRealVar sigmd("sigmd", "sigma", si[12], smin, smax); RooRealVar sigme("sigme", "sigma", si[13], smin, smax); RooRealVar sigmf("sigmf", "sigma", si[14], smin, smax); RooRealVar fs2("fs2","fs2", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fs3("fs3","fs3", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fs4("fs4","fs4", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fs5("fs5","fs5", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fs6("fs6","fs6", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fs7("fs7","fs7", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fs8("fs8","fs8", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fs9("fs9","fs9", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fsa("fsa","fsa", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fsb("fsb","fsb", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fsc("fsc","fsc", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fsd("fsd","fsd", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fse("fse","fse", 0.0 ); // factor sigma = 1==free or 0==fix RooRealVar fsf("fsf","fsf", 0.0 ); // factor sigma = 1==free or 0==fix RooFormulaVar fsigm2( "fsigm2", " fs2*sigm2 + (1.0-fs2)*sigm1" , RooArgSet(sigm1,sigm2,fs2) ); RooFormulaVar fsigm3( "fsigm3", " fs3*sigm3 + (1.0-fs3)*sigm1" , RooArgSet(sigm1,sigm3,fs3) ); RooFormulaVar fsigm4( "fsigm4", " fs4*sigm4 + (1.0-fs4)*sigm1" , RooArgSet(sigm1,sigm4,fs4) ); RooFormulaVar fsigm5( "fsigm5", " fs5*sigm5 + (1.0-fs5)*sigm1" , RooArgSet(sigm1,sigm5,fs5) ); RooFormulaVar fsigm6( "fsigm6", " fs6*sigm6 + (1.0-fs6)*sigm1" , RooArgSet(sigm1,sigm6,fs6) ); RooFormulaVar fsigm7( "fsigm7", " fs7*sigm7 + (1.0-fs7)*sigm1" , RooArgSet(sigm1,sigm7,fs7) ); RooFormulaVar fsigm8( "fsigm8", " fs8*sigm8 + (1.0-fs8)*sigm1" , RooArgSet(sigm1,sigm8,fs8) ); RooFormulaVar fsigm9( "fsigm9", " fs9*sigm9 + (1.0-fs9)*sigm1" , RooArgSet(sigm1,sigm9,fs9) ); RooFormulaVar fsigma( "fsigma", " fsa*sigma + (1.0-fsa)*sigm1" , RooArgSet(sigm1,sigma,fsa) ); RooFormulaVar fsigmb( "fsigmb", " fsb*sigmb + (1.0-fsb)*sigm1" , RooArgSet(sigm1,sigmb,fsb) ); RooFormulaVar fsigmc( "fsigmc", " fsc*sigmc + (1.0-fsc)*sigm1" , RooArgSet(sigm1,sigmc,fsc) ); RooFormulaVar fsigmd( "fsigmd", " fsd*sigmd + (1.0-fsd)*sigm1" , RooArgSet(sigm1,sigmd,fsd) ); RooFormulaVar fsigme( "fsigme", " fse*sigme + (1.0-fse)*sigm1" , RooArgSet(sigm1,sigme,fse) ); RooFormulaVar fsigmf( "fsigmf", " fsf*sigmf + (1.0-fsf)*sigm1" , RooArgSet(sigm1,sigmf,fsf) ); // -------- fsx 0== FIX to sigm1; 1==free sigma fs2.setVal( 0.0 ); fs3.setVal( 0.0 ); fs4.setVal( 0.0 ); fs5.setVal( 1.0 ); fs6.setVal( 1.0 ); fs7.setVal( 1.0 ); fs8.setVal( 1.0 ); fs9.setVal( 1.0 ); fsa.setVal( 1.0 ); fsb.setVal( 1.0 ); fsc.setVal( 1.0 ); fsd.setVal( 1.0 ); fse.setVal( 1.0 ); fsf.setVal( 1.0 ); fs2.setConstant( kTRUE ); fs3.setConstant( kTRUE ); fs4.setConstant( kTRUE ); fs5.setConstant( kTRUE ); fs6.setConstant( kTRUE ); fs7.setConstant( kTRUE ); fs8.setConstant( kTRUE ); fs9.setConstant( kTRUE ); fsa.setConstant( kTRUE ); fsb.setConstant( kTRUE ); fsc.setConstant( kTRUE ); fsd.setConstant( kTRUE ); fse.setConstant( kTRUE ); fsf.setConstant( kTRUE ); if (fs2.getVal()==0.0){sigm2.setConstant( kTRUE );} if (fs3.getVal()==0.0){sigm3.setConstant( kTRUE );} if (fs4.getVal()==0.0){sigm4.setConstant( kTRUE );} if (fs5.getVal()==0.0){sigm5.setConstant( kTRUE );} if (fs6.getVal()==0.0){sigm6.setConstant( kTRUE );} if (fs7.getVal()==0.0){sigm7.setConstant( kTRUE );} if (fs8.getVal()==0.0){sigm8.setConstant( kTRUE );} if (fs9.getVal()==0.0){sigm9.setConstant( kTRUE );} if (fsa.getVal()==0.0){sigma.setConstant( kTRUE );} if (fsb.getVal()==0.0){sigmb.setConstant( kTRUE );} if (fsc.getVal()==0.0){sigmc.setConstant( kTRUE );} if (fsd.getVal()==0.0){sigmd.setConstant( kTRUE );} if (fse.getVal()==0.0){sigme.setConstant( kTRUE );} if (fsf.getVal()==0.0){sigmf.setConstant( kTRUE );} // extra thing that goes to RootSet RooRealVar area1("area1", "area_", ar[0], amin, amax); RooRealVar area2("area2", "area_", ar[1], amin, amax); RooRealVar area3("area3", "area_", ar[2], amin, amax); RooRealVar area4("area4", "area_", ar[3], amin, amax); RooRealVar area5("area5", "area_", ar[4], amin, amax); RooRealVar area6("area6", "area_", ar[5], amin, amax); RooRealVar area7("area7", "area_", ar[6], amin, amax); RooRealVar area8("area8", "area_", ar[7], amin, amax); RooRealVar area9("area9", "area_", ar[8], amin, amax); RooRealVar areaa("areaa", "area_", ar[9], amin, amax); RooRealVar areab("areab", "area_", ar[10], amin, amax); RooRealVar areac("areac", "area_", ar[11], amin, amax); RooRealVar aread("aread", "area_", ar[12], amin, amax); RooRealVar areae("areae", "area_", ar[13], amin, amax); RooRealVar areaf("areaf", "area_", ar[14], amin, amax); RooRealVar bgarea("bgarea", "bgarea", 1.0*(amin+amax)/2., 0, amax); //=================== only one instance =================== RooRealVar alph1("alph1", "alph1", al[0], almin, almax ); RooRealVar ncbs1("n1", "n1", n1, nmin, nmax ); RooCBShape cb1("cb1","CBS", x,mean1, sigm1,alph1,ncbs1); RooCBShape cb2("cb2","CBS", x,mean2,fsigm2,alph1,ncbs1); RooCBShape cb3("cb3","CBS", x,mean3,fsigm3,alph1,ncbs1); RooCBShape cb4("cb4","CBS", x,mean4,fsigm4,alph1,ncbs1); RooCBShape cb5("cb5","CBS", x,mean5,fsigm5,alph1,ncbs1); RooCBShape cb6("cb6","CBS", x,mean6,fsigm6,alph1,ncbs1); RooCBShape cb7("cb7","CBS", x,mean7,fsigm7,alph1,ncbs1); RooCBShape cb8("cb8","CBS", x,mean8,fsigm8,alph1,ncbs1); RooCBShape cb9("cb9","CBS", x,mean9,fsigm9,alph1,ncbs1); RooCBShape cba("cba","CBS", x,meana,fsigma,alph1,ncbs1); RooCBShape cbb("cbb","CBS", x,meanb,fsigmb,alph1,ncbs1); RooCBShape cbc("cbc","CBS", x,meanc,fsigmc,alph1,ncbs1); RooCBShape cbd("cbd","CBS", x,meand,fsigmd,alph1,ncbs1); RooCBShape cbe("cbe","CBS", x,meane,fsigme,alph1,ncbs1); RooCBShape cbf("cbf","CBS", x,meanf,fsigmf,alph1,ncbs1); RooExtendPdf ecb1("ecb1","ECBS", cb1, area1 ); RooExtendPdf ecb2("ecb2","ECBS", cb2, area2 ); RooExtendPdf ecb3("ecb3","ECBS", cb3, area3 ); RooExtendPdf ecb4("ecb4","ECBS", cb4, area4 ); RooExtendPdf ecb5("ecb5","ECBS", cb5, area5 ); RooExtendPdf ecb6("ecb6","ECBS", cb6, area6 ); RooExtendPdf ecb7("ecb7","ECBS", cb7, area7 ); RooExtendPdf ecb8("ecb8","ECBS", cb8, area8 ); RooExtendPdf ecb9("ecb9","ECBS", cb9, area9 ); RooExtendPdf ecba("ecba","ECBS", cba, areaa ); RooExtendPdf ecbb("ecbb","ECBS", cbb, areab ); RooExtendPdf ecbc("ecbc","ECBS", cbc, areac ); RooExtendPdf ecbd("ecbd","ECBS", cbd, aread ); RooExtendPdf ecbe("ecbe","ECBS", cbe, areae ); RooExtendPdf ecbf("ecbf","ECBS", cbf, areaf ); RooArgList erl; if (npeaks>0)erl.add( ecb1 ); if (npeaks>1)erl.add( ecb2 ); if (npeaks>2)erl.add( ecb3 ); if (npeaks>3)erl.add( ecb4 ); if (npeaks>4)erl.add( ecb5 ); if (npeaks>5)erl.add( ecb6 ); if (npeaks>6)erl.add( ecb7 ); if (npeaks>7)erl.add( ecb8 ); if (npeaks>8)erl.add( ecb9 ); if (npeaks>9)erl.add( ecba ); if (npeaks>10)erl.add( ecbb ); if (npeaks>11)erl.add( ecbc ); if (npeaks>12)erl.add( ecbd ); if (npeaks>13)erl.add( ecbe ); if (npeaks>14)erl.add( ecbf ); RooExtendPdf ebkg("ebkg","EBkg", bkg, bgarea ); erl.add( ebkg ); RooAddPdf emodelV("emodel","emultiplet", erl ); emodelV.Print("v"); RooDataHist datah("datah","datah with x",x,h2); RooPlot* xframe = x.frame(); datah.plotOn(xframe, DrawOption("logy") ); // RooPlot* xframe = x.frame(); /* bkg.plotOn( xframe, LineColor(kBlue) ); cb1.plotOn( xframe, LineColor(kRed) ); */ // xframe->Draw(); /* * Here I believe to put the parameters for fit???? * */ /* RooArgList rl; if (npeaks>0)rl.add( cb1 ); if (npeaks>1)rl.add( cb2 ); if (npeaks>2)rl.add( cb3 ); if (npeaks>3)rl.add( cb4 ); if (npeaks>4)rl.add( cb5 ); if (npeaks>5)rl.add( cb6 ); if (npeaks>6)rl.add( cb7 ); if (npeaks>7)rl.add( cb8 ); if (npeaks>8)rl.add( cb9 ); if (npeaks>9)rl.add( cba ); if (npeaks>10)rl.add( cbb ); if (npeaks>11)rl.add( cbc ); if (npeaks>12)rl.add( cbd ); if (npeaks>13)rl.add( cbe ); if (npeaks>14)rl.add( cbf ); rl.add( bkg ); // asi zastoupeni jednotlivych piku viz vyse------------ // RooArgSet rs; RooArgList 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 ); if (npeaks>6)rs.add( area7 ); if (npeaks>7)rs.add( area8 ); if (npeaks>8)rs.add( area9 ); if (npeaks>9)rs.add( areaa ); if (npeaks>10)rs.add( areab ); if (npeaks>11)rs.add( areac ); if (npeaks>12)rs.add( aread ); if (npeaks>13)rs.add( areae ); if (npeaks>14)rs.add( areaf ); rs.add( bgarea ); //if # coefficients(rs)+1=functions(rl) => coef.are interpreted as fractions RooAddPdf modelV("model","multiplet", rl, rs ); modelV.Print("v"); */ /* * WITH CUSTOMIZER - I can change parameters inside. But * - then all is a clone and I dont know how to reach it.->Iterations...difficlt I try something with RooFormulaVar */ fitresult = emodelV.fitTo( datah , Save() ); fitresult->Print("v") ; fitresult->floatParsFinal().Print("s") ; // model->Print(); // not interesting........ emodelV.plotOn(xframe, LineColor(kRed), DrawOption("l0z") ); emodelV.plotOn(xframe, Components(ecb1),LineColor(kGreen),LineStyle(kDashed) ); emodelV.plotOn(xframe, Components(RooArgSet(ecb1,ebkg)),LineColor(kBlue),LineStyle(kDashed) ); emodelV.plotOn(xframe, Components(RooArgSet(ecb2,ebkg)),LineColor(kBlue),LineStyle(kDashed) ); emodelV.plotOn(xframe, Components(RooArgSet(ecb3,ebkg)),LineColor(kBlue),LineStyle(kDashed) ); emodelV.plotOn(xframe, Components(RooArgSet(ecb4,ebkg)),LineColor(kBlue),LineStyle(kDashed) ); emodelV.plotOn(xframe, Components( RooArgSet(ebkg) ), LineColor(kRed) ); xframe->Draw(); printf("FWHM = = %f chan\n", sigm1.getVal()*2.3548 ); printf("FWHM = = %f keV\n", sigm1.getVal()*2.3548 *5804.0/p1 ); return sigm1.getVal()*2.3548 *5804.0/p1 ; }//==================================ro_fit4 ======
void OneSidedFrequentistUpperLimitWithBands(const char* infile = "", const char* workspaceName = "combined", const char* modelConfigName = "ModelConfig", const char* dataName = "obsData") { double confidenceLevel=0.95; int nPointsToScan = 20; int nToyMC = 200; // ------------------------------------------------------- // 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; } // ------------------------------------------------------- // Now get the data and workspace // 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; } // ------------------------------------------------------- // Now get the POI for convenience // you may want to adjust the range of your POI RooRealVar* firstPOI = (RooRealVar*) mc->GetParametersOfInterest()->first(); /* firstPOI->setMin(0);*/ /* firstPOI->setMax(10);*/ // -------------------------------------------- // Create and use the FeldmanCousins tool // to find and plot the 95% confidence interval // on the parameter of interest as specified // in the model config // REMEMBER, we will change the test statistic // so this is NOT a Feldman-Cousins interval FeldmanCousins fc(*data,*mc); fc.SetConfidenceLevel(confidenceLevel); /* fc.AdditionalNToysFactor(0.25); // degrade/improve sampling that defines confidence belt*/ /* fc.UseAdaptiveSampling(true); // speed it up a bit, don't use for expected limits*/ fc.SetNBins(nPointsToScan); // set how many points per parameter of interest to scan fc.CreateConfBelt(true); // save the information in the belt for plotting // ------------------------------------------------------- // Feldman-Cousins is a unified limit by definition // but the tool takes care of a few things for us like which values // of the nuisance parameters should be used to generate toys. // so let's just change the test statistic and realize this is // no longer "Feldman-Cousins" but is a fully frequentist Neyman-Construction. /* ProfileLikelihoodTestStatModified onesided(*mc->GetPdf());*/ /* fc.GetTestStatSampler()->SetTestStatistic(&onesided);*/ /* ((ToyMCSampler*) fc.GetTestStatSampler())->SetGenerateBinned(true); */ ToyMCSampler* toymcsampler = (ToyMCSampler*) fc.GetTestStatSampler(); ProfileLikelihoodTestStat* testStat = dynamic_cast<ProfileLikelihoodTestStat*>(toymcsampler->GetTestStatistic()); testStat->SetOneSided(true); // Since this tool needs to throw toy MC the PDF needs to be // extended or the tool needs to know how many entries in a dataset // per pseudo experiment. // In the 'number counting form' where the entries in the dataset // are counts, and not values of discriminating variables, the // datasets typically only have one entry and the PDF is not // extended. if(!mc->GetPdf()->canBeExtended()){ if(data->numEntries()==1) fc.FluctuateNumDataEntries(false); else cout <<"Not sure what to do about this model" <<endl; } // We can use PROOF to speed things along in parallel // However, the test statistic has to be installed on the workers // so either turn off PROOF or include the modified test statistic // in your `$ROOTSYS/roofit/roostats/inc` directory, // add the additional line to the LinkDef.h file, // and recompile root. if (useProof) { ProofConfig pc(*w, nworkers, "", false); toymcsampler->SetProofConfig(&pc); // enable proof } if(mc->GetGlobalObservables()){ cout << "will use global observables for unconditional ensemble"<<endl; mc->GetGlobalObservables()->Print(); toymcsampler->SetGlobalObservables(*mc->GetGlobalObservables()); } // Now get the interval PointSetInterval* interval = fc.GetInterval(); ConfidenceBelt* belt = fc.GetConfidenceBelt(); // print out the interval on the first Parameter of Interest cout << "\n95% interval on " <<firstPOI->GetName()<<" is : ["<< interval->LowerLimit(*firstPOI) << ", "<< interval->UpperLimit(*firstPOI) <<"] "<<endl; // get observed UL and value of test statistic evaluated there RooArgSet tmpPOI(*firstPOI); double observedUL = interval->UpperLimit(*firstPOI); firstPOI->setVal(observedUL); double obsTSatObsUL = fc.GetTestStatSampler()->EvaluateTestStatistic(*data,tmpPOI); // Ask the calculator which points were scanned RooDataSet* parameterScan = (RooDataSet*) fc.GetPointsToScan(); RooArgSet* tmpPoint; // make a histogram of parameter vs. threshold TH1F* histOfThresholds = new TH1F("histOfThresholds","", parameterScan->numEntries(), firstPOI->getMin(), firstPOI->getMax()); histOfThresholds->GetXaxis()->SetTitle(firstPOI->GetName()); histOfThresholds->GetYaxis()->SetTitle("Threshold"); // loop through the points that were tested and ask confidence belt // what the upper/lower thresholds were. // For FeldmanCousins, the lower cut off is always 0 for(Int_t i=0; i<parameterScan->numEntries(); ++i){ tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp"); //cout <<"get threshold"<<endl; double arMax = belt->GetAcceptanceRegionMax(*tmpPoint); double poiVal = tmpPoint->getRealValue(firstPOI->GetName()) ; histOfThresholds->Fill(poiVal,arMax); } TCanvas* c1 = new TCanvas(); c1->Divide(2); c1->cd(1); histOfThresholds->SetMinimum(0); histOfThresholds->Draw(); c1->cd(2); // ------------------------------------------------------- // Now we generate the expected bands and power-constraint // First: find parameter point for mu=0, with conditional MLEs for nuisance parameters RooAbsReal* nll = mc->GetPdf()->createNLL(*data); RooAbsReal* profile = nll->createProfile(*mc->GetParametersOfInterest()); firstPOI->setVal(0.); profile->getVal(); // this will do fit and set nuisance parameters to profiled values RooArgSet* poiAndNuisance = new RooArgSet(); if(mc->GetNuisanceParameters()) poiAndNuisance->add(*mc->GetNuisanceParameters()); poiAndNuisance->add(*mc->GetParametersOfInterest()); w->saveSnapshot("paramsToGenerateData",*poiAndNuisance); RooArgSet* paramsToGenerateData = (RooArgSet*) poiAndNuisance->snapshot(); cout << "\nWill use these parameter points to generate pseudo data for bkg only" << endl; paramsToGenerateData->Print("v"); RooArgSet unconditionalObs; unconditionalObs.add(*mc->GetObservables()); unconditionalObs.add(*mc->GetGlobalObservables()); // comment this out for the original conditional ensemble double CLb=0; double CLbinclusive=0; // Now we generate background only and find distribution of upper limits TH1F* histOfUL = new TH1F("histOfUL","",100,0,firstPOI->getMax()); histOfUL->GetXaxis()->SetTitle("Upper Limit (background only)"); histOfUL->GetYaxis()->SetTitle("Entries"); for(int imc=0; imc<nToyMC; ++imc){ // set parameters back to values for generating pseudo data // cout << "\n get current nuis, set vals, print again" << endl; w->loadSnapshot("paramsToGenerateData"); // poiAndNuisance->Print("v"); RooDataSet* toyData = 0; // now generate a toy dataset if(!mc->GetPdf()->canBeExtended()){ if(data->numEntries()==1) toyData = mc->GetPdf()->generate(*mc->GetObservables(),1); else cout <<"Not sure what to do about this model" <<endl; } else{ // cout << "generating extended dataset"<<endl; toyData = mc->GetPdf()->generate(*mc->GetObservables(),Extended()); } // generate global observables // need to be careful for simpdf // RooDataSet* globalData = mc->GetPdf()->generate(*mc->GetGlobalObservables(),1); RooSimultaneous* simPdf = dynamic_cast<RooSimultaneous*>(mc->GetPdf()); if(!simPdf){ RooDataSet *one = mc->GetPdf()->generate(*mc->GetGlobalObservables(), 1); const RooArgSet *values = one->get(); RooArgSet *allVars = mc->GetPdf()->getVariables(); *allVars = *values; delete allVars; delete values; delete one; } else { //try fix for sim pdf TIterator* iter = simPdf->indexCat().typeIterator() ; RooCatType* tt = NULL; while((tt=(RooCatType*) iter->Next())) { // Get pdf associated with state from simpdf RooAbsPdf* pdftmp = simPdf->getPdf(tt->GetName()) ; // Generate only global variables defined by the pdf associated with this state RooArgSet* globtmp = pdftmp->getObservables(*mc->GetGlobalObservables()) ; RooDataSet* tmp = pdftmp->generate(*globtmp,1) ; // Transfer values to output placeholder *globtmp = *tmp->get(0) ; // Cleanup delete globtmp ; delete tmp ; } } // globalData->Print("v"); // unconditionalObs = *globalData->get(); // mc->GetGlobalObservables()->Print("v"); // delete globalData; // cout << "toy data = " << endl; // toyData->get()->Print("v"); // get test stat at observed UL in observed data firstPOI->setVal(observedUL); double toyTSatObsUL = fc.GetTestStatSampler()->EvaluateTestStatistic(*toyData,tmpPOI); // toyData->get()->Print("v"); // cout <<"obsTSatObsUL " <<obsTSatObsUL << "toyTS " << toyTSatObsUL << endl; if(obsTSatObsUL < toyTSatObsUL) // not sure about <= part yet CLb+= (1.)/nToyMC; if(obsTSatObsUL <= toyTSatObsUL) // not sure about <= part yet CLbinclusive+= (1.)/nToyMC; // loop over points in belt to find upper limit for this toy data double thisUL = 0; for(Int_t i=0; i<parameterScan->numEntries(); ++i){ tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp"); double arMax = belt->GetAcceptanceRegionMax(*tmpPoint); firstPOI->setVal( tmpPoint->getRealValue(firstPOI->GetName()) ); // double thisTS = profile->getVal(); double thisTS = fc.GetTestStatSampler()->EvaluateTestStatistic(*toyData,tmpPOI); // cout << "poi = " << firstPOI->getVal() // << " max is " << arMax << " this profile = " << thisTS << endl; // cout << "thisTS = " << thisTS<<endl; if(thisTS<=arMax){ thisUL = firstPOI->getVal(); } else{ break; } } /* // loop over points in belt to find upper limit for this toy data double thisUL = 0; for(Int_t i=0; i<histOfThresholds->GetNbinsX(); ++i){ tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp"); cout <<"---------------- "<<i<<endl; tmpPoint->Print("v"); cout << "from hist " << histOfThresholds->GetBinCenter(i+1) <<endl; double arMax = histOfThresholds->GetBinContent(i+1); // cout << " threhold from Hist = aMax " << arMax<<endl; // double arMax2 = belt->GetAcceptanceRegionMax(*tmpPoint); // cout << "from scan arMax2 = "<< arMax2 << endl; // not the same due to TH1F not TH1D // cout << "scan - hist" << arMax2-arMax << endl; firstPOI->setVal( histOfThresholds->GetBinCenter(i+1)); // double thisTS = profile->getVal(); double thisTS = fc.GetTestStatSampler()->EvaluateTestStatistic(*toyData,tmpPOI); // cout << "poi = " << firstPOI->getVal() // << " max is " << arMax << " this profile = " << thisTS << endl; // cout << "thisTS = " << thisTS<<endl; // NOTE: need to add a small epsilon term for single precision vs. double precision if(thisTS<=arMax + 1e-7){ thisUL = firstPOI->getVal(); } else{ break; } } */ histOfUL->Fill(thisUL); // for few events, data is often the same, and UL is often the same // cout << "thisUL = " << thisUL<<endl; delete toyData; } histOfUL->Draw(); c1->SaveAs("one-sided_upper_limit_output.pdf"); // if you want to see a plot of the sampling distribution for a particular scan point: /* SamplingDistPlot sampPlot; int indexInScan = 0; tmpPoint = (RooArgSet*) parameterScan->get(indexInScan)->clone("temp"); firstPOI->setVal( tmpPoint->getRealValue(firstPOI->GetName()) ); toymcsampler->SetParametersForTestStat(tmpPOI); SamplingDistribution* samp = toymcsampler->GetSamplingDistribution(*tmpPoint); sampPlot.AddSamplingDistribution(samp); sampPlot.Draw(); */ // Now find bands and power constraint Double_t* bins = histOfUL->GetIntegral(); TH1F* cumulative = (TH1F*) histOfUL->Clone("cumulative"); cumulative->SetContent(bins); double band2sigDown, band1sigDown, bandMedian, band1sigUp,band2sigUp; for(int i=1; i<=cumulative->GetNbinsX(); ++i){ if(bins[i]<RooStats::SignificanceToPValue(2)) band2sigDown=cumulative->GetBinCenter(i); if(bins[i]<RooStats::SignificanceToPValue(1)) band1sigDown=cumulative->GetBinCenter(i); if(bins[i]<0.5) bandMedian=cumulative->GetBinCenter(i); if(bins[i]<RooStats::SignificanceToPValue(-1)) band1sigUp=cumulative->GetBinCenter(i); if(bins[i]<RooStats::SignificanceToPValue(-2)) band2sigUp=cumulative->GetBinCenter(i); } cout << "-2 sigma band " << band2sigDown << endl; cout << "-1 sigma band " << band1sigDown << " [Power Constraint)]" << endl; cout << "median of band " << bandMedian << endl; cout << "+1 sigma band " << band1sigUp << endl; cout << "+2 sigma band " << band2sigUp << endl; // print out the interval on the first Parameter of Interest cout << "\nobserved 95% upper-limit "<< interval->UpperLimit(*firstPOI) <<endl; cout << "CLb strict [P(toy>obs|0)] for observed 95% upper-limit "<< CLb <<endl; cout << "CLb inclusive [P(toy>=obs|0)] for observed 95% upper-limit "<< CLbinclusive <<endl; delete profile; delete nll; }