Exemplo n.º 1
0
int main(int argc, const char** argv){
  bool ReDoCuts=false;

  TCut TwelveCut = "gamma_CL>0.1&&BDT_response>0.36&&piplus_MC12TuneV3_ProbNNpi>0.2&&piminus_MC12TuneV3_ProbNNpi>0.2&&Kaon_MC12TuneV3_ProbNNk>0.4";
  TCut ElevenCut = "gamma_CL>0.1&&BDT_response>0.30&&piplus_MC12TuneV3_ProbNNpi>0.2&&piminus_MC12TuneV3_ProbNNpi>0.2&&Kaon_MC12TuneV3_ProbNNk>0.4";
  
  //______________________________MAKE CUT FILE FOR 2012___________________________________
  if(ReDoCuts){
    DataFile MCA(std::getenv("BUKETAPMCBDTRESPROOT"),MC,Twel,MagAll,buketap,"BDTApplied_SampleA");
    
    DataFile MCB(std::getenv("BUKETAPMCBDTRESPROOT"),MC,Twel,MagAll,buketap,"BDTApplied_SampleB");
  
    TreeReader* MC12Reader=  new TreeReader("DecayTree");
    MC12Reader->AddFile(MCA);
    MC12Reader->AddFile(MCB);
    MC12Reader->Initialize();
    
    TFile* MC12Cut = new TFile("CutFile12.root","RECREATE");
    TTree* MC12CutTree=MC12Reader->CopyTree(TwelveCut,-1,"DecayTree");
    TRandom3 *MCRand = new TRandom3(224);
    TH1I * MCnCands12= new TH1I("MCnCands12","MCnCands12",10,0,10);
    TTree*MC12SingleTree=HandyFunctions::GetSingleTree(MCRand,MC12CutTree,MCnCands12,NULL);
    MCnCands12->Write();
    MC12SingleTree->Write();
    MC12Cut->Close();
    
    //________________________________MAKE CUT FILE FOR 2011__________________________________
    
    DataFile MC11A(std::getenv("BUKETAPMCBDTRESPROOT"),MC,Elev,MagAll,buketap,"BDTApplied_SampleA");
    
    DataFile MC11B(std::getenv("BUKETAPMCBDTRESPROOT"),MC,Elev,MagAll,buketap,"BDTApplied_SampleB");
    
    TreeReader* MC11Reader= new TreeReader("DecayTree");
    MC11Reader->AddFile(MC11A);
    MC11Reader->AddFile(MC11B);
    MC11Reader->Initialize();
    
    TFile* MC11Cut = new TFile("CutFile11.root","RECREATE");
    TTree* MC11CutTree=MC11Reader->CopyTree(ElevenCut,-1,"DecayTree");

    TH1I * MCnCands11= new TH1I("MCnCands11","MCnCands11",10,0,10);
    TTree* MC11SingleTree=HandyFunctions::GetSingleTree(MCRand,MC11CutTree,MCnCands11,NULL);
    MCnCands11->Write();
    MC11SingleTree->Write();
    MC11Cut->Close();
  //_________________________________ MAKE FLAT TREES  ____________________________________
  
    TFile* MC12Input = new TFile("CutFile12.root");
    TTree* MC12InputTree=(TTree*)MC12Input->Get("DecayTree");
    Float_t MCEta_Mass12[20]; MC12InputTree->SetBranchAddress("Bu_DTFNoFix_eta_prime_M",&MCEta_Mass12);
    Int_t isSingle12; MC12InputTree->SetBranchAddress("isSingle",&isSingle12);
    
    TFile* MC12FlatOut = new TFile("MCMinimalFile12.root","RECREATE");
    TTree* MC12FlatTree = MC12InputTree->CloneTree(0);
    Double_t MCBu_DTFNoFix_eta_Prime_MF12; MC12FlatTree->Branch("Bu_DTFNoFix_eta_prime_MF",&MCBu_DTFNoFix_eta_Prime_MF12,"Bu_DTFNoFix_eta_prime_MF/D");
    
    Long64_t Entries12=MC12InputTree->GetEntries();
    
    for(int i=0;i<Entries12;++i){
      MC12InputTree->GetEntry(i);
      if(isSingle12==0)continue;
      MCBu_DTFNoFix_eta_Prime_MF12=MCEta_Mass12[0];
      MC12FlatTree->Fill();
    }
    
    MC12FlatTree->Write();
    MC12FlatOut->Close();
    
    TFile* MC11Input = new TFile("CutFile11.root");
    TTree* MC11InputTree=(TTree*)MC11Input->Get("DecayTree");
    Float_t MCEta_Mass11[20]; MC11InputTree->SetBranchAddress("Bu_DTFNoFix_eta_prime_M",&MCEta_Mass11);
    Int_t isSingle11; MC11InputTree->SetBranchAddress("isSingle",&isSingle11);
    
    TFile* MC11FlatOut = new TFile("MCMinimalFile11.root","RECREATE");
    TTree* MC11FlatTree = MC11InputTree->CloneTree(0);
    Double_t MCBu_DTFNoFix_eta_Prime_MF11; MC11FlatTree->Branch("Bu_DTFNoFix_eta_prime_MF",&MCBu_DTFNoFix_eta_Prime_MF11,"Bu_DTFNoFix_eta_prime_MF/D");
    
    Long64_t Entries11=MC11InputTree->GetEntries();
    
    for(int i=0;i<Entries11;++i){
      MC11InputTree->GetEntry(i);
      if(isSingle11==0)continue;
      MCBu_DTFNoFix_eta_Prime_MF11=MCEta_Mass11[0];
      MC11FlatTree->Fill();
    }
    
    MC11FlatTree->Write();
    MC11FlatOut->Close();
  }
  
  //_____________________________________________LOAD ROODATASETS___________________________________

  TFile* MCFlatInput12= new TFile("MCMinimalFile12.root");
  TTree* MCFlatInputTree12=(TTree*)MCFlatInput12->Get("DecayTree");

  TFile* MCFlatInput11= new TFile("MCMinimalFile11.root");
  TTree* MCFlatInputTree11=(TTree*)MCFlatInput11->Get("DecayTree");

  RooRealVar MCBMass("Bu_DTF_MF","Bu_DTF_MF",5000.0,5600.0);
  RooRealVar MCEtaMass("eta_prime_MM","eta_prime_MM",700.0,1200.0);
  RooRealVar BDT_response("BDT_response","BDT_response",-1.0,1.0);
  RooRealVar gamma_CL("gamma_CL","gamma_CL",0.1,1.0);
  RooArgSet Args(MCBMass,MCEtaMass,BDT_response,gamma_CL);

  RooDataSet* MCData12 = new RooDataSet("MCData12","MCData12",Args,Import(*MCFlatInputTree12));
  
  std::cout <<" Data File 12 Loaded"<<std::endl;
  
  RooDataSet* MCData11 = new RooDataSet("MCData11","MCData11",Args,Import(*MCFlatInputTree11));

  std::cout<<" Data File 11 loaded"<<std::endl;

  RooDataSet* MCDataAll= new RooDataSet("MCDataAll","MCDataAll",Args);

  MCDataAll->append(*MCData12);
  MCDataAll->append(*MCData11);
  
  RooPlot* massFrame = MCBMass.frame(Title("Data Import Check"),Bins(50));
  MCDataAll->plotOn(massFrame);
  
  RooPlot *BDTFrame = BDT_response.frame(Title("BDT Cut Check"),Bins(50));
  MCDataAll->plotOn(BDTFrame);
  TCanvas C;
  C.Divide(2,1);
  C.cd(1);
  massFrame->Draw();
  C.cd(2);
  BDTFrame->Draw();
  C.SaveAs("ImportChecks.eps");

  //________________________________MAKE MCROODATACATEGORIES__________________________________

  RooDataSet* MCBData=(RooDataSet*)MCDataAll->reduce(RooArgSet(MCBMass));
  MCBData->Print("v");
  
  RooDataSet* MCEtaData=(RooDataSet*)MCDataAll->reduce(RooArgSet(MCEtaMass));
  MCEtaData->Print("v");

  RooCategory MCMassType("MCMassType","MCMassType") ;
  MCMassType.defineType("B") ;
  MCMassType.defineType("Eta") ;
  
  // Construct combined dataset in (x,sample)
  RooDataSet MCcombData("MCcombData","MC combined data",Args,Index(MCMassType),Import("B",*MCBData),Import("Eta",*MCEtaData));

  
  //=============================================== MC FIT MODEL===================================
  
  RooRealVar Mean("Mean","Mean",5279.29,5276.0,5284.00);
  RooRealVar Sigma("Sigma","Sigma",20.54,17.0,24.8);
  RooRealVar LAlpha("LAlpha","LAlpha",-1.064,-2.5,0.0);
  RooRealVar RAlpha("RAlpha","RAlpha",1.88,0.0,5.0);
  RooRealVar LN("LN","LN",13.0,0.0,40.0);
  RooRealVar RN("RN","RN",2.56,0.0,6.0);

  RooCBShape CBLeft("CBLeft","CBLeft",MCBMass,Mean,Sigma,LAlpha,LN);
  
  RooCBShape CBRight("CBRight","CBRight",MCBMass,Mean,Sigma,RAlpha,RN);

  RooRealVar FitFraction("FitFraction","FitFraction",0.5,0.0,1.0);
  RooAddPdf DCB("DCB","DCB",RooArgList(CBRight,CBLeft),FitFraction);

  RooRealVar SignalYield("SignalYield","SignalYield",4338.0,500.0,10000.0);
  //  RooExtendPdf ExtDCB("ExtDCB","ExtDCB",DCB,SignalYield);
  
  //==============================ETA DCB ++++++++++++++++++++++++++++++
  
  RooRealVar MCEtamean("MCEtamean","MCEtamean",958.0,955.0,960.0);
  RooRealVar MCEtasigma("MCEtasigma","MCEtasigma",9.16,8.0,14.0);
  RooRealVar EtaLAlpha("EtaLAlpha","EtaLAlpha",-1.45,-5.0,1.0);
  RooRealVar EtaRAlpha("EtaRAlpha","EtaRAlpha",1.76,0.0,4.0);
  RooRealVar EtaLN("EtaLN","EtaLN",0.1,0.0,20.0);
  RooRealVar EtaRN("EtaRN","EtaRN",0.1,0.0,20.0);

  RooCBShape EtaCBLeft("EtaCBLeft","EtaCBLeft",MCEtaMass,MCEtamean,MCEtasigma,EtaLAlpha,EtaLN);
  
  RooCBShape EtaCBRight("EtaCBRight","EtaCBRight",MCEtaMass,MCEtamean,MCEtasigma,EtaRAlpha,EtaRN);

  RooRealVar EtaFitFraction("EtaFitFraction","EtaFitFraction",0.22,0.1,1.0);
  RooAddPdf EtaDCB("EteaDCB","EtaDCB",RooArgList(EtaCBRight,EtaCBLeft),EtaFitFraction);

  RooProdPdf MCSignalPdf("MCSignalPdf","MCSignalPdf",RooArgSet(EtaDCB,DCB));
  
  RooExtendPdf ExtendedMCSignalPdf("ExtendedMCSignalPdf","ExtendedMCSignalPdf",MCSignalPdf,SignalYield);

  RooSimultaneous MCsimPdf("MCsimPdf","MC simultaneous pdf",MCMassType) ;
  //  MCsimPdf.addPdf(ExtDCB,"B");
  //  MCsimPdf.addPdf(ExtendedMCEtaDCB,"Eta"); 

  //============================== DO the MC FIT =======================================
  //MCsimPdf.fitTo(MCcombData,Extended(kTRUE),Minos(kTRUE));
  //ExtendedMCEtaDCB.fitTo(*MCEtaData,Extended(kTRUE),Minos(kTRUE));
  //ExtDCB.fitTo(*MCBData,Extended(
  ExtendedMCSignalPdf.fitTo(*MCDataAll,Extended(kTRUE),Minos(kTRUE));
  
  RooPlot* MCframe1 = MCBMass.frame(Range(5100.0,5500.0),Bins(50),Title("B mass projection"));
  MCDataAll->plotOn(MCframe1);
  ExtendedMCSignalPdf.plotOn(MCframe1);
  ExtendedMCSignalPdf.paramOn(MCframe1);
  
  RooPlot* MCframe2 = MCEtaMass.frame(Range(880.0,1020.0),Bins(50),Title("Eta mass projection")) ;
  MCDataAll->plotOn(MCframe2);
  ExtendedMCSignalPdf.plotOn(MCframe2);
  ExtendedMCSignalPdf.paramOn(MCframe2);
  
  TCanvas* MCc = new TCanvas("rf501_simultaneouspdf","rf403_simultaneouspdf",1200,1000) ;
  gPad->SetLeftMargin(0.15) ; MCframe1->GetYaxis()->SetTitleOffset(1.4) ; MCframe1->Draw() ;
  MCc->SaveAs("MCSimulCanvas.pdf");

  TCanvas* MCcEta = new TCanvas(" Eta Canvas","Eta Canvas",1200,1000);
  gPad->SetLeftMargin(0.15) ; MCframe2->GetYaxis()->SetTitleOffset(1.4) ; MCframe2->Draw() ;
  MCcEta->SaveAs("MCEtaCanvas.pdf");

  TFile* MCFits= new TFile("MCFitResult.root","RECREATE");
  //  TCanvas* DecMCB=HandyFunctions::DecoratePlot(MCframe1);
  //  TCanvas* DecMCEta=HandyFunctions::DecoratePlot(MCframe2);
  //DecMCEta->Write();
  //  DecMCB->Write();
  MCc->Write();
  MCcEta->Write();

  std::cout<<"MC Eta Chi2 = "<<MCframe2->chiSquare()<<std::endl;
  std::cout<<"MC B Chi2 = "<<MCframe1->chiSquare()<<std::endl;

  //___________________________________ CUT DOWN COLLISION DATA ______________________________
  if(ReDoCuts){
    DataFile TwelveA(std::getenv("BUKETAPDATABDTRESPROOT"),Data,Twel,MagAll,buketap,"BDTApplied_SampleA");

    DataFile TwelveB(std::getenv("BUKETAPDATABDTRESPROOT"),Data,Twel,MagAll,buketap,"BDTApplied_SampleB");
  
    DataFile ElevenA(std::getenv("BUKETAPDATABDTRESPROOT"),Data,Elev,MagAll,buketap,"BDTApplied_SampleA");

    DataFile ElevenB(std::getenv("BUKETAPDATABDTRESPROOT"),Data,Elev,MagAll,buketap,"BDTApplied_SampleB");		

    TRandom3* DataRand= new TRandom3(224);
    TH1I* DataNCand12= new TH1I("DataNCand12","DataNCand12",10,0,10);
    TH1I* DataNCand11= new TH1I("DataNCand11","DataNCand11",10,0,10);
    
    TreeReader* UncutDataReader12= new TreeReader("DecayTree");
    UncutDataReader12->AddFile(TwelveA);
    UncutDataReader12->AddFile(TwelveB);
    UncutDataReader12->Initialize();
    
    TFile* CutDataFile12 = new TFile("CutDataFile12.root","RECREATE");
    TTree* CutDataTree12 = UncutDataReader12->CopyTree(TwelveCut,-1,"DecayTree");
    TTree* SingleCutDataTree12=HandyFunctions::GetSingleTree(DataRand,CutDataTree12,DataNCand12,NULL);
    SingleCutDataTree12->Write();
    CutDataFile12->Close();
    
    TreeReader* UncutDataReader11= new TreeReader("DecayTree");
    UncutDataReader11->AddFile(ElevenB);
    UncutDataReader11->AddFile(ElevenA);
    UncutDataReader11->Initialize();
    
    TFile* CutDataFile11 = new TFile("CutDataFile11.root","RECREATE");
    TTree* CutDataTree11 = UncutDataReader11->CopyTree(ElevenCut,-1,"DecayTree");
    TTree* SingleCutDataTree11=HandyFunctions::GetSingleTree(DataRand,CutDataTree11,DataNCand11,NULL);
    SingleCutDataTree11->Write();
    CutDataFile11->Close();
  

    TFile* DataInput12 = new TFile("CutDataFile12.root");
    TTree* DataInputTree12=(TTree*)DataInput12->Get("DecayTree");
    DataInputTree12->SetBranchStatus("*",0);
    DataInputTree12->SetBranchStatus("Bu_DTF_MF",1);
    DataInputTree12->SetBranchStatus("Bu_DTFNoFix_eta_prime_M",1);
    DataInputTree12->SetBranchStatus("eta_prime_MM",1);
    DataInputTree12->SetBranchStatus("isSingle",1);
    Float_t Eta_Mass12[20]; DataInputTree12->SetBranchAddress("Bu_DTFNoFix_eta_prime_M",&Eta_Mass12);
    Int_t isSingle12; DataInputTree12->SetBranchAddress("isSingle",&isSingle12);
    
    TFile* MinimalDataFile12 = new TFile("MinimalDataFile12.root","RECREATE");
    TTree* MinimalDataTree12= DataInputTree12->CloneTree(0);
    Double_t Bu_DTFNoFix_eta_prime_MF12; MinimalDataTree12->Branch("Bu_DTFNoFix_eta_prime_MF",&Bu_DTFNoFix_eta_prime_MF12,"Bu_DTFNoFix_eta_prime_MF/D");
    
    Long64_t Entries12=DataInputTree12->GetEntries();
    
    for(int i=0;i<Entries12;++i){
      DataInputTree12->GetEntry(i);
      if(isSingle12==0)continue;
      Bu_DTFNoFix_eta_prime_MF12=Eta_Mass12[0];
      MinimalDataTree12->Fill();
    }
    
    MinimalDataTree12->Write();
    MinimalDataFile12->Close();
    
    TFile* DataInput11 = new TFile("CutDataFile11.root");
    TTree* DataInputTree11=(TTree*)DataInput11->Get("DecayTree");
    DataInputTree11->SetBranchStatus("*",0);
    DataInputTree11->SetBranchStatus("Bu_DTF_MF",1);
    DataInputTree11->SetBranchStatus("Bu_DTFNoFix_eta_prime_M",1);
    DataInputTree11->SetBranchStatus("eta_prime_MM",1);
    DataInputTree11->SetBranchStatus("isSingle",1);
    Float_t Eta_Mass11[20]; DataInputTree11->SetBranchAddress("Bu_DTFNoFix_eta_prime_M",&Eta_Mass11);
    Int_t isSingle11; DataInputTree11->SetBranchAddress("isSingle",&isSingle11);
    
    TFile* MinimalDataFile11 = new TFile("MinimalDataFile11.root","RECREATE");
    TTree* MinimalDataTree11= DataInputTree11->CloneTree(0);
    Double_t Bu_DTFNoFix_eta_prime_MF11; MinimalDataTree11->Branch("Bu_DTFNoFix_eta_prime_MF",&Bu_DTFNoFix_eta_prime_MF11,"Bu_DTFNoFix_eta_prime_MF/D");
    
    Long64_t Entries11=DataInputTree11->GetEntries();
    
    for(int i=0;i<Entries11;++i){
    DataInputTree11->GetEntry(i);
    if(isSingle11==0)continue;
    Bu_DTFNoFix_eta_prime_MF11=Eta_Mass11[0];
    MinimalDataTree11->Fill();
    }
    MinimalDataTree11->Write();
    MinimalDataFile11->Close();
  }

  //___________________________________ LOAD DATA TO ROODATASET____________________________________
  
  RooRealVar BMass("Bu_DTF_MF","Bu_DTF_MF",5000.0,5600.0);
  RooRealVar EtaMass("eta_prime_MM","eta_prime_MM",870.0,1050.0);
  RooArgSet MassArgs(BMass,EtaMass);

  TFile* Data12File = new TFile("MinimalDataFile12.root");
  TTree* DataTree12=(TTree*)Data12File->Get("DecayTree");

  RooDataSet* Data12 = new RooDataSet("Data12","Data12",MassArgs,Import(*DataTree12));

  TFile* Data11File = new TFile("MinimalDataFile11.root");
  TTree* DataTree11=(TTree*)Data11File->Get("DecayTree");

  RooDataSet* Data11 = new RooDataSet("Data11","Data11",MassArgs,Import(*DataTree11));
  
  RooDataSet* AllData = new RooDataSet("AllData","AllData",MassArgs);
  AllData->append(*Data12);
  AllData->append(*Data11);
  TCanvas ImportC;
  RooPlot* ImportCheck = BMass.frame(Title("ImportCheck"),Bins(50));
  AllData->plotOn(ImportCheck);
  ImportCheck->Draw();
  ImportC.SaveAs("Alldataimport.pdf");

  std::cout<<" Data Loaded, Total Entries = "<<AllData->numEntries()<<std::endl;

  AllData->Print("v");

  RooDataSet* BData=(RooDataSet*)AllData->reduce(RooArgSet(BMass));
  BData->Print("v");

  RooDataSet* EtaData=(RooDataSet*)AllData->reduce(RooArgSet(EtaMass));
  EtaData->Print("v");

  //___________________________________Fit to Eta_Prime in BMass Sidebands______________________

  RooDataSet* BSidebands=(RooDataSet*)AllData->reduce(Cut("(Bu_DTF_MF>5000.0&&Bu_DTF_MF<5179.0)||(Bu_DTF_MF>5379.0&&Bu_DTF_MF<5800.0)"));

  TCanvas BSidebandCanvas;
  RooPlot* BSidebandPlot = EtaMass.frame(Title("B sidebands"),Bins(30));
  BSidebands->plotOn(BSidebandPlot);
  BSidebandPlot->Draw();
  BSidebandCanvas.SaveAs("BSidebandDataCheck.pdf");

  
  RooRealVar BsbMean(" Mean","BsbMean",958.0,900.0,1020.0);
  RooRealVar BsbSigma(" Sigma","BsbSigma",19.8,10.0,40.8);
  RooRealVar BsbLAlpha(" Alpha","BsbLAlpha",-1.63,-10.0,0.0);
  //  RooRealVar BsbRAlpha("BsbRAlpha","BsbRAlpha",1.47,0.0,10.0);
  RooRealVar BsbLN(" N","BsbLN",0.1,0.0,20.0);
  //  RooRealVar BsbRN("BsbRN","BsbRN",0.1,0.0,20.0);

  RooCBShape BsbCBLeft("BsbCBLeft","BsbCBLeft",EtaMass,BsbMean,BsbSigma,BsbLAlpha,BsbLN);
  
  //  RooCBShape BsbCBRight("BsbCBRight","BsbCBRight",EtaMass,BsbMean,BsbSigma,BsbRAlpha,BsbRN);

  //  RooRealVar BsbFitFraction("BsbFitFraction","BsbFitFraction",0.5,0.0,1.0);
  //  RooAddPdf BsbDCB("BsbDCB","BsbDCB",RooArgList(BsbCBRight,BsbCBLeft),BsbFitFraction);
  RooRealVar Bsbslope("Bsbslope","Bsbslope",0.5,0.0,1.0);
  RooRealVar BsbP2("BsbP2","BsbP2",-0.5,-1.0,0.0);
  RooChebychev BsbLinear("BsbLinear","BsbLinear",EtaMass,RooArgSet(Bsbslope,BsbP2));

  RooRealVar BsbFitFraction("BsbFitFraction","BsbFitFraction",0.2,0.0,1.0);

  RooAddPdf BsbBackground("BsbBackground","BsbBackground",RooArgList(BsbLinear,BsbCBLeft),BsbFitFraction);
  
  RooRealVar BsbYield(" Yield","BsbYield",500.0,0.0,1000.0);
  RooExtendPdf BsbExtDCB("BsbExtDCB","BsbExtDCB",BsbCBLeft,BsbYield);

  BsbExtDCB.fitTo(*BSidebands,Extended(kTRUE),Minos(kTRUE));
  TCanvas BSBFitCanvas;
  RooPlot* BSBFitPlot = EtaMass.frame(Title("Eta fit in B Sidebands"),Bins(30));
  BSidebands->plotOn(BSBFitPlot);
  BsbExtDCB.plotOn(BSBFitPlot);
  BsbExtDCB.paramOn(BSBFitPlot);
  BSBFitPlot->Draw();
  BSBFitCanvas.SaveAs("BSidebandFit.pdf");
  TFile * SidebandFitFile= new TFile("SidebandFit.root","RECREATE");
  BSBFitCanvas.Write();
  SidebandFitFile->Close();
  
  //___________________________________DO THE 2D FIT TO DATA___________________________________


  const double PDGBMass= 5279.26;
  BMass.setRange("SignalWindow",PDGBMass-(3*Sigma.getVal()),PDGBMass+(3*Sigma.getVal()));
  RooRealVar DSignalYield("DSignalYield","DSignalYield",4000.0,0.0,10000.0);

  //================================= B MASS SIGNAL PDF==============================
  RooRealVar DMean("Mean","DMean",5279.29,5270.0,5290.00);
  RooRealVar DSigma("Sigma","DSigma",19.8,10.0,40.8);
  RooRealVar DLAlpha("DLAlpha","DLAlpha",LAlpha.getVal());
  RooRealVar DRAlpha("DRAlpha","DRAlpha",RAlpha.getVal());
  RooRealVar DLN("DLN","DLN",LN.getVal());
  RooRealVar DRN("DRN","DRN",RN.getVal());

  RooCBShape DCBLeft("DCBLeft","DCBLeft",BMass,DMean,DSigma,DLAlpha,DLN);
  
  RooCBShape DCBRight("DCBRight","DCBRight",BMass,DMean,DSigma,DRAlpha,DRN);

  RooRealVar DFitFraction("FitFraction","DFitFraction",0.5,0.0,1.0);
  RooAddPdf DDCB("DDCB","DDCB",RooArgList(DCBRight,DCBLeft),DFitFraction);
  
  //==============================B MASS BKG PDF==============================
  RooRealVar slope("slope","slope",-0.5,-1.0,0.0);
  RooChebychev bkg("bkg","Background",BMass,RooArgSet(slope));
  
  //==============================Eta mass signal pdf================================
  RooRealVar DEtamean("Etamean","DEtamean",958.0,945.0,980.0) ;
  RooRealVar DEtasigma("Etasigma","DEtasigma",15.0,5.0,65.0) ;
  RooRealVar DEtaLAlpha("DEtaLAlpha","DEtaLAlpha",EtaLAlpha.getVal());
  RooRealVar DEtaRAlpha("DEtaRAlpha","DEtaRAlpha",EtaRAlpha.getVal());
  RooRealVar DEtaLN("DEtaLN","DEtaLN",EtaLN.getVal());
  RooRealVar DEtaRN("DEtaRN","DEtaRN",EtaRN.getVal());
  
  RooCBShape EtaDCBLeft("EtaDCBLeft","EtaDCBLeft",EtaMass,DEtamean,DEtasigma,DEtaLAlpha,DEtaLN);
  
  RooCBShape EtaDCBRight("EtaDCBRight","EtaDCBRight",EtaMass,DEtamean,DEtasigma,DEtaRAlpha,DEtaRN);
  
  RooRealVar DEtaFitFraction("EtaFitFraction","DEtaFitFraction",0.5,0.0,1.0);
  RooAddPdf EtaDDCB("EtaDDCB","EtaDDCB",RooArgList(EtaDCBRight,EtaDCBLeft),DEtaFitFraction);

  RooProdPdf DSignalPdf("DSignalPdf","DSignalPdf",RooArgList(EtaDDCB,DDCB));
  
  RooExtendPdf DExtSignalPdf("DExtSignalPdf","DExtSignalPdf",DSignalPdf,DSignalYield);

  //=============================== Eta mass bkg pdf==================================
  
  RooRealVar EtaBkgMean("EtaBkgMean","EtaBkgMean",958.0,900.0,1020.0);
  RooRealVar EtaBkgSigma("EtaBkgSigma","EtaBkgSigma",19.8,10.0,40.8);
  RooRealVar EtaBkgLAlpha("EtaBkgLAlpha","EtaBkgLAlpha",BsbLAlpha.getVal());
  //  RooRealVar EtaBkgRAlpha("EtaBkgRAlpha","EtaBkgRAlpha",BsbRAlpha.getVal());
  RooRealVar EtaBkgLN("EtaBkgLN","EtaBkgLN",BsbLN.getVal());
  //  RooRealVar EtaBkgRN("EtaBkgRN","EtaBkgRN",BsbRN.getVal());

  RooCBShape EtaBkgCBLeft("EtaBkgCBLeft","EtaBkgCBLeft",EtaMass,DEtamean,EtaBkgSigma,EtaBkgLAlpha,EtaBkgLN);
  
  //  RooCBShape EtaBkgCBRight("EtaBkgCBRight","EtaBkgCBRight",EtaMass,DEtamean,EtaBkgSigma,EtaBkgRAlpha,EtaBkgRN);
  
  //  RooRealVar EtaBkgFitFraction("EtaBkgFitFraction","EtaBkgFitFraction",0.5,0.0,1.0);
  //  RooAddPdf EtaBkgDCB("EtaBkgDCB","EtaBkgDCB",RooArgList(EtaBkgCBRight,EtaBkgCBLeft),EtaBkgFitFraction);
  
  RooProdPdf DataBackgroundPDF("DataBackgroundPDF","DataBackgroundPDF",RooArgList(EtaBkgCBLeft,bkg));
  
  RooRealVar DataBackgroundYield("BackgroundYield","DataBackgroundYield",500.0,0.0,10000.0);
  
  RooExtendPdf ExtDataBackgroundPDF("ExtDataBackgroundPDF","ExtDataBackgroundPDF",DataBackgroundPDF,DataBackgroundYield);

  RooAddPdf TotalPDF("TotalPDF","TotalPDF",RooArgList(ExtDataBackgroundPDF,DExtSignalPdf));
  std::cout<<"Dependents = "<<std::endl;
  RooArgSet* Dependents=TotalPDF.getDependents(AllData);
  Dependents->Print("v");
  std::cout<<"parameters= "<<std::endl;
  RooArgSet* parameters=TotalPDF.getParameters(AllData);
  parameters->Print("v");
  RooCategory MassType("MassType","MassType") ;
  MassType.defineType("B") ;
  MassType.defineType("Eta") ;
  
  // Construct combined dataset in (x,sample)
  RooDataSet combData("combData","combined data",MassArgs,Index(MassType),Import("B",*BData),Import("Eta",*EtaData));

  RooSimultaneous simPdf("simPdf","simultaneous pdf",MassType) ;

  // Associate model with the physics state and model_ctl with the control state
  //  simPdf.addPdf(WholeFit,"B");
  //  simPdf.addPdf(WholeEtaFit,"Eta"); 

  //  simPdf.fitTo(combData,Extended(kTRUE)/*,Minos(kTRUE)*/);
  
  TotalPDF.fitTo(*AllData,Extended(kTRUE),Minos(kTRUE));

  RooPlot* frame1 = BMass.frame(Bins(50),Title("B mass projection"));
  AllData->plotOn(frame1);
  TotalPDF.plotOn(frame1,Components(ExtDataBackgroundPDF),LineStyle(kDashed),LineColor(kRed));
  TotalPDF.plotOn(frame1);
  TotalPDF.paramOn(frame1);
  
  // The same plot for the control sample slice
  RooPlot* frame2 = EtaMass.frame(Bins(50),Title("Eta mass projection")) ;
  AllData->plotOn(frame2);
  TotalPDF.plotOn(frame2,Components(ExtDataBackgroundPDF),LineStyle(kDashed),LineColor(kRed));
  TotalPDF.plotOn(frame2);
  TotalPDF.paramOn(frame2);
  TCanvas* DecoratedCanvas =HandyFunctions::DecoratePlot(frame2);

  
  TCanvas* DataBC= new TCanvas("BCanvas","BCanvas",1200,1000) ;
  gPad->SetLeftMargin(0.15) ; frame1->GetYaxis()->SetTitleOffset(1.4) ; frame1->Draw() ;
  TCanvas* EtaBC= new TCanvas("EtaCanvas","EtaCanvas",1200,1000) ;
  gPad->SetLeftMargin(0.15) ; frame2->GetYaxis()->SetTitleOffset(1.4) ; frame2->Draw() ;
  DataBC->SaveAs("DataBC.pdf");
  EtaBC->SaveAs("EtaBC.pdf");
  
  TFile * DataSimulFit = new TFile("DataSimulFit.root","RECREATE");
  DataBC->Write();
  EtaBC->Write();
  DecoratedCanvas->Write();

  
		 
		  

  
}
Exemplo n.º 2
0
int main (int argc, char **argv)
{
  const char* chInFile = "ws.root";
  const char* chOutFile = "ws_gen.root";
  int numSignal = 10000;
  int numBkg = 100000;

  char option_char;
  while ( (option_char = getopt(argc,argv, "i:o:s:b:")) != EOF )
    switch (option_char)
      {
         case 'i': chInFile = optarg; break;
         case 'o': chOutFile = optarg; break;
         case 's': numSignal = atoi(optarg); break;
         case 'b': numBkg = atoi(optarg); break;
         case '?': fprintf (stderr,
                            "usage: %s [i<input file> o<output file>]\n", argv[0]);
      }

  cout << "In File = " << chInFile << endl;
  cout << "Out File = " << chOutFile << endl;
  cout << "Signal Events = " << numSignal << endl;
  cout << "Bkg Events = " << numBkg << endl;

  TFile inFile(chInFile,"READ");
  RooWorkspace* ws = (RooWorkspace*) inFile.Get("rws");
  TFile outFile(chOutFile,"RECREATE");

/*
  ws->var("tau")->setVal(1.417);
  ws->var("DG")->setVal(0.151);
  ws->var("beta")->setVal(0.25);
  ws->var("A02")->setVal(0.553);
  ws->var("A1")->setVal(0.487);
  ws->var("delta_l")->setVal(3.15);
  ws->var("fs")->setVal(0.147);
*/

//  ws->var("delta_l")->setConstant(kTRUE);
//  ws->var("delta_p")->setConstant(kTRUE);
//  ws->var("Dm")->setConstant(kTRUE);

  //*ws->var("xs") = numSignal/(numSignal+numBkg);
//  int numSignal = numEvents * ws->var("xs")->getVal();
//  int numBkg = numEvents - numSignal;

  ws->factory("Gaussian::dilutionGauss(d,0,0.276)");
  //ws->factory("SUM::dSignalPDF(xds[0.109]*dilutionGauss,TruthModel(d))");
  //ws->factory("SUM::dBkgPDF(xdb[0.109]*dilutionGauss,TruthModel(d))");
  ws->factory("SUM::dSignalPDF(xds[1]*dilutionGauss,TruthModel(d))");
  ws->factory("SUM::dBkgPDF(xdb[1]*dilutionGauss,TruthModel(d))");

/*
  ws->factory("GaussModel::xetGaussianS(et,meanGaussEtS,sigmaGaussEtS)");
  ws->factory("Decay::xerrorSignal(et,tauEtS,xetGaussianS,SingleSided]");

  ws->factory("PROD::xsignalTimeAngle(timeAngle|et,xerrorSignal");
  ws->factory("PROD::xsignal(massSignal,xsignalTimeAngle,DmConstraint)");
*/

  RooDataSet* dSignalData = ws->pdf("dSignalPDF")->generate(RooArgSet(*ws->var("d")),numSignal);
  RooDataSet *dataSignal = ws->pdf("signal")->generate(RooArgSet(*ws->var("m"),*ws->var("t"),*ws->var("et"),*ws->var("cpsi"),*ws->var("ctheta"),*ws->var("phi")), RooFit::ProtoData(*dSignalData));

  ws->factory("GaussModel::xetGaussianPR(et,meanGaussEtPR,sigmaGaussEtPR)");
  ws->factory("Decay::xerrBkgPR(et,tauEtPR,xetGaussianPR,SingleSided]");

  ws->factory("GaussModel::xetGaussianNP(et,meanGaussEtNP,sigmaGaussEtNP)");
  ws->factory("Decay::xerrBkgNP(et,tauEtNP,xetGaussianNP,SingleSided]");


  /* Time */
  ws->factory("GaussModel::xresolution(t,0,scale,et)");
  ws->factory("Decay::xnegativeDecay(t,tauNeg,xresolution,Flipped)");
  ws->factory("Decay::xpositiveDecay(t,tauPos,xresolution,SingleSided)");
  ws->factory("Decay::xpositiveLongDecay(t,tauLngPos,xresolution,SingleSided)");

  ws->factory("RSUM::xtBkgNP(xn*xnegativeDecay,xp*xpositiveDecay,xpositiveLongDecay");

/*               Promt and Non-Prompt                       */
   ws->factory("PROD::xtimeBkgNP(xtBkgNP|et,xerrBkgNP)");
   ws->factory("PROD::xtimeBkgPR(xresolution|et,xerrBkgPR)");

   ws->factory("PROD::xPrompt(massBkgPR,xtimeBkgPR,anglePR)");
   ws->factory("PROD::xNonPrompt(massBkgNP,xtimeBkgNP,angleNP)");

  ws->factory("SUM::xbackground(xprompt*xPrompt,xNonPrompt)");


  RooDataSet* dBkgData = ws->pdf("dBkgPDF")->generate(RooArgSet(*ws->var("d")),numBkg);
  RooDataSet* dataBkg  = ws->pdf("xbackground")->generate(RooArgSet(*ws->var("m"),*ws->var("t"),*ws->var("et"),*ws->var("cpsi"),*ws->var("ctheta"),*ws->var("phi")), numBkg);

  dataBkg->merge(dBkgData);
  dataSignal->SetName("dataGenSignal");
  dataBkg->SetName("dataGenBkg");
  ws->import(*dataSignal);
  ws->import(*dataBkg);

  ////ws->import(*dataBkg,RooFit::Rename("dataGenBkg"));

  dataSignal->append(*dataBkg);
  dataSignal->SetName("dataGen");
  ws->import(*dataSignal);

  //RooFitResult *fit_result = ws->pdf("model")->fitTo(*ws->data("data"), RooFit::Save(kTRUE), RooFit::ConditionalObservables(*ws->var("d")), RooFit::NumCPU(2), RooFit::PrintLevel(3));
/*
        gROOT->SetStyle("Plain");

        TCanvas canvas("canvas", "canvas", 400,400);

        RooPlot *m_frame = ws->var("t")->frame();
        dataSignal->plotOn(m_frame, RooFit::MarkerSize(0.3));
        m_frame->Draw();

	canvas.SaveAs("m_toy_plot.png");
*/
/*
        gROOT->SetStyle("Plain");

        TCanvas canvas("canvas", "canvas", 800,400);
        canvas.Divide(2);

        canvas.cd(1);
        RooPlot *t_frame = ws->var("t")->frame();
        ws->data("data")->plotOn(t_frame, RooFit::MarkerSize(0.3));
        gPad->SetLogy(1);
        t_frame->Draw();

        canvas.cd(2);
        RooPlot *et_frame = ws->var("et")->frame();
        ws->data("data")->plotOn(et_frame,RooFit::MarkerSize(0.2));
        ws->pdf("errorSignal")->plotOn(et_frame);
        gPad->SetLogy(1);
        et_frame->Draw();

        canvas.SaveAs("t.png"); 


        canvas.cd(2);
        gPad->SetLogy(0);
        RooPlot *cpsi_frame = ws.var("cpsi")->frame();
        data->plotOn(cpsi_frame,RooFit::MarkerSize(0.2), RooFit::Rescale(1));
        data2->plotOn(cpsi_frame,
                RooFit::LineColor(kBlue), RooFit::DrawOption("L"));
        cpsi_frame->Draw();

        canvas.cd(3);
        RooPlot *ctheta_frame = ws.var("ctheta")->frame();
        data->plotOn(ctheta_frame,RooFit::MarkerSize(0.2), RooFit::Rescale(1));
        data2->plotOn(ctheta_frame,
                RooFit::LineColor(kBlue), RooFit::DrawOption("L"));
        ctheta_frame->Draw();

        canvas.cd(4);
        RooPlot *phi_frame = ws.var("phi")->frame();
        data->plotOn(phi_frame,RooFit::MarkerSize(0.2), RooFit::Rescale(1));
        data2->plotOn(phi_frame,
                RooFit::LineColor(kBlue), RooFit::DrawOption("L"));
        phi_frame->Draw();

       canvas.SaveAs("t.png");

*/

  ws->data("dataGen")->Print();
  ws->data("dataGenSignal")->Print();
  ws->data("dataGenBkg")->Print();

  ws->Write("rws");
  outFile.Close();
  inFile.Close();
}
Exemplo n.º 3
0
int main(int argc, char* argv[]){

  string bkgFileName;
  string sigFileName;
  string sigWSName;
  string bkgWSName;
  string outFileName;
  string datFileName;
  string outDir;
  int cat;
  int ntoys;
  int jobn;
  int seed;
  float mu_low;
  float mu_high;
  float mu_step;
  float expectSignal;
  int expectSignalMass;
  bool skipPlots=false;
  int verbosity;
  bool throwHybridToys=false;
  vector<float> switchMass;
  vector<string> switchFunc;

  po::options_description desc("Allowed options");
  desc.add_options()
    ("help,h",                                                                                  "Show help")
    ("sigfilename,s", po::value<string>(&sigFileName),                                          "Signal file name")
    ("bkgfilename,b", po::value<string>(&bkgFileName),                                          "Background file name")
    ("sigwsname", po::value<string>(&sigWSName)->default_value("cms_hgg_workspace"),            "Signal workspace name")
    ("bkgwsname", po::value<string>(&bkgWSName)->default_value("cms_hgg_workspace"),            "Background workspace name")
    ("outfilename,o", po::value<string>(&outFileName)->default_value("BiasStudyOut.root"),      "Output file name")
    ("datfile,d", po::value<string>(&datFileName)->default_value("config.dat"),                 "Name of datfile containing pdf info")
    ("outDir,D", po::value<string>(&outDir)->default_value("./"),                               "Name of out directory for plots")
    ("cat,c", po::value<int>(&cat),                                                             "Category")
    ("ntoys,t", po::value<int>(&ntoys)->default_value(0),                                       "Number of toys to run")
    ("jobn,j", po::value<int>(&jobn)->default_value(0),                                         "Job number")
    ("seed,r", po::value<int>(&seed)->default_value(0),                                         "Set random seed")
    ("mulow,L", po::value<float>(&mu_low)->default_value(-3.),                                  "Value of mu to start scan")
    ("muhigh,H", po::value<float>(&mu_high)->default_value(3.),                                 "Value of mu to end scan")
    ("mustep,S", po::value<float>(&mu_step)->default_value(0.01),                               "Value of mu step size")
    ("expectSignal", po::value<float>(&expectSignal)->default_value(0.),                        "Inject signal into toy")
    ("expectSignalMass", po::value<int>(&expectSignalMass)->default_value(125),                 "Inject signal at this mass")
    ("skipPlots",                                                                               "Skip full profile and toy plots")                        
    ("verbosity,v", po::value<int>(&verbosity)->default_value(0),                               "Verbosity level")
  ;    
  
  po::variables_map vm;
  po::store(po::parse_command_line(argc,argv,desc),vm);
  po::notify(vm);
  if (vm.count("help")) { cout << desc << endl; exit(1); }
  if (vm.count("skipPlots")) skipPlots=true;
  if (expectSignalMass!=110 && expectSignalMass!=115 && expectSignalMass!=120 && expectSignalMass!=125 && expectSignalMass!=130 && expectSignalMass!=135 && expectSignalMass!=140 && expectSignalMass!=145 && expectSignalMass!=150){
    cerr << "ERROR - expectSignalMass has to be integer in range (110,150,5)" << endl;
    exit(1);
  }

  vector<pair<int,pair<string,string> > > toysMap;
  vector<pair<int,pair<string,string> > > fabianMap;
  vector<pair<int,pair<string,string> > > paulMap;
  readDatFile(datFileName,cat,toysMap,fabianMap,paulMap);
  
  cout << "Toy vector.." << endl;
  printOptionsMap(toysMap);
  cout << "Fabian vector.." << endl;
  printOptionsMap(fabianMap);
  cout << "Paul vector.." << endl;
  printOptionsMap(paulMap);
  
  TStopwatch sw;
  sw.Start();
 
  if (verbosity<1) {
    RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR);
    RooMsgService::instance().setSilentMode(true);
  }
  
  TFile *bkgFile = TFile::Open(bkgFileName.c_str());
  TFile *sigFile = TFile::Open(sigFileName.c_str());

  //RooWorkspace *bkgWS = (RooWorkspace*)bkgFile->Get("cms_hgg_workspace");
  RooWorkspace *bkgWS = (RooWorkspace*)bkgFile->Get(bkgWSName.c_str());
  RooWorkspace *sigWS = (RooWorkspace*)sigFile->Get(sigWSName.c_str());

  if (!bkgWS || !sigWS){
    cerr << "ERROR - one of signal or background workspace is NULL" << endl;
    exit(1);
  }

  RooRealVar *mass = (RooRealVar*)bkgWS->var("CMS_hgg_mass");
  RooRealVar *mu = new RooRealVar("mu","mu",0.,mu_low,mu_high);

  TFile *outFile = new TFile(outFileName.c_str(),"RECREATE");
  TTree *muTree = new TTree("muTree","muTree");
  int toyn;
  vector<string> truthModel;
  vector<double> muFab;
  vector<double> muPaul;
  vector<double> muChi2;
  vector<double> muAIC;
  vector<double> muFabErrLow;
  vector<double> muPaulErrLow;
  vector<double> muChi2ErrLow;
  vector<double> muAICErrLow;
  vector<double> muFabErrHigh;
  vector<double> muPaulErrHigh;
  vector<double> muChi2ErrHigh;
  vector<double> muAICErrHigh;
  muTree->Branch("jobn",&jobn);
  muTree->Branch("toyn",&toyn);
  muTree->Branch("truthModel",&truthModel);
  muTree->Branch("muFab",&muFab);
  muTree->Branch("muPaul",&muPaul);
  muTree->Branch("muChi2",&muChi2);
  muTree->Branch("muAIC",&muAIC);
  muTree->Branch("muFabErrLow",&muFabErrLow);
  muTree->Branch("muPaulErrLow",&muPaulErrLow);
  muTree->Branch("muChi2ErrLow",&muChi2ErrLow);
  muTree->Branch("muAICErrLow",&muAICErrLow);
  muTree->Branch("muFabErrHigh",&muFabErrHigh);
  muTree->Branch("muPaulErrHigh",&muPaulErrHigh);
  muTree->Branch("muChi2ErrHigh",&muChi2ErrHigh);
  muTree->Branch("muAICErrHigh",&muAICErrHigh);
  
  //TH1F *muDistFab = new TH1F("muDistFab","muDistFab",int(20*(mu_high-mu_low)),mu_low,mu_high);
  //TH1F *muDistPaul = new TH1F("muDistPaul","muDistPaul",int(20*(mu_high-mu_low)),mu_low,mu_high);
  //TH1F *muDistChi2 = new TH1F("muDistChi2","muDistChi2",int(20*(mu_high-mu_low)),mu_low,mu_high);
  //TH1F *muDistAIC = new TH1F("muDistAIC","muDistAIC",int(20*(mu_high-mu_low)),mu_low,mu_high);
  
  mass->setBins(320);
  RooDataSet *data = (RooDataSet*)bkgWS->data(Form("data_mass_cat%d",cat));
  //RooDataSet *data = (RooDataSet*)bkgWS->data(Form("data_cat%d_7TeV",cat));
  RooDataHist *dataBinned = new RooDataHist(Form("roohist_data_mass_cat%d",cat),Form("roohist_data_mass_cat%d",cat),RooArgSet(*mass),*data);
  RooDataSet *sigMC = (RooDataSet*)sigWS->data(Form("sig_ggh_mass_m%d_cat%d",expectSignalMass,cat));
  RooDataSet *sigMC_vbf = (RooDataSet*)sigWS->data(Form("sig_wzh_mass_m%d_cat%d",expectSignalMass,cat));
  RooDataSet *sigMC_wzh = (RooDataSet*)sigWS->data(Form("sig_vbf_mass_m%d_cat%d",expectSignalMass,cat));
  RooDataSet *sigMC_tth = (RooDataSet*)sigWS->data(Form("sig_tth_mass_m%d_cat%d",expectSignalMass,cat));
  sigMC->append(*sigMC_vbf);
  sigMC->append(*sigMC_wzh);
  sigMC->append(*sigMC_tth);
  //RooExtendPdf *ggh_pdf = (RooExtendPdf*)sigWS->pdf(Form("sigpdfsmrel_cat%d_7TeV_ggh",cat));
  //RooExtendPdf *vbf_pdf = (RooExtendPdf*)sigWS->pdf(Form("sigpdfsmrel_cat%d_7TeV_vbf",cat));
  //RooExtendPdf *wzh_pdf = (RooExtendPdf*)sigWS->pdf(Form("sigpdfsmrel_cat%d_7TeV_wzh",cat));
  //RooExtendPdf *tth_pdf = (RooExtendPdf*)sigWS->pdf(Form("sigpdfsmrel_cat%d_7TeV_tth",cat));
  //RooAbsPdf *sigPdf = new RooAddPdf(Form("sigpdfsmrel_cat%d_7TeV",cat),Form("sigpdfsmrel_cat%d_7TeV",cat),RooArgList(*ggh_pdf,*vbf_pdf,*wzh_pdf,*tth_pdf));
  
  if (!dataBinned || !sigMC){
    cerr << "ERROR -- one of data or signal is NULL" << endl;
    exit(1);
  }
  
  // set of truth models to throw toys from
  PdfModelBuilder toysModel;
  toysModel.setObsVar(mass);
  toysModel.setSignalModifier(mu);
  // add truth pdfs from config datfile these need to be cached
  // to throw a toy from the SB fit make sure that the cache happens at makeSBPdfs
  for (vector<pair<int,pair<string,string> > >::iterator it=toysMap.begin(); it!=toysMap.end(); it++){
    if (it->first==-1) { // this is a hyrbid toy
      throwHybridToys=true;
      vector<string> temp;
      split(temp,it->second.first,boost::is_any_of(","));
      split(switchFunc,it->second.second,boost::is_any_of(","));
      for (unsigned int i=0; i<temp.size(); i++){
        switchMass.push_back(atof(temp[i].c_str()));
      }
      continue; 
    }
    if (it->first==-2) { // this is a keys pdf toy
      double rho = lexical_cast<double>(it->second.first);
      toysModel.setKeysPdfAttributes(data,rho);
      toysModel.addBkgPdf("KeysPdf",0,Form("truth_%s_cat%d",it->second.second.c_str(),cat),false);
      continue;
    }
    if (it->first==-3) { // this is read pdf from file
      toysModel.addBkgPdf(it->second.second,it->first,it->second.first,false);
      continue;
    }
    toysModel.addBkgPdf(it->second.second,it->first,Form("truth_%s_cat%d",it->second.first.c_str(),cat),false); 
  }
  toysModel.setSignalPdfFromMC(sigMC);
  //toysModel.setSignalPdf(sigPdf);
  toysModel.makeSBPdfs(true);
  map<string,RooAbsPdf*> toyBkgPdfs = toysModel.getBkgPdfs();
  map<string,RooAbsPdf*> toySBPdfs = toysModel.getSBPdfs();
  toysModel.setSeed(seed);

  // fabians chosen model
  PdfModelBuilder fabianModel;
  fabianModel.setObsVar(mass);
  fabianModel.setSignalModifier(mu);
  // add pdfs from config datfile - should be no need to cache these
  for (vector<pair<int,pair<string,string> > >::iterator it=fabianMap.begin(); it!=fabianMap.end(); it++){
    fabianModel.addBkgPdf(it->second.second,it->first,Form("fabian_%s_cat%d",it->second.first.c_str(),cat),false); 
  }
  fabianModel.setSignalPdfFromMC(sigMC);
  //fabianModel.setSignalPdf(sigPdf);
  fabianModel.makeSBPdfs(false);
  map<string,RooAbsPdf*> fabianBkgPdfs = fabianModel.getBkgPdfs();
  map<string,RooAbsPdf*> fabianSBPdfs = fabianModel.getSBPdfs();

  // set of models to profile 
  PdfModelBuilder paulModel;
  paulModel.setObsVar(mass);
  paulModel.setSignalModifier(mu);
  // add pdfs from config datfile - should be no need to cache these
  for (vector<pair<int,pair<string,string> > >::iterator it=paulMap.begin(); it!=paulMap.end(); it++){
    paulModel.addBkgPdf(it->second.second,it->first,Form("paul_%s_cat%d",it->second.first.c_str(),cat),false); 
  }
  paulModel.setSignalPdfFromMC(sigMC);
  //paulModel.setSignalPdf(sigPdf);
  paulModel.makeSBPdfs(false);
  map<string,RooAbsPdf*> paulBkgPdfs = paulModel.getBkgPdfs();
  map<string,RooAbsPdf*> paulSBPdfs = paulModel.getSBPdfs();

  // set up profile for Fabians models
  ProfileMultiplePdfs fabianProfiler;
  for (map<string,RooAbsPdf*>::iterator pdf=fabianSBPdfs.begin(); pdf!=fabianSBPdfs.end(); pdf++){
    fabianProfiler.addPdf(pdf->second);
  }
  cout << "Fabian profiler pdfs:" << endl;
  fabianProfiler.printPdfs();

  // set up profile for Pauls models
  ProfileMultiplePdfs paulProfiler;
  for (map<string,RooAbsPdf*>::iterator pdf=paulSBPdfs.begin(); pdf!=paulSBPdfs.end(); pdf++){
    paulProfiler.addPdf(pdf->second);
  }
  cout << "Paul profiler pdfs:" << endl;
  paulProfiler.printPdfs();

  if (!skipPlots) {
    system(Form("mkdir -p %s/plots/truthToData",outDir.c_str()));
    system(Form("mkdir -p %s/plots/envelopeNlls",outDir.c_str()));
    system(Form("mkdir -p %s/plots/toys",outDir.c_str()));
  }
  
  // throw toys - only need to fit data once as result will be cached
  cout << "------ FITTING TRUTH TO DATA ------" << endl;
  // sometimes useful to do best fit first to get reasonable starting value
  toysModel.setSignalModifierConstant(false);
  toysModel.fitToData(dataBinned,false,false,true);
  // -----
  toysModel.setSignalModifierVal(expectSignal);
  toysModel.setSignalModifierConstant(true);
  toysModel.fitToData(dataBinned,false,true,true);
  if (!skipPlots) toysModel.plotPdfsToData(dataBinned,80,Form("%s/plots/truthToData/datafit_mu%3.1f",outDir.c_str(),expectSignal),false);
  toysModel.setSignalModifierConstant(false);
  toysModel.saveWorkspace(outFile);
  
  for (int toy=0; toy<ntoys; toy++){
    cout << "---------------------------" << endl;
    cout << "--- RUNNING TOY " << toy << " / " << ntoys << " ----" << endl;
    cout << "---------------------------" << endl;
    // wipe stuff for tree
    truthModel.clear();
    muFab.clear();
    muPaul.clear();
    muChi2.clear();
    muAIC.clear();
    muFabErrLow.clear();
    muPaulErrLow.clear();
    muChi2ErrLow.clear();
    muAICErrLow.clear();
    muFabErrHigh.clear();
    muPaulErrHigh.clear();
    muChi2ErrHigh.clear();
    muAICErrHigh.clear();
    // throw toy
    map<string,RooAbsData*> toys; 
    if (throwHybridToys) {
      toysModel.throwHybridToy(Form("truth_job%d_toy%d",jobn,toy),dataBinned->sumEntries(),switchMass,switchFunc,false,true,true,true);
      toys = toysModel.getHybridToyData();
      if (!skipPlots) toysModel.plotToysWithPdfs(Form("%s/plots/toys/job%d_toy%d",outDir.c_str(),jobn,toy),80,false);
      if (!skipPlots) toysModel.plotHybridToy(Form("%s/plots/toys/job%d_toy%d",outDir.c_str(),jobn,toy),80,switchMass,switchFunc,false);
    }
    else {
      toysModel.throwToy(Form("truth_job%d_toy%d",jobn,toy),dataBinned->sumEntries(),false,true,true,true);
      toys = toysModel.getToyData();
      if (!skipPlots) toysModel.plotToysWithPdfs(Form("%s/plots/toys/job%d_toy%d",outDir.c_str(),jobn,toy),80,false);
    }
    for (map<string,RooAbsData*>::iterator it=toys.begin(); it!=toys.end(); it++){
      // ----- USEFUL DEBUG -----------
      //  --- this can be a useful check that the truth model values are being cached properly ---
      //toysModel.fitToData(it->second,true,false,true);
      //toysModel.plotPdfsToData(it->second,80,Form("%s/plots/toys/job%d_toy%d",outDir.c_str(),jobn,toy),true,"NONE");
      if (!skipPlots) fabianProfiler.plotNominalFits(it->second,mass,80,Form("%s/plots/toys/job%d_toy%d_fit_fab",outDir.c_str(),jobn,toy));
      if (!skipPlots) paulProfiler.plotNominalFits(it->second,mass,80,Form("%s/plots/toys/job%d_toy%d_fit_paul",outDir.c_str(),jobn,toy));
      //continue;
      // --------------------------------
      cout << "Fitting toy for truth model " << distance(toys.begin(),it) << "/" << toys.size() << " (" << it->first << ") " << endl;
      // get Fabian envelope
      pair<double,map<string,TGraph*> > fabianMinNlls = fabianProfiler.profileLikelihood(it->second,mass,mu,mu_low,mu_high,mu_step);
      pair<double,map<string,TGraph*> > fabianEnvelope = fabianProfiler.computeEnvelope(fabianMinNlls,Form("fabEnvelope_job%d_%s_cat%d_toy%d",jobn,it->first.c_str(),cat,toy),0.);
      if (!skipPlots) fabianProfiler.plot(fabianEnvelope.second,Form("%s/plots/envelopeNlls/nlls_fab_%s_cat%d_toy%d",outDir.c_str(),it->first.c_str(),cat,toy));
     
      // get Paul envelopes
      pair<double,map<string,TGraph*> > paulMinNlls = paulProfiler.profileLikelihood(it->second,mass,mu,mu_low,mu_high,mu_step);
      pair<double,map<string,TGraph*> > paulEnvelope = paulProfiler.computeEnvelope(paulMinNlls,Form("paulEnvelope_job%d_%s_cat%d_toy%d",jobn,it->first.c_str(),cat,toy),0.);
      if (!skipPlots) paulProfiler.plot(paulEnvelope.second,Form("%s/plots/envelopeNlls/nlls_paul_%s_cat%d_toy%d",outDir.c_str(),it->first.c_str(),cat,toy));
      pair<double,map<string,TGraph*> > chi2Envelope = paulProfiler.computeEnvelope(paulMinNlls,Form("chi2Envelope_job%d_%s_cat%d_toy%d",jobn,it->first.c_str(),cat,toy),1.);
      if (!skipPlots) paulProfiler.plot(chi2Envelope.second,Form("%s/plots/envelopeNlls/nlls_chi2_%s_cat%d_toy%d",outDir.c_str(),it->first.c_str(),cat,toy));
      pair<double,map<string,TGraph*> > aicEnvelope = paulProfiler.computeEnvelope(paulMinNlls,Form("aicEnvelope_job%d_%s_cat%d_toy%d",jobn,it->first.c_str(),cat,toy),2.);
      if (!skipPlots) paulProfiler.plot(aicEnvelope.second,Form("%s/plots/envelopeNlls/nlls_aic_%s_cat%d_toy%d",outDir.c_str(),it->first.c_str(),cat,toy));
     
      pair<double,pair<double,double> > muFabInfo = ProfileMultiplePdfs::getMinAndErrorAsymm(fabianEnvelope.second["envelope"],1.);
      pair<double,pair<double,double> > muPaulInfo = ProfileMultiplePdfs::getMinAndErrorAsymm(paulEnvelope.second["envelope"],1.);
      pair<double,pair<double,double> > muChi2Info = ProfileMultiplePdfs::getMinAndErrorAsymm(chi2Envelope.second["envelope"],1.);
      pair<double,pair<double,double> > muAICInfo = ProfileMultiplePdfs::getMinAndErrorAsymm(aicEnvelope.second["envelope"],1.);

      truthModel.push_back(it->first);
      muFab.push_back(muFabInfo.first);
      muPaul.push_back(muPaulInfo.first);
      muChi2.push_back(muChi2Info.first);
      muAIC.push_back(muAICInfo.first);
      muFabErrLow.push_back(muFabInfo.second.first);
      muPaulErrLow.push_back(muPaulInfo.second.first);
      muChi2ErrLow.push_back(muChi2Info.second.first);
      muAICErrLow.push_back(muAICInfo.second.first);
      muFabErrHigh.push_back(muFabInfo.second.second);
      muPaulErrHigh.push_back(muPaulInfo.second.second);
      muChi2ErrHigh.push_back(muChi2Info.second.second);
      muAICErrHigh.push_back(muAICInfo.second.second);

      cout << "Fab mu = " << muFabInfo.first << " - " << muFabInfo.second.first << " + " << muFabInfo.second.second << endl;
      cout << "Paul mu = " << muPaulInfo.first << " - " << muPaulInfo.second.first << " + " << muPaulInfo.second.second << endl;
      cout << "Chi2 mu = " << muChi2Info.first << " - " << muChi2Info.second.first << " + " << muChi2Info.second.second << endl;
      cout << "AIC mu = " << muAICInfo.first << " - " << muAICInfo.second.first << " + " << muAICInfo.second.second << endl;

      outFile->cd();
      fabianEnvelope.second["envelope"]->Write();
      paulEnvelope.second["envelope"]->Write();
      chi2Envelope.second["envelope"]->Write();
      aicEnvelope.second["envelope"]->Write();
    }
    toyn=toy;
    muTree->Fill();
  }

  outFile->cd();
  muTree->Write();
  cout << "Done." << endl;
  cout << "Whole process took..." << endl;
  cout << "\t "; sw.Print();
 
  outFile->Close();

  return 0;
}
int main (int argc, char **argv) {

  TFile *tf = TFile::Open("tmp/DataSets.root");
  RooWorkspace *w = (RooWorkspace*)tf->Get("w");

  RooDataSet *Data = (RooDataSet*)w->data("Data2011")->Clone("Data");
  Data->append( *((RooDataSet*)w->data("Data2012")) );

  RooDataSet *Bs2Kst0Kst0_MC = (RooDataSet*)w->data("Bs2Kst0Kst0_MC2011")->Clone("Bs2KstKst0_MC");
  Bs2Kst0Kst0_MC->append( *((RooDataSet*)w->data("Bs2Kst0Kst0_MC2012")) );

  RooDataSet *Bs2Kst0Kst01430_MC = (RooDataSet*)w->data("Bs2Kst0Kst01430_MC2011")->Clone("Bs2KstKst0_MC");
  Bs2Kst0Kst01430_MC->append( *((RooDataSet*)w->data("Bs2Kst0Kst01430_MC2012")) );

  RooDataSet *Bs2Kst01430Kst01430_MC = (RooDataSet*)w->data("Bs2Kst01430Kst01430_MC2011")->Clone("Bs2KstKst0_MC");
  Bs2Kst01430Kst01430_MC->append( *((RooDataSet*)w->data("Bs2Kst01430Kst01430_MC2012")) );

  RooDataSet *Bd2Kst0Kst0_MC = (RooDataSet*)w->data("Bd2Kst0Kst0_MC2011")->Clone("Bs2KstKst0_MC");
  Bd2Kst0Kst0_MC->append( *((RooDataSet*)w->data("Bd2Kst0Kst0_MC2012")) );

  RooDataSet *Bd2PhiKst0_MC = (RooDataSet*)w->data("Bd2PhiKst0_MC2011")->Clone("Bs2KstKst0_MC");
  Bd2PhiKst0_MC->append( *((RooDataSet*)w->data("Bd2PhiKst0_MC2012")) );

  RooDataSet *Bs2PhiKst0_MC = (RooDataSet*)w->data("Bs2PhiKst0_MC2011")->Clone("Bs2KstKst0_MC");
  Bs2PhiKst0_MC->append( *((RooDataSet*)w->data("Bs2PhiKst0_MC2012")) );

  RooDataSet *Bd2RhoKst0_MC = (RooDataSet*)w->data("Bd2RhoKst0_MC2011")->Clone("Bs2KstKst0_MC");
  Bd2RhoKst0_MC->append( *((RooDataSet*)w->data("Bd2RhoKst0_MC2012")) );

  RooDataSet *Lb2ppipipi_MC = (RooDataSet*)w->data("Lb2ppipipi_MC2011")->Clone("Bs2KstKst0_MC");
  Lb2ppipipi_MC->append( *((RooDataSet*)w->data("Lb2ppipipi_MC2012")) );

  RooDataSet *Lb2pKpipi_MC = (RooDataSet*)w->data("Lb2pKpipi_MC2011")->Clone("Bs2KstKst0_MC");
  Lb2pKpipi_MC->append( *((RooDataSet*)w->data("Lb2pKpipi_MC2012")) );


  w->import(*Data);
  w->import(*Bs2Kst0Kst0_MC);
  w->import(*Bs2Kst0Kst01430_MC);
  w->import(*Bs2Kst01430Kst01430_MC);
  w->import(*Bd2Kst0Kst0_MC);
  w->import(*Bd2PhiKst0_MC);
  w->import(*Bs2PhiKst0_MC);
  w->import(*Bd2RhoKst0_MC);
  w->import(*Lb2ppipipi_MC);
  w->import(*Lb2pKpipi_MC);

  RooRealVar *mass = (RooRealVar*)w->var("B_s0_DTF_B_s0_M");

  fitIpatia( w, "bs2kstkst_mc", "Bs2KstKst0_MC");

  // Make the PDF here
  RooRealVar *p1 = new RooRealVar("p1","p1",-0.002,-0.004,0.);
  RooExponential *exp = new RooExponential("exp","exp",*mass,*p1);
  //RooRealVar *m1 = new RooRealVar("m1","m1",5320,5380);
  //RooRealVar *s1 = new RooRealVar("s1","s1",1,20);
  //RooGaussian *sig = new RooGaussian("sig","sig",*mass,*m1,*s1);
  RooRealVar *m2 = new RooRealVar("m2","m2",5320,5380);
  RooRealVar *s2 = new RooRealVar("s2","s2",1,20);
  RooGaussian *sig_bd = new RooGaussian("sig_bd","sig_bd",*mass,*m2,*s2);

  //
  RooRealVar *bs2kstkst_l       = new RooRealVar( "bs2kstkst_l"    ,"", -5, -20, -1.);
  RooConstVar *bs2kstkst_zeta   = new RooConstVar( "bs2kstkst_zeta","",0.              );
  RooConstVar *bs2kstkst_fb     = new RooConstVar( "bs2kstkst_fb"  ,"",0.              );
  RooRealVar *bs2kstkst_sigma   = new RooRealVar( "bs2kstkst_sigma","",15    ,10   ,20 );
  RooRealVar *bs2kstkst_mu      = new RooRealVar( "bs2kstkst_mu"   ,"",5350  ,5380     );
  RooRealVar *bs2kstkst_a       = new RooRealVar( "bs2kstkst_a"    ,"",2.5  , 0    ,10 );
  RooRealVar *bs2kstkst_n       = new RooRealVar( "bs2kstkst_n"    ,"",2.5  , 0    ,10 );
  RooRealVar *bs2kstkst_a2      = new RooRealVar( "bs2kstkst_a2"   ,"",2.5  , 0    ,10 );
  RooRealVar *bs2kstkst_n2      = new RooRealVar( "bs2kstkst_n2"   ,"",2.5  , 0    ,10 );

  RooIpatia2 *sig = new RooIpatia2("sig","sig",*mass,*bs2kstkst_l,*bs2kstkst_zeta,*bs2kstkst_fb,*bs2kstkst_sigma,*bs2kstkst_mu,*bs2kstkst_a,*bs2kstkst_n,*bs2kstkst_a2,*bs2kstkst_n2);

  RooRealVar *bkg_y = new RooRealVar("bkg_y","bkg_y",10e3,10e5);
  RooRealVar *sig_y = new RooRealVar("sig_y","sig_y",0,20e3);
  RooRealVar *sig_bd_y = new RooRealVar("sig_bd_y","sig_bd_y",0,3000);

  RooArgList *pdfs = new RooArgList();
  RooArgList *yields = new RooArgList();

  pdfs->add( *exp );
  pdfs->add( *sig );
  pdfs->add( *sig_bd );

  yields->add( *bkg_y );
  yields->add( *sig_y );
  yields->add( *sig_bd_y );

  RooAddPdf *pdf = new RooAddPdf("pdf","pdf",*pdfs,*yields);

  pdf->fitTo(*Data, Extended() );

  RooPlot *plot = mass->frame();
  Data->plotOn(plot);
    // set fit params constant;
  pdf->plotOn(plot);

  TCanvas *c = new TCanvas();
  plot->Draw();
  c->Print("tmp/mass.pdf");

  // Plots Kst Ms with no sweights
  TCanvas *c1 = new TCanvas("c1","c1",800,1200);
  c1->Divide(1,2);
  c1->cd(1);
  RooPlot *c1p1 = w->var("B_s0_DTF_KST1_M")->frame();
  Data->plotOn(c1p1);
  c1p1->Draw();
  c1->cd(2);
  RooPlot *c1p2 = w->var("B_s0_DTF_KST2_M")->frame();
  Data->plotOn(c1p2);
  c1p2->Draw();
  c1->Print("tmp/nosw.pdf");

  // set fit params constant
  p1->setConstant(true);
  //m1->setConstant(true);
  //s1->setConstant(true);
  bs2kstkst_l->setConstant(true);
  //bs2kstkst_zeta->setConstant(true);
  //bs2kstkst_fb->setConstant(true);
  bs2kstkst_sigma->setConstant(true);
  bs2kstkst_mu->setConstant(true);
  bs2kstkst_a->setConstant(true);
  bs2kstkst_n->setConstant(true);
  bs2kstkst_a2->setConstant(true);
  bs2kstkst_n2->setConstant(true);
  m2->setConstant(true);
  s2->setConstant(true);

  RooStats::SPlot *sData = new RooStats::SPlot("sData","sData", *Data, pdf, *yields);

  w->import(*sData);
  w->import(*Data,Rename("Data_wsweights"));

  RooDataSet *swdata = new RooDataSet("Data_wsweights", "Data", Data, *Data->get(), 0 , "sig_y_sw");
  // Plots Kst Ms with no sweights
  TCanvas *c2 = new TCanvas("c2","c2",800,1200);
  c2->Divide(1,2);
  c2->cd(1);
  RooPlot *c2p1 = w->var("B_s0_DTF_KST1_M")->frame();
  swdata->plotOn(c2p1);
  c2p1->Draw();
  c2->cd(2);
  RooPlot *c2p2 = w->var("B_s0_DTF_KST2_M")->frame();
  swdata->plotOn(c2p2);
  c2p2->Draw();
  c2->Print("tmp/withsw.pdf");


  tf->Close();
  return 0;
}
Exemplo n.º 5
0
void fitbkgdataCard(TString configCard="template.config", 
		    bool dobands  = true,  // create baerror bands for BG models
		    bool dosignal = false, // plot the signal model (needs to be present)
		    bool blinded  = true,  // blind the data in the plots?
		    bool verbose  = true  ) {
  
  gROOT->Macro("MitStyle.C");
  gStyle->SetErrorX(0); 
  gStyle->SetOptStat(0);
  gROOT->ForceStyle();  
  
  TString projectDir;

  std::vector<TString> catdesc;
  std::vector<TString> catnames;  
  std::vector<int>     polorder;

  double massmin = -1.;
  double massmax = -1.;

  double theCMenergy = -1.;

  bool readStatus = readFromConfigCard( configCard,
					projectDir,
					catnames,
					catdesc,
					polorder,
					massmin,
					massmax,
					theCMenergy
					);
  
  if( !readStatus ) {
    std::cerr<<" ERROR: Could not read from card > "<<configCard.Data()<<" <."<<std::endl;
    return;
  }
  
  TFile *fdata = new TFile(TString::Format("%s/CMS-HGG-data.root",projectDir.Data()),"READ");
  if( !fdata ) {
    std::cerr<<" ERROR: Could not open file "<<projectDir.Data()<<"/CMS-HGG-data.root."<<std::endl;
    return;
  }
  
  if( !gSystem->cd(TString::Format("%s/databkg/",projectDir.Data())) ) {
    std::cerr<<" ERROR: Could not change directory to "<<TString::Format("%s/databkg/",projectDir.Data()).Data()<<"."<<std::endl;
    return;
  }
  
  // ----------------------------------------------------------------------
  // load the input workspace....
  RooWorkspace* win = (RooWorkspace*)fdata->Get("cms_hgg_workspace_data");
  if( !win ) {
    std::cerr<<" ERROR: Could not load workspace > cms_hgg_workspace_data < from file > "<<TString::Format("%s/CMS-HGG-data.root",projectDir.Data()).Data()<<" <."<<std::endl;
    return;
  }

  RooRealVar *intLumi = win->var("IntLumi");
  RooRealVar *hmass   = win->var("CMS_hgg_mass");
  if( !intLumi || !hmass ) {
    std::cerr<<" ERROR: Could not load needed variables > IntLumi < or > CMS_hgg_mass < forom input workspace."<<std::endl;
    return;
  }

  //win->Print();

  hmass->setRange(massmin,massmax);
  hmass->setBins(4*(int)(massmax-massmin));
  hmass->SetTitle("m_{#gamma#gamma}");
  hmass->setUnit("GeV");
  hmass->setRange("fitrange",massmin,massmax);

  hmass->setRange("blind1",100.,110.);
  hmass->setRange("blind2",150.,180.);
  
  // ----------------------------------------------------------------------
  // some auxiliray vectro (don't know the meaning of all of them ... yet...
  std::vector<RooAbsData*> data_vec;
  std::vector<RooAbsPdf*>  pdfShape_vec;   // vector to store the NOT-EXTENDED PDFs (aka pdfshape)
  std::vector<RooAbsPdf*>  pdf_vec;        // vector to store the EXTENDED PDFs
  
  std::vector<RooAbsReal*> normu_vec;      // this holds the normalization vars for each Cat (needed in bands for combined cat)

  RooArgList               normList;       // list of range-limityed normalizations (needed for error bands on combined category)

  //std::vector<RooRealVar*> coeffv;
  //std::vector<RooAbsReal*> normu_vecv; // ???

  // ----------------------------------------------------------------------
  // define output works
  RooWorkspace *wOut = new RooWorkspace("wbkg","wbkg") ;
  
  // util;ities for the combined fit
  RooCategory     finalcat  ("finalcat",  "finalcat") ;  
  RooSimultaneous fullbkgpdf("fullbkgpdf","fullbkgpdf",finalcat);
  RooDataSet      datacomb  ("datacomb",  "datacomb",  RooArgList(*hmass,finalcat)) ;

  RooDataSet *datacombcat = new RooDataSet("data_combcat","",RooArgList(*hmass)) ;
  
  // add the 'combcat' to the list...if more than one cat
  if( catnames.size() > 1 ) {
    catnames.push_back("combcat");    
    catdesc.push_back("Combined");
  }
  
  for (UInt_t icat=0; icat<catnames.size(); ++icat) {
    TString catname = catnames.at(icat);
    finalcat.defineType(catname);
    
    // check if we're in a sub-cat or the comb-cat
    RooDataSet *data   = NULL;
    RooDataSet *inData = NULL;
    if( icat < (catnames.size() - 1) || catnames.size() == 1) { // this is NOT the last cat (which is by construction the combination)
      inData = (RooDataSet*)win->data(TString("data_mass_")+catname);
      if( !inData ) {
	std::cerr<<" ERROR: Could not find dataset > data_mass_"<<catname.Data()<<" < in input workspace."<<std::endl;
	return;
      }
      data = new RooDataSet(TString("data_")+catname,"",*hmass,Import(*inData));  // copy the dataset (why?)
      
      // append the data to the combined data...
      RooDataSet *datacat = new RooDataSet(TString("datacat")+catname,"",*hmass,Index(finalcat),Import(catname,*data)) ;
      datacomb.append(*datacat);
      datacombcat->append(*data);
      
      // normalization for this category
      RooRealVar *nbkg = new RooRealVar(TString::Format("CMS_hgg_%s_bkgshape_norm",catname.Data()),"",800.0,0.0,25e3);
      
      // we keep track of the normalizario vars only for N-1 cats, naming convetnions hystoric...
      if( catnames.size() > 2 && icat < (catnames.size() - 2) ) {
	RooRealVar* cbkg = new RooRealVar(TString::Format("cbkg%s",catname.Data()),"",0.0,0.0,1e3);
	cbkg->removeRange();
	normu_vec.push_back(cbkg);
	normList.add(*cbkg);
      }
      
      /// generate the Bernstrin polynomial (FIX-ME: add possibility ro create other models...)
      fstBernModel* theBGmodel = new fstBernModel(hmass, polorder[icat], icat, catname);            // using my dedicated class...
      
      std::cout<<" model name is "<<theBGmodel->getPdf()->GetName()<<std::endl;

      RooAbsPdf*    bkgshape   = theBGmodel->getPdf();                                              // the BG shape
      RooAbsPdf*    bkgpdf     = new RooExtendPdf(TString("bkgpdf")+catname,"",*bkgshape,*nbkg);    // the extended PDF
      
      // add the extedned PDF to the RooSimultaneous holding all models...
      fullbkgpdf.addPdf(*bkgpdf,catname);
      // store the NON-EXTENDED PDF for usgae to compute the error bands later..
      pdfShape_vec.push_back(bkgshape);
      pdf_vec     .push_back(bkgpdf);
      data_vec    .push_back(data);
      
    } else {
      data = datacombcat;   // we're looking at the last cat (by construction the combination)
      data_vec.push_back(data);
      
      // sum up all the cts PDFs for combined PDF
      RooArgList subpdfs;
      for (int ipdf=0; ipdf<pdf_vec.size(); ++ipdf) {
	subpdfs.add(*pdf_vec.at(ipdf));
      }
      RooAddPdf* bkgpdf = new RooAddPdf(TString("bkgpdf")+catname,"",subpdfs);
      pdfShape_vec.push_back(bkgpdf);      
      pdf_vec     .push_back(bkgpdf);  // I don't think this is really needed though....
    }
    
    // generate the binned dataset (to be put into the workspace... just in case...)
    RooDataHist *databinned = new RooDataHist(TString("databinned_")+catname,"",*hmass,*data);
    
    wOut->import(*data);
    wOut->import(*databinned);

  }
  
  std::cout<<" ***************** "<<std::endl;

  // fit the RooSimultaneous to the combined dataset -> (we could also fit each cat separately)
  fullbkgpdf.fitTo(datacomb,Strategy(1),Minos(kFALSE),Save(kTRUE));
  RooFitResult *fullbkgfitres = fullbkgpdf.fitTo(datacomb,Strategy(2),Minos(kFALSE),Save(kTRUE));
  
  // in principle we're done now, so store the results in the output workspace
  wOut->import(datacomb);  
  wOut->import(fullbkgpdf);
  wOut->import(*fullbkgfitres);

  std::cout<<" ***************** "<<std::endl;
  

  if( verbose ) wOut->Print();

  
  std::cout<<" ***************** "<<std::endl;

  wOut->writeToFile("bkgdatawithfit.root") ;  
  
  if( verbose ) {
    printf("IntLumi = %5f\n",intLumi->getVal());
    printf("ndata:\n");
    for (UInt_t icat=0; icat<catnames.size(); ++icat) {    
      printf("%i ",data_vec.at(icat)->numEntries());      
    }   
    printf("\n");
  } 
  
  // --------------------------------------------------------------------------------------------
  // Now comesd the plotting
  // chage the Statistics style...
  gStyle->SetOptStat(1110);
  
  // we want to plot in 1GeV bins (apparently...)
  UInt_t nbins = (UInt_t) (massmax-massmin);
  
  // here we'll store the curves for the bands...
  std::vector<RooCurve*> fitcurves;
  
  // loop again over the cats
  TCanvas **canbkg = new TCanvas*[catnames.size()];
  RooPlot** plot   = new RooPlot*[catnames.size()];

  TLatex** lat  = new TLatex*[catnames.size()];
  TLatex** lat2 = new TLatex*[catnames.size()];

  std::cout<<"  beofre plotting..."<<std::endl;
  

  for (UInt_t icat=0; icat<catnames.size(); ++icat) {
    TString catname = catnames.at(icat);
    

    std::cout<<" trying to plot #"<<icat<<std::endl;

    // plot the data and the fit 
    canbkg[icat] = new TCanvas;
    plot  [icat] = hmass->frame(Bins(nbins),Range("fitrange"));
    
    std::cout<<" trying to plot #"<<icat<<std::endl;

    // first plot the data invisibly... and put the fitted BG model on top...
    data_vec    .at(icat)->plotOn(plot[icat],RooFit::LineColor(kWhite),MarkerColor(kWhite),Invisible());
    pdfShape_vec.at(icat)->plotOn(plot[icat],RooFit::LineColor(kRed),Range("fitrange"),NormRange("fitrange"));
    
    std::cout<<" trying to plot #"<<icat<<std::endl;


    // if toggled on, plot also the Data visibly
    if( !blinded ) {
      data_vec.at(icat)->plotOn(plot[icat]);
    }
   
    std::cout<<" trying to plot #"<<icat<<std::endl;

    // some cosmetics...
    plot[icat]->SetTitle("");      
    plot[icat]->SetMinimum(0.0);
    plot[icat]->SetMaximum(1.40*plot[icat]->GetMaximum());
    plot[icat]->GetXaxis()->SetTitle("m_{#gamma#gamma} (GeV/c^{2})");
    plot[icat]->Draw();       
            

    std::cout<<" trying to plot #"<<icat<<std::endl;

    // legend....
    TLegend *legmc = new TLegend(0.68,0.70,0.97,0.90);
    legmc->AddEntry(plot[icat]->getObject(2),"Data","LPE");
    legmc->AddEntry(plot[icat]->getObject(1),"Bkg Model","L");
    
    // this part computes the 1/2-sigma bands.    
    TGraphAsymmErrors *onesigma = NULL;
    TGraphAsymmErrors *twosigma = NULL;
    
    std::cout<<" trying ***  to plot #"<<icat<<std::endl;

    RooAddition* sumcatsnm1 = NULL;

    if ( dobands ) { //&& icat == (catnames.size() - 1) ) {

      onesigma = new TGraphAsymmErrors();
      twosigma = new TGraphAsymmErrors();

      // get the PDF for this cat from the vector
      RooAbsPdf *thisPdf = pdfShape_vec.at(icat); 

      // get the nominal fir curve
      RooCurve *nomcurve = dynamic_cast<RooCurve*>(plot[icat]->getObject(1));
      fitcurves.push_back(nomcurve);

      bool iscombcat       = ( icat == (catnames.size() - 1) && catnames.size() > 1);
      RooAbsData *datanorm = ( iscombcat ? &datacomb : data_vec.at(icat) );

      // this si the nornmalization in the 'sliding-window' (i.e. per 'test-bin')
      RooRealVar *nlim = new RooRealVar(TString::Format("nlim%s",catnames.at(icat).Data()),"",0.0,0.0,10.0);
      nlim->removeRange();

      if( iscombcat ) {
	// ----------- HISTORIC NAMING  ----------------------------------------
	sumcatsnm1 = new RooAddition("sumcatsnm1","",normList);   // summing all normalizations epect the last Cat
	// this is the normlization of the last Cat
	RooFormulaVar *nlast = new RooFormulaVar("nlast","","TMath::Max(0.1,@0-@1)",RooArgList(*nlim,*sumcatsnm1));
	// ... and adding it ot the list of norms
	normu_vec.push_back(nlast);
      }

      //if (icat == 1 && catnames.size() == 2) continue; // only 1 cat, so don't need combination

      for (int i=1; i<(plot[icat]->GetXaxis()->GetNbins()+1); ++i) {
	
	// this defines the 'binning' we use for the error bands
        double lowedge = plot[icat]->GetXaxis()->GetBinLowEdge(i);
        double upedge = plot[icat]->GetXaxis()->GetBinUpEdge(i);
        double center = plot[icat]->GetXaxis()->GetBinCenter(i);
        
	// get the nominal value at the center of the bin
        double nombkg = nomcurve->interpolate(center);
        nlim->setVal(nombkg);
        hmass->setRange("errRange",lowedge,upedge);

	// this is the new extended PDF whith the normalization restricted to the bin-area
        RooAbsPdf *extLimPdf = NULL;
	if( iscombcat ) {
	  extLimPdf = new RooSimultaneous("epdf","",finalcat);
	  // loop over the cats and generate temporary extended PDFs
	  for (int jcat=0; jcat<(catnames.size()-1); ++jcat) {
            RooRealVar *rvar = dynamic_cast<RooRealVar*>(normu_vec.at(jcat));
            if (rvar) rvar->setVal(fitcurves.at(jcat)->interpolate(center));
            RooExtendPdf *ecpdf = new RooExtendPdf(TString::Format("ecpdf%s",catnames.at(jcat).Data()),"",*pdfShape_vec.at(jcat),*normu_vec.at(jcat),"errRange");
            static_cast<RooSimultaneous*>(extLimPdf)->addPdf(*ecpdf,catnames.at(jcat));
          }
	} else
	  extLimPdf = new RooExtendPdf("extLimPdf","",*thisPdf,*nlim,"errRange");

        RooAbsReal *nll = extLimPdf->createNLL(*datanorm,Extended(),NumCPU(1));
        RooMinimizer minim(*nll);
        minim.setStrategy(0);
        double clone = 1.0 - 2.0*RooStats::SignificanceToPValue(1.0);
        double cltwo = 1.0 - 2.0*RooStats::SignificanceToPValue(2.0);
	
        if (iscombcat) minim.setStrategy(2);
        
        minim.migrad();
	
        if (!iscombcat) { 
          minim.minos(*nlim);
        }
        else {
          minim.hesse();
          nlim->removeAsymError();
        }

	if( verbose ) 
	  printf("errlo = %5f, errhi = %5f\n",nlim->getErrorLo(),nlim->getErrorHi());
        
        onesigma->SetPoint(i-1,center,nombkg);
        onesigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());
        
	// to get the 2-sigma bands...
        minim.setErrorLevel(0.5*pow(ROOT::Math::normal_quantile(1-0.5*(1-cltwo),1.0), 2)); // the 0.5 is because qmu is -2*NLL
                          // eventually if cl = 0.95 this is the usual 1.92!      
        
        if (!iscombcat) { 
          minim.migrad();
          minim.minos(*nlim);
        }
        else {
          nlim->setError(2.0*nlim->getError());
          nlim->removeAsymError();          
        }
	
        twosigma->SetPoint(i-1,center,nombkg);
        twosigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());      
        
        // for memory clean-up
        delete nll;
        delete extLimPdf;
      }
      
      hmass->setRange("errRange",massmin,massmax);

      if( verbose )
	onesigma->Print("V");
      
      // plot[icat] the error bands
      twosigma->SetLineColor(kGreen);
      twosigma->SetFillColor(kGreen);
      twosigma->SetMarkerColor(kGreen);
      twosigma->Draw("L3 SAME");     
      
      onesigma->SetLineColor(kYellow);
      onesigma->SetFillColor(kYellow);
      onesigma->SetMarkerColor(kYellow);
      onesigma->Draw("L3 SAME");
      
      plot[icat]->Draw("SAME");
    
      // and add the error bands to the legend
      legmc->AddEntry(onesigma,"#pm1 #sigma","F");  
      legmc->AddEntry(twosigma,"#pm2 #sigma","F");  
    }
    
    std::cout<<" trying ***2  to plot #"<<icat<<std::endl;

    // rest of the legend ....
    legmc->SetBorderSize(0);
    legmc->SetFillStyle(0);
    legmc->Draw();   

    lat[icat]  = new TLatex(103.0,0.9*plot[icat]->GetMaximum(),TString::Format("#scale[0.7]{#splitline{CMS preliminary}{#sqrt{s} = %.1f TeV L = %.2f fb^{-1}}}",theCMenergy,intLumi->getVal()));
    lat2[icat] = new TLatex(103.0,0.75*plot[icat]->GetMaximum(),catdesc.at(icat));

    lat[icat] ->Draw();
    lat2[icat]->Draw();
    
    // -------------------------------------------------------    
    // save canvas in different formats
    canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".pdf"));
    canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".eps"));
    canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".root"));              
  }
  
  return;
  
}
int main(){
  
  system("mkdir -p plots");
  RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR);
  TFile *bkgFile = TFile::Open("comb_svn/hgg.inputbkgdata_8TeV_MVA.root");
  TFile *sigFile = TFile::Open("comb_svn/hgg.inputsig_8TeV_nosplitVH_MVA.root");
  RooWorkspace *bkgWS = (RooWorkspace*)bkgFile->Get("cms_hgg_workspace");
  RooWorkspace *sigWS = (RooWorkspace*)sigFile->Get("wsig_8TeV");

  RooRealVar *mass = (RooRealVar*)bkgWS->var("CMS_hgg_mass");
  RooRealVar *mu = new RooRealVar("mu","mu",-5.,5.);

  mass->setBins(320);
  cout << mass->getBins() << endl;
  RooDataSet *dataAll;
  
  int firstCat=1;
  int lastCat=1;
  float mu_low=-1.;
  float mu_high=3.;
  float mu_step=0.01;

  vector<pair<double,TGraph*> > minNlltrack;

  for (int cat=firstCat; cat<=lastCat; cat++){
    RooDataSet *data = (RooDataSet*)bkgWS->data(Form("data_mass_cat%d",cat));
    if (cat==firstCat) dataAll = (RooDataSet*)data->Clone("data_mass_all");
    else dataAll->append(*data);
    RooDataHist *dataBinned = new RooDataHist(Form("roohist_data_mass_cat%d",cat),Form("roohist_data_mass_cat%d",cat),RooArgSet(*mass),*data);
    RooDataSet *sigMC = (RooDataSet*)sigWS->data(Form("sig_mass_m125_cat%d",cat));

    if (!dataBinned || !sigMC){
      cerr << "ERROR -- one of data or signal is NULL" << endl;
      exit(1);
    }
    
    // Construct PDFs for this category using PdfModelBuilder
    PdfModelBuilder modelBuilder;
    modelBuilder.setObsVar(mass);
    modelBuilder.setSignalModifier(mu);
    // For Standard Analysis
    //if (cat>=0 && cat<=3) modelBuilder.addBkgPdf("Bernstein",5,Form("pol5_cat%d",cat));
    //if (cat>=4 && cat<=5) modelBuilder.addBkgPdf("Bernstein",4,Form("pol4_cat%d",cat));
    //if (cat>=6 && cat<=8) modelBuilder.addBkgPdf("Bernstein",3,Form("pol3_cat%d",cat));
    // To Profile Multiple PDFs
    if (cat==0 || cat==1 || cat==2 || cat==3){
      modelBuilder.addBkgPdf("Bernstein",4,Form("pol4_cat%d",cat));
      modelBuilder.addBkgPdf("Bernstein",5,Form("pol5_cat%d",cat));
      modelBuilder.addBkgPdf("Bernstein",6,Form("pol6_cat%d",cat));
      /*
      modelBuilder.addBkgPdf("PowerLaw",1,Form("pow1_cat%d",cat));
      modelBuilder.addBkgPdf("PowerLaw",3,Form("pow3_cat%d",cat));
      modelBuilder.addBkgPdf("PowerLaw",5,Form("pow5_cat%d",cat));
      modelBuilder.addBkgPdf("Exponential",1,Form("exp1_cat%d",cat));
      modelBuilder.addBkgPdf("Exponential",3,Form("exp3_cat%d",cat));
      modelBuilder.addBkgPdf("Exponential",5,Form("exp5_cat%d",cat));
      modelBuilder.addBkgPdf("Laurent",1,Form("lau1_cat%d",cat));
      modelBuilder.addBkgPdf("Laurent",3,Form("lau3_cat%d",cat));
      modelBuilder.addBkgPdf("Laurent",5,Form("lau5_cat%d",cat));
      */
    }
    if (cat==4 || cat==5 || cat==6 || cat==7 || cat==8) {
      modelBuilder.addBkgPdf("Bernstein",3,Form("pol3_cat%d",cat));
      modelBuilder.addBkgPdf("Bernstein",4,Form("pol4_cat%d",cat));
      /*
      modelBuilder.addBkgPdf("PowerLaw",1,Form("pow1_cat%d",cat));
      modelBuilder.addBkgPdf("PowerLaw",3,Form("pow3_cat%d",cat));
      modelBuilder.addBkgPdf("Exponential",1,Form("exp1_cat%d",cat));
      modelBuilder.addBkgPdf("Exponential",3,Form("exp3_cat%d",cat));
      modelBuilder.addBkgPdf("Laurent",1,Form("lau1_cat%d",cat));
      modelBuilder.addBkgPdf("Laurent",3,Form("lau3_cat%d",cat));
      */
    }
    map<string,RooAbsPdf*> bkgPdfs = modelBuilder.getBkgPdfs();
    modelBuilder.setSignalPdfFromMC(sigMC);
    modelBuilder.makeSBPdfs();
    map<string,RooAbsPdf*> sbPdfs = modelBuilder.getSBPdfs();

    modelBuilder.fitToData(dataBinned,true,true);
    modelBuilder.fitToData(dataBinned,false,true);

    modelBuilder.throwToy(Form("cat%d_toy0",cat),dataBinned->sumEntries(),true,true);

    // Profile this category using ProfileMultiplePdfs
    ProfileMultiplePdfs profiler;
    for (map<string,RooAbsPdf*>::iterator pdf=sbPdfs.begin(); pdf!=sbPdfs.end(); pdf++) {
      string bkgOnlyName = pdf->first.substr(pdf->first.find("sb_")+3,string::npos);
      if (bkgPdfs.find(bkgOnlyName)==bkgPdfs.end()){
        cerr << "ERROR -- couldn't find bkg only pdf " << bkgOnlyName << " for SB pdf " << pdf->first << endl;
        pdf->second->fitTo(*dataBinned);
        exit(1);
      }
      int nParams = bkgPdfs[bkgOnlyName]->getVariables()->getSize()-1;
      profiler.addPdf(pdf->second,2*nParams);
      //profiler.addPdf(pdf->second);
      cout << pdf->second->GetName() << " nParams=" << pdf->second->getVariables()->getSize() << " nBkgParams=" << nParams << endl;
    }
    profiler.printPdfs();
    //cout << "Continue?" << endl;
    //string bus; cin >> bus;
    profiler.plotNominalFits(dataBinned,mass,80,Form("cat%d",cat));
    pair<double,map<string,TGraph*> > minNlls = profiler.profileLikelihood(dataBinned,mass,mu,mu_low,mu_high,mu_step);
    pair<double,map<string,TGraph*> > correctedNlls = profiler.computeEnvelope(minNlls,Form("cat%d",cat),2.);
    minNlltrack.push_back(make_pair(correctedNlls.first,correctedNlls.second["envelope"]));
    //minNlls.second.insert(pair<string,TGraph*>("envelope",envelopeNll.second));
    //map<string,TGraph*> minNLLs = profiler.profileLikelihoodEnvelope(dataBinned,mu,mu_low,mu_high,mu_step);
    profiler.plot(correctedNlls.second,Form("cat%d_nlls",cat));
    //profiler.print(minNLLs,mu_low,mu_high,mu_step);
    /*
    if (minNLLs.find("envelope")==minNLLs.end()){
      cerr << "ERROR -- envelope TGraph not found in minNLLs" << endl;
      exit(1);
    }
    */
    //minNlltrack.push_back(make_pair(profiler.getGlobalMinNLL(),minNLLs["envelope"]));
  }
  //exit(1);
  TGraph *comb = new TGraph();
  for (vector<pair<double,TGraph*> >::iterator it=minNlltrack.begin(); it!=minNlltrack.end(); it++){
    if (it->second->GetN()!=minNlltrack.begin()->second->GetN()){
      cerr << "ERROR -- unequal number of points for TGraphs " << it->second->GetName() << " and " << minNlltrack.begin()->second->GetName() << endl;
      exit(1);
    }
  }
  for (int p=0; p<minNlltrack.begin()->second->GetN(); p++){
    double x,y,sumy=0;
    for (vector<pair<double,TGraph*> >::iterator it=minNlltrack.begin(); it!=minNlltrack.end(); it++){
      it->second->GetPoint(p,x,y);
      sumy += (y+it->first);
    }
    comb->SetPoint(p,x,sumy);
  }
  pair<double,double> globalMin = getGraphMin(comb);
  for (int p=0; p<comb->GetN(); p++){
    double x,y;
    comb->GetPoint(p,x,y);
    comb->SetPoint(p,x,y-globalMin.second);
  }
  vector<double> fitVal = getValsFromLikelihood(comb);

  cout << "Best fit.." << endl;
  cout << "\t mu = " << Form("%4.3f",fitVal[0]) << " +/- (1sig) = " << fitVal[2]-fitVal[0] << " / " << fitVal[0]-fitVal[1] << endl;
  cout << "\t      " << "    " << " +/- (2sig) = " << fitVal[4]-fitVal[0] << " / " << fitVal[0]-fitVal[3] << endl;

  cout << comb->Eval(fitVal[0]) << " " << comb->Eval(fitVal[1]) << " " << comb->Eval(fitVal[2]) << " " << comb->Eval(fitVal[3]) << " " << comb->Eval(fitVal[4]) << endl;

  double quadInterpVal = ProfileMultiplePdfs::quadInterpMinimum(comb);
  cout << "quadInterp: mu = " << quadInterpVal << endl;
  cout << "\t " << comb->Eval(quadInterpVal) << " " << comb->Eval(quadInterpVal-0.005) << " " << comb->Eval(quadInterpVal-0.01) << " " << comb->Eval(quadInterpVal+0.005) << " " << comb->Eval(quadInterpVal+0.01) << endl;
  
  comb->SetLineWidth(2);
  TCanvas *canv = new TCanvas();
  comb->Draw("ALP");
  canv->Print("plots/comb.pdf");
  TFile *tempOut = new TFile("tempOut.root","RECREATE");
  tempOut->cd();
  comb->SetName("comb");
  comb->Write();
  tempOut->Close();
  return 0;
}
string runQuickRejig(string oldfilename, int ncats){
  
  string newfilename="TestWS.root";
  TFile *oldFile = TFile::Open(oldfilename.c_str());
  TFile *newFile = new TFile(newfilename.c_str(),"RECREATE");

  RooWorkspace *oldWS = (RooWorkspace*)oldFile->Get("cms_hgg_workspace");
  RooWorkspace *newWS = new RooWorkspace("wsig_8TeV");
  
  RooRealVar *mass = (RooRealVar*)oldWS->var("CMS_hgg_mass");

  RooDataSet *tot;

  RooRealVar *normT1 = new RooRealVar("nT1","nT1",500,0,550);
  RooRealVar *meanT1 = new RooRealVar("mT1","mT1",125,122,128);
  RooRealVar *sigmaT1 = new RooRealVar("sT1","sT1",3.1,1.,10.);
  RooGaussian *gausT1 = new RooGaussian("gT1","gT1",*mass,*meanT1,*sigmaT1);
  RooRealVar *normT2 = new RooRealVar("nT2","nT2",2,0,500);
  RooRealVar *meanT2 = new RooRealVar("mT2","mT2",125,122,128);
  RooRealVar *sigmaT2 = new RooRealVar("sT2","sT2",1.7,0.,10.);
  RooGaussian *gausT2 = new RooGaussian("gT2","gT2",*mass,*meanT2,*sigmaT2);
  RooRealVar *normT3 = new RooRealVar("nT3","nT3",2,0,500);
  RooRealVar *meanT3 = new RooRealVar("mT3","mT3",125,122,128);
  RooRealVar *sigmaT3 = new RooRealVar("sT3","sT3",1.7,0.,10.);
  RooGaussian *gausT3 = new RooGaussian("gT3","gT3",*mass,*meanT3,*sigmaT3);
  RooAddPdf *gausT = new RooAddPdf("gT","gT",RooArgList(*gausT1,*gausT2,*gausT3),RooArgList(*normT1,*normT2,*normT3));

  for (int cat=0; cat<ncats; cat++){
    RooDataSet *thisData = (RooDataSet*)oldWS->data(Form("sig_ggh_mass_m125_cat%d",cat));
    newWS->import(*thisData);
    RooRealVar *norm1 = new RooRealVar(Form("n1%d",cat),Form("n1%d",cat),500,0,550);
    RooRealVar *mean1 = new RooRealVar(Form("m1%d",cat),Form("m1%d",cat),125,122,128);
    RooRealVar *sigma1 = new RooRealVar(Form("s1%d",cat),Form("s1%d",cat),3.1,1.,10.);
    RooGaussian *gaus1 = new RooGaussian(Form("g1%d",cat),Form("g1%d",cat),*mass,*mean1,*sigma1);
    RooRealVar *norm2 = new RooRealVar(Form("n2%d",cat),Form("n2%d",cat),2,0,500);
    RooRealVar *mean2 = new RooRealVar(Form("m2%d",cat),Form("m2%d",cat),125,122,128);
    RooRealVar *sigma2 = new RooRealVar(Form("s2%d",cat),Form("s2%d",cat),1.7,0.,10.);
    RooGaussian *gaus2 = new RooGaussian(Form("g2%d",cat),Form("g2%d",cat),*mass,*mean2,*sigma2);
    RooRealVar *norm3 = new RooRealVar(Form("n3%d",cat),Form("n3%d",cat),2,0,500);
    RooRealVar *mean3 = new RooRealVar(Form("m3%d",cat),Form("m3%d",cat),125,122,128);
    RooRealVar *sigma3 = new RooRealVar(Form("s3%d",cat),Form("s3%d",cat),1.7,0.,10.);
    RooGaussian *gaus3 = new RooGaussian(Form("g3%d",cat),Form("g3%d",cat),*mass,*mean3,*sigma3);
    RooAddPdf *gaus = new RooAddPdf(Form("g%d",cat),"g",RooArgList(*gaus1,*gaus2,*gaus3),RooArgList(*norm1,*norm2,*norm3));
    gaus->fitTo(*thisData,SumW2Error(kTRUE));
    newWS->import(*gaus);
    if (cat==0) {
      tot = thisData;
      tot->SetName("sig_ggh_m125");
    }
    else tot->append(*thisData);
  }
  newWS->import(*tot);
  gausT->fitTo(*tot,SumW2Error(kTRUE));
  newWS->import(*gausT);
  newWS->Write();
  oldFile->Close();
  newFile->Close();
  delete newFile;
  delete newWS;

  return newfilename;

}