C++ ToyMCSampler::GenerateToyData方法代码示例

//.........这里部分代码省略.........

  /////////////////////////////////////////////////////////////
  // 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;

result fit_toy(RooWorkspace* wspace, int n, const RooArgSet* globals) {
    RooRandom::randomGenerator()->SetSeed(0);
    // TFile f(filename);
    // RooWorkspace *wspace = (RooWorkspace*)f.Get("combined");
    ModelConfig* model = (ModelConfig*)wspace->obj("ModelConfig");

    RooAbsPdf* pdf;
    pdf = model->GetPdf();

    RooAbsPdf* top_constraint = (RooAbsPdf*)wspace->obj("top_ratio_constraint");
    RooAbsPdf* vv_constraint = (RooAbsPdf*)wspace->obj("vv_ratio_constraint");
    RooAbsPdf* top_vv_constraint_sf = (RooAbsPdf*)wspace->obj("top_vv_ratio_sf_constraint");
    RooAbsPdf* top_vv_constraint_of = (RooAbsPdf*)wspace->obj("top_vv_ratio_of_constraint");


    // generate constraint global observables
    RooRealVar *nom_top_ratio = (RooRealVar*)wspace->obj("nom_top_ratio");
    nom_top_ratio->setRange(0, 100);
    RooRealVar *nom_vv_ratio = (RooRealVar*)wspace->obj("nom_vv_ratio");
    nom_vv_ratio->setRange(0,100);
    RooRealVar *nom_top_vv_ratio_sf = (RooRealVar*)wspace->obj("nom_top_vv_ratio_sf");
    nom_top_vv_ratio_sf->setRange(0,100);
    RooRealVar *nom_top_vv_ratio_of = (RooRealVar*)wspace->obj("nom_top_vv_ratio_of");
    nom_top_vv_ratio_of->setRange(0,100);

    RooDataSet *nom_top_generated = top_constraint->generateSimGlobal(RooArgSet(*nom_top_ratio), 1);
    nom_top_ratio->setVal(((RooRealVar*)nom_top_generated->get(0)->find("nom_top_ratio"))->getVal());

    RooDataSet *nom_vv_generated = vv_constraint->generateSimGlobal(RooArgSet(*nom_vv_ratio), 1);
    nom_vv_ratio->setVal(((RooRealVar*)nom_vv_generated->get(0)->find("nom_vv_ratio"))->getVal());

    RooDataSet *nom_top_vv_sf_generated = top_vv_constraint_sf->generateSimGlobal(RooArgSet(*nom_top_vv_ratio_sf), 1);
    nom_top_vv_ratio_sf->setVal(((RooRealVar*)nom_top_vv_sf_generated->get(0)->find("nom_top_vv_ratio_sf"))->getVal());

    RooDataSet *nom_top_vv_of_generated = top_vv_constraint_of->generateSimGlobal(RooArgSet(*nom_top_vv_ratio_of), 1);
    nom_top_vv_ratio_of->setVal(((RooRealVar*)nom_top_vv_of_generated->get(0)->find("nom_top_vv_ratio_of"))->getVal());

    NumEventsTestStat* dummy = new NumEventsTestStat(*pdf);

    ToyMCSampler* mc = new ToyMCSampler(*dummy, 1);
    mc->SetPdf(*pdf);
    mc->SetObservables(*model->GetObservables());
    mc->SetGlobalObservables(*globals);
    mc->SetNuisanceParameters(*model->GetNuisanceParameters());
    mc->SetParametersForTestStat(*model->GetParametersOfInterest());
    mc->SetNEventsPerToy(n);

    RooArgSet constr;
    constr.add(*(model->GetNuisanceParameters()));
    RemoveConstantParameters(&constr);

    RooDataSet* toy_data = (RooDataSet*)mc->GenerateToyData(*const_cast<RooArgSet*>(model->GetSnapshot()));

    RooFitResult *res = pdf->fitTo(*toy_data, Constrain(constr), PrintLevel(0), Save(),
                                               Range("fitRange"), InitialHesse(),
                                               ExternalConstraints(RooArgSet(*top_constraint, *vv_constraint, *top_vv_constraint_sf, *top_vv_constraint_of)));
    result yield = get_results(wspace, res);
    yield.of.generated_sum.val = toy_data->sumEntries("(channelCat==channelCat::of) & (obs_x_of>120)");
    yield.sf.generated_sum.val = toy_data->sumEntries("(channelCat==channelCat::sf) & (obs_x_sf>120)");

    delete mc;
    delete dummy;
    // f.Close();

    return yield;
}