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; }
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 StandardHistFactoryPlotsWithCategories(const char* infile = "", const char* workspaceName = "combined", const char* modelConfigName = "ModelConfig", const char* dataName = "obsData"){ double nSigmaToVary=5.; double muVal=0; bool doFit=false; // ------------------------------------------------------- // 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; } // ------------------------------------------------------- // Tutorial starts here // ------------------------------------------------------- // 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 use the profile inspector RooRealVar* obs = (RooRealVar*)mc->GetObservables()->first(); TList* list = new TList(); RooRealVar * firstPOI = dynamic_cast<RooRealVar*>(mc->GetParametersOfInterest()->first()); firstPOI->setVal(muVal); // firstPOI->setConstant(); if(doFit){ mc->GetPdf()->fitTo(*data); } // ------------------------------------------------------- mc->GetNuisanceParameters()->Print("v"); int nPlotsMax = 1000; cout <<" check expectedData by category"<<endl; RooDataSet* simData=NULL; RooSimultaneous* simPdf = NULL; if(strcmp(mc->GetPdf()->ClassName(),"RooSimultaneous")==0){ cout <<"Is a simultaneous PDF"<<endl; simPdf = (RooSimultaneous *)(mc->GetPdf()); } else { cout <<"Is not a simultaneous PDF"<<endl; } if(doFit) { RooCategory* channelCat = (RooCategory*) (&simPdf->indexCat()); TIterator* iter = channelCat->typeIterator() ; RooCatType* tt = NULL; tt=(RooCatType*) iter->Next(); RooAbsPdf* pdftmp = ((RooSimultaneous*)mc->GetPdf())->getPdf(tt->GetName()) ; RooArgSet* obstmp = pdftmp->getObservables(*mc->GetObservables()) ; obs = ((RooRealVar*)obstmp->first()); RooPlot* frame = obs->frame(); cout <<Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())<<endl; cout << tt->GetName() << " " << channelCat->getLabel() <<endl; data->plotOn(frame,MarkerSize(1),Cut(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())),DataError(RooAbsData::None)); Double_t normCount = data->sumEntries(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())) ; pdftmp->plotOn(frame,LineWidth(2.),Normalization(normCount,RooAbsReal::NumEvent)) ; frame->Draw(); cout <<"expected events = " << mc->GetPdf()->expectedEvents(*data->get()) <<endl; return; } int nPlots=0; if(!simPdf){ TIterator* it = mc->GetNuisanceParameters()->createIterator(); RooRealVar* var = NULL; while( (var = (RooRealVar*) it->Next()) != NULL){ RooPlot* frame = obs->frame(); frame->SetYTitle(var->GetName()); data->plotOn(frame,MarkerSize(1)); var->setVal(0); mc->GetPdf()->plotOn(frame,LineWidth(1.)); var->setVal(1); mc->GetPdf()->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(1)); var->setVal(-1); mc->GetPdf()->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(1)); list->Add(frame); var->setVal(0); } } else { RooCategory* channelCat = (RooCategory*) (&simPdf->indexCat()); // TIterator* iter = simPdf->indexCat().typeIterator() ; TIterator* iter = channelCat->typeIterator() ; RooCatType* tt = NULL; while(nPlots<nPlotsMax && (tt=(RooCatType*) iter->Next())) { cout << "on type " << tt->GetName() << " " << endl; // Get pdf associated with state from simpdf RooAbsPdf* pdftmp = simPdf->getPdf(tt->GetName()) ; // Generate observables defined by the pdf associated with this state RooArgSet* obstmp = pdftmp->getObservables(*mc->GetObservables()) ; // obstmp->Print(); obs = ((RooRealVar*)obstmp->first()); TIterator* it = mc->GetNuisanceParameters()->createIterator(); RooRealVar* var = NULL; while(nPlots<nPlotsMax && (var = (RooRealVar*) it->Next())){ TCanvas* c2 = new TCanvas("c2"); RooPlot* frame = obs->frame(); frame->SetName(Form("frame%d",nPlots)); frame->SetYTitle(var->GetName()); cout <<Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())<<endl; cout << tt->GetName() << " " << channelCat->getLabel() <<endl; data->plotOn(frame,MarkerSize(1),Cut(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())),DataError(RooAbsData::None)); Double_t normCount = data->sumEntries(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())) ; if(strcmp(var->GetName(),"Lumi")==0){ cout <<"working on lumi"<<endl; var->setVal(w->var("nominalLumi")->getVal()); var->Print(); } else{ var->setVal(0); } // w->allVars().Print("v"); // mc->GetNuisanceParameters()->Print("v"); // pdftmp->plotOn(frame,LineWidth(2.)); // mc->GetPdf()->plotOn(frame,LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data)); //pdftmp->plotOn(frame,LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data)); normCount = pdftmp->expectedEvents(*obs); pdftmp->plotOn(frame,LineWidth(2.),Normalization(normCount,RooAbsReal::NumEvent)) ; if(strcmp(var->GetName(),"Lumi")==0){ cout <<"working on lumi"<<endl; var->setVal(w->var("nominalLumi")->getVal()+0.05); var->Print(); } else{ var->setVal(nSigmaToVary); } // pdftmp->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2)); // mc->GetPdf()->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data)); //pdftmp->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data)); normCount = pdftmp->expectedEvents(*obs); pdftmp->plotOn(frame,LineWidth(2.),LineColor(kRed),LineStyle(kDashed),Normalization(normCount,RooAbsReal::NumEvent)) ; if(strcmp(var->GetName(),"Lumi")==0){ cout <<"working on lumi"<<endl; var->setVal(w->var("nominalLumi")->getVal()-0.05); var->Print(); } else{ var->setVal(-nSigmaToVary); } // pdftmp->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2)); // mc->GetPdf()->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2),Slice(*channelCat,tt->GetName()),ProjWData(*data)); //pdftmp->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2),Slice(*channelCat,tt->GetName()),ProjWData(*data)); normCount = pdftmp->expectedEvents(*obs); pdftmp->plotOn(frame,LineWidth(2.),LineColor(kGreen),LineStyle(kDashed),Normalization(normCount,RooAbsReal::NumEvent)) ; // set them back to normal if(strcmp(var->GetName(),"Lumi")==0){ cout <<"working on lumi"<<endl; var->setVal(w->var("nominalLumi")->getVal()); var->Print(); } else{ var->setVal(0); } list->Add(frame); // quit making plots ++nPlots; frame->Draw(); c2->SaveAs(Form("%s_%s_%s.pdf",tt->GetName(),obs->GetName(),var->GetName())); delete c2; } } } // ------------------------------------------------------- // now make plots TCanvas* c1 = new TCanvas("c1","ProfileInspectorDemo",800,200); if(list->GetSize()>4){ double n = list->GetSize(); int nx = (int)sqrt(n) ; int ny = TMath::CeilNint(n/nx); nx = TMath::CeilNint( sqrt(n) ); c1->Divide(ny,nx); } else c1->Divide(list->GetSize()); for(int i=0; i<list->GetSize(); ++i){ c1->cd(i+1); list->At(i)->Draw(); } }