void gen1(const char* output, const char* suffix) {
// S e t u p m o d e l
// ---------------------
gRandom = new TRandom();
gRandom->SetSeed(0);
RooWorkspace *ws = new RooWorkspace("workspace");
// Declare variables x,mean,sigma with associated name, title, initial value and allowed range
ws->factory("invMass[2,5]");
RooRealVar *invMass = ws->var("invMass");
RooRealVar *weight = new RooRealVar("weight","weight",1,0,1e6);
ws->factory(Form("Gaussian::siga_nonorm_%s(invMass,m_%s[3,2.5,3.5],sigmaa_%s[0.02,0.,0.5])",suffix,suffix,suffix));
ws->factory(Form("Gaussian::sigb_nonorm_%s(invMass,m_%s,sigmab_%s[0.1,0.,0.5])",suffix,suffix,suffix));
ws->factory(Form("SUM::sig_nonorm_%s(f_%s[0.8,0,1]*siga_nonorm_%s,sigb_nonorm_%s)",suffix,suffix,suffix,suffix));
ws->factory(Form("RooExtendPdf::sig_%s(sig_nonorm_%s,Nsig_%s[1e4,-1e5,1e5])",suffix,suffix,suffix));
ws->factory(Form("Gaussian::sig2_nonorm_%s(invMass,m2_%s[3.5,3.,4.],sigma2_%s[0.1,0.,0.5])",suffix,suffix,suffix));
ws->factory(Form("RooFormulaVar::Nsig2_%s('@0*@1',{Nsig_%s,frac_%s[0.5,-10,10]})",suffix,suffix,suffix));
ws->factory(Form("RooExtendPdf::sig2_%s(sig2_nonorm_%s,Nsig2_%s)",suffix,suffix,suffix));
ws->factory(Form("Chebychev::bkg_nonorm_%s(invMass,{lambda0_%s[0.1,-1.5,1.5],lambda1_%s[0.1,-1.5,1.5]})",suffix,suffix,suffix));
ws->factory(Form("RooExtendPdf::bkg_%s(bkg_nonorm_%s,Nbkg_%s[1e4,-1e5,1e5])",suffix,suffix,suffix));
// ws->factory(Form("SUM::tot_%s( sig_%s, bkg_%s)",suffix,suffix,suffix));
// RooAbsPdf *thepdf = ws->pdf(Form("tot_%s",suffix));
RooAbsPdf *thepdf = new RooAddPdf(Form("tot_%s",suffix), Form("tot_%s",suffix),
RooArgList(*ws->pdf(Form("sig_%s",suffix)), *ws->pdf(Form("sig2_%s",suffix)), *ws->pdf(Form("bkg_%s",suffix))));
ws->import(*thepdf);
// G e n e r a t e e v e n t s
// -----------------------------
// Generate a dataset of 1000 events in x from gauss
RooDataSet* data = thepdf->generate(*invMass,2e4,Name(Form("data_%s",suffix))) ;
ws->import(*data);
ws->writeToFile(output);
}
//____________________________________
void AddData(RooWorkspace* wks){
// Add a toy dataset
Int_t nEvents = 150;
RooAbsPdf* model = wks->pdf("model");
RooRealVar* invMass = wks->var("invMass");
RooDataSet* data = model->generate(*invMass,nEvents);
wks->import(*data, Rename("data"));
}
MakeBiasStudy::MakeBiasStudy() {
int Nmodels = 8;
//RooRealVar* mass = ws->var("mass");
RooRealVar *mass = new RooRealVar("mass","mass", 100,180);
RooRealVar *nBkgTruth = new RooRealVar("TruthNBkg","", 0,1e9);
// RooAbsData* realData = ws->data("Data_Combined")->reduce( Form("evtcat==evtcat::%s",cat.Data()) );
double Bias[Nmodels][Nmodels];
double BiasE[Nmodels][Nmodels];
MakeAICFits MakeAIC_Fits;
for(int truthType = 0; truthType < Nmodels; truthType++){
RooAbsPdf *truthPdf = MakeAIC_Fits.getBackgroundPdf(truthType,mass);
RooExtendPdf *truthExtendedPdf = new RooExtendPdf("truthExtendedPdf","",*truthPdf,*nBkgTruth);
//truthExtendedPdf.fitTo(*realData,RooFit::Strategy(0),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE));
//truthExtendedPdf.fitTo(*realData,RooFit::Strategy(2),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE));
double BiasWindow = 2.00;
mass->setRange("biasRegion", mh-BiasWindow, mh+BiasWindow);
double TruthFrac = truthExtendedPdf->createIntegral(mass,RooFit::Range("biasRegion"),RooFit::NormSet(*mass))->getVal();
double NTruth = TruthFrac * nBkgTruth->getVal();
double NTruthE = TruthFrac * nBkgTruth->getError();
RooDataSet* truthbkg = truthPdf->generate(RooArgSet(*mass),nBkgTruth);
for(int modelType = 0; modelType < Nmodels; modelType++){
RooAbsPdf* ModelShape = MakeAIC_Fits.getBackgroundPdf(modelType,mass);
RooRealVar *nBkgFit = new RooRealVar("FitNBkg", "", 0, 1e9);
RooExtendPdf ModelExtendedPdf = new RooExtendPdf("ModelExtendedPdf", "",*ModelShape, *nBkgFit);
ModelExtendedPdf.fitTo(truthbkg, RooFit::Strategy(0),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE));
ModelExtendedPdf.fitTo(truthbkg, RooFit::Strategy(2),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE));
double FitFrac = ModelExtendedPdf.createIntegral(mass,RooFit::Range("biasRegion"),RooFit::NormSet(mass))->getVal();
double NFit = FitFrac * nBkgFit->getVal();
double NFitE = FitFrac * nBkgFit->getError();
Bias[truthType][modelType] = fabs(NFit - NTruth);
BiasE[truthType][modelType] = fabs(NFitE - NTruthE);
}
}
for(int i = 0; i < Nmodels; i++) {
std::cout << "===== Truth Model : " << MakeBiasStudy::Category(i) << " ===== " << std::endl;
for (int j = 0; j < Nmodels; j++) {
std::cout << "Fit Model: " << MakeBiasStudy::Category(j) << " , Bias = " << Bias[i][j] << " +/- " << BiasE[i][j] << std::endl;
}
}
}
RooDataSet*GenericPDFModel::GenerateDataSet(RooAbsPdf& parDist, const RooArgList* params)
{
// Generate dataset for the observables using the given parameter probability distribution
// If optional parameter list params is given, it is used instead of the default
// defined parameter list of the model
Info("GenerateDataSet","Generating %d datapoints with parameter distribution %s",
GetNumGen(), parDist.GetName());
RooProdPdf Multimodel("Multimodel","observables for parameter distributions", parDist,
Conditional(*theModel,GetObservables()));
// get marginalized distributions model for observables
if(!params) params = &GetParameters();
RooAbsPdf* margin = Multimodel.createProjection(*params);
RooDataSet* data = margin->generate(GetObservables(),fNGen);
delete margin;
return data;
}
//____________________________________
void AddData(RooWorkspace* ws){
// Add a toy dataset
// how many events do we want?
Int_t nEvents = 1000;
// get what we need out of the workspace to make toy data
RooAbsPdf* model = ws->pdf("model");
RooRealVar* invMass = ws->var("invMass");
RooRealVar* isolation = ws->var("isolation");
// make the toy data
std::cout << "make data set and import to workspace" << std::endl;
RooDataSet* data = model->generate(RooArgSet(*invMass, *isolation),nEvents);
// import data into workspace
ws->import(*data, Rename("data"));
}
void rf510_wsnamedsets()
{
// C r e a t e m o d e l a n d d a t a s e t
// -----------------------------------------------
RooWorkspace* w = new RooWorkspace("w") ;
fillWorkspace(*w) ;
// Exploit convention encoded in named set "parameters" and "observables"
// to use workspace contents w/o need for introspected
RooAbsPdf* model = w->pdf("model") ;
// Generate data from p.d.f. in given observables
RooDataSet* data = model->generate(*w->set("observables"),1000) ;
// Fit model to data
model->fitTo(*data) ;
// Plot fitted model and data on frame of first (only) observable
RooPlot* frame = ((RooRealVar*)w->set("observables")->first())->frame() ;
data->plotOn(frame) ;
model->plotOn(frame) ;
// Overlay plot with model with reference parameters as stored in snapshots
w->loadSnapshot("reference_fit") ;
model->plotOn(frame,LineColor(kRed)) ;
w->loadSnapshot("reference_fit_bkgonly") ;
model->plotOn(frame,LineColor(kRed),LineStyle(kDashed)) ;
// Draw the frame on the canvas
new TCanvas("rf510_wsnamedsets","rf503_wsnamedsets",600,600) ;
gPad->SetLeftMargin(0.15) ; frame->GetYaxis()->SetTitleOffset(1.4) ; frame->Draw() ;
// Print workspace contents
w->Print() ;
// Workspace will remain in memory after macro finishes
gDirectory->Add(w) ;
}
void rf105_funcbinding()
{
// B i n d T M a t h : : E r f C f u n c t i o n
// ---------------------------------------------------
// Bind one-dimensional TMath::Erf function as RooAbsReal function
RooRealVar x("x","x",-3,3) ;
RooAbsReal* errorFunc = bindFunction("erf",TMath::Erf,x) ;
// Print erf definition
errorFunc->Print() ;
// Plot erf on frame
RooPlot* frame1 = x.frame(Title("TMath::Erf bound as RooFit function")) ;
errorFunc->plotOn(frame1) ;
// B i n d R O O T : : M a t h : : b e t a _ p d f C f u n c t i o n
// -----------------------------------------------------------------------
// Bind pdf ROOT::Math::Beta with three variables as RooAbsPdf function
RooRealVar x2("x2","x2",0,0.999) ;
RooRealVar a("a","a",5,0,10) ;
RooRealVar b("b","b",2,0,10) ;
RooAbsPdf* beta = bindPdf("beta",ROOT::Math::beta_pdf,x2,a,b) ;
// Perf beta definition
beta->Print() ;
// Generate some events and fit
RooDataSet* data = beta->generate(x2,10000) ;
beta->fitTo(*data) ;
// Plot data and pdf on frame
RooPlot* frame2 = x2.frame(Title("ROOT::Math::Beta bound as RooFit pdf")) ;
data->plotOn(frame2) ;
beta->plotOn(frame2) ;
// B i n d R O O T T F 1 a s R o o F i t f u n c t i o n
// ---------------------------------------------------------------
// Create a ROOT TF1 function
TF1 *fa1 = new TF1("fa1","sin(x)/x",0,10);
// Create an observable
RooRealVar x3("x3","x3",0.01,20) ;
// Create binding of TF1 object to above observable
RooAbsReal* rfa1 = bindFunction(fa1,x3) ;
// Print rfa1 definition
rfa1->Print() ;
// Make plot frame in observable, plot TF1 binding function
RooPlot* frame3 = x3.frame(Title("TF1 bound as RooFit function")) ;
rfa1->plotOn(frame3) ;
TCanvas* c = new TCanvas("rf105_funcbinding","rf105_funcbinding",1200,400) ;
c->Divide(3) ;
c->cd(1) ; gPad->SetLeftMargin(0.15) ; frame1->GetYaxis()->SetTitleOffset(1.6) ; frame1->Draw() ;
c->cd(2) ; gPad->SetLeftMargin(0.15) ; frame2->GetYaxis()->SetTitleOffset(1.6) ; frame2->Draw() ;
c->cd(3) ; gPad->SetLeftMargin(0.15) ; frame3->GetYaxis()->SetTitleOffset(1.6) ; frame3->Draw() ;
}
exampleScript()
{
gSystem->CompileMacro("betaHelperFunctions.h" ,"kO") ;
gSystem->CompileMacro("RooNormalFromFlatPdf.cxx" ,"kO") ;
gSystem->CompileMacro("RooBetaInverseCDF.cxx" ,"kO") ;
gSystem->CompileMacro("RooBetaPrimeInverseCDF.cxx" ,"kO") ;
gSystem->CompileMacro("RooCorrelatedBetaGeneratorHelper.cxx" ,"kO") ;
gSystem->CompileMacro("RooCorrelatedBetaPrimeGeneratorHelper.cxx" ,"kO") ;
gSystem->CompileMacro("rooFitBetaHelperFunctions.h","kO") ;
TFile betaTest("betaTest.root","RECREATE");
betaTest.cd();
RooWorkspace workspace("workspace");
TString correlatedName("testVariable");
TString observables("observables");
TString nuisances("nuisances");
RooAbsArg* betaOne = getCorrelatedBetaConstraint(workspace,"betaOne","",
0.5 , 0.1 ,
observables, nuisances,
correlatedName );
printf("\n\n *** constraint name is %s from betaOne and %s\n\n", betaOne->GetName(), correlatedName.Data() ) ;
RooAbsArg* betaTwo = getCorrelatedBetaConstraint(workspace,"betaTwo","",
0 , 0 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaThree = getCorrelatedBetaConstraint(workspace,"betaThree","",
0.2 , 0.01 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaFour = getCorrelatedBetaConstraint(workspace,"betaFour","",
0.7 , 0.1 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaFourC = getCorrelatedBetaConstraint(workspace,"betaFourC","",
0.7 , 0.1 ,
observables, nuisances,
correlatedName, kTRUE );
RooAbsArg* betaPrimeOne = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeOne","",
1.0 , 0.5 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeOneC = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeOneC","",
1.0 , 0.5 ,
observables, nuisances,
correlatedName, kTRUE );
RooAbsArg* betaPrimeTwo = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeTwo","",
0.7 , 0.5 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeThree = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeThree","",
0.1 , 0.05 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeFour = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeFour","",
7 , 1 ,
observables, nuisances,
correlatedName );
RooRealVar* correlatedParameter = workspace.var(correlatedName);
RooAbsPdf* normalFromFlat = workspace.pdf(correlatedName+"_Constraint");
RooDataSet* data = normalFromFlat->generate(RooArgSet(*correlatedParameter),1e5);
data->addColumn(*normalFromFlat);
data->addColumn(*betaOne);
data->addColumn(*betaTwo);
data->addColumn(*betaThree);
data->addColumn(*betaFour);
data->addColumn(*betaFourC);
data->addColumn(*betaPrimeOne);
data->addColumn(*betaPrimeTwo);
data->addColumn(*betaPrimeThree);
data->addColumn(*betaPrimeFour);
data->addColumn(*betaPrimeOneC);
data->Print("v");
workspace.Print() ;
//Setup Plotting Kluges:
RooRealVar normalPlotter (correlatedName+"_Constraint" , correlatedName+"_Constraint" ,0,1);
RooPlot* normalPlot = normalPlotter.frame();
data->plotOn(normalPlot);
RooRealVar betaOnePlotter ("betaOne_BetaInverseCDF" ,"betaOne_BetaInverseCDF" ,0,1);
RooRealVar betaTwoPlotter ("betaTwo_BetaInverseCDF" ,"betaTwo_BetaInverseCDF" ,0,1);
RooRealVar betaThreePlotter("betaThree_BetaInverseCDF","betaThree_BetaInverseCDF",0,1);
RooRealVar betaFourPlotter ("betaFour_BetaInverseCDF" ,"betaFour_BetaInverseCDF" ,0,1);
RooRealVar betaFourCPlotter ("betaFourC_BetaInverseCDF" ,"betaFourC_BetaInverseCDF" ,0,1);
RooRealVar betaPrimeOnePlotter ("betaPrimeOne_BetaPrimeInverseCDF" ,"betaPrimeOne_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeOneCPlotter ("betaPrimeOneC_BetaPrimeInverseCDF" ,"betaPrimeOneC_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeTwoPlotter ("betaPrimeTwo_BetaPrimeInverseCDF" ,"betaPrimeTwo_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeThreePlotter("betaPrimeThree_BetaPrimeInverseCDF","betaPrimeThree_BetaPrimeInverseCDF",0,0.3);
RooRealVar betaPrimeFourPlotter ("betaPrimeFour_BetaPrimeInverseCDF" ,"betaPrimeFour_BetaPrimeInverseCDF" ,4,12);
RooPlot* betaOnePlot = betaOnePlotter .frame();
RooPlot* betaTwoPlot = betaTwoPlotter .frame();
RooPlot* betaThreePlot = betaThreePlotter.frame();
RooPlot* betaFourPlot = betaFourPlotter .frame();
RooPlot* betaFourCPlot = betaFourCPlotter .frame();
data->plotOn(betaOnePlot );
data->plotOn(betaTwoPlot );
data->plotOn(betaThreePlot);
data->plotOn(betaFourPlot );
data->plotOn(betaFourCPlot );
RooPlot* betaPrimeOnePlot = betaPrimeOnePlotter .frame();
RooPlot* betaPrimeOneCPlot = betaPrimeOneCPlotter .frame();
RooPlot* betaPrimeTwoPlot = betaPrimeTwoPlotter .frame();
RooPlot* betaPrimeThreePlot = betaPrimeThreePlotter.frame();
RooPlot* betaPrimeFourPlot = betaPrimeFourPlotter .frame();
data->plotOn(betaPrimeOnePlot );
data->plotOn(betaPrimeOneCPlot );
data->plotOn(betaPrimeTwoPlot );
data->plotOn(betaPrimeThreePlot);
data->plotOn(betaPrimeFourPlot );
TCanvas* underlyingVariable = new TCanvas("underlyingVariable","underlyingVariable",800,800);
underlyingVariable->Divide(2,2);
underlyingVariable->cd(1);
RooPlot* underlyingPlot = correlatedParameter->frame();
data->plotOn(underlyingPlot);
underlyingPlot->Draw();
underlyingVariable->cd(2);
normalPlot->Draw();
underlyingVariable->cd(3);
TH2F* underlying = data->createHistogram(*correlatedParameter,normalPlotter,50,50);
underlying->Draw("col");
TH2F* legoUnderlying = (TH2F*)underlying->Clone();
underlyingVariable->cd(4);
legoUnderlying->Draw("lego");
underlyingVariable->SaveAs("underlyingVariable.pdf");
TCanvas* betaCanvas = new TCanvas("betaCanvas","betaCanvas",800,800);
betaCanvas->Divide(3,2);
betaCanvas->cd(1);
betaOnePlot->Draw();
betaCanvas->cd(2);
betaTwoPlot->Draw();
betaCanvas->cd(3);
betaThreePlot->Draw();
betaCanvas->cd(4);
betaFourPlot->Draw();
betaCanvas->cd(5);
betaFourCPlot->Draw();
betaCanvas->SaveAs("betaVariables.pdf");
TCanvas* betaPrimeCanvas = new TCanvas("betaPrimeCanvas","betaPrimeCanvas",1200,800);
betaPrimeCanvas->Divide(3,2);
betaPrimeCanvas->cd(1);
betaPrimeOnePlot->Draw();
betaPrimeCanvas->cd(2);
betaPrimeTwoPlot->Draw();
betaPrimeCanvas->cd(3);
betaPrimeThreePlot->Draw();
betaPrimeCanvas->cd(4);
betaPrimeFourPlot->Draw();
betaPrimeCanvas->cd(5);
betaPrimeOneCPlot->Draw();
betaPrimeCanvas->SaveAs("betaPrimeVariables.pdf");
TCanvas* betaCorrelationsCanvas = new TCanvas("betaCorrelationsCanvas","betaCorrelationsCanvas",1600,800);
betaCorrelationsCanvas->Divide(4,2);
TH2F* oneTwo = data->createHistogram(betaOnePlotter,betaTwoPlotter,30,30);
TH2F* oneThree = data->createHistogram(betaOnePlotter,betaThreePlotter,30,30);
TH2F* oneFour = data->createHistogram(betaOnePlotter,betaFourPlotter,30,30);
TH2F* twoThree = data->createHistogram(betaTwoPlotter,betaThreePlotter,30,30);
TH2F* twoFour = data->createHistogram(betaTwoPlotter,betaFourPlotter,30,30);
TH2F* threeFour = data->createHistogram(betaThreePlotter,betaFourPlotter,30,30);
TH2F* twoFourC = data->createHistogram(betaTwoPlotter,betaFourCPlotter,30,30);
TH2F* fourFourC = data->createHistogram(betaFourPlotter,betaFourCPlotter,30,30);
betaCorrelationsCanvas->cd(1);
oneTwo->DrawCopy("lego");
betaCorrelationsCanvas->cd(2);
oneThree->DrawCopy("lego");
betaCorrelationsCanvas->cd(3);
oneFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(4);
twoThree->DrawCopy("lego");
betaCorrelationsCanvas->cd(5);
twoFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(6);
threeFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(7);
twoFourC->DrawCopy("lego");
betaCorrelationsCanvas->cd(8);
fourFourC->DrawCopy("lego");
betaCorrelationsCanvas->SaveAs("betaCorrelations.pdf");
TCanvas* betaPrimeCorrelationsCanvas = new TCanvas("betaPrimeCorrelationsCanvas","betaPrimeCorrelationsCanvas",1600,800);
betaPrimeCorrelationsCanvas->Divide(4,2);
TH2F* oneTwo = data->createHistogram(betaPrimeOnePlotter,betaPrimeTwoPlotter,30,30);
TH2F* oneThree = data->createHistogram(betaPrimeOnePlotter,betaPrimeThreePlotter,30,30);
TH2F* oneFour = data->createHistogram(betaPrimeOnePlotter,betaPrimeFourPlotter,30,30);
TH2F* twoThree = data->createHistogram(betaPrimeTwoPlotter,betaPrimeThreePlotter,30,30);
TH2F* twoFour = data->createHistogram(betaPrimeTwoPlotter,betaPrimeFourPlotter,30,30);
TH2F* threeFour = data->createHistogram(betaPrimeThreePlotter,betaPrimeFourPlotter,30,30);
TH2F* oneOneC = data->createHistogram(betaPrimeOnePlotter,betaPrimeOneCPlotter,30,30);
betaPrimeCorrelationsCanvas->cd(1);
oneTwo->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(2);
oneThree->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(3);
oneFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(4);
twoThree->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(5);
twoFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(6);
threeFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(7);
oneOneC->DrawCopy("lego");
betaPrimeCorrelationsCanvas->SaveAs("betaPrimeCorrelations.pdf");
RooProdPdf totalPdf("totalPdf","totalPdf",workspace.allPdfs());
totalPdf.Print("v");
RooArgSet* observableSet = workspace.set("observables");
observableSet->Print();
RooDataSet* allDataOne = totalPdf.generate(*observableSet,1);
allDataOne->Print("v");
correlatedParameter->setVal(0.25);
RooDataSet* allDataTwo = totalPdf.generate(*observableSet,1);
allDataTwo->Print("v");
correlatedParameter->setVal(0.75);
RooDataSet* allDataThree = totalPdf.generate(*observableSet,1);
allDataThree->Print("v");
//Testing for extreme values!
for(int i = 0; i< 101; i++)
{
correlatedParameter->setVal((double)i/100.);
cout << "Correlation parameter has value of " << correlatedParameter->getVal();
cout << " and the pdf has an unnormalized value of " << normalFromFlat->getVal() << endl;
}
}
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 FitterUtils::generate()
{
//***************Get the PDFs from the workspace
TFile fw(workspacename.c_str(), "UPDATE");
RooWorkspace* workspace = (RooWorkspace*)fw.Get("workspace");
RooRealVar *B_plus_M = workspace->var("B_plus_M");
RooRealVar *misPT = workspace->var("misPT");
RooRealVar *T = workspace->var("T");
RooRealVar *n = workspace->var("n");
RooRealVar *expoConst = workspace->var("expoConst");
RooRealVar *trueExp = workspace->var("trueExp");
RooRealVar *fractionalErrorJpsiLeak = workspace->var("fractionalErrorJpsiLeak");
cout<<"VALUE OF T IN GENERATE: "<<T->getVal()<<" +- "<<T->getError()<<endl;
cout<<"VALUE OF n IN GENERATE: "<<n->getVal()<<" +- "<<n->getError()<<endl;
RooHistPdf *histPdfSignalZeroGamma = (RooHistPdf *) workspace->pdf("histPdfSignalZeroGamma");
RooHistPdf *histPdfSignalOneGamma = (RooHistPdf *) workspace->pdf("histPdfSignalOneGamma");
RooHistPdf *histPdfSignalTwoGamma = (RooHistPdf *) workspace->pdf("histPdfSignalTwoGamma");
RooHistPdf *histPdfPartReco = (RooHistPdf *) workspace->pdf("histPdfPartReco");
RooHistPdf *histPdfJpsiLeak(0);
if(nGenJpsiLeak>1) histPdfJpsiLeak = (RooHistPdf *) workspace->pdf("histPdfJpsiLeak");
RooAbsPdf *combPDF;
if (fit2D)
{
combPDF = new RooPTMVis("combPDF", "combPDF", *misPT, *B_plus_M, *T, *n, *expoConst);
}
else
{
combPDF = new RooExponential("combPDF", "combPDF", *B_plus_M, *expoConst);
}
double trueExpConst(trueExp->getValV());
expoConst->setVal(trueExpConst);
//***************Prepare generation
int nGenSignalZeroGamma(floor(nGenFracZeroGamma*nGenSignal));
int nGenSignalOneGamma(floor(nGenFracOneGamma*nGenSignal));
int nGenSignalTwoGamma(floor(nGenSignal-nGenSignalZeroGamma-nGenSignalOneGamma));
RooArgSet argset2(*B_plus_M);
if (fit2D) argset2.add(*misPT);
cout<<"Preparing the generation of events 1";
RooRandom::randomGenerator()->SetSeed();
RooAbsPdf::GenSpec* GenSpecSignalZeroGamma = histPdfSignalZeroGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalZeroGamma)); cout<<" 2 ";
RooAbsPdf::GenSpec* GenSpecSignalOneGamma = histPdfSignalOneGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalOneGamma)); cout<<" 3 ";
RooAbsPdf::GenSpec* GenSpecSignalTwoGamma = histPdfSignalTwoGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalTwoGamma)); cout<<" 4 ";
RooAbsPdf::GenSpec* GenSpecPartReco = histPdfPartReco->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenPartReco)); cout<<" 5 "<<endl;
RooAbsPdf::GenSpec* GenSpecComb = combPDF->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenComb));
RooAbsPdf::GenSpec* GenSpecJpsiLeak(0);
if(nGenJpsiLeak>1) GenSpecJpsiLeak = histPdfJpsiLeak->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenJpsiLeak));
cout<<"Variable loaded:"<<endl;
B_plus_M->Print(); expoConst->Print(); //B_plus_DTFM_M_zero->Print();
if (fit2D) misPT->Print();
//***************Generate some datasets
cout<<"Generating signal Zero Photon"<<endl;
RooDataSet* dataGenSignalZeroGamma = histPdfSignalZeroGamma->generate(*GenSpecSignalZeroGamma);//(argset, 250, false, true, "", false, true);
dataGenSignalZeroGamma->SetName("dataGenSignalZeroGamma"); dataGenSignalZeroGamma->SetTitle("dataGenSignalZeroGamma");
cout<<"Generating signal One Photon"<<endl;
RooDataSet* dataGenSignalOneGamma = histPdfSignalOneGamma->generate(*GenSpecSignalOneGamma);//(argset, 250, false, true, "", false, true);
dataGenSignalOneGamma->SetName("dataGenSignalOneGamma"); dataGenSignalOneGamma->SetTitle("dataGenSignalOneGamma");
cout<<"Generating signal two Photons"<<endl;
RooDataSet* dataGenSignalTwoGamma = histPdfSignalTwoGamma->generate(*GenSpecSignalTwoGamma);//(argset, 250, false, true, "", false, true);
dataGenSignalTwoGamma->SetName("dataGenSignalTwoGamma"); dataGenSignalTwoGamma->SetTitle("dataGenSignalTwoGamma");
cout<<"Generating combinatorial"<<endl;
RooDataSet* dataGenComb = combPDF->generate(*GenSpecComb);//(argset, 100, false, true, "", false, true);
dataGenComb->SetName("dataGenComb"); dataGenComb->SetTitle("dataGenComb");
cout<<"Generating PartReco"<<endl;
RooDataSet* dataGenPartReco = histPdfPartReco->generate(*GenSpecPartReco);//argset, 160, false, true, "", false, true);
dataGenPartReco->SetName("dataGenPartReco"); dataGenPartReco->SetTitle("dataGenPartReco");
RooDataSet* dataGenJpsiLeak(0);
if(nGenJpsiLeak>1)
{
cout<<"Generating Leaking JPsi"<<endl;
dataGenJpsiLeak = histPdfJpsiLeak->generate(*GenSpecJpsiLeak);//argset, 160, false, true, "", false, true);
dataGenJpsiLeak->SetName("dataGenJpsiLeak"); dataGenJpsiLeak->SetTitle("dataGenJpsiLeak");
}
//*************Saving the generated datasets in a workspace
RooWorkspace workspaceGen("workspaceGen", "workspaceGen");
workspaceGen.import(*dataGenSignalZeroGamma);
workspaceGen.import(*dataGenSignalOneGamma);
workspaceGen.import(*dataGenSignalTwoGamma);
workspaceGen.import(*dataGenComb);
workspaceGen.import(*dataGenPartReco);
if(nGenJpsiLeak>1) workspaceGen.import(*dataGenJpsiLeak);
workspaceGen.Write("", TObject::kOverwrite);
//delete workspace;
fw.Close();
delete dataGenSignalZeroGamma;
delete dataGenSignalOneGamma;
delete dataGenSignalTwoGamma;
delete dataGenComb;
delete dataGenPartReco;
if(nGenJpsiLeak>1) delete dataGenJpsiLeak;
delete GenSpecSignalZeroGamma;
delete GenSpecSignalOneGamma;
delete GenSpecSignalTwoGamma;
delete GenSpecComb;
delete GenSpecPartReco;
delete combPDF;
if(nGenJpsiLeak>1) delete GenSpecJpsiLeak;
delete histPdfSignalZeroGamma;
delete histPdfSignalOneGamma;
delete histPdfSignalTwoGamma;
delete histPdfPartReco;
if(nGenJpsiLeak>1) delete histPdfJpsiLeak;
}
int compute(RooFitResult* fit, int nbdata, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin,
double et_plateau, double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin,
bool draw, bool verbose)
{
// Extract fit parameters //
std::cout<<"erereo4"<<std::endl;
RooArgList param = fit->floatParsFinal() ;
std::cout<<"erereo6"<<std::endl;
double err[5] ;
double mu[5] ;
for(Int_t i = 0; i < param.getSize(); i++) {
RooRealVar* var = ( dynamic_cast<RooRealVar*>( param.at(i) ) );
//var->Print() ;
mu[i] = var->getVal() ;
err[i] = var->getError() ;
}
std::cout<<"erereo5"<<std::endl;
double min, max;
min = mu[0]-5*err[0] ;
if (mu[0]-5*err[0]<0) min = 0. ;
RooRealVar alpha("alpha","#alpha",mu[0],min,mu[0]+5*err[0]);
min = mu[1]-5*err[1] ;
if (mu[1]-5*err[1]<5) min = 5. ;
RooRealVar mean("mean","mean",mu[1],min,mu[1]+5*err[1]);
min = mu[2]-5*err[2] ;
if (mu[2]-5*err[2]<1) min = 1. ;
RooRealVar n("n","n",mu[2],min,mu[2]+5*err[2]);
min = mu[3]-5*err[3] ;
if (mu[3]-5*err[3]<0.6) min = 0.6 ;
max = mu[3]+5*err[3] ;
if (mu[3]+5*err[3]>1.) max = 1. ;
RooRealVar norm("norm","N",mu[3],min,max);
min = mu[4]-5*err[4] ;
if (mu[4]-5*err[4]<0.) min = 0. ;
RooRealVar sigma("sigma","#sigma",mu[4],min,mu[4]+5*err[4]);
RooRealVar xaxis("x","x",0,150) ;
// Create PDF and generate nbdata sets of CB parameters
RooAbsPdf* parabPdf = fit->createHessePdf(RooArgSet(norm,alpha,n,mean,sigma)) ;
RooDataSet* data = parabPdf->generate(RooArgSet(norm,alpha,n,mean,sigma),nbdata) ;
// Generate histo to extract error bar on efficiency(xaxis)
xaxis = et_plateau ;
cout << "Generate histo to extract error bars" << endl;
genHisto(nbdata, data, nEff, eff, et, et_errmax, et_errmin, eff_plateau, eff_plateau_errmax, eff_plateau_errmin,
xaxis, mean, sigma, alpha, n, norm, draw, verbose);
/* int genHisto(int nbdata, RooDataSet* data, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin,
double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin,
RooRealVar xaxis, RooRealVar mean, RooRealVar sigma, RooRealVar alpha, RooRealVar n, RooRealVar norm,
bool draw, bool verbose)
int compute(RooFitResult* fit, int nbdata, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin,
double et_plateau, double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin,
bool draw, bool verbose)
*/
return 1;
}
void rf509_wsinteractive()
{
// C r e a t e a n d f i l l w o r k s p a c e
// ------------------------------------------------
// Create a workspace named 'w'
// With CINT w could exports its contents to
// a same-name C++ namespace in CINT 'namespace w'.
// but this does not work anymore in CLING.
// so this tutorial is an example on how to
// change the code
RooWorkspace* w = new RooWorkspace("w",kTRUE) ;
// Fill workspace with p.d.f. and data in a separate function
fillWorkspace(*w) ;
// Print workspace contents
w->Print() ;
// this does not work anymore with CLING
// use normal workspace functionality
// U s e w o r k s p a c e c o n t e n t s
// ----------------------------------------------
// Old syntax to use the name space prefix operator to access the workspace contents
//
//RooDataSet* d = w::model.generate(w::x,1000) ;
//RooFitResult* r = w::model.fitTo(*d) ;
// use normal workspace methods
RooAbsPdf * model = w->pdf("model");
RooRealVar * x = w->var("x");
RooDataSet* d = model->generate(*x,1000) ;
RooFitResult* r = model->fitTo(*d) ;
// old syntax to access the variable x
// RooPlot* frame = w::x.frame() ;
RooPlot* frame = x->frame() ;
d->plotOn(frame) ;
// OLD syntax to ommit x::
// NB: The 'w::' prefix can be omitted if namespace w is imported in local namespace
// in the usual C++ way
//
// using namespace w;
// model.plotOn(frame) ;
// model.plotOn(frame,Components(bkg),LineStyle(kDashed)) ;
// new correct syntax
RooAbsPdf *bkg = w->pdf("bkg");
model->plotOn(frame);
model->plotOn(frame,Components(*bkg),LineStyle(kDashed)) ;
// Draw the frame on the canvas
new TCanvas("rf509_wsinteractive","rf509_wsinteractive",600,600) ;
gPad->SetLeftMargin(0.15) ; frame->GetYaxis()->SetTitleOffset(1.4) ; frame->Draw() ;
}
void rf104_classfactory()
{
// W r i t e c l a s s s k e l e t o n c o d e
// --------------------------------------------------
// Write skeleton p.d.f class with variable x,a,b
// To use this class,
// - Edit the file MyPdfV1.cxx and implement the evaluate() method in terms of x,a and b
// - Compile and link class with '.x MyPdfV1.cxx+'
//
RooClassFactory::makePdf("MyPdfV1","x,A,B") ;
// W i t h a d d e d i n i t i a l v a l u e e x p r e s s i o n
// ---------------------------------------------------------------------
// Write skeleton p.d.f class with variable x,a,b and given formula expression
// To use this class,
// - Compile and link class with '.x MyPdfV2.cxx+'
//
RooClassFactory::makePdf("MyPdfV2","x,A,B","","A*fabs(x)+pow(x-B,2)") ;
// W i t h a d d e d a n a l y t i c a l i n t e g r a l e x p r e s s i o n
// ---------------------------------------------------------------------------------
// Write skeleton p.d.f class with variable x,a,b, given formula expression _and_
// given expression for analytical integral over x
// To use this class,
// - Compile and link class with '.x MyPdfV3.cxx+'
//
RooClassFactory::makePdf("MyPdfV3","x,A,B","","A*fabs(x)+pow(x-B,2)",kTRUE,kFALSE,
"x:(A/2)*(pow(x.max(rangeName),2)+pow(x.min(rangeName),2))+(1./3)*(pow(x.max(rangeName)-B,3)-pow(x.min(rangeName)-B,3))") ;
// U s e i n s t a n c e o f c r e a t e d c l a s s
// ---------------------------------------------------------
// Compile MyPdfV3 class (only when running in CINT)
gROOT->ProcessLineSync(".x MyPdfV3.cxx+") ;
// Create instance of MyPdfV3 class
RooRealVar a("a","a",1) ;
RooRealVar b("b","b",2,-10,10) ;
RooRealVar y("y","y",-10,10);
MyPdfV3 pdf("pdf","pdf",y,a,b) ;
// Generate toy data from pdf and plot data and p.d.f on frame
RooPlot* frame1 = y.frame(Title("Compiled class MyPdfV3")) ;
RooDataSet* data = pdf.generate(y,1000) ;
pdf.fitTo(*data) ;
data->plotOn(frame1) ;
pdf.plotOn(frame1) ;
// -----------------------------------------------------------------
// C o m p i l e d v e r s i o n o f e x a m p l e r f 1 0 3
// =================================================================
// Declare observable x
RooRealVar x("x","x",-20,20) ;
// The RooClassFactory::makePdfInstance() function performs code writing, compiling, linking
// and object instantiation in one go and can serve as a straight replacement of RooGenericPdf
RooRealVar alpha("alpha","alpha",5,0.1,10) ;
RooAbsPdf* genpdf = RooClassFactory::makePdfInstance("GenPdf","(1+0.1*fabs(x)+sin(sqrt(fabs(x*alpha+0.1))))",RooArgSet(x,alpha)) ;
// Generate a toy dataset from the interpreted p.d.f
RooDataSet* data2 = genpdf->generate(x,50000) ;
// Fit the interpreted p.d.f to the generated data
genpdf->fitTo(*data2) ;
// Make a plot of the data and the p.d.f overlaid
RooPlot* frame2 = x.frame(Title("Compiled version of pdf of rf103")) ;
data2->plotOn(frame2) ;
genpdf->plotOn(frame2) ;
// Draw all frames on a canvas
TCanvas* c = new TCanvas("rf104_classfactory","rf104_classfactory",800,400) ;
c->Divide(2) ;
c->cd(1) ; gPad->SetLeftMargin(0.15) ; frame1->GetYaxis()->SetTitleOffset(1.4) ; frame1->Draw() ;
c->cd(2) ; gPad->SetLeftMargin(0.15) ; frame2->GetYaxis()->SetTitleOffset(1.4) ; frame2->Draw() ;
}
void LeptonPreselectionCMG( PreselType type, RooWorkspace * w ) {
const Options & opt = Options::getInstance();
if (type == ELE)
cout << "Running Electron Preselection :" << endl;
else if (type == MU)
cout << "Running Muon Preselection :" << endl;
else if (type == EMU)
cout << "Running Electron-Muon Preselection() ..." << endl;
else if (type == PHOT)
cout << "Running Photon Preselection :" << endl;
string systVar;
try {
systVar = opt.checkStringOption("SYSTEMATIC_VAR");
} catch (const std::string & exc) {
cout << exc << endl;
}
if (systVar == "NONE")
systVar.clear();
#ifdef CMSSWENV
JetCorrectionUncertainty jecUnc("Summer13_V4_MC_Uncertainty_AK5PFchs.txt");
#endif
string inputDir = opt.checkStringOption("INPUT_DIR");
string outputDir = opt.checkStringOption("OUTPUT_DIR");
string sampleName = opt.checkStringOption("SAMPLE_NAME");
string inputFile = inputDir + '/' + sampleName + ".root";
cout << "\tInput file: " << inputFile << endl;
bool isSignal = opt.checkBoolOption("SIGNAL");
TGraph * higgsW = 0;
TGraph * higgsI = 0;
if (isSignal) {
double higgsM = opt.checkDoubleOption("HIGGS_MASS");
if (higgsM >= 400) {
string dirName = "H" + double2string(higgsM);
bool isVBF = opt.checkBoolOption("VBF");
string lshapeHistName = "cps";
string intHistName = "nominal";
if (systVar == "LSHAPE_UP") {
intHistName = "up";
} else if (systVar == "LSHAPE_DOWN") {
intHistName = "down";
}
if (isVBF) {
TFile weightFile("VBF_LineShapes.root");
higgsW = (TGraph *) ( (TDirectory *) weightFile.Get(dirName.c_str()))->Get( lshapeHistName.c_str() )->Clone();
} else {
TFile weightFile("GG_LineShapes.root");
higgsW = (TGraph *) ( (TDirectory *) weightFile.Get(dirName.c_str()))->Get( lshapeHistName.c_str() )->Clone();
TFile interfFile("newwgts_interf.root");
higgsI = (TGraph *) ( (TDirectory *) interfFile.Get(dirName.c_str()))->Get( intHistName.c_str() )->Clone();
}
}
}
TFile * file = new TFile( inputFile.c_str() );
if (!file->IsOpen())
throw string("ERROR: Can't open the file: " + inputFile + "!");
TDirectory * dir = (TDirectory *) file->Get("dataAnalyzer");
TH1D * nEvHisto = (TH1D *) dir->Get("cutflow");
TH1D * puHisto = (TH1D *) dir->Get("pileup");
TTree * tree = ( TTree * ) dir->Get( "data" );
Event ev( tree );
const int * runP = ev.getSVA<int>("run");
const int * lumiP = ev.getSVA<int>("lumi");
const int * eventP = ev.getSVA<int>("event");
const bool * trigBits = ev.getAVA<bool>("t_bits");
const int * trigPres = ev.getAVA<int>("t_prescale");
const float * metPtA = ev.getAVA<float>("met_pt");
const float * metPhiA = ev.getAVA<float>("met_phi");
const float * rhoP = ev.getSVA<float>("rho");
const float * rho25P = ev.getSVA<float>("rho25");
const int * nvtxP = ev.getSVA<int>("nvtx");
const int * niP = ev.getSVA<int>("ngenITpu");
#ifdef PRINTEVENTS
string eventFileName;
if (type == ELE)
eventFileName = "events_ele.txt";
else if (type == MU)
eventFileName = "events_mu.txt";
else if (type == EMU)
eventFileName = "events_emu.txt";
EventPrinter evPrint(ev, type, eventFileName);
evPrint.readInEvents("diff.txt");
evPrint.printElectrons();
evPrint.printMuons();
evPrint.printZboson();
evPrint.printJets();
evPrint.printHeader();
#endif
string outputFile = outputDir + '/' + sampleName;
if (systVar.size())
outputFile += ('_' + systVar);
if (type == ELE)
outputFile += "_elePresel.root";
else if (type == MU)
outputFile += "_muPresel.root";
else if (type == EMU)
outputFile += "_emuPresel.root";
else if (type == PHOT)
outputFile += "_phPresel.root";
cout << "\tOutput file: " << outputFile << endl;
TFile * out = new TFile( outputFile.c_str(), "recreate" );
TH1D * outNEvHisto = new TH1D("nevt", "nevt", 1, 0, 1);
outNEvHisto->SetBinContent(1, nEvHisto->GetBinContent(1));
outNEvHisto->Write("nevt");
TH1D * outPuHisto = new TH1D( *puHisto );
outPuHisto->Write("pileup");
std::vector< std::tuple<std::string, std::string> > eleVars;
eleVars.push_back( std::make_tuple("ln_px", "F") );
eleVars.push_back( std::make_tuple("ln_py", "F") );
eleVars.push_back( std::make_tuple("ln_pz", "F") );
eleVars.push_back( std::make_tuple("ln_en", "F") );
eleVars.push_back( std::make_tuple("ln_idbits", "I") );
eleVars.push_back( std::make_tuple("ln_d0", "F") );
eleVars.push_back( std::make_tuple("ln_dZ", "F") );
eleVars.push_back( std::make_tuple("ln_nhIso03", "F") );
eleVars.push_back( std::make_tuple("ln_gIso03", "F") );
eleVars.push_back( std::make_tuple("ln_chIso03", "F") );
eleVars.push_back( std::make_tuple("ln_trkLostInnerHits", "F") );
std::vector< std::tuple<std::string, std::string> > addEleVars;
addEleVars.push_back( std::make_tuple("egn_sceta", "F") );
addEleVars.push_back( std::make_tuple("egn_detain", "F") );
addEleVars.push_back( std::make_tuple("egn_dphiin", "F") );
addEleVars.push_back( std::make_tuple("egn_sihih", "F") );
addEleVars.push_back( std::make_tuple("egn_hoe", "F") );
addEleVars.push_back( std::make_tuple("egn_ooemoop", "F") );
addEleVars.push_back( std::make_tuple("egn_isConv", "B") );
std::vector< std::tuple<std::string, std::string> > muVars;
muVars.push_back( std::make_tuple("ln_px", "F") );
muVars.push_back( std::make_tuple("ln_py", "F") );
muVars.push_back( std::make_tuple("ln_pz", "F") );
muVars.push_back( std::make_tuple("ln_en", "F") );
muVars.push_back( std::make_tuple("ln_idbits", "I") );
muVars.push_back( std::make_tuple("ln_d0", "F") );
muVars.push_back( std::make_tuple("ln_dZ", "F") );
muVars.push_back( std::make_tuple("ln_nhIso04", "F") );
muVars.push_back( std::make_tuple("ln_gIso04", "F") );
muVars.push_back( std::make_tuple("ln_chIso04", "F") );
muVars.push_back( std::make_tuple("ln_puchIso04", "F") );
muVars.push_back( std::make_tuple("ln_trkchi2", "F") );
muVars.push_back( std::make_tuple("ln_trkValidPixelHits", "F") );
std::vector< std::tuple<std::string, std::string> > addMuVars;
addMuVars.push_back( std::make_tuple("mn_trkLayersWithMeasurement", "F") );
addMuVars.push_back( std::make_tuple("mn_pixelLayersWithMeasurement", "F") );
addMuVars.push_back( std::make_tuple("mn_innerTrackChi2", "F") );
addMuVars.push_back( std::make_tuple("mn_validMuonHits", "F") );
addMuVars.push_back( std::make_tuple("mn_nMatchedStations", "F") );
unsigned run;
unsigned lumi;
unsigned event;
double pfmet;
int nele;
int nmu;
int nsoftmu;
double l1pt;
double l1eta;
double l1phi;
double l2pt;
double l2eta;
double l2phi;
double zmass;
double zpt;
double zeta;
double mt;
int nsoftjet;
int nhardjet;
double maxJetBTag;
double minDeltaPhiJetMet;
double detajj;
double mjj;
int nvtx;
int ni;
int category;
double weight;
double hmass;
double hweight;
TTree * smallTree = new TTree("HZZ2l2nuAnalysis", "HZZ2l2nu Analysis Tree");
smallTree->Branch( "Run", &run, "Run/i" );
smallTree->Branch( "Lumi", &lumi, "Lumi/i" );
smallTree->Branch( "Event", &event, "Event/i" );
smallTree->Branch( "PFMET", &pfmet, "PFMET/D" );
smallTree->Branch( "NELE", &nele, "NELE/I" );
smallTree->Branch( "NMU", &nmu, "NMU/I" );
smallTree->Branch( "NSOFTMU", &nsoftmu, "NSOFTMU/I" );
smallTree->Branch( "L1PT", &l1pt, "L1PT/D" );
smallTree->Branch( "L1ETA", &l1eta, "L1ETA/D" );
smallTree->Branch( "L1PHI", &l1phi, "L1PHI/D" );
smallTree->Branch( "L2PT", &l2pt, "L2PT/D" );
smallTree->Branch( "L2ETA", &l2eta, "L2ETA/D" );
smallTree->Branch( "L2PHI", &l2phi, "L2PHI/D" );
smallTree->Branch( "ZMASS", &zmass, "ZMASS/D" );
smallTree->Branch( "ZPT", &zpt, "ZPT/D" );
smallTree->Branch( "ZETA", &zeta, "ZETA/D" );
smallTree->Branch( "MT", &mt, "MT/D" );
smallTree->Branch( "NSOFTJET", &nsoftjet, "NSOFTJET/I" );
smallTree->Branch( "NHARDJET", &nhardjet, "NHARDJET/I" );
smallTree->Branch( "MAXJETBTAG", &maxJetBTag, "MAXJETBTAG/D" );
smallTree->Branch( "MINDPJETMET", &minDeltaPhiJetMet, "MINDPJETMET/D" );
smallTree->Branch( "DETAJJ", &detajj, "DETAJJ/D" );
smallTree->Branch( "MJJ", &mjj, "MJJ/D" );
smallTree->Branch( "NVTX", &nvtx, "NVTX/I" );
smallTree->Branch( "nInter" , &ni, "nInter/I" );
smallTree->Branch( "CATEGORY", &category, "CATEGORY/I" );
smallTree->Branch( "Weight" , &weight, "Weight/D" );
smallTree->Branch( "HMASS", &hmass, "HMASS/D" );
smallTree->Branch( "HWEIGHT", &hweight, "HWEIGHT/D" );
bool isData = opt.checkBoolOption("DATA");
unsigned long nentries = tree->GetEntries();
RooDataSet * events = nullptr;
PhotonPrescale photonPrescales;
vector<int> thresholds;
if (type == PHOT) {
if (w == nullptr)
throw string("ERROR: No mass peak pdf!");
RooRealVar * zmass = w->var("mass");
zmass->setRange(76.0, 106.0);
RooAbsPdf * pdf = w->pdf("massPDF");
events = pdf->generate(*zmass, nentries);
photonPrescales.addTrigger("HLT_Photon36_R9Id90_HE10_Iso40_EBOnly", 36, 3, 7);
photonPrescales.addTrigger("HLT_Photon50_R9Id90_HE10_Iso40_EBOnly", 50, 5, 8);
photonPrescales.addTrigger("HLT_Photon75_R9Id90_HE10_Iso40_EBOnly", 75, 7, 9);
photonPrescales.addTrigger("HLT_Photon90_R9Id90_HE10_Iso40_EBOnly", 90, 10, 10);
}
TH1D ptSpectrum("ptSpectrum", "ptSpectrum", 200, 55, 755);
ptSpectrum.Sumw2();
unordered_set<EventAdr> eventsSet;
for ( unsigned long iEvent = 0; iEvent < nentries; iEvent++ ) {
// if (iEvent < 6060000)
// continue;
if ( iEvent % 10000 == 0) {
cout << string(40, '\b');
cout << setw(10) << iEvent << " / " << setw(10) << nentries << " done ..." << std::flush;
}
tree->GetEntry( iEvent );
run = -999;
lumi = -999;
event = -999;
pfmet = -999;
nele = -999;
nmu = -999;
nsoftmu = -999;
l1pt = -999;
l1eta = -999;
l1phi = -999;
l2pt = -999;
l2eta = -999;
l2phi = -999;
zmass = -999;
zpt = -999;
zeta = -999;
mt = -999;
nsoftjet = -999;
nhardjet = -999;
maxJetBTag = -999;
minDeltaPhiJetMet = -999;
detajj = -999;
mjj = -999;
nvtx = -999;
ni = -999;
weight = -999;
category = -1;
hmass = -999;
hweight = -999;
run = *runP;
lumi = *lumiP;
event = *eventP;
EventAdr tmp(run, lumi, event);
if (eventsSet.find( tmp ) != eventsSet.end()) {
continue;
}
eventsSet.insert( tmp );
if (type == ELE && isData) {
if (trigBits[0] != 1 || trigPres[0] != 1)
continue;
}
if (type == MU && isData) {
if ( (trigBits[2] != 1 || trigPres[2] != 1)
&& (trigBits[3] != 1 || trigPres[3] != 1)
&& (trigBits[6] != 1 || trigPres[6] != 1)
)
continue;
}
if (type == EMU && isData) {
if ( (trigBits[4] != 1 || trigPres[4] != 1)
&& (trigBits[5] != 1 || trigPres[5] != 1)
)
continue;
}
vector<Electron> electrons = buildLeptonCollection<Electron, 11>(ev, eleVars, addEleVars);
vector<Muon> muons = buildLeptonCollection<Muon, 13>(ev, muVars, addMuVars);
float rho = *rhoP;
float rho25 = *rho25P;
vector<Electron> looseElectrons;
vector<Electron> selectedElectrons;
for (unsigned j = 0; j < electrons.size(); ++j) {
try {
TLorentzVector lv = electrons[j].lorentzVector();
if (
lv.Pt() > 10 &&
fabs(lv.Eta()) < 2.5 &&
!electrons[j].isInCrack() &&
electrons[j].passesVetoID() &&
electrons[j].isPFIsolatedLoose(rho25)
) {
looseElectrons.push_back(electrons[j]);
}
if (
lv.Pt() > 20 &&
fabs(lv.Eta()) < 2.5 &&
!electrons[j].isInCrack() &&
electrons[j].passesMediumID() &&
electrons[j].isPFIsolatedMedium(rho25)
) {
selectedElectrons.push_back(electrons[j]);
}
} catch (const string & exc) {
cout << exc << endl;
cout << "run = " << run << endl;
cout << "lumi = " << lumi << endl;
cout << "event = " << event << endl;
}
}
vector<Muon> looseMuons;
vector<Muon> softMuons;
vector<Muon> selectedMuons;
for (unsigned j = 0; j < muons.size(); ++j) {
TLorentzVector lv = muons[j].lorentzVector();
if (
lv.Pt() > 10 &&
fabs(lv.Eta()) < 2.4 &&
muons[j].isLooseMuon() &&
muons[j].isPFIsolatedLoose()
) {
looseMuons.push_back(muons[j]);
} else if (
lv.Pt() > 3 &&
fabs(lv.Eta()) < 2.4 &&
muons[j].isSoftMuon()
) {
softMuons.push_back(muons[j]);
}
if (
lv.Pt() > 20 &&
fabs(lv.Eta()) < 2.4 &&
muons[j].isTightMuon() &&
muons[j].isPFIsolatedTight()
) {
selectedMuons.push_back(muons[j]);
}
}
vector<Lepton> looseLeptons;
for (unsigned i = 0; i < looseElectrons.size(); ++i)
looseLeptons.push_back(looseElectrons[i]);
for (unsigned i = 0; i < looseMuons.size(); ++i)
looseLeptons.push_back(looseMuons[i]);
for (unsigned i = 0; i < softMuons.size(); ++i)
looseLeptons.push_back(softMuons[i]);
#ifdef PRINTEVENTS
evPrint.setElectronCollection(selectedElectrons);
evPrint.setMuonCollection(selectedMuons);
#endif
vector<Photon> photons = selectPhotonsCMG( ev );
vector<Photon> selectedPhotons;
for (unsigned i = 0; i < photons.size(); ++i) {
if (photons[i].isSelected(rho) && photons[i].lorentzVector().Pt() > 55)
selectedPhotons.push_back( photons[i] );
}
if (type == PHOT) {
vector<Electron> tmpElectrons;
for (unsigned i = 0; i < selectedPhotons.size(); ++i) {
TLorentzVector phVec = selectedPhotons[i].lorentzVector();
for (unsigned j = 0; j < looseElectrons.size(); ++j) {
TLorentzVector elVec = looseElectrons[j].lorentzVector();
double dR = deltaR(phVec.Eta(), phVec.Phi(), elVec.Eta(), elVec.Phi());
if ( dR > 0.05 )
tmpElectrons.push_back( looseElectrons[j] );
}
}
looseElectrons = tmpElectrons;
}
string leptonsType;
Lepton * selectedLeptons[2] = {0};
if (type == ELE) {
if (selectedElectrons.size() < 2) {
continue;
} else {
selectedLeptons[0] = &selectedElectrons[0];
selectedLeptons[1] = &selectedElectrons[1];
}
} else if (type == MU) {
if (selectedMuons.size() < 2) {
continue;
} else {
selectedLeptons[0] = &selectedMuons[0];
selectedLeptons[1] = &selectedMuons[1];
}
} else if (type == EMU) {
if (selectedElectrons.size() < 1 || selectedMuons.size() < 1) {
continue;
} else {
selectedLeptons[0] = &selectedElectrons[0];
selectedLeptons[1] = &selectedMuons[0];
}
} else if (type == PHOT) {
if (selectedPhotons.size() != 1) {
continue;
}
}
nele = looseElectrons.size();
nmu = looseMuons.size();
nsoftmu = softMuons.size();
TLorentzVector Zcand;
if (type == ELE || type == MU || type == EMU) {
TLorentzVector lep1 = selectedLeptons[0]->lorentzVector();
TLorentzVector lep2 = selectedLeptons[1]->lorentzVector();
if (lep2.Pt() > lep1.Pt() && type != EMU) {
TLorentzVector temp = lep1;
lep1 = lep2;
lep2 = temp;
}
l1pt = lep1.Pt();
l1eta = lep1.Eta();
l1phi = lep1.Phi();
l2pt = lep2.Pt();
l2eta = lep2.Eta();
l2phi = lep2.Phi();
Zcand = lep1 + lep2;
zmass = Zcand.M();
} else if (type == PHOT) {
Zcand = selectedPhotons[0].lorentzVector();
zmass = events->get(iEvent)->getRealValue("mass");
}
zpt = Zcand.Pt();
zeta = Zcand.Eta();
if (type == PHOT) {
unsigned idx = photonPrescales.getIndex(zpt);
if (trigBits[idx])
weight = trigPres[idx];
else
continue;
ptSpectrum.Fill(zpt, weight);
}
TLorentzVector met;
met.SetPtEtaPhiM(metPtA[0], 0.0, metPhiA[0], 0.0);
TLorentzVector clusteredFlux;
unsigned mode = 0;
if (systVar == "JES_UP")
mode = 1;
else if (systVar == "JES_DOWN")
mode = 2;
TLorentzVector jecCorr;
#ifdef CMSSWENV
vector<Jet> jetsAll = selectJetsCMG( ev, looseLeptons, jecUnc, &jecCorr, mode );
#else
vector<Jet> jetsAll = selectJetsCMG( ev, looseLeptons, &jecCorr, mode );
#endif
met -= jecCorr;
mode = 0;
if (systVar == "JER_UP")
mode = 1;
else if (systVar == "JER_DOWN")
mode = 2;
TLorentzVector smearCorr = smearJets( jetsAll, mode );
if (isData && smearCorr != TLorentzVector())
throw std::string("Jet smearing corrections different from zero in DATA!");
met -= smearCorr;
vector<Jet> selectedJets;
for (unsigned i = 0; i < jetsAll.size(); ++i) {
if (
jetsAll[i].lorentzVector().Pt() > 10
&& fabs(jetsAll[i].lorentzVector().Eta()) < 4.7
&& jetsAll[i].passesPUID() &&
jetsAll[i].passesPFLooseID()
)
selectedJets.push_back( jetsAll[i] );
}
if (type == PHOT) {
vector<Jet> tmpJets;
for (unsigned i = 0; i < selectedPhotons.size(); ++i) {
TLorentzVector phVec = selectedPhotons[i].lorentzVector();
for (unsigned j = 0; j < selectedJets.size(); ++j) {
TLorentzVector jVec = selectedJets[j].lorentzVector();
double dR = deltaR(phVec.Eta(), phVec.Phi(), jVec.Eta(), jVec.Phi());
if ( dR > 0.4 )
tmpJets.push_back( selectedJets[j] );
}
}
selectedJets = tmpJets;
}
if (systVar == "UMET_UP" || systVar == "UMET_DOWN") {
for (unsigned i = 0; i < jetsAll.size(); ++i)
clusteredFlux += jetsAll[i].lorentzVector();
for (unsigned i = 0; i < looseElectrons.size(); ++i)
clusteredFlux += looseElectrons[i].lorentzVector();
for (unsigned i = 0; i < looseMuons.size(); ++i)
clusteredFlux += looseMuons[i].lorentzVector();
TLorentzVector unclusteredFlux = -(met + clusteredFlux);
if (systVar == "UMET_UP")
unclusteredFlux *= 1.1;
else
unclusteredFlux *= 0.9;
met = -(clusteredFlux + unclusteredFlux);
}
if (systVar == "LES_UP" || systVar == "LES_DOWN") {
TLorentzVector diff;
double sign = 1.0;
if (systVar == "LES_DOWN")
sign = -1.0;
for (unsigned i = 0; i < looseElectrons.size(); ++i) {
TLorentzVector tempEle = looseElectrons[i].lorentzVector();
if (looseElectrons[i].isEB())
diff += sign * 0.02 * tempEle;
else
diff += sign * 0.05 * tempEle;
}
for (unsigned i = 0; i < looseMuons.size(); ++i)
diff += sign * 0.01 * looseMuons[i].lorentzVector();
met -= diff;
}
pfmet = met.Pt();
double px = met.Px() + Zcand.Px();
double py = met.Py() + Zcand.Py();
double pt2 = px * px + py * py;
double e = sqrt(zpt * zpt + zmass * zmass) + sqrt(pfmet * pfmet + zmass * zmass);
double mt2 = e * e - pt2;
mt = (mt2 > 0) ? sqrt(mt2) : 0;
vector<Jet> hardjets;
vector<Jet> softjets;
maxJetBTag = -999;
minDeltaPhiJetMet = 999;
for ( unsigned j = 0; j < selectedJets.size(); ++j ) {
TLorentzVector jet = selectedJets[j].lorentzVector();
if ( jet.Pt() > 30 ) {
hardjets.push_back( selectedJets[j] );
}
if ( jet.Pt() > 15 )
softjets.push_back( selectedJets[j] );
}
nhardjet = hardjets.size();
nsoftjet = softjets.size();
// if ( type == PHOT && nsoftjet == 0 )
// continue;
if (nhardjet > 1) {
sort(hardjets.begin(), hardjets.end(), [](const Jet & a, const Jet & b) {
return a.lorentzVector().Pt() > b.lorentzVector().Pt();
});
TLorentzVector jet1 = hardjets[0].lorentzVector();
TLorentzVector jet2 = hardjets[1].lorentzVector();
const double maxEta = max( jet1.Eta(), jet2.Eta() );
const double minEta = min( jet1.Eta(), jet2.Eta() );
bool passCJV = true;
for (unsigned j = 2; j < hardjets.size(); ++j) {
double tmpEta = hardjets[j].lorentzVector().Eta();
if ( tmpEta > minEta && tmpEta < maxEta )
passCJV = false;
}
const double tmpDelEta = std::fabs(jet2.Eta() - jet1.Eta());
TLorentzVector diJetSystem = jet1 + jet2;
const double tmpMass = diJetSystem.M();
if ( type == PHOT) {
if (passCJV && tmpDelEta > 4.0 && tmpMass > 500 && zeta > minEta && maxEta > zeta) {
detajj = tmpDelEta;
mjj = tmpMass;
}
} else {
if (passCJV && tmpDelEta > 4.0 && tmpMass > 500 && l1eta > minEta && l2eta > minEta && maxEta > l1eta && maxEta > l2eta) {
detajj = tmpDelEta;
mjj = tmpMass;
}
}
}
category = evCategory(nhardjet, nsoftjet, detajj, mjj, type == PHOT);
minDeltaPhiJetMet = 10;
for ( unsigned j = 0; j < hardjets.size(); ++j ) {
TLorentzVector jet = hardjets[j].lorentzVector();
if ( hardjets[j].getVarF("jn_jp") > maxJetBTag && fabs(jet.Eta()) < 2.5 )
maxJetBTag = hardjets[j].getVarF("jn_jp");
double tempDelPhiJetMet = deltaPhi(met.Phi(), jet.Phi());
if ( tempDelPhiJetMet < minDeltaPhiJetMet )
minDeltaPhiJetMet = tempDelPhiJetMet;
}
nvtx = *nvtxP;
if (isData)
ni = -1;
else
ni = *niP;
if (isSignal) {
const int nMC = ev.getSVV<int>("mcn");
const int * mcID = ev.getAVA<int>("mc_id");
int hIdx = 0;
for (; hIdx < nMC; ++hIdx)
if (fabs(mcID[hIdx]) == 25)
break;
if (hIdx == nMC)
throw string("ERROR: Higgs not found in signal sample!");
float Hpx = ev.getAVV<float>("mc_px", hIdx);
float Hpy = ev.getAVV<float>("mc_py", hIdx);
float Hpz = ev.getAVV<float>("mc_pz", hIdx);
float Hen = ev.getAVV<float>("mc_en", hIdx);
TLorentzVector higgs;
higgs.SetPxPyPzE( Hpx, Hpy, Hpz, Hen );
hmass = higgs.M();
if (higgsW) {
hweight = higgsW->Eval(hmass);
if (higgsI)
hweight *= higgsI->Eval(hmass);
} else
hweight = 1;
}
if ( opt.checkBoolOption("ADDITIONAL_LEPTON_VETO") && (type == ELE || type == MU || type == EMU) && ((nele + nmu + nsoftmu) > 2) )
continue;
if ( opt.checkBoolOption("ADDITIONAL_LEPTON_VETO") && (type == PHOT) && ((nele + nmu + nsoftmu) > 0) )
continue;
if ( opt.checkBoolOption("ZPT_CUT") && zpt < 55 )
continue;
// for different background estimation methods different window should be applied:
// * sample for photons should have 76.0 < zmass < 106.0
// * sample for non-resonant background should not have this cut applied
if ( opt.checkBoolOption("TIGHT_ZMASS_CUT") && (type == ELE || type == MU) && (zmass < 76.0 || zmass > 106.0))
continue;
if ( opt.checkBoolOption("WIDE_ZMASS_CUT") && (type == ELE || type == MU) && (zmass < 76.0 || zmass > 106.0))
continue;
if ( opt.checkBoolOption("BTAG_CUT") && ( maxJetBTag > 0.264) )
continue;
if ( opt.checkBoolOption("DPHI_CUT") && ( minDeltaPhiJetMet < 0.5) )
continue;
#ifdef PRINTEVENTS
evPrint.setJetCollection(hardjets);
evPrint.setMET(met);
evPrint.setMT(mt);
string channelType;
if (type == ELE)
channelType = "ee";
else if (type == MU)
channelType = "mumu";
else if (type == EMU)
channelType = "emu";
if (category == 1)
channelType += "eq0jets";
else if (category == 2)
channelType += "geq1jets";
else
channelType += "vbf";
evPrint.setChannel(channelType);
unsigned bits = 0;
bits |= (0x7);
bits |= ((zmass > 76.0 && zmass < 106.0) << 3);
bits |= ((zpt > 55) << 4);
bits |= (((nele + nmu + nsoftmu) == 2) << 5);
bits |= ((maxJetBTag < 0.275) << 6);
bits |= ((minDeltaPhiJetMet > 0.5) << 7);
evPrint.setBits(bits);
evPrint.print();
#endif
smallTree->Fill();
}
cout << endl;
TCanvas canv("canv", "canv", 800, 600);
//effNum.Sumw2();
//effDen.Sumw2();
//effNum.Divide(&effDen);
//effNum.Draw();
canv.SetGridy();
canv.SetGridx();
//canv.SaveAs("triggEff.ps");
//canv.Clear();
ptSpectrum.SetMarkerStyle(20);
ptSpectrum.SetMarkerSize(0.5);
ptSpectrum.Draw("P0E");
//ptSpectrum.Draw("COLZ");
canv.SetLogy();
canv.SaveAs("ptSpectrum.ps");
delete file;
smallTree->Write("", TObject::kOverwrite);
delete smallTree;
delete out;
}