//put very small data entries in a binned dataset to avoid unphysical pdfs, specifically for H->ZZ->4l
RooDataSet* makeData(RooDataSet* orig, RooSimultaneous* simPdf, const RooArgSet* observables, RooRealVar* firstPOI, double mass, double& mu_min)
{
double max_soverb = 0;
mu_min = -10e9;
map<string, RooDataSet*> data_map;
firstPOI->setVal(0);
RooCategory* cat = (RooCategory*)&simPdf->indexCat();
TList* datalist = orig->split(*(RooAbsCategory*)cat, true);
TIterator* dataItr = datalist->MakeIterator();
RooAbsData* ds;
RooRealVar* weightVar = new RooRealVar("weightVar","weightVar",1);
while ((ds = (RooAbsData*)dataItr->Next()))
{
string typeName(ds->GetName());
cat->setLabel(typeName.c_str());
RooAbsPdf* pdf = simPdf->getPdf(typeName.c_str());
cout << "pdf: " << pdf << endl;
RooArgSet* obs = pdf->getObservables(observables);
cout << "obs: " << obs << endl;
RooArgSet obsAndWeight(*obs, *weightVar);
obsAndWeight.add(*cat);
stringstream datasetName;
datasetName << "newData_" << typeName;
RooDataSet* thisData = new RooDataSet(datasetName.str().c_str(),datasetName.str().c_str(), obsAndWeight, WeightVar(*weightVar));
RooRealVar* firstObs = (RooRealVar*)obs->first();
//int ibin = 0;
int nrEntries = ds->numEntries();
for (int ib=0;ib<nrEntries;ib++)
{
const RooArgSet* event = ds->get(ib);
const RooRealVar* thisObs = (RooRealVar*)event->find(firstObs->GetName());
firstObs->setVal(thisObs->getVal());
firstPOI->setVal(0);
double b = pdf->expectedEvents(*firstObs)*pdf->getVal(obs);
firstPOI->setVal(1);
double s = pdf->expectedEvents(*firstObs)*pdf->getVal(obs) - b;
if (s > 0)
{
mu_min = max(mu_min, -b/s);
double soverb = s/b;
if (soverb > max_soverb)
{
max_soverb = soverb;
cout << "Found new max s/b: " << soverb << " in pdf " << pdf->GetName() << " at m = " << thisObs->getVal() << endl;
}
}
if (b == 0 && s != 0)
{
cout << "Expecting non-zero signal and zero bg at m=" << firstObs->getVal() << " in pdf " << pdf->GetName() << endl;
}
if (s+b <= 0)
{
cout << "expecting zero" << endl;
continue;
}
double weight = ds->weight();
if ((typeName.find("ATLAS_H_4mu") != string::npos ||
typeName.find("ATLAS_H_4e") != string::npos ||
typeName.find("ATLAS_H_2mu2e") != string::npos ||
typeName.find("ATLAS_H_2e2mu") != string::npos) && fabs(firstObs->getVal() - mass) < 10 && weight == 0)
{
cout << "adding event: " << firstObs->getVal() << endl;
thisData->add(*event, pow(10., -9.));
}
else
{
//weight = max(pow(10.0, -9), weight);
thisData->add(*event, weight);
}
}
data_map[string(ds->GetName())] = (RooDataSet*)thisData;
}
RooDataSet* newData = new RooDataSet("newData","newData",RooArgSet(*observables, *weightVar),
Index(*cat), Import(data_map), WeightVar(*weightVar));
orig->Print();
newData->Print();
//newData->tree()->Scan("*");
return newData;
}
void setup(ModelConfig* mcInWs) {
RooAbsPdf* combPdf = mcInWs->GetPdf();
RooArgSet mc_obs = *mcInWs->GetObservables();
RooArgSet mc_globs = *mcInWs->GetGlobalObservables();
RooArgSet mc_nuis = *mcInWs->GetNuisanceParameters();
// pair the nuisance parameter to the global observable
RooArgSet mc_nuis_tmp = mc_nuis;
RooArgList nui_list;
RooArgList glob_list;
RooArgSet constraint_set_tmp(*combPdf->getAllConstraints(mc_obs, mc_nuis_tmp, false));
RooArgSet constraint_set;
int counter_tmp = 0;
unfoldConstraints(constraint_set_tmp, constraint_set, mc_obs, mc_nuis_tmp, counter_tmp);
TIterator* cIter = constraint_set.createIterator();
RooAbsArg* arg;
while ((arg = (RooAbsArg*)cIter->Next())) {
RooAbsPdf* pdf = (RooAbsPdf*)arg;
if (!pdf) continue;
// pdf->Print();
TIterator* nIter = mc_nuis.createIterator();
RooRealVar* thisNui = NULL;
RooAbsArg* nui_arg;
while ((nui_arg = (RooAbsArg*)nIter->Next())) {
if (pdf->dependsOn(*nui_arg)) {
thisNui = (RooRealVar*)nui_arg;
break;
}
}
delete nIter;
// need this incase the observable isn't fundamental.
// in this case, see which variable is dependent on the nuisance parameter and use that.
RooArgSet* components = pdf->getComponents();
// components->Print();
components->remove(*pdf);
if (components->getSize()) {
TIterator* itr1 = components->createIterator();
RooAbsArg* arg1;
while ((arg1 = (RooAbsArg*)itr1->Next())) {
TIterator* itr2 = components->createIterator();
RooAbsArg* arg2;
while ((arg2 = (RooAbsArg*)itr2->Next())) {
if (arg1 == arg2) continue;
if (arg2->dependsOn(*arg1)) {
components->remove(*arg1);
}
}
delete itr2;
}
delete itr1;
}
if (components->getSize() > 1) {
cout << "ERROR::Couldn't isolate proper nuisance parameter" << endl;
return;
}
else if (components->getSize() == 1) {
thisNui = (RooRealVar*)components->first();
}
TIterator* gIter = mc_globs.createIterator();
RooRealVar* thisGlob = NULL;
RooAbsArg* glob_arg;
while ((glob_arg = (RooAbsArg*)gIter->Next())) {
if (pdf->dependsOn(*glob_arg)) {
thisGlob = (RooRealVar*)glob_arg;
break;
}
}
delete gIter;
if (!thisNui || !thisGlob) {
cout << "WARNING::Couldn't find nui or glob for constraint: " << pdf->GetName() << endl;
//return;
continue;
}
// cout << "Pairing nui: " << thisNui->GetName() << ", with glob: " << thisGlob->GetName() << ", from constraint: " << pdf->GetName() << endl;
nui_list.add(*thisNui);
glob_list.add(*thisGlob);
if (string(pdf->ClassName()) == "RooPoisson") {
double minVal = max(0.0, thisGlob->getVal() - 8*sqrt(thisGlob->getVal()));
double maxVal = max(10.0, thisGlob->getVal() + 8*sqrt(thisGlob->getVal()));
thisNui->setRange(minVal, maxVal);
thisGlob->setRange(minVal, maxVal);
}
else if (string(pdf->ClassName()) == "RooGaussian") {
thisNui->setRange(-7, 7);
thisGlob->setRange(-10, 10);
}
// thisNui->Print();
// thisGlob->Print();
}
delete cIter;
}
void statTest(double mu_pe, double mu_hyp, ModelConfig *mc , RooDataSet *data ){
int nToyMC = 5;
// set roofit seed
RooRandom::randomGenerator()->SetSeed();
cout << endl;
cout << endl;
cout << "Will generate " << nToyMC << " pseudo-experiments for : " << endl;
cout << " - mu[pseudo-data] = " << mu_pe << endl;
cout << " - mu[stat-test] = " << mu_hyp << endl;
cout << endl;
// Check number of POI (for Wald approx)
RooArgSet *ParamOfInterest = (RooArgSet*) mc->GetParametersOfInterest();
int nPOI = ParamOfInterest->getSize();
if(nPOI>1){
cout <<"not sure what to do with other parameters of interest, but here are their values"<<endl;
mc->GetParametersOfInterest()->Print("v");
}
RooRealVar* firstPOI = (RooRealVar*) ParamOfInterest->first();
RooAbsPdf *simPdf = (mc->GetPdf());
//PrintAllParametersAndValues( *mc->GetGlobalObservables() );
//PrintAllParametersAndValues( *mc->GetObservables() );
firstPOI->setVal(0.0); // FIXME
//simPdf->fitTo( *data, Hesse(kTRUE), Minos(kTRUE), PrintLevel(1) );
simPdf->fitTo( *data );
// set up the sampler
ToyMCSampler sampler;
sampler.SetPdf(*mc->GetPdf());
sampler.SetObservables(*mc->GetObservables());
sampler.SetNToys(nToyMC);
sampler.SetGlobalObservables(*mc->GetGlobalObservables());
sampler.SetParametersForTestStat(*mc->GetParametersOfInterest());
RooArgSet* poiset = dynamic_cast<RooArgSet*>(ParamOfInterest->Clone());
// only unconditional fit
MinNLLTestStat *minNll = new MinNLLTestStat(*mc->GetPdf());
minNll->EnableDetailedOutput(true);
sampler.AddTestStatistic(minNll);
// enable PROOF if desired
//ProofConfig pc(*w, 8, "workers=8", kFALSE);
//sampler.SetProofConfig(&pc);
// evaluate the test statistics - this is where most of our time will be spent
cout << "Generating " << nToyMC << " toys...this will take a few minutes" << endl;
TStopwatch *mn_t = new TStopwatch;
mn_t->Start();
RooDataSet* sd = sampler.GetSamplingDistributions(*poiset);
cout << "Toy generation complete :" << endl;
// stop timing
mn_t->Stop();
cout << " total CPU time: " << mn_t->CpuTime() << endl;
cout << " total real time: " << mn_t->RealTime() << endl;
// now sd contains all information about our test statistics, including detailed output
// we might eg. want to explore the results either directly, or first converting to a TTree
// do the conversion
TFile f("mytoys.root", "RECREATE");
TTree *toyTree = RooStats::GetAsTTree("toyTree", "TTree created from test statistics", *sd);
// save result to file, but in general do whatever you like
f.cd();
toyTree->Write();
f.Close();
/*
TFile* tmpFile = new TFile("mytoys.root","READ");
TTree* myTree = (TTree*)tmpFile->Get("toyTree");
// get boundaries for histograms
TIter nextLeaf( (myTree->GetListOfLeaves())->MakeIterator() );
TObject* leafObj(0);
map<TString, float> xMaxs;
map<TString, float> xMins;
for(int i(0); i<myTree->GetEntries(); i++) {
myTree->GetEntry(i);
nextLeaf = ( (myTree->GetListOfLeaves())->MakeIterator() );
while( (leafObj = nextLeaf.Next()) ) {
TString name(leafObj->GetName());
float value(myTree->GetLeaf( leafObj->GetName() )->GetValue());
if(value > xMaxs[name]) { xMaxs[name] = value; }
if(value < xMins[name]) { xMins[name] = value; }
} // loop over leaves
} // loop over tree entries
// plot everything in the tree
myTree->GetEntry(0);
nextLeaf = ( (myTree->GetListOfLeaves())->MakeIterator() );
leafObj = 0;
// make a histogram per leaf
map<TString, TH1F*> hists;
myTree->GetEntry(0);
while( (leafObj = nextLeaf.Next()) ) {
if(!leafObj) { continue; }
//cout << leafObj->GetName() << endl;
TString name(leafObj->GetName());
// special ones : fit related things
if(name.Contains("covQual")) { hists[name] = new TH1F(name,name,5,0,5); continue; }
if(name.Contains("fitStatus")) { hists[name] = new TH1F(name,name,5,0,5); continue; }
int nbin(500);
float histMin( xMins[name] - 0.1*fabs(xMins[name]) );
float histMax( xMaxs[name] + 0.1*fabs(xMaxs[name]) );
if(name.Contains("ATLAS_norm")) { // floating normalization factors
histMin = 0; histMax = 10;
}
else if(name.Contains("gamma_stat")) { // statistical nus param
if(name.Contains("globObs")) { // get custom range for sampling
histMin = int( xMins[name] - 0.1*fabs(xMins[name]) );
histMax = int( xMaxs[name] + 0.1*fabs(xMaxs[name]) );
} // use small range for pull and error
else { nbin = 100; histMin = 0.0; histMax = 2.0; }
}
else if(name.Contains("_err")) { // errors on nus param
nbin = 100; histMin = 0.0; histMax = 2.0;
}
else if(name.Contains("fitCond") || name.Contains("fitUncond") || name.Contains("globObs")) { // fit pulls
nbin = 500; histMin = -5; histMax = 5;
}
hists[name] = new TH1F(name,name,nbin,histMin,histMax);
} // loop over leaves to declare histos
// loop over entries and fill histograms
for(int i(0); i<myTree->GetEntries(); i++) {
myTree->GetEntry(i);
nextLeaf = ( (myTree->GetListOfLeaves())->MakeIterator() );
while( (leafObj = nextLeaf.Next()) ) {
TString name(leafObj->GetName());
if(hists.find(name) == hists.end()) { continue; }
hists[name]->Fill( myTree->GetLeaf( leafObj->GetName() )->GetValue() );
} // loop over leaves
} // loop over tree entries
// overflow and underflow
for(map<TString,TH1F*>::iterator ihist(hists.begin()); ihist!=hists.end(); ihist++) {
if(ihist->second->GetBinContent(0)>0) {
ihist->second->SetBinContent(1, ihist->second->GetBinContent(0) + ihist->second->GetBinContent(1) );
// fix err
}
int nBinx = ihist->second->GetNbinsX();
if(ihist->second->GetBinContent(nBinx)>0) {
ihist->second->SetBinContent(nBinx-1, ihist->second->GetBinContent(nBinx) + ihist->second->GetBinContent(nBinx-1) );
// fix err
}
}
// save the results
TString dirName(OutputDir+"/PlotsStatisticalTest/GlobalFit");
if(drawPlots) {
system(TString("mkdir -vp "+dirName));
}
TCanvas* canvas = new TCanvas("pulls");
TLegend *leg = new TLegend(0.67, 0.64, 0.87, 0.86);
LegendStyle(leg);
for(map<TString,TH1F*>::iterator ihist(hists.begin()); ihist!=hists.end(); ihist++) {
if( (ihist->first).Contains("fitCond_") ) { continue; } // skip unconditional fit - get it explicitly
canvas->Clear();
leg->Clear();
TString niceName(ihist->first);
niceName.ReplaceAll("fitUncond_","");
//niceName.ReplaceAll("SD_TS0_",""); // not good if have multiple test statistics
// conditional fit information
ihist->second->SetLineColor(kGray+2);
ihist->second->SetTitle(niceName);
ihist->second->SetLineStyle(kSolid);
ihist->second->SetLineWidth(2);
if((ihist->first).Contains("fit") && !(ihist->first).Contains("_err")
&& !(ihist->first).Contains("Qual") && !(ihist->first).Contains("Status")) {
ihist->second->Rebin(4);
}
// ihist->second->GetXaxis()->SetTitle("");
// ihist->second->GetYaxis()->SetTitle("");
if(niceName.Contains("globObs")) {
leg->AddEntry( ihist->second, "Sampling", "l" ); // add value of mu
} else {
leg->AddEntry( ihist->second, "Unconditional Fit", "l" ); // add value of mu
}
TString condName(ihist->first);
condName.ReplaceAll("fitUncond","fitCond");
// uncomditional fit information
if(hists.find(condName) != hists.end() && condName != ihist->first) {
hists[condName]->SetLineColor(kGray+2);
hists[condName]->SetLineStyle(kDashed);
hists[condName]->SetLineWidth(2);
if(!(ihist->first).Contains("_err")) { hists[condName]->Rebin(4); }
leg->AddEntry( hists[condName], "Conditional Fit", "l" );
if( hists[condName]->GetMaximum() > ihist->second->GetMaximum() ) {
ihist->second->SetMaximum( hists[condName]->GetMaximum() );
}
}
ihist->second->SetMaximum( 1.2 * ihist->second->GetMaximum() );
canvas->cd();
ihist->second->Draw();
leg->Draw();
if(hists[condName] && condName != ihist->first) { hists[condName]->Draw("same"); }
if(drawPlots) {
canvas->Print(dirName+"/"+niceName+".eps");
canvas->Print(dirName+"/"+niceName+".png");
}
MainDirStatTest->cd();
canvas->Write();
gROOT->cd();
}
*/
return;
}
void Plot_BG(TString wsname)
{
//get the stuff from the workspace:
TFile* file=TFile::Open(wsname);
RooWorkspace* ws = (RooWorkspace*)file->Get("combined");
mc = (ModelConfig*)ws->obj("ModelConfig");
data = ws->data("obsData");
RooSimultaneous* simPdf=(RooSimultaneous*)(mc->GetPdf());
RooAbsReal* nll=simPdf->createNLL(*data);
//run on channels
RooCategory* chanCat = (RooCategory*) (&simPdf->indexCat());
TIterator* iterat = chanCat->typeIterator() ;
RooCatType* ttype;
bool stop = kFALSE;
while ((ttype = (RooCatType*) iterat->Next())&&!stop)
{
// bool toggle to run on one channel or all
stop = kTRUE;
RooAbsPdf *pdf_state = simPdf->getPdf(ttype->GetName()) ;
RooArgSet *obstmp = pdf_state->getObservables( *mc->GetObservables() ) ;
RooAbsData *datatmp = data->reduce(Form("%s==%s::%s",chanCat->GetName(),chanCat->GetName(),ttype->GetName()));
RooRealVar *obs = ((RooRealVar*) obstmp->first());
TString chanName(ttype->GetName());
// get data
TH1* hdata = datatmp->createHistogram("Data "+chanName,*obs);
// set errors to gaussian
for (int ib=0 ; ib<hdata->GetNbinsX()+1 ; ib++) hdata->SetBinError(ib, sqrt(hdata->GetBinContent(ib)));
// get initial BG
TH1* h_initial_BG = pdf_state->createHistogram("initial_BG_"+chanName,*obs);
// get initial gammas
int nbins = h_initial_BG->GetNbinsX();
double InitGamma[nbins];
for (int i=0; i<nbins; i++)
{
TString varname = "gamma_B0_0j_l1pt0_bin_"+NumberToString(i);
InitGamma[i] = ws->var(varname)->getVal();
cout << "initial gamma"+NumberToString(i)+" = " << InitGamma[i] << endl;
}
double InitFpt = ws->var("fl1pt_l1pt0")->getVal();
cout << "initial fpt_l1pt0 = " << InitFpt << endl;
TCanvas* c1 = new TCanvas("BG and Data "+chanName,"BG and Data "+chanName,600,600);
h_initial_BG->Draw();
//hdata->DrawNormalized("sames E1");
// DO THE GLOBAL FIT
RooMinimizer minim(*nll);
//set some options:
minim.setPrintLevel(0);
minim.optimizeConst(1);
minim.setOffsetting(true);
minim.setMinimizerType("Minuit2");
minim.minimize("Minuit2");
minim.setStrategy(3); //0-3 where 0 is the fastest
minim.migrad();
// get gammas after fit
double FinalGamma[nbins];
TH1* h_initBG_times_gamma = (TH1*)h_initial_BG->Clone("initBG_times_gamma");
for (int i=0; i<nbins; i++)
{
TString varname = "gamma_B0_0j_l1pt0_bin_"+NumberToString(i);
FinalGamma[i] = ws->var(varname)->getVal();
cout << "Final gamma in bin "+NumberToString(i)+" = " << FinalGamma[i] << endl;
h_initBG_times_gamma->SetBinContent(i+1,h_initial_BG->GetBinContent(i+1)*FinalGamma[i]);
}
double FinalFpt = ws->var("fl1pt_l1pt0")->getVal();
cout << "initial fpt_l1pt0 = " << InitFpt << endl;
cout << "final fpt_l1pt0 = " << FinalFpt << endl;
TH1* h_final_BG = pdf_state->createHistogram("final_BG_"+chanName,*obs);
//TCanvas* cf = new TCanvas("final BG","final BG",600,600);
h_final_BG->Draw("sames");
h_initBG_times_gamma->Draw("sames");
TH1* h_ratio = (TH1*)h_initial_BG->Clone("h_ratio");
h_ratio->Divide(h_final_BG);
//h_ratio->Draw();
cout << "channel name = " << chanName << endl;
for ( int j=1; j<=nbins; j++)
{
double init = h_initial_BG->GetBinContent(j);
double fina = h_final_BG->GetBinContent(j);
double r = (fina)/init;
cout << "in bin " << j << ", initial B = " << init << ", final B = " << fina << ", ratio = " << r << ", Gamma = " << FinalGamma[j-1] << endl;
}
}
}
void PlotAll(TString wsname)
{
char* binLabels[19] = {"60","70","80","90","100","110","120","130","140","150","160","170","180","190","200","250","300","400","1000"};
//get the stuff from the workspace:
TFile* file=TFile::Open(wsname);
RooWorkspace* ws = (RooWorkspace*)file->Get("combined");
ModelConfig *mc = (ModelConfig*)ws->obj("ModelConfig");
RooAbsData *data = ws->data("obsData");
RooSimultaneous* simPdf=(RooSimultaneous*)(mc->GetPdf());
RooAbsReal* nll=simPdf->createNLL(*data);
// FPT 0 **************************************
// EM channel
RooCategory* chanCat = (RooCategory*) (&simPdf->indexCat());
TIterator* iterat = chanCat->typeIterator() ;
RooCatType* ttype = (RooCatType*)iterat->Next();
RooAbsPdf *pdf_stateEM = simPdf->getPdf(ttype->GetName()) ;
RooArgSet *obstmpEM = pdf_stateEM->getObservables( *mc->GetObservables() ) ;
// get EM data
RooAbsData *dataEM = data->reduce(Form("%s==%s::%s",chanCat->GetName(),chanCat->GetName(),ttype->GetName()));
RooRealVar *obsEM = ((RooRealVar*) obstmpEM->first());
TString chanName1(ttype->GetName());
// create data histogram
TH1* hdataEM = dataEM->createHistogram("Data "+chanName1,*obsEM);
// set errors to gaussian
for (int ib=0 ; ib<hdataEM->GetNbinsX()+1 ; ib++) hdataEM->SetBinError(ib, sqrt(hdataEM->GetBinContent(ib)));
double EMnorm = pdf_stateEM->expectedEvents(*obsEM);
//****************************
// ME channel
ttype = (RooCatType*)iterat->Next();
RooAbsPdf* pdf_stateME = simPdf->getPdf(ttype->GetName()) ;
RooArgSet* obstmpME = pdf_stateME->getObservables( *mc->GetObservables() ) ;
// get ME data
RooAbsData *dataME = data->reduce(Form("%s==%s::%s",chanCat->GetName(),chanCat->GetName(),ttype->GetName()));
RooRealVar* obsME = ((RooRealVar*) obstmpME->first());
TString chanName2(ttype->GetName());
// create data histogram
TH1* hdataME = dataME->createHistogram("Data "+chanName2,*obsME);
// set errors to gaussian
for (int ib=0 ; ib<hdataME->GetNbinsX()+1 ; ib++) hdataME->SetBinError(ib, sqrt(hdataME->GetBinContent(ib)));
// get initial BG histogram
//TH1* h_initial_BG_EM = pdf_stateEM->createHistogram("initial_BG_EM",*obsEM);
//TH1* h_initial_BG_ME = pdf_stateME->createHistogram("initial_BG_ME",*obsME);
double MEnorm = pdf_stateME->expectedEvents(*obsME);
cout << "EM expected events = " << EMnorm << ", ME expected events = " << MEnorm << "." << endl;
//h_initial_BG_EM->Scale(EMnorm);
//h_initial_BG_ME->Scale(MEnorm);
// get initial gammas
int nbins = hdataEM->GetNbinsX();
double InitGamma[nbins];
for (int i=0; i<nbins; i++)
{
TString varname = "gamma_B0_l1pt0_bin_"+NumberToString(i);
InitGamma[i] = ws->var(varname)->getVal();
cout << "initial gamma"+NumberToString(i)+" = " << InitGamma[i] << endl;
}
double InitFpt = ws->var("fl1pt_l1pt0")->getVal();
cout << "initial fpt_l1pt0 = " << InitFpt << endl;
// DO THE GLOBAL FIT
minimize(nll);
// get final BG histograms
TH1* h_final_BG_EM = pdf_stateEM->createHistogram("final_BG_EM",*obsEM);
TH1* h_final_BG_ME = pdf_stateME->createHistogram("final_BG_ME",*obsME);
h_final_BG_EM->Scale(EMnorm);
h_final_BG_ME->Scale(MEnorm);
// uncertainty bands
TH1D* BuncertaintyEM = new TH1D("BuncertaintyEM","BuncertaintyEM",nbins,0,nbins);
TH1D* BuncertaintyME = new TH1D("BuncertaintyME","BuncertaintyME",nbins,0,nbins);
for (int i=1; i<=nbins; i++){
double sigbEM = h_final_BG_EM->GetBinError(i);
double bEM = h_final_BG_EM->GetBinContent(i);
BuncertaintyEM->SetBinError(i,sigbEM); BuncertaintyEM->SetBinContent(i,bEM);
double sigbME = h_final_BG_ME->GetBinError(i);
double bME = h_final_BG_ME->GetBinContent(i);
BuncertaintyME->SetBinError(i,sigbME); BuncertaintyME->SetBinContent(i,bME);
}
//BuncertaintyEM->SetFillStyle(3004);
BuncertaintyEM->SetFillColor(kGreen-9);
BuncertaintyEM->SetLineColor(kBlack); BuncertaintyEM->SetLineStyle(2);
//BuncertaintyME->SetFillStyle(3004);
BuncertaintyME->SetFillColor(kBlue-9);
BuncertaintyME->SetLineColor(kBlack); BuncertaintyME->SetLineStyle(2);
// get gammas after fit
double FinalGamma[nbins];
//TH1* h_initBG_times_gamma = (TH1*)h_initial_BG_EM->Clone("initBGEM_times_gamma");
for (int i=0; i<nbins; i++)
{
TString varname = "gamma_B0_l1pt0_bin_"+NumberToString(i);
FinalGamma[i] = ws->var(varname)->getVal();
cout << "Final gamma in bin "+NumberToString(i)+" = " << FinalGamma[i] << endl;
// h_initBG_times_gamma->SetBinContent(i+1,h_initial_BG_EM->GetBinContent(i+1)*FinalGamma[i]);
}
//double FinalFpt = ws->var("fl1pt_l1pt0")->getVal();
// get final alpha (pull)
RooRealVar* alphaVar = ws->var("alpha_l1ptsys_l1pt0");
double alpha, alphaErr;
if (alphaVar != NULL) {
alpha = ws->var("alpha_l1ptsys_l1pt0")->getVal();
alphaErr = ws->var("alpha_l1ptsys_l1pt0")->getError();
}
//FOR UNCONSTRAINED FPT - get final fpts
double FinalFpt[5];
double FinalFptErr[5];
for (int k=0; k<5; k++){
TString varname = "fl1pt_l1pt"+NumberToString(k);
FinalFpt[k] = ws->var(varname)->getVal();
FinalFptErr[k] = ws->var(varname)->getError();
cout << varname << " = " << FinalFpt[k] << " +- " << FinalFptErr[k] << endl;
}
// get POI value
double mu = ws->var("mu_BR_htm")->getVal();
double muErr = ws->var("mu_BR_htm")->getError();
// Draw
TCanvas* c1 = new TCanvas("BG and Data "+chanName1+" "+chanName2,"BG and Data "+chanName1+" "+chanName2,600,600);
BuncertaintyEM->Draw("E3 sames"); BuncertaintyME->Draw("E3 sames");
//h_initial_BG_EM->SetLineColor(kGreen+2); h_initial_BG_EM->SetLineStyle(2); h_initial_BG_EM->Draw("sames");
hdataEM->SetLineColor(kGreen+2); hdataEM->SetMarkerStyle(20); hdataEM->SetMarkerColor(kGreen+2);
hdataEM->Draw("e1 sames");
//h_initial_BG_ME->SetLineColor(kBlue); h_initial_BG_ME->SetLineStyle(2); h_initial_BG_ME->Draw("sames");
hdataME->SetLineColor(kBlue); hdataME->SetMarkerStyle(20); hdataME->SetMarkerColor(kBlue);
hdataME->Draw("e1 sames");
h_final_BG_EM->SetLineColor(kGreen+2); h_final_BG_EM->SetLineWidth(2); h_final_BG_EM->Draw("sames");
h_final_BG_ME->SetLineColor(kBlue); h_final_BG_ME->SetLineWidth(2); h_final_BG_ME->Draw("sames");
TLegend* leg = new TLegend(0.5,0.45,0.85,0.65);
leg->SetFillColor(kWhite); leg->SetBorderSize(1); leg->SetLineColor(0); //leg->SetTextFont(14);
leg->SetTextSize(.03);
leg->AddEntry(hdataME,"DATA #mue","lep");
leg->AddEntry(hdataEM,"DATA e#mu","lep");
//leg->AddEntry(h_initial_BG_ME,"Initial #mue PDF","l");
//leg->AddEntry(h_initial_BG_EM,"Initial e#mu PDF","l");
leg->AddEntry(h_final_BG_ME,"#mue PDF = #gamma_{i}B_{i} + #muS_{i}","l");
leg->AddEntry(h_final_BG_EM,"e#mu PDF = f(1+#alpha#sigma)(#gamma_{i}B_{i}+#muW_{i})","l");
leg->Draw();
cout << " ********************* Fit Values **************************** " << endl;
if (alphaVar != NULL){cout << "alpha = " << alpha << " +- " << alphaErr << endl;}
cout << "mu = " << mu << " +- " << muErr << endl;
TString WriteDownAlphaValue;
TString WriteDownMuValue;
WriteDownAlphaValue = "Fpt0 = ";
WriteDownMuValue = "#mu = ";
WriteDownAlphaValue += Form("%4.4f",FinalFpt[0]);
WriteDownAlphaValue += "#pm";
WriteDownAlphaValue += Form("%4.4f",FinalFptErr[0]);
WriteDownMuValue += Form("%4.4f",mu);
WriteDownMuValue += "#pm";
WriteDownMuValue += Form("%4.4f",muErr);
TLatex *texl = new TLatex(12,25,WriteDownAlphaValue);
texl->SetTextAlign(22); texl->SetTextSize(0.03);
TLatex *texl2 = new TLatex(12,23,WriteDownMuValue);
texl2->SetTextAlign(22); texl2->SetTextSize(0.03);
texl->Draw();
texl2->Draw();
//FPT 1 ***********************************
ttype = (RooCatType*)iterat->Next();
RooAbsPdf *pdf_stateEM1 = simPdf->getPdf(ttype->GetName()) ;
RooArgSet *obstmpEM1 = pdf_stateEM1->getObservables( *mc->GetObservables() ) ;
RooAbsData *dataEM1 = data->reduce(Form("%s==%s::%s",chanCat->GetName(),chanCat->GetName(),ttype->GetName()));
RooRealVar *obsEM1 = ((RooRealVar*) obstmpEM1->first());
TString chanName11(ttype->GetName());
TH1* hdataEM1 = dataEM1->createHistogram("Data "+chanName11,*obsEM1);
for (int ib=0 ; ib<hdataEM1->GetNbinsX()+1 ; ib++) hdataEM1->SetBinError(ib, sqrt(hdataEM1->GetBinContent(ib)));
double EMnorm1 = pdf_stateEM1->expectedEvents(*obsEM1);
ttype = (RooCatType*)iterat->Next();
RooAbsPdf* pdf_stateME1 = simPdf->getPdf(ttype->GetName()) ;
RooArgSet* obstmpME1 = pdf_stateME1->getObservables( *mc->GetObservables() ) ;
RooAbsData *dataME1 = data->reduce(Form("%s==%s::%s",chanCat->GetName(),chanCat->GetName(),ttype->GetName()));
RooRealVar* obsME1 = ((RooRealVar*) obstmpME1->first());
TString chanName21(ttype->GetName());
TH1* hdataME1 = dataME1->createHistogram("Data "+chanName21,*obsME1);
for (int ib=0 ; ib<hdataME1->GetNbinsX()+1 ; ib++) hdataME1->SetBinError(ib, sqrt(hdataME1->GetBinContent(ib)));
double MEnorm1 = pdf_stateME1->expectedEvents(*obsME1);
TH1* h_final_BG_EM1 = pdf_stateEM1->createHistogram("final_BG_EM1",*obsEM1);
TH1* h_final_BG_ME1 = pdf_stateME1->createHistogram("final_BG_ME1",*obsME1);
h_final_BG_EM1->Scale(EMnorm1);
h_final_BG_ME1->Scale(MEnorm1);
TH1D* BuncertaintyEM1 = new TH1D("BuncertaintyEM1","BuncertaintyEM1",nbins,0,nbins);
TH1D* BuncertaintyME1 = new TH1D("BuncertaintyME1","BuncertaintyME1",nbins,0,nbins);
for (int i=1; i<=nbins; i++){
double sigbEM = h_final_BG_EM1->GetBinError(i);
double bEM = h_final_BG_EM1->GetBinContent(i);
BuncertaintyEM1->SetBinError(i,sigbEM); BuncertaintyEM1->SetBinContent(i,bEM);
double sigbME = h_final_BG_ME1->GetBinError(i);
double bME = h_final_BG_ME1->GetBinContent(i);
BuncertaintyME1->SetBinError(i,sigbME); BuncertaintyME1->SetBinContent(i,bME);
}
BuncertaintyEM1->SetFillColor(kGreen-9);
BuncertaintyEM1->SetLineColor(kBlack); BuncertaintyEM1->SetLineStyle(2);
BuncertaintyME1->SetFillColor(kBlue-9);
BuncertaintyME1->SetLineColor(kBlack); BuncertaintyME1->SetLineStyle(2);
double FinalGamma1[nbins];
for (int i=0; i<nbins; i++)
{
TString varname = "gamma_B0_l1pt1_bin_"+NumberToString(i);
FinalGamma1[i] = ws->var(varname)->getVal();
cout << "Final gamma in bin "+NumberToString(i)+" = " << FinalGamma1[i] << endl;
}
TCanvas* c2 = new TCanvas("BG and Data "+chanName11+" "+chanName21,"BG and Data "+chanName11+" "+chanName21,600,600);
BuncertaintyEM1->Draw("E3 sames"); BuncertaintyME1->Draw("E3 sames");
hdataEM1->SetLineColor(kGreen+2); hdataEM1->SetMarkerStyle(20); hdataEM1->SetMarkerColor(kGreen+2);
hdataEM1->Draw("e1 sames");
hdataME1->SetLineColor(kBlue); hdataME1->SetMarkerStyle(20); hdataME1->SetMarkerColor(kBlue);
hdataME1->Draw("e1 sames");
h_final_BG_EM1->SetLineColor(kGreen+2); h_final_BG_EM1->SetLineWidth(2); h_final_BG_EM1->Draw("sames");
h_final_BG_ME1->SetLineColor(kBlue); h_final_BG_ME1->SetLineWidth(2); h_final_BG_ME1->Draw("sames");
leg->Draw();
cout << " ********************* Fit Values **************************** " << endl;
cout << "mu = " << mu << " +- " << muErr << endl;
TString WriteDownAlphaValue1;
WriteDownAlphaValue1 = "Fpt1 = ";
WriteDownAlphaValue1 += Form("%4.4f",FinalFpt[1]);
WriteDownAlphaValue1 += "#pm";
WriteDownAlphaValue1 += Form("%4.4f",FinalFptErr[1]);
TLatex *texl11 = new TLatex(12,25,WriteDownAlphaValue1);
texl11->SetTextAlign(22); texl11->SetTextSize(0.03);
texl11->Draw();
texl2->Draw();
}
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();
}
}
void ptBestFit(float BIN_SIZE=5.0,bool BLIND=false,TString MASS,TString NAME)
{
gROOT->ProcessLine(".x ../../common/styleCMSTDR.C");
gSystem->Load("libHiggsAnalysisCombinedLimit.so");
gROOT->ForceStyle();
gStyle->SetOptStat(0);
gStyle->SetOptTitle(0);
gROOT->SetBatch(1);
gStyle->SetPadRightMargin(0.04);
gStyle->SetPadLeftMargin(0.16);
gStyle->SetPadTopMargin(0.06);
gStyle->SetPadBottomMargin(0.10);
gStyle->SetTitleFont(42,"XY");
gStyle->SetTitleSize(0.0475,"XY");
gStyle->SetTitleOffset(0.9,"X");
gStyle->SetTitleOffset(1.5,"Y");
gStyle->SetLabelSize(0.0375,"XY");
RooMsgService::instance().setSilentMode(kTRUE);
for(int i=0;i<2;i++) {
RooMsgService::instance().setStreamStatus(i,kFALSE);
}
float XMIN = 80;
float XMAX = 200;
TFile *f1 = TFile::Open("datacards/datacard_m"+MASS+"_"+NAME+".root");
TFile *f2 = TFile::Open("combine/mlfit.vbfHbb_"+NAME+"_mH"+MASS+".root");
TFile *f3 = TFile::Open("root/sig_shapes_workspace_B80-200.root");
TFile *f4 = TFile::Open("root/data_shapes_workspace_"+NAME+".root");
RooWorkspace *w = (RooWorkspace*)f1->Get("w");
//w->Print();
RooAbsPdf *bkg_model = (RooAbsPdf*)w->pdf("model_s");
RooFitResult *res_s = (RooFitResult*)f2->Get("fit_s");
RooFitResult *res_b = (RooFitResult*)f2->Get("fit_b");
RooRealVar *rFit = dynamic_cast<RooRealVar *>(res_s->floatParsFinal()).find("r");
RooDataSet *data = (RooDataSet*)w->data("data_obs");
int nparS=0,nparB=0;
cout << res_s->floatParsFinal().getSize() << endl;
cout << res_b->floatParsFinal().getSize() << endl;
nparS = res_s->floatParsFinal().getSize();
nparB = res_b->floatParsFinal().getSize();
float chi2sumS = 0.;
float chi2sumB = 0.;
int nparsum = 0;
// if (BLIND) {
// res_b->Print();
// }
// else {
// res_s->Print();
// }
w->allVars().assignValueOnly(res_s->floatParsFinal());
// w->Print();
// w->allVars()->Print();
RooWorkspace *wSig = (RooWorkspace*)f3->Get("w");
RooWorkspace *wDat = (RooWorkspace*)f4->Get("w");
const RooSimultaneous *sim = dynamic_cast<const RooSimultaneous *> (bkg_model);
const RooAbsCategoryLValue &cat = (RooAbsCategoryLValue &) sim->indexCat();
TList *datasets = data->split(cat,true);
TIter next(datasets);
//int count = 0;
for(RooAbsData *ds = (RooAbsData*)next();ds != 0; ds = (RooAbsData*)next()) {
//if (count > 0) return 0;
//count++;
RooAbsPdf *pdfi = sim->getPdf(ds->GetName());
RooArgSet *obs = (RooArgSet*)pdfi->getObservables(ds);
RooRealVar *x = dynamic_cast<RooRealVar *>(obs->first());
RooRealVar *yield_vbf = (RooRealVar*)wSig->var("yield_signalVBF_mass"+MASS+"_"+TString(ds->GetName()));
RooRealVar *yield_gf = (RooRealVar*)wSig->var("yield_signalGF_mass"+MASS+"_"+TString(ds->GetName()));
TString ds_name(ds->GetName());
//----- get the QCD normalization -----------
RooRealVar *qcd_norm_final = dynamic_cast<RooRealVar *>(res_s->floatParsFinal()).find("CMS_vbfbb_qcd_norm_"+ds_name);
RooRealVar *qcd_yield = (RooRealVar*)wDat->var("yield_data_"+ds_name);
float Nqcd = exp(log(1.5)*qcd_norm_final->getVal())*qcd_yield->getVal();
float eNqcd = log(1.5)*qcd_norm_final->getError()*Nqcd;
cout<<"QCD normalization = "<<Nqcd<<" +/- "<<eNqcd<<endl;
TH1 *hCoarse = (TH1*)ds->createHistogram("coarseHisto_"+ds_name,*x);
float norm = hCoarse->Integral();
int rebin = BIN_SIZE/hCoarse->GetBinWidth(1);
hCoarse->Rebin(rebin);
float MIN_VAL = TMath::Max(0.9*hCoarse->GetBinContent(hCoarse->GetMinimumBin()),1.0);
float MAX_VAL = 1.3*hCoarse->GetBinContent(hCoarse->GetMaximumBin());
RooDataHist ds_coarse("ds_coarse_"+ds_name,"ds_coarse_"+ds_name,*x,hCoarse);
TH1F *hBlind = (TH1F*)hCoarse->Clone("blindHisto_"+ds_name);
for(int i=0;i<hBlind->GetNbinsX();i++) {
double x0 = hBlind->GetBinCenter(i+1);
if (x0 > 100 && x0 < 150) {
hBlind->SetBinContent(i+1,0);
hBlind->SetBinError(i+1,0);
}
}
RooDataHist ds_blind("ds_blind_"+ds_name,"ds_blind_"+ds_name,*x,hBlind);
RooHist *hresid,*hresid0;
RooPlot *frame1 = x->frame();
RooPlot *frame2 = x->frame();
if (BLIND) {
//cout << "Blind case: " << ds_coarse.GetName() << endl;
ds_coarse.plotOn(frame1,LineColor(0),MarkerColor(0));
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name),VisualizeError(*res_s,1,kTRUE),FillColor(0),MoveToBack());
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name),LineWidth(2),LineStyle(3));
ds_blind.plotOn(frame1);
hresid = frame1->residHist();
frame2->addPlotable(hresid,"pE1");
}
else {
//cout << "Non-blind case: " << ds_coarse.GetName() << endl;
ds_coarse.plotOn(frame1);
pdfi->plotOn(frame1);
//cout << pdfi->getParameters(ds_coarse)->selectByAttrib("Constant",kFALSE)->getSize() << endl;
cout<<"chi2/ndof (bkg+sig) = "<<frame1->chiSquare()<<endl;
cout << ds_coarse.numEntries() << endl;
chi2sumS += frame1->chiSquare()*ds_coarse.numEntries();
nparsum += ds_coarse.numEntries();
//hresid0 = frame1->residHist();
//pdfi->plotOn(frame1,VisualizeError(*res_s,1,kTRUE),FillColor(0),MoveToBack());
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name),LineWidth(2),LineStyle(5),LineColor(kGreen+2));
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name),LineWidth(2),LineStyle(2),LineColor(kBlack));
cout<<"chi2/ndof (bkg) = "<<frame1->chiSquare()<<endl;
chi2sumB += frame1->chiSquare()*ds_coarse.numEntries();
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name),LineWidth(2),LineStyle(2),LineColor(kBlack),VisualizeError(*res_s,1,kTRUE),FillColor(0),MoveToBack());
hresid = frame1->residHist();
frame2->addPlotable(hresid,"pE1");
float yield_sig = rFit->getValV()*(yield_vbf->getValV()+yield_gf->getValV());
RooAbsPdf *signal_pdf = (RooAbsPdf*)w->pdf("shapeSig_qqH_"+ds_name);
signal_pdf->plotOn(frame2,LineWidth(2),LineColor(kRed),Normalization(yield_sig,RooAbsReal::NumEvent),MoveToBack());
}
// hresid0->Print();
// hresid->Print();
// double x2,y2;
// for (int i=0; i<3; ++i) {
// hresid0->GetPoint(i,x2,y2);
// cout << "BKG+SIG\t" << x2 << "\t" << y2 << endl;
// hresid->GetPoint(i,x2,y2);
// cout << "BKG\t" << x2 << "\t" << y2 << endl;
// ds_coarse.get(i);
// cout << ds_coarse.weightError(RooAbsData::SumW2) << endl;
// cout << endl;
// }
TCanvas* canFit = new TCanvas("Higgs_fit_"+ds_name,"Higgs_fit_"+ds_name,900,750);
canFit->cd(1)->SetBottomMargin(0.4);
frame1->SetMinimum(MIN_VAL);
frame1->SetMaximum(MAX_VAL);
frame1->GetYaxis()->SetNdivisions(510);
frame1->GetXaxis()->SetTitleSize(0);
frame1->GetXaxis()->SetLabelSize(0);
frame1->GetYaxis()->SetTitle(TString::Format("Events / %1.1f GeV",BIN_SIZE));
frame1->Draw();
gPad->Update();
TList *list = (TList*)gPad->GetListOfPrimitives();
//list->Print();
TH1F *hUncH = new TH1F("hUncH"+ds_name,"hUncH"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
TH1F *hUncL = new TH1F("hUncL"+ds_name,"hUncL"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
TH1F *hUnc2H = new TH1F("hUnc2H"+ds_name,"hUnc2H"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
TH1F *hUnc2L = new TH1F("hUnc2L"+ds_name,"hUnc2L"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
TH1F *hUncC = new TH1F("hUncC"+ds_name,"hUncC"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
RooCurve *errorBand,*gFit,*gQCDFit,*gBkgFit;
//list->Print();
if (BLIND) {
errorBand = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]_errorband_Comp[shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name+"]");
gFit = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]"+"_Comp[shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name+"]");
}
else {
//errorBand = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]_errorband");
errorBand = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]_errorband_Comp[shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name+"]");
gFit = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]");
}
gQCDFit = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]"+"_Comp[shapeBkg_qcd_"+ds_name+"]");
gBkgFit = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]"+"_Comp[shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name+"]");
for(int i=0;i<hUncH->GetNbinsX();i++) {
double x0 = hUncH->GetBinCenter(i+1);
double e1 = fabs(errorBand->Eval(x0)-gBkgFit->Eval(x0));
//double e1 = fabs(errorBand->Eval(x0)-gFit->Eval(x0));
double e2 = eNqcd/hUncH->GetNbinsX();
hUncH->SetBinContent(i+1,sqrt(pow(e2,2)+pow(e1,2)));
hUnc2H->SetBinContent(i+1,2*sqrt(pow(e2,2)+pow(e1,2)));
hUncL->SetBinContent(i+1,-sqrt(pow(e2,2)+pow(e1,2)));
hUnc2L->SetBinContent(i+1,-2*sqrt(pow(e2,2)+pow(e1,2)));
hUncC->SetBinContent(i+1,0.);
}
TPad* pad = new TPad("pad", "pad", 0., 0., 1., 1.);
pad->SetTopMargin(0.63);
pad->SetFillColor(0);
pad->SetFillStyle(0);
pad->Draw();
pad->cd(0);
hUnc2H->GetXaxis()->SetTitle("m_{bb} (GeV)");
hUnc2H->GetYaxis()->SetTitle("Data - Bkg");
//hUnc2H->GetYaxis()->SetTitle("Data - Fit");
double YMAX = 1.1*frame2->GetMaximum();
double YMIN = -1.1*frame2->GetMaximum();
hUnc2H->GetYaxis()->SetRangeUser(YMIN,YMAX);
hUnc2H->GetYaxis()->SetNdivisions(507);
// hUnc2H->GetXaxis()->SetTitleOffset(0.9);
// hUnc2H->GetYaxis()->SetTitleOffset(1.0);
hUnc2H->GetYaxis()->SetTickLength(0.0);
// hUnc2H->GetYaxis()->SetTitleSize(0.05);
// hUnc2H->GetYaxis()->SetLabelSize(0.04);
hUnc2H->GetYaxis()->CenterTitle(kTRUE);
hUnc2H->SetFillColor(kGreen);
hUnc2L->SetFillColor(kGreen);
hUncH->SetFillColor(kYellow);
hUncL->SetFillColor(kYellow);
hUncC->SetLineColor(kBlack);
hUncC->SetLineStyle(7);
hUnc2H->Draw("HIST");
hUnc2L->Draw("same HIST");
hUncH->Draw("same HIST");
hUncL->Draw("same HIST");
hUncC->Draw("same HIST");
frame2->GetYaxis()->SetTickLength(0.03/0.4);
frame2->Draw("same");
TList *list1 = (TList*)gPad->GetListOfPrimitives();
//list1->Print();
RooCurve *gSigFit = (RooCurve*)list1->FindObject("shapeSig_qqH_"+ds_name+"_Norm[mbbReg_"+ds_name+"]");
TLegend *leg = new TLegend(0.70,0.61,0.94,1.-gStyle->GetPadTopMargin()-0.01);
leg->SetTextFont(42);
leg->SetFillStyle(-1);
//leg->SetHeader(ds_name+" (m_{H}="+MASS+")");
leg->SetHeader(TString::Format("Category %d",atoi(ds_name(3,1).Data())+1));
leg->AddEntry(hBlind,"Data","P");
if (!BLIND) {
leg->AddEntry(gSigFit,"Fitted signal","L");
}
TLine *gEmpty = new TLine(0.0,0.0,0.0,0.0);
gEmpty->SetLineWidth(0);
TLegendEntry *l1 = leg->AddEntry(gEmpty,"(m_{H} = "+MASS+" GeV)","");
l1->SetTextSize(0.038*0.97*0.85);
leg->AddEntry(gFit,"Bkg. + signal","L");
leg->AddEntry(gBkgFit,"Bkg.","L");
leg->AddEntry(gQCDFit,"QCD","L");
leg->AddEntry(hUnc2H,"2#sigma bkg. unc.","F");
leg->AddEntry(hUncH,"1#sigma bkg. unc.","F");
leg->SetFillColor(0);
leg->SetBorderSize(0);
leg->SetTextFont(42);
leg->SetTextSize(0.038*0.98);
leg->Draw();
leg->SetY1(leg->GetY2()-leg->GetNRows()*0.045*0.96);
TPaveText *paveCMS = new TPaveText(gStyle->GetPadLeftMargin()+0.02,0.7,gStyle->GetPadLeftMargin()+0.15,1.-gStyle->GetPadTopMargin()-0.01,"NDC");
paveCMS->SetTextFont(62);
paveCMS->SetTextSize(gStyle->GetPadTopMargin()*3./4.);
paveCMS->SetBorderSize(0);
paveCMS->SetFillStyle(-1);
paveCMS->SetTextAlign(12);
paveCMS->AddText("CMS");
paveCMS->Draw();
gPad->Update();
paveCMS->SetY1NDC(paveCMS->GetY2NDC()-paveCMS->GetListOfLines()->GetSize()*gStyle->GetPadTopMargin());
TPaveText *paveLumi = new TPaveText(0.5,1.-gStyle->GetPadTopMargin(),0.98,1.00,"NDC");
paveLumi->SetTextFont(42);
paveLumi->SetTextSize(gStyle->GetPadTopMargin()*3./4.);
paveLumi->SetBorderSize(0);
paveLumi->SetFillStyle(-1);
paveLumi->SetTextAlign(32);
paveLumi->AddText(TString::Format("%.1f fb^{-1} (8TeV)",(atoi(ds_name(3,1).Data())<4 ? 19.8 : 18.3)).Data());//+ 18.2 ;
paveLumi->Draw();
TString path=".";
//TString path="BiasV10_limit_BRN5p4_dX0p1_B80-200_CAT0-6/output/";
system(TString::Format("[ ! -d %s/plot ] && mkdir %s/plot",path.Data(),path.Data()).Data());
system(TString::Format("[ ! -d %s/plot/fits ] && mkdir %s/plot/fits",path.Data(),path.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s.pdf",path.Data(),MASS.Data(),ds_name.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s.png",path.Data(),MASS.Data(),ds_name.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s.eps",path.Data(),MASS.Data(),ds_name.Data()).Data());
TText *l = (TText*)paveCMS->AddText("Preliminary");
l->SetTextFont(52);
paveCMS->Draw();
gPad->Update();
paveCMS->SetY1NDC(paveCMS->GetY2NDC()-paveCMS->GetListOfLines()->GetSize()*gStyle->GetPadTopMargin());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s_prelim.pdf",path.Data(),MASS.Data(),ds_name.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s_prelim.png",path.Data(),MASS.Data(),ds_name.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s_prelim.eps",path.Data(),MASS.Data(),ds_name.Data()).Data());
delete ds;
}
cout << "chi2sumS: " << chi2sumS << endl;
cout << "chi2sumB: " << chi2sumB << endl;
cout << "nparS: " << nparS << endl;
cout << "nparB: " << nparB << endl;
cout << "nbinsum: " << nparsum << endl;
cout << "chi2sumS/(nbinsum - nparS): " << chi2sumS / (float)(nparsum - nparS) << endl;
cout << "chi2sumB/(nbinsum - nparB): " << chi2sumB / (float)(nparsum - nparB) << endl;
delete datasets;
}
