void draw_data_mgg(TString folderName,bool blind=true,float min=103,float max=160)
{
TFile inputFile(folderName+"/data.root");
const int nCat = 5;
TString cats[5] = {"HighPt","Hbb","Zbb","HighRes","LowRes"};
TCanvas cv;
for(int iCat=0; iCat < nCat; iCat++) {
RooWorkspace *ws = (RooWorkspace*)inputFile.Get(cats[iCat]+"_mgg_workspace");
RooFitResult* res = (RooFitResult*)ws->obj("fitresult_pdf_data");
RooRealVar * mass = ws->var("mgg");
mass->setRange("all",min,max);
mass->setRange("blind",121,130);
mass->setRange("low",106,121);
mass->setRange("high",130,160);
mass->setUnit("GeV");
mass->SetTitle("m_{#gamma#gamma}");
RooAbsPdf * pdf = ws->pdf("pdf");
RooPlot *plot = mass->frame(min,max,max-min);
plot->SetTitle("");
RooAbsData* data = ws->data("data")->reduce(Form("mgg > %f && mgg < %f",min,max));
double nTot = data->sumEntries();
if(blind) data = data->reduce("mgg < 121 || mgg>130");
double nBlind = data->sumEntries();
double norm = nTot/nBlind; //normalization for the plot
data->plotOn(plot);
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"),RooFit::LineWidth(0.1) );
plot->Print();
//add the fix error band
RooCurve* c = plot->getCurve("pdf_Norm[mgg]_Range[Full]_NormRange[Full]");
const int Nc = c->GetN();
//TGraphErrors errfix(Nc);
//TGraphErrors errfix2(Nc);
TGraphAsymmErrors errfix(Nc);
TGraphAsymmErrors errfix2(Nc);
Double_t *x = c->GetX();
Double_t *y = c->GetY();
double NtotalFit = ws->var("Nbkg1")->getVal()*ws->var("Nbkg1")->getVal() + ws->var("Nbkg2")->getVal()*ws->var("Nbkg2")->getVal();
for( int i = 0; i < Nc; i++ )
{
errfix.SetPoint(i,x[i],y[i]);
errfix2.SetPoint(i,x[i],y[i]);
mass->setVal(x[i]);
double shapeErr = pdf->getPropagatedError(*res)*NtotalFit;
//double totalErr = TMath::Sqrt( shapeErr*shapeErr + y[i] );
//total normalization error
double totalErr = TMath::Sqrt( shapeErr*shapeErr + y[i]*y[i]/NtotalFit );
if ( y[i] - totalErr > .0 )
{
errfix.SetPointError(i, 0, 0, totalErr, totalErr );
}
else
{
errfix.SetPointError(i, 0, 0, y[i] - 0.01, totalErr );
}
//2sigma
if ( y[i] - 2.*totalErr > .0 )
{
errfix2.SetPointError(i, 0, 0, 2.*totalErr, 2.*totalErr );
}
else
{
errfix2.SetPointError(i, 0, 0, y[i] - 0.01, 2.*totalErr );
}
/*
std::cout << x[i] << " " << y[i] << " "
<< " ,pdf get Val: " << pdf->getVal()
<< " ,pdf get Prop Err: " << pdf->getPropagatedError(*res)*NtotalFit
<< " stat uncertainty: " << TMath::Sqrt(y[i]) << " Ntot: " << NtotalFit << std::endl;
*/
}
errfix.SetFillColor(kYellow);
errfix2.SetFillColor(kGreen);
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kFALSE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kFALSE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kTRUE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kTRUE));
plot->addObject(&errfix,"4");
plot->addObject(&errfix2,"4");
plot->addObject(&errfix,"4");
data->plotOn(plot);
TBox blindBox(121,plot->GetMinimum()-(plot->GetMaximum()-plot->GetMinimum())*0.015,130,plot->GetMaximum());
blindBox.SetFillColor(kGray);
if(blind) {
plot->addObject(&blindBox);
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kTRUE));
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kTRUE));
}
//plot->addObject(&errfix,"4");
//data->plotOn(plot);
//pdf->plotOn(plot,RooFit::Normalization( norm ) );
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"),RooFit::LineWidth(1.5) );
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"), RooFit::LineWidth(1));
data->plotOn(plot);
/*
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::Range("all"),RooFit::LineWidth(0.8) );
//pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kGreen),RooFit::Range("all"), RooFit::VisualizeError(*res,2.0,kFALSE));
//pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kYellow),RooFit::Range("all"), RooFit::VisualizeError(*res,1.0,kFALSE));
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kGreen),RooFit::Range("all"), RooFit::VisualizeError(*res,2.0,kTRUE));
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kYellow),RooFit::Range("all"), RooFit::VisualizeError(*res,1.0,kTRUE));
data->plotOn(plot);
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::Range("all"),RooFit::LineWidth(0.8) );
*/
TLatex lbl0(0.1,0.96,"CMS Preliminary");
lbl0.SetNDC();
lbl0.SetTextSize(0.042);
plot->addObject(&lbl0);
TLatex lbl(0.4,0.96,Form("%s Box",cats[iCat].Data()));
lbl.SetNDC();
lbl.SetTextSize(0.042);
plot->addObject(&lbl);
TLatex lbl2(0.6,0.96,"#sqrt{s}=8 TeV L = 19.78 fb^{-1}");
lbl2.SetNDC();
lbl2.SetTextSize(0.042);
plot->addObject(&lbl2);
int iObj=-1;
TNamed *obj;
while( (obj = (TNamed*)plot->getObject(++iObj)) ) {
obj->SetName(Form("Object_%d",iObj));
}
plot->Draw();
TString tag = (blind ? "_BLIND" : "");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".png");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".pdf");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".C");
}
}
int main() {
float min_logL1 = 5986.94;
float min_logL0 = 5987.16;
string filepath="FINAL_RESULT_AB.root_RESULT__RESULT";
filepath="/shome/buchmann/KillerKoala/CBAF/Development/exchange/RooFit__WorkSpace__Exchange_201417_175622__RNSG_46692.4.root__RESULT__RESULT"; // final MCwS
filepath="/shome/buchmann/KillerKoala/CBAF/Development/exchange/RooFit__WorkSpace__Exchange_201417_175622__RNSG_46692.4.root__RESULT__RESULT";
filepath="/shome/buchmann/KillerKoala/CBAF/Development/exchange/RooFit__WorkSpace__Exchange_201417_141126__RNSG_97048.1.root__RESULT__RESULT";
// *************************************************************************************
setlumi(PlottingSetup::luminosity);
setessentialcut(PlottingSetup::essential); // this sets the essential cut; this one is used in the draw command so it is AUTOMATICALLY applied everywhere. IMPORTANT: Do NOT store weights here!
stringstream resultsummary;
// write_analysis_type(PlottingSetup::RestrictToMassPeak,PlottingSetup::DoBTag);
do_png(true);
do_pdf(true);
do_eps(false);
do_C(true);
do_root(false);
PlottingSetup::directoryname = "pValuePlot";
gROOT->SetStyle("Plain");
bool do_fat_line = false; // if you want to have HistLineWidth=1 and FuncWidth=1 as it was before instead of 2
setTDRStyle(do_fat_line);
gStyle->SetTextFont(42);
bool showList = true;
set_directory(PlottingSetup::directoryname); // Indicate the directory name where you'd like to save the output files in Setup.C
set_treename("events"); // you can set the treename here to be used; options are "events" (for reco) for "PFevents" (for particle flow)
TFile *f = new TFile(filepath.c_str());
if(f->IsZombie()) {
cout << "Seems to be a zombie. goodbye." << endl;
return -1;
}
RooWorkspace *wa = (RooWorkspace*)f->Get("transferSpace");
RooPlot *plot = (RooPlot*) wa->obj("frame_mlledge_109fde50");
// cout << plot << endl;
wa->Print("v");
TCanvas *can = new TCanvas("can","can");
cout << "Address of plot : " << plot << endl;
// plot->Draw();
float pVal_mllmin=35;
float pVal_mllmax=90;
int is_data=PlottingSetup::data;
vector < std::pair < float, float> > loglikelihoods;
string function="";
for(int i=0; i< plot->numItems();i++){
string name = plot->getObject(i)->GetName();
if (plot->getObject(i)->IsA()->InheritsFrom( "RooCurve" ))function=name;
}
RooCurve* curve = (RooCurve*) plot->findObject(function.c_str(),RooCurve::Class()) ;
if (!curve) {
dout << "RooPlot::residHist(" << plot->GetName() << ") cannot find curve" << endl ;
return 0 ;
}
int iMinimum=0;
float min=1e7;
for(int i=0;i<curve->GetN();i++) {
double x,y;
curve->GetPoint(i,x,y);
if(y<min & y>=0) {
min=y;
iMinimum=i;
}
}
double x,y;
curve->GetPoint(iMinimum,x,y);
cout << "Minimum is at " << x << " : " << y << endl;
loglikelihoods.push_back(make_pair(x,y+min_logL1));
//move right starting from the minimum
for(int i=iMinimum+1;i<curve->GetN();i++) {
float yold=y;
curve->GetPoint(i,x,y);
//if(abs((y-yold)/yold)>0.5) continue;
loglikelihoods.push_back(make_pair(x,y+min_logL1));
}
/*
for(int i=0;i<curve->GetN();i++) {
double x,y;
curve->GetPoint(i,x,y);
loglikelihoods.push_back(make_pair(x,y+min_logL1));
}*/
cout << "The whole thing contains " << loglikelihoods.size() << " points " << endl;
ProduceSignificancePlots(min_logL0, loglikelihoods, pVal_mllmin, pVal_mllmax, is_data, "", "");
can->SaveAs("Crap.png");
delete can;
delete plot;
delete wa;
f->Close();
return 0;
}