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Copy pathR2GGBBFitter_mtot_range.cc
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R2GGBBFitter_mtot_range.cc
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//Important options first
Bool_t doblinding = false; //True if you want to blind
Bool_t details_signal_model = false;
const int minfit =320, maxfit=1200;
// this one is for 4 body fit
using namespace RooFit;
using namespace RooStats ;
const Int_t NCAT = 2;
// declare the functions
void AddSigData(RooWorkspace*, Float_t);
void AddBkgData(RooWorkspace*);
void SigModelFit(RooWorkspace*, Float_t);
void MakePlots(RooWorkspace*, Float_t, RooFitResult* );
void MakeSigWS(RooWorkspace* w, const char* filename);
void MakeBkgWS(RooWorkspace* w, const char* filename);
void MakeDataCardonecat(RooWorkspace* w, const char* filename, const char* filename1);
void MakeDataCardREP(RooWorkspace* w, const char* filename, const char* filename1);
void SetParamNames(RooWorkspace*);
void SetConstantParams(const RooArgSet* params);
RooFitResult* fitresult[NCAT]; // container for the fit results
RooFitResult* BkgModelFitBernstein(RooWorkspace*, Bool_t);
RooArgSet* defineVariables()
{
// define variables of the input ntuple
RooRealVar* mtot = new RooRealVar("mtot","M(#gamma#gammajj)",320,1200,"GeV");
RooRealVar* mgg = new RooRealVar("mgg","M(#gamma#gamma)",100,180,"GeV");
RooRealVar* mjj = new RooRealVar("mjj","M(jj)",0,500,"GeV");
RooRealVar* evWeight = new RooRealVar("evWeight","HqT x PUwei",0,100000000,"");
RooCategory* cut_based_ct = new RooCategory("cut_based_ct","event category 2") ;
//
cut_based_ct->defineType("cat4_0",0);
cut_based_ct->defineType("cat4_1",1);
//
RooArgSet* ntplVars = new RooArgSet(*mtot, *mgg, * cut_based_ct, *evWeight);
ntplVars->add(*cut_based_ct);
ntplVars->add(*mtot);
ntplVars->add(*mgg);
ntplVars->add(*mjj);
ntplVars->add(*evWeight);
return ntplVars;
}
void runfits(const Float_t mass=120, Int_t mode=1, Bool_t dobands = false)
{
style();
TString fileBaseName(TString::Format("hgghbb.mH%.1f_8TeV", mass));
TString fileBkgName(TString::Format("hgghbb.inputbkg_8TeV", mass));
TString card_name("models_mtot_range_m550.rs"); // fit model parameters to kinfit
// TString card_name("models_mtot_range.rs"); // fit model parameters no kinfit
// declare a first WS
HLFactory hlf("HLFactory", card_name, false);
RooWorkspace* w = hlf.GetWs(); // Get models and variables
RooFitResult* fitresults;
//PAS limit trees
// TString ssignal = "/afs/cern.ch/work/o/obondu/public/forRadion/limitTrees/v28/v28_fitToMggjj_withKinFit/Radion_m550_8TeV_m550.root";
// TString ddata = "/afs/cern.ch/work/o/obondu/public/forRadion/limitTrees/v28/v28_fitToMggjj_withKinFit/Data_m500.root";
TString ddata = "/afs/cern.ch/work/o/obondu/public/forRadion/limitTrees/v44/v44_fitToMggjj_withKinFit/Data_m400.root";
TString ssignal = "/afs/cern.ch/work/o/obondu/public/forRadion/limitTrees/v44/v44_fitToMggjj_withKinFit/Radion_m550_8TeV_m550.root";
//
cout<<"Signal: "<< ssignal<<endl;
cout<<"Data: "<< ddata<<endl;
AddSigData(w, mass,ssignal);
AddBkgData(w,ddata);
w->Print("v");
// construct the models to fit
SigModelFit(w, mass);
fitresults = BkgModelFitBernstein(w, dobands);
// Construct points workspace
MakeSigWS(w, fileBaseName);
MakeBkgWS(w, fileBkgName);
MakePlots(w, mass, fitresults);
MakeDataCardonecat(w, fileBaseName, fileBkgName);
MakeDataCardREP(w, fileBaseName, fileBkgName);
cout<< "here"<<endl;
return;
} // close runfits
////////////////////////////////////////////////////////////////////
// we add the data to the workspace in categories
void AddSigData(RooWorkspace* w, Float_t mass, TString signalfile) {
const Int_t ncat = NCAT;
Float_t MASS(mass);
// Luminosity:
Float_t Lum = 19712.0; // pb-1
RooRealVar lumi("lumi","lumi",Lum);
w->import(lumi);
RooArgSet* ntplVars = defineVariables();
// file input
TFile sigFile(signalfile);
TTree* sigTree = (TTree*) sigFile.Get("TCVARS");
// common preselection cut
TString mainCut("1");
// one channel with right weights
RooDataSet sigScaled(
"sigScaled",
"dataset",
sigTree,
*ntplVars,
mainCut,
"evWeight");
RooDataSet* sigToFit[ncat];
TString cut0 = "&& 1";
for (int c = 0; c < ncat; ++c) {
sigToFit[c] = (RooDataSet*) sigScaled.reduce(
*w->var("mtot"),
mainCut+TString::Format(" && cut_based_ct==%d",c)+cut0);
w->import(*sigToFit[c],Rename(TString::Format("Sig_cat%d",c)));
} // close ncat
// Create full signal data set without categorization
RooDataSet* sigToFitAll = (RooDataSet*) sigScaled.reduce(*w->var("mtot"),mainCut);
w->import(*sigToFitAll,Rename("Sig"));
// here we print the number of entries on the different categories
cout << "========= the number of entries on the different categories ==========" << endl;
cout << "---- one channel: " << sigScaled.sumEntries() << endl;
for (int c = 0; c < ncat; ++c) {
Float_t nExpEvt = sigToFit[c]->sumEntries();
cout << TString::Format("nEvt exp. cat%d : ",c) << nExpEvt
<< TString::Format(" eff x Acc cat%d : ",c)
<< "%"
<< endl;
}
cout << "======================================================================" << endl;
sigScaled.Print("v");
return;
} // end add signal function
///////////////////////////////////////////////////////////////////////////////////
// we add the data to the workspace in categories
void AddBkgData(RooWorkspace* w, TString datafile) {
const Int_t ncat = NCAT;
// common preselection cut
TString mainCut("1");
RooArgSet* ntplVars = defineVariables();
// weith data as with 1
RooRealVar weightVar("weightVar","",1,0,1000);
weightVar.setVal(1.);
TFile dataFile(datafile);
TTree* dataTree = (TTree*) dataFile.Get("TCVARS");
RooDataSet Data("Data","dataset",dataTree,*ntplVars,"","weightVar");
RooDataSet* dataToFit[ncat];
RooDataSet* dataToPlot[ncat];
TString cut0;
if(doblinding){ cut0 = "&& 1"; }//do not show any data
else{ cut0 = "&& 1>0 "; }
for (int c = 0; c < ncat; ++c) {
dataToFit[c] = (RooDataSet*) Data.reduce(
*w->var("mtot"),
TString::Format(" cut_based_ct==%d && mtot > %d",c,minfit));
dataToPlot[c] = (RooDataSet*) Data.reduce(
*w->var("mtot"),
TString::Format(" cut_based_ct==%d && mtot > %d",c,minfit)+ cut0);
w->import(*dataToFit[c],Rename(TString::Format("Data_cat%d",c)));
w->import(*dataToPlot[c],Rename(TString::Format("Dataplot_cat%d",c)));
}
// Create full data set without categorization
RooDataSet* data = (RooDataSet*) Data.reduce(*w->var("mtot"));
w->import(*data, Rename("Data"));
data->Print("v");
return;
} // close add data ..
/////////////////////////////////////////////////////////////////////
// we make the fit model
void SigModelFit(RooWorkspace* w, Float_t mass) {
const Int_t ncat = NCAT;
Float_t MASS(mass);
const int minsigfit =mass - 120, maxsigfit=mass +120;
RooDataSet* sigToFit[ncat];
RooAbsPdf* mtotSig[ncat];
// fit range
Float_t minMassFit(minfit),maxMassFit(maxsigfit);
for (int c = 0; c < ncat; ++c) {
// import sig and data from workspace
sigToFit[c] = (RooDataSet*) w->data(TString::Format("Sig_cat%d",c));
mtotSig[c] = (RooAbsPdf*) w->pdf(TString::Format("mtotSig_cat%d",c));
RooRealVar* peak = w->var(TString::Format("mtot_sig_m0_cat%d",c));
peak->setVal(MASS);
cout << "OK up to now..." <<MASS<< endl;
// Fit model as M(x|y) to D(x,y)
if(c==0) mtotSig[c]->fitTo(*sigToFit[c],Range(minMassFit,maxMassFit),SumW2Error(kTRUE));
if(c==1) mtotSig[c]->fitTo(*sigToFit[c],Range(minMassFit,maxMassFit),SumW2Error(kTRUE));
// IMPORTANT: fix all pdf parameters to constant
w->defineSet(TString::Format("SigPdfParam_cat%d",c),
RooArgSet(
*w->var(TString::Format("mtot_sig_m0_cat%d",c)),
*w->var(TString::Format("mtot_sig_alpha_cat%d",c)),
*w->var(TString::Format("mtot_sig_n_cat%d",c)),
*w->var(TString::Format("mtot_sig_sigma_cat%d",c)),
// *w->var(TString::Format("mtot_sig_g_cat%d",c)), // voi
*w->var(TString::Format("mtot_sig_gsigma_cat%d",c)),
*w->var(TString::Format("mtot_sig_frac_cat%d",c))) );
SetConstantParams(w->set(TString::Format("SigPdfParam_cat%d",c)));
} // close for ncat
} // close signal model fit
////////////////////////////////////////////////////////////
// BKG model berestein 3
RooFitResult* BkgModelFitBernstein(RooWorkspace* w, Bool_t dobands) {
const Int_t ncat = NCAT; dobands=true;
std::vector<TString> catdesc;
catdesc.push_back("High-purity");//2 btag");
catdesc.push_back("Medium-purity");//1 btag");
//******************************************//
// Fit background with model pdfs
//******************************************//
// retrieve pdfs and datasets from workspace to fit with pdf models
RooDataSet* data[ncat];
RooDataSet* dataplot[ncat];
RooDataSet* emptyplot[ncat];
//RooBernstein* mtotBkg[ncat];
RooPlot* plotmtotBkg[ncat];
RooPlot* plotlinemtotBkg[ncat];
RooDataSet* sigToFit[ncat]; // the signal
RooAbsPdf* mtotSig[ncat]; // polinomial of 4* order for signal
Float_t minMassFit(minfit),maxMassFit(maxfit);
// Fit data with background pdf for data limit
RooRealVar* mtot = w->var("mtot");
mtot->setUnit("GeV");
//
TLatex *text = new TLatex();
text->SetNDC();
text->SetTextSize(0.04);
//
int order=-2;
//
for (int c = 0; c < ncat; ++c) {
data[c] = (RooDataSet*) w->data(TString::Format("Data_cat%d",c));
cout << "!!!!!!!!!!!!!" << endl;
/*
w->factory(TString::Format("mtot_bkg_8TeV_norm_cat%d[1.0,0.0,100000]",c)); // is is on the .rs
*/
////////////////////////////////////
// these are the parameters for exponential fit
// one slope by category - not squared slopes
RooFormulaVar *p1mod = new RooFormulaVar(
TString::Format("p1mod_cat%d",c),"","@0",*w->var(TString::Format("mtot_bkg_8TeV_slope1_cat%d",c)));
RooFormulaVar *p2mod;
RooAbsPdf* mtotBkg;
if(c==1) p2mod = new RooFormulaVar(
TString::Format("p2mod_cat%d",c),"","@0",*w->var(TString::Format("mtot_bkg_8TeV_slope2_cat%d",c)));
if(c==0) mtotBkg = new RooGenericPdf( // if exp function
TString::Format("mtotBkg_cat%d",c),
"1./pow(@0,@1*@1)",
RooArgList(*mtot, *p1mod));
if(c==1) mtotBkg = new RooGenericPdf( // if exp function
TString::Format("mtotBkg_cat%d",c),
"1./pow(@0+@2,@1*@1)",
RooArgList(*mtot, *p1mod, *p2mod));
w->factory(TString::Format("mtot_bkg_8TeV_cat%d_norm[1.0,0.0,100000]",c));
RooExtendPdf mtotBkgExt( // we copy the pdf? normalized
TString::Format("mtotBkgExt_cat%d",c),
"",*mtotBkg,
*w->var(TString::Format("mtot_bkg_8TeV_cat%d_norm",c)));
fitresult[c] = mtotBkgExt.fitTo( // fit with normalized pdf,and return values
*data[c], // bkg
Strategy(1), // MINUIT strategy
Minos(kFALSE), // interpretation on the errors, nonlinearities
Range(minMassFit,maxMassFit),
SumW2Error(kTRUE),
Save(kTRUE));
w->defineSet(TString::Format("BkgPdfParam_cat%d",c),
RooArgSet(
*w->var(TString::Format("mtot_bkg_8TeV_slope2_cat%d",c))) );
SetConstantParams(w->set(TString::Format("BkgPdfParam_cat%d",c)));
w->import(mtotBkgExt); //store the normalized pdf on wp
//************************************************//
// Plot mtot background fit results per categories
//************************************************//
TCanvas* ctmp = new TCanvas(TString::Format("ctmpBkg_cat%d",c),"mtot Background Categories",0,0,501,501);
ctmp->cd();
Int_t nBinsMass(44);
plotmtotBkg[c] = mtot->frame(minfit,maxfit,nBinsMass);
//plotlinemtotBkg[c] = mtot->frame(nBinsMass);
dataplot[c] = (RooDataSet*) w->data(TString::Format("Dataplot_cat%d",c));
emptyplot[c] = (RooDataSet*) w->data(TString::Format("Dataplot_cat%d",c));
if(doblinding) dataplot[c]->plotOn(plotmtotBkg[c], Invisible(), Name(Form("Dataplot_cat%d_plot",c)));
else dataplot[c]->plotOn(plotmtotBkg[c], Name(Form("Dataplot_cat%d_plot",c)));
mtotBkgExt.plotOn(
plotmtotBkg[c],
LineColor(kBlue),
Range(minfit+10., maxfit-10.),NormRange("fitrange"));
cout << "!!!!!!!!!!!!!!!!!" << endl;
cout << "!!!!!!!!!!!!!!!!!" << endl; // now we fit the gaussian on signal
// we draw signal on the same
plotmtotBkg[c]->SetTitle("");
plotmtotBkg[c]->Draw();
if (dobands) {
RooAbsPdf *cpdf; cpdf = mtotBkg;
TGraphAsymmErrors *onesigma = new TGraphAsymmErrors();
TGraphAsymmErrors *twosigma = new TGraphAsymmErrors();
RooRealVar *nlim = new RooRealVar(TString::Format("nlim%d",c),"",0.0,0.0,10.0);
nlim->removeRange();
RooCurve *nomcurve = dynamic_cast<RooCurve*>(plotmtotBkg[c]->getObject(1));
for (int i=1; i<(plotmtotBkg[c]->GetXaxis()->GetNbins()+1); ++i) {
double lowedge = plotmtotBkg[c]->GetXaxis()->GetBinLowEdge(i);
double upedge = plotmtotBkg[c]->GetXaxis()->GetBinUpEdge(i);
double center = plotmtotBkg[c]->GetXaxis()->GetBinCenter(i);
double nombkg = nomcurve->interpolate(center);
nlim->setVal(nombkg);
mtot->setRange("errRange",lowedge,upedge);
RooAbsPdf *epdf = 0;
epdf = new RooExtendPdf("epdf","",*cpdf,*nlim,"errRange");
RooAbsReal *nll = epdf->createNLL(*(data[c]),Extended());
RooMinimizer minim(*nll);
minim.setStrategy(0);
double clone = 1.0 - 2.0*RooStats::SignificanceToPValue(1.0);
double cltwo = 1.0 - 2.0*RooStats::SignificanceToPValue(2.0);
minim.migrad();
minim.minos(*nlim);
// printf("errlo = %5f, errhi = %5f\n",nlim->getErrorLo(),nlim->getErrorHi());
onesigma->SetPoint(i-1,center,nombkg);
onesigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());
minim.setErrorLevel(0.5*pow(ROOT::Math::normal_quantile(1-0.5*(1-cltwo),1.0), 2));
// the 0.5 is because qmu is -2*NLL
minim.migrad();
minim.minos(*nlim);
twosigma->SetPoint(i-1,center,nombkg);
twosigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());
delete nll;
delete epdf;
} // close for each bin
if (c==0) mtot->setRange("errRange",minMassFit,maxMassFit);
if (c==1) mtot->setRange("errRange",minMassFit,maxMassFit);
twosigma->SetLineColor(kYellow-4);
twosigma->SetFillColor(kYellow-4);
twosigma->SetMarkerColor(kYellow-4);
twosigma->Draw("L3 SAME");
onesigma->SetLineColor(kGreen);
onesigma->SetFillColor(kGreen);
onesigma->SetMarkerColor(kGreen);
onesigma->Draw("L3 SAME");
//plotmtotBkg[c]->Draw("SAME");
} // close dobands
if(doblinding) emptyplot[c]->plotOn(plotmtotBkg[c], Invisible(), Name(Form("emptyplot_cat%d_plot",c)));
else emptyplot[c]->plotOn(plotmtotBkg[c], Name(Form("emptyplot_cat%d_plot",c)), MarkerSize(0));
const double alpha = 1 - 0.6827;
for (int i = 0; i < (plotmtotBkg[c]->getHist(Form("Dataplot_cat%d_plot",c)))->GetN() ; i++)
{
Double_t x,y;
(plotmtotBkg[c]->getHist(Form("Dataplot_cat%d_plot",c)))->GetPoint(i, x, y);
int N = y;
double L = (N==0) ? 0 : (ROOT::Math::gamma_quantile(alpha/2,N,1.));
double U = ROOT::Math::gamma_quantile_c(alpha/2,N+1,1);
(plotmtotBkg[c]->getHist(Form("Dataplot_cat%d_plot",c)))->SetPointError(i, 0, 0, N-L, U-N);
if (N==0)
{
(plotmtotBkg[c]->getHist(Form("emptyplot_cat%d_plot",c)))->SetPoint(i, x, 1.0e-6);
(plotmtotBkg[c]->getHist(Form("emptyplot_cat%d_plot",c)))->SetPointError(i, 0, 0, N-L, U-N);
} else {
(plotmtotBkg[c]->getHist(Form("emptyplot_cat%d_plot",c)))->SetPoint(i, x, 0.);
}
}
//plotlinemtotBkg[c]->Draw("SAME");
// //plotmtotBkg[c]->getObject(1)->Draw("SAME");
// if(doblinding) dataplot[c]->plotOn(plotmtotBkg[c],Invisible());
// else dataplot[c]->plotOn(plotmtotBkg[c]);
int nbins = (plotmtotBkg[c]->getHist(Form("Dataplot_cat%d_plot",c)))->GetN();
if(doblinding) dataplot[c]->plotOn(plotmtotBkg[c], Invisible(), Name(Form("Dataplot_cat%d_plot",c)));
else dataplot[c]->plotOn(plotmtotBkg[c], Name(Form("Dataplot_cat%d_plot",c)));
const double alpha = 1 - 0.6827;
for (int i = 0; i < nbins ; i++)
{
Double_t x,y;
(plotmtotBkg[c]->getHist(Form("Dataplot_cat%d_plot",c)))->GetPoint(i, x, y);
int N = y;
double L = (N==0) ? 0 : (ROOT::Math::gamma_quantile(alpha/2,N,1.));
double U = ROOT::Math::gamma_quantile_c(alpha/2,N+1,1);
(plotmtotBkg[c]->getHist(Form("Dataplot_cat%d_plot",c)))->SetPointError(i, 0, 0, N-L, U-N);
}
plotmtotBkg[c]->Draw("SAME");
plotmtotBkg[c]->GetYaxis()->SetRangeUser(1.0e-7,10);
if(c==0) plotmtotBkg[c]->SetMaximum(5.5);
if (c==1) plotmtotBkg[c]->SetMaximum(13);
plotmtotBkg[c]->GetXaxis()->SetTitle("m_{#gamma#gammajj}^{kin} (GeV)");
plotmtotBkg[c]->SetYTitle(Form("Events / %i GeV", (int)plotmtotBkg[c]->getFitRangeBinW()));
// plotmtotBkg[c]->Draw("AC");
//////////////////////////////////////////////////////////////////
TPaveText *pt = new TPaveText(0.2,0.93,0.8,0.99, "brNDC");
// pt->SetName("title");
pt->SetBorderSize(0);
pt->SetFillColor(0);
// pt->SetShadowColor(kWhite);
pt->AddText(" CMS Preliminary L = 19.7 fb^{-1} #sqrt{s} = 8 TeV ");
pt->SetTextSize(0.04);
// pt->Draw();
TLatex *latexLabel = new TLatex();
latexLabel->SetTextSize(0.75 * ctmp->GetTopMargin());
latexLabel->SetNDC();
latexLabel->SetTextFont(42); // helvetica
latexLabel->DrawLatex(0.72, 0.96, "19.7 fb^{-1} (8 TeV)");
latexLabel->SetTextFont(61); // helvetica bold face
latexLabel->DrawLatex(0.19, 0.89, "CMS");
////////////////////////////////////////////////////////////////////
ctmp->SetLogy(0);
// ctmp->SetGrid(0);
cout << "!!!!!!!!!!!!!!!!!" << endl;
TLegend *legmc = new TLegend(0.37,0.75,0.85,0.80);
TLegend *legmc2 = new TLegend(0.52,0.70,0.84,0.75);
legmc->SetTextFont(41);
legmc->SetNColumns(2);
legmc2->SetTextFont(42);
legmc2->SetNColumns(2);
if(doblinding) legmc->AddEntry(plotmtotBkg[c]->getObject(3),"Data ","");
else legmc->AddEntry(plotmtotBkg[c]->getObject(3),"Data ","LPE");
legmc->AddEntry(plotmtotBkg[c]->getObject(1), "Background model","L");
if(dobands)legmc2->AddEntry(onesigma,"68% CL","F");
if(dobands)legmc2->AddEntry(twosigma,"95% CL","F");
//legmc->SetHeader("m_{X} = 550 GeV");
legmc2->SetBorderSize(0);
legmc2->SetFillStyle(0);
legmc2->Draw();
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
latexLabel->SetTextFont(42); // helvetica
// latexLabel->SetTextSize(0.6 * ctmp->GetTopMargin());
latexLabel->DrawLatex(0.37, 0.88, "pp #rightarrow X #rightarrow HH #rightarrow #gamma#gammab#bar{b}");
latexLabel->DrawLatex(0.37, 0.83, catdesc.at(c));
TLatex *lat1 = new TLatex(minfit+43.0,0.91*plotmtotBkg[c]->GetMaximum(),"pp #rightarrow X #rightarrow HH #rightarrow #gamma#gammab#bar{b}");
// lat1->Draw();
TLatex *lat2 = new TLatex(minfit+43.0,0.81*plotmtotBkg[c]->GetMaximum(),catdesc.at(c));
// lat2->Draw();
ctmp->SaveAs(TString::Format("databkgoversig_cat%d.pdf",c));
cout<<"here 2 "<< c<<endl;
ctmp->SaveAs(TString::Format("databkgoversig_cat%d.png",c));
ctmp->SaveAs(TString::Format("databkgoversig_cat%d.root",c));
cout<<"here 3 "<< c<<endl;
//ctmp->SaveAs(TString::Format("databkgoversig_cat%d.C",c));
} // close to each category
cout<<"here out loop"<<endl;
return fitresult;
} // close berestein 3
///////////////////////////////////////////////////////////////
void MakeSigWS(RooWorkspace* w, const char* fileBaseName) {
TString wsDir = "workspaces/";
const Int_t ncat = NCAT;
//**********************************************************************//
// Write pdfs and datasets into the workspace
// for statistical tests.
//**********************************************************************//
RooAbsPdf* mtotSigPdf[ncat];
RooWorkspace *wAll = new RooWorkspace("w_all","w_all");
// import pdfs from previous fit calculation before to save
for (int c = 0; c < ncat; ++c) {
mtotSigPdf[c] = (RooAbsPdf*) w->pdf(TString::Format("mtotSig_cat%d",c));
wAll->import(*w->pdf(TString::Format("mtotSig_cat%d",c))); // import datasets from previous fit calculation
}
// (2) Systematics on energy scale and resolution
// 1,1,1 statistical to be treated on the datacard
wAll->factory("CMS_hgg_sig_m0_absShift[1,1,1]");
// wAll->factory("CMS_hgg_sig_m0_absShift_cat1[1,1,1]");
// wAll->factory("CMS_hgg_sig_m0_absShift_cat2[1,1,1]"); //CHANGE
//
wAll->factory("prod::CMS_hgg_sig_m0_cat0(mtot_sig_m0_cat0, CMS_hgg_sig_m0_absShift)");
wAll->factory("prod::CMS_hgg_sig_m0_cat1(mtot_sig_m0_cat1, CMS_hgg_sig_m0_absShift)");
// (3) Systematics on resolution
// 1,1,1 statistical to be treated on the datacard
wAll->factory("CMS_hgg_sig_sigmaScale[1,1,1]");
//
wAll->factory("prod::CMS_hgg_sig_sigma_cat0(mtot_sig_sigma_cat0, CMS_hgg_sig_sigmaScale)");
wAll->factory("prod::CMS_hgg_sig_sigma_cat1(mtot_sig_sigma_cat1, CMS_hgg_sig_sigmaScale)");
//
wAll->factory("prod::CMS_hgg_sig_gsigma_cat0(mtot_sig_gsigma_cat0, CMS_hgg_sig_sigmaScale)");
wAll->factory("prod::CMS_hgg_sig_gsigma_cat1(mtot_sig_gsigma_cat1, CMS_hgg_sig_sigmaScale)");
// (4) do reparametrization of signal
for (int c = 0; c < ncat; ++c) wAll->factory(
TString::Format("EDIT::CMS_hgg_sig_cat%d(mtotSig_cat%d,",c,c) +
TString::Format(" mtot_sig_m0_cat%d=CMS_hgg_sig_m0_cat%d, ", c,c) +
TString::Format(" mtot_sig_sigma_cat%d=CMS_hgg_sig_sigma_cat%d, ", c,c) +
TString::Format(" mtot_sig_gsigma_cat%d=CMS_hgg_sig_gsigma_cat%d)", c,c)
);
TString filename(wsDir+TString(fileBaseName)+".inputsig.root");
wAll->writeToFile(filename);
cout << "Write signal workspace in: " << filename << " file" << endl;
return;
} // close make signal WP
////////////////////////////////////////////////////////////////
void MakeBkgWS(RooWorkspace* w, const char* fileBaseName) {
TString wsDir = "workspaces/";
const Int_t ncat = NCAT;
//**********************************************************************//
// Write pdfs and datasets into the workspace
// for statistical tests.
//**********************************************************************//
RooDataSet* data[ncat];
RooAbsPdf* mtotBkgPdf[ncat];
// (1) import everything functions before to save to a file
RooWorkspace *wAll = new RooWorkspace("w_all","w_all");
for (int c = 0; c < ncat; ++c) {
data[c] = (RooDataSet*) w->data(TString::Format("Data_cat%d",c));
//RooDataHist* dataBinned = data[c]->binnedClone(); // Uncomment if you want to use wights in the limits
mtotBkgPdf[c] = (RooAbsPdf*) w->pdf(TString::Format("mtotBkg_cat%d",c));
wAll->import(*data[c], Rename(TString::Format("data_obs_cat%d",c))); // Comment if you want to use wights in the limits
//wAll->import(*dataBinned, Rename(TString::Format("data_obs_cat%d",c))); // Uncomment if you want to use wights in the limits
wAll->import(*w->pdf(TString::Format("mtotBkg_cat%d",c)));
wAll->import(*w->var(TString::Format("mtot_bkg_8TeV_cat%d_norm",c)));
wAll->factory(
TString::Format("CMS_hgg_bkg_8TeV_cat%d_norm[%g,0.0,100000.0]",
c, wAll->var(TString::Format("mtot_bkg_8TeV_cat%d_norm",c))->getVal()));
wAll->factory(
TString::Format("CMS_hgg_bkg_8TeV_slope1_cat%d[%g, -10., 10.]",
c, wAll->var(TString::Format("mtot_bkg_8TeV_slope1_cat%d",c))->getVal()));
/* if(c==0)wAll->factory(
TString::Format("CMS_hgg_bkg_8TeV_slope2_cat%d[%g,0,0]",
c, wAll->var(TString::Format("mtot_bkg_8TeV_slope2_cat%d",c))->getVal()));
*/
/*if(c==1)wAll->factory(
TString::Format("CMS_hgg_bkg_8TeV_slope2_cat%d[%g,800, 1200]",
c, wAll->var(TString::Format("mtot_bkg_8TeV_slope2_cat%d",c))->getVal()));*/
}
// (2) do reparametrization of background
for (int c = 0; c < ncat; ++c){
if(c==0) wAll->factory(
TString::Format("EDIT::CMS_hgg_bkg_8TeV_cat%d(mtotBkg_cat%d,",c,c) +
TString::Format(" mtot_bkg_8TeV_cat%d_norm=CMS_hgg_bkg_8TeV_cat%d_norm,", c,c)+
TString::Format(" mtot_bkg_8TeV_slope1_cat%d=CMS_hgg_bkg_8TeV_slope1_cat%d)", c,c)
);
if(c==1) wAll->factory(
TString::Format("EDIT::CMS_hgg_bkg_8TeV_cat%d(mtotBkg_cat%d,",c,c) +
TString::Format(" mtot_bkg_8TeV_cat%d_norm=CMS_hgg_bkg_8TeV_cat%d_norm,", c,c)+
TString::Format(" mtot_bkg_8TeV_slope1_cat%d=CMS_hgg_bkg_8TeV_slope1_cat%d)", c,c)
);
} // close for cat
TString filename(wsDir+TString(fileBaseName)+".root");
wAll->writeToFile(filename);
cout << "Write background workspace in: " << filename << " file" << endl;
std::cout << "observation ";
for (int c = 0; c < ncat; ++c) {
std::cout << " " << wAll->data(TString::Format("data_obs_cat%d",c))->sumEntries();
}
std::cout << std::endl;
return;
} // close make BKG workspace
////////////////////////////////////////////////////////////////////
void SetConstantParams(const RooArgSet* params) {
// set constant parameters for signal fit, ... NO IDEA !!!!
TIterator* iter(params->createIterator());
for (TObject *a = iter->Next(); a != 0; a = iter->Next()) {
RooRealVar *rrv = dynamic_cast<RooRealVar *>(a);
if (rrv) { rrv->setConstant(true); std::cout << " " << rrv->GetName(); }
}
} // close set const parameters
////////////////////////////////////////////////////////////////////////
void MakePlots(RooWorkspace* w, Float_t Mass, RooFitResult* fitresults) {
const Int_t ncat = NCAT;
const int minsigfit =Mass - 120, maxsigfit=Mass +120;
std::vector<TString> catdesc;
catdesc.push_back("High-purity");//2 btag");
catdesc.push_back("Medium-purity");//1 btag");
RooDataSet* signalAll = (RooDataSet*) w->data("Sig");
// blinded dataset
RooDataSet* sigToFit[ncat];
RooAbsPdf* mtotGaussSig[ncat];
RooAbsPdf* mtotCBSig[ncat];
RooAbsPdf* mtotSig[ncat];
for (int c = 0; c < ncat; ++c) {
sigToFit[c] = (RooDataSet*) w->data(TString::Format("Sig_cat%d",c));
mtotGaussSig[c] = (RooAbsPdf*) w->pdf(TString::Format("mtotGaussSig_cat%d",c));
mtotCBSig[c] = (RooAbsPdf*) w->pdf(TString::Format("mtotCBSig_cat%d",c));
mtotSig[c] = (RooAbsPdf*) w->pdf(TString::Format("mtotSig_cat%d",c));
} // close categories
RooRealVar* mtot = w->var("mtot");
mtot->setUnit("GeV");
RooAbsPdf* mtotGaussSigAll = w->pdf("mtotGaussSig");
RooAbsPdf* mtotCBSigAll = w->pdf("mtotCBSig");
RooAbsPdf* mtotSigAll = w->pdf("mtotSig");
RooAbsPdf* mtotBkgAll = w->pdf("mtotBkg_cat1");
//****************************//
// Plot mtot Fit results
//****************************//
Float_t minMassFit(minsigfit),maxMassFit(maxsigfit);
Float_t MASS(Mass);
Int_t nBinsMass(60);
RooPlot* plotmtotAll = mtot->frame(Range(minMassFit,maxMassFit),Bins(nBinsMass));
//****************************//
// Plot Signal Categories
//****************************//
//TLatex *text = new TLatex();
//text->SetNDC();
//text->SetTextSize(0.04);
RooPlot* plotmtot[ncat];
Int_t nBinsMass(24);
for (int c = 0; c < ncat; ++c) {
if(c==0)plotmtot[c] = mtot->frame(Range(minMassFit,maxMassFit),Bins(nBinsMass));
if(c==1)plotmtot[c] = mtot->frame(Range(minMassFit,maxMassFit),Bins(nBinsMass));
sigToFit[c]->plotOn(plotmtot[c], MarkerStyle(25));
mtotSig[c] ->plotOn(plotmtot[c]);
double chi2n = plotmtot[c]->chiSquare(0) ;
cout << "------------------------- Experimentakl chi2 = " << chi2n << endl;
if (details_signal_model) mtotSig[c] ->plotOn(
plotmtot[c],
Components(TString::Format("mtotGaussSig_cat%d",c)),
LineStyle(kDashed),LineColor(kGreen));
if (details_signal_model) mtotSig[c] ->plotOn(
plotmtot[c],
Components(TString::Format("mtotCBSig_cat%d",c)),
LineStyle(kDashed),LineColor(kRed));
//mtotSig[c] ->paramOn(plotmtot[c]);
sigToFit[c] ->plotOn(plotmtot[c], MarkerStyle(25));
// TCanvas* dummy = new TCanvas("dummy", "dummy",0, 0, 450, 450);
//TH1F *hist = new TH1F("hist", "hist", 450, minMassFit, maxMassFit);
TCanvas* ctmp = new TCanvas(TString::Format("ctmpSig_cat%d",c),"Background Categories",0,0,501,501);
ctmp->cd();
plotmtot[c]->Draw("AC");
plotmtot[c]->SetTitle("");
//plotmtot[c]->Draw();
plotmtot[c]->SetMinimum(0.0);
plotmtot[c]->SetMaximum(1.40*plotmtot[c]->GetMaximum());
plotmtot[c]->GetXaxis()->SetTitle("m_{#gamma#gammajj}^{kin} (GeV)");
plotmtot[c]->SetYTitle(Form("Norm. to unity / %i GeV", (int)plotmtot[c]->getFitRangeBinW()));
plotmtot[c]->Draw("SAME");
TLegend *legmc = new TLegend(0.36,0.70,0.93,0.76);
legmc->SetTextFont(42);
legmc->SetTextSize(0.75 * ctmp->GetTopMargin());
legmc->SetNColumns(2);
std::cout << "plotmtot[c]->getObject(0)= " << plotmtot[c]->getObject(0) << std::endl;
legmc->AddEntry(plotmtot[c]->getObject(0),"Simulation","LPE");
if (details_signal_model) legmc->AddEntry(plotmtot[c]->getObject(2),"Gaussian ","L");
legmc->AddEntry(plotmtot[c]->getObject(1),"Parametric model","L");
if (details_signal_model) legmc->AddEntry(plotmtot[c]->getObject(3),"Crystal Ball ","L");
//legmc->SetHeader(" ");
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
// float effS = effSigma(hist);
TLatex *lat = new TLatex(
minMassFit+10.5,0.91*plotmtot[c]->GetMaximum(),
"X#rightarrowHH#rightarrow#gamma#gammab#bar{b}");
// lat->Draw();
TLatex *lat2 = new TLatex(
minMassFit+10.5,0.81*plotmtot[c]->GetMaximum(),
"m_{X} = 550 GeV");
// lat2->Draw();
TLatex *lat2 = new TLatex(
minMassFit+10.5,0.71*plotmtot[c]->GetMaximum(),catdesc.at(c));
// lat2->Draw();
TPaveText *pt = new TPaveText(0.2,0.93,0.8,0.99, "brNDC");
// pt->SetName("title");
pt->SetBorderSize(0);
pt->SetFillColor(0);
// pt->SetShadowColor(kWhite);
pt->AddText(" CMS Preliminary L = 19.7 fb^{-1} #sqrt{s} = 8 TeV ");
pt->SetTextSize(0.04);
// pt->Draw();
TLatex *latexLabel = new TLatex();
latexLabel->SetTextSize(0.75 * ctmp->GetTopMargin());
latexLabel->SetNDC();
latexLabel->SetTextFont(42); // helvetica
latexLabel->DrawLatex(0.87, 0.96, "8 TeV");
latexLabel->SetTextFont(61); // helvetica bold face
latexLabel->DrawLatex(0.19, 0.89, "CMS");
latexLabel->SetTextFont(52); // helvetica italics
latexLabel->DrawLatex(0.19, 0.85, "Simulation");
latexLabel->DrawLatex(0.19, 0.81, "Supplementary");
latexLabel->SetTextFont(42); // helvetica
// latexLabel->SetTextSize(0.6 * ctmp->GetTopMargin());
latexLabel->DrawLatex(0.45, 0.88, "pp #rightarrow X #rightarrow HH #rightarrow #gamma#gammab#bar{b}");
latexLabel->DrawLatex(0.45, 0.83, "m_{X} = 550 GeV");
latexLabel->DrawLatex(0.45, 0.78, catdesc.at(c));
ctmp->SaveAs(TString::Format("sigmodel_cat%d.pdf",c));
ctmp->SaveAs(TString::Format("sigmodel_cat%d.png",c));
ctmp->SaveAs(TString::Format("sigmodel_cat%d.root",c));
} // close categories
return;
} // close makeplots
// with reparametrization of BKG
void MakeDataCardREP(RooWorkspace* w, const char* fileBaseName, const char* fileBkgName) {
TString cardDir = "datacards/";
const Int_t ncat = NCAT;
RooDataSet* data[ncat];
RooDataSet* sigToFit[ncat];
for (int c = 0; c < ncat; ++c) {
data[c] = (RooDataSet*) w->data(TString::Format("Data_cat%d",c));
sigToFit[c] = (RooDataSet*) w->data(TString::Format("Sig_cat%d",c));
}
RooRealVar* lumi = w->var("lumi");
cout << "======== Expected Events Number =====================" << endl;
cout << ".........Measured Data for L = " << lumi->getVal() << " pb-1 ............................" << endl;
if(!doblinding){ cout << "#Events data: " << data[0]->sumEntries() + data[1]->sumEntries() << endl;}
else cout << "#Events data: -1 " << endl;
if(!doblinding){
for (int c = 0; c < ncat; ++c) {
cout << TString::Format("#Events data cat%d: ",c) << data[c]->sumEntries() << endl;
}
}else{
for (int c = 0; c < ncat; ++c) {
cout << TString::Format("#Events data cat%d: ",c) << -1 << endl;
}
}
cout << ".........Expected Signal for L = " << lumi->getVal() << " pb-1 ............................" << endl;
cout << "#Events Signal: " << sigToFit[0]->sumEntries()+sigToFit[1]->sumEntries() << endl;
Float_t siglikeErr[ncat];
for (int c = 0; c < ncat; ++c) {
cout << TString::Format("#Events Signal cat%d: ",c) << sigToFit[c]->sumEntries() << endl;
siglikeErr[c]=0.6*sigToFit[c]->sumEntries();
}
cout << "====================================================" << endl;
TString filename(cardDir+TString(fileBaseName)+"rep.txt");
ofstream outFile(filename);
outFile << "#CMS-HGG DataCard for Unbinned Limit Setting, " << lumi->getVal() << " pb-1 " << endl;
outFile << "#Run with: combine -d hgghbb.mH130.0.shapes-Unbinned.txt -U -m 130 -H ProfileLikelihood -M MarkovChainMC --rMin=0 --rMax=20.0 -b 3000 -i 50000 --optimizeSim=1 --tries 30" << endl;
outFile << "# Lumi = " << lumi->getVal() << " pb-1" << endl;
outFile << "imax "<<ncat << endl;
outFile << "jmax 1" << endl;
outFile << "kmax *" << endl;
outFile << "---------------" << endl;
cout<<"here"<<endl;
outFile << "# the name after w_all is the name of the rooextpdf we want to use, we have both saved" << endl;
outFile << "# BKG" << endl;
outFile << "shapes data_obs cat0 " << TString(fileBkgName)+".root" << " w_all:data_obs_cat0" << endl;
outFile << "shapes data_obs cat1 "<< TString(fileBkgName)+".root" << " w_all:data_obs_cat1" << endl;
outFile << "############## shape with reparametrization" << endl;
outFile << "shapes mtotBkg cat0 " << TString(fileBkgName)+".root" << " w_all:CMS_hgg_bkg_8TeV_cat0" << endl;
outFile << "shapes mtotBkg cat1 "<< TString(fileBkgName)+".root" << " w_all:CMS_hgg_bkg_8TeV_cat1" << endl;
outFile << "# signal" << endl;
outFile << "shapes mtotSig cat0 " << TString(fileBaseName)+".inputsig.root" << " w_all:CMS_hgg_sig_cat0" << endl;
outFile << "shapes mtotSig cat1 " << TString(fileBaseName)+".inputsig.root" << " w_all:CMS_hgg_sig_cat1" << endl;
outFile << "---------------" << endl;
/////////////////////////////////////
/////////////////////////////////////
outFile << "bin cat0 cat1 " << endl;
if(!doblinding){ outFile << "observation "
<< data[0]->sumEntries() << " "
<< data[1]->sumEntries() << " "
<< endl;
}else outFile << "observation -1 -1 " << endl;
outFile << "------------------------------" << endl;
outFile << "bin cat0 cat0 cat1 cat1" << endl;
outFile << "process mtotSig mtotBkg mtotSig mtotBkg" << endl;
outFile << "process 0 1 0 1" << endl;
outFile << "rate "
<< " " << sigToFit[0]->sumEntries() << " " << 1
<< " " << sigToFit[1]->sumEntries() << " " << 1
<< " " << endl;
outFile << "--------------------------------" << endl;
outFile << "lumi_8TeV lnN "
<< "1.026 - "
<< "1.026 - " << endl;
outFile << "DiphoTrigger lnN "
<< "1.01 - "
<< "1.01 - "
<< "# Trigger efficiency" << endl;
outFile << "############## jet" << endl;
outFile << "Extra_Photon_selectios_accep lnN "
<< "1.050 - "
<< "1.050 - "
<<"# photon acceptance " << endl;
outFile << "Photon_selectios_accep lnN "
<< "1.010 - "
<< "1.010 - "
<<"# photon acceptance = sqrt(0.8^2 +5^2)" << endl;
outFile << "Mjj_acceptance lnN "
<< "1.015 - "
<< "1.015 - "
<<"# JER and JES " << endl;
outFile << "btag_eff lnN "
<< "1.050 - "
<< "0.972 - "
<<"# b tag efficiency uncertainty" << endl;
outFile << "############## photon " << endl;
outFile << "CMS_hgg_eff_g lnN "
<< "1.010 - "
<< "1.010 - "
<< "# photon selection accep." << endl;
outFile << "############## for mtot fit" << endl;
outFile << "maa_acceptance lnN "
<< "1.005 - "
<< "1.005 - "
<< "# photon energy resolution" << endl;
outFile << "############## normalization floating" << endl;
outFile << "# Parametric shape uncertainties, entered by hand. they act on both higgs/signal " << endl;
outFile << "CMS_hgg_sig_m0_absShift param 1 0.014 # displacement of the dipho mean (0.45 + 0.8 + 1.0) in quadrature" << endl;
outFile << "CMS_hgg_sig_sigmaScale param 1 0.10 # optimistic estimative of resolution uncertainty " << endl;
outFile << "############## for mtot fit - slopes" << endl;
outFile << "############## with reparametrization" << endl;
outFile << "CMS_hgg_bkg_8TeV_cat0_norm flatParam # Normalization uncertainty on background slope" << endl;
outFile << "CMS_hgg_bkg_8TeV_cat1_norm flatParam # Normalization uncertainty on background slope" << endl;
outFile << "CMS_hgg_bkg_8TeV_slope1_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile << "CMS_hgg_bkg_8TeV_slope1_cat1 flatParam # Mean and absolute uncertainty on background slope" << endl;
//outFile << "CMS_hgg_bkg_8TeV_slope2_cat1 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile.close();
cout << "Write data card in: " << filename << " file" << endl;
return;
} // close write datacard with rep
//////////////////////////////////////////////////
void MakeDataCardonecat(RooWorkspace* w, const char* fileBaseName, const char* fileBkgName) {
TString cardDir = "datacards/";
const Int_t ncat = 1;
RooDataSet* data[ncat];
RooDataSet* sigToFit[ncat];
for (int c = 0; c < ncat; ++c) {
data[c] = (RooDataSet*) w->data(TString::Format("Data_cat%d",c));
sigToFit[c] = (RooDataSet*) w->data(TString::Format("Sig_cat%d",c));
}
RooRealVar* lumi = w->var("lumi");
cout << "======== Expected Events Number =====================" << endl;
cout << ".........Measured Data for L = " << lumi->getVal() << " pb-1 ............................" << endl;
if(!doblinding){ cout << "#Events data: " << data[0]->sumEntries() << endl; }
else cout << "#Events data: -1 " << endl;
if(!doblinding){
for (int c = 0; c < ncat; ++c)
cout << TString::Format("#Events data cat%d: ",c) << data[c]->sumEntries() << endl;
}else{
for (int c = 0; c < ncat; ++c)
cout << TString::Format("#Events data cat%d: ",c) << -1 << endl;
}
cout << ".........Expected Signal for L = " << lumi->getVal() << " pb-1 ............................" << endl;
cout << "#Events Signal: " << sigToFit[0]->sumEntries() << endl;
Float_t siglikeErr[ncat];
for (int c = 0; c < ncat; ++c) {
cout << TString::Format("#Events Signal cat%d: ",c) << sigToFit[c]->sumEntries() << endl;
siglikeErr[c]=0.6*sigToFit[c]->sumEntries();
}
cout << "====================================================" << endl;
TString filename(cardDir+TString(fileBaseName)+"onecat.txt");
ofstream outFile(filename);
outFile << "#CMS-HGG DataCard for Unbinned Limit Setting, " << lumi->getVal() << " pb-1 " << endl;
outFile << "#Run with: combine -d hgghbb.mH130.0.shapes-Unbinned.txt -U -m 130 -H ProfileLikelihood -M MarkovChainMC --rMin=0 --rMax=20.0 -b 3000 -i 50000 --optimizeSim=1 --tries 30" << endl;
outFile << "# Lumi = " << lumi->getVal() << " pb-1" << endl;
outFile << "imax 1" << endl;
outFile << "jmax 1" << endl;
outFile << "kmax *" << endl;
outFile << "---------------" << endl;
cout<<"here"<<endl;
outFile << "# the name after w_all is the name of the rooextpdf we want to use, we have both saved" << endl;
outFile << "# BKG" << endl;
outFile << "shapes data_obs cat0 " << TString(fileBkgName)+".root" << " w_all:data_obs_cat0" << endl;
outFile << "shapes data_obs cat1 "<< TString(fileBkgName)+".root" << " w_all:data_obs_cat1" << endl;
outFile << "############## shape with reparametrization" << endl;
outFile << "shapes mtotBkg cat0 " << TString(fileBkgName)+".root" << " w_all:CMS_hgg_bkg_8TeV_cat0" << endl;
outFile << "shapes mtotBkg cat1 "<< TString(fileBkgName)+".root" << " w_all:CMS_hgg_bkg_8TeV_cat1" << endl;
outFile << "# signal" << endl;
outFile << "shapes mtotSig cat0 " << TString(fileBaseName)+".inputsig.root" << " w_all:CMS_hgg_sig_cat0" << endl;
outFile << "shapes mtotSig cat1 " << TString(fileBaseName)+".inputsig.root" << " w_all:CMS_hgg_sig_cat1" << endl;
outFile << "---------------" << endl;
/////////////////////////////////////
/////////////////////////////////////
outFile << "bin cat0 " << endl;
if(!doblinding){ outFile << "observation "
<< data[0]->sumEntries() << " "
<< endl;
}else{
outFile << "observation -1 " << endl;
}
outFile << "------------------------------" << endl;
outFile << "bin cat0 cat0 " << endl;
outFile << "process mtotSig mtotBkg" << endl;
outFile << "process 0 1 " << endl;
outFile << "rate "
<< " " << sigToFit[0]->sumEntries() << " " << 1
<< " " << endl;
outFile << "--------------------------------" << endl;
outFile << "lumi_8TeV lnN "
<< "1.026 - "
<< endl;
outFile << "############## jet" << endl;
outFile << "Mjj_acceptance lnN "
<< "1.015 - "
<<"# JER and JES " << endl;
outFile << "btag_eff lnN "
<< "1.050 - "
<<"# b tag efficiency uncertainty" << endl;
outFile << "############## photon " << endl;
outFile << "CMS_hgg_eff_g lnN "
<< "1.010 - "
<< "# photon selection accep." << endl;
outFile << "DiphoTrigger lnN "
<< "1.01 - "
<< "# Trigger efficiency" << endl;
outFile << "############## for mtot fit" << endl;
outFile << "maa_acceptance lnN "
<< "1.005 - "
<< "# photon energy resolution" << endl;
outFile << "Photon_selectios_accep lnN "
<< "1.01 - "
<<"# photon acceptance = sqrt(0.8^2 +5^2)" << endl;
outFile << "############## normalization floating" << endl;
outFile << "# Parametric shape uncertainties, entered by hand. they act on both higgs/signal " << endl;
outFile << "CMS_hgg_sig_m0_absShift param 1 0.014 # displacement of the dipho mean" << endl;
outFile << "CMS_hgg_sig_sigmaScale param 1 0.10 # optimistic estimative of resolution uncertainty " << endl;
outFile << "############## for mtot fit - slopes" << endl;
outFile << "############## with reparametrization" << endl;
outFile << "CMS_hgg_bkg_8TeV_cat0_norm flatParam # Normalization uncertainty on background slope" << endl;
outFile << "CMS_hgg_bkg_8TeV_slope1_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
//outFile << "CMS_hgg_bkg_8TeV_slope2_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile.close();
cout << "Write data card in: " << filename << " file" << endl;
return;
} // close write datacard
void style(){
TStyle *defaultStyle = new TStyle("defaultStyle","Default Style");
defaultStyle->SetOptStat(0000);
defaultStyle->SetOptFit(000);
defaultStyle->SetPalette(1);
/////// pad ////////////
defaultStyle->SetPadBorderMode(1);
defaultStyle->SetPadBorderSize(1);
defaultStyle->SetPadColor(0);
defaultStyle->SetPadTopMargin(0.05);
defaultStyle->SetPadBottomMargin(0.13);
defaultStyle->SetPadLeftMargin(0.15);
defaultStyle->SetPadRightMargin(0.04);
/////// canvas /////////
defaultStyle->SetCanvasBorderMode(0);
defaultStyle->SetCanvasColor(0);
defaultStyle->SetCanvasDefH(600);
defaultStyle->SetCanvasDefW(600);
/////// frame //////////
defaultStyle->SetFrameBorderMode(0);
defaultStyle->SetFrameBorderSize(1);
defaultStyle->SetFrameFillColor(0);
defaultStyle->SetFrameLineColor(1);
/////// label //////////
defaultStyle->SetLabelOffset(0.005,"XY");
defaultStyle->SetLabelSize(0.05,"XY");
defaultStyle->SetLabelFont(42,"XY");
/////// title //////////
defaultStyle->SetTitleOffset(1.1,"X");
defaultStyle->SetTitleSize(0.01,"X");
defaultStyle->SetTitleOffset(1.10,"Y");
defaultStyle->SetTitleSize(0.05,"Y");
defaultStyle->SetTitleFont(42, "XYZ");
/////// various ////////
defaultStyle->SetNdivisions(505,"Y");
defaultStyle->SetLegendBorderSize(0); // For the axis titles:
defaultStyle->SetTitleColor(1, "XYZ");
defaultStyle->SetTitleFont(42, "XYZ");
defaultStyle->SetTitleSize(0.06, "XYZ");
defaultStyle->SetTitleXOffset(0.9);
defaultStyle->SetTitleYOffset(1.05);
// For the axis labels:
defaultStyle->SetLabelColor(1, "XYZ");
defaultStyle->SetLabelFont(42, "XYZ");
defaultStyle->SetLabelOffset(0.007, "XYZ");
defaultStyle->SetLabelSize(0.04, "XYZ");
// For the axis:
defaultStyle->SetAxisColor(1, "XYZ");
defaultStyle->SetStripDecimals(kTRUE);
defaultStyle->SetTickLength(0.03, "XYZ");
defaultStyle->SetNdivisions(510, "XYZ");
defaultStyle->SetPadTickX(1);
defaultStyle->SetPadTickY(1);
defaultStyle->cd();
return;
}
void SetParamNames(RooWorkspace* w) { // not used it if Workspaces are created => float fit
const Int_t ncat = NCAT;
//****************************//
// mtot signal all categories
//****************************//
RooRealVar* mtot_sig_m0 = w->var("mtot_sig_m0");