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doWP_tomgg.cc
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// Alexandra Oliveira
//
// template by Serguei and Chiara
//
using namespace RooFit;
using namespace RooStats ;
//
// this code is frozen to use 2 b tag categories with leveled exponential
//
// declare the functions
void AddSigData(RooWorkspace* w, Float_t, const char* filename);
void AddBkgData(RooWorkspace* w, Float_t, const char* filename, bool dobands);
void MakeDataCard(RooWorkspace* sig, RooWorkspace* bkg, const char* fileBaseName, const char* fileBkgName);
void MakeDataCardoneCat(RooWorkspace* sig, RooWorkspace* bkg, const char* fileBaseName, const char* fileBkgName);
void SetParamNames(RooWorkspace*);
void SetConstantParams(const RooArgSet* params);
//
// container for the fit results
RooFitResult* fitresult[2]; //NCAT=2
//
const int minfit =100, maxfit=180;
RooArgSet* defineVariables()
{
// define variables of the input ntuple
RooRealVar* mtot = new RooRealVar("mtot","M(#gamma#gamma jj)",200,1200,"GeV");
RooRealVar* mjj = new RooRealVar("mjj","M(jj)",90,190,"GeV");
RooRealVar* mgg = new RooRealVar("mgg","M(#gamma#gamma)",80,180,"GeV");
RooRealVar* evWeight = new RooRealVar("evWeight","HqT x PUwei",0,1000000000,"");
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, *mjj);
// RooArgSet* ntplVars = new RooArgSet(*mtot, *mgg, *cut_based_ct, *evWeight);
ntplVars->add(*mtot);
ntplVars->add(*mjj);
ntplVars->add(*mgg);
ntplVars->add(*cut_based_ct);
ntplVars->add(*evWeight);
return ntplVars;
}
////////////////////////////////////////////////////////////////////////
void runfits(const Float_t mass=120, Int_t mode=1)
{
style();
TString fileBaseName(TString::Format("hgg.mH500_8TeV", mass));
TString fileBkgName(TString::Format("hgg.mH500.inputbkg_8TeV", mass));
RooFitResult* fitresults;
// Add the signal and background models to the workspace.
// the minitree to be addeed
TString ssignal = "MiniTrees/OlivierOc13/v15_regkin_mgg_0_massCutVersion0/02013-10-30-Radion_m500_8TeV_nm_m500.root";
TString ddata = "MiniTrees/OlivierOc13/v15_regkin_mgg_0_massCutVersion0/02013-10-30-Data_m500.root";
//TString ddata = "MiniTrees/OlivierAug13/v02_regkin_mgg_0/Data_regression-m300_minimal.root";
//
cout<<"Signal: "<< ssignal<<endl;
cout<<"Data: "<< ddata<<endl;
// declare the worspace outside the function to construct the datacard
// for signal
RooWorkspace *wall = new RooWorkspace("w_all","w_all");
TString card_nameS("models_mgg_sig.rs"); // put the model parameters here!
HLFactory hlfS("w_allS", card_nameS, false);
RooWorkspace* wall = hlfS.GetWs(); // Get the RooWorkspace containing the models and variables
AddSigData(wall,mass,ssignal,fileBaseName); //OK!
// for BKG
RooWorkspace *wAll = new RooWorkspace("w_all","w_all");
TString card_nameB("models_mgg_bkg.rs"); // put the model parameters here!
HLFactory hlfB("w_allB", card_nameB, false);
RooWorkspace* wAll = hlfB.GetWs(); // Get the RooWorkspace containing the models and variables
bool dobands=false;
AddBkgData(wAll,ddata,fileBkgName,dobands);
//
MakeDataCard(wall,wAll,fileBaseName,fileBkgName);
MakeDataCardoneCat(wall,wAll,fileBaseName,fileBkgName);
cout<< "here"<<endl;
return;
} // close runfits
////////////////////////////////////////////////////////////////////////////////
// we add the data to the workspace in categories
void AddSigData(RooWorkspace* wall, Float_t mass, TString signalfile, const char* fileBasename) {
// file input
TFile sigFile(signalfile);
TTree* sigTree = (TTree*) sigFile.Get("TCVARS");
//Float_t Lum = 19785.0; // pb-1
//RooRealVar lumi("lumi","lumi",Lum);
//wall->import(lumi);
//
RooArgSet* ntplVars = defineVariables();
//
const Int_t ncat = 2;
Float_t MASS(mass);
// common preselection cut
TString mainCut("1");
//--------------------------------------------
// re-scale signal to the ratio r to be in fb
// no cross section added on weights
//--------------------------------------------
// one channel with default weights
/* RooDataSet sigScaled1(
"sigScaled1",
"dataset",
sigTree, // all variables of RooArgList
*ntplVars,
mainCut);
RooRealVar *k = new RooRealVar("k", "k", 0.0019706 ,"GeV"); // 19.706/10000
RooFormulaVar *nw = new RooFormulaVar("nw", "nw", "@0*@1", RooArgSet(*evWeight, *k));
sigScaled1.addColumn(*nw);
//sigScaled1.setWeightVar("nw");
//sigScaled1->Print();
RooArgSet* ntplVars1 = sigScaled1.get();
//ntplVars->add(nw);
*/
RooRealVar *evWeight = (RooRealVar*) (*ntplVars)["evWeight"] ;
RooDataSet sigScaled(
"sigScaled",
"dataset",
sigTree,
*ntplVars,
mainCut,
"evWeight");
RooDataSet* sigToFit[ncat];
//----------------------------------------------
// cuts
TString cut0 = "&& 1>0";// "&& mtot > 450 && mtot < 550 "; //"&& 1>0";//
TString cut1 ="&& 1>0";// "&& mtot > 450 && mtot < 550 "; // "&& 1>0";//
//
TString cutj0 ="&& 1>0";// "&& mjj > 90 && mjj < 170 "; //"&& 1>0";//
TString cutj1 ="&& 1>0";// "&& mjj > 100 && mjj < 160 "; // "&& 1>0";//
//
// we take only mtot to fit to the workspace, we include the cuts
sigToFit[0] = (RooDataSet*) sigScaled.reduce(
*wall->var("mgg"),
mainCut+TString::Format(" && cut_based_ct==%d ",0)+cut0+cutj0);
wall->import(*sigToFit[0],Rename(TString::Format("Sig_cat%d",0)));
//
sigToFit[1] = (RooDataSet*) sigScaled.reduce(
*wall->var("mgg"),
mainCut+TString::Format(" && cut_based_ct==%d ",1)+cut1+cutj1);
wall->import(*sigToFit[1],Rename(TString::Format("Sig_cat%d",1)));
//////////////////////////////////////////////////////////////////////
// here we print the number of entries on the different categories
cout << "========= the number of entries on the different categories ==========" << endl;
cout << "---- one channel: " << sigToFit[0]->sumEntries() +sigToFit[1]->sumEntries() << 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");
// we end adding signal function
//////////////////////////////////////////////////////////////////////////
// we do the model fitting on the same function and save to anew WS
Float_t MASS(mass);
// fit range
Float_t minMassFit(minfit),maxMassFit(maxfit);
//
RooDataSet* sigFit[ncat];
RooAbsPdf* mggSig[ncat];
for (int c = 0; c < ncat; ++c) {
// import sig from workspace
sigFit[c] = (RooDataSet*) wall->data(TString::Format("Sig_cat%d",c));
mggSig[c] = (RooAbsPdf*) wall->pdf(TString::Format("mggSig_cat%d",c));
cout << "OK up to now..." <<MASS<< endl;
((RooRealVar*) wall->var(TString::Format("mgg_sig_m0_cat%d",c)))->setVal(MASS);
// Fit model as M(x|y) to D(x,y)
mggSig[c]->fitTo(*sigFit[c],Range(minMassFit,maxMassFit),SumW2Error(kTRUE));
cout << "OK up to now again ..." <<MASS<< endl;
// IMPORTANT: fix all pdf parameters to constant
wall->defineSet(TString::Format("SigPdfParam_cat%d",c),
RooArgSet(
*wall->var(TString::Format("mgg_sig_m0_cat%d",c)),
*wall->var(TString::Format("mgg_sig_alpha_cat%d",c)),
*wall->var(TString::Format("mgg_sig_n_cat%d",c)),
*wall->var(TString::Format("mgg_sig_gsigma_cat%d",c)),
*wall->var(TString::Format("mgg_sig_sigma_cat%d",c)),
*wall->var(TString::Format("mgg_sig_frac_cat%d",c)))
);
SetConstantParams(wall->set(TString::Format("SigPdfParam_cat%d",c)));
} // close for ncat
// (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("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)
);
*/
//
// save to a file
TString filename(TString(fileBasename)+".inputsig.root");
wall->writeToFile(filename);
cout << "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!" << endl;
cout << "Write signal workspace in: " << filename << " file" << endl;
//wall->Print();
//return;
//
// we finish fitting,
//////////////////////////////////////////////////////////////////////
// we do plots
std::vector<TString> catdesc;
catdesc.push_back("2 btag");
catdesc.push_back("1 btag");
// retrieve data sets from the workspace
// blinded dataset
RooRealVar* mgg = wall->var("mgg");
mgg->setUnit("GeV");
Int_t nBinsMass(93); // just need to plot
RooPlot* plotmtotAll = mgg->frame(Range(minMassFit,maxMassFit),Bins(nBinsMass));
//signalAll->plotOn(plotmtotAll);
gStyle->SetOptTitle(0);
//
TLatex *text = new TLatex();
text->SetNDC();
text->SetTextSize(0.04);
RooPlot* plotmtot[ncat];
for (int c = 0; c < ncat; ++c) {
plotmtot[c] = mgg->frame(Range(minMassFit,maxMassFit),Bins(nBinsMass));
sigFit[c] ->plotOn(plotmtot[c]);
mggSig[c] ->plotOn(plotmtot[c]);
mggSig[c] ->plotOn(
plotmtot[c],
Components(TString::Format("GaussSig_cat%d",c)),
LineStyle(kDashed),LineColor(kGreen));
mggSig[c] ->plotOn(
plotmtot[c],
Components(TString::Format("CBSig_cat%d",c)),
LineStyle(kDashed),LineColor(kRed));
mggSig[c] ->paramOn(plotmtot[c]);
sigFit[c] ->plotOn(plotmtot[c]);
TH1F *hist = new TH1F("hist", "hist", 400, minMassFit, maxMassFit);
plotmtot[c]->SetTitle("CMS preliminary 19.62/fb ");
plotmtot[c]->SetMinimum(0.0);
plotmtot[c]->SetMaximum(1.40*plotmtot[c]->GetMaximum());
plotmtot[c]->GetXaxis()->SetTitle("M_{#gamma#gamma} (GeV)");
TCanvas* ctmp = new TCanvas("ctmp","Background Categories",0,0,501,501);
plotmtot[c]->Draw();
plotmtot[c]->Draw("SAME");
TLegend *legmc = new TLegend(0.52,0.65,0.95,0.9);
legmc->AddEntry(plotmtot[c]->getObject(0),"Simulation","LPE");
legmc->AddEntry(plotmtot[c]->getObject(1),"Parametric Model","L");
legmc->AddEntry(plotmtot[c]->getObject(2),"Crystal Ball component","L");
legmc->AddEntry(plotmtot[c]->getObject(3),"Gaussian Outliers","L");
legmc->SetHeader(" ");
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
TLatex *lat = new TLatex(
minMassFit+1.5,0.85*plotmtot[c]->GetMaximum(),
" WP4 500 GeV");
lat->Draw();
TLatex *lat2 = new TLatex(
minMassFit+1.5,0.75*plotmtot[c]->GetMaximum(),catdesc.at(c));
lat2->Draw();
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.C",c));
} // close categories
return;
} // end with signal
////////////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////////////
// we add the data to the workspace in categories
void AddBkgData(RooWorkspace* wAll, TString datafile, const char* fileBaseName, bool dobands) {
std::vector<TString> catdesc;
catdesc.push_back("2 btag");
catdesc.push_back("1 btag");
const Int_t ncat = 2;
// common preselection cut
TString mainCut("1");
// Variables
RooArgSet* ntplVars = defineVariables();
TFile dataFile(datafile); // haaaaa
TTree* dataTree = (TTree*) dataFile.Get("TCVARS");
RooDataSet data("data","dataset",dataTree,*ntplVars,"");
cout<<" data events "<< data.sumEntries()<< endl;
RooDataSet* dataToFit[ncat];
RooDataSet* dataToPlot[ncat];
RooRealVar* mgg = wAll->var("mgg");
// cuts
TString cut0 ="&& 1>0";// "&& mtot > 450 && mtot < 550 "; //"&& 1>0";//
TString cut1 ="&& 1>0";// "&& mtot > 450 && mtot < 550 "; // "&& 1>0";//
//
TString cutj0 ="&& 1>0";// "&& mjj > 90 && mjj < 170 "; //"&& 1>0";//
TString cutj1 ="&& 1>0";// "&& mjj > 100 && mjj < 160 "; // "&& 1>0";//
//
// apply the cuts
dataToFit[0] = (RooDataSet*) data.reduce(
*wAll->var("mgg"),
TString::Format(" cut_based_ct==%d",0)+cut0+cutj0);
dataToPlot[0] = (RooDataSet*) data.reduce(
*wAll->var("mgg"),
TString::Format(" cut_based_ct==%d",0)+cut0+cutj0
+TString::Format(" && (mgg < 120 || mgg > 130)") // blind
);
//
dataToFit[1] = (RooDataSet*) data.reduce(
*wAll->var("mgg"),
TString::Format(" cut_based_ct==%d",1)+cut1+cutj1);
dataToPlot[1] = (RooDataSet*) data.reduce(
*wAll->var("mgg"),
TString::Format(" cut_based_ct==%d",1)+cut1+cutj1
+TString::Format(" && (mgg < 120 || mgg > 130)") // blind
);
//
//char nameToSave[300];
for (int c = 0; c < ncat; ++c){
//
// convert it into a roodatahist - chiara: come capisco i bin??
//RooArgSet setqui2(*mtot);
//sprintf(nameToSave,"data_obs_cat%d",c);
//RooDataHist dataBinned(nameToSave, nameToSave, setqui2, data);
//wAll->import(dataBinned);
// unbinned dataset only
// combine understand data as data_obs
wAll->import(*dataToFit[c],Rename(TString::Format("data_obs_cat%d",c)));
//wAll->import(*dataToPlot[c],Rename(TString::Format("Dataplot_cat%d",c)));
}
for (int c = 0; c < ncat; ++c) {
Float_t nExpEvt = dataToFit[c]->sumEntries();
cout << TString::Format("nEvt exp. cat%d : ",c) << nExpEvt
<< TString::Format(" eff x Acc cat%d : ",c)
<< "%"
<< endl;
}
cout << "======================================================================" << endl;
data.Print("v");
for (int c = 0; c < ncat; ++c) {
std::cout << " " << wAll->data(TString::Format("data_obs_cat%d",c))->sumEntries();
}
// we adeed signal
///////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////
// we do the model fitting on the same function
//
// fit range
Float_t minMassFit(minfit),maxMassFit(maxfit);
RooPlot* plotmtotBkg[ncat];
// dumb dataset
RooDataSet* datafake[ncat];
// declare pdf - same for both categories
//
Int_t nBinsMass(80);
for (int c = 0; c < ncat; ++c) {
// the parameters are set positive, because they are squared!!!!!!!!!!!!!!
RooFormulaVar *p1mod = new RooFormulaVar(
TString::Format("p1mod_cat%d",c),
"","@0*@0",
*wAll->var(TString::Format("mgg_bkg_8TeV_slope1_cat%d",c)));
RooFormulaVar *p2mod = new RooFormulaVar(
TString::Format("p2mod_cat%d",c)
,"","@0*@0",
*wAll->var(TString::Format("mgg_bkg_8TeV_slope2_cat%d",c)));
RooFormulaVar *p3mod = new RooFormulaVar(
TString::Format("p3mod_cat%d",c),
"","@0*@0",
*wAll->var(TString::Format("mgg_bkg_8TeV_slope3_cat%d",c)));
////////////////////////////////////////////////////////////////////
RooAbsPdf* mggBkgTmp0 = 0; // declare a empty pdf
// adding pdf's, using the variables
mggBkgTmp0 = new RooBernstein( // fill the pdf with the floating parameters
TString::Format("mggBkgTmp0_cat%d",c),
"", *mgg,
RooArgList(RooConst(1.0),*p1mod, *p2mod, *p3mod));
cout<<"here 6 "<< c<<endl;
// the normalization variable
// wAll->factory(TString::Format("mtot_bkg_8TeV_norm_cat%d[1.0,0.0,100000]",c));
// we copy the pdf to normalize
wAll->factory(TString::Format("mgg_bkg_8TeV_norm_cat%d[1.0,0.0,100000]",c));
RooExtendPdf mggBkgTmp(
TString::Format("mggBkg_cat%d",c),
"",*mggBkgTmp0,
*wAll->var(TString::Format("mgg_bkg_8TeV_norm_cat%d",c)));
//
fitresult[c] = mggBkgTmp.fitTo( // fit with normalized pdf,and return values
*dataToFit[c], // bkg
Strategy(1), // MINUIT strategy
Minos(kFALSE), // interpretation on the errors, nonlinearities
Range(minMassFit,maxMassFit),
SumW2Error(kTRUE),
Save(kTRUE));
wAll->import(mggBkgTmp); //store the normalized pdf on wp
//
// we plot
TCanvas* ctmp = new TCanvas("ctmp","mgg Background Categories",0,0,501,501);
plotmtotBkg[c] = mgg->frame(nBinsMass);
//dataToPlot[c] = (RooDataSet*) wAll->data(TString::Format("Data_cat%d",c));
dataToPlot[c]->plotOn(plotmtotBkg[c],LineColor(kWhite),MarkerColor(kWhite));
mggBkgTmp.plotOn(
plotmtotBkg[c],
LineColor(kBlue),
Range("fitrange"),NormRange("fitrange"));
dataToPlot[c]->plotOn(plotmtotBkg[c]); // blind
plotmtotBkg[c]->SetTitle("CMS preliminary 19.62/fb");
plotmtotBkg[c]->SetMinimum(0.0);
plotmtotBkg[c]->SetMaximum(30.0*plotmtotBkg[c]->GetMaximum());
plotmtotBkg[c]->GetXaxis()->SetTitle("M_{#gamma#gamma} (GeV)");
plotmtotBkg[c]->Draw();
cout << "!!!!!!!!!!!!!!!!!" << endl;
if (dobands) {
RooAbsPdf *cpdf; cpdf = mtotBkgTmp0;
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);
mgg->setRange("errRange",lowedge,upedge);
RooAbsPdf *epdf = 0;
epdf = new RooExtendPdf("epdf","",*cpdf,*nlim,"errRange");
RooAbsReal *nll = epdf->createNLL(*(dataToFit[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);
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
// eventually if cl = 0.95 this is the usual 1.92!
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;
}
mgg->setRange("errRange",minMassFit,maxMassFit);
twosigma->SetLineColor(kGreen);
twosigma->SetFillColor(kGreen);
twosigma->SetMarkerColor(kGreen);
twosigma->Draw("L3 SAME");
onesigma->SetLineColor(kYellow);
onesigma->SetFillColor(kYellow);
onesigma->SetMarkerColor(kYellow);
onesigma->Draw("L3 SAME");
plotmtotBkg[c]->Draw("SAME");
} else {
cout << "!!!!!!!!!!!!!!!!!" << endl; // now we fit the gaussian on signal
plotmtotBkg[c]->Draw("SAME");
}// close dobands
plotmtotBkg[c]->GetYaxis()->SetRangeUser(0.0000001,20);
//plotmtotBkg[c]->Draw("AC");
ctmp->SetLogy(0);
ctmp->SetGrid(1);
cout << "!!!!!!!!!!!!!!!!!" << endl;
TLegend *legmc = new TLegend(0.52,0.65,0.92,0.9);
legmc->AddEntry(plotmtotBkg[c]->getObject(2),"19.706 fb-1 ",""); //"LPE" blind
legmc->AddEntry(plotmtotBkg[c]->getObject(1),"3* Berntein fit","L");
if(dobands)legmc->AddEntry(twosigma,"two sigma ","F"); // not...
if(dobands)legmc->AddEntry(onesigma,"one sigma","F");
legmc->SetHeader("WP4 500 GeV");
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
TLatex *lat2 = new TLatex(minMassFit+1.5,0.75*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));
cout<<"here 3 "<< c<<endl;
} // close to each category
/* // (1) import everything functions / depends on quantity of parameters... change it if change the function!
for (int c = 0; c < ncat; ++c) {
wAll->factory(
TString::Format("CMS_hgg_bkg_8TeV_cat%d_norm[%g,0.0,1000.0]",
c, wAll->var(TString::Format("mtot_bkg_8TeV_norm_cat%d",c))->getVal())); // what is this 1* slope?
wAll->factory(
TString::Format("CMS_hgg_bkg_8TeV_slope1_cat%d[%g,0.0,300]",
c, wAll->var(TString::Format("mtot_bkg_8TeV_slope1_cat%d",c))->getVal()));
wAll->factory(
TString::Format("CMS_hgg_bkg_8TeV_slope2_cat%d[%g,0.0,100]",
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){
wAll->factory(
TString::Format("EDIT::CMS_hgg_bkg_8TeV_cat%d(mtotBkg_cat%d,",c,c) +
TString::Format(" mtot_bkg_8TeV_norm_cat%d=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)+
TString::Format(" mtot_bkg_8TeV_slope2_cat%d=CMS_hgg_bkg_8TeV_slope2_cat%d)", c,c)
);
} // close for cat
*/
// import also observed
//
TString filename(TString(fileBaseName)+".root");
wAll->writeToFile(filename);
cout << "Write background workspace in: " << filename << " file" << endl;
// import data to workspace
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;
// we finish fitting,
///////////////////////////////////////////////////////////////////
cout<<"here out loop"<<endl;
return;
} // close add data ..
//////////////////////////////////////////////////
void MakeDataCard(RooWorkspace* wall, RooWorkspace* wAll, const char* fileBaseName, const char* fileBkgName) {
//TString cardDir = "datacards/";
cout<< " signal " <<endl;
wall->Print();
cout<< " BKG " <<endl;
wAll->Print();
//
const Int_t ncat = 2;
RooDataSet* Data[ncat];
RooDataSet* sigToFit[ncat];
cout << "======== Start datacard maker =====================" << endl;
for (int c = 0; c < ncat; ++c) {
Data[c] = (RooDataSet*) wAll->data(TString::Format("data_obs_cat%d",c));
sigToFit[c] = (RooDataSet*) wall->data(TString::Format("Sig_cat%d",c));
}
// RooRealVar* lumi = wAll->var("lumi");
cout << "======== Expected signal Events Number =====================" << endl;
//Float_t siglikeErr[2];
for (int c = 0; c < 2; ++c) {
cout << TString::Format("#Events Signal cat%d: ",c) << sigToFit[c]->sumEntries() << endl;
//siglikeErr[c]=0.6*sigToFit[c]->sumEntries();
}
cout << "======== Expected Events Number =====================" << endl;
for (int c = 0; c < ncat; ++c) {
cout << TString::Format("#Events data cat%d: ",c)<< Data[c]->sumEntries() << endl;
}
cout << "====================================================" << endl;
TString filename(TString(fileBaseName)+".txt");
ofstream outFile(filename);
// name of files
//outFile << "#CMS-HGG DataCard for Unbinned Limit Setting, " << lumi->getVal() << " pb-1 " << endl;
outFile << "#Run: combine -M Asymptotic hgg.mH500.0_8TeV.txt" << 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 << "# BKG" << endl;
outFile << "shapes data_obs cat0 " << TString(fileBkgName)+".root" << " w_allB_ws:data_obs_cat0" << endl;
outFile << "shapes data_obs cat1 "<< TString(fileBkgName)+".root" << " w_allB_ws:data_obs_cat1" << endl;
outFile << "shapes mtotBkg cat0 " << TString(fileBkgName)+".root" << " w_allB_ws:mggBkg_cat0" << endl;
outFile << "shapes mtotBkg cat1 "<< TString(fileBkgName)+".root" << " w_allB_ws:mggBkg_cat1" << endl;
outFile << "# signal" << endl;
outFile << "shapes mtotSig cat0 " << TString(fileBaseName)+".inputsig.root" << " w_allS_ws:mggSig_cat0" << endl;
outFile << "shapes mtotSig cat1 " << TString(fileBaseName)+".inputsig.root" << " w_allS_ws:mggSig_cat1" << endl;
outFile << "---------------" << endl;
/////////////////////////////////////
// begin declaration
outFile << "bin cat0 cat1 " << endl;
outFile << "observation "
<< Data[0]->sumEntries() << " "
<< Data[1]->sumEntries() << " "
<< 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() << " " << Data[0]->sumEntries()
<< " " << sigToFit[1]->sumEntries() << " " << Data[1]->sumEntries()
<< " " << endl;
outFile << "--------------------------------" << endl;
outFile << "lumi_8TeV lnN "
<< "1.022 - "
<< "1.022 - " << endl;
outFile << "############## jet" << endl;
outFile << "Mjj_acceptance lnN "
<< "1.015 - "
<< "1.015 - "
<<"# JER and JES " << endl; // change latter
outFile << "btag_eff lnN "
<< "1.06 - "
<< "1.03 - "
<<"# b tag efficiency uncertainty" << endl;
outFile << "############## photon " << endl;
outFile << "CMS_hgg_eff_g lnN "
<< "1.010 - "
<< "1.010 - "
<< "# photon selection accep." << endl;
outFile << "DiphoTrigger lnN "
<< "1.01 - "
<< "1.01 - "
<< "# Trigger efficiency" << endl;
outFile << "############## for mtot fit" << endl;
outFile << "maajj_acceptance lnN "
<< "1.10 - "
<< "1.10 - "
<< "# photon energy resolution" << endl;
outFile << "# Parametric shape uncertainties, entered by hand. they act on both higgs/signal " << endl;
outFile << "CMS_hgg_sig_m0_absShift param 1 0.006 # displacement of the dipho mean" << endl;
outFile << "CMS_hgg_sig_sigmaScale param 1 0.30 # optimistic estimative of resolution uncertainty " << endl;
outFile << "############## for mtot fit - slopes" << endl;
outFile << "mgg_bkg_8TeV_norm_cat0 flatParam # Normalization uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_norm_cat1 flatParam # Normalization uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_slope1_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_slope1_cat1 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_slope2_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_slope2_cat1 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_slope2_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile << "mgg_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
//////////////////////////////////////////////////
void MakeDataCardoneCat(RooWorkspace* wall, RooWorkspace* wAll, const char* fileBaseName, const char* fileBkgName) {
//TString cardDir = "datacards/";
cout<< " signal " <<endl;
wall->Print();
cout<< " BKG " <<endl;
wAll->Print();
//
const Int_t ncat = 2;
RooDataSet* Data[ncat];
RooDataSet* sigToFit[ncat];
cout << "======== Start datacard maker =====================" << endl;
for (int c = 0; c < ncat; ++c) {
Data[c] = (RooDataSet*) wAll->data(TString::Format("data_obs_cat%d",c));
sigToFit[c] = (RooDataSet*) wall->data(TString::Format("Sig_cat%d",c));
}
// RooRealVar* lumi = wAll->var("lumi");
cout << "======== Expected signal Events Number =====================" << endl;
//Float_t siglikeErr[2];
for (int c = 0; c < 2; ++c) {
cout << TString::Format("#Events Signal cat%d: ",c) << sigToFit[c]->sumEntries() << endl;
//siglikeErr[c]=0.6*sigToFit[c]->sumEntries();
}
cout << "======== Expected Events Number =====================" << endl;
for (int c = 0; c < ncat; ++c) {
cout << TString::Format("#Events data cat%d: ",c)<< Data[c]->sumEntries() << endl;
}
cout << "====================================================" << endl;
TString filename(TString(fileBaseName)+"_onecat.txt");
ofstream outFile(filename);
// name of files
//outFile << "#CMS-HGG DataCard for Unbinned Limit Setting, " << lumi->getVal() << " pb-1 " << endl;
outFile << "#Run: combine -M Asymptotic hgg.mH500.0_8TeV.txt" << 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 << "# BKG" << endl;
outFile << "shapes data_obs cat0 " << TString(fileBkgName)+".root" << " w_allB_ws:data_obs_cat0" << endl;
//outFile << "shapes data_obs cat1 "<< TString(fileBkgName)+".root" << " w_allB_ws:data_obs_cat1" << endl;
outFile << "shapes mtotBkg cat0 " << TString(fileBkgName)+".root" << " w_allB_ws:mggBkg_cat0" << endl;
//outFile << "shapes mtotBkg cat1 "<< TString(fileBkgName)+".root" << " w_allB_ws:mggBkg_cat1" << endl;
outFile << "# signal" << endl;
outFile << "shapes mtotSig cat0 " << TString(fileBaseName)+".inputsig.root" << " w_allS_ws:mggSig_cat0" << endl;
//outFile << "shapes mtotSig cat1 " << TString(fileBaseName)+".inputsig.root" << " w_allS_ws:mggSig_cat1" << endl;
outFile << "---------------" << endl;
/////////////////////////////////////
// begin declaration
outFile << "bin cat0 " << endl;
outFile << "observation "
<< Data[0]->sumEntries() << " "
//<< Data[1]->sumEntries() << " "
<< endl;
outFile << "------------------------------" << endl;
outFile << "bin cat0 cat0 " << endl;
outFile << "process mtotSig mtotBkg " << endl;
outFile << "process 0 1 " << endl;
outFile << "rate "
<< " " << sigToFit[0]->sumEntries() << " " << Data[0]->sumEntries()
//<< " " << sigToFit[1]->sumEntries() << " " << Data[1]->sumEntries()
<< " " << endl;
outFile << "--------------------------------" << endl;
outFile << "lumi_8TeV lnN "
<< "1.022 - "
//<< "1.022 - "
<< endl;
outFile << "############## jet" << endl;
outFile << "Mjj_acceptance lnN "
<< "1.015 - "
//<< "1.015 - "
<<"# JER and JES " << endl; // change latter
outFile << "btag_eff lnN "
<< "1.06 - "
//<< "1.03 - "
<<"# b tag efficiency uncertainty" << endl;
outFile << "############## photon " << endl;
outFile << "CMS_hgg_eff_g lnN "
<< "1.010 - "
//<< "1.010 - "
<< "# photon selection accep." << endl;
outFile << "DiphoTrigger lnN "
<< "1.01 - "
//<< "1.01 - "
<< "# Trigger efficiency" << endl;
outFile << "############## for mtot fit" << endl;
outFile << "maajj_acceptance lnN "
<< "1.10 - "
//<< "1.10 - "
<< "# photon energy resolution" << endl;
outFile << "# Parametric shape uncertainties, entered by hand. they act on both higgs/signal " << endl;
outFile << "CMS_hgg_sig_m0_absShift param 1 0.006 # displacement of the dipho mean" << endl;
outFile << "CMS_hgg_sig_sigmaScale param 1 0.30 # optimistic estimative of resolution uncertainty " << endl;
outFile << "############## for mtot fit - slopes" << endl;
outFile << "mgg_bkg_8TeV_norm_cat0 flatParam # Normalization uncertainty on background slope" << endl;
//outFile << "mgg_bkg_8TeV_norm_cat1 flatParam # Normalization uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_slope1_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
//outFile << "mgg_bkg_8TeV_slope1_cat1 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_slope2_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
//outFile << "mgg_bkg_8TeV_slope2_cat1 flatParam # Mean and absolute uncertainty on background slope" << endl;
outFile << "mgg_bkg_8TeV_slope2_cat0 flatParam # Mean and absolute uncertainty on background slope" << endl;
//outFile << "mgg_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
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(); }
}
*/
cout << endl; cout << "Entering SetConstantParams" << endl;
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 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(0.13);
defaultStyle->SetPadRightMargin(0.02);
/////// 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(1.25,"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->SetTitleYSize(Float_t size = 0.02);
defaultStyle->SetTitleXOffset(0.9);
defaultStyle->SetTitleYOffset(1.05);
// defaultStyle->SetTitleOffset(1.1, "Y"); // Another way to set the Offset
// 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); // To get tick marks on the opposite side of the frame
defaultStyle->SetPadTickY(1);
defaultStyle->cd();
return;
}