pair<double,double> bkgEvPerGeV(RooWorkspace *work, int m_hyp, int cat, int spin=false){
RooRealVar *mass = (RooRealVar*)work->var("CMS_hgg_mass");
if (spin) mass = (RooRealVar*)work->var("mass");
mass->setRange(100,180);
RooAbsPdf *pdf = (RooAbsPdf*)work->pdf(Form("pdf_data_pol_model_8TeV_cat%d",cat));
RooAbsData *data = (RooDataSet*)work->data(Form("data_mass_cat%d",cat));
RooPlot *tempFrame = mass->frame();
data->plotOn(tempFrame,Binning(80));
pdf->plotOn(tempFrame);
RooCurve *curve = (RooCurve*)tempFrame->getObject(tempFrame->numItems()-1);
double nombkg = curve->Eval(double(m_hyp));
RooRealVar *nlim = new RooRealVar(Form("nlim%d",cat),"",0.,0.,1.e5);
//double lowedge = tempFrame->GetXaxis()->GetBinLowEdge(FindBin(double(m_hyp)));
//double upedge = tempFrame->GetXaxis()->GetBinUpEdge(FindBin(double(m_hyp)));
//double center = tempFrame->GetXaxis()->GetBinUpCenter(FindBin(double(m_hyp)));
nlim->setVal(nombkg);
mass->setRange("errRange",m_hyp-0.5,m_hyp+0.5);
RooAbsPdf *epdf = 0;
epdf = new RooExtendPdf("epdf","",*pdf,*nlim,"errRange");
RooAbsReal *nll = epdf->createNLL(*data,Extended(),NumCPU(4));
RooMinimizer minim(*nll);
minim.setStrategy(0);
minim.setPrintLevel(-1);
minim.migrad();
minim.minos(*nlim);
double error = (nlim->getErrorLo(),nlim->getErrorHi())/2.;
data->Print();
return pair<double,double>(nombkg,error);
}
void THSEventsPDF::adjustBinning(Int_t* offset1) const
{
RooRealVar* xvar = fx_off ;
if (!dynamic_cast<RooRealVar*>(xvar)) {
coutE(InputArguments) << "RooDataHist::adjustBinning(" << GetName() << ") ERROR: dimension " << xvar->GetName() << " must be real" << endl ;
assert(0) ;
}
Double_t xlo = xvar->getMin() ;
Double_t xhi = xvar->getMax() ;
//adjust bin range limits with new scale parameter
//cout<<scale<<" "<<fMean<<" "<<xlo<<" "<<xhi<<endl;
xlo=(xlo-fMean)/scale+fMean;
xhi=(xhi-fMean)/scale+fMean;
if(xvar->getBinning().lowBound()==xlo&&xvar->getBinning().highBound()==xhi) return;
xvar->setRange(xlo,xhi) ;
// Int_t xmin(0) ;
// cout<<"THSEventsPDF::adjustBinning( "<<xlo <<" "<<xhi<<endl;
//now adjust fitting range to bin limits??Possibly not
if (fRHist->GetXaxis()->GetXbins()->GetArray()) {
RooBinning xbins(fRHist->GetNbinsX(),fRHist->GetXaxis()->GetXbins()->GetArray()) ;
Double_t tolerance = 1e-6*xbins.averageBinWidth() ;
// Adjust xlo/xhi to nearest boundary
Double_t xloAdj = xbins.binLow(xbins.binNumber(xlo+tolerance)) ;
Double_t xhiAdj = xbins.binHigh(xbins.binNumber(xhi-tolerance)) ;
xbins.setRange(xloAdj,xhiAdj) ;
xvar->setBinning(xbins) ;
if (fabs(xloAdj-xlo)>tolerance||fabs(xhiAdj-xhi)<tolerance) {
coutI(DataHandling) << "RooDataHist::adjustBinning(" << GetName() << "): fit range of variable " << xvar->GetName() << " expanded to nearest bin boundaries: ["
<< xlo << "," << xhi << "] --> [" << xloAdj << "," << xhiAdj << "]" << endl ;
}
} else {
RooBinning xbins(fRHist->GetXaxis()->GetXmin(),fRHist->GetXaxis()->GetXmax()) ;
xbins.addUniform(fRHist->GetNbinsX(),fRHist->GetXaxis()->GetXmin(),fRHist->GetXaxis()->GetXmax()) ;
Double_t tolerance = 1e-6*xbins.averageBinWidth() ;
// Adjust xlo/xhi to nearest boundary
Double_t xloAdj = xbins.binLow(xbins.binNumber(xlo+tolerance)) ;
Double_t xhiAdj = xbins.binHigh(xbins.binNumber(xhi-tolerance)) ;
xbins.setRange(xloAdj,xhiAdj) ;
xvar->setRange(xloAdj,xhiAdj) ;
//xvar->setRange(xlo,xhi) ;
}
return;
}
//
// set value and range for a variable in the workspace
//
void setValRange (RooWorkspace* workspace, const char* name, double val, double vmin, double vmax)
{
RooRealVar* var = workspace->var(name);
if ( var ) {
if ( vmax>vmin ) var->setRange(vmin,vmax);
var->setVal(val);
}
}
MakeBiasStudy::MakeBiasStudy() {
int Nmodels = 8;
//RooRealVar* mass = ws->var("mass");
RooRealVar *mass = new RooRealVar("mass","mass", 100,180);
RooRealVar *nBkgTruth = new RooRealVar("TruthNBkg","", 0,1e9);
// RooAbsData* realData = ws->data("Data_Combined")->reduce( Form("evtcat==evtcat::%s",cat.Data()) );
double Bias[Nmodels][Nmodels];
double BiasE[Nmodels][Nmodels];
MakeAICFits MakeAIC_Fits;
for(int truthType = 0; truthType < Nmodels; truthType++){
RooAbsPdf *truthPdf = MakeAIC_Fits.getBackgroundPdf(truthType,mass);
RooExtendPdf *truthExtendedPdf = new RooExtendPdf("truthExtendedPdf","",*truthPdf,*nBkgTruth);
//truthExtendedPdf.fitTo(*realData,RooFit::Strategy(0),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE));
//truthExtendedPdf.fitTo(*realData,RooFit::Strategy(2),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE));
double BiasWindow = 2.00;
mass->setRange("biasRegion", mh-BiasWindow, mh+BiasWindow);
double TruthFrac = truthExtendedPdf->createIntegral(mass,RooFit::Range("biasRegion"),RooFit::NormSet(*mass))->getVal();
double NTruth = TruthFrac * nBkgTruth->getVal();
double NTruthE = TruthFrac * nBkgTruth->getError();
RooDataSet* truthbkg = truthPdf->generate(RooArgSet(*mass),nBkgTruth);
for(int modelType = 0; modelType < Nmodels; modelType++){
RooAbsPdf* ModelShape = MakeAIC_Fits.getBackgroundPdf(modelType,mass);
RooRealVar *nBkgFit = new RooRealVar("FitNBkg", "", 0, 1e9);
RooExtendPdf ModelExtendedPdf = new RooExtendPdf("ModelExtendedPdf", "",*ModelShape, *nBkgFit);
ModelExtendedPdf.fitTo(truthbkg, RooFit::Strategy(0),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE));
ModelExtendedPdf.fitTo(truthbkg, RooFit::Strategy(2),RooFit::NumCPU(NUM_CPU),RooFit::Minos(kFALSE),RooFit::Extended(kTRUE));
double FitFrac = ModelExtendedPdf.createIntegral(mass,RooFit::Range("biasRegion"),RooFit::NormSet(mass))->getVal();
double NFit = FitFrac * nBkgFit->getVal();
double NFitE = FitFrac * nBkgFit->getError();
Bias[truthType][modelType] = fabs(NFit - NTruth);
BiasE[truthType][modelType] = fabs(NFitE - NTruthE);
}
}
for(int i = 0; i < Nmodels; i++) {
std::cout << "===== Truth Model : " << MakeBiasStudy::Category(i) << " ===== " << std::endl;
for (int j = 0; j < Nmodels; j++) {
std::cout << "Fit Model: " << MakeBiasStudy::Category(j) << " , Bias = " << Bias[i][j] << " +/- " << BiasE[i][j] << std::endl;
}
}
}
void FitterUtils::initiateParams(int nGenSignalZeroGamma, int nGenSignalOneGamma, int nGenSignalTwoGamma, RooRealVar const& expoConstGen, RooRealVar& nSignal, RooRealVar& nPartReco,
RooRealVar& nComb, RooRealVar& fracZero, RooRealVar& fracOne, RooRealVar& expoConst, RooRealVar& nJpsiLeak, bool constPartReco, RooRealVar const& fracPartRecoSigma)
{
TRandom rand;
rand.SetSeed();
int nGenSignal = nGenSignalZeroGamma + nGenSignalOneGamma + nGenSignalTwoGamma;
double nGenSignal2;
double nGenPartReco2;
if(!constPartReco)
{
nGenSignal2 = rand.Uniform(nGenSignal-5*sqrt(nGenSignal), nGenSignal+5*sqrt(nGenSignal));
nGenPartReco2 = rand.Uniform(nGenPartReco-5*sqrt(nGenPartReco), nGenPartReco+5*sqrt(nGenPartReco));
}
if(constPartReco)
{
double nGenSigPartReco( nGenSignal+nGenPartReco );
double nGenSigPartReco2( rand.Uniform( nGenSigPartReco-5*sqrt(nGenSigPartReco), nGenSigPartReco+5*sqrt(nGenSigPartReco) ) );
double fracPartReco1( nGenPartReco/(1.*nGenSignal));
double fracPartReco2( rand.Uniform(fracPartReco1-5*fracPartRecoSigma.getVal(), fracPartReco1+5*fracPartRecoSigma.getVal()) );
nGenPartReco2 = fracPartReco2*nGenSigPartReco2 / (1+fracPartReco2);
nGenSignal2 = nGenSigPartReco2 / (1+fracPartReco2);
}
double nGenComb2 = rand.Uniform(nGenComb-5*sqrt(nGenComb), nGenComb+5*sqrt(nGenComb));
double nGenJpsiLeak2 = rand.Uniform(nGenJpsiLeak-5*sqrt(nGenJpsiLeak), nGenJpsiLeak+5*sqrt(nGenJpsiLeak));
nSignal.setVal(nGenSignal2);
nSignal.setRange(TMath::Max(0.,nGenSignal2-10.*sqrt(nGenSignal)) , nGenSignal2+10*sqrt(nGenSignal));
nPartReco.setVal(nGenPartReco2);
nPartReco.setRange(TMath::Max(0.,nGenPartReco2-10.*sqrt(nGenPartReco)), nGenPartReco2+10*sqrt(nGenPartReco));
nComb.setVal(nGenComb2);
nComb.setRange(TMath::Max(0.,nGenComb2-10.*sqrt(nGenComb)), nGenComb2+10*sqrt(nGenComb));
nJpsiLeak.setVal(nGenJpsiLeak2);
nJpsiLeak.setRange(TMath::Max(0., nGenJpsiLeak2-10*sqrt(nGenJpsiLeak)), nGenJpsiLeak2+10*sqrt(nGenJpsiLeak));
double fracGenZero(nGenSignalZeroGamma/(1.*nGenSignal));
double fracGenOne(nGenSignalOneGamma/(1.*nGenSignal));
fracZero.setVal(rand.Gaus(fracGenZero, sqrt(nGenSignalZeroGamma)/(1.*nGenSignal))) ;
fracZero.setRange(0., 1.);
fracOne.setVal(rand.Gaus(fracGenOne, sqrt(nGenSignalOneGamma)/(1.*nGenSignal))) ;
fracOne.setRange(0., 1.);
expoConst.setVal(rand.Uniform( expoConstGen.getVal() - 5*expoConstGen.getError(), expoConstGen.getVal() + 5*expoConstGen.getError() ) );
expoConst.setRange( expoConstGen.getVal() - 10*expoConstGen.getError(), expoConstGen.getVal() + 10*expoConstGen.getError() );
}
double NormalizedIntegral(RooAbsPdf & function, RooRealVar & integrationVar, double lowerLimit, double upperLimit){
integrationVar.setRange("integralRange",lowerLimit,upperLimit);
RooAbsReal* integral = function.createIntegral(integrationVar,NormSet(integrationVar),Range("integralRange"));
double normlizedIntegralValue = integral->getVal();
// cout<<normlizedIntegralValue<<endl;
return normlizedIntegralValue;
}
void FitterUtilsSimultaneousExpOfPolyTimesX::initiateParams(int nGenSignalZeroGamma, int nGenSignalOneGamma, int nGenSignalTwoGamma,
RooRealVar& nKemu, RooRealVar& nSignal, RooRealVar& nPartReco,
RooRealVar& nComb, RooRealVar& fracZero, RooRealVar& fracOne,
RooRealVar& nJpsiLeak, bool constPartReco, RooRealVar const& fracPartRecoSigma,
RooRealVar& l1Kee, RooRealVar& l2Kee, RooRealVar& l3Kee, RooRealVar& l4Kee, RooRealVar& l5Kee,
RooRealVar& l1Kemu, RooRealVar& l2Kemu, RooRealVar& l3Kemu, RooRealVar& l4Kemu, RooRealVar& l5Kemu,
RooRealVar const& l1KeeGen, RooRealVar const& l2KeeGen, RooRealVar const& l3KeeGen, RooRealVar const& l4KeeGen, RooRealVar const& l5KeeGen
)
{
FitterUtilsExpOfPolyTimesX::initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma,
nSignal, nPartReco, nComb, fracZero, fracOne, nJpsiLeak, constPartReco, fracPartRecoSigma,
l1Kee, l2Kee, l3Kee, l4Kee, l5Kee,
l1KeeGen, l2KeeGen, l3KeeGen, l4KeeGen, l5KeeGen );
TRandom rand;
rand.SetSeed();
nKemu.setVal(rand.Uniform(nGenKemu-5*sqrt(nGenKemu), nGenKemu+5*sqrt(nGenKemu)));
nKemu.setRange(nGenKemu-10*sqrt(nGenKemu), nGenKemu+10*sqrt(nGenKemu));
l1Kemu.setVal(rand.Uniform( l1KeeGen.getVal() - 5*l1KeeGen.getError(), l1KeeGen.getVal() + 5*l1KeeGen.getError() ) );
l1Kemu.setRange( l1KeeGen.getVal() - 10*l1KeeGen.getError(), l1KeeGen.getVal() + 10*l1KeeGen.getError() );
l2Kemu.setVal(rand.Uniform( l2KeeGen.getVal() - 5*l2KeeGen.getError(), l2KeeGen.getVal() + 5*l2KeeGen.getError() ) );
l2Kemu.setRange( l2KeeGen.getVal() - 10*l2KeeGen.getError(), l2KeeGen.getVal() + 10*l2KeeGen.getError() );
l3Kemu.setVal(rand.Uniform( l3KeeGen.getVal() - 5*l3KeeGen.getError(), l3KeeGen.getVal() + 5*l3KeeGen.getError() ) );
l3Kemu.setRange( l3KeeGen.getVal() - 10*l3KeeGen.getError(), l3KeeGen.getVal() + 10*l3KeeGen.getError() );
l4Kemu.setVal(rand.Uniform( l4KeeGen.getVal() - 5*l4KeeGen.getError(), l4KeeGen.getVal() + 5*l4KeeGen.getError() ) );
l4Kemu.setRange( l4KeeGen.getVal() - 10*l4KeeGen.getError(), l4KeeGen.getVal() + 10*l4KeeGen.getError() );
l5Kemu.setVal(rand.Uniform( l5KeeGen.getVal() - 5*l5KeeGen.getError(), l5KeeGen.getVal() + 5*l5KeeGen.getError() ) );
l5Kemu.setRange( l5KeeGen.getVal() - 10*l5KeeGen.getError(), l5KeeGen.getVal() + 10*l5KeeGen.getError() );
}
int main(int argc, char **argv)
{
bool printeff = true;
string fc = "none";
gROOT->ProcessLine(".x lhcbStyle.C");
if(argc > 1)
{
for(int a = 1; a < argc; a++)
{
string arg = argv[a];
string str = arg.substr(2,arg.length()-2);
if(arg.find("-E")!=string::npos) fc = str;
if(arg=="-peff") printeff = true;
}
}
int nexp = 100;
int nbins = 6;
double q2min[] = {8.,15.,11.0,15,16,18};
double q2max[] = {11.,20.,12.5,16,18,20};
TString datafilename = "/afs/cern.ch/work/p/pluca/weighted/Lmumu/candLb.root";
TreeReader * data = new TreeReader("candLb2Lmumu");
data->AddFile(datafilename);
TreeReader * datajpsi = new TreeReader("candLb2JpsiL");
datajpsi->AddFile(datafilename);
TFile * histFile = new TFile("Afb_bkgSys.root","recreate");
string options = "-quiet-noPlot-lin-stdAxis-XM(#Lambda#mu#mu) (MeV/c^{2})-noCost-noParams";
Analysis::SetPrintLevel("s");
RooRealVar * cosThetaL = new RooRealVar("cosThetaL","cosThetaL",0.,-1.,1.);
RooRealVar * cosThetaB = new RooRealVar("cosThetaB","cosThetaB",0.,-1.,1.);
RooRealVar * MM = new RooRealVar("Lb_MassConsLambda","Lb_MassConsLambda",5621.,5400.,6000.);
MM->setRange("Signal",5600,5640);
RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR);
//TGraphAsymmErrors * fL_vs_q2 = new TGraphAsymmErrors();
//TCanvas * ceff = new TCanvas();
RooCategory * samples = new RooCategory("samples","samples");
samples->defineType("DD");
samples->defineType("LL");
RooRealVar * afb = new RooRealVar("afb","afb",0.,-0.75,0.75);
RooRealVar * fL = new RooRealVar("fL","fL",0.6,0.,1.);
TString afbLpdf = "((3./8.)*(1.-fL)*(1 + TMath::Power(cosThetaL,2)) + afb*cosThetaL + (3./4.)*fL*(1 - TMath::Power(cosThetaL,2)))";
RooRealVar * afbB = new RooRealVar("afbB","afbB",0.,-0.5,0.5);
TString afbBpdf = "(1 + 2*afbB*cosThetaB)";
RooAbsPdf * teoPdf = new RooGenericPdf("teoPdf",afbLpdf,RooArgSet(*cosThetaL,*afb,*fL));
RooAbsPdf * teoPdfB = new RooGenericPdf("teoPdfB",afbBpdf,RooArgSet(*cosThetaB,*afbB));
TreeReader * mydata = datajpsi;
Str2VarMap jpsiParsLL = getJpsiPars("LL", CutsDef::LLcut, histFile);
Str2VarMap jpsiParsDD = getJpsiPars("DD", CutsDef::DDcut, histFile);
vector<TH1 *> fLsysh, afbsysh, afbBsysh, fLsysh_frac, afbsysh_frac, afbBsysh_frac;
for(int i = 0; i < nbins; i++)
{
TString q2name = ((TString)Form("q2_%4.2f_%4.2f",q2min[i],q2max[i])).ReplaceAll(".","");
if(i>0) { mydata = data; MM->setRange(5400,6000); }
else { q2name = "jpsi"; MM->setRange(5500,5850); }
TString curq2cut = Form("TMath::Power(J_psi_1S_MM/1000,2) >= %e && TMath::Power(J_psi_1S_MM/1000,2) < %e",q2min[i],q2max[i]);
cout << "------------------- q2 bin: " << q2min[i] << " - " << q2max[i] << " -----------------------" << endl;
/** GET AND FIT EFFICIENCIES **/
RooAbsPdf * effDDpdf = NULL, * effLLpdf = NULL, * effLLBpdf = NULL, * effDDBpdf = NULL;
getEfficiencies(q2min[i],q2max[i],&effLLpdf,&effDDpdf,&effLLBpdf,&effDDBpdf,printeff);
cout << "Efficiencies extracted" << endl;
histFile->cd();
/** FIT AFB **/
afb->setVal(0);
afbB->setVal(-0.37);
fL->setVal(0.6);
RooAbsPdf * corrPdfLL = new RooProdPdf("sigPdfLL"+q2name,"corrPdfLL",*teoPdf,*effLLpdf);
RooAbsPdf * corrPdfDD = new RooProdPdf("sigPdfDD"+q2name,"corrPdfDD",*teoPdf,*effDDpdf);
RooAbsPdf * corrPdfLLB = new RooProdPdf("sigPdfLLB"+q2name,"corrPdfLLB",*teoPdfB,*effLLBpdf);
RooAbsPdf * corrPdfDDB = new RooProdPdf("sigPdfDDB"+q2name,"corrPdfDDB",*teoPdfB,*effDDBpdf);
TCut baseCut = "";
TCut cutLL = CutsDef::LLcut + (TCut)curq2cut + baseCut;
TCut cutDD = CutsDef::DDcut + (TCut)curq2cut + baseCut;
histFile->cd();
double fracDDv[2], fracLLv[2];
double nsigDD, nsigLL;
RooDataSet * dataLL = getDataAndFrac("LL",q2name,mydata,cutLL,MM,&fracLLv[0],jpsiParsLL,&nsigLL);
RooDataSet * dataDD = getDataAndFrac("DD",q2name,mydata,cutDD,MM,&fracDDv[0],jpsiParsDD,&nsigDD);
double nevts = nsigDD+nsigLL;
cout << fixed << setprecision(3) << fracDDv[0] << " " << fracDDv[1] << endl;
RooRealVar * fracLL = new RooRealVar("fracLL","fracLL",fracLLv[0]);
RooRealVar * fracDD = new RooRealVar("fracDD","fracDD",fracDDv[0]);
RooAbsPdf * bkgLL = NULL, * bkgLLB = NULL, * bkgDD = NULL, * bkgDDB = NULL;
buildBkgPdfs(q2min[i],q2max[i],"LL",CutsDef::LLcut,&bkgLL,&bkgLLB);
buildBkgPdfs(q2min[i],q2max[i],"DD",CutsDef::DDcut,&bkgDD,&bkgDDB);
cout << "Backgrounds extracted" << endl;
RooAbsPdf * modelLL = new RooAddPdf("modelLL","modelLL",RooArgSet(*corrPdfLL,*bkgLL),*fracLL);
RooAbsPdf * modelDD = new RooAddPdf("modelDD","modelDD",RooArgSet(*corrPdfDD,*bkgDD),*fracDD);
RooAbsPdf * modelLLB = new RooAddPdf("modelLLB","modelLLB",RooArgSet(*corrPdfLLB,*bkgLLB),*fracLL);
RooAbsPdf * modelDDB = new RooAddPdf("modelDDB","modelDDB",RooArgSet(*corrPdfDDB,*bkgDDB),*fracDD);
// CREATE COMBINED DATASET
RooDataSet * combData = new RooDataSet(Form("combData_%i",i),"combined data",RooArgSet(*MM,*cosThetaL,*cosThetaB),Index(*samples),Import("DD",*dataDD),Import("LL",*dataLL));
Str2VarMap params;
params["fL"] = fL;
params["afb"] = afb;
Str2VarMap paramsB;
paramsB["afbB"] = afbB;
// FIT COS LEPTON
RooSimultaneous * combModel = new RooSimultaneous(Form("combModel_%i",i),"",*samples);
combModel->addPdf(*modelLL,"LL");
combModel->addPdf(*modelDD,"DD");
RooFitResult * res = safeFit(combModel,combData,params,&isInAllowedArea);
// FIT COS HADRON
RooSimultaneous * combModelB = new RooSimultaneous(Form("combModelB_%i",i),"",*samples);
combModelB->addPdf(*modelLLB,"LL");
combModelB->addPdf(*modelDDB,"DD");
RooFitResult * resB = safeFit(combModelB,combData,paramsB,&isInAllowedAreaB);
cout << endl << fixed << setprecision(6) << "AfbB = " << afbB->getVal() << " +/- " << afbB->getError() << endl;
cout << "Afb = " << afb->getVal() << " +/- " << afb->getError() << endl;
cout << "fL = " << fL->getVal() << " +/- " << fL->getError() << endl;
cout << endl;
cout << "lepton: " << res->edm() << " " << res->covQual() << endl;
cout << "baryon: " << resB->edm() << " " << resB->covQual() << endl;
cout << endl;
TH1F * fLsys = new TH1F(Form("fLsys_%i",i),"fLsys",40,-1,1);
TH1F * afbsys = new TH1F(Form("afbsys_%i",i),"afbsys",40,-1,1);
TH1F * afbBsys = new TH1F(Form("afbBsys_%i",i),"afbBsys",40,-1,1);
TH1F * fLsys_frac = new TH1F(Form("fLsys_frac%i",i),"fLsys",40,-1,1);
TH1F * afbsys_frac = new TH1F(Form("afbsys_frac%i",i),"afbsys",40,-1,1);
TH1F * afbBsys_frac = new TH1F(Form("afbBsys_frac%i",i),"afbBsys",40,-1,1);
RooAbsPdf * mybkgDD_2 = NULL, * mybkgDDB_2 = NULL;
buildBkgPdfs(q2min[i],q2max[i],"DD",CutsDef::DDcut,&mybkgDD_2,&mybkgDDB_2,"RooKeyPdf");
//cout << nevts << endl;
//TRandom3 r(0);
for(int e = 0; e < nexp; e++)
{
histFile->cd();
RooAbsPdf * toypdf = (RooAbsPdf *)modelDD->Clone();
Analysis * toy = new Analysis("toy",cosThetaL,modelDD,nevts);
RooAbsPdf * toypdfB = (RooAbsPdf *)modelDDB->Clone();
Analysis * toyB = new Analysis("toyB",cosThetaB,modelDDB,nevts);
afb->setVal(0);
afbB->setVal(-0.37);
fL->setVal(0.6);
safeFit(toypdf,toy->GetDataSet("-recalc"),params,&isInAllowedArea);
safeFit(toypdfB,toyB->GetDataSet("-recalc"),paramsB,&isInAllowedAreaB);
double def_afb = afb->getVal();
double def_fL = fL->getVal();
double def_afbB = afbB->getVal();
afb->setVal(0);
afbB->setVal(-0.37);
fL->setVal(0.6);
RooAbsPdf * modelDD_2 = new RooAddPdf("modelDD_2","modelDD",RooArgSet(*corrPdfDD,*mybkgDD_2),*fracDD);
RooAbsPdf * modelDDB_2 = new RooAddPdf("modelDDB_2","modelDDB",RooArgSet(*corrPdfDDB,*mybkgDDB_2),*fracDD);
safeFit(modelDD_2,toy->GetDataSet("-recalc"),params,&isInAllowedArea);
safeFit(modelDDB_2,toyB->GetDataSet("-recalc"),paramsB,&isInAllowedAreaB);
double oth_afb = afb->getVal();
double oth_fL = fL->getVal();
double oth_afbB = afbB->getVal();
fLsys->Fill(oth_fL-def_fL);
afbsys->Fill(oth_afb-def_afb);
afbBsys->Fill(oth_afbB-def_afbB);
afb->setVal(0.);
afbB->setVal(-0.37);
fL->setVal(0.6);
//double rdm_frac = r.Gaus(fracDDv[0],fracDDv[1]);
double rdm_frac = fracDDv[0] + fracDDv[1];
RooRealVar * fracDD_2 = new RooRealVar("fracDD_2","fracDD_2",rdm_frac);
RooAbsPdf * modelDD_3 = new RooAddPdf("modelDD_3","modelDD",RooArgSet(*corrPdfDD,*bkgDD),*fracDD_2);
RooAbsPdf * modelDDB_3 = new RooAddPdf("modelDDB_3","modelDDB",RooArgSet(*corrPdfDDB,*bkgDDB),*fracDD_2);
safeFit(modelDD_3,toy->GetDataSet("-recalc"),params,&isInAllowedArea);
safeFit(modelDDB_3,toyB->GetDataSet("-recalc"),paramsB,&isInAllowedAreaB);
double frc_afb = afb->getVal();
double frc_fL = fL->getVal();
double frc_afbB = afbB->getVal();
fLsys_frac->Fill(frc_fL-def_fL);
afbsys_frac->Fill(frc_afb-def_afb);
afbBsys_frac->Fill(frc_afbB-def_afbB);
}
afbsysh.push_back(afbsys);
afbBsysh.push_back(afbBsys);
fLsysh.push_back(fLsys);
afbsysh_frac.push_back(afbsys_frac);
afbBsysh_frac.push_back(afbBsys_frac);
fLsysh_frac.push_back(fLsys_frac);
}
for(int q = 0; q < nbins; q++)
{
cout << fixed << setprecision(2) << "-------- Bin " << q2min[q] << "-" << q2max[q] << endl;
cout << fixed << setprecision(5) << "fL sys = " << fLsysh[q]->GetMean() << " +/- " << fLsysh[q]->GetMeanError() << endl;
cout << "Afb sys = " << afbsysh[q]->GetMean() << " +/- " << afbsysh[q]->GetMeanError() << endl;
cout << "AfbB sys = " << afbBsysh[q]->GetMean() << " +/- " << afbBsysh[q]->GetMeanError() << endl;
}
cout << "#################################################################" << endl;
for(int q = 0; q < nbins; q++)
{
cout << fixed << setprecision(2) << "-------- Bin " << q2min[q] << "-" << q2max[q] << endl;
cout << fixed << setprecision(5) << "fL sys = " << fLsysh_frac[q]->GetMean() << " +/- " << fLsysh_frac[q]->GetMeanError() << endl;
cout << "Afb sys = " << afbsysh_frac[q]->GetMean() << " +/- " << afbsysh_frac[q]->GetMeanError() << endl;
cout << "AfbB sys = " << afbBsysh_frac[q]->GetMean() << " +/- " << afbBsysh_frac[q]->GetMeanError() << endl;
}
cout << "#################################################################" << endl;
for(int q = 0; q < nbins; q++)
{
cout << fixed << setprecision(2) << "-------- Bin " << q2min[q] << "-" << q2max[q] << endl;
cout << fixed << setprecision(5) << "fL sys = " << TMath::Sqrt(TMath::Power(fLsysh_frac[q]->GetMean(),2) + TMath::Power(fLsysh[q]->GetMean(),2) ) << endl;
cout << "Afb sys = " << TMath::Sqrt(TMath::Power(afbsysh_frac[q]->GetMean(),2) + TMath::Power(afbsysh[q]->GetMean(),2) ) << endl;
cout << "AfbB sys = " << TMath::Sqrt(TMath::Power(afbBsysh_frac[q]->GetMean(),2) + TMath::Power(afbBsysh[q]->GetMean(),2) ) << endl;
}
}
void FitterUtilsSimultaneousExpOfPolyTimesX::generate(bool wantPlots, string plotsfile)
{
FitterUtilsExpOfPolyTimesX::generate(wantPlots, plotsfile);
TFile fw(workspacename.c_str(), "UPDATE");
RooWorkspace* workspace = (RooWorkspace*)fw.Get("workspace");
RooRealVar *B_plus_M = workspace->var("B_plus_M");
RooRealVar *misPT = workspace->var("misPT");
RooDataSet* dataSetCombExt = (RooDataSet*)workspace->data("dataSetCombExt");
RooDataSet* dataSetComb = (RooDataSet*)workspace->data("dataSetComb");
// RooRealVar *l1KeeGen = workspace->var("l1KeeGen");
// RooRealVar *l2KeeGen = workspace->var("l2KeeGen");
// RooRealVar *l3KeeGen = workspace->var("l3KeeGen");
// RooRealVar *l4KeeGen = workspace->var("l4KeeGen");
// RooRealVar *l5KeeGen = workspace->var("l5KeeGen");
//
//
// RooExpOfPolyTimesX kemuPDF("kemuPDF", "kemuPDF", *B_plus_M, *misPT, *l1KeeGen, *l2KeeGen, *l3KeeGen, *l4KeeGen, *l5KeeGen);
//
// RooAbsPdf::GenSpec* GenSpecKemu = kemuPDF.prepareMultiGen(RooArgSet(*B_plus_M, *misPT), RooFit::Extended(1), NumEvents(nGenKemu));
//
// cout<<"Generating Kemu"<<endl;
// RooDataSet* dataGenKemu = kemuPDF.generate(*GenSpecKemu);//(argset, 100, false, true, "", false, true);
// dataGenKemu->SetName("dataGenKemu"); dataGenKemu->SetTitle("dataGenKemu");
//
//
// RooWorkspace* workspaceGen = (RooWorkspace*)fw.Get("workspaceGen");
// workspaceGen->import(*dataGenKemu);
//
// workspaceGen->Write("", TObject::kOverwrite);
// fw.Close();
// delete dataGenKemu;
// delete GenSpecKemu;
TVectorD rho(2);
rho[0] = 2.5;
rho[1] = 1.5;
misPT->setRange(-2000, 5000);
RooNDKeysPdf kemuPDF("kemuPDF", "kemuPDF", RooArgList(*B_plus_M, *misPT), *dataSetCombExt, rho, "ma",3, true);
misPT->setRange(0, 5000);
RooAbsPdf::GenSpec* GenSpecKemu = kemuPDF.prepareMultiGen(RooArgSet(*B_plus_M, *misPT), RooFit::Extended(1), NumEvents(nGenKemu));
cout<<"Generating Kemu"<<endl;
RooDataSet* dataGenKemu = kemuPDF.generate(*GenSpecKemu);//(argset, 100, false, true, "", false, true);
dataGenKemu->SetName("dataGenKemu"); dataGenKemu->SetTitle("dataGenKemu");
RooWorkspace* workspaceGen = (RooWorkspace*)fw.Get("workspaceGen");
workspaceGen->import(*dataGenKemu);
if(wantPlots) PlotShape(*dataSetComb, *dataGenKemu, kemuPDF, plotsfile, "cKemuKeys", *B_plus_M, *misPT);
fw.cd();
workspaceGen->Write("", TObject::kOverwrite);
fw.Close();
delete dataGenKemu;
delete GenSpecKemu;
}
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;
}
int main(int argc, char* argv[]) {
doofit::builder::EasyPdf *epdf = new doofit::builder::EasyPdf();
epdf->Var("sig_yield");
epdf->Var("sig_yield").setVal(153000);
epdf->Var("sig_yield").setConstant(false);
//decay time
epdf->Var("obsTime");
epdf->Var("obsTime").SetTitle("t_{#kern[-0.2]{B}_{#kern[-0.1]{ d}}^{#kern[-0.1]{ 0}}}");
epdf->Var("obsTime").setUnit("ps");
epdf->Var("obsTime").setRange(0.,16.);
// tag, respectively the initial state of the produced B meson
epdf->Cat("obsTag");
epdf->Cat("obsTag").defineType("B_S",1);
epdf->Cat("obsTag").defineType("Bbar_S",-1);
//finalstate
epdf->Cat("catFinalState");
epdf->Cat("catFinalState").defineType("f",1);
epdf->Cat("catFinalState").defineType("fbar",-1);
epdf->Var("obsEtaOS");
epdf->Var("obsEtaOS").setRange(0.0,0.5);
std::vector<double> knots;
knots.push_back(0.07);
knots.push_back(0.10);
knots.push_back(0.138);
knots.push_back(0.16);
knots.push_back(0.23);
knots.push_back(0.28);
knots.push_back(0.35);
knots.push_back(0.42);
knots.push_back(0.44);
knots.push_back(0.48);
knots.push_back(0.5);
// empty arg list for coefficients
RooArgList* list = new RooArgList();
// create first coefficient
RooRealVar* coeff_first = &(epdf->Var("parCSpline1"));
coeff_first->setRange(0,10000);
coeff_first->setVal(1);
coeff_first->setConstant(false);
list->add( *coeff_first );
for (unsigned int i=1; i <= knots.size(); ++i){
std::string number = boost::lexical_cast<std::string>(i);
RooRealVar* coeff = &(epdf->Var("parCSpline"+number));
coeff->setRange(0,10000);
coeff->setVal(1);
coeff->setConstant(false);
list->add( *coeff );
}
// create last coefficient
RooRealVar* coeff_last = &(epdf->Var("parCSpline"+boost::lexical_cast<std::string>(knots.size())));
coeff_last->setRange(0,10000);
coeff_last->setVal(1);
coeff_last->setConstant(false);
list->add( *coeff_last );
list->Print();
// define Eta PDF
doofit::roofit::pdfs::DooCubicSplinePdf splinePdf("splinePdf",epdf->Var("obsEtaOS"),knots,*list,0,0.5);
//Berechne die Tagging Assymetrie
epdf->Var("p0");
epdf->Var("p0").setVal(0.369);
epdf->Var("p0").setConstant(true);
epdf->Var("p1");
epdf->Var("p1").setVal(0.952);
epdf->Var("p1").setConstant(true);
epdf->Var("delta_p0");
epdf->Var("delta_p0").setVal(0.019);
epdf->Var("delta_p0").setConstant(true);
epdf->Var("delta_p1");
epdf->Var("delta_p1").setVal(-0.012);
epdf->Var("delta_p1").setConstant(true);
epdf->Var("etamean");
epdf->Var("etamean").setVal(0.365);
epdf->Var("etamean").setConstant(true);
epdf->Formula("omega","@0 +@1/2 +(@2+@3/2)*(@4-@5)", RooArgList(epdf->Var("p0"),epdf->Var("delta_p0"),epdf->Var("p1"),epdf->Var("delta_p1"),epdf->Var("obsEtaOS"),epdf->Var("etamean")));
epdf->Formula("omegabar","@0 -@1/2 +(@2-@3/2)*(@4-@5)", RooArgList(epdf->Var("p0"),epdf->Var("delta_p0"),epdf->Var("p1"),epdf->Var("delta_p1"),epdf->Var("obsEtaOS"),epdf->Var("etamean")));
//Koeffizienten
DecRateCoeff *coeff_c = new DecRateCoeff("coef_cos","coef_cos",DecRateCoeff::CPOdd,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("C_f"),epdf->Var("C_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Real("omega"),epdf->Real("omegabar"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_s = new DecRateCoeff("coef_sin","coef_sin",DecRateCoeff::CPOdd,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("S_f"),epdf->Var("S_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Real("omega"),epdf->Real("omegabar"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_sh = new DecRateCoeff("coef_sinh","coef_sinh",DecRateCoeff::CPEven,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("f1_f"),epdf->Var("f1_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Real("omega"),epdf->Real("omegabar"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_ch = new DecRateCoeff("coef_cosh","coef_cosh",DecRateCoeff::CPEven,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("f0_f"),epdf->Var("f0_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Real("omega"),epdf->Real("omegabar"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
epdf->AddRealToStore(coeff_ch);
epdf->AddRealToStore(coeff_sh);
epdf->AddRealToStore(coeff_c);
epdf->AddRealToStore(coeff_s);
///////////////////Generiere PDF's/////////////////////
//Zeit
epdf->GaussModel("resTimeGauss",epdf->Var("obsTime"),epdf->Var("allTimeResMean"),epdf->Var("allTimeReso"));
epdf->BDecay("pdfSigTime",epdf->Var("obsTime"),epdf->Var("tau"),epdf->Var("dgamma"),epdf->Real("coef_cosh"),epdf->Real("coef_sinh"),epdf->Real("coef_cos"),epdf->Real("coef_sin"),epdf->Var("deltaM"),epdf->Model("resTimeGauss"));
//Zusammenfassen der Parameter in einem RooArgSet
RooArgSet Observables;
Observables.add(RooArgSet( epdf->Var("obsTime"),epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("obsEtaOS")));
epdf->Extend("pdfExtend", epdf->Pdf("pdfSigTime"),epdf->Real("sig_yield"));
RooWorkspace ws;
ws.import(epdf->Pdf("pdfExtend"));
ws.defineSet("Observables",Observables, true);
ws.Print();
doofit::config::CommonConfig cfg_com("common");
cfg_com.InitializeOptions(argc, argv);
doofit::toy::ToyFactoryStdConfig cfg_tfac("toyfac");
cfg_tfac.InitializeOptions(cfg_com);
doofit::toy::ToyStudyStdConfig cfg_tstudy("toystudy");
cfg_tstudy.InitializeOptions(cfg_tfac);
// set a previously defined workspace to get PDF from (not mandatory, but convenient)
cfg_tfac.set_workspace(&ws);
cfg_com.CheckHelpFlagAndPrintHelp();
// Initialize the toy factory module with the config objects and start
// generating toy samples.
doofit::toy::ToyFactoryStd tfac(cfg_com, cfg_tfac);
doofit::toy::ToyStudyStd tstudy(cfg_com, cfg_tstudy);
//Generate data
RooDataSet* data = tfac.Generate();
data->Print();
epdf->Pdf("pdfExtend").getParameters(data)->readFromFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-parameter.txt");
epdf->Pdf("pdfExtend").getParameters(data)->writeToFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-parameter.txt.new");
//FIT-PDF-Koeffizienten
epdf->Var("asym_prodFit");
epdf->Var("asym_prodFit").setVal(-0.0108);
epdf->Var("asym_prodFit").setConstant(false);
DecRateCoeff *coeff_cFit = new DecRateCoeff("coef_cosFit","coef_cosFit",DecRateCoeff::CPOdd,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("C_f"),epdf->Var("C_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Real("omega"),epdf->Real("omegabar"),epdf->Var("asym_prodFit"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_sFit = new DecRateCoeff("coef_sinFit","coef_sinFit",DecRateCoeff::CPOdd,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("S_f"),epdf->Var("S_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Real("omega"),epdf->Real("omegabar"),epdf->Var("asym_prodFit"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_shFit = new DecRateCoeff("coef_sinhFit","coef_sinhFit",DecRateCoeff::CPEven,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("f1_f"),epdf->Var("f1_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Real("omega"),epdf->Real("omegabar"),epdf->Var("asym_prodFit"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_chFit = new DecRateCoeff("coef_coshFit","coef_coshFit",DecRateCoeff::CPEven,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("f0_f"),epdf->Var("f0_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Real("omega"),epdf->Real("omegabar"),epdf->Var("asym_prodFit"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
epdf->AddRealToStore(coeff_chFit);
epdf->AddRealToStore(coeff_shFit);
epdf->AddRealToStore(coeff_cFit);
epdf->AddRealToStore(coeff_sFit);
///////////////////Generiere PDF's/////////////////////
//Zeit
epdf->BDecay("pdfSigTimeFit",epdf->Var("obsTime"),epdf->Var("tau"),epdf->Var("dgamma"),epdf->Real("coef_coshFit"),epdf->Real("coef_sinhFit"),epdf->Real("coef_cosFit"),epdf->Real("coef_sinFit"),epdf->Var("deltaM"),epdf->Model("resTimeGauss"));
//Zusammenfassen der Parameter in einem RooArgSet
RooArgSet ObservablesFit;
ObservablesFit.add(RooArgSet( epdf->Var("obsTime"),epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("obsEtaOS")));
epdf->Extend("pdfExtendFit", epdf->Pdf("pdfSigTimeFit"),epdf->Real("sig_yield"));
RooFitResult* fit_result = epdf->Pdf("pdfExtendFit").fitTo(*data, RooFit::Save(true));
tstudy.StoreFitResult(fit_result);
//epdf->Pdf("pdfExtendFit").getParameters(data)->readFromFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-parameter.txt");
//epdf->Pdf("pdfExtendFit").getParameters(data)->writeToFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-parameter.txt.new");
//Plotten auf lhcb
/*using namespace doofit::plotting;
PlotConfig cfg_plot("cfg_plot");
cfg_plot.InitializeOptions();
cfg_plot.set_plot_directory("/net/storage03/data/users/chasenberg/ergebnis/dootoycp_float-lhcb/dgamma/time/");
// plot PDF and directly specify components
Plot myplot(cfg_plot, epdf->Var("obsTime"), *data, RooArgList(epdf->Pdf("pdfExtend")));
myplot.PlotItLogNoLogY();
PlotConfig cfg_plotEta("cfg_plotEta");
cfg_plotEta.InitializeOptions();
cfg_plotEta.set_plot_directory("/net/storage03/data/users/chasenberg/ergebnis/dootoycp_float-lhcb/dgamma/eta/");
// plot PDF and directly specify components
Plot myplotEta(cfg_plotEta, epdf->Var("obsEtaOS"), *data, RooArgList(splinePdf));
myplotEta.PlotIt();*/
}
// The actual job
void backgroundFits_qqzz_1Dw(int channel, int sqrts, int VBFtag)
{
if(sqrts==7)return;
TString schannel;
if (channel == 1) schannel = "4mu";
else if (channel == 2) schannel = "4e";
else if (channel == 3) schannel = "2e2mu";
else cout << "Not a valid channel: " << schannel << endl;
TString ssqrts = (long) sqrts + TString("TeV");
cout << "schannel = " << schannel << " sqrts = " << sqrts << " VBFtag = " << VBFtag << endl;
TString outfile;
if(VBFtag<2) outfile = "CardFragments/qqzzBackgroundFit_" + ssqrts + "_" + schannel + "_" + Form("%d",int(VBFtag)) + ".txt";
if(VBFtag==2) outfile = "CardFragments/qqzzBackgroundFit_" + ssqrts + "_" + schannel + ".txt";
ofstream of(outfile,ios_base::out);
of << "### background functions ###" << endl;
gSystem->AddIncludePath("-I$ROOFITSYS/include");
gROOT->ProcessLine(".L ../CreateDatacards/include/tdrstyle.cc");
setTDRStyle(false);
gStyle->SetPadLeftMargin(0.16);
TString filepath;
if (sqrts==7) {
filepath = filePath7TeV;
} else if (sqrts==8) {
filepath = filePath8TeV;
}
TChain* tree = new TChain("SelectedTree");
tree->Add( filepath+ "/" + (schannel=="2e2mu"?"2mu2e":schannel) + "/HZZ4lTree_ZZTo*.root");
RooRealVar* MC_weight = new RooRealVar("MC_weight","MC_weight",0.,2.) ;
RooRealVar* ZZMass = new RooRealVar("ZZMass","ZZMass",100.,1000.);
RooRealVar* NJets30 = new RooRealVar("NJets30","NJets30",0.,100.);
RooArgSet ntupleVarSet(*ZZMass,*NJets30,*MC_weight);
RooDataSet *set = new RooDataSet("set","set",ntupleVarSet,WeightVar("MC_weight"));
Float_t myMC,myMass;
Short_t myNJets;
int nentries = tree->GetEntries();
tree->SetBranchAddress("ZZMass",&myMass);
tree->SetBranchAddress("MC_weight",&myMC);
tree->SetBranchAddress("NJets30",&myNJets);
for(int i =0;i<nentries;i++) {
tree->GetEntry(i);
if(VBFtag==1 && myNJets<2)continue;
if(VBFtag==0 && myNJets>1)continue;
ntupleVarSet.setRealValue("ZZMass",myMass);
ntupleVarSet.setRealValue("MC_weight",myMC);
ntupleVarSet.setRealValue("NJets30",(double)myNJets);
set->add(ntupleVarSet, myMC);
}
double totalweight = 0.;
double totalweight_z = 0.;
for (int i=0 ; i<set->numEntries() ; i++) {
//set->get(i) ;
RooArgSet* row = set->get(i) ;
//row->Print("v");
totalweight += set->weight();
if (row->getRealValue("ZZMass") < 200) totalweight_z += set->weight();
}
cout << "nEntries: " << set->numEntries() << ", totalweight: " << totalweight << ", totalweight_z: " << totalweight_z << endl;
gSystem->Load("libHiggsAnalysisCombinedLimit.so");
//// ---------------------------------------
//Background
RooRealVar CMS_qqzzbkg_a0("CMS_qqzzbkg_a0","CMS_qqzzbkg_a0",115.3,0.,200.);
RooRealVar CMS_qqzzbkg_a1("CMS_qqzzbkg_a1","CMS_qqzzbkg_a1",21.96,0.,200.);
RooRealVar CMS_qqzzbkg_a2("CMS_qqzzbkg_a2","CMS_qqzzbkg_a2",122.8,0.,200.);
RooRealVar CMS_qqzzbkg_a3("CMS_qqzzbkg_a3","CMS_qqzzbkg_a3",0.03479,0.,1.);
RooRealVar CMS_qqzzbkg_a4("CMS_qqzzbkg_a4","CMS_qqzzbkg_a4",185.5,0.,200.);
RooRealVar CMS_qqzzbkg_a5("CMS_qqzzbkg_a5","CMS_qqzzbkg_a5",12.67,0.,200.);
RooRealVar CMS_qqzzbkg_a6("CMS_qqzzbkg_a6","CMS_qqzzbkg_a6",34.81,0.,100.);
RooRealVar CMS_qqzzbkg_a7("CMS_qqzzbkg_a7","CMS_qqzzbkg_a7",0.1393,0.,1.);
RooRealVar CMS_qqzzbkg_a8("CMS_qqzzbkg_a8","CMS_qqzzbkg_a8",66.,0.,200.);
RooRealVar CMS_qqzzbkg_a9("CMS_qqzzbkg_a9","CMS_qqzzbkg_a9",0.07191,0.,1.);
RooRealVar CMS_qqzzbkg_a10("CMS_qqzzbkg_a10","CMS_qqzzbkg_a10",94.11,0.,200.);
RooRealVar CMS_qqzzbkg_a11("CMS_qqzzbkg_a11","CMS_qqzzbkg_a11",-5.111,-100.,100.);
RooRealVar CMS_qqzzbkg_a12("CMS_qqzzbkg_a12","CMS_qqzzbkg_a12",4834,0.,10000.);
RooRealVar CMS_qqzzbkg_a13("CMS_qqzzbkg_a13","CMS_qqzzbkg_a13",0.2543,0.,1.);
if (channel == 1){
///* 4mu
CMS_qqzzbkg_a0.setVal(103.854);
CMS_qqzzbkg_a1.setVal(10.0718);
CMS_qqzzbkg_a2.setVal(117.551);
CMS_qqzzbkg_a3.setVal(0.0450287);
CMS_qqzzbkg_a4.setVal(185.262);
CMS_qqzzbkg_a5.setVal(7.99428);
CMS_qqzzbkg_a6.setVal(39.7813);
CMS_qqzzbkg_a7.setVal(0.0986891);
CMS_qqzzbkg_a8.setVal(49.1325);
CMS_qqzzbkg_a9.setVal(0.0389984);
CMS_qqzzbkg_a10.setVal(98.6645);
CMS_qqzzbkg_a11.setVal(-7.02043);
CMS_qqzzbkg_a12.setVal(5694.66);
CMS_qqzzbkg_a13.setVal(0.0774525);
//*/
}
else if (channel == 2){
///* 4e
CMS_qqzzbkg_a0.setVal(111.165);
CMS_qqzzbkg_a1.setVal(19.8178);
CMS_qqzzbkg_a2.setVal(120.89);
CMS_qqzzbkg_a3.setVal(0.0546639);
CMS_qqzzbkg_a4.setVal(184.878);
CMS_qqzzbkg_a5.setVal(11.7041);
CMS_qqzzbkg_a6.setVal(33.2659);
CMS_qqzzbkg_a7.setVal(0.140858);
CMS_qqzzbkg_a8.setVal(56.1226);
CMS_qqzzbkg_a9.setVal(0.0957699);
CMS_qqzzbkg_a10.setVal(98.3662);
CMS_qqzzbkg_a11.setVal(-6.98701);
CMS_qqzzbkg_a12.setVal(10.0536);
CMS_qqzzbkg_a13.setVal(0.110576);
//*/
}
else if (channel == 3){
///* 2e2mu
CMS_qqzzbkg_a0.setVal(110.293);
CMS_qqzzbkg_a1.setVal(11.8334);
CMS_qqzzbkg_a2.setVal(116.91);
CMS_qqzzbkg_a3.setVal(0.0433151);
CMS_qqzzbkg_a4.setVal(185.817);
CMS_qqzzbkg_a5.setVal(10.5945);
CMS_qqzzbkg_a6.setVal(29.6208);
CMS_qqzzbkg_a7.setVal(0.0826);
CMS_qqzzbkg_a8.setVal(53.1346);
CMS_qqzzbkg_a9.setVal(0.0882081);
CMS_qqzzbkg_a10.setVal(85.3776);
CMS_qqzzbkg_a11.setVal(-13.3836);
CMS_qqzzbkg_a12.setVal(7587.95);
CMS_qqzzbkg_a13.setVal(0.325621);
//*/
}
else {
cout << "disaster" << endl;
}
RooqqZZPdf_v2* bkg_qqzz = new RooqqZZPdf_v2("bkg_qqzz","bkg_qqzz",*ZZMass,
CMS_qqzzbkg_a0,CMS_qqzzbkg_a1,CMS_qqzzbkg_a2,CMS_qqzzbkg_a3,CMS_qqzzbkg_a4,
CMS_qqzzbkg_a5,CMS_qqzzbkg_a6,CMS_qqzzbkg_a7,CMS_qqzzbkg_a8,
CMS_qqzzbkg_a9,CMS_qqzzbkg_a10,CMS_qqzzbkg_a11,CMS_qqzzbkg_a12,CMS_qqzzbkg_a13);
RooArgSet myASet(*ZZMass, CMS_qqzzbkg_a0,CMS_qqzzbkg_a1,CMS_qqzzbkg_a2,CMS_qqzzbkg_a3,CMS_qqzzbkg_a4,
CMS_qqzzbkg_a5,CMS_qqzzbkg_a6,CMS_qqzzbkg_a7);
myASet.add(CMS_qqzzbkg_a8);
myASet.add(CMS_qqzzbkg_a9);
myASet.add(CMS_qqzzbkg_a10);
myASet.add(CMS_qqzzbkg_a11);
myASet.add(CMS_qqzzbkg_a12);
myASet.add(CMS_qqzzbkg_a13);
RooFitResult *r1 = bkg_qqzz->fitTo( *set, Save(kTRUE), SumW2Error(kTRUE) );//, Save(kTRUE), SumW2Error(kTRUE)) ;
cout << endl;
cout << "------- Parameters for " << schannel << " sqrts=" << sqrts << endl;
cout << " a0_bkgd = " << CMS_qqzzbkg_a0.getVal() << endl;
cout << " a1_bkgd = " << CMS_qqzzbkg_a1.getVal() << endl;
cout << " a2_bkgd = " << CMS_qqzzbkg_a2.getVal() << endl;
cout << " a3_bkgd = " << CMS_qqzzbkg_a3.getVal() << endl;
cout << " a4_bkgd = " << CMS_qqzzbkg_a4.getVal() << endl;
cout << " a5_bkgd = " << CMS_qqzzbkg_a5.getVal() << endl;
cout << " a6_bkgd = " << CMS_qqzzbkg_a6.getVal() << endl;
cout << " a7_bkgd = " << CMS_qqzzbkg_a7.getVal() << endl;
cout << " a8_bkgd = " << CMS_qqzzbkg_a8.getVal() << endl;
cout << " a9_bkgd = " << CMS_qqzzbkg_a9.getVal() << endl;
cout << " a10_bkgd = " << CMS_qqzzbkg_a10.getVal() << endl;
cout << " a11_bkgd = " << CMS_qqzzbkg_a11.getVal() << endl;
cout << " a12_bkgd = " << CMS_qqzzbkg_a12.getVal() << endl;
cout << " a13_bkgd = " << CMS_qqzzbkg_a13.getVal() << endl;
cout << "}" << endl;
cout << "---------------------------" << endl;
of << "qqZZshape a0_bkgd " << CMS_qqzzbkg_a0.getVal() << endl;
of << "qqZZshape a1_bkgd " << CMS_qqzzbkg_a1.getVal() << endl;
of << "qqZZshape a2_bkgd " << CMS_qqzzbkg_a2.getVal() << endl;
of << "qqZZshape a3_bkgd " << CMS_qqzzbkg_a3.getVal() << endl;
of << "qqZZshape a4_bkgd " << CMS_qqzzbkg_a4.getVal() << endl;
of << "qqZZshape a5_bkgd " << CMS_qqzzbkg_a5.getVal() << endl;
of << "qqZZshape a6_bkgd " << CMS_qqzzbkg_a6.getVal() << endl;
of << "qqZZshape a7_bkgd " << CMS_qqzzbkg_a7.getVal() << endl;
of << "qqZZshape a8_bkgd " << CMS_qqzzbkg_a8.getVal() << endl;
of << "qqZZshape a9_bkgd " << CMS_qqzzbkg_a9.getVal() << endl;
of << "qqZZshape a10_bkgd " << CMS_qqzzbkg_a10.getVal() << endl;
of << "qqZZshape a11_bkgd " << CMS_qqzzbkg_a11.getVal() << endl;
of << "qqZZshape a12_bkgd " << CMS_qqzzbkg_a12.getVal() << endl;
of << "qqZZshape a13_bkgd " << CMS_qqzzbkg_a13.getVal() << endl;
of << endl << endl;
of.close();
cout << endl << "Output written to: " << outfile << endl;
double qqzznorm;
if (channel == 1) qqzznorm = 20.5836;
else if (channel == 2) qqzznorm = 13.8871;
else if (channel == 3) qqzznorm = 32.9883;
else { cout << "disaster!" << endl; }
ZZMass->setRange("fullrange",100.,1000.);
ZZMass->setRange("largerange",100.,600.);
ZZMass->setRange("zoomrange",100.,200.);
double rescale = qqzznorm/totalweight;
double rescale_z = qqzznorm/totalweight_z;
cout << "rescale: " << rescale << ", rescale_z: " << rescale_z << endl;
// Plot m4l and
RooPlot* frameM4l = ZZMass->frame(Title("M4L"),Range(100,600),Bins(250)) ;
set->plotOn(frameM4l, MarkerStyle(20), Rescale(rescale)) ;
//set->plotOn(frameM4l) ;
RooPlot* frameM4lz = ZZMass->frame(Title("M4L"),Range(100,200),Bins(100)) ;
set->plotOn(frameM4lz, MarkerStyle(20), Rescale(rescale)) ;
int iLineColor = 1;
string lab = "blah";
if (channel == 1) { iLineColor = 2; lab = "4#mu"; }
if (channel == 3) { iLineColor = 4; lab = "2e2#mu"; }
if (channel == 2) { iLineColor = 6; lab = "4e"; }
bkg_qqzz->plotOn(frameM4l,LineColor(iLineColor),NormRange("largerange")) ;
bkg_qqzz->plotOn(frameM4lz,LineColor(iLineColor),NormRange("zoomrange")) ;
//second shape to compare with (if previous comparison code unceommented)
//bkg_qqzz_bkgd->plotOn(frameM4l,LineColor(1),NormRange("largerange")) ;
//bkg_qqzz_bkgd->plotOn(frameM4lz,LineColor(1),NormRange("zoomrange")) ;
double normalizationBackground_qqzz = bkg_qqzz->createIntegral( RooArgSet(*ZZMass), Range("fullrange") )->getVal();
cout << "Norm all = " << normalizationBackground_qqzz << endl;
frameM4l->GetXaxis()->SetTitle("m_{4l} [GeV]");
frameM4l->GetYaxis()->SetTitle("a.u.");
frameM4lz->GetXaxis()->SetTitle("m_{4l} [GeV]");
frameM4lz->GetYaxis()->SetTitle("a.u.");
char lname[192];
sprintf(lname,"qq #rightarrow ZZ #rightarrow %s", lab.c_str() );
char lname2[192];
sprintf(lname2,"Shape Model, %s", lab.c_str() );
// dummy!
TF1* dummyF = new TF1("dummyF","1",0.,1.);
TH1F* dummyH = new TH1F("dummyH","",1, 0.,1.);
dummyF->SetLineColor( iLineColor );
dummyF->SetLineWidth( 2 );
dummyH->SetLineColor( kBlue );
TLegend * box2 = new TLegend(0.4,0.70,0.80,0.90);
box2->SetFillColor(0);
box2->SetBorderSize(0);
box2->AddEntry(dummyH,"Simulation (POWHEG+Pythia) ","pe");
box2->AddEntry(dummyH,lname,"");
box2->AddEntry(dummyH,"","");
box2->AddEntry(dummyF,lname2,"l");
TPaveText *pt = new TPaveText(0.15,0.955,0.4,0.99,"NDC");
pt->SetFillColor(0);
pt->SetBorderSize(0);
pt->AddText("CMS Preliminary 2012");
TPaveText *pt2 = new TPaveText(0.84,0.955,0.99,0.99,"NDC");
pt2->SetFillColor(0);
pt2->SetBorderSize(0);
TString entag;entag.Form("#sqrt{s} = %d TeV",sqrts);
pt2->AddText(entag.Data());
TCanvas *c = new TCanvas("c","c",800,600);
c->cd();
frameM4l->Draw();
frameM4l->GetYaxis()->SetRangeUser(0,0.4);
if(channel == 3)frameM4l->GetYaxis()->SetRangeUser(0,0.7);
box2->Draw();
pt->Draw();
pt2->Draw();
TString outputPath = "bkgFigs";
outputPath = outputPath+ (long) sqrts + "TeV/";
TString outputName;
if(VBFtag<2) outputName = outputPath + "bkgqqzz_" + schannel + "_" + Form("%d",int(VBFtag));
if(VBFtag==2) outputName = outputPath + "bkgqqzz_" + schannel;
c->SaveAs(outputName + ".eps");
c->SaveAs(outputName + ".png");
TCanvas *c2 = new TCanvas("c2","c2",1000,500);
c2->Divide(2,1);
c2->cd(1);
frameM4l->Draw();
box2->Draw("same");
c2->cd(2);
frameM4lz->Draw();
box2->Draw("same");
if (VBFtag<2) outputName = outputPath + "bkgqqzz_" + schannel + "_z" + "_" + Form("%d",int(VBFtag));
if (VBFtag==2) outputName = outputPath + "bkgqqzz_" + schannel + "_z";
c2->SaveAs(outputName + ".eps");
c2->SaveAs(outputName + ".png");
/* TO make the ratio btw 2 shapes, if needed for compairson
TCanvas *c3 = new TCanvas("c3","c3",1000,500);
if(sqrts==7)
sprintf(outputName, "bkgFigs7TeV/bkgqqzz_%s_ratio.eps",schannel.c_str());
else if(sqrts==8)
sprintf(outputName, "bkgFigs8TeV/bkgqqzz_%s_ratio.eps",schannel.c_str());
const int nPoints = 501.;
double masses[nPoints] ;
int j=0;
for (int i=100; i<601; i++){
masses[j] = i;
j++;
}
cout<<j<<endl;
double effDiff[nPoints];
for (int i = 0; i < nPoints; i++){
ZZMass->setVal(masses[i]);
double eval = (bkg_qqzz_bkgd->getVal(otherASet)-bkg_qqzz->getVal(myASet))/(bkg_qqzz->getVal(myASet));
//cout<<bkg_qqzz_bkgd->getVal(otherASet)<<" "<<bkg_qqzz->getVal(myASet)<<" "<<eval<<endl;
effDiff[i]=eval;
}
TGraph* grEffDiff = new TGraph( nPoints, masses, effDiff );
grEffDiff->SetMarkerStyle(20);
grEffDiff->Draw("AL");
//c3->SaveAs(outputName);
*/
if (VBFtag<2) outputName = outputPath + "bkgqqzz_" + schannel + "_z" + "_" + Form("%d",int(VBFtag)) + ".root";
if (VBFtag==2) outputName = outputPath + "bkgqqzz_" + schannel + "_z" + ".root";
TFile* outF = new TFile(outputName,"RECREATE");
outF->cd();
c2->Write();
frameM4l->Write();
frameM4lz->Write();
outF->Close();
delete c;
delete c2;
}
//void RunToyScan5(TString fileName, double startVal, double stopVal, TString outFile) {
void frequentist(TString fileName) {
cout << "Starting frequentist " << time(NULL) << endl;
double startVal = 0;
double stopVal = 200;
TString outFile = "";
int nToys = 1 ;
int nscanpoints = 2 ;
/*
gROOT->LoadMacro("RooBetaPdf.cxx+") ;
gROOT->LoadMacro("RooRatio.cxx+") ;
gROOT->LoadMacro("RooPosDefCorrGauss.cxx+") ;
*/
// get relevant objects out of the "ws" file
TFile *file = TFile::Open(fileName);
if(!file){
cout <<"file not found" << endl;
return;
}
RooWorkspace* w = (RooWorkspace*) file->Get("workspace");
if(!w){
cout <<"workspace not found" << endl;
return;
}
ModelConfig* mc = (ModelConfig*) w->obj("S+B_model");
RooAbsData* data = w->data("data");
if( !data || !mc ){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
RooRealVar* myPOI = (RooRealVar*) mc->GetParametersOfInterest()->first();
myPOI->setRange(0, 1000.);
ModelConfig* bModel = (ModelConfig*) w->obj("B_model");
ModelConfig* sbModel = (ModelConfig*) w->obj("S+B_model");
ProfileLikelihoodTestStat profll(*sbModel->GetPdf());
profll.SetPrintLevel(2);
profll.SetOneSided(1);
TestStatistic * testStat = &profll;
HypoTestCalculatorGeneric * hc = 0;
hc = new FrequentistCalculator(*data, *bModel, *sbModel);
ToyMCSampler *toymcs = (ToyMCSampler*)hc->GetTestStatSampler();
toymcs->SetMaxToys(10000);
toymcs->SetNEventsPerToy(1);
toymcs->SetTestStatistic(testStat);
((FrequentistCalculator *)hc)->SetToys(nToys,nToys);
HypoTestInverter calc(*hc);
calc.SetConfidenceLevel(0.95);
calc.UseCLs(true);
//calc.SetVerbose(true);
calc.SetVerbose(2);
cout << "About to set fixed scan " << time(NULL) << endl;
calc.SetFixedScan(nscanpoints,startVal,stopVal);
cout << "About to do inverter " << time(NULL) << endl;
HypoTestInverterResult * res_toysCLs_calculator = calc.GetInterval();
cout << "CLs = " << res_toysCLs_calculator->UpperLimit()
<< " CLs_exp = " << res_toysCLs_calculator->GetExpectedUpperLimit(0)
<< " CLs_exp(-1s) = " << res_toysCLs_calculator->GetExpectedUpperLimit(-1)
<< " CLs_exp(+1s) = " << res_toysCLs_calculator->GetExpectedUpperLimit(1) << endl ;
/*
// dump results string to output file
ofstream outStream ;
outStream.open(outFile,ios::app) ;
outStream << "CLs = " << res_toysCLs_calculator->UpperLimit()
<< " CLs_exp = " << res_toysCLs_calculator->GetExpectedUpperLimit(0)
<< " CLs_exp(-1s) = " << res_toysCLs_calculator->GetExpectedUpperLimit(-1)
<< " CLs_exp(+1s) = " << res_toysCLs_calculator->GetExpectedUpperLimit(1) << endl ;
outStream.close() ;
*/
cout << "End of frequentist " << time(NULL) << endl;
return ;
}
void LeptonPreselectionCMG( PreselType type, RooWorkspace * w ) {
const Options & opt = Options::getInstance();
if (type == ELE)
cout << "Running Electron Preselection :" << endl;
else if (type == MU)
cout << "Running Muon Preselection :" << endl;
else if (type == EMU)
cout << "Running Electron-Muon Preselection() ..." << endl;
else if (type == PHOT)
cout << "Running Photon Preselection :" << endl;
string systVar;
try {
systVar = opt.checkStringOption("SYSTEMATIC_VAR");
} catch (const std::string & exc) {
cout << exc << endl;
}
if (systVar == "NONE")
systVar.clear();
#ifdef CMSSWENV
JetCorrectionUncertainty jecUnc("Summer13_V4_MC_Uncertainty_AK5PFchs.txt");
#endif
string inputDir = opt.checkStringOption("INPUT_DIR");
string outputDir = opt.checkStringOption("OUTPUT_DIR");
string sampleName = opt.checkStringOption("SAMPLE_NAME");
string inputFile = inputDir + '/' + sampleName + ".root";
cout << "\tInput file: " << inputFile << endl;
bool isSignal = opt.checkBoolOption("SIGNAL");
TGraph * higgsW = 0;
TGraph * higgsI = 0;
if (isSignal) {
double higgsM = opt.checkDoubleOption("HIGGS_MASS");
if (higgsM >= 400) {
string dirName = "H" + double2string(higgsM);
bool isVBF = opt.checkBoolOption("VBF");
string lshapeHistName = "cps";
string intHistName = "nominal";
if (systVar == "LSHAPE_UP") {
intHistName = "up";
} else if (systVar == "LSHAPE_DOWN") {
intHistName = "down";
}
if (isVBF) {
TFile weightFile("VBF_LineShapes.root");
higgsW = (TGraph *) ( (TDirectory *) weightFile.Get(dirName.c_str()))->Get( lshapeHistName.c_str() )->Clone();
} else {
TFile weightFile("GG_LineShapes.root");
higgsW = (TGraph *) ( (TDirectory *) weightFile.Get(dirName.c_str()))->Get( lshapeHistName.c_str() )->Clone();
TFile interfFile("newwgts_interf.root");
higgsI = (TGraph *) ( (TDirectory *) interfFile.Get(dirName.c_str()))->Get( intHistName.c_str() )->Clone();
}
}
}
TFile * file = new TFile( inputFile.c_str() );
if (!file->IsOpen())
throw string("ERROR: Can't open the file: " + inputFile + "!");
TDirectory * dir = (TDirectory *) file->Get("dataAnalyzer");
TH1D * nEvHisto = (TH1D *) dir->Get("cutflow");
TH1D * puHisto = (TH1D *) dir->Get("pileup");
TTree * tree = ( TTree * ) dir->Get( "data" );
Event ev( tree );
const int * runP = ev.getSVA<int>("run");
const int * lumiP = ev.getSVA<int>("lumi");
const int * eventP = ev.getSVA<int>("event");
const bool * trigBits = ev.getAVA<bool>("t_bits");
const int * trigPres = ev.getAVA<int>("t_prescale");
const float * metPtA = ev.getAVA<float>("met_pt");
const float * metPhiA = ev.getAVA<float>("met_phi");
const float * rhoP = ev.getSVA<float>("rho");
const float * rho25P = ev.getSVA<float>("rho25");
const int * nvtxP = ev.getSVA<int>("nvtx");
const int * niP = ev.getSVA<int>("ngenITpu");
#ifdef PRINTEVENTS
string eventFileName;
if (type == ELE)
eventFileName = "events_ele.txt";
else if (type == MU)
eventFileName = "events_mu.txt";
else if (type == EMU)
eventFileName = "events_emu.txt";
EventPrinter evPrint(ev, type, eventFileName);
evPrint.readInEvents("diff.txt");
evPrint.printElectrons();
evPrint.printMuons();
evPrint.printZboson();
evPrint.printJets();
evPrint.printHeader();
#endif
string outputFile = outputDir + '/' + sampleName;
if (systVar.size())
outputFile += ('_' + systVar);
if (type == ELE)
outputFile += "_elePresel.root";
else if (type == MU)
outputFile += "_muPresel.root";
else if (type == EMU)
outputFile += "_emuPresel.root";
else if (type == PHOT)
outputFile += "_phPresel.root";
cout << "\tOutput file: " << outputFile << endl;
TFile * out = new TFile( outputFile.c_str(), "recreate" );
TH1D * outNEvHisto = new TH1D("nevt", "nevt", 1, 0, 1);
outNEvHisto->SetBinContent(1, nEvHisto->GetBinContent(1));
outNEvHisto->Write("nevt");
TH1D * outPuHisto = new TH1D( *puHisto );
outPuHisto->Write("pileup");
std::vector< std::tuple<std::string, std::string> > eleVars;
eleVars.push_back( std::make_tuple("ln_px", "F") );
eleVars.push_back( std::make_tuple("ln_py", "F") );
eleVars.push_back( std::make_tuple("ln_pz", "F") );
eleVars.push_back( std::make_tuple("ln_en", "F") );
eleVars.push_back( std::make_tuple("ln_idbits", "I") );
eleVars.push_back( std::make_tuple("ln_d0", "F") );
eleVars.push_back( std::make_tuple("ln_dZ", "F") );
eleVars.push_back( std::make_tuple("ln_nhIso03", "F") );
eleVars.push_back( std::make_tuple("ln_gIso03", "F") );
eleVars.push_back( std::make_tuple("ln_chIso03", "F") );
eleVars.push_back( std::make_tuple("ln_trkLostInnerHits", "F") );
std::vector< std::tuple<std::string, std::string> > addEleVars;
addEleVars.push_back( std::make_tuple("egn_sceta", "F") );
addEleVars.push_back( std::make_tuple("egn_detain", "F") );
addEleVars.push_back( std::make_tuple("egn_dphiin", "F") );
addEleVars.push_back( std::make_tuple("egn_sihih", "F") );
addEleVars.push_back( std::make_tuple("egn_hoe", "F") );
addEleVars.push_back( std::make_tuple("egn_ooemoop", "F") );
addEleVars.push_back( std::make_tuple("egn_isConv", "B") );
std::vector< std::tuple<std::string, std::string> > muVars;
muVars.push_back( std::make_tuple("ln_px", "F") );
muVars.push_back( std::make_tuple("ln_py", "F") );
muVars.push_back( std::make_tuple("ln_pz", "F") );
muVars.push_back( std::make_tuple("ln_en", "F") );
muVars.push_back( std::make_tuple("ln_idbits", "I") );
muVars.push_back( std::make_tuple("ln_d0", "F") );
muVars.push_back( std::make_tuple("ln_dZ", "F") );
muVars.push_back( std::make_tuple("ln_nhIso04", "F") );
muVars.push_back( std::make_tuple("ln_gIso04", "F") );
muVars.push_back( std::make_tuple("ln_chIso04", "F") );
muVars.push_back( std::make_tuple("ln_puchIso04", "F") );
muVars.push_back( std::make_tuple("ln_trkchi2", "F") );
muVars.push_back( std::make_tuple("ln_trkValidPixelHits", "F") );
std::vector< std::tuple<std::string, std::string> > addMuVars;
addMuVars.push_back( std::make_tuple("mn_trkLayersWithMeasurement", "F") );
addMuVars.push_back( std::make_tuple("mn_pixelLayersWithMeasurement", "F") );
addMuVars.push_back( std::make_tuple("mn_innerTrackChi2", "F") );
addMuVars.push_back( std::make_tuple("mn_validMuonHits", "F") );
addMuVars.push_back( std::make_tuple("mn_nMatchedStations", "F") );
unsigned run;
unsigned lumi;
unsigned event;
double pfmet;
int nele;
int nmu;
int nsoftmu;
double l1pt;
double l1eta;
double l1phi;
double l2pt;
double l2eta;
double l2phi;
double zmass;
double zpt;
double zeta;
double mt;
int nsoftjet;
int nhardjet;
double maxJetBTag;
double minDeltaPhiJetMet;
double detajj;
double mjj;
int nvtx;
int ni;
int category;
double weight;
double hmass;
double hweight;
TTree * smallTree = new TTree("HZZ2l2nuAnalysis", "HZZ2l2nu Analysis Tree");
smallTree->Branch( "Run", &run, "Run/i" );
smallTree->Branch( "Lumi", &lumi, "Lumi/i" );
smallTree->Branch( "Event", &event, "Event/i" );
smallTree->Branch( "PFMET", &pfmet, "PFMET/D" );
smallTree->Branch( "NELE", &nele, "NELE/I" );
smallTree->Branch( "NMU", &nmu, "NMU/I" );
smallTree->Branch( "NSOFTMU", &nsoftmu, "NSOFTMU/I" );
smallTree->Branch( "L1PT", &l1pt, "L1PT/D" );
smallTree->Branch( "L1ETA", &l1eta, "L1ETA/D" );
smallTree->Branch( "L1PHI", &l1phi, "L1PHI/D" );
smallTree->Branch( "L2PT", &l2pt, "L2PT/D" );
smallTree->Branch( "L2ETA", &l2eta, "L2ETA/D" );
smallTree->Branch( "L2PHI", &l2phi, "L2PHI/D" );
smallTree->Branch( "ZMASS", &zmass, "ZMASS/D" );
smallTree->Branch( "ZPT", &zpt, "ZPT/D" );
smallTree->Branch( "ZETA", &zeta, "ZETA/D" );
smallTree->Branch( "MT", &mt, "MT/D" );
smallTree->Branch( "NSOFTJET", &nsoftjet, "NSOFTJET/I" );
smallTree->Branch( "NHARDJET", &nhardjet, "NHARDJET/I" );
smallTree->Branch( "MAXJETBTAG", &maxJetBTag, "MAXJETBTAG/D" );
smallTree->Branch( "MINDPJETMET", &minDeltaPhiJetMet, "MINDPJETMET/D" );
smallTree->Branch( "DETAJJ", &detajj, "DETAJJ/D" );
smallTree->Branch( "MJJ", &mjj, "MJJ/D" );
smallTree->Branch( "NVTX", &nvtx, "NVTX/I" );
smallTree->Branch( "nInter" , &ni, "nInter/I" );
smallTree->Branch( "CATEGORY", &category, "CATEGORY/I" );
smallTree->Branch( "Weight" , &weight, "Weight/D" );
smallTree->Branch( "HMASS", &hmass, "HMASS/D" );
smallTree->Branch( "HWEIGHT", &hweight, "HWEIGHT/D" );
bool isData = opt.checkBoolOption("DATA");
unsigned long nentries = tree->GetEntries();
RooDataSet * events = nullptr;
PhotonPrescale photonPrescales;
vector<int> thresholds;
if (type == PHOT) {
if (w == nullptr)
throw string("ERROR: No mass peak pdf!");
RooRealVar * zmass = w->var("mass");
zmass->setRange(76.0, 106.0);
RooAbsPdf * pdf = w->pdf("massPDF");
events = pdf->generate(*zmass, nentries);
photonPrescales.addTrigger("HLT_Photon36_R9Id90_HE10_Iso40_EBOnly", 36, 3, 7);
photonPrescales.addTrigger("HLT_Photon50_R9Id90_HE10_Iso40_EBOnly", 50, 5, 8);
photonPrescales.addTrigger("HLT_Photon75_R9Id90_HE10_Iso40_EBOnly", 75, 7, 9);
photonPrescales.addTrigger("HLT_Photon90_R9Id90_HE10_Iso40_EBOnly", 90, 10, 10);
}
TH1D ptSpectrum("ptSpectrum", "ptSpectrum", 200, 55, 755);
ptSpectrum.Sumw2();
unordered_set<EventAdr> eventsSet;
for ( unsigned long iEvent = 0; iEvent < nentries; iEvent++ ) {
// if (iEvent < 6060000)
// continue;
if ( iEvent % 10000 == 0) {
cout << string(40, '\b');
cout << setw(10) << iEvent << " / " << setw(10) << nentries << " done ..." << std::flush;
}
tree->GetEntry( iEvent );
run = -999;
lumi = -999;
event = -999;
pfmet = -999;
nele = -999;
nmu = -999;
nsoftmu = -999;
l1pt = -999;
l1eta = -999;
l1phi = -999;
l2pt = -999;
l2eta = -999;
l2phi = -999;
zmass = -999;
zpt = -999;
zeta = -999;
mt = -999;
nsoftjet = -999;
nhardjet = -999;
maxJetBTag = -999;
minDeltaPhiJetMet = -999;
detajj = -999;
mjj = -999;
nvtx = -999;
ni = -999;
weight = -999;
category = -1;
hmass = -999;
hweight = -999;
run = *runP;
lumi = *lumiP;
event = *eventP;
EventAdr tmp(run, lumi, event);
if (eventsSet.find( tmp ) != eventsSet.end()) {
continue;
}
eventsSet.insert( tmp );
if (type == ELE && isData) {
if (trigBits[0] != 1 || trigPres[0] != 1)
continue;
}
if (type == MU && isData) {
if ( (trigBits[2] != 1 || trigPres[2] != 1)
&& (trigBits[3] != 1 || trigPres[3] != 1)
&& (trigBits[6] != 1 || trigPres[6] != 1)
)
continue;
}
if (type == EMU && isData) {
if ( (trigBits[4] != 1 || trigPres[4] != 1)
&& (trigBits[5] != 1 || trigPres[5] != 1)
)
continue;
}
vector<Electron> electrons = buildLeptonCollection<Electron, 11>(ev, eleVars, addEleVars);
vector<Muon> muons = buildLeptonCollection<Muon, 13>(ev, muVars, addMuVars);
float rho = *rhoP;
float rho25 = *rho25P;
vector<Electron> looseElectrons;
vector<Electron> selectedElectrons;
for (unsigned j = 0; j < electrons.size(); ++j) {
try {
TLorentzVector lv = electrons[j].lorentzVector();
if (
lv.Pt() > 10 &&
fabs(lv.Eta()) < 2.5 &&
!electrons[j].isInCrack() &&
electrons[j].passesVetoID() &&
electrons[j].isPFIsolatedLoose(rho25)
) {
looseElectrons.push_back(electrons[j]);
}
if (
lv.Pt() > 20 &&
fabs(lv.Eta()) < 2.5 &&
!electrons[j].isInCrack() &&
electrons[j].passesMediumID() &&
electrons[j].isPFIsolatedMedium(rho25)
) {
selectedElectrons.push_back(electrons[j]);
}
} catch (const string & exc) {
cout << exc << endl;
cout << "run = " << run << endl;
cout << "lumi = " << lumi << endl;
cout << "event = " << event << endl;
}
}
vector<Muon> looseMuons;
vector<Muon> softMuons;
vector<Muon> selectedMuons;
for (unsigned j = 0; j < muons.size(); ++j) {
TLorentzVector lv = muons[j].lorentzVector();
if (
lv.Pt() > 10 &&
fabs(lv.Eta()) < 2.4 &&
muons[j].isLooseMuon() &&
muons[j].isPFIsolatedLoose()
) {
looseMuons.push_back(muons[j]);
} else if (
lv.Pt() > 3 &&
fabs(lv.Eta()) < 2.4 &&
muons[j].isSoftMuon()
) {
softMuons.push_back(muons[j]);
}
if (
lv.Pt() > 20 &&
fabs(lv.Eta()) < 2.4 &&
muons[j].isTightMuon() &&
muons[j].isPFIsolatedTight()
) {
selectedMuons.push_back(muons[j]);
}
}
vector<Lepton> looseLeptons;
for (unsigned i = 0; i < looseElectrons.size(); ++i)
looseLeptons.push_back(looseElectrons[i]);
for (unsigned i = 0; i < looseMuons.size(); ++i)
looseLeptons.push_back(looseMuons[i]);
for (unsigned i = 0; i < softMuons.size(); ++i)
looseLeptons.push_back(softMuons[i]);
#ifdef PRINTEVENTS
evPrint.setElectronCollection(selectedElectrons);
evPrint.setMuonCollection(selectedMuons);
#endif
vector<Photon> photons = selectPhotonsCMG( ev );
vector<Photon> selectedPhotons;
for (unsigned i = 0; i < photons.size(); ++i) {
if (photons[i].isSelected(rho) && photons[i].lorentzVector().Pt() > 55)
selectedPhotons.push_back( photons[i] );
}
if (type == PHOT) {
vector<Electron> tmpElectrons;
for (unsigned i = 0; i < selectedPhotons.size(); ++i) {
TLorentzVector phVec = selectedPhotons[i].lorentzVector();
for (unsigned j = 0; j < looseElectrons.size(); ++j) {
TLorentzVector elVec = looseElectrons[j].lorentzVector();
double dR = deltaR(phVec.Eta(), phVec.Phi(), elVec.Eta(), elVec.Phi());
if ( dR > 0.05 )
tmpElectrons.push_back( looseElectrons[j] );
}
}
looseElectrons = tmpElectrons;
}
string leptonsType;
Lepton * selectedLeptons[2] = {0};
if (type == ELE) {
if (selectedElectrons.size() < 2) {
continue;
} else {
selectedLeptons[0] = &selectedElectrons[0];
selectedLeptons[1] = &selectedElectrons[1];
}
} else if (type == MU) {
if (selectedMuons.size() < 2) {
continue;
} else {
selectedLeptons[0] = &selectedMuons[0];
selectedLeptons[1] = &selectedMuons[1];
}
} else if (type == EMU) {
if (selectedElectrons.size() < 1 || selectedMuons.size() < 1) {
continue;
} else {
selectedLeptons[0] = &selectedElectrons[0];
selectedLeptons[1] = &selectedMuons[0];
}
} else if (type == PHOT) {
if (selectedPhotons.size() != 1) {
continue;
}
}
nele = looseElectrons.size();
nmu = looseMuons.size();
nsoftmu = softMuons.size();
TLorentzVector Zcand;
if (type == ELE || type == MU || type == EMU) {
TLorentzVector lep1 = selectedLeptons[0]->lorentzVector();
TLorentzVector lep2 = selectedLeptons[1]->lorentzVector();
if (lep2.Pt() > lep1.Pt() && type != EMU) {
TLorentzVector temp = lep1;
lep1 = lep2;
lep2 = temp;
}
l1pt = lep1.Pt();
l1eta = lep1.Eta();
l1phi = lep1.Phi();
l2pt = lep2.Pt();
l2eta = lep2.Eta();
l2phi = lep2.Phi();
Zcand = lep1 + lep2;
zmass = Zcand.M();
} else if (type == PHOT) {
Zcand = selectedPhotons[0].lorentzVector();
zmass = events->get(iEvent)->getRealValue("mass");
}
zpt = Zcand.Pt();
zeta = Zcand.Eta();
if (type == PHOT) {
unsigned idx = photonPrescales.getIndex(zpt);
if (trigBits[idx])
weight = trigPres[idx];
else
continue;
ptSpectrum.Fill(zpt, weight);
}
TLorentzVector met;
met.SetPtEtaPhiM(metPtA[0], 0.0, metPhiA[0], 0.0);
TLorentzVector clusteredFlux;
unsigned mode = 0;
if (systVar == "JES_UP")
mode = 1;
else if (systVar == "JES_DOWN")
mode = 2;
TLorentzVector jecCorr;
#ifdef CMSSWENV
vector<Jet> jetsAll = selectJetsCMG( ev, looseLeptons, jecUnc, &jecCorr, mode );
#else
vector<Jet> jetsAll = selectJetsCMG( ev, looseLeptons, &jecCorr, mode );
#endif
met -= jecCorr;
mode = 0;
if (systVar == "JER_UP")
mode = 1;
else if (systVar == "JER_DOWN")
mode = 2;
TLorentzVector smearCorr = smearJets( jetsAll, mode );
if (isData && smearCorr != TLorentzVector())
throw std::string("Jet smearing corrections different from zero in DATA!");
met -= smearCorr;
vector<Jet> selectedJets;
for (unsigned i = 0; i < jetsAll.size(); ++i) {
if (
jetsAll[i].lorentzVector().Pt() > 10
&& fabs(jetsAll[i].lorentzVector().Eta()) < 4.7
&& jetsAll[i].passesPUID() &&
jetsAll[i].passesPFLooseID()
)
selectedJets.push_back( jetsAll[i] );
}
if (type == PHOT) {
vector<Jet> tmpJets;
for (unsigned i = 0; i < selectedPhotons.size(); ++i) {
TLorentzVector phVec = selectedPhotons[i].lorentzVector();
for (unsigned j = 0; j < selectedJets.size(); ++j) {
TLorentzVector jVec = selectedJets[j].lorentzVector();
double dR = deltaR(phVec.Eta(), phVec.Phi(), jVec.Eta(), jVec.Phi());
if ( dR > 0.4 )
tmpJets.push_back( selectedJets[j] );
}
}
selectedJets = tmpJets;
}
if (systVar == "UMET_UP" || systVar == "UMET_DOWN") {
for (unsigned i = 0; i < jetsAll.size(); ++i)
clusteredFlux += jetsAll[i].lorentzVector();
for (unsigned i = 0; i < looseElectrons.size(); ++i)
clusteredFlux += looseElectrons[i].lorentzVector();
for (unsigned i = 0; i < looseMuons.size(); ++i)
clusteredFlux += looseMuons[i].lorentzVector();
TLorentzVector unclusteredFlux = -(met + clusteredFlux);
if (systVar == "UMET_UP")
unclusteredFlux *= 1.1;
else
unclusteredFlux *= 0.9;
met = -(clusteredFlux + unclusteredFlux);
}
if (systVar == "LES_UP" || systVar == "LES_DOWN") {
TLorentzVector diff;
double sign = 1.0;
if (systVar == "LES_DOWN")
sign = -1.0;
for (unsigned i = 0; i < looseElectrons.size(); ++i) {
TLorentzVector tempEle = looseElectrons[i].lorentzVector();
if (looseElectrons[i].isEB())
diff += sign * 0.02 * tempEle;
else
diff += sign * 0.05 * tempEle;
}
for (unsigned i = 0; i < looseMuons.size(); ++i)
diff += sign * 0.01 * looseMuons[i].lorentzVector();
met -= diff;
}
pfmet = met.Pt();
double px = met.Px() + Zcand.Px();
double py = met.Py() + Zcand.Py();
double pt2 = px * px + py * py;
double e = sqrt(zpt * zpt + zmass * zmass) + sqrt(pfmet * pfmet + zmass * zmass);
double mt2 = e * e - pt2;
mt = (mt2 > 0) ? sqrt(mt2) : 0;
vector<Jet> hardjets;
vector<Jet> softjets;
maxJetBTag = -999;
minDeltaPhiJetMet = 999;
for ( unsigned j = 0; j < selectedJets.size(); ++j ) {
TLorentzVector jet = selectedJets[j].lorentzVector();
if ( jet.Pt() > 30 ) {
hardjets.push_back( selectedJets[j] );
}
if ( jet.Pt() > 15 )
softjets.push_back( selectedJets[j] );
}
nhardjet = hardjets.size();
nsoftjet = softjets.size();
// if ( type == PHOT && nsoftjet == 0 )
// continue;
if (nhardjet > 1) {
sort(hardjets.begin(), hardjets.end(), [](const Jet & a, const Jet & b) {
return a.lorentzVector().Pt() > b.lorentzVector().Pt();
});
TLorentzVector jet1 = hardjets[0].lorentzVector();
TLorentzVector jet2 = hardjets[1].lorentzVector();
const double maxEta = max( jet1.Eta(), jet2.Eta() );
const double minEta = min( jet1.Eta(), jet2.Eta() );
bool passCJV = true;
for (unsigned j = 2; j < hardjets.size(); ++j) {
double tmpEta = hardjets[j].lorentzVector().Eta();
if ( tmpEta > minEta && tmpEta < maxEta )
passCJV = false;
}
const double tmpDelEta = std::fabs(jet2.Eta() - jet1.Eta());
TLorentzVector diJetSystem = jet1 + jet2;
const double tmpMass = diJetSystem.M();
if ( type == PHOT) {
if (passCJV && tmpDelEta > 4.0 && tmpMass > 500 && zeta > minEta && maxEta > zeta) {
detajj = tmpDelEta;
mjj = tmpMass;
}
} else {
if (passCJV && tmpDelEta > 4.0 && tmpMass > 500 && l1eta > minEta && l2eta > minEta && maxEta > l1eta && maxEta > l2eta) {
detajj = tmpDelEta;
mjj = tmpMass;
}
}
}
category = evCategory(nhardjet, nsoftjet, detajj, mjj, type == PHOT);
minDeltaPhiJetMet = 10;
for ( unsigned j = 0; j < hardjets.size(); ++j ) {
TLorentzVector jet = hardjets[j].lorentzVector();
if ( hardjets[j].getVarF("jn_jp") > maxJetBTag && fabs(jet.Eta()) < 2.5 )
maxJetBTag = hardjets[j].getVarF("jn_jp");
double tempDelPhiJetMet = deltaPhi(met.Phi(), jet.Phi());
if ( tempDelPhiJetMet < minDeltaPhiJetMet )
minDeltaPhiJetMet = tempDelPhiJetMet;
}
nvtx = *nvtxP;
if (isData)
ni = -1;
else
ni = *niP;
if (isSignal) {
const int nMC = ev.getSVV<int>("mcn");
const int * mcID = ev.getAVA<int>("mc_id");
int hIdx = 0;
for (; hIdx < nMC; ++hIdx)
if (fabs(mcID[hIdx]) == 25)
break;
if (hIdx == nMC)
throw string("ERROR: Higgs not found in signal sample!");
float Hpx = ev.getAVV<float>("mc_px", hIdx);
float Hpy = ev.getAVV<float>("mc_py", hIdx);
float Hpz = ev.getAVV<float>("mc_pz", hIdx);
float Hen = ev.getAVV<float>("mc_en", hIdx);
TLorentzVector higgs;
higgs.SetPxPyPzE( Hpx, Hpy, Hpz, Hen );
hmass = higgs.M();
if (higgsW) {
hweight = higgsW->Eval(hmass);
if (higgsI)
hweight *= higgsI->Eval(hmass);
} else
hweight = 1;
}
if ( opt.checkBoolOption("ADDITIONAL_LEPTON_VETO") && (type == ELE || type == MU || type == EMU) && ((nele + nmu + nsoftmu) > 2) )
continue;
if ( opt.checkBoolOption("ADDITIONAL_LEPTON_VETO") && (type == PHOT) && ((nele + nmu + nsoftmu) > 0) )
continue;
if ( opt.checkBoolOption("ZPT_CUT") && zpt < 55 )
continue;
// for different background estimation methods different window should be applied:
// * sample for photons should have 76.0 < zmass < 106.0
// * sample for non-resonant background should not have this cut applied
if ( opt.checkBoolOption("TIGHT_ZMASS_CUT") && (type == ELE || type == MU) && (zmass < 76.0 || zmass > 106.0))
continue;
if ( opt.checkBoolOption("WIDE_ZMASS_CUT") && (type == ELE || type == MU) && (zmass < 76.0 || zmass > 106.0))
continue;
if ( opt.checkBoolOption("BTAG_CUT") && ( maxJetBTag > 0.264) )
continue;
if ( opt.checkBoolOption("DPHI_CUT") && ( minDeltaPhiJetMet < 0.5) )
continue;
#ifdef PRINTEVENTS
evPrint.setJetCollection(hardjets);
evPrint.setMET(met);
evPrint.setMT(mt);
string channelType;
if (type == ELE)
channelType = "ee";
else if (type == MU)
channelType = "mumu";
else if (type == EMU)
channelType = "emu";
if (category == 1)
channelType += "eq0jets";
else if (category == 2)
channelType += "geq1jets";
else
channelType += "vbf";
evPrint.setChannel(channelType);
unsigned bits = 0;
bits |= (0x7);
bits |= ((zmass > 76.0 && zmass < 106.0) << 3);
bits |= ((zpt > 55) << 4);
bits |= (((nele + nmu + nsoftmu) == 2) << 5);
bits |= ((maxJetBTag < 0.275) << 6);
bits |= ((minDeltaPhiJetMet > 0.5) << 7);
evPrint.setBits(bits);
evPrint.print();
#endif
smallTree->Fill();
}
cout << endl;
TCanvas canv("canv", "canv", 800, 600);
//effNum.Sumw2();
//effDen.Sumw2();
//effNum.Divide(&effDen);
//effNum.Draw();
canv.SetGridy();
canv.SetGridx();
//canv.SaveAs("triggEff.ps");
//canv.Clear();
ptSpectrum.SetMarkerStyle(20);
ptSpectrum.SetMarkerSize(0.5);
ptSpectrum.Draw("P0E");
//ptSpectrum.Draw("COLZ");
canv.SetLogy();
canv.SaveAs("ptSpectrum.ps");
delete file;
smallTree->Write("", TObject::kOverwrite);
delete smallTree;
delete out;
}
TH1D* runSig(RooWorkspace* ws,
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData",
const char* asimov1DataName = "asimovData_1",
const char* conditional1Snapshot = "conditionalGlobs_1",
const char* nominalSnapshot = "nominalGlobs")
{
string defaultMinimizer = "Minuit"; // or "Minuit"
int defaultStrategy = 2; // Minimization strategy. 0-2. 0 = fastest, least robust. 2 = slowest, most robust
double mu_profile_value = 1; // mu value to profile the obs data at wbefore generating the expected
bool doUncap = 1; // uncap p0
bool doInj = 0; // setup the poi for injection study (zero is faster if you're not)
bool doMedian = 1; // compute median significance
bool isBlind = 0; // Dont look at observed data
bool doConditional = !isBlind; // do conditional expected data
bool doObs = !isBlind; // compute observed significance
TStopwatch timer;
timer.Start();
if (!ws)
{
cout << "ERROR::Workspace is NULL!" << endl;
return NULL;
}
ModelConfig* mc = (ModelConfig*)ws->obj(modelConfigName);
if (!mc)
{
cout << "ERROR::ModelConfig: " << modelConfigName << " doesn't exist!" << endl;
return NULL;
}
RooDataSet* data = (RooDataSet*)ws->data(dataName);
if (!data)
{
cout << "ERROR::Dataset: " << dataName << " doesn't exist!" << endl;
return NULL;
}
mc->GetNuisanceParameters()->Print("v");
//RooNLLVar::SetIgnoreZeroEntries(1);
ROOT::Math::MinimizerOptions::SetDefaultMinimizer(defaultMinimizer.c_str());
ROOT::Math::MinimizerOptions::SetDefaultStrategy(defaultStrategy);
ROOT::Math::MinimizerOptions::SetDefaultPrintLevel(-1);
// cout << "Setting max function calls" << endl;
//ROOT::Math::MinimizerOptions::SetDefaultMaxFunctionCalls(20000);
//RooMinimizer::SetMaxFunctionCalls(10000);
ws->loadSnapshot("conditionalNuis_0");
RooArgSet nuis(*mc->GetNuisanceParameters());
RooRealVar* mu = (RooRealVar*)mc->GetParametersOfInterest()->first();
RooAbsPdf* pdf_temp = mc->GetPdf();
string condSnapshot(conditional1Snapshot);
RooArgSet nuis_tmp2 = *mc->GetNuisanceParameters();
RooNLLVar* obs_nll = doObs ? (RooNLLVar*)pdf_temp->createNLL(*data, Constrain(nuis_tmp2)) : NULL;
RooDataSet* asimovData1 = (RooDataSet*)ws->data(asimov1DataName);
if (!asimovData1)
{
cout << "Asimov data doesn't exist! Please, allow me to build one for you..." << endl;
string mu_str, mu_prof_str;
asimovData1 = makeAsimovData(mc, doConditional, ws, obs_nll, 1, &mu_str, &mu_prof_str, mu_profile_value, true);
condSnapshot="conditionalGlobs"+mu_prof_str;
//makeAsimovData(mc, true, ws, mc->GetPdf(), data, 0);
//ws->Print();
//asimovData1 = (RooDataSet*)ws->data("asimovData_1");
}
if (!doUncap) mu->setRange(0, 40);
else mu->setRange(-40, 40);
RooAbsPdf* pdf = mc->GetPdf();
RooArgSet nuis_tmp1 = *mc->GetNuisanceParameters();
RooNLLVar* asimov_nll = (RooNLLVar*)pdf->createNLL(*asimovData1, Constrain(nuis_tmp1));
//do asimov
mu->setVal(1);
mu->setConstant(0);
if (!doInj) mu->setConstant(1);
int status,sign;
double med_sig=0,obs_sig=0,asimov_q0=0,obs_q0=0;
if (doMedian)
{
ws->loadSnapshot(condSnapshot.c_str());
if (doInj) ws->loadSnapshot("conditionalNuis_inj");
else ws->loadSnapshot("conditionalNuis_1");
mc->GetGlobalObservables()->Print("v");
mu->setVal(0);
mu->setConstant(1);
status = minimize(asimov_nll, ws);
if (status >= 0) cout << "Success!" << endl;
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov_nll_cond = asimov_nll->getVal();
mu->setVal(1);
if (doInj) ws->loadSnapshot("conditionalNuis_inj");
else ws->loadSnapshot("conditionalNuis_1");
if (doInj) mu->setConstant(0);
status = minimize(asimov_nll, ws);
if (status >= 0) cout << "Success!" << endl;
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov_nll_min = asimov_nll->getVal();
asimov_q0 = 2*(asimov_nll_cond - asimov_nll_min);
if (doUncap && mu->getVal() < 0) asimov_q0 = -asimov_q0;
sign = int(asimov_q0 != 0 ? asimov_q0/fabs(asimov_q0) : 0);
med_sig = sign*sqrt(fabs(asimov_q0));
ws->loadSnapshot(nominalSnapshot);
}
if (doObs)
{
ws->loadSnapshot("conditionalNuis_0");
mu->setVal(0);
mu->setConstant(1);
status = minimize(obs_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(obs_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double obs_nll_cond = obs_nll->getVal();
//ws->loadSnapshot("ucmles");
mu->setConstant(0);
status = minimize(obs_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(obs_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double obs_nll_min = obs_nll->getVal();
obs_q0 = 2*(obs_nll_cond - obs_nll_min);
if (doUncap && mu->getVal() < 0) obs_q0 = -obs_q0;
sign = int(obs_q0 == 0 ? 0 : obs_q0 / fabs(obs_q0));
if (!doUncap && ((obs_q0 < 0 && obs_q0 > -0.1) || mu->getVal() < 0.001)) obs_sig = 0;
else obs_sig = sign*sqrt(fabs(obs_q0));
}
cout << "obs: " << obs_sig << endl;
cout << "Observed significance: " << obs_sig << endl;
if (med_sig)
{
cout << "Median test stat val: " << asimov_q0 << endl;
cout << "Median significance: " << med_sig << endl;
}
TH1D* h_hypo = new TH1D("hypo","hypo",2,0,2);
h_hypo->SetBinContent(1, obs_sig);
h_hypo->SetBinContent(2, med_sig);
timer.Stop();
timer.Print();
return h_hypo;
}
void eregtesting_13TeV_Eta(bool dobarrel=true, bool doele=false,int gammaID=0) {
//output dir
TString EEorEB = "EE";
if(dobarrel)
{
EEorEB = "EB";
}
TString gammaDir = "bothGammas";
if(gammaID==1)
{
gammaDir = "gamma1";
}
else if(gammaID==2)
{
gammaDir = "gamma2";
}
TString dirname = TString::Format("ereg_test_plots_Eta/%s_%s",gammaDir.Data(),EEorEB.Data());
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
TString infile = TString::Format("../../ereg_ws_Eta/%s/%s",gammaDir.Data(),fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *meantgt = static_cast<RooGBRTargetFlex*>(ws->arg("sigmeant"));
RooRealVar *tgtvar = ws->var("tgtvar");
RooArgList vars;
vars.add(meantgt->FuncVars());
vars.add(*tgtvar);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
//TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
//TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiPion_FlatPt-1To15/Gun_FlatPt1to15_MultiPion_withPhotonPtFilter_pythia8/photons_0_half2.root");
//TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiEta_FlatPt-1To15/Gun_FlatPt1to15_MultiEta_withPhotonPtFilter_pythia8/photons_22Aug2017_V3_half2.root");
TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiEta_FlatPt-1To15/Gun_FlatPt1to15_MultiEtaToGG_withPhotonPtFilter_pythia8/photons_20171008_half2.root");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
//selection cuts for testing
//TCut selcut = "(STr2_enG1_true/cosh(STr2_Eta_1)>1.0) && (STr2_S4S9_1>0.75)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_enG_true/STr2_enG_rec)<3.0 && STr2_EOverEOther < 10.0 && STr2_EOverEOther > 0.1";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_mPi0_nocor>0.1)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2)";
TCut selcut = "";
if(dobarrel) selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.2) && (STr2_mPi0_nocor < 1.0) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)<1.479 && (!STr2_fromPi0)";
//if(dobarrel) selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)<1.479";
else selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.2) && (STr2_mPi0_nocor < 1.0) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)>1.479 && (!STr2_fromPi0)";
//else selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)>1.479";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_iEta_on2520==0 || STr2_iPhi_on20==0) ";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)>60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
/*
TCut selcut;
if (dobarrel)
selcut = "ph.genpt>25. && ph.isbarrel && ph.ispromptgen";
else
selcut = "ph.genpt>25. && !ph.isbarrel && ph.ispromptgen";
*/
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(Entry$%10==0)";
TCut prescale10alt = "(Entry$%10==1)";
TCut prescale25 = "(Entry$%25==0)";
TCut prescale100 = "(Entry$%100==0)";
TCut prescale1000 = "(Entry$%1000==0)";
TCut evenevents = "(Entry$%2==0)";
TCut oddevents = "(Entry$%2==1)";
TCut prescale100alt = "(Entry$%100==1)";
TCut prescale1000alt = "(Entry$%1000==1)";
TCut prescale50alt = "(Entry$%50==1)";
TCut Events3_4 = "(Entry$%4==3)";
TCut Events1_4 = "(Entry$%4==1)";
TCut Events2_4 = "(Entry$%4==2)";
TCut Events0_4 = "(Entry$%4==0)";
TCut Events01_4 = "(Entry$%4<2)";
TCut Events23_4 = "(Entry$%4>1)";
TCut EventsTest = "(Entry$%2==1)";
//weightvar.SetTitle(EventsTest*selcut);
weightvar.SetTitle(selcut);
/*
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
*/
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
if (doele)
weightvar.SetTitle(prescale1000alt*selcut);
else
weightvar.SetTitle(prescale10alt*selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
//input variable corresponding to sceta
RooRealVar *scEraw = ws->var("var_0");
scEraw->setRange(1.,2.);
scEraw->setBins(100);
// RooRealVar *scetavar = ws->var("var_1");
// RooRealVar *scphivar = ws->var("var_2");
//regressed output functions
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
// RooAbsReal *sigalphalim = ws->function("sigalphalim");
//RooAbsReal *sigalpha2lim = ws->function("sigalpha2lim");
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
// RooRealVar *alphavar = (RooRealVar*)hdataclone->addColumn(*sigalphalim);
// RooRealVar *alpha2var = (RooRealVar*)hdataclone->addColumn(*sigalpha2lim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.6,2.0,100);
hdata->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
craw->SaveAs("RawE.pdf");
craw->SaveAs("RawE.png");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.pdf");
craw->SaveAs("RawElog.png");
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.pdf");
cmean->SaveAs("mean.png");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.pdf");
cwidth->SaveAs("width.png");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.pdf");
cn->SaveAs("n.png");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.pdf");
cn2->SaveAs("n2.png");
/*
TCanvas *calpha = new TCanvas;
RooPlot *plotalpha = alphavar->frame(0.,5.,200);
hdataclone->plotOn(plotalpha);
plotalpha->Draw();
calpha->SaveAs("alpha.pdf");
calpha->SaveAs("alpha.png");
TCanvas *calpha2 = new TCanvas;
RooPlot *plotalpha2 = alpha2var->frame(0.,5.,200);
hdataclone->plotOn(plotalpha2);
plotalpha2->Draw();
calpha2->SaveAs("alpha2.pdf");
calpha2->SaveAs("alpha2.png");
*/
/*
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.pdf");
ceta->SaveAs("eta.png");
*/
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw;// = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor;// = hdata->createHistogram("hecor",*ecorvar);
if (EEorEB == "EB")
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.0));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(800,0.,2.0));
}
else
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(200,0.,2.));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(200,0.,2.));
}
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
heraw->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
hecor->GetXaxis()->SetRangeUser(0.0,1.5);
heraw->GetXaxis()->SetRangeUser(0.0,1.5);
/*if(EEorEB == "EE")
{
heraw->GetYaxis()->SetRangeUser(10.0,200.0);
hecor->GetYaxis()->SetRangeUser(10.0,200.0);
}
*/
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
double effsigma_cor, effsigma_raw, fwhm_cor, fwhm_raw;
if(EEorEB == "EB")
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(800,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(800,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
else
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
TCanvas *cresponse = new TCanvas;
gStyle->SetOptStat(0);
gStyle->SetPalette(107);
hecor->SetTitle("");
heraw->SetTitle("");
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
//show errSigma in the plot
TLegend *leg = new TLegend(0.1, 0.75, 0.7, 0.9);
leg->AddEntry(hecor,Form("E_{cor}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_cor, fwhm_cor),"l");
leg->AddEntry(heraw,Form("E_{raw}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_raw, fwhm_raw),"l");
leg->SetFillStyle(0);
leg->SetBorderSize(0);
// leg->SetTextColor(kRed);
leg->Draw();
cresponse->SaveAs("response.pdf");
cresponse->SaveAs("response.png");
cresponse->SetLogy();
cresponse->SaveAs("responselog.pdf");
cresponse->SaveAs("responselog.png");
// draw CCs vs eta and phi
/*
TCanvas *c_eta = new TCanvas;
TH1 *h_eta = hdata->createHistogram("h_eta",*scetavar,Binning(100,-3.2,3.2));
h_eta->Draw("HIST");
c_eta->SaveAs("heta.pdf");
c_eta->SaveAs("heta.png");
TCanvas *c_phi = new TCanvas;
TH1 *h_phi = hdata->createHistogram("h_phi",*scphivar,Binning(100,-3.2,3.2));
h_phi->Draw("HIST");
c_phi->SaveAs("hphi.pdf");
c_phi->SaveAs("hphi.png");
*/
RooRealVar *scetaiXvar = ws->var("var_4");
RooRealVar *scphiiYvar = ws->var("var_5");
if(EEorEB=="EB")
{
scetaiXvar->setRange(-90,90);
scetaiXvar->setBins(180);
scphiiYvar->setRange(0,360);
scphiiYvar->setBins(360);
}
else
{
scetaiXvar->setRange(0,50);
scetaiXvar->setBins(50);
scphiiYvar->setRange(0,50);
scphiiYvar->setBins(50);
}
ecorvar->setRange(0.5,1.5);
ecorvar->setBins(800);
rawvar->setRange(0.5,1.5);
rawvar->setBins(800);
TCanvas *c_cor_eta = new TCanvas;
TH3F *h3_CC_eta_phi = (TH3F*) hdata->createHistogram("var_5,var_4,ecor",(EEorEB=="EB") ? 170 : 100, (EEorEB=="EB") ? 360 : 100,25);
TProfile2D *h_CC_eta_phi = h3_CC_eta_phi->Project3DProfile();
h_CC_eta_phi->SetTitle("E_{cor}/E_{true}");
if(EEorEB=="EB")
{
h_CC_eta_phi->GetXaxis()->SetTitle("i#eta");
h_CC_eta_phi->GetYaxis()->SetTitle("i#phi");
h_CC_eta_phi->GetXaxis()->SetRangeUser(-85,85);
h_CC_eta_phi->GetYaxis()->SetRangeUser(0,360);
}
else
{
h_CC_eta_phi->GetXaxis()->SetTitle("iX");
h_CC_eta_phi->GetYaxis()->SetTitle("iY");
}
h_CC_eta_phi->SetMinimum(0.5);
h_CC_eta_phi->SetMaximum(1.5);
h_CC_eta_phi->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta_phi.pdf");
c_cor_eta->SaveAs("cor_vs_eta_phi.png");
TH2F *h_CC_eta = hdata->createHistogram(*scetaiXvar, *ecorvar, "","cor_vs_eta");
if(EEorEB=="EB")
{
h_CC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetXaxis()->SetTitle("iX");
}
h_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_eta->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta.pdf");
c_cor_eta->SaveAs("cor_vs_eta.png");
TCanvas *c_cor_scEraw = new TCanvas;
TH2F *h_CC_scEraw = hdata->createHistogram(*scEraw, *ecorvar, "","cor_vs_scEraw");
h_CC_scEraw->GetXaxis()->SetTitle("E_{raw}");
h_CC_scEraw->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_scEraw->Draw("COLZ");
c_cor_scEraw->SaveAs("cor_vs_scEraw.pdf");
c_cor_scEraw->SaveAs("cor_vs_scEraw.png");
TCanvas *c_raw_scEraw = new TCanvas;
TH2F *h_RC_scEraw = hdata->createHistogram(*scEraw, *rawvar, "","raw_vs_scEraw");
h_RC_scEraw->GetXaxis()->SetTitle("E_{raw}");
h_RC_scEraw->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_scEraw->Draw("COLZ");
c_raw_scEraw->SaveAs("raw_vs_scEraw.pdf");
c_raw_scEraw->SaveAs("raw_vs_scEraw.png");
TCanvas *c_cor_phi = new TCanvas;
TH2F *h_CC_phi = hdata->createHistogram(*scphiiYvar, *ecorvar, "","cor_vs_phi");
if(EEorEB=="EB")
{
h_CC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetXaxis()->SetTitle("iY");
}
h_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_phi->Draw("COLZ");
c_cor_phi->SaveAs("cor_vs_phi.pdf");
c_cor_phi->SaveAs("cor_vs_phi.png");
TCanvas *c_raw_eta = new TCanvas;
TH3F *h3_RC_eta_phi = (TH3F*) hdata->createHistogram("var_5,var_4,raw",(EEorEB=="EB") ? 170 : 100, (EEorEB=="EB") ? 360 : 100,25);
TProfile2D *h_RC_eta_phi = h3_RC_eta_phi->Project3DProfile();
h_RC_eta_phi->SetTitle("E_{raw}/E_{true}");
if(EEorEB=="EB")
{
h_RC_eta_phi->GetXaxis()->SetTitle("i#eta");
h_RC_eta_phi->GetYaxis()->SetTitle("i#phi");
h_RC_eta_phi->GetXaxis()->SetRangeUser(-85,85);
h_RC_eta_phi->GetYaxis()->SetRangeUser(0,360);
}
else
{
h_RC_eta_phi->GetXaxis()->SetTitle("iX");
h_RC_eta_phi->GetYaxis()->SetTitle("iY");
}
h_RC_eta_phi->SetMinimum(0.5);
h_RC_eta_phi->SetMaximum(1.5);
h_RC_eta_phi->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta_phi.pdf");
c_raw_eta->SaveAs("raw_vs_eta_phi.png");
TH2F *h_RC_eta = hdata->createHistogram(*scetaiXvar, *rawvar, "","raw_vs_eta");
if(EEorEB=="EB")
{
h_RC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_RC_eta->GetXaxis()->SetTitle("iX");
}
h_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_eta->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta.pdf");
c_raw_eta->SaveAs("raw_vs_eta.png");
TCanvas *c_raw_phi = new TCanvas;
TH2F *h_RC_phi = hdata->createHistogram(*scphiiYvar, *rawvar, "","raw_vs_phi");
if(EEorEB=="EB")
{
h_RC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_RC_phi->GetXaxis()->SetTitle("iY");
}
h_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_phi->Draw("COLZ");
c_raw_phi->SaveAs("raw_vs_phi.pdf");
c_raw_phi->SaveAs("raw_vs_phi.png");
//on2,5,20, etc
if(EEorEB == "EB")
{
TCanvas *myC_iCrystal_mod = new TCanvas;
RooRealVar *SM_distvar = ws->var("var_6");
SM_distvar->setRange(0,10);
SM_distvar->setBins(10);
TH2F *h_CC_SM_dist = hdata->createHistogram(*SM_distvar, *ecorvar, "","cor_vs_SM_dist");
h_CC_SM_dist->GetXaxis()->SetTitle("SM_dist");
h_CC_SM_dist->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_SM_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_SM_dist.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_SM_dist.png");
TH2F *h_RC_SM_dist = hdata->createHistogram(*SM_distvar, *rawvar, "","raw_vs_SM_dist");
h_RC_SM_dist->GetXaxis()->SetTitle("distance to SM gap");
h_RC_SM_dist->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_SM_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_SM_dist.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_SM_dist.png");
RooRealVar *M_distvar = ws->var("var_7");
M_distvar->setRange(0,13);
M_distvar->setBins(10);
TH2F *h_CC_M_dist = hdata->createHistogram(*M_distvar, *ecorvar, "","cor_vs_M_dist");
h_CC_M_dist->GetXaxis()->SetTitle("M_dist");
h_CC_M_dist->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_M_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_M_dist.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_M_dist.png");
TH2F *h_RC_M_dist = hdata->createHistogram(*M_distvar, *rawvar, "","raw_vs_M_dist");
h_RC_M_dist->GetXaxis()->SetTitle("distance to module gap");
h_RC_M_dist->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_M_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_M_dist.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_M_dist.png");
/*
RooRealVar *DeltaRG1G2var = ws->var("var_8");
DeltaRG1G2var->setRange(0,0.2);
DeltaRG1G2var->setBins(100);
TH2F *h_CC_DeltaRG1G2 = hdata->createHistogram(*DeltaRG1G2var, *ecorvar, "","cor_vs_DeltaRG1G2");
h_CC_DeltaRG1G2->GetXaxis()->SetTitle("DeltaRG1G2");
h_CC_DeltaRG1G2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_DeltaRG1G2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_DeltaRG1G2.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_DeltaRG1G2.png");
TH2F *h_RC_DeltaRG1G2 = hdata->createHistogram(*DeltaRG1G2var, *rawvar, "","raw_vs_DeltaRG1G2");
h_RC_DeltaRG1G2->GetXaxis()->SetTitle("distance to module gap");
h_RC_DeltaRG1G2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_DeltaRG1G2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_DeltaRG1G2.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_DeltaRG1G2.png");
*/
}
// other variables
TCanvas *myC_variables = new TCanvas;
RooRealVar *Nxtalvar = ws->var("var_1");
Nxtalvar->setRange(0,10);
Nxtalvar->setBins(10);
TH2F *h_CC_Nxtal = hdata->createHistogram(*Nxtalvar, *ecorvar, "","cor_vs_Nxtal");
h_CC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_CC_Nxtal->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Nxtal.pdf");
myC_variables->SaveAs("cor_vs_Nxtal.png");
TH2F *h_RC_Nxtal = hdata->createHistogram(*Nxtalvar, *rawvar, "","raw_vs_Nxtal");
h_RC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_RC_Nxtal->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Nxtal.pdf");
myC_variables->SaveAs("raw_vs_Nxtal.png");
RooRealVar *S4S9var = ws->var("var_2");
int Nbins_S4S9 = 100;
double Low_S4S9 = 0.6;
double High_S4S9 = 1.0;
S4S9var->setRange(Low_S4S9,High_S4S9);
S4S9var->setBins(Nbins_S4S9);
TH2F *h_CC_S4S9 = hdata->createHistogram(*S4S9var, *ecorvar, "","cor_vs_S4S9");
h_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h_CC_S4S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S4S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S4S9.pdf");
myC_variables->SaveAs("cor_vs_S4S9.png");
TH2F *h_RC_S4S9 = hdata->createHistogram(*S4S9var, *rawvar, "","raw_vs_S4S9");
h_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h_RC_S4S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S4S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S4S9.pdf");
myC_variables->SaveAs("raw_vs_S4S9.png");
RooRealVar *S2S9var = ws->var("var_3");
int Nbins_S2S9 = 100;
double Low_S2S9 = 0.5;
double High_S2S9 = 1.0;
S2S9var->setRange(Low_S2S9,High_S2S9);
S2S9var->setBins(Nbins_S2S9);
TH2F *h_CC_S2S9 = hdata->createHistogram(*S2S9var, *ecorvar, "","cor_vs_S2S9");
h_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h_CC_S2S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S2S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S2S9.pdf");
myC_variables->SaveAs("cor_vs_S2S9.png");
TH2F *h_RC_S2S9 = hdata->createHistogram(*S2S9var, *rawvar, "","raw_vs_S2S9");
h_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h_RC_S2S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S2S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S2S9.pdf");
myC_variables->SaveAs("raw_vs_S2S9.png");
TH2F *h_S2S9_eta = hdata->createHistogram(*scetaiXvar, *S2S9var, "","S2S9_vs_eta");
h_S2S9_eta->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S2S9_eta->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_eta.pdf");
myC_variables->SaveAs("S2S9_vs_eta.png");
TH2F *h_S4S9_eta = hdata->createHistogram(*scetaiXvar, *S4S9var, "","S4S9_vs_eta");
h_S4S9_eta->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S4S9_eta->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_eta.pdf");
myC_variables->SaveAs("S4S9_vs_eta.png");
TH2F *h_S2S9_phi = hdata->createHistogram(*scphiiYvar, *S2S9var, "","S2S9_vs_phi");
h_S2S9_phi->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S2S9_phi->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_phi.pdf");
myC_variables->SaveAs("S2S9_vs_phi.png");
TH2F *h_S4S9_phi = hdata->createHistogram(*scphiiYvar, *S4S9var, "","S4S9_vs_phi");
h_S4S9_phi->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S4S9_phi->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_phi.pdf");
myC_variables->SaveAs("S4S9_vs_phi.png");
if(EEorEB=="EE")
{
}
TProfile *p_CC_eta = h_CC_eta->ProfileX("p_CC_eta");//,1,-1,"s");
p_CC_eta->GetYaxis()->SetRangeUser(0.8,1.05);
if(EEorEB == "EB")
{
// p_CC_eta->GetYaxis()->SetRangeUser(0.85,1.0);
// p_CC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_eta->SetTitle("");
p_CC_eta->Draw();
myC_variables->SaveAs("profile_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_cor_vs_eta.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_CC_eta = new TH1F("h1_fit_CC_eta","h1_fit_CC_eta",(EEorEB=="EB") ? 180 : 50,(EEorEB=="EB") ? -90 : 0, (EEorEB=="EB") ? 90 : 50);
for(int ix = 1;ix <= h_CC_eta->GetNbinsX(); ix++)
{
stringstream os_iEta;
os_iEta << ((EEorEB=="EB") ? (-90 + ix -1) : (0 + ix -1));
string ss_iEta = os_iEta.str();
TH1D * h_temp = h_CC_eta->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.95,1.07);
h_temp->Fit("f_temp","R");
h1_fit_CC_eta->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_CC_eta->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{cor}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".pdf").c_str());
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".png").c_str());
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_CC_eta->GetYaxis()->SetRangeUser(0.95,1.05);
h1_fit_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h1_fit_CC_eta->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#eta" : "iX");
h1_fit_CC_eta->SetTitle("");
h1_fit_CC_eta->Draw();
myC_variables->SaveAs("profile_fit_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_fit_cor_vs_eta.png");
myC_variables->SaveAs("profile_fit_cor_vs_eta.C");
TProfile *p_RC_eta = h_RC_eta->ProfileX("p_RC_eta");//,1,-1,"s");
p_RC_eta->GetYaxis()->SetRangeUser(0.8,1.05);
if(EEorEB=="EB")
{
// p_RC_eta->GetYaxis()->SetRangeUser(0.80,0.95);
// p_RC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_eta->SetTitle("");
p_RC_eta->Draw();
myC_variables->SaveAs("profile_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_raw_vs_eta.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_RC_eta = new TH1F("h1_fit_RC_eta","h1_fit_RC_eta",(EEorEB=="EB") ? 180 : 50,(EEorEB=="EB") ? -90 : 0, (EEorEB=="EB") ? 90 : 50);
for(int ix = 1;ix <= h_RC_eta->GetNbinsX(); ix++)
{
stringstream os_iEta;
os_iEta << ((EEorEB=="EB") ? (-90 + ix -1) : (0 + ix -1));
string ss_iEta = os_iEta.str();
TH1D * h_temp = h_RC_eta->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.87,1.05);
h_temp->Fit("f_temp","R");
h1_fit_RC_eta->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_RC_eta->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{raw}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".pdf").c_str());
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".png").c_str());
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_RC_eta->GetYaxis()->SetRangeUser(0.9,1.0);
h1_fit_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h1_fit_RC_eta->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#eta" : "iX");
h1_fit_RC_eta->SetTitle("");
h1_fit_RC_eta->Draw();
myC_variables->SaveAs("profile_fit_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_fit_raw_vs_eta.png");
myC_variables->SaveAs("profile_fit_raw_vs_eta.C");
int Nbins_iEta = EEorEB=="EB" ? 180 : 50;
int nLow_iEta = EEorEB=="EB" ? -90 : 0;
int nHigh_iEta = EEorEB=="EB" ? 90 : 50;
TH1F *h1_RC_eta = new TH1F("h1_RC_eta","h1_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_RC_eta->SetBinContent(i,p_RC_eta->GetBinError(i));
}
h1_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_RC_eta->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_eta->SetTitle("");
h1_RC_eta->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.png");
TH1F *h1_CC_eta = new TH1F("h1_CC_eta","h1_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_CC_eta->SetBinContent(i,p_CC_eta->GetBinError(i));
}
h1_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_CC_eta->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_eta->SetTitle("");
h1_CC_eta->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.png");
TProfile *p_CC_phi = h_CC_phi->ProfileX("p_CC_phi");//,1,-1,"s");
p_CC_phi->GetYaxis()->SetRangeUser(0.9,1.0);
if(EEorEB == "EB")
{
// p_CC_phi->GetYaxis()->SetRangeUser(0.94,1.00);
}
p_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_phi->SetTitle("");
p_CC_phi->Draw();
myC_variables->SaveAs("profile_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_cor_vs_phi.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_CC_phi = new TH1F("h1_fit_CC_phi","h1_fit_CC_phi",(EEorEB=="EB") ? 360 : 50,(EEorEB=="EB") ? 0 : 0, (EEorEB=="EB") ? 360 : 50);
for(int ix = 1;ix <= h_CC_phi->GetNbinsX(); ix++)
{
stringstream os_iPhi;
os_iPhi << ((EEorEB=="EB") ? (0 + ix -1) : (0 + ix -1));
string ss_iPhi = os_iPhi.str();
TH1D * h_temp = h_CC_phi->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.95,1.07);
h_temp->Fit("f_temp","R");
h1_fit_CC_phi->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_CC_phi->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{cor}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".pdf").c_str());
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".png").c_str());
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_CC_phi->GetYaxis()->SetRangeUser(0.95,1.05);
h1_fit_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h1_fit_CC_phi->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#phi" : "iX");
h1_fit_CC_phi->SetTitle("");
h1_fit_CC_phi->Draw();
myC_variables->SaveAs("profile_fit_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_fit_cor_vs_phi.png");
myC_variables->SaveAs("profile_fit_cor_vs_phi.C");
TProfile *p_RC_phi = h_RC_phi->ProfileX("p_RC_phi");//,1,-1,"s");
p_RC_phi->GetYaxis()->SetRangeUser(0.8,0.9);
if(EEorEB=="EB")
{
// p_RC_phi->GetYaxis()->SetRangeUser(0.89,0.95);
}
p_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_phi->SetTitle("");
p_RC_phi->Draw();
myC_variables->SaveAs("profile_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_raw_vs_phi.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_RC_phi = new TH1F("h1_fit_RC_phi","h1_fit_RC_phi",(EEorEB=="EB") ? 360 : 50,(EEorEB=="EB") ? 0 : 0, (EEorEB=="EB") ? 360 : 50);
for(int ix = 1;ix <= h_RC_phi->GetNbinsX(); ix++)
{
stringstream os_iPhi;
os_iPhi << ((EEorEB=="EB") ? (0 + ix -1) : (0 + ix -1));
string ss_iPhi = os_iPhi.str();
TH1D * h_temp = h_RC_phi->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.87,1.05);
h_temp->Fit("f_temp","R");
h1_fit_RC_phi->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_RC_phi->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{raw}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".pdf").c_str());
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".png").c_str());
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_RC_phi->GetYaxis()->SetRangeUser(0.9,1.0);
h1_fit_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h1_fit_RC_phi->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#phi" : "iX");
h1_fit_RC_phi->SetTitle("");
h1_fit_RC_phi->Draw();
myC_variables->SaveAs("profile_fit_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_fit_raw_vs_phi.png");
myC_variables->SaveAs("profile_fit_raw_vs_phi.C");
int Nbins_iPhi = EEorEB=="EB" ? 360 : 50;
int nLow_iPhi = EEorEB=="EB" ? 0 : 0;
int nHigh_iPhi = EEorEB=="EB" ? 360 : 50;
TH1F *h1_RC_phi = new TH1F("h1_RC_phi","h1_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_RC_phi->SetBinContent(i,p_RC_phi->GetBinError(i));
}
h1_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_RC_phi->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_phi->SetTitle("");
h1_RC_phi->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.png");
TH1F *h1_CC_phi = new TH1F("h1_CC_phi","h1_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_CC_phi->SetBinContent(i,p_CC_phi->GetBinError(i));
}
h1_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_CC_phi->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_phi->SetTitle("");
h1_CC_phi->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.png");
// FWHM over sigma_eff vs. eta/phi
TH1F *h1_FoverS_RC_phi = new TH1F("h1_FoverS_RC_phi","h1_FoverS_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_CC_phi = new TH1F("h1_FoverS_CC_phi","h1_FoverS_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_RC_eta = new TH1F("h1_FoverS_RC_eta","h1_FoverS_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_eta = new TH1F("h1_FoverS_CC_eta","h1_FoverS_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_S2S9 = new TH1F("h1_FoverS_CC_S2S9","h1_FoverS_CC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_RC_S2S9 = new TH1F("h1_FoverS_RC_S2S9","h1_FoverS_RC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_CC_S4S9 = new TH1F("h1_FoverS_CC_S4S9","h1_FoverS_CC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
TH1F *h1_FoverS_RC_S4S9 = new TH1F("h1_FoverS_RC_S4S9","h1_FoverS_RC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
float FWHMoverSigmaEff = 0.0;
TH1F *h_tmp_rawvar = new TH1F("tmp_rawvar","tmp_rawvar",800,0.5,1.5);
TH1F *h_tmp_corvar = new TH1F("tmp_corvar","tmp_corvar",800,0.5,1.5);
for(int i=1;i<=Nbins_iPhi;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_phi->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_phi->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_phi->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_phi->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_CC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_phi->SetTitle("");
h1_FoverS_CC_phi->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.png");
h1_FoverS_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_RC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_phi->SetTitle("");
h1_FoverS_RC_phi->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.png");
for(int i=1;i<=Nbins_iEta;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_eta->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_eta->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_eta->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_eta->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_CC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_eta->SetTitle("");
h1_FoverS_CC_eta->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.png");
h1_FoverS_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_RC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_eta->SetTitle("");
h1_FoverS_RC_eta->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.png");
for(int i=1;i<=Nbins_S2S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S2S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S2S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_CC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S2S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S2S9->SetTitle("");
h1_FoverS_CC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.png");
h1_FoverS_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_RC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S2S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S2S9->SetTitle("");
h1_FoverS_RC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.png");
for(int i=1;i<=Nbins_S4S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S4S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S4S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_CC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S4S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S4S9->SetTitle("");
h1_FoverS_CC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.png");
h1_FoverS_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_RC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S4S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S4S9->SetTitle("");
h1_FoverS_RC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.png");
printf("calc effsigma\n");
std::cout<<"_"<<EEorEB<<std::endl;
printf("corrected curve effSigma= %5f, FWHM=%5f \n",effsigma_cor, fwhm_cor);
printf("raw curve effSigma= %5f FWHM=%5f \n",effsigma_raw, fwhm_raw);
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
}
void fitbkgdataCard(TString configCard="template.config",
bool dobands = true, // create baerror bands for BG models
bool dosignal = false, // plot the signal model (needs to be present)
bool blinded = true, // blind the data in the plots?
bool verbose = true ) {
gROOT->Macro("MitStyle.C");
gStyle->SetErrorX(0);
gStyle->SetOptStat(0);
gROOT->ForceStyle();
TString projectDir;
std::vector<TString> catdesc;
std::vector<TString> catnames;
std::vector<int> polorder;
double massmin = -1.;
double massmax = -1.;
double theCMenergy = -1.;
bool readStatus = readFromConfigCard( configCard,
projectDir,
catnames,
catdesc,
polorder,
massmin,
massmax,
theCMenergy
);
if( !readStatus ) {
std::cerr<<" ERROR: Could not read from card > "<<configCard.Data()<<" <."<<std::endl;
return;
}
TFile *fdata = new TFile(TString::Format("%s/CMS-HGG-data.root",projectDir.Data()),"READ");
if( !fdata ) {
std::cerr<<" ERROR: Could not open file "<<projectDir.Data()<<"/CMS-HGG-data.root."<<std::endl;
return;
}
if( !gSystem->cd(TString::Format("%s/databkg/",projectDir.Data())) ) {
std::cerr<<" ERROR: Could not change directory to "<<TString::Format("%s/databkg/",projectDir.Data()).Data()<<"."<<std::endl;
return;
}
// ----------------------------------------------------------------------
// load the input workspace....
RooWorkspace* win = (RooWorkspace*)fdata->Get("cms_hgg_workspace_data");
if( !win ) {
std::cerr<<" ERROR: Could not load workspace > cms_hgg_workspace_data < from file > "<<TString::Format("%s/CMS-HGG-data.root",projectDir.Data()).Data()<<" <."<<std::endl;
return;
}
RooRealVar *intLumi = win->var("IntLumi");
RooRealVar *hmass = win->var("CMS_hgg_mass");
if( !intLumi || !hmass ) {
std::cerr<<" ERROR: Could not load needed variables > IntLumi < or > CMS_hgg_mass < forom input workspace."<<std::endl;
return;
}
//win->Print();
hmass->setRange(massmin,massmax);
hmass->setBins(4*(int)(massmax-massmin));
hmass->SetTitle("m_{#gamma#gamma}");
hmass->setUnit("GeV");
hmass->setRange("fitrange",massmin,massmax);
hmass->setRange("blind1",100.,110.);
hmass->setRange("blind2",150.,180.);
// ----------------------------------------------------------------------
// some auxiliray vectro (don't know the meaning of all of them ... yet...
std::vector<RooAbsData*> data_vec;
std::vector<RooAbsPdf*> pdfShape_vec; // vector to store the NOT-EXTENDED PDFs (aka pdfshape)
std::vector<RooAbsPdf*> pdf_vec; // vector to store the EXTENDED PDFs
std::vector<RooAbsReal*> normu_vec; // this holds the normalization vars for each Cat (needed in bands for combined cat)
RooArgList normList; // list of range-limityed normalizations (needed for error bands on combined category)
//std::vector<RooRealVar*> coeffv;
//std::vector<RooAbsReal*> normu_vecv; // ???
// ----------------------------------------------------------------------
// define output works
RooWorkspace *wOut = new RooWorkspace("wbkg","wbkg") ;
// util;ities for the combined fit
RooCategory finalcat ("finalcat", "finalcat") ;
RooSimultaneous fullbkgpdf("fullbkgpdf","fullbkgpdf",finalcat);
RooDataSet datacomb ("datacomb", "datacomb", RooArgList(*hmass,finalcat)) ;
RooDataSet *datacombcat = new RooDataSet("data_combcat","",RooArgList(*hmass)) ;
// add the 'combcat' to the list...if more than one cat
if( catnames.size() > 1 ) {
catnames.push_back("combcat");
catdesc.push_back("Combined");
}
for (UInt_t icat=0; icat<catnames.size(); ++icat) {
TString catname = catnames.at(icat);
finalcat.defineType(catname);
// check if we're in a sub-cat or the comb-cat
RooDataSet *data = NULL;
RooDataSet *inData = NULL;
if( icat < (catnames.size() - 1) || catnames.size() == 1) { // this is NOT the last cat (which is by construction the combination)
inData = (RooDataSet*)win->data(TString("data_mass_")+catname);
if( !inData ) {
std::cerr<<" ERROR: Could not find dataset > data_mass_"<<catname.Data()<<" < in input workspace."<<std::endl;
return;
}
data = new RooDataSet(TString("data_")+catname,"",*hmass,Import(*inData)); // copy the dataset (why?)
// append the data to the combined data...
RooDataSet *datacat = new RooDataSet(TString("datacat")+catname,"",*hmass,Index(finalcat),Import(catname,*data)) ;
datacomb.append(*datacat);
datacombcat->append(*data);
// normalization for this category
RooRealVar *nbkg = new RooRealVar(TString::Format("CMS_hgg_%s_bkgshape_norm",catname.Data()),"",800.0,0.0,25e3);
// we keep track of the normalizario vars only for N-1 cats, naming convetnions hystoric...
if( catnames.size() > 2 && icat < (catnames.size() - 2) ) {
RooRealVar* cbkg = new RooRealVar(TString::Format("cbkg%s",catname.Data()),"",0.0,0.0,1e3);
cbkg->removeRange();
normu_vec.push_back(cbkg);
normList.add(*cbkg);
}
/// generate the Bernstrin polynomial (FIX-ME: add possibility ro create other models...)
fstBernModel* theBGmodel = new fstBernModel(hmass, polorder[icat], icat, catname); // using my dedicated class...
std::cout<<" model name is "<<theBGmodel->getPdf()->GetName()<<std::endl;
RooAbsPdf* bkgshape = theBGmodel->getPdf(); // the BG shape
RooAbsPdf* bkgpdf = new RooExtendPdf(TString("bkgpdf")+catname,"",*bkgshape,*nbkg); // the extended PDF
// add the extedned PDF to the RooSimultaneous holding all models...
fullbkgpdf.addPdf(*bkgpdf,catname);
// store the NON-EXTENDED PDF for usgae to compute the error bands later..
pdfShape_vec.push_back(bkgshape);
pdf_vec .push_back(bkgpdf);
data_vec .push_back(data);
} else {
data = datacombcat; // we're looking at the last cat (by construction the combination)
data_vec.push_back(data);
// sum up all the cts PDFs for combined PDF
RooArgList subpdfs;
for (int ipdf=0; ipdf<pdf_vec.size(); ++ipdf) {
subpdfs.add(*pdf_vec.at(ipdf));
}
RooAddPdf* bkgpdf = new RooAddPdf(TString("bkgpdf")+catname,"",subpdfs);
pdfShape_vec.push_back(bkgpdf);
pdf_vec .push_back(bkgpdf); // I don't think this is really needed though....
}
// generate the binned dataset (to be put into the workspace... just in case...)
RooDataHist *databinned = new RooDataHist(TString("databinned_")+catname,"",*hmass,*data);
wOut->import(*data);
wOut->import(*databinned);
}
std::cout<<" ***************** "<<std::endl;
// fit the RooSimultaneous to the combined dataset -> (we could also fit each cat separately)
fullbkgpdf.fitTo(datacomb,Strategy(1),Minos(kFALSE),Save(kTRUE));
RooFitResult *fullbkgfitres = fullbkgpdf.fitTo(datacomb,Strategy(2),Minos(kFALSE),Save(kTRUE));
// in principle we're done now, so store the results in the output workspace
wOut->import(datacomb);
wOut->import(fullbkgpdf);
wOut->import(*fullbkgfitres);
std::cout<<" ***************** "<<std::endl;
if( verbose ) wOut->Print();
std::cout<<" ***************** "<<std::endl;
wOut->writeToFile("bkgdatawithfit.root") ;
if( verbose ) {
printf("IntLumi = %5f\n",intLumi->getVal());
printf("ndata:\n");
for (UInt_t icat=0; icat<catnames.size(); ++icat) {
printf("%i ",data_vec.at(icat)->numEntries());
}
printf("\n");
}
// --------------------------------------------------------------------------------------------
// Now comesd the plotting
// chage the Statistics style...
gStyle->SetOptStat(1110);
// we want to plot in 1GeV bins (apparently...)
UInt_t nbins = (UInt_t) (massmax-massmin);
// here we'll store the curves for the bands...
std::vector<RooCurve*> fitcurves;
// loop again over the cats
TCanvas **canbkg = new TCanvas*[catnames.size()];
RooPlot** plot = new RooPlot*[catnames.size()];
TLatex** lat = new TLatex*[catnames.size()];
TLatex** lat2 = new TLatex*[catnames.size()];
std::cout<<" beofre plotting..."<<std::endl;
for (UInt_t icat=0; icat<catnames.size(); ++icat) {
TString catname = catnames.at(icat);
std::cout<<" trying to plot #"<<icat<<std::endl;
// plot the data and the fit
canbkg[icat] = new TCanvas;
plot [icat] = hmass->frame(Bins(nbins),Range("fitrange"));
std::cout<<" trying to plot #"<<icat<<std::endl;
// first plot the data invisibly... and put the fitted BG model on top...
data_vec .at(icat)->plotOn(plot[icat],RooFit::LineColor(kWhite),MarkerColor(kWhite),Invisible());
pdfShape_vec.at(icat)->plotOn(plot[icat],RooFit::LineColor(kRed),Range("fitrange"),NormRange("fitrange"));
std::cout<<" trying to plot #"<<icat<<std::endl;
// if toggled on, plot also the Data visibly
if( !blinded ) {
data_vec.at(icat)->plotOn(plot[icat]);
}
std::cout<<" trying to plot #"<<icat<<std::endl;
// some cosmetics...
plot[icat]->SetTitle("");
plot[icat]->SetMinimum(0.0);
plot[icat]->SetMaximum(1.40*plot[icat]->GetMaximum());
plot[icat]->GetXaxis()->SetTitle("m_{#gamma#gamma} (GeV/c^{2})");
plot[icat]->Draw();
std::cout<<" trying to plot #"<<icat<<std::endl;
// legend....
TLegend *legmc = new TLegend(0.68,0.70,0.97,0.90);
legmc->AddEntry(plot[icat]->getObject(2),"Data","LPE");
legmc->AddEntry(plot[icat]->getObject(1),"Bkg Model","L");
// this part computes the 1/2-sigma bands.
TGraphAsymmErrors *onesigma = NULL;
TGraphAsymmErrors *twosigma = NULL;
std::cout<<" trying *** to plot #"<<icat<<std::endl;
RooAddition* sumcatsnm1 = NULL;
if ( dobands ) { //&& icat == (catnames.size() - 1) ) {
onesigma = new TGraphAsymmErrors();
twosigma = new TGraphAsymmErrors();
// get the PDF for this cat from the vector
RooAbsPdf *thisPdf = pdfShape_vec.at(icat);
// get the nominal fir curve
RooCurve *nomcurve = dynamic_cast<RooCurve*>(plot[icat]->getObject(1));
fitcurves.push_back(nomcurve);
bool iscombcat = ( icat == (catnames.size() - 1) && catnames.size() > 1);
RooAbsData *datanorm = ( iscombcat ? &datacomb : data_vec.at(icat) );
// this si the nornmalization in the 'sliding-window' (i.e. per 'test-bin')
RooRealVar *nlim = new RooRealVar(TString::Format("nlim%s",catnames.at(icat).Data()),"",0.0,0.0,10.0);
nlim->removeRange();
if( iscombcat ) {
// ----------- HISTORIC NAMING ----------------------------------------
sumcatsnm1 = new RooAddition("sumcatsnm1","",normList); // summing all normalizations epect the last Cat
// this is the normlization of the last Cat
RooFormulaVar *nlast = new RooFormulaVar("nlast","","TMath::Max(0.1,@0-@1)",RooArgList(*nlim,*sumcatsnm1));
// ... and adding it ot the list of norms
normu_vec.push_back(nlast);
}
//if (icat == 1 && catnames.size() == 2) continue; // only 1 cat, so don't need combination
for (int i=1; i<(plot[icat]->GetXaxis()->GetNbins()+1); ++i) {
// this defines the 'binning' we use for the error bands
double lowedge = plot[icat]->GetXaxis()->GetBinLowEdge(i);
double upedge = plot[icat]->GetXaxis()->GetBinUpEdge(i);
double center = plot[icat]->GetXaxis()->GetBinCenter(i);
// get the nominal value at the center of the bin
double nombkg = nomcurve->interpolate(center);
nlim->setVal(nombkg);
hmass->setRange("errRange",lowedge,upedge);
// this is the new extended PDF whith the normalization restricted to the bin-area
RooAbsPdf *extLimPdf = NULL;
if( iscombcat ) {
extLimPdf = new RooSimultaneous("epdf","",finalcat);
// loop over the cats and generate temporary extended PDFs
for (int jcat=0; jcat<(catnames.size()-1); ++jcat) {
RooRealVar *rvar = dynamic_cast<RooRealVar*>(normu_vec.at(jcat));
if (rvar) rvar->setVal(fitcurves.at(jcat)->interpolate(center));
RooExtendPdf *ecpdf = new RooExtendPdf(TString::Format("ecpdf%s",catnames.at(jcat).Data()),"",*pdfShape_vec.at(jcat),*normu_vec.at(jcat),"errRange");
static_cast<RooSimultaneous*>(extLimPdf)->addPdf(*ecpdf,catnames.at(jcat));
}
} else
extLimPdf = new RooExtendPdf("extLimPdf","",*thisPdf,*nlim,"errRange");
RooAbsReal *nll = extLimPdf->createNLL(*datanorm,Extended(),NumCPU(1));
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);
if (iscombcat) minim.setStrategy(2);
minim.migrad();
if (!iscombcat) {
minim.minos(*nlim);
}
else {
minim.hesse();
nlim->removeAsymError();
}
if( verbose )
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());
// to get the 2-sigma bands...
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!
if (!iscombcat) {
minim.migrad();
minim.minos(*nlim);
}
else {
nlim->setError(2.0*nlim->getError());
nlim->removeAsymError();
}
twosigma->SetPoint(i-1,center,nombkg);
twosigma->SetPointError(i-1,0.,0.,-nlim->getErrorLo(),nlim->getErrorHi());
// for memory clean-up
delete nll;
delete extLimPdf;
}
hmass->setRange("errRange",massmin,massmax);
if( verbose )
onesigma->Print("V");
// plot[icat] the error bands
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");
plot[icat]->Draw("SAME");
// and add the error bands to the legend
legmc->AddEntry(onesigma,"#pm1 #sigma","F");
legmc->AddEntry(twosigma,"#pm2 #sigma","F");
}
std::cout<<" trying ***2 to plot #"<<icat<<std::endl;
// rest of the legend ....
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
lat[icat] = new TLatex(103.0,0.9*plot[icat]->GetMaximum(),TString::Format("#scale[0.7]{#splitline{CMS preliminary}{#sqrt{s} = %.1f TeV L = %.2f fb^{-1}}}",theCMenergy,intLumi->getVal()));
lat2[icat] = new TLatex(103.0,0.75*plot[icat]->GetMaximum(),catdesc.at(icat));
lat[icat] ->Draw();
lat2[icat]->Draw();
// -------------------------------------------------------
// save canvas in different formats
canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".pdf"));
canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".eps"));
canbkg[icat]->SaveAs(TString("databkg") + catname + TString(".root"));
}
return;
}
void runQ(const char* inFileName,
const char* wsName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData",
const char* asimov0DataName = "asimovData_0",
const char* conditional0Snapshot = "conditionalGlobs_0",
const char* asimov1DataName = "asimovData_1",
const char* conditional1Snapshot = "conditionalGlobs_1",
const char* nominalSnapshot = "nominalGlobs",
string smass = "130",
string folder = "test")
{
double mass;
stringstream massStr;
massStr << smass;
massStr >> mass;
bool errFast = 0;
bool goFast = 1;
bool remakeData = 1;
bool doRightSided = 1;
bool doInj = 0;
bool doObs = 1;
bool doMedian = 1;
TStopwatch timer;
timer.Start();
TFile f(inFileName);
RooWorkspace* ws = (RooWorkspace*)f.Get(wsName);
if (!ws)
{
cout << "ERROR::Workspace: " << wsName << " doesn't exist!" << endl;
return;
}
ModelConfig* mc = (ModelConfig*)ws->obj(modelConfigName);
if (!mc)
{
cout << "ERROR::ModelConfig: " << modelConfigName << " doesn't exist!" << endl;
return;
}
RooDataSet* data = (RooDataSet*)ws->data(dataName);
if (!data)
{
cout << "ERROR::Dataset: " << dataName << " doesn't exist!" << endl;
return;
}
mc->GetNuisanceParameters()->Print("v");
RooNLLVar::SetIgnoreZeroEntries(1);
ROOT::Math::MinimizerOptions::SetDefaultMinimizer("Minuit2");
ROOT::Math::MinimizerOptions::SetDefaultStrategy(0);
ROOT::Math::MinimizerOptions::SetDefaultPrintLevel(1);
cout << "Setting max function calls" << endl;
//ROOT::Math::MinimizerOptions::SetDefaultMaxFunctionCalls(20000);
RooMinimizer::SetMaxFunctionCalls(10000);
ws->loadSnapshot("conditionalNuis_0");
RooArgSet nuis(*mc->GetNuisanceParameters());
RooRealVar* mu = (RooRealVar*)mc->GetParametersOfInterest()->first();
if (string(mc->GetPdf()->ClassName()) == "RooSimultaneous" && remakeData)
{
RooSimultaneous* simPdf = (RooSimultaneous*)mc->GetPdf();
double min_mu;
data = makeData(data, simPdf, mc->GetObservables(), mu, mass, min_mu);
}
RooDataSet* asimovData0 = (RooDataSet*)ws->data(asimov0DataName);
if (!asimovData0)
{
cout << "Asimov data doesn't exist! Please, allow me to build one for you..." << endl;
makeAsimovData(mc, true, ws, mc->GetPdf(), data, 1);
ws->Print();
asimovData0 = (RooDataSet*)ws->data("asimovData_0");
}
RooDataSet* asimovData1 = (RooDataSet*)ws->data(asimov1DataName);
if (!asimovData1)
{
cout << "Asimov data doesn't exist! Please, allow me to build one for you..." << endl;
makeAsimovData(mc, true, ws, mc->GetPdf(), data, 0);
ws->Print();
asimovData1 = (RooDataSet*)ws->data("asimovData_1");
}
if (!doRightSided) mu->setRange(0, 40);
else mu->setRange(-40, 40);
bool old = false;
if (old)
{
mu->setVal(0);
RooArgSet poi(*mu);
ProfileLikelihoodTestStat_modified asimov_testStat_sig(*mc->GetPdf());
asimov_testStat_sig.SetRightSided(doRightSided);
asimov_testStat_sig.SetNuis(&nuis);
if (!doInj) asimov_testStat_sig.SetDoAsimov(true, 1);
asimov_testStat_sig.SetWorkspace(ws);
ProfileLikelihoodTestStat_modified testStat(*mc->GetPdf());
testStat.SetRightSided(doRightSided);
testStat.SetNuis(&nuis);
testStat.SetWorkspace(ws);
//RooMinimizerFcn::SetOverrideEverything(true);
double med_sig = 0;
double med_testStat_val = 0;
//gRandom->SetSeed(1);
//RooRandom::randomGenerator()->SetSeed(1);
RooNLLVar::SetIgnoreZeroEntries(1);
if (asimov1DataName != "" && doMedian)
{
mu->setVal(0);
if (!doInj) mu->setRange(0, 2);
ws->loadSnapshot("conditionalNuis_0");
asimov_testStat_sig.SetLoadUncondSnapshot("conditionalNuis_1");
if (string(conditional1Snapshot) != "") ws->loadSnapshot(conditional1Snapshot);
med_testStat_val = 2*asimov_testStat_sig.Evaluate(*asimovData1, poi);
if (med_testStat_val < 0 && !doInj)
{
mu->setVal(0);
med_testStat_val = 2*asimov_testStat_sig.Evaluate(*asimovData1, poi); // just try again
}
int sign = med_testStat_val != 0 ? med_testStat_val/fabs(med_testStat_val) : 0;
med_sig = sign*sqrt(fabs(med_testStat_val));
if (string(nominalSnapshot) != "") ws->loadSnapshot(nominalSnapshot);
if (!doRightSided) mu->setRange(0, 40);
else mu->setRange(-40, 40);
}
RooNLLVar::SetIgnoreZeroEntries(0);
//gRandom->SetSeed(1);
//RooRandom::randomGenerator()->SetSeed(1);
//RooMinimizerFcn::SetOverrideEverything(false);
cout << "med test stat: " << med_testStat_val << endl;
ws->loadSnapshot("nominalGlobs");
ws->loadSnapshot("conditionalNuis_0");
mu->setVal(0);
testStat.SetWorkspace(ws);
testStat.SetLoadUncondSnapshot("ucmles");
double obsTestStat_val = doObs ? 2*testStat.Evaluate(*data, poi) : 0;
cout << "obs test stat: " << obsTestStat_val << endl;
// obsTestStat_val = 2*testStat.Evaluate(*data, poi);
// cout << "obs test stat: " << obsTestStat_val << endl;
// obsTestStat_val = 2*testStat.Evaluate(*data, poi);
// cout << "obs test stat: " << obsTestStat_val << endl;
double obs_sig;
int sign = obsTestStat_val == 0 ? 0 : obsTestStat_val / fabs(obsTestStat_val);
if (!doRightSided && (obsTestStat_val < 0 && obsTestStat_val > -0.1 || mu->getVal() < 0.001)) obs_sig = 0;
else obs_sig = sign*sqrt(fabs(obsTestStat_val));
if (obs_sig != obs_sig) //nan, do by hand
{
cout << "Obs test stat gave nan: try by hand" << endl;
mu->setVal(0);
mu->setConstant(1);
mc->GetPdf()->fitTo(*data, Hesse(0), Minos(0), PrintLevel(-1), Constrain(*mc->GetNuisanceParameters()));
mu->setConstant(0);
double L_0 = mc->GetPdf()->getVal();
//mu->setVal(0);
//mu->setConstant(1);
mc->GetPdf()->fitTo(*data, Hesse(0), Minos(0), PrintLevel(-1), Constrain(*mc->GetNuisanceParameters()));
//mu->setConstant(0);
double L_muhat = mc->GetPdf()->getVal();
cout << "L_0: " << L_0 << ", L_muhat: " << L_muhat << endl;
obs_sig = sqrt(-2*TMath::Log(L_0/L_muhat));
//still nan
if (obs_sig != obs_sig && fabs(L_0 - L_muhat) < 0.000001) obs_sig = 0;
}
cout << "obs: " << obs_sig << endl;
cout << "Observed significance: " << obs_sig << endl;
if (med_sig)
{
cout << "Median test stat val: " << med_testStat_val << endl;
cout << "Median significance: " << med_sig << endl;
}
f.Close();
stringstream fileName;
fileName << "root_files/" << folder << "/" << mass << ".root";
system(("mkdir -vp root_files/" + folder).c_str());
TFile f2(fileName.str().c_str(),"recreate");
// stringstream fileName;
// fileName << "results_sig/" << mass << ".root";
// system("mkdir results_sig");
// TFile f(fileName.str().c_str(),"recreate");
TH1D* h_hypo = new TH1D("hypo","hypo",2,0,2);
h_hypo->SetBinContent(1, obs_sig);
h_hypo->SetBinContent(2, med_sig);
f2.Write();
f2.Close();
//mc->GetPdf()->fitTo(*data, PrintLevel(0));
timer.Stop();
timer.Print();
}
else
{
RooAbsPdf* pdf = mc->GetPdf();
RooArgSet nuis_tmp1 = *mc->GetNuisanceParameters();
RooNLLVar* asimov_nll0 = (RooNLLVar*)pdf->createNLL(*asimovData0, Constrain(nuis_tmp1));
RooArgSet nuis_tmp2 = *mc->GetNuisanceParameters();
RooNLLVar* asimov_nll1 = (RooNLLVar*)pdf->createNLL(*asimovData1, Constrain(nuis_tmp2));
RooArgSet nuis_tmp3 = *mc->GetNuisanceParameters();
RooNLLVar* obs_nll = (RooNLLVar*)pdf->createNLL(*data, Constrain(nuis_tmp3));
//do asimov
int status;
//get sigma_b
ws->loadSnapshot(conditional0Snapshot);
status = ws->loadSnapshot("conditionalNuis_0");
if (status != 0 && goFast) errFast = 1;
mu->setVal(0);
mu->setConstant(1);
status = goFast ? 0 : minimize(asimov_nll0, ws);
if (status < 0)
{
cout << "Retrying" << endl;
//ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll0, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov0_nll0 = asimov_nll0->getVal();
mu->setVal(1);
ws->loadSnapshot("conditionalNuis_1");
status = minimize(asimov_nll0, ws);
if (status < 0)
{
cout << "Retrying" << endl;
//ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll0, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov0_nll1 = asimov_nll0->getVal();
double asimov0_q = 2*(asimov0_nll1 - asimov0_nll0);
double sigma_b = sqrt(1./asimov0_q);
ws->loadSnapshot(nominalSnapshot);
//get sigma_sb
ws->loadSnapshot(conditional1Snapshot);
ws->loadSnapshot("conditionalNuis_0");
mu->setVal(0);
mu->setConstant(1);
status = minimize(asimov_nll1, ws);
if (status < 0)
{
cout << "Retrying" << endl;
//ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll1, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov1_nll0 = asimov_nll1->getVal();
mu->setVal(1);
status = ws->loadSnapshot("conditionalNuis_1");
if (status != 0 && goFast) errFast = 1;
status = goFast ? 0 : minimize(asimov_nll1, ws);
if (status < 0)
{
cout << "Retrying" << endl;
//ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll1, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov1_nll1 = asimov_nll1->getVal();
double asimov1_q = 2*(asimov1_nll1 - asimov1_nll0);
double sigma_sb = sqrt(-1./asimov1_q);
ws->loadSnapshot(nominalSnapshot);
//do obs
mu->setVal(0);
status = ws->loadSnapshot("conditionalNuis_0");
if (status != 0 && goFast) errFast = 1;
mu->setConstant(1);
status = goFast ? 0 : minimize(obs_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(obs_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double obs_nll0 = obs_nll->getVal();
status = ws->loadSnapshot("conditionalNuis_1");
if (status != 0 && goFast) errFast = 1;
mu->setVal(1);
status = goFast ? 0 : minimize(obs_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(obs_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double obs_nll1 = obs_nll->getVal();
double obs_q = 2*(obs_nll1 - obs_nll0);
double Zobs = (1./sigma_b/sigma_b - obs_q) / (2./sigma_b);
double Zexp = (1./sigma_b/sigma_b - asimov1_q) / (2./sigma_b);
double pb_obs = 1-ROOT::Math::gaussian_cdf(Zobs);
double pb_exp = 1-ROOT::Math::gaussian_cdf(Zexp);
cout << "asimov0_q = " << asimov0_q << endl;
cout << "asimov1_q = " << asimov1_q << endl;
cout << "obs_q = " << obs_q << endl;
cout << "sigma_b = " << sigma_b << endl;
cout << "sigma_sb = " << sigma_sb << endl;
cout << "Z obs = " << Zobs << endl;
cout << "Z exp = " << Zexp << endl;
f.Close();
stringstream fileName;
fileName << "root_files/" << folder << "/" << mass << ".root";
system(("mkdir -vp root_files/" + folder).c_str());
TFile f2(fileName.str().c_str(),"recreate");
TH1D* h_hypo = new TH1D("hypo_tev","hypo_tev",2,0,2);
h_hypo->SetBinContent(1, pb_obs);
h_hypo->SetBinContent(2, pb_exp);
f2.Write();
f2.Close();
stringstream fileName3;
fileName3 << "root_files/" << folder << "_llr/" << mass << ".root";
system(("mkdir -vp root_files/" + folder + "_llr").c_str());
TFile f3(fileName3.str().c_str(),"recreate");
TH1D* h_hypo3 = new TH1D("hypo_llr","hypo_llr",7,0,7);
h_hypo3->SetBinContent(1, -obs_q);
h_hypo3->SetBinContent(2, -asimov1_q);
h_hypo3->SetBinContent(3, -asimov0_q);
h_hypo3->SetBinContent(4, -asimov0_q-2*2/sigma_b);
h_hypo3->SetBinContent(5, -asimov0_q-1*2/sigma_b);
h_hypo3->SetBinContent(6, -asimov0_q+1*2/sigma_b);
h_hypo3->SetBinContent(7, -asimov0_q+2*2/sigma_b);
f3.Write();
f3.Close();
timer.Stop();
timer.Print();
}
}
///
/// Find the global minimum in a more thorough way.
/// First fit with external start parameters, then
/// for each parameter that starts with "d" or "r" (typically angles and ratios):
/// - at upper scan range, rest at start parameters
/// - at lower scan range, rest at start parameters
/// This amounts to a maximum of 1+2^n fits, where n is the number
/// of parameters to be varied.
///
/// \param w Workspace holding the pdf.
/// \param name Name of the pdf without leading "pdf_".
/// \param forceVariables Apply the force method for these variables only. Format
/// "var1,var2,var3," (list must end with comma). Default is to apply for all angles,
/// all ratios except rD_k3pi and rD_kpi, and the k3pi coherence factor.
///
RooFitResult* Utils::fitToMinForce(RooWorkspace *w, TString name, TString forceVariables)
{
bool debug = true;
TString parsName = "par_"+name;
TString obsName = "obs_"+name;
TString pdfName = "pdf_"+name;
RooFitResult *r = 0;
int printlevel = -1;
RooMsgService::instance().setGlobalKillBelow(ERROR);
// save start parameters
if ( !w->set(parsName) ){
cout << "MethodProbScan::scan2d() : ERROR : parsName not found: " << parsName << endl;
exit(1);
}
RooDataSet *startPars = new RooDataSet("startParsForce", "startParsForce", *w->set(parsName));
startPars->add(*w->set(parsName));
// set up parameters and ranges
RooArgList *varyPars = new RooArgList();
TIterator* it = w->set(parsName)->createIterator();
while ( RooRealVar* p = (RooRealVar*)it->Next() )
{
if ( p->isConstant() ) continue;
if ( forceVariables=="" && ( false
|| TString(p->GetName()).BeginsWith("d") ///< use these variables
// || TString(p->GetName()).BeginsWith("r")
|| TString(p->GetName()).BeginsWith("k")
|| TString(p->GetName()) == "g"
) && ! (
TString(p->GetName()) == "rD_k3pi" ///< don't use these
|| TString(p->GetName()) == "rD_kpi"
// || TString(p->GetName()) == "dD_kpi"
|| TString(p->GetName()) == "d_dk"
|| TString(p->GetName()) == "d_dsk"
))
{
varyPars->add(*p);
}
else if ( forceVariables.Contains(TString(p->GetName())+",") )
{
varyPars->add(*p);
}
}
delete it;
int nPars = varyPars->getSize();
if ( debug ) cout << "Utils::fitToMinForce() : nPars = " << nPars << " => " << pow(2.,nPars) << " fits" << endl;
if ( debug ) cout << "Utils::fitToMinForce() : varying ";
if ( debug ) varyPars->Print();
//////////
r = fitToMinBringBackAngles(w->pdf(pdfName), false, printlevel);
//////////
int nErrors = 0;
// We define a binary mask where each bit corresponds
// to parameter at max or at min.
for ( int i=0; i<pow(2.,nPars); i++ )
{
if ( debug ) cout << "Utils::fitToMinForce() : fit " << i << " \r" << flush;
setParameters(w, parsName, startPars->get(0));
for ( int ip=0; ip<nPars; ip++ )
{
RooRealVar *p = (RooRealVar*)varyPars->at(ip);
float oldMin = p->getMin();
float oldMax = p->getMax();
setLimit(w, p->GetName(), "force");
if ( i/(int)pow(2.,ip) % 2==0 ) { p->setVal(p->getMin()); }
if ( i/(int)pow(2.,ip) % 2==1 ) { p->setVal(p->getMax()); }
p->setRange(oldMin, oldMax);
}
// check if start parameters are sensible, skip if they're not
double startParChi2 = getChi2(w->pdf(pdfName));
if ( startParChi2>2000 ){
nErrors += 1;
continue;
}
// refit
RooFitResult *r2 = fitToMinBringBackAngles(w->pdf(pdfName), false, printlevel);
// In case the initial fit failed, accept the second one.
// If both failed, still select the second one and hope the
// next fit succeeds.
if ( !(r->edm()<1 && r->covQual()==3) ){
delete r;
r = r2;
}
else if ( r2->edm()<1 && r2->covQual()==3 && r2->minNll()<r->minNll() ){
// better minimum found!
delete r;
r = r2;
}
else{
delete r2;
}
}
if ( debug ) cout << endl;
if ( debug ) cout << "Utils::fitToMinForce() : nErrors = " << nErrors << endl;
RooMsgService::instance().setGlobalKillBelow(INFO);
// (re)set to best parameters
setParameters(w, parsName, r);
delete startPars;
return r;
}
void exercise_3() {
//Open the rootfile and get the workspace from the exercise_0
TFile fIn("exercise_0.root");
fIn.cd();
RooWorkspace *w = (RooWorkspace*)fIn.Get("w");
//You can set constant parameters that are known
//If you leave them floating, the fit procedure will determine their uncertainty
w->var("mean")->setConstant(kFALSE); //don't fix the mean, it's what we want to know the interval for!
w->var("sigma")->setConstant(kTRUE);
w->var("tau")->setConstant(kTRUE);
w->var("Nsig")->setConstant(kTRUE);
w->var("Nbkg")->setConstant(kTRUE);
//Set the RooModelConfig and let it know what the content of the workspace is about
ModelConfig model;
model.SetWorkspace(*w);
model.SetPdf("PDFtot");
//Let the model know what is the parameter of interest
RooRealVar* mean = w->var("mean");
mean->setRange(120., 130.); //this is mostly for plotting reasons
RooArgSet poi(*mean);
// set confidence level
double confidenceLevel = 0.68;
//Build the profile likelihood calculator
ProfileLikelihoodCalculator plc;
plc.SetData(*(w->data("PDFtotData")));
plc.SetModel(model);
plc.SetParameters(poi);
plc.SetConfidenceLevel(confidenceLevel);
//Get the interval
LikelihoodInterval* plInt = plc.GetInterval();
//Now let's do the same for the Bayesian Calculator
//Now we also need to specify a prior in the ModelConfig
//To be quicker, we'll use the PDF factory facility of RooWorkspace
//NB!! For simplicity, we are using a flat prior, but this doesn't mean it's the best choice!
w->factory("Uniform::prior(mean)");
model.SetPriorPdf(*w->pdf("prior"));
//Construct the bayesian calculator
BayesianCalculator bc(*(w->data("PDFtotData")), model);
bc.SetConfidenceLevel(confidenceLevel);
bc.SetParameters(poi);
SimpleInterval* bcInt = bc.GetInterval();
// Let's make a plot
TCanvas dataCanvas("dataCanvas");
dataCanvas.Divide(2,1);
dataCanvas.cd(1);
LikelihoodIntervalPlot plotInt((LikelihoodInterval*)plInt);
plotInt.SetTitle("Profile Likelihood Ratio and Posterior for mH");
plotInt.SetMaximum(3.);
plotInt.Draw();
dataCanvas.cd(2);
RooPlot *bcPlot = bc.GetPosteriorPlot();
bcPlot->Draw();
dataCanvas.SaveAs("exercise_3.gif");
//Now print the interval for mH for the two methods
cout << "PLC interval is [" << plInt->LowerLimit(*mean) << ", " <<
plInt->UpperLimit(*mean) << "]" << endl;
cout << "Bayesian interval is [" << bcInt->LowerLimit() << ", " <<
bcInt->UpperLimit() << "]" << endl;
}
int main(int argc, char* argv[]) {
doofit::builder::EasyPdf *epdf = new doofit::builder::EasyPdf();
epdf->Var("sig_yield");
epdf->Var("sig_yield").setVal(153000);
epdf->Var("sig_yield").setConstant(false);
//decay time
epdf->Var("obsTime");
epdf->Var("obsTime").SetTitle("t_{#kern[-0.2]{B}_{#kern[-0.1]{ d}}^{#kern[-0.1]{ 0}}}");
epdf->Var("obsTime").setUnit("ps");
epdf->Var("obsTime").setRange(0.,16.);
// tag, respectively the initial state of the produced B meson
epdf->Cat("obsTag");
epdf->Cat("obsTag").defineType("B_S",1);
epdf->Cat("obsTag").defineType("Bbar_S",-1);
//finalstate
epdf->Cat("catFinalState");
epdf->Cat("catFinalState").defineType("f",1);
epdf->Cat("catFinalState").defineType("fbar",-1);
epdf->Var("obsEtaOS");
epdf->Var("obsEtaOS").setRange(0.0,0.5);
std::vector<double> knots;
knots.push_back(0.07);
knots.push_back(0.10);
knots.push_back(0.138);
knots.push_back(0.16);
knots.push_back(0.23);
knots.push_back(0.28);
knots.push_back(0.35);
knots.push_back(0.42);
knots.push_back(0.44);
knots.push_back(0.48);
knots.push_back(0.5);
// empty arg list for coefficients
RooArgList* list = new RooArgList();
// create first coefficient
RooRealVar* coeff_first = &(epdf->Var("parCSpline1"));
coeff_first->setRange(0,10000);
coeff_first->setVal(1);
coeff_first->setConstant(false);
list->add( *coeff_first );
for (unsigned int i=1; i <= knots.size(); ++i){
std::string number = boost::lexical_cast<std::string>(i);
RooRealVar* coeff = &(epdf->Var("parCSpline"+number));
coeff->setRange(0,10000);
coeff->setVal(1);
coeff->setConstant(false);
list->add( *coeff );
}
// create last coefficient
RooRealVar* coeff_last = &(epdf->Var("parCSpline"+boost::lexical_cast<std::string>(knots.size())));
coeff_last->setRange(0,10000);
coeff_last->setVal(1);
coeff_last->setConstant(false);
list->add( *coeff_last );
list->Print();
doofit::roofit::pdfs::DooCubicSplinePdf splinePdf("splinePdf",epdf->Var("obsEtaOS"),knots,*list,0,0.5);
//doofit::roofit::pdfs::DooCubicSplinePdf* splinePdf = new doofit::roofit::pdfs::DooCubicSplinePdf("splinePdf", epdf->Var("obsEtaOS"), knots, *list,0,0.5);
//Koeffizienten
DecRateCoeff *coeff_c = new DecRateCoeff("coef_cos","coef_cos",DecRateCoeff::CPOdd,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("C_f"),epdf->Var("C_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Var("obsEtaOS"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_s = new DecRateCoeff("coef_sin","coef_sin",DecRateCoeff::CPOdd,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("S_f"),epdf->Var("S_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Var("obsEtaOS"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_sh = new DecRateCoeff("coef_sinh","coef_sinh",DecRateCoeff::CPEven,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("f1_f"),epdf->Var("f1_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Var("obsEtaOS"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
DecRateCoeff *coeff_ch = new DecRateCoeff("coef_cosh","coef_cosh",DecRateCoeff::CPEven,epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("f0_f"),epdf->Var("f0_fbar"),epdf->Var("obsEtaOS"),splinePdf,epdf->Var("tageff"),epdf->Var("obsEtaOS"),epdf->Var("asym_prod"),epdf->Var("asym_det"),epdf->Var("asym_tageff"));
epdf->AddRealToStore(coeff_ch);
epdf->AddRealToStore(coeff_sh);
epdf->AddRealToStore(coeff_c);
epdf->AddRealToStore(coeff_s);
///////////////////Generiere PDF's/////////////////////
//Zeit
epdf->GaussModel("resTimeGauss",epdf->Var("obsTime"),epdf->Var("allTimeResMean"),epdf->Var("allTimeReso"));
epdf->BDecay("pdfSigTime",epdf->Var("obsTime"),epdf->Var("tau"),epdf->Var("dgamma"),epdf->Real("coef_cosh"),epdf->Real("coef_sinh"),epdf->Real("coef_cos"),epdf->Real("coef_sin"),epdf->Var("deltaM"),epdf->Model("resTimeGauss"));
//Zusammenfassen der Parameter in einem RooArgSet
RooArgSet Observables;
Observables.add(RooArgSet( epdf->Var("obsTime"),epdf->Cat("catFinalState"),epdf->Cat("obsTag"),epdf->Var("obsEtaOS")));
epdf->Extend("pdfExtend", epdf->Pdf("pdfSigTime"),epdf->Real("sig_yield"));
//Multipliziere Signal und Untergrund PDF mit ihrer jeweiligen Zerfalls PDF//
//Untergrund * Zerfall
/*epdf->Product("pdf_bkg", RooArgSet(epdf->Pdf("pdf_bkg_mass_expo"), epdf->Pdf("pdf_bkg_mass_time")));
//Signal * Zerfall
epdf->Product("pdf_sig", RooArgSet(epdf->Pdf("pdf_sig_mass_gauss"),epdf->Pdf("pdfSigTime")));
//Addiere PDF's
epdf->Add("pdf_total", RooArgSet(epdf->Pdf("pdf_sig_mass_gauss*pdf_sig_time_decay"), epdf->Pdf("pdf_bkg_mass*pdf_bkg_time_decay")), RooArgSet(epdf->Var("bkg_Yield"),epdf->Var("sig_Yield")));*/
RooWorkspace ws;
ws.import(epdf->Pdf("pdfExtend"));
ws.defineSet("Observables",Observables, true);
ws.Print();
doofit::config::CommonConfig cfg_com("common");
cfg_com.InitializeOptions(argc, argv);
doofit::toy::ToyFactoryStdConfig cfg_tfac("toyfac");
cfg_tfac.InitializeOptions(cfg_com);
doofit::toy::ToyStudyStdConfig cfg_tstudy("toystudy");
cfg_tstudy.InitializeOptions(cfg_tfac);
// set a previously defined workspace to get PDF from (not mandatory, but convenient)
cfg_tfac.set_workspace(&ws);
// Check for a set --help flag and if so, print help and exit gracefully
// (recommended).
cfg_com.CheckHelpFlagAndPrintHelp();
// More custom code, e.g. to set options internally.
// Not required as configuration via command line/config file is enough.
cfg_com.PrintAll();
// Print overview of all options (optional)
// cfg_com.PrintAll();
// Initialize the toy factory module with the config objects and start
// generating toy samples.
doofit::toy::ToyFactoryStd tfac(cfg_com, cfg_tfac);
doofit::toy::ToyStudyStd tstudy(cfg_com, cfg_tstudy);
RooDataSet* data = tfac.Generate();
data->Print();
epdf->Pdf("pdfExtend").getParameters(data)->readFromFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-parameter_spline.txt");
epdf->Pdf("pdfExtend").getParameters(data)->writeToFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-parameter_spline.txt.new");
//epdf->Pdf("pdfExtend").fitTo(*data);
//epdf->Pdf("pdfExtend").getParameters(data)->writeToFile("/home/chasenberg/Repository/bachelor-template/ToyStudy/dootoycp-fit-result.txt");
RooFitResult* fit_result = epdf->Pdf("pdfExtend").fitTo(*data, RooFit::Save(true));
tstudy.StoreFitResult(fit_result);
/*using namespace doofit::plotting;
PlotConfig cfg_plot("cfg_plot");
cfg_plot.InitializeOptions();
cfg_plot.set_plot_directory("/net/lhcb-tank/home/chasenberg/Ergebnis/dootoycp_spline-lhcb/time/");
// plot PDF and directly specify components
Plot myplot(cfg_plot, epdf->Var("obsTime"), *data, RooArgList(epdf->Pdf("pdfExtend")));
myplot.PlotItLogNoLogY();
PlotConfig cfg_plotEta("cfg_plotEta");
cfg_plotEta.InitializeOptions();
cfg_plotEta.set_plot_directory("/net/lhcb-tank/home/chasenberg/Ergebnis/dootoycp_spline-lhcb/eta/");
// plot PDF and directly specify components
Plot myplotEta(cfg_plotEta, epdf->Var("obsEtaOS"), *data, RooArgList(splinePdf));
myplotEta.PlotIt();*/
}
void eregtestingExample(bool dobarrel=true, bool doele=true) {
//output dir
TString dirname = "/data/bendavid/eregexampletest/eregexampletest_test/";
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
TString infile = TString::Format("/data/bendavid/eregexampletest/%s",fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *meantgt = static_cast<RooGBRTargetFlex*>(ws->arg("sigmeant"));
RooRealVar *tgtvar = ws->var("tgtvar");
RooArgList vars;
vars.add(meantgt->FuncVars());
vars.add(*tgtvar);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
//TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
TFile *fdin = TFile::Open("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
//selection cuts for testing
TCut selcut;
if (dobarrel)
selcut = "ph.genpt>25. && ph.isbarrel && ph.ispromptgen";
else
selcut = "ph.genpt>25. && !ph.isbarrel && ph.ispromptgen";
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(evt%10==0)";
TCut prescale10alt = "(evt%10==1)";
TCut prescale25 = "(evt%25==0)";
TCut prescale100 = "(evt%100==0)";
TCut prescale1000 = "(evt%1000==0)";
TCut evenevents = "(evt%2==0)";
TCut oddevents = "(evt%2==1)";
TCut prescale100alt = "(evt%100==1)";
TCut prescale1000alt = "(evt%1000==1)";
TCut prescale50alt = "(evt%50==1)";
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
if (doele)
weightvar.SetTitle(prescale1000alt*selcut);
else
weightvar.SetTitle(prescale10alt*selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
//input variable corresponding to sceta
RooRealVar *scetavar = ws->var("var_1");
//regressed output functions
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.6,2.0,100);
hdata->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
craw->SaveAs("RawE.eps");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.eps");
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.eps");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.eps");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.eps");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.eps");
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.eps");
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor = hdata->createHistogram("hecor",*ecorvar);
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetXaxis()->SetRangeUser(0.6,1.2);
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
TCanvas *cresponse = new TCanvas;
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
cresponse->SaveAs("response.eps");
cresponse->SetLogy();
cresponse->SaveAs("responselog.eps");
printf("make fine histogram\n");
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(20e3,0.,2.));
printf("calc effsigma\n");
double effsigma = effSigma(hecorfine);
printf("effsigma = %5f\n",effsigma);
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
}
void compute_p0(const char* inFileName,
const char* wsName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData",
const char* asimov1DataName = "asimovData_1",
const char* conditional1Snapshot = "conditionalGlobs_1",
const char* nominalSnapshot = "nominalGlobs",
string smass = "130",
string folder = "test")
{
double mass;
stringstream massStr;
massStr << smass;
massStr >> mass;
double mu_profile_value = 1; // mu value to profile the obs data at wbefore generating the expected
bool doConditional = 1; // do conditional expected data
bool remakeData = 0; // handle unphysical pdf cases in H->ZZ->4l
bool doUncap = 1; // uncap p0
bool doInj = 0; // setup the poi for injection study (zero is faster if you're not)
bool doObs = 1; // compute median significance
bool doMedian = 1; // compute observed significance
TStopwatch timer;
timer.Start();
TFile f(inFileName);
RooWorkspace* ws = (RooWorkspace*)f.Get(wsName);
if (!ws)
{
cout << "ERROR::Workspace: " << wsName << " doesn't exist!" << endl;
return;
}
ModelConfig* mc = (ModelConfig*)ws->obj(modelConfigName);
if (!mc)
{
cout << "ERROR::ModelConfig: " << modelConfigName << " doesn't exist!" << endl;
return;
}
RooDataSet* data = (RooDataSet*)ws->data(dataName);
if (!data)
{
cout << "ERROR::Dataset: " << dataName << " doesn't exist!" << endl;
return;
}
mc->GetNuisanceParameters()->Print("v");
ROOT::Math::MinimizerOptions::SetDefaultMinimizer("Minuit2");
ROOT::Math::MinimizerOptions::SetDefaultStrategy(0);
ROOT::Math::MinimizerOptions::SetDefaultPrintLevel(1);
cout << "Setting max function calls" << endl;
ws->loadSnapshot("conditionalNuis_0");
RooArgSet nuis(*mc->GetNuisanceParameters());
RooRealVar* mu = (RooRealVar*)mc->GetParametersOfInterest()->first();
RooAbsPdf* pdf = mc->GetPdf();
string condSnapshot(conditional1Snapshot);
RooArgSet nuis_tmp2 = *mc->GetNuisanceParameters();
RooNLLVar* obs_nll = doObs ? (RooNLLVar*)pdf->createNLL(*data, Constrain(nuis_tmp2)) : NULL;
RooDataSet* asimovData1 = (RooDataSet*)ws->data(asimov1DataName);
RooRealVar* emb = (RooRealVar*)mc->GetNuisanceParameters()->find("ATLAS_EMB");
if (!asimovData1 || (string(inFileName).find("ic10") != string::npos && emb))
{
if (emb) emb->setVal(0.7);
cout << "Asimov data doesn't exist! Please, allow me to build one for you..." << endl;
string mu_str, mu_prof_str;
asimovData1 = makeAsimovData(mc, doConditional, ws, obs_nll, 1, &mu_str, &mu_prof_str, mu_profile_value, true);
condSnapshot="conditionalGlobs"+mu_prof_str;
}
if (!doUncap) mu->setRange(0, 40);
else mu->setRange(-40, 40);
RooAbsPdf* pdf = mc->GetPdf();
RooArgSet nuis_tmp1 = *mc->GetNuisanceParameters();
RooNLLVar* asimov_nll = (RooNLLVar*)pdf->createNLL(*asimovData1, Constrain(nuis_tmp1));
//do asimov
mu->setVal(1);
mu->setConstant(0);
if (!doInj) mu->setConstant(1);
int status,sign;
double med_sig=0,obs_sig=0,asimov_q0=0,obs_q0=0;
if (doMedian)
{
ws->loadSnapshot(condSnapshot.c_str());
if (doInj) ws->loadSnapshot("conditionalNuis_inj");
else ws->loadSnapshot("conditionalNuis_1");
mc->GetGlobalObservables()->Print("v");
mu->setVal(0);
mu->setConstant(1);
status = minimize(asimov_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov_nll_cond = asimov_nll->getVal();
mu->setVal(1);
if (doInj) ws->loadSnapshot("conditionalNuis_inj");
else ws->loadSnapshot("conditionalNuis_1");
if (doInj) mu->setConstant(0);
status = minimize(asimov_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(asimov_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double asimov_nll_min = asimov_nll->getVal();
asimov_q0 = 2*(asimov_nll_cond - asimov_nll_min);
if (doUncap && mu->getVal() < 0) asimov_q0 = -asimov_q0;
sign = int(asimov_q0 != 0 ? asimov_q0/fabs(asimov_q0) : 0);
med_sig = sign*sqrt(fabs(asimov_q0));
ws->loadSnapshot(nominalSnapshot);
}
if (doObs)
{
ws->loadSnapshot("conditionalNuis_0");
mu->setVal(0);
mu->setConstant(1);
status = minimize(obs_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(obs_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double obs_nll_cond = obs_nll->getVal();
mu->setConstant(0);
status = minimize(obs_nll, ws);
if (status < 0)
{
cout << "Retrying with conditional snapshot at mu=1" << endl;
ws->loadSnapshot("conditionalNuis_0");
status = minimize(obs_nll, ws);
if (status >= 0) cout << "Success!" << endl;
}
double obs_nll_min = obs_nll->getVal();
obs_q0 = 2*(obs_nll_cond - obs_nll_min);
if (doUncap && mu->getVal() < 0) obs_q0 = -obs_q0;
sign = int(obs_q0 == 0 ? 0 : obs_q0 / fabs(obs_q0));
if (!doUncap && (obs_q0 < 0 && obs_q0 > -0.1 || mu->getVal() < 0.001)) obs_sig = 0;
else obs_sig = sign*sqrt(fabs(obs_q0));
}
// Report results
cout << "obs: " << obs_sig << endl;
cout << "Observed significance: " << obs_sig << endl;
cout << "Corresponding to a p-value of " << (1-ROOT::Math::gaussian_cdf( obs_sig )) << endl;
if (med_sig)
{
cout << "Median test stat val: " << asimov_q0 << endl;
cout << "Median significance: " << med_sig << endl;
}
f.Close();
stringstream fileName;
fileName << "root-files/" << folder << "/" << mass << ".root";
system(("mkdir -vp root-files/" + folder).c_str());
TFile f2(fileName.str().c_str(),"recreate");
TH1D* h_hypo = new TH1D("hypo","hypo",2,0,2);
h_hypo->SetBinContent(1, obs_sig);
h_hypo->SetBinContent(2, med_sig);
f2.Write();
f2.Close();
timer.Stop();
timer.Print();
}
void fit_mass(TString fileN="") {//suffix added before file extension, e.g., '.pdf'
TString placeholder;//to add strings before using them, e.g., for saving text files
gROOT->SetBatch(kTRUE);
gROOT->ProcessLine(".x /afs/cern.ch/user/m/mwilkins/cmtuser/src/lhcbStyle.C");
// gStyle->SetPadTickX(1);
// gStyle->SetPadTickY(1);
// gStyle->SetPadLeftMargin(0.15);
// gStyle->SetTextSize(0.3);
// //open file and get histogram
// TFile *inHistos = new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/data/histos_data.root", "READ");
// TH1F * h100 = (TH1F*)inHistos->Get("h70");
// cout<<"data histogram gotten"<<endl;
//unbinned
TFile *hastree = new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/data/cutfile_Optimized.root", "READ");
TTree * h100 = (TTree*)hastree->Get("mytree");
cout<<"tree gotten"<<endl;
TFile *SMChistos= new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/MC/withKScut/histos_SMCfile_fullMC.root", "READ");
cout<<"SMC file opened"<<endl;
TH1F *SMCh = (TH1F*)SMChistos->Get("h00");
cout<<"SMC hist gotten"<<endl;
RooRealVar *mass = new RooRealVar("Bs_LOKI_MASS_JpsiConstr","m(J/#psi #Lambda)",4100,6100,"MeV");
mass->setRange("bkg1",4300,4800);
mass->setRange("bkg2",5700,5950);
mass->setRange("bkg3",4300,5500);
mass->setRange("bkg4",5100,5500);
mass->setRange("L",5350,5950);
mass->setRange("tot",4300,5950);
cout<<"mass declared"<<endl;
// RooDataHist *data = new RooDataHist("data","1D",RooArgList(*mass),h100);
//unbinned
RooDataSet *data = new RooDataSet("data","1D",h100,*mass);
cout<<"data declared"<<endl;
RooDataHist *SMC = new RooDataHist("SMC","1D",RooArgList(*mass),SMCh);
cout<<"SMC hist assigned to RooDataHist"<<endl;
// Construct Pdf Model
// /\0
//gaussian
RooRealVar mean1L("mean1L","/\\ gaus 1: mean",5621.103095,5525,5700);
RooRealVar sig1L("sig1L","/\\ gaus 1: sigma",6.898126,0,100);
RooGaussian gau1L("gau1L","#Lambda signal: gaussian 1",*mass,mean1L,sig1L);
RooFormulaVar mean2L("mean2L","@0",mean1L);
RooRealVar sig2L("sig2L","/\\ gaus 2: sigma",14.693117,0,100);
RooGaussian gau2L("gau2L","#Lambda signal: gaussian 2",*mass,mean2L,sig2L);
RooRealVar f1L("f1L","/\\ signal: fraction gaussian 1",0.748776,0,1);
RooAddPdf sigL("sigL","#Lambda signal",RooArgList(gau1L,gau2L),RooArgList(f1L));
// //CB
// RooRealVar mean3L("mean3L","/\\ CB: mean",5621.001,5525,5700);
// RooRealVar sig3L("sig3L","/\\ CB: sigma",5.161,0,100);
// RooRealVar alphaL3("alphaL3","/\\ CB: alpha",2.077,0,1000);
// RooRealVar nL3("nL1","/\\ CB: n",0.286,0,1000);
// RooCBShape CBL("CBL","#Lambda signal: CB",*mass,mean3L,sig3L,alphaL3,nL3);
// RooRealVar mean4L("mean4L","/\\ gaus: mean",5621.804,5525,5700);
// RooRealVar sig4L("sig4L","/\\ gaus: sigma",10.819,0,100);
// RooGaussian gauL("gauL","#Lambda signal: gaussian",*mass,mean4L,sig4L);
// RooRealVar f1L("f1L","/\\ signal: fraction CB",0.578,0,1);
// RooAddPdf sigL("sigL","#Lambda signal",RooArgList(CBL,gauL),RooArgList(f1L));
// sigma0
//using RooHistPdf from MC--no need to build pdf here
RooHistPdf sigS = makeroohistpdf(SMC,mass,"sigS","#Sigma^{0} signal (RooHistPdf)");
// /\*
cout<<"Lst stuff"<<endl;
RooRealVar meanLst1("meanLst1","/\\*(misc.): mean1",5011.031237,4900,5100);
RooRealVar sigLst1("sigLst1","/\\*(misc.): sigma1",70.522092,0,100);
RooRealVar meanLst2("mean5Lst2","/\\*(1405): mean2",5245.261703,5100,5350);
RooRealVar sigLst2("sigLst2","/\\*(1405): sigma2",64.564763,0,100);
RooRealVar alphaLst2("alphaLst2","/\\*(1405): alpha2",29.150301);
RooRealVar nLst2("nLst2","/\\*(1405): n2",4.615817,0,50);
RooGaussian gauLst1("gauLst1","#Lambda*(misc.), gaus",*mass,meanLst1,sigLst1);
RooCBShape gauLst2("gauLst2","#Lambda*(1405), CB",*mass,meanLst2,sigLst2,alphaLst2,nLst2);
// RooRealVar fLst1("fLst1","/\\* bkg: fraction gaus 1",0.743,0,1);
// RooAddPdf bkgLst("bkgLst","#Lambda* signal",RooArgList(gauLst1,gauLst2),RooArgList(fLst1));
//Poly func BKG mass
// RooRealVar b0("b0","Background: Chebychev b0",-1.071,-10000,10000);
RooRealVar b1("b1","Background: Chebychev b1",-1.323004,-10,-0.00000000000000000000001);
RooRealVar b2("b2","Background: Chebychev b2",0.145494,0,10);
RooRealVar b3("b3","Background: Chebychev b3",-0.316,-10000,10000);
RooRealVar b4("b4","Background: Chebychev b4",0.102,-10000,10000);
RooRealVar b5("b5","Background: Chebychev b5",0.014,-10000,10000);
RooRealVar b6("b6","Background: Chebychev b6",-0.015,-10000,10000);
RooRealVar b7("b7","Background: Chebychev b7",0.012,-10000,10000);
RooArgList bList(b1,b2);
RooChebychev bkg("bkg","Background", *mass, bList);
// TF1 *ep = new TF1("ep","[2]*exp([0]*x+[1]*x*x)",4300,5950);
// ep->SetParameter(0,1);
// ep->SetParameter(1,-1);
// ep->SetParameter(2,2000);
// ep->SetParName(0,"a");
// ep->SetParName(1,"b");
// ep->SetParName(2,"c");
// RooRealVar a("a","Background: Coefficent of x",1,-10000,10000);
// RooRealVar b("b","Background: Coefficent of x*x",-1,-10000,10000);
// RooRealVar c("c","Background: Coefficent of exp()",2000,-10000,10000);
// RooTFnPdfBinding bkg("ep","ep",ep,RooArgList(*mass,a,b));
//number of each shape
RooRealVar nbkg("nbkg","N bkg",2165.490249,0,100000000);
RooRealVar nsigL("nsigL","N /\\",1689.637290,0,1000000000);
RooRealVar nsigS("nsigS","N sigma",0.000002,0,10000000000);
RooRealVar ngauLst1("ngauLst1","N /\\*(misc.)",439.812103,0,10000000000);
RooRealVar ngauLst2("ngauLst2","N /\\*(1405)",152.061617,0,10000000000);
RooRealVar nbkgLst("nbkgLst","N /\\*",591.828,0,1000000000);
//add shapes and their number to a totalPdf
RooArgList shapes;
RooArgList yields;
shapes.add(sigL); yields.add(nsigL);
shapes.add(sigS); yields.add(nsigS);
// shapes.add(bkgLst); yields.add(nbkgLst);
shapes.add(gauLst1); yields.add(ngauLst1);
shapes.add(gauLst2); yields.add(ngauLst2);
shapes.add(bkg); yields.add(nbkg);
RooAddPdf totalPdf("totalPdf","totalPdf",shapes,yields);
//fit the totalPdf
RooAbsReal * nll = totalPdf.createNLL(*data,Extended(kTRUE),Range("tot"));
RooMinuit m(*nll);
m.setVerbose(kFALSE);
m.migrad();
m.minos();
m.minos();
//display and save information
ofstream textfile;//create text file to hold data
placeholder = "plots/fit"+fileN+".txt";
textfile.open(placeholder);
TString outputtext;//for useful text
//plot things
RooPlot *framex = mass->frame();
framex->GetYaxis()->SetTitle("Events/(5 MeV)");
data->plotOn(framex,Name("Hist"),MarkerColor(kBlack),LineColor(kBlack),DataError(RooAbsData::SumW2));
totalPdf.plotOn(framex,Name("curvetot"),LineColor(kBlue));
RooArgSet* totalPdfComponents = totalPdf.getComponents();
TIterator* itertPC = totalPdfComponents->createIterator();
RooAddPdf* vartPC = (RooAddPdf*) itertPC->Next();
vartPC = (RooAddPdf*) itertPC->Next();//skip totalPdf
int i=0;//color index
TLegend *leg = new TLegend(0.2, 0.02, .4, .42);
leg->SetTextSize(0.06);
leg->AddEntry(framex->findObject("curvetot"),"Total PDF","l");
while(vartPC){//loop over compotents of totalPdf
TString vartPCtitle = vartPC->GetTitle();
TIterator* itercompPars;//forward declare so it persists outside the if statement
RooRealVar* varcompPars;
if(!(vartPCtitle.Contains(":")||vartPCtitle.Contains("@"))){//only for non-sub-shapes
while(i==0||i==10||i==4||i==1||i==5||(i>=10&&i<=27))i++;//avoid white and blue and black and yellow and horribleness
RooArgSet* compPars = vartPC->getParameters(data);//set of the parameters of the component the loop is on
itercompPars = compPars->createIterator();
varcompPars = (RooRealVar*) itercompPars->Next();
while(varcompPars){//write and print mean, sig, etc. of sub-shapes
TString vartitle = varcompPars->GetTitle();
double varval = varcompPars->getVal();
TString varvalstring = Form("%f",varval);
double hi = varcompPars->getErrorHi();
TString varerrorstring = "[exact]";
if(hi!=-1){
double lo = varcompPars->getErrorLo();
double varerror = TMath::Max(fabs(lo),hi);
varerrorstring = Form("%E",varerror);
}
outputtext = vartitle+" = "+varvalstring+" +/- "+varerrorstring;
textfile<<outputtext<<endl;
cout<<outputtext<<endl;
varcompPars = (RooRealVar*) itercompPars->Next();
}
totalPdf.plotOn(framex,Name(vartPC->GetName()),LineStyle(kDashed),LineColor(i),Components(vartPC->GetName()));
leg->AddEntry(framex->findObject(vartPC->GetName()),vartPCtitle,"l");
i++;
}
vartPC = (RooAddPdf*) itertPC->Next();
itercompPars->Reset();//make sure it's ready for the next vartPC
}
// Calculate chi2/ndf
RooArgSet *floatpar = totalPdf.getParameters(data);
int floatpars = (floatpar->selectByAttrib("Constant",kFALSE))->getSize();
Double_t chi2 = framex->chiSquare("curvetot","Hist",floatpars);
TString chi2string = Form("%f",chi2);
//create text box to list important parameters on the plot
// TPaveText* txt = new TPaveText(0.1,0.5,0.7,0.9,"NBNDC");
// txt->SetTextSize(0.06);
// txt->SetTextColor(kBlack);
// txt->SetBorderSize(0);
// txt->SetFillColor(0);
// txt->SetFillStyle(0);
outputtext = "#chi^{2}/N_{DoF} = "+chi2string;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
// txt->AddText(outputtext);
// Print stuff
TIterator* iteryields = yields.createIterator();
RooRealVar* varyields = (RooRealVar*) iteryields->Next();//only inherits things from TObject unless class specified
vector<double> Y, E;//holds yields and associated errors
vector<TString> YS, ES;//holds strings of the corresponding yields
int j=0;//count vector position
int jS=0, jL=0;//these hold the position of the S and L results;initialized in case there is no nsigS or nsigL
while(varyields){//loop over yields
TString varname = varyields->GetName();
TString vartitle = varyields->GetTitle();
double varval = varyields->getVal();
Y.push_back(varval);
double lo = varyields->getErrorLo();
double hi = varyields->getErrorHi();
E.push_back(TMath::Max(fabs(lo),hi));
YS.push_back(Form("%f",Y[j]));
ES.push_back(Form("%f",E[j]));
if(varname=="nsigS") jS=j;
if(varname=="nsigL") jL=j;
outputtext = vartitle+" = "+YS[j]+" +/- "+ES[j];
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
varyields = (RooRealVar*) iteryields->Next();
j++;
}
//S/L
double result = Y[jS]/Y[jL];
cout<<"result declared"<<endl;
double E_result = TMath::Abs(result)*sqrt(pow(E[jS]/Y[jS],2)+pow(E[jL]/Y[jL],2));
cout<<"E_result declared"<<endl;
TString resultstring = Form("%E",result);
TString E_resultstring = Form("%E",E_result);
outputtext = "Y_{#Sigma^{0}}/Y_{#Lambda} = "+resultstring+" +/- "+E_resultstring;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
double resultlimit = (Y[jS]+E[jS])/(Y[jL]-E[jL]);
outputtext = Form("%E",resultlimit);
outputtext = "limit = "+outputtext;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
// Create canvas and pads, set style
TCanvas *c1 = new TCanvas("c1","data fits",1200,800);
TPad *pad1 = new TPad("pad1","pad1",0.0,0.3,1.0,1.0);
TPad *pad2 = new TPad("pad2","pad2",0.0,0.0,1.0,0.3);
pad1->SetBottomMargin(0);
pad2->SetTopMargin(0);
pad2->SetBottomMargin(0.5);
pad2->SetBorderMode(0);
pad1->SetBorderMode(0);
c1->SetBorderMode(0);
pad2->Draw();
pad1->Draw();
pad1->cd();
framex->SetMinimum(1);
framex->SetMaximum(3000);
framex->addObject(leg);//add legend to frame
//framex->addObject(txt);//add text to frame
gPad->SetTopMargin(0.06);
pad1->SetLogy();
// pad1->Range(4100,0,6100,0.0005);
pad1->Update();
framex->Draw();
// Pull distribution
RooPlot *framex2 = mass->frame();
RooHist* hpull = framex->pullHist("Hist","curvetot");
framex2->addPlotable(hpull,"P");
hpull->SetLineColor(kBlack);
hpull->SetMarkerColor(kBlack);
framex2->SetTitle(0);
framex2->GetYaxis()->SetTitle("Pull");
framex2->GetYaxis()->SetTitleSize(0.15);
framex2->GetYaxis()->SetLabelSize(0.15);
framex2->GetXaxis()->SetTitleSize(0.2);
framex2->GetXaxis()->SetLabelSize(0.15);
framex2->GetYaxis()->CenterTitle();
framex2->GetYaxis()->SetTitleOffset(0.45);
framex2->GetXaxis()->SetTitleOffset(1.1);
framex2->GetYaxis()->SetNdivisions(505);
framex2->GetYaxis()->SetRangeUser(-8.8,8.8);
pad2->cd();
framex2->Draw();
c1->cd();
placeholder = "plots/fit"+fileN+".eps";
c1->Print(placeholder);
placeholder = "plots/fit"+fileN+".C";
c1->SaveAs(placeholder);
textfile.close();
}
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");
}
}
void rf208_convolution()
{
// S e t u p c o m p o n e n t p d f s
// ---------------------------------------
// Construct observable
RooRealVar t("t","t",-10,30) ;
// Construct landau(t,ml,sl) ;
RooRealVar ml("ml","mean bw",5.,-20,20) ;
RooRealVar sl("sl","sigma bw",1,0.1,10) ;
RooBreitWigner bw("bw","bw",t,ml,sl) ;
// Construct gauss(t,mg,sg)
RooRealVar mg("mg","mg",0) ;
RooRealVar sg("sg","sg",2,0.1,10) ;
RooGaussian gauss("gauss","gauss",t,mg,sg) ;
// C o n s t r u c t c o n v o l u t i o n p d f
// ---------------------------------------
// Set #bins to be used for FFT sampling to 10000
t.setBins(10000,"cache") ;
// Construct landau (x) gauss
RooFFTConvPdf lxg("lxg","bw (X) gauss",t,bw,gauss) ;
// S a m p l e , f i t a n d p l o t c o n v o l u t e d p d f
// ----------------------------------------------------------------------
// Sample 1000 events in x from gxlx
RooDataSet* data = lxg.generate(t,10000) ;
// Fit gxlx to data
lxg.fitTo(*data) ;
// Plot data, landau pdf, landau (X) gauss pdf
RooPlot* frame = t.frame(Title("landau (x) gauss convolution")) ;
data->plotOn(frame) ;
lxg.plotOn(frame) ;
bw.plotOn(frame,LineStyle(kDashed)) ;
// Draw frame on canvas
new TCanvas("rf208_convolution","rf208_convolution",600,600) ;
gPad->SetLeftMargin(0.15) ; frame->GetYaxis()->SetTitleOffset(1.4) ; frame->Draw() ;
//add a variable to the dataset
RooFormulaVar *r_formula = new RooFormulaVar("r_formula","","@0",t);
RooRealVar* r = (RooRealVar*) data->addColumn(*r_formula);
r->SetName("r");
r->SetTitle("r");
RooDataSet* data_r =(RooDataSet*) data->reduce(*r, "");
r->setRange("sigrange",-10.,30.);
RooPlot* r_frame = r->frame(Range("sigRange"),Title(" r (x) gauss convolution")) ;
data_r->plotOn(r_frame, MarkerColor(kRed));
r_frame->GetXaxis()->SetRangeUser(-10., 30.);
r_frame->Draw() ;
}
vector<Double_t*> simFit(bool makeSoupFit_ = false,
const string tnp_ = "etoTauMargLooseNoCracks70",
const string category_ = "tauAntiEMVA",
const string bin_ = "abseta<1.5",
const float binCenter_ = 0.75,
const float binWidth_ = 0.75,
const float xLow_=60,
const float xHigh_=120,
bool SumW2_ = false,
bool verbose_ = true){
vector<Double_t*> out;
//return out;
//TFile *test = new TFile( outFile->GetName(),"UPDATE");
// output file
TFile *test = new TFile( Form("EtoTauPlotsFit_%s_%s_%f.root",tnp_.c_str(),category_.c_str(),binCenter_),"RECREATE");
test->mkdir(Form("bin%f",binCenter_));
TCanvas *c = new TCanvas("fitCanvas",Form("fitCanvas_%s_%s",tnp_.c_str(),bin_.c_str()),10,30,650,600);
c->SetGrid(0,0);
c->SetFillStyle(4000);
c->SetFillColor(10);
c->SetTicky();
c->SetObjectStat(0);
TCanvas *c2 = new TCanvas("fitCanvasTemplate",Form("fitCanvasTemplate_%s_%s",tnp_.c_str(),bin_.c_str()),10,30,650,600);
c2->SetGrid(0,0);
c2->SetFillStyle(4000);
c2->SetFillColor(10);
c2->SetTicky();
c2->SetObjectStat(0);
// input files
TFile fsup("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup.root");
TFile fbkg("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup_bkg.root");
TFile fsgn("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup_sgn.root");
TFile fdat("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_Data.root");
// data from 2iter:
//TFile fdat("/data_CMS/cms/lbianchini/35pb/testNewWriteFromPAT_Data.root");
//********************** signal only tree *************************/
TTree *fullTreeSgn = (TTree*)fsgn.Get((tnp_+"/fitter_tree").c_str());
TH1F* hSall = new TH1F("hSall","",1,0,150);
TH1F* hSPall = new TH1F("hSPall","",1,0,150);
TH1F* hS = new TH1F("hS","",1,0,150);
TH1F* hSP = new TH1F("hSP","",1,0,150);
fullTreeSgn->Draw("mass>>hS",Form("weight*(%s && mass>%f && mass<%f && mcTrue && signalPFChargedHadrCands<1.5)",bin_.c_str(),xLow_,xHigh_));
fullTreeSgn->Draw("mass>>hSall",Form("weight*(%s && mass>%f && mass<%f)",bin_.c_str(),xLow_,xHigh_));
float SGNtrue = hS->Integral();
float SGNall = hSall->Integral();
fullTreeSgn->Draw("mass>>hSP",Form("weight*(%s && %s>0 && mass>%f && mass<%f && mcTrue && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
fullTreeSgn->Draw("mass>>hSPall",Form("weight*(%s && %s>0 && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
float SGNtruePass = hSP->Integral();
float SGNallPass = hSPall->Integral();
//********************** background only tree *************************//
TTree *fullTreeBkg = (TTree*)fbkg.Get((tnp_+"/fitter_tree").c_str());
TH1F* hB = new TH1F("hB","",1,0,150);
TH1F* hBP = new TH1F("hBP","",1,0,150);
fullTreeBkg->Draw("mass>>hB",Form("weight*(%s && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),xLow_,xHigh_));
float BKG = hB->Integral();
float BKGUnWeighted = hB->GetEntries();
fullTreeBkg->Draw("mass>>hBP",Form("weight*(%s && %s>0 && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
float BKGPass = hBP->Integral();
float BKGUnWeightedPass = hBP->GetEntries();
float BKGFail = BKG-BKGPass;
cout << "*********** BKGFail " << BKGFail << endl;
//********************** soup tree *************************//
TTree *fullTreeSoup = (TTree*)fsup.Get((tnp_+"/fitter_tree").c_str());
//********************** data tree *************************//
TTree *fullTreeData = (TTree*)fdat.Get((tnp_+"/fitter_tree").c_str());
//********************** workspace ***********************//
RooWorkspace *w = new RooWorkspace("w","w");
// tree variables to be imported
w->factory("mass[30,120]");
w->factory("weight[0,10000]");
w->factory("abseta[0,2.5]");
w->factory("pt[0,200]");
w->factory("mcTrue[0,1]");
w->factory("signalPFChargedHadrCands[0,10]");
w->factory((category_+"[0,1]").c_str());
// background pass pdf for MC
w->factory("RooExponential::McBackgroundPdfP(mass,McCP[0,-10,10])");
// background fail pdf for MC
w->factory("RooExponential::McBackgroundPdfF(mass,McCF[0,-10,10])");
// background pass pdf for Data
w->factory("RooExponential::DataBackgroundPdfP(mass,DataCP[0,-10,10])");
// background fail pdf for Data
w->factory("RooExponential::DataBackgroundPdfF(mass,DataCF[0,-10,10])");
// fit parameters for background
w->factory("McEfficiency[0.04,0,1]");
w->factory("McNumSgn[0,1000000]");
w->factory("McNumBkgP[0,100000]");
w->factory("McNumBkgF[0,100000]");
w->factory("expr::McNumSgnP('McEfficiency*McNumSgn',McEfficiency,McNumSgn)");
w->factory("expr::McNumSgnF('(1-McEfficiency)*McNumSgn',McEfficiency,McNumSgn)");
w->factory("McPassing[pass=1,fail=0]");
// fit parameters for data
w->factory("DataEfficiency[0.1,0,1]");
w->factory("DataNumSgn[0,1000000]");
w->factory("DataNumBkgP[0,1000000]");
w->factory("DataNumBkgF[0,10000]");
w->factory("expr::DataNumSgnP('DataEfficiency*DataNumSgn',DataEfficiency,DataNumSgn)");
w->factory("expr::DataNumSgnF('(1-DataEfficiency)*DataNumSgn',DataEfficiency,DataNumSgn)");
w->factory("DataPassing[pass=1,fail=0]");
RooRealVar *weight = w->var("weight");
RooRealVar *abseta = w->var("abseta");
RooRealVar *pt = w->var("pt");
RooRealVar *mass = w->var("mass");
mass->setRange(xLow_,xHigh_);
RooRealVar *mcTrue = w->var("mcTrue");
RooRealVar *cut = w->var( category_.c_str() );
RooRealVar *signalPFChargedHadrCands = w->var("signalPFChargedHadrCands");
// build the template for the signal pass sample:
RooDataSet templateP("templateP","dataset for signal-pass template", RooArgSet(*mass,*weight,*abseta,*pt,*cut,*mcTrue,*signalPFChargedHadrCands), Import( *fullTreeSgn ), /*WeightVar( *weight ),*/ Cut( Form("(mcTrue && %s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()) ) );
// build the template for the signal fail sample:
RooDataSet templateF("templateF","dataset for signal-fail template", RooArgSet(*mass,*weight,*abseta,*pt,*cut,*mcTrue,*signalPFChargedHadrCands), Import( *fullTreeSgn ), /*WeightVar( *weight ),*/ Cut( Form("(mcTrue && %s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()) ) );
mass->setBins(24);
RooDataHist templateHistP("templateHistP","",RooArgSet(*mass), templateP, 1.0);
RooHistPdf TemplateSignalPdfP("TemplateSignalPdfP","",RooArgSet(*mass),templateHistP);
w->import(TemplateSignalPdfP);
mass->setBins(24);
RooDataHist templateHistF("templateHistF","",RooArgSet(*mass),templateF,1.0);
RooHistPdf TemplateSignalPdfF("TemplateSignalPdfF","",RooArgSet(*mass),templateHistF);
w->import(TemplateSignalPdfF);
mass->setBins(10000,"fft");
RooPlot* TemplateFrameP = mass->frame(Bins(24),Title("Template passing"));
templateP.plotOn(TemplateFrameP);
w->pdf("TemplateSignalPdfP")->plotOn(TemplateFrameP);
RooPlot* TemplateFrameF = mass->frame(Bins(24),Title("Template failing"));
templateF.plotOn(TemplateFrameF);
w->pdf("TemplateSignalPdfF")->plotOn(TemplateFrameF);
//w->factory("RooFFTConvPdf::McSignalPdfP(mass,TemplateSignalPdfP,RooTruthModel::McResolModP(mass))");
//w->factory("RooFFTConvPdf::McSignalPdfF(mass,TemplateSignalPdfF,RooTruthModel::McResolModF(mass))");
// FOR GREGORY: PROBLEM WHEN TRY TO USE THE PURE TEMPLATE =>
RooHistPdf McSignalPdfP("McSignalPdfP","McSignalPdfP",RooArgSet(*mass),templateHistP);
RooHistPdf McSignalPdfF("McSignalPdfF","McSignalPdfF",RooArgSet(*mass),templateHistF);
w->import(McSignalPdfP);
w->import(McSignalPdfF);
// FOR GREGORY: FOR DATA, CONVOLUTION IS OK =>
w->factory("RooFFTConvPdf::DataSignalPdfP(mass,TemplateSignalPdfP,RooGaussian::DataResolModP(mass,DataMeanResP[0.0,-5.,5.],DataSigmaResP[0.5,0.,10]))");
w->factory("RooFFTConvPdf::DataSignalPdfF(mass,TemplateSignalPdfF,RooGaussian::DataResolModF(mass,DataMeanResF[-5.,-10.,10.],DataSigmaResF[0.5,0.,10]))");
//w->factory("RooCBShape::DataSignalPdfF(mass,DataMeanF[91.2,88,95.],DataSigmaF[3,0.5,8],DataAlfaF[1.8,0.,10],DataNF[1.0,1e-06,10])");
//w->factory("RooFFTConvPdf::DataSignalPdfF(mass,RooVoigtian::DataVoigF(mass,DataMeanF[85,80,95],DataWidthF[2.49],DataSigmaF[3,0.5,10]),RooCBShape::DataResolModF(mass,DataMeanResF[0.5,0.,10.],DataSigmaResF[0.5,0.,10],DataAlphaResF[0.5,0.,10],DataNResF[1.0,1e-06,10]))");
//w->factory("SUM::DataSignalPdfF(fVBP[0.5,0,1]*RooBifurGauss::bifF(mass,DataMeanResF[91.2,80,95],sigmaLF[10,0.5,40],sigmaRF[0.]), RooVoigtian::voigF(mass, DataMeanResF, widthF[2.49], sigmaVoigF[5,0.1,10]) )" );
// composite model pass for MC
w->factory("SUM::McModelP(McNumSgnP*McSignalPdfP,McNumBkgP*McBackgroundPdfP)");
w->factory("SUM::McModelF(McNumSgnF*McSignalPdfF,McNumBkgF*McBackgroundPdfF)");
// composite model pass for data
w->factory("SUM::DataModelP(DataNumSgnP*DataSignalPdfP,DataNumBkgP*DataBackgroundPdfP)");
w->factory("SUM::DataModelF(DataNumSgnF*DataSignalPdfF,DataNumBkgF*DataBackgroundPdfF)");
// simultaneous fir for MC
w->factory("SIMUL::McModel(McPassing,pass=McModelP,fail=McModelF)");
// simultaneous fir for data
w->factory("SIMUL::DataModel(DataPassing,pass=DataModelP,fail=DataModelF)");
w->Print("V");
w->saveSnapshot("clean", w->allVars());
w->loadSnapshot("clean");
/****************** sim fit to soup **************************/
///////////////////////////////////////////////////////////////
TFile *f = new TFile("dummySoup.root","RECREATE");
TTree* cutTreeSoupP = fullTreeSoup->CopyTree(Form("(%s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
TTree* cutTreeSoupF = fullTreeSoup->CopyTree(Form("(%s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
RooDataSet McDataP("McDataP","dataset pass for the soup", RooArgSet(*mass), Import( *cutTreeSoupP ) );
RooDataSet McDataF("McDataF","dataset fail for the soup", RooArgSet(*mass), Import( *cutTreeSoupF ) );
RooDataHist McCombData("McCombData","combined data for the soup", RooArgSet(*mass), Index(*(w->cat("McPassing"))), Import("pass", *(McDataP.createHistogram("histoP",*mass)) ), Import("fail",*(McDataF.createHistogram("histoF",*mass)) ) ) ;
RooPlot* McFrameP = 0;
RooPlot* McFrameF = 0;
RooRealVar* McEffFit = 0;
if(makeSoupFit_){
cout << "**************** N bins in mass " << w->var("mass")->getBins() << endl;
RooFitResult* ResMcCombinedFit = w->pdf("McModel")->fitTo(McCombData, Extended(1), Minos(1), Save(1), SumW2Error( SumW2_ ), Range(xLow_,xHigh_), NumCPU(4) /*, ExternalConstraints( *(w->pdf("ConstrainMcNumBkgF")) )*/ );
test->cd(Form("bin%f",binCenter_));
ResMcCombinedFit->Write("McFitResults_Combined");
RooArgSet McFitParam(ResMcCombinedFit->floatParsFinal());
McEffFit = (RooRealVar*)(&McFitParam["McEfficiency"]);
RooRealVar* McNumSigFit = (RooRealVar*)(&McFitParam["McNumSgn"]);
RooRealVar* McNumBkgPFit = (RooRealVar*)(&McFitParam["McNumBkgP"]);
RooRealVar* McNumBkgFFit = (RooRealVar*)(&McFitParam["McNumBkgF"]);
McFrameP = mass->frame(Bins(24),Title("MC: passing sample"));
McCombData.plotOn(McFrameP,Cut("McPassing==McPassing::pass"));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McSignalPdfP"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McBackgroundPdfP"), LineColor(kGreen),Range(xLow_,xHigh_));
McFrameF = mass->frame(Bins(24),Title("MC: failing sample"));
McCombData.plotOn(McFrameF,Cut("McPassing==McPassing::fail"));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McSignalPdfF"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McBackgroundPdfF"), LineColor(kGreen),Range(xLow_,xHigh_));
}
///////////////////////////////////////////////////////////////
/****************** sim fit to data **************************/
///////////////////////////////////////////////////////////////
TFile *f2 = new TFile("dummyData.root","RECREATE");
TTree* cutTreeDataP = fullTreeData->CopyTree(Form("(%s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
TTree* cutTreeDataF = fullTreeData->CopyTree(Form("(%s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
RooDataSet DataDataP("DataDataP","dataset pass for the soup", RooArgSet(*mass), Import( *cutTreeDataP ) );
RooDataSet DataDataF("DataDataF","dataset fail for the soup", RooArgSet(*mass), Import( *cutTreeDataF ) );
RooDataHist DataCombData("DataCombData","combined data for the soup", RooArgSet(*mass), Index(*(w->cat("DataPassing"))), Import("pass",*(DataDataP.createHistogram("histoDataP",*mass))),Import("fail",*(DataDataF.createHistogram("histoDataF",*mass)))) ;
RooFitResult* ResDataCombinedFit = w->pdf("DataModel")->fitTo(DataCombData, Extended(1), Minos(1), Save(1), SumW2Error( SumW2_ ), Range(xLow_,xHigh_), NumCPU(4));
test->cd(Form("bin%f",binCenter_));
ResDataCombinedFit->Write("DataFitResults_Combined");
RooArgSet DataFitParam(ResDataCombinedFit->floatParsFinal());
RooRealVar* DataEffFit = (RooRealVar*)(&DataFitParam["DataEfficiency"]);
RooRealVar* DataNumSigFit = (RooRealVar*)(&DataFitParam["DataNumSgn"]);
RooRealVar* DataNumBkgPFit = (RooRealVar*)(&DataFitParam["DataNumBkgP"]);
RooRealVar* DataNumBkgFFit = (RooRealVar*)(&DataFitParam["DataNumBkgF"]);
RooPlot* DataFrameP = mass->frame(Bins(24),Title("Data: passing sample"));
DataCombData.plotOn(DataFrameP,Cut("DataPassing==DataPassing::pass"));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataSignalPdfP"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataBackgroundPdfP"), LineColor(kGreen),LineStyle(kDashed),Range(xLow_,xHigh_));
RooPlot* DataFrameF = mass->frame(Bins(24),Title("Data: failing sample"));
DataCombData.plotOn(DataFrameF,Cut("DataPassing==DataPassing::fail"));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataSignalPdfF"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataBackgroundPdfF"), LineColor(kGreen),LineStyle(kDashed),Range(xLow_,xHigh_));
///////////////////////////////////////////////////////////////
if(makeSoupFit_) c->Divide(2,2);
else c->Divide(2,1);
c->cd(1);
DataFrameP->Draw();
c->cd(2);
DataFrameF->Draw();
if(makeSoupFit_){
c->cd(3);
McFrameP->Draw();
c->cd(4);
McFrameF->Draw();
}
c->Draw();
test->cd(Form("bin%f",binCenter_));
c->Write();
c2->Divide(2,1);
c2->cd(1);
TemplateFrameP->Draw();
c2->cd(2);
TemplateFrameF->Draw();
c2->Draw();
test->cd(Form("bin%f",binCenter_));
c2->Write();
// MINOS errors, otherwise HESSE quadratic errors
float McErrorLo = 0;
float McErrorHi = 0;
if(makeSoupFit_){
McErrorLo = McEffFit->getErrorLo()<0 ? McEffFit->getErrorLo() : (-1)*McEffFit->getError();
McErrorHi = McEffFit->getErrorHi()>0 ? McEffFit->getErrorHi() : McEffFit->getError();
}
float DataErrorLo = DataEffFit->getErrorLo()<0 ? DataEffFit->getErrorLo() : (-1)*DataEffFit->getError();
float DataErrorHi = DataEffFit->getErrorHi()>0 ? DataEffFit->getErrorHi() : DataEffFit->getError();
float BinomialError = TMath::Sqrt(SGNtruePass/SGNtrue*(1-SGNtruePass/SGNtrue)/SGNtrue);
Double_t* truthMC = new Double_t[6];
Double_t* tnpMC = new Double_t[6];
Double_t* tnpData = new Double_t[6];
truthMC[0] = binCenter_;
truthMC[1] = binWidth_;
truthMC[2] = binWidth_;
truthMC[3] = SGNtruePass/SGNtrue;
truthMC[4] = BinomialError;
truthMC[5] = BinomialError;
if(makeSoupFit_){
tnpMC[0] = binCenter_;
tnpMC[1] = binWidth_;
tnpMC[2] = binWidth_;
tnpMC[3] = McEffFit->getVal();
tnpMC[4] = (-1)*McErrorLo;
tnpMC[5] = McErrorHi;
}
tnpData[0] = binCenter_;
tnpData[1] = binWidth_;
tnpData[2] = binWidth_;
tnpData[3] = DataEffFit->getVal();
tnpData[4] = (-1)*DataErrorLo;
tnpData[5] = DataErrorHi;
out.push_back(truthMC);
out.push_back(tnpData);
if(makeSoupFit_) out.push_back(tnpMC);
test->Close();
//delete c; delete c2;
if(verbose_) cout << "returning from bin " << bin_ << endl;
return out;
}
void forData(string channel, string catcut, bool removeMinor=true){
// Suppress all the INFO message
RooMsgService::instance().setGlobalKillBelow(RooFit::WARNING);
// Input files and sum all backgrounds
TChain* treeData = new TChain("tree");
TChain* treeZjets = new TChain("tree");
if( channel == "ele" ){
treeData->Add(Form("%s/data/SingleElectron-Run2015D-05Oct2015-v1_toyMCnew.root", channel.data()));
treeData->Add(Form("%s/data/SingleElectron-Run2015D-PromptReco-V4_toyMCnew.root", channel.data()));
}
else if( channel == "mu" ){
treeData->Add(Form("%s/data/SingleMuon-Run2015D-05Oct2015-v1_toyMCnew.root", channel.data()));
treeData->Add(Form("%s/data/SingleMuon-Run2015D-PromptReco-V4_toyMCnew.root", channel.data()));
}
else return;
treeZjets->Add(Form("%s/Zjets/DYJetsToLL_M-50_HT-100to200_13TeV_toyMCnew.root", channel.data()));
treeZjets->Add(Form("%s/Zjets/DYJetsToLL_M-50_HT-200to400_13TeV_toyMCnew.root", channel.data()));
treeZjets->Add(Form("%s/Zjets/DYJetsToLL_M-50_HT-400to600_13TeV_toyMCnew.root", channel.data()));
treeZjets->Add(Form("%s/Zjets/DYJetsToLL_M-50_HT-600toInf_13TeV_toyMCnew.root", channel.data()));
// To remove minor background contribution in data set (weight is -1)
if( removeMinor ){
treeData->Add(Form("%s/VV/WW_TuneCUETP8M1_13TeV_toyMCnew.root", channel.data()));
treeData->Add(Form("%s/VV/WZ_TuneCUETP8M1_13TeV_toyMCnew.root", channel.data()));
treeData->Add(Form("%s/VV/ZZ_TuneCUETP8M1_13TeV_toyMCnew.root", channel.data()));
treeData->Add(Form("%s/TT/TT_TuneCUETP8M1_13TeV_toyMCnew.root", channel.data()));
}
// Define all the variables from the trees
RooRealVar cat ("cat", "", 0, 2);
RooRealVar mJet("prmass", "M_{jet}", 30., 300., "GeV");
RooRealVar mZH ("mllbb", "M_{ZH}", 900., 3000., "GeV");
RooRealVar evWeight("evweight", "", -1.e3, 1.e3);
// Set the range in jet mass
mJet.setRange("allRange", 30., 300.);
mJet.setRange("lowSB", 30., 65.);
mJet.setRange("highSB", 135., 300.);
mJet.setRange("signal", 105., 135.);
RooBinning binsmJet(54, 30, 300);
RooArgSet variables(cat, mJet, mZH, evWeight);
TCut catCut = Form("cat==%s", catcut.c_str());
TCut sbCut = "prmass>30 && !(prmass>65 && prmass<135) && prmass<300";
TCut sigCut = "prmass>105 && prmass<135";
// Create a dataset from a tree -> to process an unbinned likelihood fitting
RooDataSet dataSetData ("dataSetData", "dataSetData", variables, Cut(catCut), WeightVar(evWeight), Import(*treeData));
RooDataSet dataSetDataSB ("dataSetDataSB", "dataSetDataSB", variables, Cut(catCut && sbCut), WeightVar(evWeight), Import(*treeData));
RooDataSet dataSetZjets ("dataSetZjets", "dataSetZjets", variables, Cut(catCut), WeightVar(evWeight), Import(*treeZjets));
RooDataSet dataSetZjetsSB("dataSetZjetsSB", "dataSetZjetsSB", variables, Cut(catCut && sbCut), WeightVar(evWeight), Import(*treeZjets));
RooDataSet dataSetZjetsSG("dataSetZjetsSG", "dataSetZjetsSG", variables, Cut(catCut && sigCut), WeightVar(evWeight), Import(*treeZjets));
// Total events number
float totalMcEv = dataSetZjetsSB.sumEntries() + dataSetZjetsSG.sumEntries();
float totalDataEv = dataSetData.sumEntries();
RooRealVar nMcEvents("nMcEvents", "nMcEvents", 0., 99999.);
RooRealVar nDataEvents("nDataEvents", "nDataEvents", 0., 99999.);
nMcEvents.setVal(totalMcEv);
nMcEvents.setConstant(true);
nDataEvents.setVal(totalDataEv);
nDataEvents.setConstant(true);
// Signal region jet mass
RooRealVar constant("constant", "constant", -0.02, -1., 0.);
RooRealVar offset ("offset", "offset", 30., -50., 200.);
RooRealVar width ("width", "width", 100., 0., 200.);
if( catcut == "1" ) offset.setConstant(true);
RooErfExpPdf model_mJet("model_mJet", "model_mJet", mJet, constant, offset, width);
RooExtendPdf ext_model_mJet("ext_model_mJet", "ext_model_mJet", model_mJet, nMcEvents);
RooFitResult* mJet_result = ext_model_mJet.fitTo(dataSetZjets, SumW2Error(true), Extended(true), Range("allRange"), Strategy(2), Minimizer("Minuit2"), Save(1));
// Side band jet mass
RooRealVar constantSB("constantSB", "constantSB", constant.getVal(), -1., 0.);
RooRealVar offsetSB ("offsetSB", "offsetSB", offset.getVal(), -50., 200.);
RooRealVar widthSB ("widthSB", "widthSB", width.getVal(), 0., 200.);
offsetSB.setConstant(true);
RooErfExpPdf model_mJetSB("model_mJetSB", "model_mJetSB", mJet, constantSB, offsetSB, widthSB);
RooExtendPdf ext_model_mJetSB("ext_model_mJetSB", "ext_model_mJetSB", model_mJetSB, nMcEvents);
RooFitResult* mJetSB_result = ext_model_mJetSB.fitTo(dataSetZjetsSB, SumW2Error(true), Extended(true), Range("lowSB,highSB"), Strategy(2), Minimizer("Minuit2"), Save(1));
RooAbsReal* nSIGFit = ext_model_mJetSB.createIntegral(RooArgSet(mJet), NormSet(mJet), Range("signal"));
float normFactor = nSIGFit->getVal() * totalMcEv;
// Plot the results on a frame
RooPlot* mJetFrame = mJet.frame();
dataSetZjetsSB. plotOn(mJetFrame, Binning(binsmJet));
ext_model_mJetSB.plotOn(mJetFrame, Range("allRange"), VisualizeError(*mJetSB_result), FillColor(kYellow));
dataSetZjetsSB. plotOn(mJetFrame, Binning(binsmJet));
ext_model_mJetSB.plotOn(mJetFrame, Range("allRange"));
mJetFrame->SetTitle("M_{jet} distribution in Z+jets MC");
// Alpha ratio part
mZH.setRange("fullRange", 900., 3000.);
RooBinning binsmZH(21, 900, 3000);
RooRealVar a("a", "a", 0., -1., 1.);
RooRealVar b("b", "b", 1000, 0., 4000.);
RooGenericPdf model_ZHSB("model_ZHSB", "model_ZHSB", "TMath::Exp(@1*@0+@2/@0)", RooArgSet(mZH,a,b));
RooGenericPdf model_ZHSG("model_ZHSG", "model_ZHSG", "TMath::Exp(@1*@0+@2/@0)", RooArgSet(mZH,a,b));
RooGenericPdf model_ZH ("model_ZH", "model_ZH", "TMath::Exp(@1*@0+@2/@0)", RooArgSet(mZH,a,b));
RooExtendPdf ext_model_ZHSB("ext_model_ZHSB", "ext_model_ZHSB", model_ZHSB, nMcEvents);
RooExtendPdf ext_model_ZHSG("ext_model_ZHSG", "ext_model_ZHSG", model_ZHSG, nMcEvents);
RooExtendPdf ext_model_ZH ("ext_model_ZH", "ext_model_ZH", model_ZH, nDataEvents);
// Fit ZH mass in side band
RooFitResult* mZHSB_result = ext_model_ZHSB.fitTo(dataSetZjetsSB, SumW2Error(true), Extended(true), Range("fullRange"), Strategy(2), Minimizer("Minuit2"), Save(1));
float p0 = a.getVal();
float p1 = b.getVal();
// Fit ZH mass in signal region
RooFitResult* mZHSG_result = ext_model_ZHSG.fitTo(dataSetZjetsSG, SumW2Error(true), Extended(true), Range("fullRange"), Strategy(2), Minimizer("Minuit2"), Save(1));
float p2 = a.getVal();
float p3 = b.getVal();
// Fit ZH mass in side band region (data)
RooFitResult* mZH_result = ext_model_ZH.fitTo(dataSetDataSB, SumW2Error(true), Extended(true), Range("fullRange"), Strategy(2), Minimizer("Minuit2"), Save(1));
// Draw the model of alpha ratio
// Multiply the model of background in data side band with the model of alpha ratio to the a model of background in data signal region
RooGenericPdf model_alpha("model_alpha", "model_alpha", Form("TMath::Exp(%f*@0+%f/@0)/TMath::Exp(%f*@0+%f/@0)", p2,p3,p0,p1), RooArgSet(mZH));
RooProdPdf model_sigData("model_sigData", "ext_model_ZH*model_alpha", RooArgList(ext_model_ZH,model_alpha));
// Plot the results to a frame
RooPlot* mZHFrameMC = mZH.frame();
dataSetZjetsSB.plotOn(mZHFrameMC, Binning(binsmZH));
ext_model_ZHSB.plotOn(mZHFrameMC, VisualizeError(*mZHSB_result), FillColor(kYellow));
dataSetZjetsSB.plotOn(mZHFrameMC, Binning(binsmZH));
ext_model_ZHSB.plotOn(mZHFrameMC, LineStyle(7), LineColor(kBlue));
dataSetZjetsSG.plotOn(mZHFrameMC, Binning(binsmZH));
ext_model_ZHSG.plotOn(mZHFrameMC, VisualizeError(*mZHSG_result), FillColor(kYellow));
dataSetZjetsSG.plotOn(mZHFrameMC, Binning(binsmZH));
ext_model_ZHSG.plotOn(mZHFrameMC, LineStyle(7), LineColor(kRed));
TLegend* leg = new TLegend(0.65,0.77,0.85,0.85);
leg->AddEntry(mZHFrameMC->findObject(mZHFrameMC->nameOf(3)), "side band", "l");
leg->AddEntry(mZHFrameMC->findObject(mZHFrameMC->nameOf(7)), "signal region", "l");
leg->Draw();
mZHFrameMC->addObject(leg);
mZHFrameMC->SetTitle("M_{ZH} distribution in MC");
RooPlot* mZHFrame = mZH.frame();
dataSetDataSB.plotOn(mZHFrame, Binning(binsmZH));
ext_model_ZH .plotOn(mZHFrame, VisualizeError(*mZH_result), FillColor(kYellow));
dataSetDataSB.plotOn(mZHFrame, Binning(binsmZH));
ext_model_ZH .plotOn(mZHFrame, LineStyle(7), LineColor(kBlue));
model_sigData.plotOn(mZHFrame, Normalization(normFactor, RooAbsReal::NumEvent), LineStyle(7), LineColor(kRed));
TLegend* leg1 = new TLegend(0.65,0.77,0.85,0.85);
leg1->AddEntry(mZHFrame->findObject(mZHFrame->nameOf(3)), "side band", "l");
leg1->AddEntry(mZHFrame->findObject(mZHFrame->nameOf(4)), "signal region", "l");
leg1->Draw();
mZHFrame->addObject(leg1);
mZHFrame->SetTitle("M_{ZH} distribution in Data");
TCanvas* c = new TCanvas("c","",0,0,1000,800);
c->cd();
mZHFrameMC->Draw();
c->Print(Form("rooFit_forData_%s_cat%s.pdf(", channel.data(), catcut.data()));
c->cd();
mZHFrame->Draw();
c->Print(Form("rooFit_forData_%s_cat%s.pdf", channel.data(), catcut.data()));
c->cd();
mJetFrame->Draw();
c->Print(Form("rooFit_forData_%s_cat%s.pdf)", channel.data(), catcut.data()));
}
//-------------------------------------------------------------
//Plot the model fitting function for signal+background
//=============================================================
void MakePlots(RooWorkspace *ws, RooFitResult *fitResult2D) {
RooPlot* framex = 0;
RooPlot* framey = 0;
//Import yield variables
RooRealVar *nsig = ws->var("N (Sig)");
RooRealVar *nres = ws->var("N (ResBkg)");
RooRealVar *nnonres = ws->var("N (NonResBkg)");
//Select and plot only one experiment
if (! (nsig->getVal() >= 15.6 && nsig->getVal() <= 17.0
&& nres->getVal() >= 27.9 && nres->getVal() <= 28.0
&& nnonres->getVal() <= 287.))
return;
if (alreadyPlotted) return;
alreadyPlotted = 1;
//Import the PDF's
RooAbsPdf *model2Dpdf = ws->pdf("model2Dpdf");
RooAbsPdf *sigPDFPho = ws->pdf("sigPDFPho");
RooAbsPdf *resPDFPho = ws->pdf("resPDFPho");
RooAbsPdf *nonresPDFPho = ws->pdf("nonresPDFPho");
RooAbsPdf *sigPDFBjet = ws->pdf("sigPDFBjet");
RooAbsPdf *sigPDFBjetCut = ws->pdf("sigPDFBjetCut");
RooAbsPdf *resPDFBjet = ws->pdf("resPDFBjet");
RooAbsPdf *resPDFBjetExt = ws->pdf("resPDFBjetExt");
RooAbsPdf *nonresPDFBjet = ws->pdf("nonresPDFBjet");
//x-axis variables
RooRealVar *massPho = ws->var("massPho");
RooRealVar *massBjet = ws->var("massBjet");
RooRealVar *massBjetExt = ws->var("massBjetExt");
RooRealVar *massBjetCut = ws->var("massBjetCut");
//sig variables
RooRealVar *sigMeanBjet = ws->var("sigMeanBjet");
RooRealVar *sigSigmaBjet = ws->var("sigSigmaBjet");
RooRealVar *sigAlpha = ws->var("sigAlpha");
RooRealVar *sigPower = ws->var("sigPower");
//res bkg variables
RooRealVar *resMeanBjet = ws->var("resMeanBjet");
RooRealVar *resSigmaBjet = ws->var("resSigmaBjet");
RooRealVar *resAlpha = ws->var("resAlpha");
RooRealVar *resPower = ws->var("resPower");
RooRealVar *resExpo = ws->var("resExpo");
RooRealVar *nbbH = ws->var("nbbH");
RooRealVar *nOthers = ws->var("nOthers");
//simulated data
RooDataHist *sigBjetData = (RooDataHist *)ws->data("sigBjetData");
RooDataHist *resBjetDataExt = (RooDataHist *)ws->data("resBjetDataExt");
RooDataSet *pseudoData2D = (RooDataSet *)ws->data("pseudoData2D");
//Plot of 2D generated data and fits
TH1 *data2d = pseudoData2D->createHistogram("2D Data", *massBjet,Binning(25), YVar(*massPho,Binning(25)));
data2d->SetStats(0);
TH1 *fit2d = model2Dpdf->createHistogram("2D Fit", *massBjet, YVar(*massPho));
fit2d->SetStats(0);
cv = new TCanvas("cv","cv",1600,600);
cv->Divide(2);
cv->cd(1); gPad->SetLeftMargin(0.15); data2d->Draw("LEGO2");
data2d->SetTitle("");
data2d->GetXaxis()->SetTitleOffset(2); data2d->GetXaxis()->SetTitle("M_{bb} [GeV/c^{2}]");
data2d->GetYaxis()->SetTitleOffset(2.2); data2d->GetYaxis()->SetTitle("M_{#gamma#gamma} [GeV/c^{2}]");
data2d->GetZaxis()->SetTitleOffset(1.75);
cv->cd(2); gPad->SetLeftMargin(0.15); fit2d->Draw("SURF1");
fit2d->SetTitle("");
fit2d->GetXaxis()->SetTitleOffset(2); data2d->GetXaxis()->SetTitle("M_{bb} [GeV/c^{2}]");
fit2d->GetYaxis()->SetTitleOffset(2.2); data2d->GetYaxis()->SetTitle("M_{#gamma#gamma} [GeV/c^{2}]");
fit2d->GetZaxis()->SetTitleOffset(1.75);
cv->SaveAs(Form("Plots/AllSignalBkgd/Fits/Toys/twoDimensionalFits_%d.gif",1));
//Plot of massBjet and massPho projections from 2D fit
massPho->setRange("PhoWindow",120,130);
framex = massBjet->frame(Bins(50));
framex->SetTitle(""); framex->SetXTitle("M_{bb} [GeV/c^{2}]"); framex->SetYTitle("Number of Events");
pseudoData2D->plotOn(framex, CutRange("PhoWindow"));
model2Dpdf->plotOn(framex, ProjectionRange("PhoWindow"), VisualizeError(*fitResult2D), FillStyle(3001));
model2Dpdf->plotOn(framex, ProjectionRange("PhoWindow"));
model2Dpdf->plotOn(framex, ProjectionRange("PhoWindow"), Components("sigPDFBjet"), LineStyle(kDashed), LineColor(kRed));
model2Dpdf->plotOn(framex, ProjectionRange("PhoWindow"), Components("resPDFBjet"), LineStyle(kDashed), LineColor(kOrange));
model2Dpdf->plotOn(framex, ProjectionRange("PhoWindow"), Components("nonresPDFBjet"), LineStyle(kDashed), LineColor(kGreen));
framey = massPho->frame(Bins(50));
framey->SetTitle(""); framey->SetXTitle("M_{#gamma#gamma} [GeV/c^{2}]"); framey->SetYTitle("Number of Events");
pseudoData2D->plotOn(framey);
model2Dpdf->plotOn(framey, VisualizeError(*fitResult2D), FillStyle(3001));
model2Dpdf->plotOn(framey);
model2Dpdf->plotOn(framey,Components("sigPDFPho"), LineStyle(kDashed), LineColor(kRed));
model2Dpdf->plotOn(framey,Components("resPDFPho"), LineStyle(kDashed), LineColor(kOrange));
model2Dpdf->plotOn(framey,Components("nonresPDFPho"), LineStyle(kDashed), LineColor(kGreen));
cv = new TCanvas("cv","cv",1600,600);
cv->Divide(2);
cv->cd(1); framex->Draw();
tex = new TLatex();
tex->SetNDC();
tex->SetTextSize(0.042);
tex->SetTextFont(42);
tex->DrawLatex(0.52, 0.84, Form("N_{Sig} = %.2f +/- %.2f", nsig->getVal(), nsig->getPropagatedError(*fitResult2D)));
tex->DrawLatex(0.52, 0.79, Form("N_{ResBkg} = %.2f +/- %.2f", nres->getVal(), nres->getPropagatedError(*fitResult2D)));
tex->DrawLatex(0.52, 0.74, Form("N_{NonResBkg} = %.2f +/- %.2f", nnonres->getVal(), nnonres->getPropagatedError(*fitResult2D)));
tex->Draw();
cv->Update();
cv->cd(2); framey->Draw();
tex->DrawLatex(0.52, 0.84, Form("N_{Sig} = %.2f +/- %.2f", nsig->getVal(), nsig->getPropagatedError(*fitResult2D)));
tex->DrawLatex(0.52, 0.79, Form("N_{ResBkg} = %.2f +/- %.2f", nres->getVal(), nres->getPropagatedError(*fitResult2D)));
tex->DrawLatex(0.52, 0.74, Form("N_{NonResBkg} = %.2f +/- %.2f", nnonres->getVal(), nnonres->getPropagatedError(*fitResult2D)));
tex->Draw();
cv->Update();
cv->SaveAs(Form("Plots/AllSignalBkgd/Fits/Toys/projectionFits_%d.gif",1));
}
void eregtesting_13TeV_Pi0(bool dobarrel=true, bool doele=false,int gammaID=0) {
//output dir
TString EEorEB = "EE";
if(dobarrel)
{
EEorEB = "EB";
}
TString gammaDir = "bothGammas";
if(gammaID==1)
{
gammaDir = "gamma1";
}
else if(gammaID==2)
{
gammaDir = "gamma2";
}
TString dirname = TString::Format("ereg_test_plots/%s_%s",gammaDir.Data(),EEorEB.Data());
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
TString infile = TString::Format("../../ereg_ws/%s/%s",gammaDir.Data(),fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *meantgt = static_cast<RooGBRTargetFlex*>(ws->arg("sigmeant"));
RooRealVar *tgtvar = ws->var("tgtvar");
RooArgList vars;
vars.add(meantgt->FuncVars());
vars.add(*tgtvar);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
//TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
if(dobarrel)
{
TFile *fdin = TFile::Open("/afs/cern.ch/work/z/zhicaiz/public/ECALpro_MC_TreeForRegression/Gun_Pi0_Pt1To15_FlatPU0to50RAW_withHLT_80X_mcRun2_GEN-SIM-RAW_ALL_EcalNtp_ALL_EB_combine_test.root");//("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
else
{
TFile *fdin = TFile::Open("/afs/cern.ch/work/z/zhicaiz/public/ECALpro_MC_TreeForRegression/Gun_Pi0_Pt1To15_FlatPU0to50RAW_withHLT_80X_mcRun2_GEN-SIM-RAW_ALL_EcalNtp_ALL_EE_combine_test.root");//("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
}
//selection cuts for testing
//TCut selcut = "(STr2_enG1_true/cosh(STr2_Eta_1)>1.0) && (STr2_S4S9_1>0.75)";
TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)>60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
/*
TCut selcut;
if (dobarrel)
selcut = "ph.genpt>25. && ph.isbarrel && ph.ispromptgen";
else
selcut = "ph.genpt>25. && !ph.isbarrel && ph.ispromptgen";
*/
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(Entry$%10==0)";
TCut prescale10alt = "(Entry$%10==1)";
TCut prescale25 = "(Entry$%25==0)";
TCut prescale100 = "(Entry$%100==0)";
TCut prescale1000 = "(Entry$%1000==0)";
TCut evenevents = "(Entry$%2==0)";
TCut oddevents = "(Entry$%2==1)";
TCut prescale100alt = "(Entry$%100==1)";
TCut prescale1000alt = "(Entry$%1000==1)";
TCut prescale50alt = "(Entry$%50==1)";
TCut Events3_4 = "(Entry$%4==3)";
TCut Events1_4 = "(Entry$%4==1)";
TCut Events2_4 = "(Entry$%4==2)";
TCut Events0_4 = "(Entry$%4==0)";
TCut Events01_4 = "(Entry$%4<2)";
TCut Events23_4 = "(Entry$%4>1)";
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
if (doele)
weightvar.SetTitle(prescale1000alt*selcut);
else
weightvar.SetTitle(prescale10alt*selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
//input variable corresponding to sceta
RooRealVar *scetavar = ws->var("var_1");
RooRealVar *scphivar = ws->var("var_2");
//regressed output functions
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
RooAbsReal *sigalphalim = ws->function("sigalphalim");
RooAbsReal *sigalpha2lim = ws->function("sigalpha2lim");
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
RooRealVar *alphavar = (RooRealVar*)hdataclone->addColumn(*sigalphalim);
RooRealVar *alpha2var = (RooRealVar*)hdataclone->addColumn(*sigalpha2lim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.6,2.0,100);
hdata->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
craw->SaveAs("RawE.pdf");
craw->SaveAs("RawE.png");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.pdf");
craw->SaveAs("RawElog.png");
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.pdf");
cmean->SaveAs("mean.png");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.pdf");
cwidth->SaveAs("width.png");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.pdf");
cn->SaveAs("n.png");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.pdf");
cn2->SaveAs("n2.png");
TCanvas *calpha = new TCanvas;
RooPlot *plotalpha = alphavar->frame(0.,5.,200);
hdataclone->plotOn(plotalpha);
plotalpha->Draw();
calpha->SaveAs("alpha.pdf");
calpha->SaveAs("alpha.png");
TCanvas *calpha2 = new TCanvas;
RooPlot *plotalpha2 = alpha2var->frame(0.,5.,200);
hdataclone->plotOn(plotalpha2);
plotalpha2->Draw();
calpha2->SaveAs("alpha2.pdf");
calpha2->SaveAs("alpha2.png");
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.pdf");
ceta->SaveAs("eta.png");
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw;// = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor;// = hdata->createHistogram("hecor",*ecorvar);
if (EEorEB == "EB")
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.8,1.1));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(800,0.8,1.1));
}
else
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(200,0.,2.));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(200,0.,2.));
}
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
heraw->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
hecor->GetXaxis()->SetRangeUser(0.0,1.5);
heraw->GetXaxis()->SetRangeUser(0.0,1.5);
/*if(EEorEB == "EE")
{
heraw->GetYaxis()->SetRangeUser(10.0,200.0);
hecor->GetYaxis()->SetRangeUser(10.0,200.0);
}
*/
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
double effsigma_cor, effsigma_raw, fwhm_cor, fwhm_raw;
if(EEorEB == "EB")
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
else
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
TCanvas *cresponse = new TCanvas;
gStyle->SetOptStat(0);
gStyle->SetPalette(107);
hecor->SetTitle("");
heraw->SetTitle("");
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
//show errSigma in the plot
TLegend *leg = new TLegend(0.1, 0.75, 0.7, 0.9);
leg->AddEntry(hecor,Form("E_{cor}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_cor, fwhm_cor),"l");
leg->AddEntry(heraw,Form("E_{raw}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_raw, fwhm_raw),"l");
leg->SetFillStyle(0);
leg->SetBorderSize(0);
// leg->SetTextColor(kRed);
leg->Draw();
cresponse->SaveAs("response.pdf");
cresponse->SaveAs("response.png");
cresponse->SetLogy();
cresponse->SaveAs("responselog.pdf");
cresponse->SaveAs("responselog.png");
// draw CCs vs eta and phi
TCanvas *c_eta = new TCanvas;
TH1 *h_eta = hdata->createHistogram("h_eta",*scetavar,Binning(100,-3.2,3.2));
h_eta->Draw("HIST");
c_eta->SaveAs("heta.pdf");
c_eta->SaveAs("heta.png");
TCanvas *c_phi = new TCanvas;
TH1 *h_phi = hdata->createHistogram("h_phi",*scphivar,Binning(100,-3.2,3.2));
h_phi->Draw("HIST");
c_phi->SaveAs("hphi.pdf");
c_phi->SaveAs("hphi.png");
RooRealVar *scetaiXvar = ws->var("var_6");
RooRealVar *scphiiYvar = ws->var("var_7");
if(EEorEB=="EB")
{
scetaiXvar->setRange(-90,90);
scetaiXvar->setBins(180);
scphiiYvar->setRange(0,360);
scphiiYvar->setBins(360);
}
else
{
scetaiXvar->setRange(0,50);
scetaiXvar->setBins(50);
scphiiYvar->setRange(0,50);
scphiiYvar->setBins(50);
}
ecorvar->setRange(0.5,1.5);
ecorvar->setBins(800);
rawvar->setRange(0.5,1.5);
rawvar->setBins(800);
TCanvas *c_cor_eta = new TCanvas;
TH2F *h_CC_eta = hdata->createHistogram(*scetaiXvar, *ecorvar, "","cor_vs_eta");
if(EEorEB=="EB")
{
h_CC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetXaxis()->SetTitle("iX");
}
h_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_eta->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta.pdf");
c_cor_eta->SaveAs("cor_vs_eta.png");
TCanvas *c_cor_phi = new TCanvas;
TH2F *h_CC_phi = hdata->createHistogram(*scphiiYvar, *ecorvar, "","cor_vs_phi");
if(EEorEB=="EB")
{
h_CC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetXaxis()->SetTitle("iY");
}
h_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_phi->Draw("COLZ");
c_cor_phi->SaveAs("cor_vs_phi.pdf");
c_cor_phi->SaveAs("cor_vs_phi.png");
TCanvas *c_raw_eta = new TCanvas;
TH2F *h_RC_eta = hdata->createHistogram(*scetaiXvar, *rawvar, "","raw_vs_eta");
if(EEorEB=="EB")
{
h_RC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_RC_eta->GetXaxis()->SetTitle("iX");
}
h_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_eta->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta.pdf");
c_raw_eta->SaveAs("raw_vs_eta.png");
TCanvas *c_raw_phi = new TCanvas;
TH2F *h_RC_phi = hdata->createHistogram(*scphiiYvar, *rawvar, "","raw_vs_phi");
if(EEorEB=="EB")
{
h_RC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_RC_phi->GetXaxis()->SetTitle("iY");
}
h_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_phi->Draw("COLZ");
c_raw_phi->SaveAs("raw_vs_phi.pdf");
c_raw_phi->SaveAs("raw_vs_phi.png");
//on2,5,20, etc
if(EEorEB == "EB")
{
TCanvas *myC_iCrystal_mod = new TCanvas;
RooRealVar *iEtaOn5var = ws->var("var_8");
iEtaOn5var->setRange(0,5);
iEtaOn5var->setBins(5);
TH2F *h_CC_iEtaOn5 = hdata->createHistogram(*iEtaOn5var, *ecorvar, "","cor_vs_iEtaOn5");
h_CC_iEtaOn5->GetXaxis()->SetTitle("iEtaOn5");
h_CC_iEtaOn5->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iEtaOn5->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn5.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn5.png");
TH2F *h_RC_iEtaOn5 = hdata->createHistogram(*iEtaOn5var, *rawvar, "","raw_vs_iEtaOn5");
h_RC_iEtaOn5->GetXaxis()->SetTitle("iEtaOn5");
h_RC_iEtaOn5->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iEtaOn5->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn5.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn5.png");
RooRealVar *iPhiOn2var = ws->var("var_9");
iPhiOn2var->setRange(0,2);
iPhiOn2var->setBins(2);
TH2F *h_CC_iPhiOn2 = hdata->createHistogram(*iPhiOn2var, *ecorvar, "","cor_vs_iPhiOn2");
h_CC_iPhiOn2->GetXaxis()->SetTitle("iPhiOn2");
h_CC_iPhiOn2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iPhiOn2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn2.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn2.png");
TH2F *h_RC_iPhiOn2 = hdata->createHistogram(*iPhiOn2var, *rawvar, "","raw_vs_iPhiOn2");
h_RC_iPhiOn2->GetXaxis()->SetTitle("iPhiOn2");
h_RC_iPhiOn2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iPhiOn2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn2.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn2.png");
RooRealVar *iPhiOn20var = ws->var("var_10");
iPhiOn20var->setRange(0,20);
iPhiOn20var->setBins(20);
TH2F *h_CC_iPhiOn20 = hdata->createHistogram(*iPhiOn20var, *ecorvar, "","cor_vs_iPhiOn20");
h_CC_iPhiOn20->GetXaxis()->SetTitle("iPhiOn20");
h_CC_iPhiOn20->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iPhiOn20->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn20.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn20.png");
TH2F *h_RC_iPhiOn20 = hdata->createHistogram(*iPhiOn20var, *rawvar, "","raw_vs_iPhiOn20");
h_RC_iPhiOn20->GetXaxis()->SetTitle("iPhiOn20");
h_RC_iPhiOn20->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iPhiOn20->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn20.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn20.png");
RooRealVar *iEtaOn2520var = ws->var("var_11");
iEtaOn2520var->setRange(-25,25);
iEtaOn2520var->setBins(50);
TH2F *h_CC_iEtaOn2520 = hdata->createHistogram(*iEtaOn2520var, *ecorvar, "","cor_vs_iEtaOn2520");
h_CC_iEtaOn2520->GetXaxis()->SetTitle("iEtaOn2520");
h_CC_iEtaOn2520->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iEtaOn2520->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn2520.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn2520.png");
TH2F *h_RC_iEtaOn2520 = hdata->createHistogram(*iEtaOn2520var, *rawvar, "","raw_vs_iEtaOn2520");
h_RC_iEtaOn2520->GetXaxis()->SetTitle("iEtaOn2520");
h_RC_iEtaOn2520->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iEtaOn2520->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn2520.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn2520.png");
}
// other variables
TCanvas *myC_variables = new TCanvas;
RooRealVar *Nxtalvar = ws->var("var_3");
Nxtalvar->setRange(0,10);
Nxtalvar->setBins(10);
TH2F *h_CC_Nxtal = hdata->createHistogram(*Nxtalvar, *ecorvar, "","cor_vs_Nxtal");
h_CC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_CC_Nxtal->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Nxtal.pdf");
myC_variables->SaveAs("cor_vs_Nxtal.png");
TH2F *h_RC_Nxtal = hdata->createHistogram(*Nxtalvar, *rawvar, "","raw_vs_Nxtal");
h_RC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_RC_Nxtal->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Nxtal.pdf");
myC_variables->SaveAs("raw_vs_Nxtal.png");
RooRealVar *S4S9var = ws->var("var_4");
int Nbins_S4S9 = 100;
double Low_S4S9 = 0.6;
double High_S4S9 = 1.0;
S4S9var->setRange(Low_S4S9,High_S4S9);
S4S9var->setBins(Nbins_S4S9);
TH2F *h_CC_S4S9 = hdata->createHistogram(*S4S9var, *ecorvar, "","cor_vs_S4S9");
h_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h_CC_S4S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S4S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S4S9.pdf");
myC_variables->SaveAs("cor_vs_S4S9.png");
TH2F *h_RC_S4S9 = hdata->createHistogram(*S4S9var, *rawvar, "","raw_vs_S4S9");
h_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h_RC_S4S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S4S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S4S9.pdf");
myC_variables->SaveAs("raw_vs_S4S9.png");
/*
RooRealVar *S1S9var = ws->var("var_5");
S1S9var->setRange(0.3,1.0);
S1S9var->setBins(100);
TH2F *h_CC_S1S9 = hdata->createHistogram(*S1S9var, *ecorvar, "","cor_vs_S1S9");
h_CC_S1S9->GetXaxis()->SetTitle("S1S9");
h_CC_S1S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S1S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S1S9.pdf");
TH2F *h_RC_S1S9 = hdata->createHistogram(*S1S9var, *rawvar, "","raw_vs_S1S9");
h_RC_S1S9->GetXaxis()->SetTitle("S1S9");
h_RC_S1S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S1S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S1S9.pdf");
*/
RooRealVar *S2S9var = ws->var("var_5");
int Nbins_S2S9 = 100;
double Low_S2S9 = 0.5;
double High_S2S9 = 1.0;
S2S9var->setRange(Low_S2S9,High_S2S9);
S2S9var->setBins(Nbins_S2S9);
TH2F *h_CC_S2S9 = hdata->createHistogram(*S2S9var, *ecorvar, "","cor_vs_S2S9");
h_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h_CC_S2S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S2S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S2S9.pdf");
myC_variables->SaveAs("cor_vs_S2S9.png");
TH2F *h_RC_S2S9 = hdata->createHistogram(*S2S9var, *rawvar, "","raw_vs_S2S9");
h_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h_RC_S2S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S2S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S2S9.pdf");
myC_variables->SaveAs("raw_vs_S2S9.png");
TH2F *h_S2S9_eta = hdata->createHistogram(*scetaiXvar, *S2S9var, "","S2S9_vs_eta");
h_S2S9_eta->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S2S9_eta->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_eta.pdf");
myC_variables->SaveAs("S2S9_vs_eta.png");
TH2F *h_S4S9_eta = hdata->createHistogram(*scetaiXvar, *S4S9var, "","S4S9_vs_eta");
h_S4S9_eta->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S4S9_eta->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_eta.pdf");
myC_variables->SaveAs("S4S9_vs_eta.png");
TH2F *h_S2S9_phi = hdata->createHistogram(*scphiiYvar, *S2S9var, "","S2S9_vs_phi");
h_S2S9_phi->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S2S9_phi->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_phi.pdf");
myC_variables->SaveAs("S2S9_vs_phi.png");
TH2F *h_S4S9_phi = hdata->createHistogram(*scphiiYvar, *S4S9var, "","S4S9_vs_phi");
h_S4S9_phi->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S4S9_phi->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_phi.pdf");
myC_variables->SaveAs("S4S9_vs_phi.png");
/*
RooRealVar *DeltaRvar = ws->var("var_6");
DeltaRvar->setRange(0.0,0.1);
DeltaRvar->setBins(100);
TH2F *h_CC_DeltaR = hdata->createHistogram(*DeltaRvar, *ecorvar, "","cor_vs_DeltaR");
h_CC_DeltaR->GetXaxis()->SetTitle("#Delta R");
h_CC_DeltaR->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_DeltaR->Draw("COLZ");
myC_variables->SaveAs("cor_vs_DeltaR.pdf");
myC_variables->SaveAs("cor_vs_DeltaR.png");
TH2F *h_RC_DeltaR = hdata->createHistogram(*DeltaRvar, *rawvar, "","raw_vs_DeltaR");
h_RC_DeltaR->GetXaxis()->SetTitle("#Delta R");
h_RC_DeltaR->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_DeltaR->Draw("COLZ");
myC_variables->SaveAs("raw_vs_DeltaR.pdf");
myC_variables->SaveAs("raw_vs_DeltaR.png");
*/
if(EEorEB=="EE")
{
/* RooRealVar *Es_e1var = ws->var("var_9");
Es_e1var->setRange(0.0,200.0);
Es_e1var->setBins(1000);
TH2F *h_CC_Es_e1 = hdata->createHistogram(*Es_e1var, *ecorvar, "","cor_vs_Es_e1");
h_CC_Es_e1->GetXaxis()->SetTitle("Es_e1");
h_CC_Es_e1->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Es_e1->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Es_e1.pdf");
myC_variables->SaveAs("cor_vs_Es_e1.png");
TH2F *h_RC_Es_e1 = hdata->createHistogram(*Es_e1var, *rawvar, "","raw_vs_Es_e1");
h_RC_Es_e1->GetXaxis()->SetTitle("Es_e1");
h_RC_Es_e1->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Es_e1->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Es_e1.pdf");
myC_variables->SaveAs("raw_vs_Es_e1.png");
RooRealVar *Es_e2var = ws->var("var_10");
Es_e2var->setRange(0.0,200.0);
Es_e2var->setBins(1000);
TH2F *h_CC_Es_e2 = hdata->createHistogram(*Es_e2var, *ecorvar, "","cor_vs_Es_e2");
h_CC_Es_e2->GetXaxis()->SetTitle("Es_e2");
h_CC_Es_e2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Es_e2->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Es_e2.pdf");
myC_variables->SaveAs("cor_vs_Es_e2.png");
TH2F *h_RC_Es_e2 = hdata->createHistogram(*Es_e2var, *rawvar, "","raw_vs_Es_e2");
h_RC_Es_e2->GetXaxis()->SetTitle("Es_e2");
h_RC_Es_e2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Es_e2->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Es_e2.pdf");
myC_variables->SaveAs("raw_vs_Es_e2.png");
*/
}
TProfile *p_CC_eta = h_CC_eta->ProfileX("p_CC_eta",1,-1,"s");
p_CC_eta->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB == "EB")
{
// p_CC_eta->GetYaxis()->SetRangeUser(0.85,1.0);
// p_CC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_eta->SetTitle("");
p_CC_eta->Draw();
myC_variables->SaveAs("profile_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_cor_vs_eta.png");
TProfile *p_RC_eta = h_RC_eta->ProfileX("p_RC_eta",1,-1,"s");
p_RC_eta->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB=="EB")
{
// p_RC_eta->GetYaxis()->SetRangeUser(0.80,0.95);
// p_RC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_eta->SetTitle("");
p_RC_eta->Draw();
myC_variables->SaveAs("profile_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_raw_vs_eta.png");
int Nbins_iEta = EEorEB=="EB" ? 180 : 50;
int nLow_iEta = EEorEB=="EB" ? -90 : 0;
int nHigh_iEta = EEorEB=="EB" ? 90 : 50;
TH1F *h1_RC_eta = new TH1F("h1_RC_eta","h1_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_RC_eta->SetBinContent(i,p_RC_eta->GetBinError(i));
}
h1_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_RC_eta->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_eta->SetTitle("");
h1_RC_eta->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.png");
TH1F *h1_CC_eta = new TH1F("h1_CC_eta","h1_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_CC_eta->SetBinContent(i,p_CC_eta->GetBinError(i));
}
h1_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_CC_eta->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_eta->SetTitle("");
h1_CC_eta->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.png");
TProfile *p_CC_phi = h_CC_phi->ProfileX("p_CC_phi",1,-1,"s");
p_CC_phi->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB == "EB")
{
// p_CC_phi->GetYaxis()->SetRangeUser(0.94,1.00);
}
p_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_phi->SetTitle("");
p_CC_phi->Draw();
myC_variables->SaveAs("profile_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_cor_vs_phi.png");
TProfile *p_RC_phi = h_RC_phi->ProfileX("p_RC_phi",1,-1,"s");
p_RC_phi->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB=="EB")
{
// p_RC_phi->GetYaxis()->SetRangeUser(0.89,0.95);
}
p_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_phi->SetTitle("");
p_RC_phi->Draw();
myC_variables->SaveAs("profile_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_raw_vs_phi.png");
int Nbins_iPhi = EEorEB=="EB" ? 360 : 50;
int nLow_iPhi = EEorEB=="EB" ? 0 : 0;
int nHigh_iPhi = EEorEB=="EB" ? 360 : 50;
TH1F *h1_RC_phi = new TH1F("h1_RC_phi","h1_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_RC_phi->SetBinContent(i,p_RC_phi->GetBinError(i));
}
h1_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_RC_phi->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_phi->SetTitle("");
h1_RC_phi->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.png");
TH1F *h1_CC_phi = new TH1F("h1_CC_phi","h1_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_CC_phi->SetBinContent(i,p_CC_phi->GetBinError(i));
}
h1_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_CC_phi->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_phi->SetTitle("");
h1_CC_phi->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.png");
// FWHM over sigma_eff vs. eta/phi
TH1F *h1_FoverS_RC_phi = new TH1F("h1_FoverS_RC_phi","h1_FoverS_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_CC_phi = new TH1F("h1_FoverS_CC_phi","h1_FoverS_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_RC_eta = new TH1F("h1_FoverS_RC_eta","h1_FoverS_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_eta = new TH1F("h1_FoverS_CC_eta","h1_FoverS_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_S2S9 = new TH1F("h1_FoverS_CC_S2S9","h1_FoverS_CC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_RC_S2S9 = new TH1F("h1_FoverS_RC_S2S9","h1_FoverS_RC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_CC_S4S9 = new TH1F("h1_FoverS_CC_S4S9","h1_FoverS_CC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
TH1F *h1_FoverS_RC_S4S9 = new TH1F("h1_FoverS_RC_S4S9","h1_FoverS_RC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
float FWHMoverSigmaEff = 0.0;
TH1F *h_tmp_rawvar = new TH1F("tmp_rawvar","tmp_rawvar",800,0.5,1.5);
TH1F *h_tmp_corvar = new TH1F("tmp_corvar","tmp_corvar",800,0.5,1.5);
for(int i=1;i<=Nbins_iPhi;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_phi->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_phi->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_phi->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_phi->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_CC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_phi->SetTitle("");
h1_FoverS_CC_phi->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.png");
h1_FoverS_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_RC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_phi->SetTitle("");
h1_FoverS_RC_phi->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.png");
for(int i=1;i<=Nbins_iEta;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_eta->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_eta->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_eta->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_eta->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_CC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_eta->SetTitle("");
h1_FoverS_CC_eta->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.png");
h1_FoverS_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_RC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_eta->SetTitle("");
h1_FoverS_RC_eta->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.png");
for(int i=1;i<=Nbins_S2S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S2S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S2S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_CC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S2S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S2S9->SetTitle("");
h1_FoverS_CC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.png");
h1_FoverS_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_RC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S2S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S2S9->SetTitle("");
h1_FoverS_RC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.png");
for(int i=1;i<=Nbins_S4S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S4S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S4S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_CC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S4S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S4S9->SetTitle("");
h1_FoverS_CC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.png");
h1_FoverS_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_RC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S4S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S4S9->SetTitle("");
h1_FoverS_RC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.png");
printf("calc effsigma\n");
std::cout<<"_"<<EEorEB<<std::endl;
printf("corrected curve effSigma= %5f, FWHM=%5f \n",effsigma_cor, fwhm_cor);
printf("raw curve effSigma= %5f FWHM=%5f \n",effsigma_raw, fwhm_raw);
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
}
