void PEs(RooAbsPdf *iGen,RooAbsPdf *iFit,int iN,int iNEvents,RooRealVar &iVar,RooRealVar &iSig,RooRealVar &iMean,
RooRealVar &iScale,RooRealVar &iRes) {
double iM0 = iMean.getVal(); double iS0 = iSig.getVal();
//iScale.setVal(iMeanScale); iRes.setVal(iSigScale);
TRandom1 *lRand = new TRandom1(0xDEADBEEF);
TNtuple * lDN= new TNtuple( "xxx","xxx","ntot:m_r:m:merr:sig_r:sig:sigerr");
for(int i0=0;i0<iN;i0++){
if(i0 % 10 == 0) cout << "+++++++++++++++++++++++++++ running ======> " << i0 << endl;
int lN = lRand->Poisson(iNEvents);
RooDataSet * lSignal = iGen->generate(iVar,lN);
iMean.setVal(iM0); iSig.setVal(iS0);
iFit->fitTo(*lSignal,Strategy(1));//,Save(kTRUE),PrintLevel(1));
if(iMean.getError() < 0.05) iFit->fitTo(*lSignal,Strategy(2));
Float_t values[]={
(Float_t) lN,
(Float_t) 90.78/iScale.getVal(),
(Float_t) iMean.getVal(),
(Float_t) iMean.getError(),
(Float_t) iSig.getVal(),
(Float_t) iSig.getVal(),
(Float_t) iSig.getError()
};
lDN->Fill(values);
}
TFile *lF = new TFile("XXX.root","RECREATE");
lDN->Write();
lF->Close();
}
void Plot(RooAbsPdf *iGen,RooAbsPdf *iFit,int iN,int iNEvents,RooRealVar &iVar,RooRealVar &iSig,RooRealVar &iMean,
RooRealVar &iScale,RooRealVar &iRes,RooDataSet *iData=0) {
TRandom1 *lRand = new TRandom1(0xDEADBEEF);
RooDataSet * lSignal = iGen->generate(iVar,iNEvents);
if(iData == 0) {
iFit->fitTo(*lSignal,Strategy(1));
if(iMean.getError() < 0.05) iFit->fitTo(*lSignal,Strategy(2));
} else {
iFit->fitTo(*iData,Strategy(1));
if(iMean.getError() < 0.05) iFit->fitTo(*iData,Strategy(2));
}
iVar.setBins(30);
RooPlot *lFrame1 = iVar.frame(RooFit::Title("XXX")) ;
if(iData == 0) lSignal->plotOn(lFrame1);
if(iData != 0) iData->plotOn(lFrame1);
iFit->plotOn(lFrame1);
TCanvas *iC =new TCanvas("A","A",800,600);
iC->cd(); lFrame1->Draw();
iC->SaveAs("Crap.png");
if(iData != 0) {
RooPlot *lFrame2 = iVar.frame(RooFit::Title("XXX")) ;
iData->plotOn(lFrame2);
iGen->plotOn(lFrame2);
TCanvas *iC1 =new TCanvas("B","B",800,600);
iC1->cd(); lFrame2->Draw();
iC1->SaveAs("Crap.png");
}
}
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() );
}
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;
}
}
}
double getSigmaError(RooWorkspace *w)
{
using namespace RooFit;
// Access saved Sigma CB values and error from WorkSpace
RooRealVar *mySavedSigma = w->var("sigma_{CB}");
RooRealVar *mySavedDeltaM = w->var("#Deltam_{CB}");
Double_t sigma = mySavedSigma->getVal();
Double_t sigmaerror = mySavedSigma->getError();
Double_t DeltaM = mySavedDeltaM->getVal();
Double_t DeltaMerror = mySavedDeltaM->getError();
Double_t Sigpercent = 100 * sigma / (91.187 + DeltaM);
Double_t Sigpercenterror = 100 * pow(pow(sigmaerror / (91.198 + DeltaM), 2) + pow((sigma * DeltaMerror) / pow(DeltaM + 91.198, 2), 2), .5);
return Sigpercenterror;
} // plotFitOn(..)
void simplePrintResults() {
vector<string> filenames;
filenames.push_back("Output/Test2/result/FIT_DATA_Psi2SJpsi_PPPrompt_Bkg_SecondOrderChebychev_pt65300_rap016_cent0200_262620_263757.root");
const char* parname = "N_Jpsi_PP";
vector<string>::iterator it = filenames.begin();
for (it; it<filenames.end(); it++) {
TFile *f = new TFile(it->c_str());
if (!f) {
cout << "Error, " << *it << " not found" << endl;
continue;
}
RooWorkspace *ws = (RooWorkspace*) f->Get("workspace");
if (!ws) {
cout << "Error, workspace not found in " << *it << endl;
continue;
}
RooRealVar *var = ws->var(parname);
if (!ws) {
cout << "Error, variable " << parname << " not found in " << *it << endl;
continue;
}
cout << *it << " " << var->getVal() << " +- " << var->getError() << endl;
}
}
void PDF_GLWADS_Dpi_K3pi::setUncertainties(config c)
{
switch(c)
{
case lumi1fb:
{
obsErrSource = "1fb-1, ExpNll/sept2012K3PIResult.root";
TString File = this->dir+"/ExpNll/sept2012K3PIResult.root";
TFile *fr = TFile::Open(File);
RooFitResult *r = (RooFitResult*)fr->Get("fitresult_model_reducedData_binned");
assert(r);
for ( int i=0; i<nObs; i++ )
{
RooRealVar* pObs = (RooRealVar*)((RooArgList*)observables)->at(i);
RooRealVar* pRes = (RooRealVar*)r->floatParsFinal().find(obsTmkToMalcolm(pObs->GetName()));
assert(pRes);
StatErr[i] = pRes->getError();
}
SystErr[0] = 0.010; // afav_dpi_obs
SystErr[1] = 0.00011; // rp_dpi_obs
SystErr[2] = 0.00011; // rm_dpi_obs
fr->Close();
delete r;
delete fr;
break;
}
default:
cout << "PDF_GLWADS_Dpi_K3pi::setUncertainties() : ERROR : config "+ConfigToTString(c)+" not found." << endl;
exit(1);
}
}
void checkBestFitPoint(std::string workspace, std::string fitFile, bool splusb){
// Open the ws file...
TFile *fd_=0;
TFile *fw_=0;
gSystem->Load("$CMSSW_BASE/lib/$SCRAM_ARCH/libHiggsAnalysisCombinedLimit.so");
gROOT->SetBatch(true);
gStyle->SetOptFit(0);
gStyle->SetOptStat(0);
gStyle->SetPalette(1,0);
fw_ = TFile::Open(workspace.c_str());
w = (RooWorkspace*) fw_->Get("w");
w->Print();
RooDataSet *data = (RooDataSet*) w->data("data_obs");
if (splusb) {
mc_s = (RooStats::ModelConfig*)w->genobj("ModelConfig");
} else {
mc_s = (RooStats::ModelConfig*)w->genobj("ModelConfig_bonly");
}
std::cout << "make nll"<<std::endl;
nll = mc_s->GetPdf()->createNLL(
*data,RooFit::Constrain(*mc_s->GetNuisanceParameters())
,RooFit::Extended(mc_s->GetPdf()->canBeExtended()));
// Now get the best fit result
fd_ = TFile::Open(fitFile.c_str());
RooFitResult *fit;
if (splusb) {
fit =(RooFitResult*)fd_->Get("fit_s");
} else {
fit =(RooFitResult*)fd_->Get("fit_b");
}
RooArgSet fitargs = fit->floatParsFinal();
std::cout << "Got the best fit values" <<std::endl;
w->saveSnapshot("bestfitall",fitargs,true);
TString filename;
if (splusb) {
filename = "minimum_s.pdf";
} else {
filename = "minimum_b.pdf";
}
// Now make the plots!
TCanvas *c = new TCanvas("c","",600,600);
c->SaveAs((filename+"["));
TIterator* iter(fitargs->createIterator());
for (TObject *a = iter->Next(); a != 0; a = iter->Next()) {
RooRealVar *rrv = dynamic_cast<RooRealVar *>(a);
std::string name = rrv->GetName();
TGraph *gr = graphLH(name,rrv->getError());
gr->Draw("ALP");
c->SaveAs((filename+"["));
}
c->SaveAs((filename+"]"));
}
// grab the initial parameters and errors for making pull distributions:
// Take these from a fit file to the data themselves
void fillInitialParams(RooArgSet *args, std::map<std::string, std::pair<double,double> > &vals){
TIterator* iter(args->createIterator());
for (TObject *a = iter->Next(); a != 0; a = iter->Next()) {
RooRealVar *rrv = dynamic_cast<RooRealVar *>(a);
std::string name = rrv->GetName();
std::pair<double,double> valE(rrv->getVal(),rrv->getError());
vals.insert( std::pair<std::string,std::pair<double ,double> > (name,valE)) ;
}
}
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() );
}
void MakeSpinPlots::MakeChannelComp(const char* mcType){
TGraphErrors graph(catNames.size());
RooRealVar mu("mu","",-50,50);
float exp = ws->data(Form("%s_Combined",mcType))->sumEntries();///total * 607*lumi/12.;
TH1F frame("frame","",catNames.size(),0,catNames.size());
//graph.GetXaxis()->SetNdivisions(catNames.size());
float min=99999,max=-99999;
for(int i=0;i<catNames.size();i++){
RooRealVar *ind = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcType, catNames.at(i).Data()) );
RooRealVar *f = ws->var( Form("Data_%s_FULLFIT_%s_fsig",mcType, catNames.at(i).Data()) );
float mu = ind->getVal()/exp/f->getVal();
float muE = ind->getError()/exp/f->getVal();
graph.SetPoint(i,i+0.5,mu);
graph.SetPointError(i,0,muE);
if(mu-muE < min) min = mu-muE;
if(mu+muE > max) max = mu+muE;
//graph.GetXaxis()->SetBinLabel(i+1,catNames.at(i));
}
TF1 fit("fit","[0]",0+0.5,catNames.size()+0.5);
graph.Fit(&fit,"MNE");
float mean = fit.GetParameter(0);
float meanE = fit.GetParError(0);
frame.SetAxisRange(min-1.5,max+0.5,"Y");
frame.SetYTitle("Fitted #sigma/#sigma_{SM}");
frame.SetXTitle("Category");
TCanvas cv;
frame.Draw();
TBox err(0,mean-meanE,catNames.size(),mean+meanE);
err.SetFillColor(kGreen);
frame.Draw();
err.Draw("SAME");
TLine mLine(0,mean,catNames.size(),mean);
mLine.Draw("SAME");
graph.Draw("PSAME");
cv.SaveAs(basePath+Form("/ChannelComp_%s_%s.png",mcType,outputTag.Data()));
cv.SaveAs(basePath+Form("/ChannelComp_%s_%s.pdf",mcType,outputTag.Data()));
}
void MakeSpinPlots::printYields(const char* mcType){
RooRealVar * tot = ws->var(Form("Data_%s_FULLFIT_Nsig",mcType));
if(tot==0) return;
cout << "Total Yield: " << tot->getVal() << " +- " << tot->getError() <<endl;
cout << "Category Yields: CONSTRAINED FIT " << endl;
for(int i=0;i<catNames.size();i++){
RooRealVar *f = ws->var( Form("Data_%s_FULLFIT_%s_fsig",mcType, catNames.at(i).Data()) );
cout << "\t" << catNames.at(i) <<": " << tot->getVal()*f->getVal() << " +- " << tot->getError()*f->getVal() <<endl;
}
cout << "\nCategory Yields: INDEPENDENT FIT " << endl;
for(int i=0;i<catNames.size();i++){
RooRealVar *ind = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcType, catNames.at(i).Data()) );
if(ind==0) continue;
cout << "\t" << catNames.at(i) <<": " << ind->getVal() << " +- " << ind->getError() <<endl;
}
float exp = ws->data(Form("%s_Combined",mcType))->sumEntries();///total * 607*lumi/12.;
cout << endl << "Expected Events: " << exp << endl;
cout << "Expected Yields Per Category: " <<endl;
for(int i=0;i<catNames.size();i++){
RooRealVar *f = ws->var( Form("Data_%s_FULLFIT_%s_fsig",mcType, catNames.at(i).Data()) );
cout << "\t" << catNames.at(i) <<": " << exp*f->getVal() <<endl;
}
cout << "mu: " << tot->getVal()/exp << " +- "
<< tot->getError()/exp <<endl;
for(int i=0;i<catNames.size();i++){
RooRealVar *ind = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcType, catNames.at(i).Data()) );
if(ind==0) continue;
RooRealVar *f = ws->var( Form("Data_%s_FULLFIT_%s_fsig",mcType, catNames.at(i).Data()) );
cout << "\t" << catNames.at(i) <<": " << ind->getVal()/(exp*f->getVal()) << " +- " << ind->getError()/(exp*f->getVal()) <<endl;
}
MakeChannelComp(mcType);
}
void logStatisticsPar(std::ostream& out, RooDataSet *dataSet, RooRealVar *realVar, int nBins, double chi2, const RooArgList &variables)
{
TH1 *histogram = dataSet->createHistogram(Form("h%s", dataSet->GetName()), *realVar, RooFit::Binning(nBins));
// Create the TeX file
out << "\\documentclass[10pt]{article}" << std::endl;
out << "\\usepackage[usenames]{color} %used for font color" << std::endl;
out << "\\usepackage{fontspec}" << std::endl;
out << "\\usepackage{xunicode}" << std::endl;
out << "\\usepackage{xltxtra}" << std::endl;
out << "\\defaultfontfeatures{Scale=MatchLowercase}" << std::endl;
out << "\\setromanfont[Mapping=tex-text]{Myriad Pro}" << std::endl;
out << "\\setsansfont[Mapping=tex-text]{Myriad Pro}" << std::endl;
out << "\\setmonofont{Monaco}" << std::endl;
out << "\\begin{document}" << std::endl;
out << "\\thispagestyle{empty}" << std::endl;
out << "\\setlength{\\tabcolsep}{1ex}" << std::endl;
out << "\\setlength{\\fboxsep}{0ex}" << std::endl;
out << "{\\fontsize{7pt}{0.9em}\\selectfont" << std::endl;
out << "\\framebox{\\begin{tabular*}{60pt}{l@{\\extracolsep{\\fill}}r}" << std::endl;
// This is the particular info for the histogram
out << "Entries & " ;
formatNumber(histogram->GetEntries(), out) << " \\\\" << std::endl;
out << "Mean & " ;
formatNumber(histogram->GetMean(), out) << " \\\\" << std::endl;
out << "RMS & " ;
formatNumber(histogram->GetRMS(), out) << " \\\\" << std::endl;
if (chi2 > 0.0) {
out << "Fit $\\chi^{2}$ & " ;
formatNumber(chi2, out) << " \\\\" << std::endl;
}
RooRealVar *theVariable;
for (int index = 0; index < variables.getSize(); index++) {
theVariable = dynamic_cast<RooRealVar*>(variables.find(variables[index].GetName()));
out << theVariable->GetTitle() << " & $\\textrm{" ;
formatNumber(theVariable->getValV(), out) << "} \\pm \\textrm{" ;
formatNumber(theVariable->getError(), out) << "}$ \\\\" << std::endl;
}
out << "\\end{tabular*}}}" << std::endl;
out << "\\end{document}" << std::endl;
histogram->Delete();
}
bool extractParameter(string fileName, const char* parName, pair<double,double>& value)
{
TFile *f = new TFile( fileName.c_str() );
if (!f) {
cout << "[Error] " << fileName << " not found" << endl; return false;
}
RooWorkspace *ws = (RooWorkspace*) f->Get("workspace");
if (!ws) {
cout << "[ERROR] Workspace not found in " << fileName << endl; return false;
}
RooRealVar *var = ws->var(parName);
if (!var) {
value = make_pair( -999.9 , -999.9 ); return true;
}
value = make_pair( var->getValV() , var->getError() );
return true;
}
RooDataSet * getDataAndFrac(TString name, TString q2name, TreeReader * mydata, TCut cut, RooRealVar * MM, double * frac, Str2VarMap jpsiPars, double *outnsig)
{
RooRealVar * cosThetaL = new RooRealVar("cosThetaL","cosThetaL",0.,-1.,1.);
RooRealVar * cosThetaB = new RooRealVar("cosThetaB","cosThetaB",0.,-1.,1.);
TCut massCut = "Lb_MassConsLambda > 5590 && Lb_MassConsLambda < 5650";
Analysis * ana = new Analysis(name+"_mass"+q2name,"Lb",mydata,&cut,MM);
ana->AddVariable("J_psi_1S_MM");
ana->AddVariable(cosThetaL);
ana->AddVariable(cosThetaB);
RooAbsPdf * mysig = stringToPdf("Gauss","sig",MM,jpsiPars);
RooAbsPdf * mybkg = stringToPdf("Exp","bkgM",MM);
RooRealVar * mynsig = new RooRealVar("mynsig","mynsig",50,0,100000);
RooRealVar * mynbkg = new RooRealVar("mynbkg","mynbkg",10,0,100000);
RooAbsPdf * Mmodel = new RooAddPdf("MassModel","MassModel",RooArgSet(*mysig,*mybkg),RooArgSet(*mynsig,*mynbkg));
ana->applyCuts(&cut);
RooDataSet * data = ana->GetDataSet("-recalc");
Mmodel->fitTo(*data,Extended(kTRUE));
double sigBkg = mybkg->createIntegral(*MM,NormSet(*MM),Range("Signal"))->getVal();
double sig = mysig->createIntegral(*MM,NormSet(*MM),Range("Signal"))->getVal();
double nsig = mynsig->getVal();
double nbkg = mynbkg->getVal();
if(frac)
{
frac[0] = nsig*sig/(nsig*sig+nbkg*sigBkg);
frac[1] = frac[0]*TMath::Sqrt( TMath::Power(mynsig->getError()/nsig,2) + TMath::Power(mynbkg->getError()/nbkg,2) );
}
TCut mycut = cut + massCut;
ana->applyCuts(&mycut);
TCanvas * cc = new TCanvas();
GetFrame(MM,Mmodel,data,"-nochi2-plotAllComp",30,NULL,0,"cos#theta_{#Lambda}")->Draw();
cc->Print("M_"+name+"_"+q2name+".pdf");
if(*outnsig) *outnsig = nsig;
return ana->GetDataSet("-recalc");
}
// internal routine to run the inverter
HypoTestInverterResult *
RooStats::HypoTestInvTool::RunInverter(RooWorkspace * w,
const char * modelSBName, const char * modelBName,
const char * dataName, int type, int testStatType,
bool useCLs, int npoints, double poimin, double poimax,
int ntoys,
bool useNumberCounting,
const char * nuisPriorName ){
std::cout << "Running HypoTestInverter on the workspace " << w->GetName() << std::endl;
w->Print();
RooAbsData * data = w->data(dataName);
if (!data) {
Error("StandardHypoTestDemo","Not existing data %s",dataName);
return 0;
}
else
std::cout << "Using data set " << dataName << std::endl;
if (mUseVectorStore) {
RooAbsData::setDefaultStorageType(RooAbsData::Vector);
data->convertToVectorStore() ;
}
// get models from WS
// get the modelConfig out of the file
ModelConfig* bModel = (ModelConfig*) w->obj(modelBName);
ModelConfig* sbModel = (ModelConfig*) w->obj(modelSBName);
if (!sbModel) {
Error("StandardHypoTestDemo","Not existing ModelConfig %s",modelSBName);
return 0;
}
// check the model
if (!sbModel->GetPdf()) {
Error("StandardHypoTestDemo","Model %s has no pdf ",modelSBName);
return 0;
}
if (!sbModel->GetParametersOfInterest()) {
Error("StandardHypoTestDemo","Model %s has no poi ",modelSBName);
return 0;
}
if (!sbModel->GetObservables()) {
Error("StandardHypoTestInvDemo","Model %s has no observables ",modelSBName);
return 0;
}
if (!sbModel->GetSnapshot() ) {
Info("StandardHypoTestInvDemo","Model %s has no snapshot - make one using model poi",modelSBName);
sbModel->SetSnapshot( *sbModel->GetParametersOfInterest() );
}
// case of no systematics
// remove nuisance parameters from model
if (noSystematics) {
const RooArgSet * nuisPar = sbModel->GetNuisanceParameters();
if (nuisPar && nuisPar->getSize() > 0) {
std::cout << "StandardHypoTestInvDemo" << " - Switch off all systematics by setting them constant to their initial values" << std::endl;
RooStats::SetAllConstant(*nuisPar);
}
if (bModel) {
const RooArgSet * bnuisPar = bModel->GetNuisanceParameters();
if (bnuisPar)
RooStats::SetAllConstant(*bnuisPar);
}
}
if (!bModel || bModel == sbModel) {
Info("StandardHypoTestInvDemo","The background model %s does not exist",modelBName);
Info("StandardHypoTestInvDemo","Copy it from ModelConfig %s and set POI to zero",modelSBName);
bModel = (ModelConfig*) sbModel->Clone();
bModel->SetName(TString(modelSBName)+TString("_with_poi_0"));
RooRealVar * var = dynamic_cast<RooRealVar*>(bModel->GetParametersOfInterest()->first());
if (!var) return 0;
double oldval = var->getVal();
var->setVal(0);
bModel->SetSnapshot( RooArgSet(*var) );
var->setVal(oldval);
}
else {
if (!bModel->GetSnapshot() ) {
Info("StandardHypoTestInvDemo","Model %s has no snapshot - make one using model poi and 0 values ",modelBName);
RooRealVar * var = dynamic_cast<RooRealVar*>(bModel->GetParametersOfInterest()->first());
if (var) {
double oldval = var->getVal();
var->setVal(0);
bModel->SetSnapshot( RooArgSet(*var) );
var->setVal(oldval);
}
else {
Error("StandardHypoTestInvDemo","Model %s has no valid poi",modelBName);
return 0;
}
}
}
// check model has global observables when there are nuisance pdf
// for the hybrid case the globobs are not needed
if (type != 1 ) {
bool hasNuisParam = (sbModel->GetNuisanceParameters() && sbModel->GetNuisanceParameters()->getSize() > 0);
bool hasGlobalObs = (sbModel->GetGlobalObservables() && sbModel->GetGlobalObservables()->getSize() > 0);
if (hasNuisParam && !hasGlobalObs ) {
// try to see if model has nuisance parameters first
RooAbsPdf * constrPdf = RooStats::MakeNuisancePdf(*sbModel,"nuisanceConstraintPdf_sbmodel");
if (constrPdf) {
Warning("StandardHypoTestInvDemo","Model %s has nuisance parameters but no global observables associated",sbModel->GetName());
Warning("StandardHypoTestInvDemo","\tThe effect of the nuisance parameters will not be treated correctly ");
}
}
}
// run first a data fit
const RooArgSet * poiSet = sbModel->GetParametersOfInterest();
RooRealVar *poi = (RooRealVar*)poiSet->first();
std::cout << "StandardHypoTestInvDemo : POI initial value: " << poi->GetName() << " = " << poi->getVal() << std::endl;
// fit the data first (need to use constraint )
TStopwatch tw;
bool doFit = initialFit;
if (testStatType == 0 && initialFit == -1) doFit = false; // case of LEP test statistic
if (type == 3 && initialFit == -1) doFit = false; // case of Asymptoticcalculator with nominal Asimov
double poihat = 0;
if (minimizerType.size()==0) minimizerType = ROOT::Math::MinimizerOptions::DefaultMinimizerType();
else
ROOT::Math::MinimizerOptions::SetDefaultMinimizer(minimizerType.c_str());
Info("StandardHypoTestInvDemo","Using %s as minimizer for computing the test statistic",
ROOT::Math::MinimizerOptions::DefaultMinimizerType().c_str() );
if (doFit) {
// do the fit : By doing a fit the POI snapshot (for S+B) is set to the fit value
// and the nuisance parameters nominal values will be set to the fit value.
// This is relevant when using LEP test statistics
Info( "StandardHypoTestInvDemo"," Doing a first fit to the observed data ");
RooArgSet constrainParams;
if (sbModel->GetNuisanceParameters() ) constrainParams.add(*sbModel->GetNuisanceParameters());
RooStats::RemoveConstantParameters(&constrainParams);
tw.Start();
RooFitResult * fitres = sbModel->GetPdf()->fitTo(*data,InitialHesse(false), Hesse(false),
Minimizer(minimizerType.c_str(),"Migrad"), Strategy(0), PrintLevel(mPrintLevel), Constrain(constrainParams), Save(true) );
if (fitres->status() != 0) {
Warning("StandardHypoTestInvDemo","Fit to the model failed - try with strategy 1 and perform first an Hesse computation");
fitres = sbModel->GetPdf()->fitTo(*data,InitialHesse(true), Hesse(false),Minimizer(minimizerType.c_str(),"Migrad"), Strategy(1), PrintLevel(mPrintLevel+1), Constrain(constrainParams), Save(true) );
}
if (fitres->status() != 0)
Warning("StandardHypoTestInvDemo"," Fit still failed - continue anyway.....");
poihat = poi->getVal();
std::cout << "StandardHypoTestInvDemo - Best Fit value : " << poi->GetName() << " = "
<< poihat << " +/- " << poi->getError() << std::endl;
std::cout << "Time for fitting : "; tw.Print();
//save best fit value in the poi snapshot
sbModel->SetSnapshot(*sbModel->GetParametersOfInterest());
std::cout << "StandardHypoTestInvo: snapshot of S+B Model " << sbModel->GetName()
<< " is set to the best fit value" << std::endl;
}
// print a message in case of LEP test statistics because it affects result by doing or not doing a fit
if (testStatType == 0) {
if (!doFit)
Info("StandardHypoTestInvDemo","Using LEP test statistic - an initial fit is not done and the TS will use the nuisances at the model value");
else
Info("StandardHypoTestInvDemo","Using LEP test statistic - an initial fit has been done and the TS will use the nuisances at the best fit value");
}
// build test statistics and hypotest calculators for running the inverter
SimpleLikelihoodRatioTestStat slrts(*sbModel->GetPdf(),*bModel->GetPdf());
// null parameters must includes snapshot of poi plus the nuisance values
RooArgSet nullParams(*sbModel->GetSnapshot());
if (sbModel->GetNuisanceParameters()) nullParams.add(*sbModel->GetNuisanceParameters());
if (sbModel->GetSnapshot()) slrts.SetNullParameters(nullParams);
RooArgSet altParams(*bModel->GetSnapshot());
if (bModel->GetNuisanceParameters()) altParams.add(*bModel->GetNuisanceParameters());
if (bModel->GetSnapshot()) slrts.SetAltParameters(altParams);
// ratio of profile likelihood - need to pass snapshot for the alt
RatioOfProfiledLikelihoodsTestStat
ropl(*sbModel->GetPdf(), *bModel->GetPdf(), bModel->GetSnapshot());
ropl.SetSubtractMLE(false);
if (testStatType == 11) ropl.SetSubtractMLE(true);
ropl.SetPrintLevel(mPrintLevel);
ropl.SetMinimizer(minimizerType.c_str());
ProfileLikelihoodTestStat profll(*sbModel->GetPdf());
if (testStatType == 3) profll.SetOneSided(true);
if (testStatType == 4) profll.SetSigned(true);
profll.SetMinimizer(minimizerType.c_str());
profll.SetPrintLevel(mPrintLevel);
profll.SetReuseNLL(mOptimize);
slrts.SetReuseNLL(mOptimize);
ropl.SetReuseNLL(mOptimize);
if (mOptimize) {
profll.SetStrategy(0);
ropl.SetStrategy(0);
ROOT::Math::MinimizerOptions::SetDefaultStrategy(0);
}
if (mMaxPoi > 0) poi->setMax(mMaxPoi); // increase limit
MaxLikelihoodEstimateTestStat maxll(*sbModel->GetPdf(),*poi);
NumEventsTestStat nevtts;
AsymptoticCalculator::SetPrintLevel(mPrintLevel);
// create the HypoTest calculator class
HypoTestCalculatorGeneric * hc = 0;
if (type == 0) hc = new FrequentistCalculator(*data, *bModel, *sbModel);
else if (type == 1) hc = new HybridCalculator(*data, *bModel, *sbModel);
// else if (type == 2 ) hc = new AsymptoticCalculator(*data, *bModel, *sbModel, false, mAsimovBins);
// else if (type == 3 ) hc = new AsymptoticCalculator(*data, *bModel, *sbModel, true, mAsimovBins); // for using Asimov data generated with nominal values
else if (type == 2 ) hc = new AsymptoticCalculator(*data, *bModel, *sbModel, false );
else if (type == 3 ) hc = new AsymptoticCalculator(*data, *bModel, *sbModel, true ); // for using Asimov data generated with nominal values
else {
Error("StandardHypoTestInvDemo","Invalid - calculator type = %d supported values are only :\n\t\t\t 0 (Frequentist) , 1 (Hybrid) , 2 (Asymptotic) ",type);
return 0;
}
// set the test statistic
TestStatistic * testStat = 0;
if (testStatType == 0) testStat = &slrts;
if (testStatType == 1 || testStatType == 11) testStat = &ropl;
if (testStatType == 2 || testStatType == 3 || testStatType == 4) testStat = &profll;
if (testStatType == 5) testStat = &maxll;
if (testStatType == 6) testStat = &nevtts;
if (testStat == 0) {
Error("StandardHypoTestInvDemo","Invalid - test statistic type = %d supported values are only :\n\t\t\t 0 (SLR) , 1 (Tevatron) , 2 (PLR), 3 (PLR1), 4(MLE)",testStatType);
return 0;
}
ToyMCSampler *toymcs = (ToyMCSampler*)hc->GetTestStatSampler();
if (toymcs && (type == 0 || type == 1) ) {
// look if pdf is number counting or extended
if (sbModel->GetPdf()->canBeExtended() ) {
if (useNumberCounting) Warning("StandardHypoTestInvDemo","Pdf is extended: but number counting flag is set: ignore it ");
}
else {
// for not extended pdf
if (!useNumberCounting ) {
int nEvents = data->numEntries();
Info("StandardHypoTestInvDemo","Pdf is not extended: number of events to generate taken from observed data set is %d",nEvents);
toymcs->SetNEventsPerToy(nEvents);
}
else {
Info("StandardHypoTestInvDemo","using a number counting pdf");
toymcs->SetNEventsPerToy(1);
}
}
toymcs->SetTestStatistic(testStat);
if (data->isWeighted() && !mGenerateBinned) {
Info("StandardHypoTestInvDemo","Data set is weighted, nentries = %d and sum of weights = %8.1f but toy generation is unbinned - it would be faster to set mGenerateBinned to true\n",data->numEntries(), data->sumEntries());
}
toymcs->SetGenerateBinned(mGenerateBinned);
toymcs->SetUseMultiGen(mOptimize);
if (mGenerateBinned && sbModel->GetObservables()->getSize() > 2) {
Warning("StandardHypoTestInvDemo","generate binned is activated but the number of ovservable is %d. Too much memory could be needed for allocating all the bins",sbModel->GetObservables()->getSize() );
}
// set the random seed if needed
if (mRandomSeed >= 0) RooRandom::randomGenerator()->SetSeed(mRandomSeed);
}
// specify if need to re-use same toys
if (reuseAltToys) {
hc->UseSameAltToys();
}
if (type == 1) {
HybridCalculator *hhc = dynamic_cast<HybridCalculator*> (hc);
assert(hhc);
hhc->SetToys(ntoys,ntoys/mNToysRatio); // can use less ntoys for b hypothesis
// remove global observables from ModelConfig (this is probably not needed anymore in 5.32)
bModel->SetGlobalObservables(RooArgSet() );
sbModel->SetGlobalObservables(RooArgSet() );
// check for nuisance prior pdf in case of nuisance parameters
if (bModel->GetNuisanceParameters() || sbModel->GetNuisanceParameters() ) {
// fix for using multigen (does not work in this case)
toymcs->SetUseMultiGen(false);
ToyMCSampler::SetAlwaysUseMultiGen(false);
RooAbsPdf * nuisPdf = 0;
if (nuisPriorName) nuisPdf = w->pdf(nuisPriorName);
// use prior defined first in bModel (then in SbModel)
if (!nuisPdf) {
Info("StandardHypoTestInvDemo","No nuisance pdf given for the HybridCalculator - try to deduce pdf from the model");
if (bModel->GetPdf() && bModel->GetObservables() )
nuisPdf = RooStats::MakeNuisancePdf(*bModel,"nuisancePdf_bmodel");
else
nuisPdf = RooStats::MakeNuisancePdf(*sbModel,"nuisancePdf_sbmodel");
}
if (!nuisPdf ) {
if (bModel->GetPriorPdf()) {
nuisPdf = bModel->GetPriorPdf();
Info("StandardHypoTestInvDemo","No nuisance pdf given - try to use %s that is defined as a prior pdf in the B model",nuisPdf->GetName());
}
else {
Error("StandardHypoTestInvDemo","Cannnot run Hybrid calculator because no prior on the nuisance parameter is specified or can be derived");
return 0;
}
}
assert(nuisPdf);
Info("StandardHypoTestInvDemo","Using as nuisance Pdf ... " );
nuisPdf->Print();
const RooArgSet * nuisParams = (bModel->GetNuisanceParameters() ) ? bModel->GetNuisanceParameters() : sbModel->GetNuisanceParameters();
RooArgSet * np = nuisPdf->getObservables(*nuisParams);
if (np->getSize() == 0) {
Warning("StandardHypoTestInvDemo","Prior nuisance does not depend on nuisance parameters. They will be smeared in their full range");
}
delete np;
hhc->ForcePriorNuisanceAlt(*nuisPdf);
hhc->ForcePriorNuisanceNull(*nuisPdf);
}
}
else if (type == 2 || type == 3) {
if (testStatType == 3) ((AsymptoticCalculator*) hc)->SetOneSided(true);
if (testStatType != 2 && testStatType != 3)
Warning("StandardHypoTestInvDemo","Only the PL test statistic can be used with AsymptoticCalculator - use by default a two-sided PL");
}
else if (type == 0 || type == 1)
((FrequentistCalculator*) hc)->SetToys(ntoys,ntoys/mNToysRatio);
// Get the result
RooMsgService::instance().getStream(1).removeTopic(RooFit::NumIntegration);
HypoTestInverter calc(*hc);
calc.SetConfidenceLevel(0.95);
calc.UseCLs(useCLs);
calc.SetVerbose(true);
// can speed up using proof-lite
if (mUseProof && mNWorkers > 1) {
ProofConfig pc(*w, mNWorkers, "", kFALSE);
toymcs->SetProofConfig(&pc); // enable proof
}
if (npoints > 0) {
if (poimin > poimax) {
// if no min/max given scan between MLE and +4 sigma
poimin = int(poihat);
poimax = int(poihat + 4 * poi->getError());
}
std::cout << "Doing a fixed scan in interval : " << poimin << " , " << poimax << std::endl;
calc.SetFixedScan(npoints,poimin,poimax);
}
else {
//poi->setMax(10*int( (poihat+ 10 *poi->getError() )/10 ) );
std::cout << "Doing an automatic scan in interval : " << poi->getMin() << " , " << poi->getMax() << std::endl;
}
tw.Start();
HypoTestInverterResult * r = calc.GetInterval();
std::cout << "Time to perform limit scan \n";
tw.Print();
if (mRebuild) {
calc.SetCloseProof(1);
tw.Start();
SamplingDistribution * limDist = calc.GetUpperLimitDistribution(true,mNToyToRebuild);
std::cout << "Time to rebuild distributions " << std::endl;
tw.Print();
if (limDist) {
std::cout << "expected up limit " << limDist->InverseCDF(0.5) << " +/- "
<< limDist->InverseCDF(0.16) << " "
<< limDist->InverseCDF(0.84) << "\n";
//update r to a new updated result object containing the rebuilt expected p-values distributions
// (it will not recompute the expected limit)
if (r) delete r; // need to delete previous object since GetInterval will return a cloned copy
r = calc.GetInterval();
}
else
std::cout << "ERROR : failed to re-build distributions " << std::endl;
}
return r;
}
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;
}
int main(int argc, char **argv)
{
bool printSw = true;
//TString massModel = "Gauss-m[5622]";
string massModel = "DCB-m[5622]";
TString effbase = "/afs/cern.ch/user/p/pluca/work/Lb/Lmumu/results/";
bool printeff = false;
TString dodata = "data";
bool fitsingle = false;
TString wstr = "physRate_polp006";
TString decayToDo = "Lb2Lmumu";
if(dodata=="genMC") wstr += "_noDecay";
gROOT->ProcessLine(".x lhcbStyle.C");
RooRealVar * cosThetaL = new RooRealVar("cosThetaL","cosThetaL",0.,-1.,1.);
RooRealVar * cosThetaB = new RooRealVar("cosThetaB","cosThetaB",0.,-1.,1.);
RooRealVar * nsig_sw = new RooRealVar("nsig_sw","nsig_sw",1,-1.e6,1.e6);
RooRealVar * MCweight = new RooRealVar(wstr,wstr,1.,-1.e10,1.e10);
RooRealVar * MM = new RooRealVar("Lb_MassConsLambda","Lb_MassConsLambda",5620.,5500.,5900.);
TString datafilename = "/afs/cern.ch/user/p/pluca/work/Lb/Lmumu/candLb.root";
if(dodata=="MC") datafilename = "/afs/cern.ch/user/p/pluca/work/Lb/Lmumu/candLb_MC.root";
if(dodata=="genMC") datafilename = "/afs/cern.ch/work/p/pluca/weighted/Lmumu/"+(string)decayToDo+"_geomMC_Pythia8_NBweighted.root";
TreeReader * data;
if(dodata!="genMC") data = new TreeReader("cand"+decayToDo);
else data = new TreeReader("MCtree");
data->AddFile(datafilename);
TFile * histFile = new TFile("Afb_hist.root","recreate");
RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR);
int nbins = 1;//CutsDef::nq2bins;
double q2min[] = {15.,11.0,15,16,18};//&CutsDef::q2min_highfirst[0];
double q2max[] = {20.,12.5,16,18,20};//&CutsDef::q2max_highfirst[0];
//int nbins = CutsDef::nq2bins
//double *q2min = &CutsDef::q2min[0];
//double *q2max = &CutsDef::q2max[0];
TGraphErrors * Afb_vs_q2 = new TGraphErrors();
TGraphErrors * AfbB_vs_q2 = new TGraphErrors();
TGraphErrors * fL_vs_q2 = new TGraphErrors();
TCanvas * ceff = new TCanvas();
RooCategory * samples = new RooCategory("samples","samples");
samples->defineType("DD");
samples->defineType("LL");
RooRealVar * afb = new RooRealVar("afb","afb",0.,-100,100);
RooRealVar * fL = new RooRealVar("fL","fL",0.7,-1.,10.);
//RooRealVar * afb = new RooRealVar("afb","afb",0.,-1.,1.);
//RooRealVar * fL = new RooRealVar("fL","fL",0.7,0.,1.);
RooRealVar * origafb = new RooRealVar("afb","afb",0.,-1.,1.);
RooRealVar * origfL = new RooRealVar("fL","fL",0.7,-1.,10.);
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.,-100,100);
//RooRealVar * afbB = new RooRealVar("afbB","afbB",0.,-1.,1.);
RooRealVar * origafbB = new RooRealVar("afbB","afbB",0.,-1.,1.);
TString afbBpdf = "(1 + 2*afbB*cosThetaB)";
vector< vector< double > > afb_errs, afbB_errs, fL_errs;
TList * LLlist = new TList, * DDlist = new TList;
TCanvas * cDD = new TCanvas();
TCanvas * cLL = new TCanvas();
TCanvas * cDDB = new TCanvas();
TCanvas * cLLB = new TCanvas();
for(int i = 0; i < nbins; i++)
{
//if(q2min[i] < 8) continue;
TString q2name = ((TString)Form("q2_%4.2f_%4.2f",q2min[i],q2max[i])).ReplaceAll(".","");
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]);
//TString curq2cut = Form("TMath::Power(J_psi_1S_MM/1000,2) >= %e && TMath::Power(J_psi_1S_MM/1000,2) < %e && (Lb_MassConsLambda > 5680 || Lb_MassConsLambda < 5590)",q2min[i],q2max[i]);
cout << "------------------- q2 bin: " << q2min[i] << " - " << q2max[i] << " -----------------------" << endl;
TFile * effFile = NULL;
TH1F * effDD = NULL, * effLL = NULL, * effLLB = NULL, * effDDB = NULL;
if(q2min[i] == 15 && q2max[i] == 20)
{
effFile = TFile::Open(effbase+"LbeffvscosThetaL_DD.root");
effDD = (TH1F *)effFile->Get("htoteff");
effFile = TFile::Open(effbase+"LbeffvscosThetaL_LL.root");
effLL = (TH1F *)effFile->Get("htoteff");
effFile = TFile::Open(effbase+"LbeffvscosThetaB_DD.root");
effDDB = (TH1F *)effFile->Get("htot_nodet_eff");
effFile = TFile::Open(effbase+"LbeffvscosThetaB_LL.root");
effLLB = (TH1F *)effFile->Get("htot_nodet_eff");
}
else
{
effFile = TFile::Open(effbase+"Lbeff2D_cosThetaL_vs_q2_DD.root");
TH2F * effDD2D = (TH2F *)effFile->Get("htot_eff");
effDD = (TH1F*)GetSliceX(effDD2D,(q2max[i]+q2min[i])/2.);
effFile = TFile::Open(effbase+"Lbeff2D_cosThetaL_vs_q2_LL.root");
TH2F * effLL2D = (TH2F *)effFile->Get("htot_eff");
effLL = (TH1F*)GetSliceX(effLL2D,(q2max[i]+q2min[i])/2.);
effFile = TFile::Open(effbase+"Lbeff2D_cosThetaB_vs_q2_DD.root");
TH2F * effDDB2D = (TH2F *)effFile->Get("hupper_eff");
effDDB = (TH1F*)GetSliceX(effDDB2D,(q2max[i]+q2min[i])/2.);
effFile = TFile::Open(effbase+"Lbeff2D_cosThetaB_vs_q2_LL.root");
TH2F * effLLB2D = (TH2F *)effFile->Get("hupper_eff");
effLLB = (TH1F*)GetSliceX(effLLB2D,(q2max[i]+q2min[i])/2.);
}
ceff->cd();
/** FIT EFFICIENCY **/
RooDataHist * hLL = new RooDataHist("hLL","hLL",*cosThetaL,effLL);
RooDataHist * hDD = new RooDataHist("hDD","hDD",*cosThetaL,effDD);
RooRealVar * c1LL = new RooRealVar("c1LL","",0.,-1.,1);
RooRealVar * c1DD = new RooRealVar("c1DD","",0.,-1.,1);
RooRealVar * c2LL = new RooRealVar("c2LL","",0.,-1.,1);
RooRealVar * c2DD = new RooRealVar("c2DD","",0.,-1.,1);
TString effLLstr = "(1 + c1LL*cosThetaL + c2LL*TMath::Power(cosThetaL,2))";
TString effDDstr = "(1 + c1DD*cosThetaL + c2DD*TMath::Power(cosThetaL,2))";
RooAbsPdf * effLLpdf = new RooGenericPdf("effLLpdf", "", effLLstr, RooArgSet(*cosThetaL, *c1LL, *c2LL));
RooAbsPdf * effDDpdf = new RooGenericPdf("effDDpdf", "", effDDstr, RooArgSet(*cosThetaL, *c1DD, *c2DD));
effLLpdf->fitTo(*hLL,PrintLevel(-1));
effDDpdf->fitTo(*hDD,PrintLevel(-1));
fixParams(effLLpdf,cosThetaL);
fixParams(effDDpdf,cosThetaL);
RooDataHist * hLLB = new RooDataHist("hLLB","hLLB",*cosThetaB,effLLB);
RooDataHist * hDDB = new RooDataHist("hDDB","hDDB",*cosThetaB,effDDB);
RooRealVar * cB1LL = new RooRealVar("cB1LL","",0,-1.,1);
RooRealVar * cB1DD = new RooRealVar("cB1DD","",0,-1.,1);
RooRealVar * cB2LL = new RooRealVar("cB2LL","",0,-1.,1);
RooRealVar * cB2DD = new RooRealVar("cB2DD","",0,-1.,1);
TString effLLBstr = "(1 + cB1LL*cosThetaB + cB2LL*TMath::Power(cosThetaB,2))";
TString effDDBstr = "(1 + cB1DD*cosThetaB + cB2DD*TMath::Power(cosThetaB,2))";
RooAbsPdf * effLLpdfB = new RooGenericPdf("effLLpdfB", "", effLLBstr, RooArgSet(*cosThetaB, *cB1LL, *cB2LL));
RooAbsPdf * effDDpdfB = new RooGenericPdf("effDDpdfB", "", effDDBstr, RooArgSet(*cosThetaB, *cB1DD, *cB2DD));
effLLpdfB->fitTo(*hLLB,PrintLevel(-1));
effDDpdfB->fitTo(*hDDB,PrintLevel(-1));
fixParams(effLLpdfB,cosThetaB);
fixParams(effDDpdfB,cosThetaB);
//cout << q2min[i] << " - " << q2max[i] << " LL cosThetaL -> " << c1LL->getVal() << " " << c2LL->getVal() << endl;
//cout << q2min[i] << " - " << q2max[i] << " DD cosThetaL -> " << c1DD->getVal() << " " << c2DD->getVal() << endl;
//cout << q2min[i] << " - " << q2max[i] << " LL cosThetaB -> " << cB1LL->getVal() << " " << cB2LL->getVal() << endl;
//cout << q2min[i] << " - " << q2max[i] << " DD cosThetaB -> " << cB1DD->getVal() << " " << cB2DD->getVal() << endl;
if(printeff) {
GetFrame(cosThetaL, hLL,effLLpdf,"-nochi2",0,NULL,0,"cos#theta_{l}","Tot. eff.")->Draw();
ceff->Print("DDeffFit"+q2name+".pdf");
GetFrame(cosThetaL, hDD,effDDpdf,"-nochi2",0,NULL,0,"cos#theta_{l}","Tot. eff.")->Draw();
ceff->Print("LLeffFit"+q2name+".pdf");
GetFrame(cosThetaB, hLLB,effLLpdfB,"-nochi2",0,NULL,0,"cos#theta_{#Lambda}","Tot. eff.")->Draw();
ceff->Print("DDeffFitB"+q2name+".pdf");
GetFrame(cosThetaB, hDDB,effDDpdfB,"-nochi2",0,NULL,0,"cos#theta_{#Lambda}","Tot. eff.")->Draw();
ceff->Print("LLeffFitB"+q2name+".pdf"); }
/** FIT AFB **/
afb->setVal(0);
afbB->setVal(0);
fL->setVal(0.7);
TString LLnorm = "1./( 1. + (2./3.)*afb*c1LL + (2./5.)*c2LL - (1./5.)*c2LL*fL )*"+effLLstr;
TString DDnorm = "1./( 1. + (2./3.)*afb*c1DD + (2./5.)*c2DD - (1./5.)*c2DD*fL )*"+effDDstr;
RooAbsPdf * corrPdfLL = new RooGenericPdf(Form("corrPdfLL_%i",i),LLnorm+"*"+afbLpdf,RooArgSet(*cosThetaL, *afb, *fL, *c1LL, *c2LL) );
RooAbsPdf * corrPdfDD = new RooGenericPdf(Form("corrPdfDD_%i",i),DDnorm+"*"+afbLpdf,RooArgSet(*cosThetaL, *afb, *fL, *c1DD, *c2DD) );
TString LLnormB = "1./( (2./3.)*( 2*afbB*cB1LL + cB2LL + 3.) )*"+effLLBstr;
TString DDnormB = "1./( (2./3.)*( 2*afbB*cB1DD + cB2DD + 3.) )*"+effDDBstr;
RooAbsPdf * corrPdfLLB = new RooGenericPdf(Form("corrPdfLLB_%i",i),LLnormB+"*"+afbBpdf,RooArgSet(*cosThetaB, *afbB, *cB1LL, *cB2LL) );
RooAbsPdf * corrPdfDDB = new RooGenericPdf(Form("corrPdfDDB_%i",i),DDnormB+"*"+afbBpdf,RooArgSet(*cosThetaB, *afbB, *cB1DD, *cB2DD) );
TCut cutLL = CutsDef::LLcut + (TCut)curq2cut;
TCut cutDD = CutsDef::DDcut + (TCut)curq2cut;
if(dodata=="genMC")
{
corrPdfLLB = new RooGenericPdf("corrPdfLL",afbBpdf,RooArgSet(*cosThetaB, *afbB, *cB1LL, *cB2LL) );
corrPdfDDB = new RooGenericPdf("corrPdfDD",afbBpdf,RooArgSet(*cosThetaB, *afbB, *cB1DD, *cB2DD) );
corrPdfLL = new RooGenericPdf("corrPdfLL",afbLpdf,RooArgSet(*cosThetaL, *afb, *fL, *c1LL, *c2LL) );
corrPdfDD = new RooGenericPdf("corrPdfDD",afbLpdf,RooArgSet(*cosThetaL, *afb, *fL, *c1DD, *c2DD) );
cutLL = (TCut)curq2cut;
cutDD = (TCut)curq2cut;
}
Analysis * anaLL = new Analysis(Form("LL_mass_%i",i),"Lb",data,&cutLL,MM);
anaLL->AddVariable(cosThetaL);
anaLL->AddVariable(cosThetaB);
anaLL->AddVariable("J_psi_1S_MM");
if(dodata!="data") anaLL->SetWeight(wstr);
RooDataSet * dataLL = anaLL->GetDataSet("-recalc-docuts");
Analysis * anaDD = new Analysis(Form("DD_mass_%i",i),"Lb",data,&cutDD,MM);
anaDD->AddVariable(cosThetaL);
anaDD->AddVariable(cosThetaB);
anaDD->AddVariable("J_psi_1S_MM");
if(dodata!="data") anaDD->SetWeight(wstr);
RooDataSet * dataDD = anaDD->GetDataSet("-recalc-docuts");
RooDataSet * sdataDD, * sdataLL;
if(dodata=="data")
{
sdataLL = anaLL->CalcSweight("",massModel.c_str(),"Exp");
if(printSw) {
GetFrame(MM,NULL,sdataLL,"-nochi2",30,NULL,0,"M(#Lambda#mu#mu) (MeV/c^{2})")->Draw();
ceff->Print("Mass_LL_sWeighted"+q2name+".pdf");
GetFrame(cosThetaL,NULL,sdataLL,"-nochi2",6,NULL,0,"cos#theta_{l}")->Draw();
ceff->Print("cosThetaL_LL_sWeighted"+q2name+".pdf");
GetFrame(cosThetaL,NULL,dataLL,"-nochi2",6,NULL,0,"cos#theta_{l}")->Draw();
ceff->Print("cosThetaL_LL_"+q2name+".pdf");
}
sdataDD = anaDD->CalcSweight("",massModel.c_str(),"Exp");
if(printSw) {
GetFrame(MM,NULL,sdataDD,"-nochi2",30,NULL,0,"M(#Lambda#mu#mu) (MeV/c^{2})")->Draw();
ceff->Print("Mass_DD_sWeighted"+q2name+".pdf");
GetFrame(cosThetaL,NULL,sdataDD,"-nochi2",10,NULL,0,"cos#theta_{l}")->Draw();
ceff->Print("cosThetaL_DD_sWeighted"+q2name+".pdf");
GetFrame(cosThetaL,NULL,dataDD,"-nochi2",10,NULL,0,"cos#theta_{l}")->Draw();
ceff->Print("cosThetaL_DD_"+q2name+".pdf");
}
}
else { sdataLL = dataLL; sdataDD = dataDD; }
histFile->cd();
TTree * LLTree = (TTree*)sdataLL->tree();
LLTree->SetName(Form("treeLL_%i",i));
LLlist->Add(LLTree);
TTree * DDTree = (TTree*)sdataDD->tree();
DDTree->SetName(Form("treeDD_%i",i));
DDlist->Add(DDTree);
// CREATE COMBINED DATASET
RooDataSet * combData;
if(dodata=="data") combData = new RooDataSet(Form("combData_%i",i),"combined data",RooArgSet(*cosThetaL,*cosThetaB,*nsig_sw),Index(*samples),Import("DD",*sdataDD),Import("LL",*sdataLL),WeightVar("nsig_sw"));
else combData = new RooDataSet(Form("combData_%i",i),"combined data",RooArgSet(*cosThetaL,*cosThetaB,*MCweight),Index(*samples),Import("DD",*sdataDD),Import("LL",*sdataLL),WeightVar(wstr));
// FIT COS LEPTON
RooSimultaneous * combModel = new RooSimultaneous(Form("combModel_%i",i),"",*samples);
combModel->addPdf(*corrPdfLL,"LL");
combModel->addPdf(*corrPdfDD,"DD");
combModel->fitTo(*combData,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE));
if(fitsingle) corrPdfLL->fitTo(*sdataLL,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE));
GetFrame(cosThetaL,corrPdfLL,sdataLL,"-sumW2err-nochi2-noCost",6,NULL,0,"cos#theta_{l}")->Draw();
ceff->Print("Afb_LL_"+q2name+".pdf");
if(fitsingle) corrPdfDD->fitTo(*sdataDD,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE));
GetFrame(cosThetaL,corrPdfDD,sdataDD,"-sumW2err-nochi2-noCost",10,NULL,0,"cos#theta_{l}")->Draw();
ceff->Print("Afb_DD_"+q2name+".pdf");
Afb_vs_q2->SetPoint(i,(q2max[i] + q2min[i])/2.,afb->getVal());
Afb_vs_q2->SetPointError(i,(q2max[i] - q2min[i])/2.,afb->getError());
fL_vs_q2->SetPoint(i,(q2max[i] + q2min[i])/2.,fL->getVal());
fL_vs_q2->SetPointError(i,(q2max[i] - q2min[i])/2.,fL->getError());
// FIT COS HADRON
RooSimultaneous * combModelB = new RooSimultaneous(Form("combModelB_%i",i),"",*samples);
combModelB->addPdf(*corrPdfLLB,"LL");
combModelB->addPdf(*corrPdfDDB,"DD");
combModelB->fitTo(*combData,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE));
if(fitsingle) corrPdfLLB->fitTo(*sdataLL,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE));
GetFrame(cosThetaB,corrPdfLLB,sdataLL,"-sumW2err-nochi2-noCost",6,NULL,0,"cos#theta_{#Lambda}")->Draw();
ceff->Print("AfbB_LL_"+q2name+".pdf");
if(fitsingle) corrPdfDDB->fitTo(*sdataDD,PrintLevel(-1),Verbose(kFALSE),SumW2Error(kTRUE));
GetFrame(cosThetaB,corrPdfDDB,sdataDD,"-sumW2err-nochi2-noCost",10,NULL,0,"cos#theta_{#Lambda}")->Draw();
ceff->Print("AfbB_DD_"+q2name+".pdf");
AfbB_vs_q2->SetPoint(i,(q2max[i] + q2min[i])/2.,afbB->getVal());
AfbB_vs_q2->SetPointError(i,(q2max[i] - q2min[i])/2.,afbB->getError());
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 << "------------------------ FELDMAN AND COUSINS ------------------------" << endl;
vector < RooDataSet * > datas;
vector < RooAbsPdf * > pdfs, pdfsB;
vector < TString > cat;
cat.push_back("LL");
cat.push_back("DD");
datas.push_back(sdataLL);
datas.push_back(sdataDD);
RooArgSet * origPars = new RooArgSet();
origPars->add(*origafb);
origPars->add(*origfL);
pdfs.push_back(corrPdfLL);
pdfs.push_back(corrPdfDD);
vector< double > afb_err, afbB_err, fL_err;
/*
double fLval = fL->getVal(), fLerr = fL->getError();
FeldmanCousins * FC = new FeldmanCousins(q2name,cat,datas,pdfs,cosThetaL,afb,"nsig_sw");
//FC->SetNPointsToScan(20);
//FC->SetNExp(1000);
if(q2min[i]==18) afb_err = FC->ExtractLimits(origPars,-0.3,0.3);
else if( (afb->getVal()-1.4*afb->getError()) > -1 && (afb->getVal()+1.4*afb->getError()) < 1 )
afb_err = FC->ExtractLimits(origPars,afb->getVal()-1.4*afb->getError(),afb->getVal()+1.4*afb->getError());
else afb_err = FC->ExtractLimits(origPars,-0.4,0.4);
//FeldmanCousins * FCfL = new FeldmanCousins(q2name,cat,datas,pdfs,cosThetaL,fL,"nsig_sw");
//if(q2min[i]==11) fL_err = FCfL->ExtractLimits(origPars,0.,0.6);
//else if (q2min[i]==18) fL_err = FCfL->ExtractLimits(origPars,0.75,0.992);
//( (fLval-1.3*fLerr) > 0 && (fLval+1.3*fLerr) <= 1 )
//else fL_err = FCfL->ExtractLimits(origPars,fLval-1.3*fLerr,fLval+1.3*fLerr);
afb_errs.push_back(afb_err);
//fL_errs.push_back(fL_err);
RooArgSet * origParsB = new RooArgSet();
origParsB->add(*origafbB);
pdfsB.push_back(corrPdfLLB);
pdfsB.push_back(corrPdfDDB);
FeldmanCousins * FCB = new FeldmanCousins(q2name,cat,datas,pdfsB,cosThetaB,afbB,"nsig_sw");
if( (afbB->getVal()-1.5*afbB->getError()) > -1 && (afbB->getVal()+1.5*afbB->getError()) < 1 )
afbB_err = FCB->ExtractLimits(origParsB,afbB->getVal()-1.5*afbB->getError(),afbB->getVal()+1.5*afbB->getError());
else afbB_err = FCB->ExtractLimits(origParsB,-0.4,0.4);
afbB_errs.push_back(afbB_err);
*/
delete effDD;
delete effLL;
delete effLLB;
delete effDDB;
}
cDD->Print("DDeff.pdf");
cLL->Print("LLeff.pdf");
cDDB->Print("DDBeff.pdf");
cLLB->Print("LLBeff.pdf");
Afb_vs_q2->GetXaxis()->SetTitle("q^{2}");
Afb_vs_q2->GetYaxis()->SetTitle("Afb");
Afb_vs_q2->SetMaximum(1);
Afb_vs_q2->SetMinimum(-1);
Afb_vs_q2->Draw("AP");
ceff->Print("Afb_vs_q2.pdf");
AfbB_vs_q2->GetXaxis()->SetTitle("q^{2}");
AfbB_vs_q2->GetYaxis()->SetTitle("AfbB");
AfbB_vs_q2->SetMaximum(1);
AfbB_vs_q2->SetMinimum(-1);
AfbB_vs_q2->Draw("AP");
ceff->Print("AfbB_vs_q2.pdf");
fL_vs_q2->GetXaxis()->SetTitle("q^{2}");
fL_vs_q2->GetYaxis()->SetTitle("fL");
fL_vs_q2->Draw("AP");
ceff->Print("fL_vs_q2.pdf");
for(int bb = 0; bb < Afb_vs_q2->GetN(); bb++)
{
double qq, qqerr, afbv, afbBv, fLv;
Afb_vs_q2->GetPoint(bb,qq,afbv);
qqerr = Afb_vs_q2->GetErrorX(bb);
AfbB_vs_q2->GetPoint(bb,qq,afbBv);
fL_vs_q2->GetPoint(bb,qq,fLv);
cout << fixed << setprecision(1) << qq-qqerr << " - " << qq+qqerr;
cout << fixed << setprecision(4);
//cout << " & $" << afbv << "_{-" << TMath::Abs(afb_errs[bb][0] - afbv) << "}^{+" << TMath::Abs(afb_errs[bb][1] - afbv) << "} \\text{(stat)} \\pm \\text{(sys)}$ ";
//cout << " & $" << afbBv << "_{-" << TMath::Abs(afbB_errs[bb][0] - afbBv) << "}^{+" << TMath::Abs(afbB_errs[bb][1]-afbBv) << "} \\text{(stat)} \\pm \\text{(sys)}$ " ;
//cout << " & $" << fLv << "_{-" << TMath::Abs(fL_errs[bb][0] - fLv) << "}^{+" << TMath::Abs(fL_errs[bb][1] - fLv) << "} \\text{(stat)} \\pm \\text{(sys)}$ ";
cout << " \\\\ " << endl;
}
histFile->cd();
TTree * finalLLtree = (TTree*)TTree::MergeTrees(LLlist);
TTree * finalDDtree = (TTree*)TTree::MergeTrees(DDlist);
finalLLtree->SetName("LL_data");
finalDDtree->SetName("DD_data");
finalLLtree->Write();
finalDDtree->Write();
delete ceff;
histFile->Write();
delete histFile;
}
void FitBias(TString CAT,TString CUT,float SIG,float BKG,int NTOYS)
{
gROOT->ForceStyle();
RooMsgService::instance().setSilentMode(kTRUE);
RooMsgService::instance().setStreamStatus(0,kFALSE);
RooMsgService::instance().setStreamStatus(1,kFALSE);
// -----------------------------------------
TFile *fTemplates = TFile::Open("templates_"+CUT+"_"+CAT+"_workspace.root");
RooWorkspace *wTemplates = (RooWorkspace*)fTemplates->Get("w");
RooRealVar *x = (RooRealVar*)wTemplates->var("mTop");
RooAbsPdf *pdf_signal = (RooAbsPdf*)wTemplates->pdf("ttbar_pdf_Nominal");
RooAbsPdf *pdf_bkg = (RooAbsPdf*)wTemplates->pdf("qcdCor_pdf");
TRandom *rnd = new TRandom();
rnd->SetSeed(0);
x->setBins(250);
RooPlot *frame;
TFile *outf;
if (NTOYS > 1) {
outf = TFile::Open("FitBiasToys_"+CUT+"_"+CAT+".root","RECREATE");
}
float nSigInj,nBkgInj,nSigFit,nBkgFit,eSigFit,eBkgFit,nll;
TTree *tr = new TTree("toys","toys");
tr->Branch("nSigInj",&nSigInj,"nSigInj/F");
tr->Branch("nSigFit",&nSigFit,"nSigFit/F");
tr->Branch("nBkgInj",&nBkgInj,"nBkgInj/F");
tr->Branch("nBkgFit",&nBkgFit,"nBkgFit/F");
tr->Branch("eSigFit",&eSigFit,"eSigFit/F");
tr->Branch("eBkgFit",&eBkgFit,"eBkgFit/F");
tr->Branch("nll" ,&nll ,"nll/F");
for(int itoy=0;itoy<NTOYS;itoy++) {
// generate pseudodataset
nSigInj = rnd->Poisson(SIG);
nBkgInj = rnd->Poisson(BKG);
RooRealVar *nSig = new RooRealVar("nSig","nSig",nSigInj);
RooRealVar *nBkg = new RooRealVar("nBkg","nBkg",nBkgInj);
RooAddPdf *model = new RooAddPdf("model","model",RooArgList(*pdf_signal,*pdf_bkg),RooArgList(*nSig,*nBkg));
RooDataSet *data = model->generate(*x,nSigInj+nBkgInj);
RooDataHist *roohist = new RooDataHist("roohist","roohist",RooArgList(*x),*data);
// build fit model
RooRealVar *nFitSig = new RooRealVar("nFitSig","nFitSig",SIG,0,10*SIG);
RooRealVar *nFitBkg = new RooRealVar("nFitBkg","nFitBkg",BKG,0,10*BKG);
RooAddPdf *modelFit = new RooAddPdf("modelFit","modelFit",RooArgList(*pdf_signal,*pdf_bkg),RooArgList(*nFitSig,*nFitBkg));
// fit the pseudo dataset
RooFitResult *res = modelFit->fitTo(*roohist,RooFit::Save(),RooFit::Extended(kTRUE));
//res->Print();
nSigFit = nFitSig->getVal();
nBkgFit = nFitBkg->getVal();
eSigFit = nFitSig->getError();
eBkgFit = nFitBkg->getError();
nll = res->minNll();
tr->Fill();
if (itoy % 100 == 0) {
cout<<"Toy #"<<itoy<<": injected = "<<nSigInj<<", fitted = "<<nSigFit<<", error = "<<eSigFit<<endl;
}
if (NTOYS == 1) {
frame = x->frame();
roohist->plotOn(frame);
model->plotOn(frame);
}
}
if (NTOYS == 1) {
TCanvas *can = new TCanvas("Toy","Toy",900,600);
frame->Draw();
}
else {
outf->cd();
tr->Write();
outf->Close();
fTemplates->Close();
}
}
vector<float*> simFit(
const string tnp_ = "elecTnP",
const string category_ = "elecID80",
double cutValue_ = 0.5,
const string bin_ = "abseta>1.5",
const float binCenter_ = 0.75,
const float binWidth_ = 0.75,
const float xLow_ = 40,
const float xHigh_ = 120,
const float nBins_ = 24,
bool doBinned_ = true,
float deltaAlpha_ = 0.0,
float deltaN_ = 0.0,
float scale_ = 0.0
)
{
vector<float*> out;
TFile fSgn("../prod/ElecTnP/treeElecTnP_DYJets-50-madgraph-PUS4-TnP.root");
TTree *fullTreeSgn = (TTree*)fSgn.Get((tnp_+"/fitter_tree").c_str());
fSgn.cd("allEventsFilter");
TH1F* totalEventsSgn = (TH1F*)gDirectory->Get("totalEvents");
float readEventsSgn = totalEventsSgn->GetBinContent(1);
// data
TFile fdat("../prod/ElecTnP/treeElecTnP_DYJets-50-madgraph-PUS4-TnP.root");
TTree *fullTreeData = (TTree*)fdat.Get((tnp_+"/fitter_tree").c_str());
TH1F* hS = new TH1F("hS","",1,0,150);
TH1F* hSP = new TH1F("hSP","",1,0,150);
fullTreeSgn->Draw("mass>>hS",Form("tag_puMCWeight*(%s && mass>%f && mass<%f && mcTrue && tag_genDecay==23*11 && tag_pfRelIso<0.1 && pair_tnpCharge==0 && event_met_pfmet<25 && tag_pt>35)",bin_.c_str(),xLow_,xHigh_));
float SGNtrue = hS->Integral();
fullTreeSgn->Draw("mass>>hSP",Form("tag_puMCWeight*(%s && %s>=%f && mass>%f && mass<%f && mcTrue && tag_genDecay==23*11 && tag_pfRelIso<0.1 && pair_tnpCharge==0 && event_met_pfmet<25 && tag_pt>35)",bin_.c_str(),category_.c_str(),cutValue_,xLow_,xHigh_));
float SGNtruePass = hSP->Integral();
float McTruthEff = SGNtruePass/SGNtrue;
float BinomialError = TMath::Sqrt(SGNtruePass/SGNtrue*(1-SGNtruePass/SGNtrue)/SGNtrue);
cout << bin_.c_str() << " ==> MCTRUTH: " << McTruthEff << " +/- " << BinomialError << endl;
delete hS; delete hSP;
// file to copy the trees
TFile *templFile = new TFile(Form("dummyTempl_bin%.2f.root",binCenter_),"RECREATE");
TTree* fullTreeSgnCutP = fullTreeSgn->CopyTree( Form("(%s>=%f && %s && pair_tnpCharge==0 && event_met_pfmet<25 && mcTrue && tag_genDecay==23*11 && tag_pfRelIso<0.1 && tag_pt>35)",category_.c_str(),cutValue_,bin_.c_str()) );
TTree* fullTreeSgnCutF = fullTreeSgn->CopyTree( Form("(%s< %f && %s && pair_tnpCharge==0 && event_met_pfmet<25 && mcTrue && tag_genDecay==23*11 && tag_pfRelIso<0.1 && tag_pt>35)",category_.c_str(),cutValue_,bin_.c_str()) );
RooRealVar mass("mass","m_{tp} (GeV/c^{2})",xLow_,xHigh_);
mass.setBins( 10000, "fft" );
mass.setBins( nBins_ );
RooRealVar meanBkgP("meanBkgP","",59,30,100);
RooRealVar sigmaBkgP("sigmaBkgP","",11,0,50);
//RooLandau bkgPdfP("bkgPdfP","",mass,meanBkgP,sigmaBkgP);
RooRealVar DataCP("DataCP","",0);
RooExponential bkgPdfP("bkgPdfP","",mass,DataCP);
RooRealVar meanBkgF("meanBkgF","",59,30,100);
RooRealVar sigmaBkgF("sigmaBkgF","",11,0,50);
//RooLandau bkgPdfF("bkgPdfF","",mass,meanBkgF,sigmaBkgF);
RooRealVar DataCF("DataCF","",0,-10,10);
RooExponential bkgPdfF("bkgPdfF","",mass,DataCF);
TCanvas *c0 = new TCanvas("fitCanvas","canvas",10,30,650,600);
c0->SetGrid(0,0);
c0->SetFillStyle(4000);
c0->SetFillColor(10);
c0->SetTicky();
c0->SetObjectStat(0);
mass.setBins( 50 );
/////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////
// passing:
RooDataSet sgnDataSetP("sgnDataSetP","dataset for signal", RooArgSet(mass), Import( *fullTreeSgnCutP ) );
RooDataHist sgnDataHistP("sgnDataHistP","",RooArgSet(mass),sgnDataSetP, 1.0);
//RooHistPdf sgnTemplatePdfP("sgnTemplatePdfP","",RooArgSet(mass),sgnDataHistP);
RooKeysPdf sgnTemplatePdfP("sgnTemplatePdfP","",mass,sgnDataSetP);
// Breit-Wigner
RooRealVar meanSgnP("meanSgnP","mean",91.19,85,100);
RooRealVar widthSgnP("widthSgnP","width",2.49,0.,10);
RooBreitWigner bwSgnP("bwSgnP","bw",mass,meanSgnP,widthSgnP);
// Crystall Ball
RooRealVar m1SgnP("m1SgnP","m1",0,-20,20);
RooRealVar sigmaSgnP("sigmaSgnP","sigma",0.5,0,20);
RooRealVar alfaSgnP("alfaSgnP","alfa", 0.5,-10,10);
RooRealVar nSgnP("nSgnP","n", 1,1e-06,50);
RooCBShape cbSgnP("cbSgnP","",mass,m1SgnP,sigmaSgnP,alfaSgnP,nSgnP);
mass.setBins( 1000 , "fft");
// BW (X) CB
RooFFTConvPdf bvcbSgnP("bvcbSgnP","",mass,bwSgnP, cbSgnP);
RooFitResult* ResSgnFitP = bvcbSgnP.fitTo(sgnDataSetP, Minos(1), Save(1), NumCPU(4) );
RooArgSet FitParamSgnP(ResSgnFitP->floatParsFinal());
RooRealVar* m1SgnFitP = (RooRealVar*)(&FitParamSgnP["m1SgnP"]);
RooRealVar* sigmaSgnFitP = (RooRealVar*)(&FitParamSgnP["sigmaSgnP"]);
RooRealVar* alfaSgnFitP = (RooRealVar*)(&FitParamSgnP["alfaSgnP"]);
RooRealVar* nSgnFitP = (RooRealVar*)(&FitParamSgnP["nSgnP"]);
RooRealVar* nMeanSgnFitP = (RooRealVar*)(&FitParamSgnP["meanSgnP"]);
RooRealVar* nWidthSgnFitP= (RooRealVar*)(&FitParamSgnP["widthSgnP"]);
RooRealVar m1SgnP_C("m1SgnP_C","m1",m1SgnFitP->getVal(),-10,10);
RooRealVar sigmaSgnP_C("sigmaSgnP_C","sigma",sigmaSgnFitP->getVal(),0,20);
// choose to let it float or not
RooRealVar meanSgnP_C("meanSgnP_C","mean", nMeanSgnFitP->getVal() ,80,120);
RooRealVar widthSgnP_C("widthSgnP_C","width",nWidthSgnFitP->getVal() /*,0.,10*/);
RooRealVar alfaSgnP_C("alfaSgnP_C","alfa",alfaSgnFitP->getVal()*(1+deltaAlpha_)/*,0,20*/);
RooRealVar nSgnP_C("nSgnP_C","n",nSgnFitP->getVal()*(1+deltaN_)/*,0,50*/);
RooCBShape cbSgnP_C("cbSgnP_C","",mass,m1SgnP_C,sigmaSgnP_C,alfaSgnP_C,nSgnP_C);
RooLognormal alfaSgnP_CPdf("alfaSgnP_CPdf","",alfaSgnP_C,RooConst(alfaSgnFitP->getVal()),RooConst(1.5));
RooLognormal nSgnP_CPdf("nSgnP_CPdf","",nSgnP_C,RooConst(nSgnFitP->getVal()), RooConst(1.5));
RooLognormal meanSgnP_CPdf("meanSgnP_CPdf","",meanSgnP_C,RooConst(nMeanSgnFitP->getVal()),RooConst(1.5));
RooLognormal widthSgnP_CPdf("widthSgnP_CPdf","",widthSgnP_C,RooConst(nWidthSgnFitP->getVal()),RooConst(1.5));
// fitted BW (X) CB
RooBreitWigner bwSgnP_C("bwSgnP_C","bw",mass,meanSgnP_C,widthSgnP_C);
RooFFTConvPdf sgnPdfP("sgnPdfP","",mass,bwSgnP_C, cbSgnP_C);
RooRealVar sgnMeanResP("sgnMeanResP","",0,-10,10);
RooRealVar sgnSigmaResP("sgnSigmaResP","",0.5,0,10);
RooGaussian resolModP("sgnResolModP","",mass,sgnMeanResP,sgnSigmaResP);
mass.setBins(nBins_);
//return;
/////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////
// failing:
RooDataSet sgnDataSetF("sgnDataSetF","dataset for signal", RooArgSet(mass), Import( *fullTreeSgnCutF ) );
RooDataHist sgnDataHistF("sgnDataHistF","",RooArgSet(mass),sgnDataSetF, 1.0);
//RooHistPdf sgnTemplatePdfF("sgnTemplatePdfF","",RooArgSet(mass),sgnDataHistF);
RooKeysPdf sgnTemplatePdfF("sgnTemplatePdfF","",mass,sgnDataSetF);
// Breit-Wigner
RooRealVar meanSgnF("meanSgnF","mean",91.19,85,100);
RooRealVar widthSgnF("widthSgnF","width",2.49,0.,10);
RooBreitWigner bwSgnF("bwSgnF","bw",mass,meanSgnF,widthSgnF);
// Crystall Ball
RooRealVar m1SgnF("m1SgnF","m1",0,-20,20);
RooRealVar sigmaSgnF("sigmaSgnF","sigma",0.5,0,20);
RooRealVar alfaSgnF("alfaSgnF","alfa", 0.5,-10,10);
RooRealVar nSgnF("nSgnF","n", 1,1e-06,50);
RooCBShape cbSgnF("cbSgnF","",mass,m1SgnF,sigmaSgnF,alfaSgnF,nSgnF);
// BW (X) CB
RooFFTConvPdf bvcbSgnF("bvcbSgnF","",mass,bwSgnF, cbSgnF);
RooFitResult* ResSgnFitF = bvcbSgnF.fitTo(sgnDataSetF, Minos(1), Save(1), NumCPU(4) );
RooArgSet FitParamSgnF(ResSgnFitF->floatParsFinal());
RooRealVar* m1SgnFitF = (RooRealVar*)(&FitParamSgnF["m1SgnF"]);
RooRealVar* sigmaSgnFitF = (RooRealVar*)(&FitParamSgnF["sigmaSgnF"]);
RooRealVar* alfaSgnFitF = (RooRealVar*)(&FitParamSgnF["alfaSgnF"]);
RooRealVar* nSgnFitF = (RooRealVar*)(&FitParamSgnF["nSgnF"]);
RooRealVar* nMeanSgnFitF = (RooRealVar*)(&FitParamSgnF["meanSgnF"]);
RooRealVar* nWidthSgnFitF= (RooRealVar*)(&FitParamSgnF["widthSgnF"]);
RooRealVar m1SgnF_C("m1SgnF_C","m1",m1SgnFitF->getVal(),-10,10);
RooRealVar sigmaSgnF_C("sigmaSgnF_C","sigma",sigmaSgnFitF->getVal(),0,20);
// choose to let it float or not
RooRealVar meanSgnF_C("meanSgnF_C","mean", nMeanSgnFitF->getVal() ,80,120);
RooRealVar widthSgnF_C("widthSgnF_C","width",nWidthSgnFitF->getVal() /*,0.,10*/);
RooRealVar alfaSgnF_C("alfaSgnF_C","alfa",alfaSgnFitF->getVal()*(1+deltaAlpha_)/*,0,20*/);
RooRealVar nSgnF_C("nSgnF_C","n",nSgnFitF->getVal()*(1+deltaN_)/*,0,50*/);
RooCBShape cbSgnF_C("cbSgnF_C","",mass,m1SgnF_C,sigmaSgnF_C,alfaSgnF_C,nSgnF_C);
RooLognormal alfaSgnF_CPdf("alfaSgnF_CPdf","",alfaSgnF_C,RooConst(alfaSgnFitF->getVal()),RooConst(1.5));
RooLognormal nSgnF_CPdf("nSgnF_CPdf","",nSgnF_C,RooConst(nSgnFitF->getVal()), RooConst(1.5));
RooLognormal meanSgnF_CPdf("meanSgnF_CPdf","",meanSgnF_C,RooConst(nMeanSgnFitF->getVal()),RooConst(1.5));
RooLognormal widthSgnF_CPdf("widthSgnF_CPdf","",widthSgnF_C,RooConst(nWidthSgnFitF->getVal()),RooConst(1.5));
// fitted BW (X) CB
RooBreitWigner bwSgnF_C("bwSgnF_C","bw",mass,meanSgnF_C,widthSgnF_C);
RooFFTConvPdf sgnPdfF("sgnPdfF","",mass,bwSgnF_C, cbSgnF_C);
RooRealVar sgnMeanResF("sgnMeanResF","",0,-10,10);
RooRealVar sgnSigmaResF("sgnSigmaResF","",0.5,0,10);
RooGaussian resolModF("sgnResolModF","",mass,sgnMeanResF,sgnSigmaResF);
mass.setBins(nBins_);
//return;
// Fit
RooCategory category("category","category") ;
category.defineType("pass") ;
category.defineType("fail") ;
RooRealVar DataNumBkgF("DataNumBkgF","",0,10000000);
RooRealVar DataNumBkgP("DataNumBkgP","",0,10000000);
RooRealVar DataNumSgn("DataNumSgn","", 0,10000000);
RooRealVar DataEfficiency("DataEfficiency","",0.5,0,1);
RooFormulaVar DataNumSgnP("DataNumSgnP","DataEfficiency*DataNumSgn", RooArgSet(DataEfficiency,DataNumSgn));
RooFormulaVar DataNumSgnF("DataNumSgnF","(1-DataEfficiency)*DataNumSgn",RooArgSet(DataEfficiency,DataNumSgn));
RooAddPdf DataModelP("DataModelP","",RooArgList(sgnPdfP,bkgPdfP),RooArgList(DataNumSgnP,DataNumBkgP));
RooAddPdf DataModelF("DataModelF","",RooArgList(sgnPdfF,bkgPdfF),RooArgList(DataNumSgnF,DataNumBkgF));
TFile* dummyData = new TFile("dummyData.root","RECREATE");
TTree* fullTreeDataCutP = fullTreeData->CopyTree( Form("(%s>=%f && %s && tag_pfRelIso<0.1 && pair_tnpCharge==0 && event_met_pfmet<25 && (tag_hlt1==1 || tag_hlt2==1) && tag_pt>35)",category_.c_str(),cutValue_,bin_.c_str()) );
TTree* fullTreeDataCutF = fullTreeData->CopyTree( Form("(%s <%f && %s && tag_pfRelIso<0.1 && pair_tnpCharge==0 && event_met_pfmet<25 && (tag_hlt1==1 || tag_hlt2==1) && tag_pt>35)",category_.c_str(),cutValue_,bin_.c_str()) );
mass.setBins(nBins_);
RooDataSet DataDataSetP("DataDataSetP","dataset for Data pass", RooArgSet(mass), Import( *fullTreeDataCutP ) );
std::cout << "data dataset Pass " << DataDataSetP.numEntries() << " " << std::endl;
//return out;
RooDataHist DataDataHistP("DataDataHistP","",RooArgSet(mass),DataDataSetP, 1.0);
RooDataSet DataDataSetF("DataDataSetF","dataset for Data fail", RooArgSet(mass), Import( *fullTreeDataCutF ) );
std::cout << "data dataset Fail " << DataDataSetF.numEntries() << " " << std::endl;
RooDataHist DataDataHistF("DataDataHistF","",RooArgSet(mass),DataDataSetF, 1.0);
RooRealVar DataNumSgnP_("DataNumSgnP_","",0,10000);
RooAddPdf DataModelP_("DataModelP_","",RooArgList(sgnPdfP,bkgPdfP),RooArgList(DataNumSgnP_,DataNumBkgP));
DataModelP_.fitTo(DataDataSetP, Extended(1), Minos(1), Save(1), NumCPU(4),SumW2Error(1) /*,ExternalConstraints( RooArgSet(meanSgn_CPdf,widthSgn_CPdf) )*/);
RooPlot* frame2 = mass.frame(Title("template"));
DataDataSetP.plotOn(frame2);
DataModelP_.plotOn(frame2, LineColor(kBlue), LineStyle(kSolid));
DataModelP_.plotOn(frame2, Components("sgnPdfP"), LineColor(kRed), LineStyle(kSolid));
DataModelP_.plotOn(frame2, Components("bkgPdfP"), LineColor(kGreen), LineStyle(kSolid));
frame2->Draw();
//return;
// binned combined dataset
RooDataHist DataCombData("DataCombData","combined data",mass,Index(category),Import("pass", *(DataDataSetP.createHistogram("histoDataP",mass)) ) ,Import("fail", *(DataDataSetF.createHistogram("histoDataF",mass))), Weight(0.5) ) ;
std::cout << "data dataHist Comb " << DataCombData.sumEntries() << " " << std::endl;
std::cout << "+++++++++++++++++++++++++++++++++++++++++++++" << std::endl;
// unbinned combined dataset
RooDataSet DataCombDataUnBinned("DataCombDataUnBinned","combined data",mass,Index(category),Import("pass", DataDataSetP ) ,Import("fail",DataDataSetF), Weight(0.5) ) ;
std::cout << "data dataset Comb " << DataCombDataUnBinned.numEntries() << " " << std::endl;
std::cout << "+++++++++++++++++++++++++++++++++++++++++++++" << std::endl;
//return out;
RooSimultaneous DataSimPdf("DataSimPdf","simultaneous pdf",category) ;
DataSimPdf.addPdf(DataModelP,"pass") ;
DataSimPdf.addPdf(DataModelF,"fail") ;
//mass.setBins( 10000, "fft" );
mass.setBins( nBins_ );
RooFitResult* ResDataCombinedFit = 0;
if(doBinned_) ResDataCombinedFit = DataSimPdf.fitTo(DataCombData , Extended(1), Minos(1), Save(1), NumCPU(4), /*ExternalConstraints( RooArgSet(alfaSgn_CPdf,nSgn_CPdf) )*/ SumW2Error(1));
else ResDataCombinedFit = DataSimPdf.fitTo(DataCombDataUnBinned , Extended(1), Minos(1), Save(1), NumCPU(4), /*ExternalConstraints( RooArgSet(alfaSgn_CPdf,nSgn_CPdf) )*/ SumW2Error(1));
RooArgSet DataFitParam(ResDataCombinedFit->floatParsFinal());
RooRealVar* DataEffFit = (RooRealVar*)(&DataFitParam["DataEfficiency"]);
RooRealVar* DataNumSigFit = (RooRealVar*)(&DataFitParam["DataNumSgn"]);
RooPlot* DataFrameP = mass.frame(Bins(40),Title("CMS Preliminary 2011 #sqrt{s}=7 TeV L=XXX pb^{-1}: passing probe"));
DataCombData.plotOn(DataFrameP,Cut("category==category::pass"));
DataSimPdf.plotOn(DataFrameP,Slice(category,"pass"), ProjWData(category,DataCombData), LineColor(kBlue));
DataSimPdf.plotOn(DataFrameP,Slice(category,"pass"), ProjWData(category,DataCombData), Components("sgnPdfP"), LineColor(kRed), LineStyle(kSolid));
DataSimPdf.plotOn(DataFrameP,Slice(category,"pass"), ProjWData(category,DataCombData), Components("bkgPdfP"), LineColor(kMagenta), LineStyle(kDashed));
RooPlot* DataFrameF = mass.frame(Bins(40),Title("CMS Preliminary 2011 #sqrt{s}=7 TeV L=XXX pb^{-1}: failing probe"));
DataCombData.plotOn(DataFrameF,Cut("category==category::fail"));
DataSimPdf.plotOn(DataFrameF,Slice(category,"fail"), ProjWData(category,DataCombData), LineColor(kBlue));
DataSimPdf.plotOn(DataFrameF,Slice(category,"fail"), ProjWData(category,DataCombData), Components("sgnPdfF"), LineColor(kRed), LineStyle(kSolid));
DataSimPdf.plotOn(DataFrameF,Slice(category,"fail"), ProjWData(category,DataCombData), Components("bkgPdfF"), LineColor(kMagenta), LineStyle(kDashed));
TCanvas *cPass = new TCanvas("fitCanvasP","canvas",10,30,650,600);
cPass->SetGrid(0,0);
cPass->SetFillStyle(4000);
cPass->SetFillColor(10);
cPass->SetTicky();
cPass->SetObjectStat(0);
cPass->cd();
DataFrameP->Draw();
string fileNameP = "fitCanvasPassElecTnP_"+tnp_+"_"+category_;
cPass->SaveAs(Form("%s_%.2f.png",fileNameP.c_str(), binCenter_));
TCanvas *cFail = new TCanvas("fitCanvasF","canvas",10,30,650,600);
cFail->SetGrid(0,0);
cFail->SetFillStyle(4000);
cFail->SetFillColor(10);
cFail->SetTicky();
cFail->SetObjectStat(0);
cFail->cd();
DataFrameF->Draw();
string fileNameF = "fitCanvasFailElecTnP_"+tnp_+"_"+category_;
cFail->SaveAs(Form("%s_%.2f.png",fileNameF.c_str(), binCenter_));
ResDataCombinedFit->printArgs(std::cout);
cout << endl;
ResDataCombinedFit->printValue(std::cout);
cout << endl;
float DataErrorLo = DataEffFit->getErrorLo()<0 ? DataEffFit->getErrorLo() : (-1)*DataEffFit->getError();
float DataErrorHi = DataEffFit->getErrorHi()>0 ? DataEffFit->getErrorHi() : DataEffFit->getError();
cout << DataEffFit->getVal() << " +/- " << DataEffFit->getError() << " ( " << DataErrorLo << ", " << DataErrorHi << ")" << endl;
float* out1 = new float[6];
float* out2 = new float[6];
out1[0]=(binCenter_);
out1[1]=(binWidth_);
out1[2]=(binWidth_);
out1[3]=(McTruthEff);
out1[4]=(BinomialError);
out1[5]=(BinomialError);
out2[0]=(binCenter_);
out2[1]=(binWidth_);
out2[2]=(binWidth_);
out2[3]=(DataEffFit->getVal());
out2[4]=((-1)*DataErrorLo);
out2[5]=(DataErrorHi);
out.push_back(out1);
out.push_back(out2);
return out;
}
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 computeLimits(
const char* ACTag, // ACTag: where to look for combined workspaces in Limits/CombinedWorkspaces/
bool doSyst= false,
double CL=0.95, // Confidence Level for limits computation
int calculatorType = 2,
int testStatType = 2,
bool useCLs = false
)
// define calc type and test stat type:
//
// calculatorType = 0 Freq calculator
// calculatorType = 1 Hybrid calculator
// calculatorType = 2 Asymptotic calculator
// calculatorType = 3 Asymptotic calculator using nominal Asimov data sets (not using fitted parameter values but nominal ones)
//
// testStatType = 0 LEP
// = 1 Tevatron
// = 2 Profile Likelihood two sided
// = 3 Profile Likelihood one sided (i.e. = 0 if mu < mu_hat)
// = 4 Profile Likelihood signed ( pll = -pll if mu < mu_hat)
// = 5 Max Likelihood Estimate as test statistic
// = 6 Number of observed event as test statistic
//
// 0,3,true for frequentist CLs; 2,3,true for asymptotic CLs; 0,2,false for FC
{
// list of files
vector<TString> theFiles = combFileList(ACTag, doSyst ? "wSyst" : "woSyst");
if ( theFiles.empty() )
{
cout << "# [Error]: No combined workspaces found" << endl;
return;
}
// File to save results
ostringstream strs;
strs << CL;
string str = strs.str();
TString sCL(str);
sCL.Remove(0,sCL.First('.')+1);
string limitsFileName = string("csv/") + "cLimits_" + string(sCL) + "_" + string(ACTag);
if ( calculatorType == 0 ) limitsFileName = limitsFileName + "_Freq";
else if ( calculatorType == 1 ) limitsFileName = limitsFileName + "_Hybr";
else if ( calculatorType == 2 ) limitsFileName = limitsFileName + "_Asym";
else if ( calculatorType == 3 ) limitsFileName = limitsFileName + "_AsymAsi";
if ( testStatType == 0 ) limitsFileName = limitsFileName + "_LEP";
else if ( testStatType == 1 ) limitsFileName = limitsFileName + "_Tev";
else if ( testStatType == 2 ) limitsFileName = limitsFileName + "_2SPL";
else if ( testStatType == 3 ) limitsFileName = limitsFileName + "_1SPL";
else if ( testStatType == 4 ) limitsFileName = limitsFileName + "_SPL";
else if ( testStatType == 5 ) limitsFileName = limitsFileName + "_MaxL";
else if ( testStatType == 6 ) limitsFileName = limitsFileName + "_NOE";
if ( doSyst ) limitsFileName = limitsFileName + "_wSyst.csv";
else limitsFileName = limitsFileName + "_woSyst.csv";
ofstream file(limitsFileName.c_str());
file << CL << endl;
// Confidence interval computation
int cnt=1;
for (vector<TString>::const_iterator it=theFiles.begin(); it!=theFiles.end(); it++)
{
cout << ">>>>>>> Computing " << CL*100 << "% " << "limits for analysis bin " << cnt << endl;
cout << "Using combined PbPb-PP workspace " << cnt << " / " << theFiles.size() << ": " << *it << endl;
anabin thebin = binFromFile(*it);
// if (thebin != anabin(1.6,2.4,3,30,40,80)) continue;
if (!usebatch) {
pair<double,double> lims = runLimit_RaaNS_Workspace(*it, "RFrac2Svs1S_PbPbvsPP_P", "simPdf", "workspace", "dOS_DATA", ACTag, CL, calculatorType, testStatType, useCLs);
file << thebin.rapbin().low() << ", " << thebin.rapbin().high() << ", "
<< thebin.ptbin().low() << ", " << thebin.ptbin().high() << ", "
<< thebin.centbin().low() << ", " << thebin.centbin().high() << ", "
<< lims.first << ", " << lims.second << endl;
} else {
TString exports;
exports += Form("export it=%s; ",it->Data());
exports += Form("export ACTag=%s; ",ACTag);
exports += Form("export CL=%f; ",CL);
exports += Form("export calculatorType=%i; ",calculatorType);
exports += Form("export testStatType=%i; ",testStatType);
exports += Form("export useCLs=%i; ",useCLs);
exports += Form("export pwd_=%s; ", gSystem->pwd());
if (calculatorType==0) {
// special case of frequentist limits: submit more jobs
TFile *f = TFile::Open(*it);
RooWorkspace *ws = (RooWorkspace*) f->Get("workspace");
ws->loadSnapshot("SbHypo_poiAndNuisance_snapshot");
RooRealVar *theVar = (RooRealVar*) ws->var("RFrac2Svs1S_PbPbvsPP_P");
double val = theVar->getVal();
double err = theVar->getError();
f->Close(); if (ws) delete ws;
double nsigma = sqrt(2)*TMath::ErfcInverse(1-CL);
// double poimin = max(0.,0.5*(val - nsigma*err));
// double poimax = 1.5*(val + nsigma*err);
double poimin = max(0.,val + 0.9*nsigma*err);
double poimax = val + 1.1*nsigma*err;
int npoints = 5;
double dpoi = (poimax-poimin)/npoints;
for (int ipoi=0; ipoi<npoints; ipoi++)
for (int irnd=0; irnd<50; irnd++) {
TString exports2 = exports + Form("export poival=%f; ",poimin+ipoi*dpoi);
exports2 += Form("export rndseed=%i; ",irnd+1);
TString command("qsub -k oe -q cms@llrt3 -p -500 "); // -p option: lower the priority since we're submitting many jobs...
command += Form("-N limits_bin%i_ipoi%i_%i ",cnt,ipoi,irnd+1);
command += "-V ";
command += Form("-o %s ", gSystem->pwd());
command += Form("-v it,ACTag,CL,calculatorType,testStatType,useCLs,pwd_,poival,rndseed ");
command += "runbatch_limits_4WS.sh";
TString command_full = exports2 + command;
cout << command_full.Data() << endl;
int njobs = atoi(exec("qstat -u $USER cms@llrt3 | wc -l").c_str());
int njobs_queue = atoi(exec("qstat cms@llrt3 | grep \" Q \" | wc -l").c_str());
while (njobs_queue>0 && njobs >= maxjobs) {
system("sleep 60");
njobs = atoi(exec("qstat -u $USER cms@llrt3 | wc -l").c_str());
njobs_queue = atoi(exec("qstat cms@llrt3 | grep \" Q \" | wc -l").c_str());
}
system(command_full.Data());
}
} else {
exports += Form("export poival=%f; ",-1.);
exports += Form("export rndseed=%i; ",-1);
TString command("qsub -k oe -q cms@llrt3 -l nodes=1:ppn=23 ");
command += Form("-N limits_bin%i ",cnt);
command += "-V ";
command += Form("-o %s ", gSystem->pwd());
command += Form("-v it,ACTag,CL,calculatorType,testStatType,useCLs,pwd_,poival,rndseed ");
command += "runbatch_limits_4WS.sh";
TString command_full = exports + command;
cout << command_full.Data() << endl;
system(command_full.Data());
}
system("sleep 1");
}
cnt++;
} // loop on the files
file.close();
cout << "Closed " << limitsFileName << endl << endl;
}
void StandardBayesianNumericalDemo(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData") {
// option definitions
double confLevel = optBayes.confLevel;
TString integrationType = optBayes.integrationType;
int nToys = optBayes.nToys;
bool scanPosterior = optBayes.scanPosterior;
int nScanPoints = optBayes.nScanPoints;
int intervalType = optBayes.intervalType;
int maxPOI = optBayes.maxPOI;
double nSigmaNuisance = optBayes.nSigmaNuisance;
/////////////////////////////////////////////////////////////
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
////////////////////////////////////////////////////////////
const char* filename = "";
if (!strcmp(infile,"")) {
filename = "results/example_combined_GaussExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return;
#endif
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
}
else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file ){
cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return;
}
/////////////////////////////////////////////////////////////
// Tutorial starts here
////////////////////////////////////////////////////////////
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
/////////////////////////////////////////////
// create and use the BayesianCalculator
// to find and plot the 95% credible interval
// on the parameter of interest as specified
// in the model config
// before we do that, we must specify our prior
// it belongs in the model config, but it may not have
// been specified
RooUniform prior("prior","",*mc->GetParametersOfInterest());
w->import(prior);
mc->SetPriorPdf(*w->pdf("prior"));
// do without systematics
//mc->SetNuisanceParameters(RooArgSet() );
if (nSigmaNuisance > 0) {
RooAbsPdf * pdf = mc->GetPdf();
assert(pdf);
RooFitResult * res = pdf->fitTo(*data, Save(true), Minimizer(ROOT::Math::MinimizerOptions::DefaultMinimizerType().c_str()), Hesse(true),
PrintLevel(ROOT::Math::MinimizerOptions::DefaultPrintLevel()-1) );
res->Print();
RooArgList nuisPar(*mc->GetNuisanceParameters());
for (int i = 0; i < nuisPar.getSize(); ++i) {
RooRealVar * v = dynamic_cast<RooRealVar*> (&nuisPar[i] );
assert( v);
v->setMin( TMath::Max( v->getMin(), v->getVal() - nSigmaNuisance * v->getError() ) );
v->setMax( TMath::Min( v->getMax(), v->getVal() + nSigmaNuisance * v->getError() ) );
std::cout << "setting interval for nuisance " << v->GetName() << " : [ " << v->getMin() << " , " << v->getMax() << " ]" << std::endl;
}
}
BayesianCalculator bayesianCalc(*data,*mc);
bayesianCalc.SetConfidenceLevel(confLevel); // 95% interval
// default of the calculator is central interval. here use shortest , central or upper limit depending on input
// doing a shortest interval might require a longer time since it requires a scan of the posterior function
if (intervalType == 0) bayesianCalc.SetShortestInterval(); // for shortest interval
if (intervalType == 1) bayesianCalc.SetLeftSideTailFraction(0.5); // for central interval
if (intervalType == 2) bayesianCalc.SetLeftSideTailFraction(0.); // for upper limit
if (!integrationType.IsNull() ) {
bayesianCalc.SetIntegrationType(integrationType); // set integrationType
bayesianCalc.SetNumIters(nToys); // set number of ietrations (i.e. number of toys for MC integrations)
}
// in case of toyMC make a nnuisance pdf
if (integrationType.Contains("TOYMC") ) {
RooAbsPdf * nuisPdf = RooStats::MakeNuisancePdf(*mc, "nuisance_pdf");
cout << "using TOYMC integration: make nuisance pdf from the model " << std::endl;
nuisPdf->Print();
bayesianCalc.ForceNuisancePdf(*nuisPdf);
scanPosterior = true; // for ToyMC the posterior is scanned anyway so used given points
}
// compute interval by scanning the posterior function
if (scanPosterior)
bayesianCalc.SetScanOfPosterior(nScanPoints);
RooRealVar* poi = (RooRealVar*) mc->GetParametersOfInterest()->first();
if (maxPOI != -999 && maxPOI > poi->getMin())
poi->setMax(maxPOI);
SimpleInterval* interval = bayesianCalc.GetInterval();
// print out the iterval on the first Parameter of Interest
cout << "\n>>>> RESULT : " << confLevel*100 << "% interval on " << poi->GetName()<<" is : ["<<
interval->LowerLimit() << ", "<<
interval->UpperLimit() <<"] "<<endl;
// make a plot
// since plotting may take a long time (it requires evaluating
// the posterior in many points) this command will speed up
// by reducing the number of points to plot - do 50
// ignore errors of PDF if is zero
RooAbsReal::setEvalErrorLoggingMode(RooAbsReal::Ignore) ;
cout << "\nDrawing plot of posterior function....." << endl;
// always plot using numer of scan points
bayesianCalc.SetScanOfPosterior(nScanPoints);
RooPlot * plot = bayesianCalc.GetPosteriorPlot();
plot->Draw();
}
int DiagnosisMacro(int Nbins = 10, int Nsigma = 10, int CPUused = 1, TString Filename = "FIT_DATA_Psi2SJpsi_PPPrompt_Bkg_SecondOrderChebychev_pt65300_rap016_cent0200_262620_263757.root", TString Outputdir = "./")
//Nbins: Number of points for which to calculate profile likelihood. Time required is about (1/CPU) minutes per point per parameter. 0 means do plain likelihood only
//Nsigma: The range in which the scan is performed (value-Nsigma*sigma, value+Nsigma*sigma)
//CPUused: anything larger than 1 causes weird fit results on my laptop, runs fine on lxplus with more (16)
{
// R e a d w o r k s p a c e f r o m f i l e
// -----------------------------------------------
// Open input file with workspace
//Filename = "FIT_DATA_Psi2SJpsi_PP_Jpsi_DoubleCrystalBall_Psi2S_DoubleCrystalBall_Bkg_Chebychev2_pt6590_rap016_cent0200.root";
//Filename = "FIT_DATA_Psi2SJpsi_PbPb_Jpsi_DoubleCrystalBall_Psi2S_DoubleCrystalBall_Bkg_Chebychev1_pt6590_rap016_cent0200.root";
TFile *f = new TFile(Filename);
// Retrieve workspace from file
RooWorkspace* w = (RooWorkspace*)f->Get("workspace");
// Retrieve x,model and data from workspace
RooRealVar* x = w->var("invMass");
RooAbsPdf* model = w->pdf("simPdf_syst");
if (model == 0) {
model = w->pdf("simPdf");
}
if (model == 0) {
model = w->pdf("pdfMASS_Tot_PP");
}
if (model == 0) {
model = w->pdf("pdfMASS_Tot_PbPb");
}
if (model == 0) {
cout << "[ERROR] pdf failed to load from the workspace" << endl;
return false;
}
RooAbsData* data = w->data("dOS_DATA");
if (data == 0) {
data = w->data("dOS_DATA_PP");
}
if (data == 0) {
data = w->data("dOS_DATA_PbPb");
}
if (data == 0) {
cout << "[ERROR] data failed to load from the workspace" << endl;
return false;
}
// Print structure of composite p.d.f.
model->Print("t");
/*
// P l o t m o d e l
// ---------------------------------------------------------
// Plot data and PDF overlaid
RooPlot* xframe = x->frame(Title("J/psi Model and Data"));
data->plotOn(xframe);
model->plotOn(xframe);
// Draw the frame on the canvas
TCanvas* c2 = new TCanvas("PlotModel", "PlotModel", 1000, 1000);
gPad->SetLeftMargin(0.15);
xframe->GetYaxis()->SetTitleOffset(2.0);
xframe->Draw();//*/
///// Check parameters
RooArgSet* paramSet1 = model->getDependents(data);
paramSet1->Print("v"); // Just check
RooArgSet* paramSet2 = model->getParameters(data);
paramSet2->Print("v");
int Nparams = paramSet2->getSize();
cout << "Number of parameters: " << Nparams<<endl<<endl;
// C o n s t r u c t p l a i n l i k e l i h o o d
// ---------------------------------------------------
// Construct unbinned likelihood
RooAbsReal* nll = model->createNLL(*data, NumCPU(CPUused));
// Minimize likelihood w.r.t all parameters before making plots
RooMinuit(*nll).migrad();
//////////////////////////////////////////////////////
/////////////////// L O O P O V E R P A R A M E T E R S
/////////////////////////////////////////////////////
/// Set up loop over parameters
TString ParamName;
double ParamValue;
double ParamError;
double ParamLimitLow;
double ParamLimitHigh;
double FitRangeLow;
double FitRangeHigh;
RooRealVar* vParam;
int counter = 0;
// Loop start
TIterator* iter = paramSet2->createIterator();
TObject* var = iter->Next();
while (var != 0) {
counter++;
ParamName = var->GetName();
vParam = w->var(ParamName);
ParamValue = vParam->getVal();
ParamError = vParam->getError();
ParamLimitLow = vParam->getMin();
ParamLimitHigh = vParam->getMax();
cout << ParamName << " has value " << ParamValue << " with error: " << ParamError << " and limits: " << ParamLimitLow << " to " << ParamLimitHigh << endl << endl;
if (ParamError == 0) { //Skipping fixed parameters
cout << "Parameter was fixed, skipping its fitting" << endl;
cout << endl << "DONE WITH " << counter << " PARAMETER OUT OF " << Nparams << endl << endl;
var = iter->Next();
continue;
}
// determining fit range: Nsigma sigma on each side unless it would be outside of parameter limits
if ((ParamValue - Nsigma * ParamError) > ParamLimitLow) {
FitRangeLow = (ParamValue - Nsigma * ParamError);
}
else {
FitRangeLow = ParamLimitLow;
}
if ((ParamValue + Nsigma * ParamError) < ParamLimitHigh) {
FitRangeHigh = (ParamValue + Nsigma * ParamError);
}
else {
FitRangeHigh = ParamLimitHigh;
}
// P l o t p l a i n l i k e l i h o o d a n d C o n s t r u c t p r o f i l e l i k e l i h o o d
// ---------------------------------------------------
RooPlot* frame1;
RooAbsReal* pll=NULL;
if (Nbins != 0) {
frame1 = vParam->frame(Bins(Nbins), Range(FitRangeLow, FitRangeHigh), Title(TString::Format("LL and profileLL in %s", ParamName.Data())));
nll->plotOn(frame1, ShiftToZero());
pll = nll->createProfile(*vParam);
// Plot the profile likelihood
pll->plotOn(frame1, LineColor(kRed), RooFit::Precision(-1));
}
else { //Skip profile likelihood
frame1 = vParam->frame(Bins(10), Range(FitRangeLow, FitRangeHigh), Title(TString::Format("LL and profileLL in %s", ParamName.Data())));
nll->plotOn(frame1, ShiftToZero());
}
// D r a w a n d s a v e p l o t s
// -----------------------------------------------------------------------
// Adjust frame maximum for visual clarity
frame1->SetMinimum(0);
frame1->SetMaximum(20);
TCanvas* c = new TCanvas("CLikelihoodResult", "CLikelihoodResult", 800, 600);
c->cd(1);
gPad->SetLeftMargin(0.15);
frame1->GetYaxis()->SetTitleOffset(1.4);
frame1->Draw();
TLegend* leg = new TLegend(0.70, 0.70, 0.95, 0.88, "");
leg->SetFillColor(kWhite);
leg->SetBorderSize(0);
leg->SetTextSize(0.035);
TLegendEntry *le1 = leg->AddEntry(nll, "Plain likelihood", "l");
le1->SetLineColor(kBlue);
le1->SetLineWidth(3);
TLegendEntry *le2 = leg->AddEntry(pll, "Profile likelihood", "l");
le2->SetLineColor(kRed);
le2->SetLineWidth(3);
leg->Draw("same");
//Save plot
TString StrippedName = TString(Filename(Filename.Last('/')+1,Filename.Length()));
StrippedName = StrippedName.ReplaceAll(".root","");
cout << StrippedName << endl;
gSystem->mkdir(Form("%s/root/%s", Outputdir.Data(), StrippedName.Data()), kTRUE);
c->SaveAs(Form("%s/root/%s/Likelihood_scan_%s.root", Outputdir.Data(), StrippedName.Data(), ParamName.Data()));
gSystem->mkdir(Form("%s/pdf/%s", Outputdir.Data(), StrippedName.Data()), kTRUE);
c->SaveAs(Form("%s/pdf/%s/Likelihood_scan_%s.pdf", Outputdir.Data(), StrippedName.Data(), ParamName.Data()));
gSystem->mkdir(Form("%s/png/%s", Outputdir.Data(), StrippedName.Data()), kTRUE);
c->SaveAs(Form("%s/png/%s/Likelihood_scan_%s.png", Outputdir.Data(), StrippedName.Data(), ParamName.Data()));
delete c;
delete frame1;
if (pll) delete pll;
cout << endl << "DONE WITH " << counter << " PARAMETER OUT OF " << Nparams << endl << endl;
//if (counter == 2){ break; } //Exit - for testing
var = iter->Next();
} // End of the loop
return true;
}
// internal routine to run the inverter
HypoTestInverterResult * RunInverter(RooWorkspace * w, const char * modelSBName, const char * modelBName,
const char * dataName, int type, int testStatType,
int npoints, double poimin, double poimax,
int ntoys, bool useCls )
{
std::cout << "Running HypoTestInverter on the workspace " << w->GetName() << std::endl;
w->Print();
RooAbsData * data = w->data(dataName);
if (!data) {
Error("RA2bHypoTestDemo","Not existing data %s",dataName);
return 0;
}
else
std::cout << "Using data set " << dataName << std::endl;
// get models from WS
// get the modelConfig out of the file
ModelConfig* bModel = (ModelConfig*) w->obj(modelBName);
ModelConfig* sbModel = (ModelConfig*) w->obj(modelSBName);
if (!sbModel) {
Error("RA2bHypoTestDemo","Not existing ModelConfig %s",modelSBName);
return 0;
}
// check the model
if (!sbModel->GetPdf()) {
Error("RA2bHypoTestDemo","Model %s has no pdf ",modelSBName);
return 0;
}
if (!sbModel->GetParametersOfInterest()) {
Error("RA2bHypoTestDemo","Model %s has no poi ",modelSBName);
return 0;
}
if (!sbModel->GetParametersOfInterest()) {
Error("RA2bHypoTestInvDemo","Model %s has no poi ",modelSBName);
return 0;
}
if (!sbModel->GetSnapshot() ) {
Info("RA2bHypoTestInvDemo","Model %s has no snapshot - make one using model poi",modelSBName);
sbModel->SetSnapshot( *sbModel->GetParametersOfInterest() );
}
if (!bModel || bModel == sbModel) {
Info("RA2bHypoTestInvDemo","The background model %s does not exist",modelBName);
Info("RA2bHypoTestInvDemo","Copy it from ModelConfig %s and set POI to zero",modelSBName);
bModel = (ModelConfig*) sbModel->Clone();
bModel->SetName(TString(modelSBName)+TString("_with_poi_0"));
RooRealVar * var = dynamic_cast<RooRealVar*>(bModel->GetParametersOfInterest()->first());
if (!var) return 0;
double oldval = var->getVal();
var->setVal(0);
bModel->SetSnapshot( RooArgSet(*var) );
var->setVal(oldval);
}
else {
if (!bModel->GetSnapshot() ) {
Info("RA2bHypoTestInvDemo","Model %s has no snapshot - make one using model poi and 0 values ",modelBName);
RooRealVar * var = dynamic_cast<RooRealVar*>(bModel->GetParametersOfInterest()->first());
if (var) {
double oldval = var->getVal();
var->setVal(0);
bModel->SetSnapshot( RooArgSet(*var) );
var->setVal(oldval);
}
else {
Error("RA2bHypoTestInvDemo","Model %s has no valid poi",modelBName);
return 0;
}
}
}
SimpleLikelihoodRatioTestStat slrts(*sbModel->GetPdf(),*bModel->GetPdf());
if (sbModel->GetSnapshot()) slrts.SetNullParameters(*sbModel->GetSnapshot());
if (bModel->GetSnapshot()) slrts.SetAltParameters(*bModel->GetSnapshot());
// ratio of profile likelihood - need to pass snapshot for the alt
RatioOfProfiledLikelihoodsTestStat
ropl(*sbModel->GetPdf(), *bModel->GetPdf(), bModel->GetSnapshot());
ropl.SetSubtractMLE(false);
//MyProfileLikelihoodTestStat profll(*sbModel->GetPdf());
ProfileLikelihoodTestStat profll(*sbModel->GetPdf());
if (testStatType == 3) profll.SetOneSided(1);
if (optimize) profll.SetReuseNLL(true);
TestStatistic * testStat = &slrts;
if (testStatType == 1) testStat = &ropl;
if (testStatType == 2 || testStatType == 3) testStat = &profll;
HypoTestCalculatorGeneric * hc = 0;
if (type == 0) hc = new FrequentistCalculator(*data, *bModel, *sbModel);
else hc = new HybridCalculator(*data, *bModel, *sbModel);
ToyMCSampler *toymcs = (ToyMCSampler*)hc->GetTestStatSampler();
//=== DEBUG
///// toymcs->SetWS( w ) ;
//=== DEBUG
toymcs->SetNEventsPerToy(1);
toymcs->SetTestStatistic(testStat);
if (optimize) toymcs->SetUseMultiGen(true);
if (type == 1) {
HybridCalculator *hhc = (HybridCalculator*) hc;
hhc->SetToys(ntoys,ntoys);
// check for nuisance prior pdf
if (bModel->GetPriorPdf() && sbModel->GetPriorPdf() ) {
hhc->ForcePriorNuisanceAlt(*bModel->GetPriorPdf());
hhc->ForcePriorNuisanceNull(*sbModel->GetPriorPdf());
}
else {
if (bModel->GetNuisanceParameters() || sbModel->GetNuisanceParameters() ) {
Error("RA2bHypoTestInvDemo","Cannnot run Hybrid calculator because no prior on the nuisance parameter is specified");
return 0;
}
}
}
else
((FrequentistCalculator*) hc)->SetToys(ntoys,ntoys);
// Get the result
RooMsgService::instance().getStream(1).removeTopic(RooFit::NumIntegration);
TStopwatch tw; tw.Start();
const RooArgSet * poiSet = sbModel->GetParametersOfInterest();
RooRealVar *poi = (RooRealVar*)poiSet->first();
// fit the data first
sbModel->GetPdf()->fitTo(*data);
double poihat = poi->getVal();
HypoTestInverter calc(*hc);
calc.SetConfidenceLevel(0.95);
calc.UseCLs(useCls);
calc.SetVerbose(true);
// can speed up using proof-lite
if (useProof && nworkers > 1) {
ProofConfig pc(*w, nworkers, "", kFALSE);
toymcs->SetProofConfig(&pc); // enable proof
}
printf(" npoints = %d, poimin = %7.2f, poimax = %7.2f\n\n", npoints, poimin, poimax ) ;
cout << flush ;
if ( npoints==1 ) {
std::cout << "Evaluating one point : " << poimax << std::endl;
calc.RunOnePoint(poimax);
} else if (npoints > 0) {
if (poimin >= poimax) {
// if no min/max given scan between MLE and +4 sigma
poimin = int(poihat);
poimax = int(poihat + 4 * poi->getError());
}
std::cout << "Doing a fixed scan in interval : " << poimin << " , " << poimax << std::endl;
calc.SetFixedScan(npoints,poimin,poimax);
}
else {
//poi->setMax(10*int( (poihat+ 10 *poi->getError() )/10 ) );
std::cout << "Doing an automatic scan in interval : " << poi->getMin() << " , " << poi->getMax() << std::endl;
}
cout << "\n\n right before calc.GetInterval(), ntoys = " << ntoys << " \n\n" << flush ;
HypoTestInverterResult * r = calc.GetInterval();
return r;
}
void FitterUtils::fit(bool wantplot, bool constPartReco,
double fracPartReco_const,
ofstream& out, TTree* t, bool update, string plotsfile)
{
//***************Get the PDFs from the workspace
TFile fw(workspacename.c_str());
RooWorkspace* workspace = (RooWorkspace*)fw.Get("workspace");
RooRealVar *B_plus_M = workspace->var("B_plus_M");
RooRealVar *misPT = workspace->var("misPT");
RooRealVar *T = workspace->var("T");
RooRealVar *n = workspace->var("n");
RooRealVar *expoConst = workspace->var("expoConst");
RooRealVar *trueExp = workspace->var("trueExp");
RooRealVar *fractionalErrorJpsiLeak = workspace->var("fractionalErrorJpsiLeak");
cout<<"VALUE OF T IN FIT: "<<T->getVal()<<" +- "<<T->getError()<<endl;
cout<<"VALUE OF n IN FIT: "<<n->getVal()<<" +- "<<n->getError()<<endl;
RooHistPdf *histPdfSignalZeroGamma = (RooHistPdf *) workspace->pdf("histPdfSignalZeroGamma");
RooHistPdf *histPdfSignalOneGamma = (RooHistPdf *) workspace->pdf("histPdfSignalOneGamma");
RooHistPdf *histPdfSignalTwoGamma = (RooHistPdf *) workspace->pdf("histPdfSignalTwoGamma");
RooHistPdf *histPdfPartReco = (RooHistPdf *) workspace->pdf("histPdfPartReco");
RooHistPdf *histPdfJpsiLeak(0);
if(nGenJpsiLeak>0) histPdfJpsiLeak = (RooHistPdf *) workspace->pdf("histPdfJpsiLeak");
RooAbsPdf *combPDF;
if (fit2D)
{
combPDF = new RooPTMVis("combPDF", "combPDF", *misPT, *B_plus_M, *T, *n, *expoConst);
}
else
{
combPDF = new RooExponential("combPDF", "combPDF", *B_plus_M, *expoConst);
}
expoConst->setVal(trueExp->getVal());
RooWorkspace* workspaceGen = (RooWorkspace*)fw.Get("workspaceGen");
RooDataSet* dataGenSignalZeroGamma = (RooDataSet*)workspaceGen->data("dataGenSignalZeroGamma");
RooDataSet* dataGenSignalOneGamma = (RooDataSet*)workspaceGen->data("dataGenSignalOneGamma");
RooDataSet* dataGenSignalTwoGamma = (RooDataSet*)workspaceGen->data("dataGenSignalTwoGamma");
RooDataSet* dataGenPartReco = (RooDataSet*)workspaceGen->data("dataGenPartReco");
RooDataSet* dataGenComb = (RooDataSet*)workspaceGen->data("dataGenComb");
RooDataSet* dataGenJpsiLeak(0);
if(nGenJpsiLeak>0) dataGenJpsiLeak = (RooDataSet*)workspaceGen->data("dataGenJpsiLeak");
if(wantplot)
{
//**************Must get the datasets
RooDataSet* dataSetSignalZeroGamma = (RooDataSet*)workspace->data("dataSetSignalZeroGamma");
RooDataSet* dataSetSignalOneGamma = (RooDataSet*)workspace->data("dataSetSignalOneGamma");
RooDataSet* dataSetSignalTwoGamma = (RooDataSet*)workspace->data("dataSetSignalTwoGamma");
RooDataSet* dataSetPartReco = (RooDataSet*)workspace->data("dataSetPartReco");
RooDataSet* dataSetComb = (RooDataSet*)workspace->data("dataSetComb");
RooDataSet* dataSetJpsiLeak = (RooDataSet*)workspace->data("dataSetJpsiLeak");
//**************Plot all the different components
cout<<"dataGenSignalZeroGamma: "<<dataGenSignalZeroGamma<<endl;
PlotShape(*dataSetSignalZeroGamma, *dataGenSignalZeroGamma, *histPdfSignalZeroGamma, plotsfile, "cSignalZeroGamma", *B_plus_M, *misPT);
PlotShape(*dataSetSignalOneGamma, *dataGenSignalOneGamma, *histPdfSignalOneGamma, plotsfile, "cSignalOneGamma", *B_plus_M, *misPT);
PlotShape(*dataSetSignalTwoGamma, *dataGenSignalTwoGamma, *histPdfSignalTwoGamma, plotsfile, "cSignalTwoGamma", *B_plus_M, *misPT);
PlotShape(*dataSetPartReco, *dataGenPartReco, *histPdfPartReco, plotsfile, "cPartReco", *B_plus_M, *misPT);
PlotShape(*dataSetComb, *dataGenComb, *combPDF, plotsfile, "cComb", *B_plus_M, *misPT);
if(nGenJpsiLeak>1) PlotShape(*dataSetJpsiLeak, *dataGenJpsiLeak, *histPdfJpsiLeak, plotsfile, "cJpsiLeak", *B_plus_M, *misPT);
}
//***************Merge datasets
RooDataSet* dataGenTot(dataGenPartReco);
dataGenTot->append(*dataGenSignalZeroGamma);
dataGenTot->append(*dataGenSignalOneGamma);
dataGenTot->append(*dataGenSignalTwoGamma);
dataGenTot->append(*dataGenComb);
if(nGenJpsiLeak>0) dataGenTot->append(*dataGenJpsiLeak);
//**************Prepare fitting function
RooRealVar nSignal("nSignal", "#signal events", 1.*nGenSignal, nGenSignal-7*sqrt(nGenSignal), nGenSignal+7*sqrt(nGenSignal));
RooRealVar nPartReco("nPartReco", "#nPartReco", 1.*nGenPartReco, nGenPartReco-7*sqrt(nGenPartReco), nGenPartReco+7*sqrt(nGenPartReco));
RooRealVar nComb("nComb", "#nComb", 1.*nGenComb, nGenComb-7*sqrt(nGenComb), nGenComb+7*sqrt(nGenComb));
RooRealVar nJpsiLeak("nJpsiLeak", "#nJpsiLeak", 1.*nGenJpsiLeak, nGenJpsiLeak-7*sqrt(nGenJpsiLeak), nGenJpsiLeak+7*sqrt(nGenJpsiLeak));
RooRealVar fracZero("fracZero", "fracZero",0.5,0,1);
RooRealVar fracOne("fracOne", "fracOne",0.5, 0,1);
RooFormulaVar fracPartReco("fracPartReco", "nPartReco/nSignal", RooArgList(nPartReco,nSignal));
RooFormulaVar fracOneRec("fracOneRec", "(1-fracZero)*fracOne", RooArgList(fracZero, fracOne));
RooAddPdf histPdfSignal("histPdfSignal", "histPdfSignal", RooArgList(*histPdfSignalZeroGamma, *histPdfSignalOneGamma, *histPdfSignalTwoGamma), RooArgList(fracZero, fracOneRec));
RooArgList pdfList(histPdfSignal, *histPdfPartReco, *combPDF);
RooArgList yieldList(nSignal, nPartReco, nComb);
if(nGenJpsiLeak>0)
{
pdfList.add(*histPdfJpsiLeak);
yieldList.add(nJpsiLeak);
}
RooAddPdf totPdf("totPdf", "totPdf", pdfList, yieldList);
//**************** Constrain the fraction of zero and one photon
int nGenSignalZeroGamma(floor(nGenFracZeroGamma*nGenSignal));
int nGenSignalOneGamma(floor(nGenFracOneGamma*nGenSignal));
int nGenSignalTwoGamma(floor(nGenSignal-nGenSignalZeroGamma-nGenSignalOneGamma));
RooRealVar fracZeroConstMean("fracZeroConstMean", "fracZeroConstMean", nGenSignalZeroGamma*1./nGenSignal);
RooRealVar fracZeroConstSigma("fracZeroConstSigma", "fracZeroConstSigma", sqrt(nGenSignalZeroGamma)/nGenSignal);
RooGaussian fracZeroConst("fracZeroConst", "fracZeroConst", fracZero, fracZeroConstMean, fracZeroConstSigma);
RooRealVar fracOneConstMean("fracOneConstMean", "fracOneConstMean", nGenSignalOneGamma*1./nGenSignal/(1-fracZeroConstMean.getVal()));
RooRealVar fracOneConstSigma("fracOneConstSigma", "fracOneConstSigma", sqrt(nGenSignalOneGamma)/nGenSignal/(1-fracZeroConstMean.getVal()));
RooGaussian fracOneConst("fracOneConst", "fracOneConst", fracOne, fracOneConstMean, fracOneConstSigma);
RooRealVar fracPartRecoMean("fracPartRecoMean", "fracPartRecoMean", nGenPartReco/(1.*nGenSignal));
RooRealVar fracPartRecoSigma("fracPartRecoSigma", "fracPartRecoSigma", fracPartReco_const*fracPartRecoMean.getVal());
RooGaussian fracPartRecoConst("fracPartRecoConst", "fracPartRecoConst", fracPartReco, fracPartRecoMean, fracPartRecoSigma);
RooRealVar JpsiLeakMean("JpsiLeakMean", "JpsiLeakMean", nGenJpsiLeak);
RooRealVar JpsiLeakSigma("JpsiLeakSigma", "JpsiLeakSigma", nGenJpsiLeak*fractionalErrorJpsiLeak->getVal());
RooGaussian JpsiLeakConst("JpsiLeakConst", "JpsiLeakConst", nJpsiLeak, JpsiLeakMean, JpsiLeakSigma);
//Extra TEST CONSTRAINT
//RooRealVar combConstMean("combConstMean", "combConstMean", nGenComb);
//RooRealVar combConstSigma("combConstSigma", "combConstSigma", 7.7);
//RooGaussian combConst("combConst", "combConst", nComb, combConstMean, combConstSigma);
//**************** fit
RooAbsReal::defaultIntegratorConfig()->setEpsAbs(1e-8) ;
RooAbsReal::defaultIntegratorConfig()->setEpsRel(1e-8) ;
RooArgSet *par_set = totPdf.getParameters(dataGenTot);
initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma,
*trueExp, nSignal, nPartReco, nComb, fracZero, fracOne, *expoConst, nJpsiLeak, constPartReco, fracPartRecoSigma);
RooArgSet constraints(fracZeroConst, fracOneConst);
if (constPartReco) constraints.add(fracPartRecoConst);
if(nGenJpsiLeak>0) constraints.add(JpsiLeakConst);
RooAbsReal* nll = totPdf.createNLL(*dataGenTot, Extended(), ExternalConstraints(constraints));
RooMinuit minuit(*nll);
minuit.setStrategy(2);
int migradRes(1);
int hesseRes(4);
vector<int> migradResVec;
vector<int> hesseResVec;
double edm(10);
int nrefit(0);
RooFitResult* fitRes(0);
vector<RooFitResult*> fitResVec;
bool hasConverged(false);
for(int i(0); (i<10) && !hasConverged ; ++i)
{
initiateParams(nGenSignalZeroGamma, nGenSignalOneGamma, nGenSignalTwoGamma,
*trueExp, nSignal, nPartReco, nComb, fracZero, fracOne, *expoConst, nJpsiLeak, constPartReco, fracPartRecoSigma);
cout<<"FITTING: starting with nsignal = "<<nSignal.getValV()<<" refit nbr. "<<i<<endl;
//if(fitRes != NULL && fitRes != 0) delete fitRes;
migradRes = minuit.migrad();
hesseRes = minuit.hesse();
fitRes = minuit.save();
edm = fitRes->edm();
fitResVec.push_back(fitRes);
migradResVec.push_back(migradRes);
hesseResVec.push_back(hesseRes);
if( migradRes == 0 && hesseRes == 0 && edm < 1e-4 ) hasConverged = true;
++nrefit;
cout<<"Fitting nbr "<<i<<" done. Hesse: "<<hesseRes<<" migrad: "<<migradRes<<" edm: "<<edm<<" minNll: "<<fitRes->minNll()<<endl;
}
if(!hasConverged)
{
double minNll(1e20);
int minIndex(-1);
for(unsigned int i(0); i<fitResVec.size(); ++i)
{
if( fitResVec.at(i)->minNll() < minNll)
{
minIndex = i;
minNll = fitResVec[i]->minNll();
}
}
migradRes = migradResVec.at(minIndex);
hesseRes = hesseResVec.at(minIndex);
cout<<"Fit not converged, choose fit "<<minIndex<<". Hesse: "<<hesseRes<<" migrad: "<<migradRes<<" edm: "<<edm<<" minNll: "<<fitRes->minNll()<<endl;
}
fillTreeResult(t, fitRes, update, migradRes, hesseRes, hasConverged);
for(unsigned int i(0); i<fitResVec.size(); ++i) delete fitResVec.at(i);
//totPdf.fitTo(*dataGenTot, Extended(), Save(), Warnings(false));
//*************** output fit status
int w(12);
out<<setw(w)<<migradRes<<setw(w)<<hesseRes<<setw(w)<<edm<<setw(w)<<nrefit<<endl;
if(wantplot) plot_fit_result(plotsfile, totPdf, *dataGenTot);
fw.Close();
//delete and return
delete nll;
delete par_set;
delete workspace;
delete workspaceGen;
delete combPDF;
}
void FitterUtils::generate()
{
//***************Get the PDFs from the workspace
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");
RooRealVar *T = workspace->var("T");
RooRealVar *n = workspace->var("n");
RooRealVar *expoConst = workspace->var("expoConst");
RooRealVar *trueExp = workspace->var("trueExp");
RooRealVar *fractionalErrorJpsiLeak = workspace->var("fractionalErrorJpsiLeak");
cout<<"VALUE OF T IN GENERATE: "<<T->getVal()<<" +- "<<T->getError()<<endl;
cout<<"VALUE OF n IN GENERATE: "<<n->getVal()<<" +- "<<n->getError()<<endl;
RooHistPdf *histPdfSignalZeroGamma = (RooHistPdf *) workspace->pdf("histPdfSignalZeroGamma");
RooHistPdf *histPdfSignalOneGamma = (RooHistPdf *) workspace->pdf("histPdfSignalOneGamma");
RooHistPdf *histPdfSignalTwoGamma = (RooHistPdf *) workspace->pdf("histPdfSignalTwoGamma");
RooHistPdf *histPdfPartReco = (RooHistPdf *) workspace->pdf("histPdfPartReco");
RooHistPdf *histPdfJpsiLeak(0);
if(nGenJpsiLeak>1) histPdfJpsiLeak = (RooHistPdf *) workspace->pdf("histPdfJpsiLeak");
RooAbsPdf *combPDF;
if (fit2D)
{
combPDF = new RooPTMVis("combPDF", "combPDF", *misPT, *B_plus_M, *T, *n, *expoConst);
}
else
{
combPDF = new RooExponential("combPDF", "combPDF", *B_plus_M, *expoConst);
}
double trueExpConst(trueExp->getValV());
expoConst->setVal(trueExpConst);
//***************Prepare generation
int nGenSignalZeroGamma(floor(nGenFracZeroGamma*nGenSignal));
int nGenSignalOneGamma(floor(nGenFracOneGamma*nGenSignal));
int nGenSignalTwoGamma(floor(nGenSignal-nGenSignalZeroGamma-nGenSignalOneGamma));
RooArgSet argset2(*B_plus_M);
if (fit2D) argset2.add(*misPT);
cout<<"Preparing the generation of events 1";
RooRandom::randomGenerator()->SetSeed();
RooAbsPdf::GenSpec* GenSpecSignalZeroGamma = histPdfSignalZeroGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalZeroGamma)); cout<<" 2 ";
RooAbsPdf::GenSpec* GenSpecSignalOneGamma = histPdfSignalOneGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalOneGamma)); cout<<" 3 ";
RooAbsPdf::GenSpec* GenSpecSignalTwoGamma = histPdfSignalTwoGamma->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenSignalTwoGamma)); cout<<" 4 ";
RooAbsPdf::GenSpec* GenSpecPartReco = histPdfPartReco->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenPartReco)); cout<<" 5 "<<endl;
RooAbsPdf::GenSpec* GenSpecComb = combPDF->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenComb));
RooAbsPdf::GenSpec* GenSpecJpsiLeak(0);
if(nGenJpsiLeak>1) GenSpecJpsiLeak = histPdfJpsiLeak->prepareMultiGen(argset2, RooFit::Extended(1), NumEvents(nGenJpsiLeak));
cout<<"Variable loaded:"<<endl;
B_plus_M->Print(); expoConst->Print(); //B_plus_DTFM_M_zero->Print();
if (fit2D) misPT->Print();
//***************Generate some datasets
cout<<"Generating signal Zero Photon"<<endl;
RooDataSet* dataGenSignalZeroGamma = histPdfSignalZeroGamma->generate(*GenSpecSignalZeroGamma);//(argset, 250, false, true, "", false, true);
dataGenSignalZeroGamma->SetName("dataGenSignalZeroGamma"); dataGenSignalZeroGamma->SetTitle("dataGenSignalZeroGamma");
cout<<"Generating signal One Photon"<<endl;
RooDataSet* dataGenSignalOneGamma = histPdfSignalOneGamma->generate(*GenSpecSignalOneGamma);//(argset, 250, false, true, "", false, true);
dataGenSignalOneGamma->SetName("dataGenSignalOneGamma"); dataGenSignalOneGamma->SetTitle("dataGenSignalOneGamma");
cout<<"Generating signal two Photons"<<endl;
RooDataSet* dataGenSignalTwoGamma = histPdfSignalTwoGamma->generate(*GenSpecSignalTwoGamma);//(argset, 250, false, true, "", false, true);
dataGenSignalTwoGamma->SetName("dataGenSignalTwoGamma"); dataGenSignalTwoGamma->SetTitle("dataGenSignalTwoGamma");
cout<<"Generating combinatorial"<<endl;
RooDataSet* dataGenComb = combPDF->generate(*GenSpecComb);//(argset, 100, false, true, "", false, true);
dataGenComb->SetName("dataGenComb"); dataGenComb->SetTitle("dataGenComb");
cout<<"Generating PartReco"<<endl;
RooDataSet* dataGenPartReco = histPdfPartReco->generate(*GenSpecPartReco);//argset, 160, false, true, "", false, true);
dataGenPartReco->SetName("dataGenPartReco"); dataGenPartReco->SetTitle("dataGenPartReco");
RooDataSet* dataGenJpsiLeak(0);
if(nGenJpsiLeak>1)
{
cout<<"Generating Leaking JPsi"<<endl;
dataGenJpsiLeak = histPdfJpsiLeak->generate(*GenSpecJpsiLeak);//argset, 160, false, true, "", false, true);
dataGenJpsiLeak->SetName("dataGenJpsiLeak"); dataGenJpsiLeak->SetTitle("dataGenJpsiLeak");
}
//*************Saving the generated datasets in a workspace
RooWorkspace workspaceGen("workspaceGen", "workspaceGen");
workspaceGen.import(*dataGenSignalZeroGamma);
workspaceGen.import(*dataGenSignalOneGamma);
workspaceGen.import(*dataGenSignalTwoGamma);
workspaceGen.import(*dataGenComb);
workspaceGen.import(*dataGenPartReco);
if(nGenJpsiLeak>1) workspaceGen.import(*dataGenJpsiLeak);
workspaceGen.Write("", TObject::kOverwrite);
//delete workspace;
fw.Close();
delete dataGenSignalZeroGamma;
delete dataGenSignalOneGamma;
delete dataGenSignalTwoGamma;
delete dataGenComb;
delete dataGenPartReco;
if(nGenJpsiLeak>1) delete dataGenJpsiLeak;
delete GenSpecSignalZeroGamma;
delete GenSpecSignalOneGamma;
delete GenSpecSignalTwoGamma;
delete GenSpecComb;
delete GenSpecPartReco;
delete combPDF;
if(nGenJpsiLeak>1) delete GenSpecJpsiLeak;
delete histPdfSignalZeroGamma;
delete histPdfSignalOneGamma;
delete histPdfSignalTwoGamma;
delete histPdfPartReco;
if(nGenJpsiLeak>1) delete histPdfJpsiLeak;
}
int compute(RooFitResult* fit, int nbdata, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin,
double et_plateau, double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin,
bool draw, bool verbose)
{
// Extract fit parameters //
std::cout<<"erereo4"<<std::endl;
RooArgList param = fit->floatParsFinal() ;
std::cout<<"erereo6"<<std::endl;
double err[5] ;
double mu[5] ;
for(Int_t i = 0; i < param.getSize(); i++) {
RooRealVar* var = ( dynamic_cast<RooRealVar*>( param.at(i) ) );
//var->Print() ;
mu[i] = var->getVal() ;
err[i] = var->getError() ;
}
std::cout<<"erereo5"<<std::endl;
double min, max;
min = mu[0]-5*err[0] ;
if (mu[0]-5*err[0]<0) min = 0. ;
RooRealVar alpha("alpha","#alpha",mu[0],min,mu[0]+5*err[0]);
min = mu[1]-5*err[1] ;
if (mu[1]-5*err[1]<5) min = 5. ;
RooRealVar mean("mean","mean",mu[1],min,mu[1]+5*err[1]);
min = mu[2]-5*err[2] ;
if (mu[2]-5*err[2]<1) min = 1. ;
RooRealVar n("n","n",mu[2],min,mu[2]+5*err[2]);
min = mu[3]-5*err[3] ;
if (mu[3]-5*err[3]<0.6) min = 0.6 ;
max = mu[3]+5*err[3] ;
if (mu[3]+5*err[3]>1.) max = 1. ;
RooRealVar norm("norm","N",mu[3],min,max);
min = mu[4]-5*err[4] ;
if (mu[4]-5*err[4]<0.) min = 0. ;
RooRealVar sigma("sigma","#sigma",mu[4],min,mu[4]+5*err[4]);
RooRealVar xaxis("x","x",0,150) ;
// Create PDF and generate nbdata sets of CB parameters
RooAbsPdf* parabPdf = fit->createHessePdf(RooArgSet(norm,alpha,n,mean,sigma)) ;
RooDataSet* data = parabPdf->generate(RooArgSet(norm,alpha,n,mean,sigma),nbdata) ;
// Generate histo to extract error bar on efficiency(xaxis)
xaxis = et_plateau ;
cout << "Generate histo to extract error bars" << endl;
genHisto(nbdata, data, nEff, eff, et, et_errmax, et_errmin, eff_plateau, eff_plateau_errmax, eff_plateau_errmin,
xaxis, mean, sigma, alpha, n, norm, draw, verbose);
/* int genHisto(int nbdata, RooDataSet* data, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin,
double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin,
RooRealVar xaxis, RooRealVar mean, RooRealVar sigma, RooRealVar alpha, RooRealVar n, RooRealVar norm,
bool draw, bool verbose)
int compute(RooFitResult* fit, int nbdata, const int nEff, double* eff, double* et, double* et_errmax, double* et_errmin,
double et_plateau, double& eff_plateau, double& eff_plateau_errmax, double& eff_plateau_errmin,
bool draw, bool verbose)
*/
return 1;
}
void printMassFrom2DParameters(RooWorkspace myws, TPad* Pad, bool isPbPb, string pdfName, bool isWeighted)
{
Pad->cd();
TLatex *t = new TLatex(); t->SetNDC(); t->SetTextSize(0.026); float dy = 0.025;
RooArgSet* Parameters = (RooArgSet*)myws.pdf(pdfName.c_str())->getParameters(RooArgSet(*myws.var("invMass"), *myws.var("ctau"), *myws.var("ctauErr")))->selectByAttrib("Constant",kFALSE);
TIterator* parIt = Parameters->createIterator();
for (RooRealVar* it = (RooRealVar*)parIt->Next(); it!=NULL; it = (RooRealVar*)parIt->Next() ) {
stringstream ss(it->GetName()); string s1, s2, s3, label;
getline(ss, s1, '_'); getline(ss, s2, '_'); getline(ss, s3, '_');
// Parse the parameter's labels
if(s1=="invMass" || s1=="ctauErr" || s1=="ctau"){continue;} else if(s1=="MassRatio"){continue;}
else if(s1=="One"){continue;} else if(s1=="mMin"){continue;} else if(s1=="mMax"){continue;}
if(s1=="RFrac2Svs1S"){ s1="R_{#psi(2S)/J/#psi}"; }
else if(s1=="rSigma21"){ s1="(#sigma_{2}/#sigma_{1})"; }
else if(s1.find("sigma")!=std::string::npos || s1.find("lambda")!=std::string::npos || s1.find("alpha")!=std::string::npos){
s1=Form("#%s",s1.c_str());
}
if(s2=="PbPbvsPP") { s2="PbPb/PP"; }
else if(s2=="Jpsi") { s2="J/#psi"; }
else if(s2=="Psi2S") { s2="#psi(2S)"; }
else if(s2=="Bkg") { s2="bkg"; }
else if(s2=="CtauRes") { continue; }
else if(s2=="JpsiNoPR") { continue; }
else if(s2=="JpsiPR") { continue; }
else if(s2=="Psi2SNoPR"){ continue; }
else if(s2=="Psi2SPR") { continue; }
else if(s2=="BkgNoPR") { continue; }
else if(s2=="BkgPR") { continue; }
else if(s2=="Bkg" && (s1=="N" || s1=="b")) { continue; }
else {continue;}
if(s3!=""){
label=Form("%s_{%s}^{%s}", s1.c_str(), s2.c_str(), s3.c_str());
}
else {
label=Form("%s^{%s}", s1.c_str(), s2.c_str());
}
// Print the parameter's results
if(s1=="N"){
t->DrawLatex(0.20, 0.76-dy, Form((isWeighted?"%s = %.6f#pm%.6f ":"%s = %.0f#pm%.0f "), label.c_str(), it->getValV(), it->getError())); dy+=0.045;
}
else if(s1.find("#sigma_{2}/#sigma_{1}")!=std::string::npos){
t->DrawLatex(0.20, 0.76-dy, Form("%s = %.3f#pm%.3f ", label.c_str(), it->getValV(), it->getError())); dy+=0.045;
}
else if(s1.find("sigma")!=std::string::npos){
t->DrawLatex(0.20, 0.76-dy, Form("%s = %.2f#pm%.2f MeV/c^{2}", label.c_str(), it->getValV()*1000., it->getError()*1000.)); dy+=0.045;
}
else if(s1.find("lambda")!=std::string::npos){
t->DrawLatex(0.20, 0.76-dy, Form("%s = %.4f#pm%.4f", label.c_str(), it->getValV(), it->getError())); dy+=0.045;
}
else if(s1.find("m")!=std::string::npos){
t->DrawLatex(0.20, 0.76-dy, Form("%s = %.5f#pm%.5f GeV/c^{2}", label.c_str(), it->getValV(), it->getError())); dy+=0.045;
}
else {
t->DrawLatex(0.20, 0.76-dy, Form("%s = %.4f#pm%.4f", label.c_str(), it->getValV(), it->getError())); dy+=0.045;
}
}
};
void bfractionVsCent(char *tagger="discr_ssvHighEff", double workingPoint=2., int fixCL=0, char *taggerName="ssvHighEff", float ptlo=80, float pthi=100, float etalo=0., float etahi=2.) {
gStyle->SetOptStat(0);
gStyle->SetOptTitle(0);
gStyle->SetLabelFont(43,"xyz");
gStyle->SetLabelSize(20,"xyz");
gStyle->SetTitleFont(43,"xyz");
gStyle->SetTitleSize(26,"xyz");
gStyle->SetTitleOffset(1.0,"xy");
gROOT->ForceStyle(1);
int doLTJP=1;
int doLTCSV=0;
const int nBins = 2;
double centBin[nBins+1] = {0,30,100};
//const int nBins = 3;
//double centBin[nBins+1] = {0,20,50,100};
Double_t bPurMC, bPurData, bEffMC, bEffDataLTJP, bEffDataLTCSV, taggedFracData, bFracMC, bFracData, bFracDataLTJP, bFracDataLTCSV, bFracJPdirect;
Double_t bPurMCError, bPurDataError, bEffMCError, bEffDataLTJPError, bEffDataLTCSVError, taggedFracDataError, bFracMCError, bFracDataError, bFracDataLTJPError, bFracDataLTCSVError, bFracJPdirectError;
Enumerations numbers;
TH1D *hBPurityData = new TH1D("hBPurityData","hBPurityData;Centrality;B-Tagging purity",nBins,centBin);
TH1D *hBPurityMC = new TH1D("hBPurityMC","hBPurityMC;Centrality;B-Tagging purity",nBins,centBin);
TH1D *hBEfficiencyMC = new TH1D("hBEfficiencyMC","hBEfficiencyMC;Centrality;B-Tagging efficiency",nBins,centBin);
TH1D *hBEfficiencyDataLTJP = new TH1D("hBEfficiencyDataLTJP","hBEfficiencyDataLTJP;Centrality;B-Tagging efficiency",nBins,centBin);
TH1D *hBEfficiencyDataLTCSV = new TH1D("hBEfficiencyDataLTCSV","hBEfficiencyDataLTCSV;Centrality;B-Tagging efficiency",nBins,centBin);
TH1D *hBFractionMC = new TH1D("hBFractionMC","hBFractionMC;Centrality;B-jet fraction",nBins,centBin);
TH1D *hBFractionData = new TH1D("hBFractionData","hBFractionData;Centrality;B-jet fraction",nBins,centBin);
TH1D *hBFractionDataLTJP = new TH1D("hBFractionDataLTJP","hBFractionDataLTJP;Centrality;B-jet fraction",nBins,centBin);
TH1D *hBFractionDataLTCSV = new TH1D("hBFractionDataLTCSV","hBFractionDataLTCSV;Centrality;B-jet fraction",nBins,centBin);
TH1D *hBFractionJPdirect = new TH1D("hBFractionJPdirect","hBFractionJPdirect;Centrality;B-jet fraction",nBins,centBin);
int ncol=1;
int nrow=1;
if(nBins==3||nBins==2){
ncol=nBins;
}
if(nBins==4){
ncol=nBins/2;
nrow=nBins/2;
}
TCanvas *c1=new TCanvas("c1","c1",1200,600);
//c1->Divide(ncol,nrow,0,0);
c1->Divide(ncol,nrow);
TCanvas *c2=new TCanvas("c2","c2",1200,600);
//c2->Divide(ncol,nrow,0,0);
c2->Divide(ncol,nrow);
TCanvas *c3=new TCanvas("c3","c3",1200,600);
//c3->Divide(ncol,nrow,0,0);
c3->Divide(ncol,nrow);
TCanvas *c4=new TCanvas("c4","c4",1200,600);
//c4->Divide(ncol,nrow,0,0);
c4->Divide(ncol,nrow);
TCanvas *cCount = new TCanvas("cCount","cCount",600,600);
for (int n=0;n<nBins;n++) {
cout<<"Processing jet centrality bin ["<<centBin[n]<<","<<centBin[n+1]<<"] ..."<<endl;
cCount->cd();
cout<<"centBin[n]: "<<centBin[n]<<" centBin[n+1]: "<<centBin[n+1]<<" tagger: "<<tagger<<" workingPoint: "<<workingPoint<<" ptlo: "<<ptlo<<" pthi: "<<pthi<<" etalo: "<<etalo<<" etahi: "<<etahi<<endl;
numbers = count(centBin[n],centBin[n+1],tagger,workingPoint,ptlo,pthi,etalo,etahi);
c1->cd(n+1);
c1->GetPad(n+1)->SetLogy();
RooRealVar fitSvtxmTag = bfractionFit(fixCL,"svtxm",0,6,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,workingPoint,6,"b-tagged sample (SSVHE > 2)",9e3);
//RooRealVar fitSvtxmTag = bfractionFit(fixCL,"svtxm",0,6,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,workingPoint,10,Form("b-tagged sample (%s at %.1f)",taggerName,workingPoint));
//RooRealVar fitJpDirect = bfractionFit(fixCL,"discr_prob",0,3,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,-2,10,"inclusive sample",5e4);
c2->cd(n+1);
c2->GetPad(n+1)->SetLogy();
RooRealVar fitJpDirect = bfractionFit(fixCL,"discr_prob",0.0,3.,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,"discr_prob",0.,3.,"inclusive sample",4e5);
if (doLTJP) {
c3->cd(n+1);
c3->GetPad(n+1)->SetLogy();
RooRealVar fitJpBeforetag = bfractionFit(fixCL,"discr_prob",0.0,3.,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,"discr_prob",0,3.,"jets with JP info",4e5);
c4->cd(n+1);
c4->GetPad(n+1)->SetLogy();
RooRealVar fitJpTag = bfractionFit(fixCL,"discr_prob",0.0,3.,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,workingPoint,6,"b-tagged sample (SSVHE > 2)",4e5);
}
if (doLTCSV) {
RooRealVar fitCsvBeforetag = bfractionFit(fixCL,"discr_csvSimple",0,1,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,-2,10,"jets with CSV info",4e5);
RooRealVar fitCsvTag = bfractionFit(fixCL,"discr_csvSimple",0,1,centBin[n],centBin[n+1],ptlo,pthi,etalo,etahi,tagger,workingPoint,10,"b-tagged sample (SSVHE > 2)",4e5);
}
taggedFracData = numbers.nTaggedJetsData / (numbers.nTaggedJetsData+numbers.nUntaggedJetsData);
taggedFracDataError = fracError(numbers.nTaggedJetsData,numbers.nUntaggedJetsData,numbers.nTaggedJetsDataError,numbers.nUntaggedJetsDataError);
//* --- b-tagging purity ---
bPurMC = numbers.nTaggedBjetsMC / numbers.nTaggedJetsMC;
cout<<" bPurMC "<<bPurMC<<" numbers.nTaggedBjetsMC "<<numbers.nTaggedBjetsMC<<" numbers.nTaggedJetsMC "<<numbers.nTaggedJetsMC<<endl;
bPurMCError = fracError(numbers.nTaggedBjetsMC,numbers.nTaggedNonBjetsMC,numbers.nTaggedBjetsMCError,numbers.nTaggedNonBjetsMCError);
bPurData = fitSvtxmTag.getVal();
bPurDataError = fitSvtxmTag.getError();
hBPurityMC->SetBinContent(n+1,bPurMC);
hBPurityMC->SetBinError(n+1,bPurMCError);
hBPurityData->SetBinContent(n+1,bPurData);
hBPurityData->SetBinError(n+1,bPurDataError);
//*/
//* --- b-tagging efficiency ---
bEffMC = numbers.nTaggedBjetsMC / numbers.nBjetsMC;
bEffMCError = fracError(numbers.nTaggedBjetsMC,numbers.nUntaggedBjetsMC,numbers.nTaggedBjetsMCError,numbers.nUntaggedBjetsMCError);
hBEfficiencyMC->SetBinContent(n+1,bEffMC);
hBEfficiencyMC->SetBinError(n+1,bEffMCError);
if (doLTJP) {
bEffDataLTJP = taggedFracData * numbers.cbForJP * fitJpTag.getVal() / fitJpBeforetag.getVal();
bEffDataLTJPError = prodError(taggedFracData,fitJpTag.getVal(),taggedFracDataError,fitJpTag.getError()) * numbers.cbForJP / fitJpBeforetag.getVal();
hBEfficiencyDataLTJP->SetBinContent(n+1,bEffDataLTJP);
hBEfficiencyDataLTJP->SetBinError(n+1,bEffDataLTJPError);
}
if (doLTCSV) {
bEffDataLTCSV = taggedFracData * numbers.cbForCSV * fitCsvTag.getVal() / fitCsvBeforetag.getVal();
bEffDataLTCSVError = prodError(taggedFracData,fitCsvTag.getVal(),taggedFracDataError,fitCsvTag.getError()) * numbers.cbForCSV / fitCsvBeforetag.getVal();
hBEfficiencyDataLTCSV->SetBinContent(n+1,bEffDataLTCSV);
hBEfficiencyDataLTCSV->SetBinError(n+1,bEffDataLTCSVError);
}
//* --- b fraction ---
bFracMC = numbers.nBjetsMC / numbers.nJetsMC;
//bFracMC = numbers.nTaggedJetsMC * bPurMC / (bEffMC * numbers.nJetsMC); // for check : same as previous
bFracMCError = fracError(numbers.nBjetsMC,numbers.nNonBjetsMC,numbers.nBjetsMCError,numbers.nNonBjetsMCError);
hBFractionMC->SetBinContent(n+1,bFracMC);
hBFractionMC->SetBinError(n+1,bFracMCError);
bFracData = taggedFracData * bPurData / bEffMC; // efficiency from MC
bFracDataError = prodError(taggedFracData,bPurData,taggedFracDataError,bPurDataError) / bEffMC; // stat.error from purity and tagged-fraction (assumed independent)
//bFracDataError = bFracData * bPurDataError / bPurData; // stat.error only from purity
hBFractionData->SetBinContent(n+1,bFracData);
hBFractionData->SetBinError(n+1,bFracDataError);
if (doLTJP) {
bFracDataLTJP = taggedFracData * bPurData / bEffDataLTJP ; // efficiency from LTJP method
bFracDataLTJPError = prodError(taggedFracData,bPurData,taggedFracDataError,bPurDataError) / bEffDataLTJP; // stat.error from purity and tagged-fraction (assumed independent)
//bFracDataLTJPError = bFracDataLTJP * bPurDataError / bPurData; // stat.error only from purity
hBFractionDataLTJP->SetBinContent(n+1,bFracDataLTJP);
hBFractionDataLTJP->SetBinError(n+1,bFracDataLTJPError);
}
if (doLTCSV) {
bFracDataLTCSV = taggedFracData * bPurData / bEffDataLTCSV; // efficiency from LTCSV method
bFracDataLTCSVError = prodError(taggedFracData,bPurData,taggedFracDataError,bPurDataError) / bEffDataLTCSV; // stat.error from purity and tagged-fraction (assumed independent)
//bFracDataLTCSVError = bFracDataLTCSV * bPurDataError / bPurData; // stat.error only from purity
hBFractionDataLTCSV->SetBinContent(n+1,bFracDataLTCSV);
hBFractionDataLTCSV->SetBinError(n+1,bFracDataLTCSVError);
}
bFracJPdirect = fitJpDirect.getVal();
bFracJPdirectError = fitJpDirect.getError();
hBFractionJPdirect->SetBinContent(n+1,bFracJPdirect);
hBFractionJPdirect->SetBinError(n+1,bFracJPdirectError);
//*/
//*
cout<<"nTaggedJetsMC "<<numbers.nTaggedJetsMC<<endl;
cout<<"nUntaggedJetsMC "<<numbers.nUntaggedJetsMC<<endl;
cout<<"nJetsMC "<<numbers.nJetsMC<<endl;
cout<<"nTaggedBjetsMC "<<numbers.nTaggedBjetsMC<<endl;
cout<<"nUntaggedBjetsMC "<<numbers.nUntaggedBjetsMC<<endl;
cout<<"nBjetsMC "<<numbers.nBjetsMC<<endl;
cout<<"nNonBjetsMC "<<numbers.nNonBjetsMC<<endl;
cout<<"nTaggedNonBjetsMC "<<numbers.nTaggedNonBjetsMC<<endl;
cout<<"nTaggedJetsData "<<numbers.nTaggedJetsData<<endl;
cout<<"nUntaggedJetsData "<<numbers.nUntaggedJetsData<<endl;
cout<<"bPurMC "<<bPurMC<<endl;
cout<<"bPurData "<<bPurData<<endl;
cout<<"bEffMC "<<bEffMC<<endl;
cout<<"CbForJP "<<numbers.cbForJP<<endl;
cout<<"bEffDataLTJP "<<bEffDataLTJP<<endl;
cout<<"CbForCSV "<<numbers.cbForCSV<<endl;
cout<<"bEffDataLTCSV "<<bEffDataLTCSV<<endl;
cout<<"bFracMC "<<bFracMC<<endl;
cout<<"bFracData "<<bFracData<<endl;
cout<<"bFracDataLTJP "<<bFracDataLTJP<<endl;
cout<<"bFracDataLTCSV "<<bFracDataLTCSV<<endl;
cout<<"bFracJPdirect "<<bFracJPdirect<<endl;
cout<<endl;
//*/
}
TLegend *legPur = new TLegend(0.4,0.15,0.85,0.3,Form("Purity of b-tagged sample (%s at %.1f)",taggerName,workingPoint));
legPur->SetBorderSize(0);
//legPur->SetFillColor(kGray);
legPur->SetFillStyle(0);
legPur->AddEntry(hBPurityMC,"MC Input","pl");
legPur->AddEntry(hBPurityData,"Data","pl");
TCanvas *cBPurity = new TCanvas("cBPurity","b purity",600,600);
hBPurityMC->SetAxisRange(0,1,"Y");
hBPurityMC->SetTitleOffset(1.3,"Y");
hBPurityMC->SetLineColor(2);
hBPurityMC->SetMarkerColor(2);
hBPurityMC->SetMarkerStyle(21);
hBPurityMC->Draw();
hBPurityData->SetLineColor(1);
hBPurityData->SetMarkerColor(1);
hBPurityData->SetMarkerStyle(20);
hBPurityData->Draw("same");
legPur->Draw();
//cBPurity->SaveAs("purity.gif");
TLegend *legEff = new TLegend(0.4,0.65,0.85,0.8,Form("Efficiency for tagging b-jets (%s at %.1f)",taggerName,workingPoint));
legEff->SetBorderSize(0);
//legEff->SetFillColor(kGray);
legEff->SetFillStyle(0);
legEff->AddEntry(hBEfficiencyMC,"MC Efficiency","pl");
if (doLTJP) legEff->AddEntry(hBEfficiencyDataLTJP,"LT method (JP)","pl");
if (doLTCSV) legEff->AddEntry(hBEfficiencyDataLTCSV,"LT method (CSV)","pl");
TCanvas *cBEfficiency = new TCanvas("cBEfficiency","B-Tagging efficiency",600,600);
hBEfficiencyMC->SetAxisRange(0,1,"Y");
hBEfficiencyMC->SetTitleOffset(1.3,"Y");
hBEfficiencyMC->SetLineColor(2);
hBEfficiencyMC->SetMarkerColor(2);
hBEfficiencyMC->SetMarkerStyle(21);
hBEfficiencyMC->Draw();
if (doLTJP) {
hBEfficiencyDataLTJP->SetLineColor(8);
hBEfficiencyDataLTJP->SetMarkerColor(8);
hBEfficiencyDataLTJP->SetMarkerStyle(20);
hBEfficiencyDataLTJP->Draw("same");
}
if (doLTCSV) {
hBEfficiencyDataLTCSV->SetLineColor(7);
hBEfficiencyDataLTCSV->SetMarkerColor(7);
hBEfficiencyDataLTCSV->SetMarkerStyle(20);
hBEfficiencyDataLTCSV->Draw("same");
}
legEff->Draw();
//cBEfficiency->SaveAs("efficiency.gif");
TLegend *legFrac = new TLegend(0.25,0.15,0.85,0.3);
legFrac->SetBorderSize(0);
//legFrac->SetFillColor(kGray);
legFrac->SetFillStyle(0);
legFrac->AddEntry(hBFractionMC,"MC Input","pl");
legFrac->AddEntry(hBFractionData,Form("%s at %.1f + pur. from SV mass + eff. from MC",taggerName,workingPoint),"pl");
if (doLTJP) legFrac->AddEntry(hBFractionDataLTJP,Form("%s at %.1f + pur. from SV mass + eff. from LT (JP)",taggerName,workingPoint),"pl");
if (doLTCSV) legFrac->AddEntry(hBFractionDataLTCSV,Form("%s at %.1f + pur. from SV mass + eff. from LT (CSV)",taggerName,workingPoint),"pl");
legFrac->AddEntry(hBFractionJPdirect,"Direct fit to JP","pl");
TCanvas *cBFraction = new TCanvas("cBFraction","B-jet fraction",600,600);
hBFractionMC->SetAxisRange(0,0.03,"Y");
hBFractionMC->SetTitleOffset(1.8,"Y");
hBFractionMC->SetLineColor(2);
hBFractionMC->SetMarkerColor(2);
hBFractionMC->SetMarkerStyle(21);
hBFractionMC->Draw();
hBFractionData->SetLineColor(1);
hBFractionData->SetMarkerColor(1);
hBFractionData->SetMarkerStyle(20);
hBFractionData->Draw("same");
if (doLTJP) {
hBFractionDataLTJP->SetLineColor(8);
hBFractionDataLTJP->SetMarkerColor(8);
hBFractionDataLTJP->SetMarkerStyle(20);
hBFractionDataLTJP->Draw("same");
}
if (doLTCSV) {
hBFractionDataLTCSV->SetLineColor(7);
hBFractionDataLTCSV->SetMarkerColor(7);
hBFractionDataLTCSV->SetMarkerStyle(20);
hBFractionDataLTCSV->Draw("same");
}
hBFractionJPdirect->SetLineColor(4);
hBFractionJPdirect->SetMarkerColor(4);
hBFractionJPdirect->SetMarkerStyle(20);
hBFractionJPdirect->Draw("same");
legFrac->Draw();
//cBFraction->SaveAs("bfraction.gif");
TFile *fout = new TFile(Form("output/bFractionMerged_%sat%.1fFixCL%d_centDep.root",taggerName,workingPoint,fixCL),"recreate");
hBFractionMC->Write();
hBFractionData->Write();
if (doLTJP) hBFractionDataLTJP->Write();
if (doLTCSV) hBFractionDataLTCSV->Write();
hBFractionJPdirect->Write();
fout->Close();
//c1->SaveAs(Form("gifs/svtxMassFit_%s.gif",fixCL?"CLfixed":"CLfree"));
//c2->SaveAs(Form("gifs/jpDirectFit_%s.gif",fixCL?"CLfixed":"CLfree"));
//c3->SaveAs(Form("gifs/jpBeforeTag_%s.gif",fixCL?"CLfixed":"CLfree"));
//c4->SaveAs(Form("gifs/jpAfterTag_%s.gif",fixCL?"CLfixed":"CLfree"));
}
