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::PlotShape2D(RooDataSet& originDataSet, RooDataSet& genDataSet, RooAbsPdf& shape, string plotsfile, string canvName, RooRealVar& B_plus_M, RooRealVar& misPT)
{
//**************Prepare TFile to save the plots
TFile f2(plotsfile.c_str(), "UPDATE");
//**************Plot Signal Zero Gamma
TH2F* th2fKey = (TH2F*)shape.createHistogram("th2Shape", B_plus_M, Binning(20), YVar(misPT, Binning(20)));
cout<<genDataSet.sumEntries()<<endl;
TH2F* th2fGen = (TH2F*)genDataSet.createHistogram("th2fGen", B_plus_M, Binning(20), YVar(misPT, Binning(20)));
RooPlot* plotM = B_plus_M.frame();
originDataSet.plotOn(plotM);
shape.plotOn(plotM);
RooPlot* plotMisPT = misPT.frame();
originDataSet.plotOn(plotMisPT);
shape.plotOn(plotMisPT);
TCanvas canv(canvName.c_str(), canvName.c_str(), 800, 800);
canv.Divide(2,2);
canv.cd(1); th2fGen->Draw("lego");
canv.cd(2); th2fKey->Draw("surf");
canv.cd(3); plotM->Draw();
canv.cd(4); plotMisPT->Draw();
canv.Write();
f2.Close();
}
//____________________________________
void MakePlots(RooWorkspace* wks) {
// Make plots of the data and the best fit model in two cases:
// first the signal+background case
// second the background-only case.
// get some things out of workspace
RooAbsPdf* model = wks->pdf("model");
RooAbsPdf* sigModel = wks->pdf("sigModel");
RooAbsPdf* zjjModel = wks->pdf("zjjModel");
RooAbsPdf* qcdModel = wks->pdf("qcdModel");
RooRealVar* mu = wks->var("mu");
RooRealVar* invMass = wks->var("invMass");
RooAbsData* data = wks->data("data");
//////////////////////////////////////////////////////////
// Make plots for the Alternate hypothesis, eg. let mu float
mu->setConstant(kFALSE);
model->fitTo(*data,Save(kTRUE),Minos(kFALSE), Hesse(kFALSE),PrintLevel(-1));
//plot sig candidates, full model, and individual componenets
new TCanvas();
RooPlot* frame = invMass->frame() ;
data->plotOn(frame ) ;
model->plotOn(frame) ;
model->plotOn(frame,Components(*sigModel),LineStyle(kDashed), LineColor(kRed)) ;
model->plotOn(frame,Components(*zjjModel),LineStyle(kDashed),LineColor(kBlack)) ;
model->plotOn(frame,Components(*qcdModel),LineStyle(kDashed),LineColor(kGreen)) ;
frame->SetTitle("An example fit to the signal + background model");
frame->Draw() ;
// cdata->SaveAs("alternateFit.gif");
//////////////////////////////////////////////////////////
// Do Fit to the Null hypothesis. Eg. fix mu=0
mu->setVal(0); // set signal fraction to 0
mu->setConstant(kTRUE); // set constant
model->fitTo(*data, Save(kTRUE), Minos(kFALSE), Hesse(kFALSE),PrintLevel(-1));
// plot signal candidates with background model and components
new TCanvas();
RooPlot* xframe2 = invMass->frame() ;
data->plotOn(xframe2, DataError(RooAbsData::SumW2)) ;
model->plotOn(xframe2) ;
model->plotOn(xframe2, Components(*zjjModel),LineStyle(kDashed),LineColor(kBlack)) ;
model->plotOn(xframe2, Components(*qcdModel),LineStyle(kDashed),LineColor(kGreen)) ;
xframe2->SetTitle("An example fit to the background-only model");
xframe2->Draw() ;
// cbkgonly->SaveAs("nullFit.gif");
}
void ComputeUpperLimit(RooAbsData *data, RooStats::ModelConfig *model, float &UpperLimit, float &signif, RooRealVar *mu, RooArgSet *nullParams,RooWorkspace *ws,REGION region,const char* tag) {
bool StoreEverything=false; // activate if you want to store frames and all
RooStats::ProfileLikelihoodCalculator *plc = new RooStats::ProfileLikelihoodCalculator(*data, *model);
plc->SetParameters(*mu);
plc->SetNullParameters(*nullParams);
plc->SetTestSize(0.05);
RooStats::LikelihoodInterval *interval = plc->GetInterval();
bool ComputationSuccessful=false;
UpperLimit = interval->UpperLimit(*mu,ComputationSuccessful);
signif = 0.0; // plc->GetHypoTest()->Significance(); // deactivated significance (to make algorithm faster)
if(!ComputationSuccessful) {
cout << "There seems to have been a problem. Returned upper limit is " << UpperLimit << " but it will be set to -999" << endl;
UpperLimit=-999;
signif=-999;
}
if(StoreEverything) {
// Store it all
RooRealVar* minv = (RooRealVar*)model->GetObservables()->first();
minv->setBins(static_cast<int>((minv->getMax()-minv->getMin())/5.));
RooPlot* frameEE = minv->frame(RooFit::Title("ee sample"));
frameEE->GetXaxis()->CenterTitle(1);
frameEE->GetYaxis()->CenterTitle(1);
RooPlot* frameMM = minv->frame(RooFit::Title("mm sample"));
frameMM->GetXaxis()->CenterTitle(1);
frameMM->GetYaxis()->CenterTitle(1);
RooPlot* frameOF = minv->frame(RooFit::Title("OF sample"));
frameOF->GetXaxis()->CenterTitle(1);
frameOF->GetYaxis()->CenterTitle(1);
data->plotOn(frameMM,RooFit::Cut("catCentral==catCentral::MMCentral"));
model->GetPdf()->plotOn(frameMM,RooFit::Slice(*ws->cat("catCentral"), "MMCentral"),RooFit::ProjWData(*data));
data->plotOn(frameEE,RooFit::Cut("catCentral==catCentral::EECentral"));
model->GetPdf()->plotOn(frameEE,RooFit::Slice(*ws->cat("catCentral"), "EECentral"),RooFit::ProjWData(*data));
data->plotOn(frameOF,RooFit::Cut("catCentral==catCentral::OFOSCentral"));
model->GetPdf()->plotOn(frameOF,RooFit::Slice(*ws->cat("catCentral"), "OFOSCentral"),RooFit::ProjWData(*data));
TFile *fout = new TFile("fout.root","UPDATE");
frameMM->Write(Concatenate(Concatenate(data->GetName(),"_MM"),tag),TObject::kOverwrite);
frameEE->Write(Concatenate(Concatenate(data->GetName(),"_EE"),tag),TObject::kOverwrite);
frameOF->Write(Concatenate(Concatenate(data->GetName(),"_OF"),tag),TObject::kOverwrite);
fout->Close();
}
delete plc;
plc=0;
}
void rf706_histpdf_modified_makeroohistpdf()
{
// gROOT->SetBatch(kTRUE);
//load data
TFile *inHistos= new TFile("output/histos.root", "READ");
TH1F * h100 = (TH1F*)inHistos->Get("cutmassLb7");
TFile * inHistos2 = new TFile("../lambda/output/histos.root", "READ");
TH1F * h200 = (TH1F*)inHistos2->Get("cutmassLb7");
double massLb = 5500;
double massLbmin = 5300;
double massLbmax = 5650;
RooRealVar *mass = new RooRealVar("mass","m(#Lambda_{b})",massLb,"MeV");
RooDataHist *hist1 = new RooDataHist("hist1","1D",RooArgList(*mass),h100);
RooDataHist *hist2 = new RooDataHist("hist2","1D",RooArgList(*mass),h200);
// Represent data in hist1 as pdf in *mass
RooHistPdf histpdf1 = makeroohistpdf(hist1,mass) ;
// Plot binned data and histogram pdf overlaid
RooPlot* frame1 = mass->frame(Title("#Sigma^{0} data with RooHistPdf")) ;
frame1->SetMaximum(1100);
hist1->plotOn(frame1) ;
histpdf1.plotOn(frame1) ;
histpdf1.paramOn(frame1) ;
TCanvas* c1 = new TCanvas("rf706_histpdf","rf706_histpdf",800,400) ;
c1->Divide(1,2);
c1->cd(1);
frame1->Draw() ;
//see what happens if I try to fit histpdf1 to lambda data
RooHistPdf histpdf2 = makeroohistpdf(hist1,mass);
RooAbsReal * nll = histpdf2.createNLL(*hist2,Extended(kTRUE));
RooMinuit m(*nll);
m.setVerbose(kTRUE);
m.migrad();
m.minos();
RooPlot* frame2 = mass->frame(Title("#Lambda^{0} data fit with RooHistPdf from #Sigma^{0} data"));
frame2->SetMaximum(1100);
hist2->plotOn(frame2);
histpdf2.plotOn(frame2);
histpdf2.paramOn(frame2);
c1->cd(2);
frame2->Draw();
//save histpdf1
// cout<<"saving histpdf1..."<<endl;
// histpdf1.RooHistPdf::SavePrimitive(std::cout);
// gROOT->SetPrimitive(kFALSE);
}
int main(){
RooMsgService::instance().setGlobalKillBelow(ERROR);
TFile *bkgFile = TFile::Open("comb_svn/hgg.inputbkgdata_8TeV_MVA.root");
RooWorkspace *bkgWS = (RooWorkspace*)bkgFile->Get("cms_hgg_workspace");
RooRealVar *mass = (RooRealVar*)bkgWS->var("CMS_hgg_mass");
RooDataSet *data = (RooDataSet*)bkgWS->data("data_mass_cat0");
RooRealVar *p1 = new RooRealVar("p1","p1",-2.,-10.,0.);
RooRealVar *p2 = new RooRealVar("p2","p2",-0.001,-0.01,0.01);
RooRealVar *p3 = new RooRealVar("p3","p3",-0.0001,-0.01,0.01);
//RooPowerLawSum *pow1 = new RooPowerLawSum("pow","pow",*mass,RooArgList(*p1));
//RooPowerLawSum *pow2 = new RooPowerLawSum("pow","pow",*mass,RooArgList(*p1,*p2));
//RooPowerLawSum *pow3 = new RooPowerLawSum("pow","pow",*mass,RooArgList(*p1,*p2,*p3));
RooExponentialSum *pow1 = new RooExponentialSum("pow1","pow1",*mass,RooArgList(*p1));
RooExponentialSum *pow2 = new RooExponentialSum("pow2","pow2",*mass,RooArgList(*p1,*p2));
RooExponentialSum *pow3 = new RooExponentialSum("pow3","pow3",*mass,RooArgList(*p1,*p2,*p3));
TCanvas *canv = new TCanvas();
RooPlot *frame = mass->frame();
data->plotOn(frame);
cout << "bus" << endl;
pow1->fitTo(*data,PrintEvalErrors(-1),PrintLevel(-1),Warnings(-1),Verbose(-1));
cout << "bus" << endl;
pow1->plotOn(frame);
pow2->fitTo(*data);
pow2->plotOn(frame,LineColor(kRed),LineStyle(kDashed));
pow3->fitTo(*data);
pow3->plotOn(frame,LineColor(kGreen),LineStyle(7));
frame->Draw();
canv->Print("test.pdf");
TFile *outFile = new TFile("test.root","RECREATE");
TTree *tree = new TTree("tree","tree");
vector<double> mu;
mu.push_back(1.);
mu.push_back(2.);
mu.push_back(3.);
mu.push_back(4.);
vector<string> label;
label.push_back("pol");
label.push_back("pow");
label.push_back("lau");
label.push_back("exp");
tree->Branch("mu",&mu);
tree->Branch("label",&label);
tree->Fill();
outFile->cd();
tree->Write();
outFile->Close();
return 0;
}
void chi2(int xmin = 0, int xmax = 200, TString filename="../DsubMC/met2j0bIso2ewkScale_0_200.root", int nparam = 2){
RooAbsData::ErrorType errorType = RooAbsData::SumW2;
file = new TFile(filename);
RooRealVar* h = new RooRealVar("h","h",xmin,xmax);
//Get Data
TH1D* hData = file->Get("dataih");
hData->SetName("hData");
//hData->Draw();
RooDataHist* data = new RooDataHist("data","data",*h,hData);
//Get Summed MC
TH1D* hMC = file->Get("hh");
hMC->SetName("hMC");
hMC->Draw();
RooDataHist rdhMC("MC","MC",*h,hMC);
RooHistPdf pdfMC("MCpdf","MCpdf",*h,rdhMC);
//make (plot) the curves
RooPlot* hFrame = h->frame(Name("hFrame"));
data->plotOn(hFrame,RooFit::DataError(errorType));
pdfMC.plotOn(hFrame,ProjWData(*data),Components(pdfMC),Name("h_total"));
//Determine Chi^2
double chi2fit = hFrame->chiSquare("h_total", "h_data", nparam);
cout<<"Chi 2 / dof: "<<chi2fit<<endl;
//Determine K-S
double ks = hMC->KolmogorovTest(hData);
cout<<"Kolmogorov-Smirnov: "<<ks<<endl;
}
pair<double,double> bkgEvPerGeV(RooWorkspace *work, int m_hyp, int cat, int spin=false){
RooRealVar *mass = (RooRealVar*)work->var("CMS_hgg_mass");
if (spin) mass = (RooRealVar*)work->var("mass");
mass->setRange(100,180);
RooAbsPdf *pdf = (RooAbsPdf*)work->pdf(Form("pdf_data_pol_model_8TeV_cat%d",cat));
RooAbsData *data = (RooDataSet*)work->data(Form("data_mass_cat%d",cat));
RooPlot *tempFrame = mass->frame();
data->plotOn(tempFrame,Binning(80));
pdf->plotOn(tempFrame);
RooCurve *curve = (RooCurve*)tempFrame->getObject(tempFrame->numItems()-1);
double nombkg = curve->Eval(double(m_hyp));
RooRealVar *nlim = new RooRealVar(Form("nlim%d",cat),"",0.,0.,1.e5);
//double lowedge = tempFrame->GetXaxis()->GetBinLowEdge(FindBin(double(m_hyp)));
//double upedge = tempFrame->GetXaxis()->GetBinUpEdge(FindBin(double(m_hyp)));
//double center = tempFrame->GetXaxis()->GetBinUpCenter(FindBin(double(m_hyp)));
nlim->setVal(nombkg);
mass->setRange("errRange",m_hyp-0.5,m_hyp+0.5);
RooAbsPdf *epdf = 0;
epdf = new RooExtendPdf("epdf","",*pdf,*nlim,"errRange");
RooAbsReal *nll = epdf->createNLL(*data,Extended(),NumCPU(4));
RooMinimizer minim(*nll);
minim.setStrategy(0);
minim.setPrintLevel(-1);
minim.migrad();
minim.minos(*nlim);
double error = (nlim->getErrorLo(),nlim->getErrorHi())/2.;
data->Print();
return pair<double,double>(nombkg,error);
}
//#include "/uscms_data/d3/cvernier/DiH_13TeV/CMSSW_7_1_5/src/HiggsAnalysis/CombinedLimit/interface/RooMultiPdf.h"
//#include "HiggsAnalysis/CombinedLimit/interface/RooMultiPdf.h"
void makeRooMultiPdfWorkspace(){
// Load the combine Library
gSystem->Load("libHiggsAnalysisCombinedLimit.so");
// Open the dummy H->gg workspace
TFile *f_hgg = TFile::Open("w_background_Bern.root");
RooWorkspace *w_hgg = (RooWorkspace*)f_hgg->Get("HbbHbb");
// The observable (CMS_hgg_mass in the workspace)
RooRealVar *mass = w_hgg->var("x");
// Get three of the functions inside, exponential, linear polynomial, power law
RooAbsPdf *pdf_exp = w_hgg->pdf("bg_exp");
RooAbsPdf *pdf_pol = w_hgg->pdf("bg");
// Fit the functions to the data to set the "prefit" state (note this can and should be redone with combine when doing
// bias studies as one typically throws toys from the "best-fit"
RooAbsData *data = w_hgg->data("data_obs");
pdf_exp->fitTo(*data); // index 0
pdf_pol->fitTo(*data); // index 2
// Make a plot (data is a toy dataset)
RooPlot *plot = mass->frame(); data->plotOn(plot);
pdf_exp->plotOn(plot,RooFit::LineColor(kBlue));
pdf_pol->plotOn(plot,RooFit::LineColor(kRed));
plot->SetTitle("PDF fits to toy data");
plot->Draw();
// Make a RooCategory object. This will control which of the pdfs is "active"
RooCategory cat("pdf_index","Index of Pdf which is active");
// Make a RooMultiPdf object. The order of the pdfs will be the order of their index, ie for below
// 0 == exponential
// 1 == linear function
// 2 == powerlaw
RooArgList mypdfs;
mypdfs.add(*pdf_exp);
mypdfs.add(*pdf_pol);
RooMultiPdf multipdf("roomultipdf","All Pdfs",cat,mypdfs);
// As usual make an extended term for the background with _norm for freely floating yield
RooRealVar norm("roomultipdf_norm","Number of background events",0,10000);
// Save to a new workspace
TFile *fout = new TFile("background_pdfs.root","RECREATE");
RooWorkspace wout("backgrounds","backgrounds");
wout.import(cat);
wout.import(norm);
wout.import(multipdf);
wout.Print();
wout.Write();
}
void FitterUtils::PlotShape1D(RooDataSet& originDataSet, RooDataSet& genDataSet, RooAbsPdf& shape, string plotsfile, string canvName, RooRealVar& B_plus_M)
{
TFile f2(plotsfile.c_str(), "UPDATE");
RooPlot* plotGen = B_plus_M.frame(Binning(20));
genDataSet.plotOn(plotGen);
RooPlot* plotM = B_plus_M.frame();
originDataSet.plotOn(plotM);
shape.plotOn(plotM);
TCanvas canv(canvName.c_str(), canvName.c_str(), 800, 800);
canv.Divide(1,2);
canv.cd(1); plotGen->Draw();
canv.cd(2); plotM->Draw();
canv.Write();
f2.Close();
}
void FitterUtils::plot_fit_result(string plotsfile, RooAbsPdf &totPdf, RooDataSet dataGenTot)
{
//**************Prepare TFile to save the plots
TFile f2(plotsfile.c_str(), "UPDATE");
//**************Plot the results of the fit
RooArgSet *var_set = totPdf.getObservables(dataGenTot);
TIterator *iter = var_set->createIterator();
RooRealVar *var;
std::vector<RooPlot*> plots;
RooPlot* frame;
while((var = (RooRealVar*) iter->Next()))
{
frame = var->frame();
dataGenTot.plotOn(frame);
totPdf.plotOn(frame, Components("histPdfPartReco"), LineColor(kBlue));
totPdf.plotOn(frame, Components("histPdfSignalZeroGamma"), LineColor(kGreen));
totPdf.plotOn(frame, Components("histPdfSignalOneGamma"), LineColor(kMagenta));
totPdf.plotOn(frame, Components("histPdfSignalTwoGamma"), LineColor(kOrange));
totPdf.plotOn(frame, Components("histPdfJpsiLeak"), LineColor(14));
totPdf.plotOn(frame, Components("combPDF"), LineColor(kBlack));
totPdf.plotOn(frame, LineColor(kRed));
plots.push_back(frame);
}
if (!(plots.size())) return;
TCanvas cFit("cFit", "cFit", 600, 800);
cFit.Divide(1,2);
cFit.cd(1); plots[0]->Draw();
if (plots.size()>1){
cFit.cd(2); plots[1]->Draw();
}
cFit.Write();
f2.Close();
}
void plotFromWorkspace() {
TFile* file = new TFile("card_m125_1JetIncl_XX_workspace.root");
RooWorkspace* w = (RooWorkspace*)file->Get("w");
RooRealVar* m = (RooRealVar*)w->var("CMS_hmumu_mass");
RooRealVar* e = (RooRealVar*)w->var("CMS_hmumu_merr");
RooDataSet* d = (RooDataSet*)w->data("data_pseudo");
RooAbsPdf * b = w->pdf("bkg_mass_merr_1JetIncl_XX_pdf");
RooAbsPdf * s = w->pdf("sig_mass_merr_ggH_1JetIncl_XX_pdf");
RooPlot* frame = m->frame();
d->plotOn(frame);
b->plotOn(frame);
//s->plotOn(frame, RooFit::ProjWData(*e, *d), RooFit::LineColor(kOrange+1));
//s->plotOn(frame, RooFit::LineColor(kOrange+1));
frame->Draw();
}
void simul(){
TFile* in = new TFile( "../bin/Kdata.root", "READ" );
TH1D* h = in->Get("tof_8");
RooRealVar * x = new RooRealVar( "x", "x", -10, 10 );
RooDataHist * rdh = new RooDataHist( "data", "data", RooArgSet( *x ), h);
RooRealVar m( "mean", "mean", 0, -1, 1 );
RooRealVar s( "sigma", "sigma", .5, 0, 1 );
RooGaussian g( "gauss", "gauss", )
RooPlot * frame = x->frame();
rdh->plotOn( frame );
frame->Draw();
}
void plot_with_residuals(TCanvas& _c,RooPlot& _frame,RooRealVar& var,Int_t& _nbins,Double_t& r_min,Double_t& r_max) {
_c.SetName("_c");
_c.Divide(1,2);
_c_1->SetPad(0.01,0.16,0.99,0.99);
_c_2->SetPad(0.01,0.01,0.99,0.16);
_c.cd(1);
_frame.Draw();
_c.cd(2);
RooHist* hpull = _frame.pullHist();
RooPlot* frame_pull = var.frame(Title(" "),Range(r_min,r_max),Bins(_nbins));
frame_pull->addPlotable(hpull,"P");
// this is if you want residuals in number of events
/*RooHist* hresid = _frame -> residHist();*/
/*RooPlot* frame2 = m_Kpipi.frame(1000,2000,25);*/
/*frame2->addPlotable(hresid,"P");*/
frame_pull->SetMinimum(-5);
frame_pull->SetMaximum(+5);
frame_pull->SetNdivisions(0,"x"); // 510 for having also an x scale here
frame_pull->SetNdivisions(203,"y"); // axis divisions was 510
frame_pull->SetXTitle(" ");
frame_pull->SetLabelSize(0.15,"Y");
frame_pull->Draw();
TLine *_line = new TLine(r_min,-3.,r_max,-3);
_line->SetLineStyle(1);
_line->SetLineColor(2);
_line->SetLineWidth(1);
_line->Draw();
_line2 = new TLine(r_min,+3.,r_max,+3);
_line2->SetLineStyle(1);
_line2->SetLineColor(2);
_line2->SetLineWidth(1);
_line2->Draw();
}
void FitterUtilsSimultaneousExpOfPolyTimesX::plot_kemu_fit_result(string plotsfile, RooAbsPdf &totKemuPdf, RooDataSet const& dataGenKemu)
{
//**************Prepare TFile to save the plots
TFile f2(plotsfile.c_str(), "UPDATE");
//**************Plot the results of the fit
RooArgSet *var_set = totKemuPdf.getObservables(dataGenKemu);
TIterator *iter = var_set->createIterator();
RooRealVar *var;
std::vector<RooPlot*> plots;
RooPlot* frame;
while((var = (RooRealVar*) iter->Next()))
{
frame = var->frame();
dataGenKemu.plotOn(frame);
totKemuPdf.plotOn(frame, LineColor(kRed));
plots.push_back(frame);
}
if (!(plots.size())) return;
TCanvas cFit("cKemuFit", "cKemuFit", 600, 800);
cFit.Divide(1,2);
cFit.cd(1); plots[0]->Draw();
if (plots.size()>1){
cFit.cd(2); plots[1]->Draw();
}
cFit.Write();
f2.Close();
}
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();
}
}
void fitWWa_el() {
TFile* fin = new TFile("../RunII_WVA_ControlPlots.root");
TH1D* data_obs = (TH1D*) fin->Get("Electron/vbf_maxpt_jj_m/data_obs");
TH1D* th1fkdata = (TH1D*) fin->Get("Electron/vbf_maxpt_jj_m/th1FakePhotons");
TH1D* th1wwa = (TH1D*) fin->Get("Electron/vbf_maxpt_jj_m/th1wwa");
TH1D* th1wza = (TH1D*) fin->Get("Electron/vbf_maxpt_jj_m/th1wza");
TH1D* th1wajets = (TH1D*) fin->Get("Electron/vbf_maxpt_jj_m/th1wajets");
TH1D* th1zajets = (TH1D*) fin->Get("Electron/vbf_maxpt_jj_m/th1zajets");
TH1D* th1Top = (TH1D*) fin->Get("Electron/vbf_maxpt_jj_m/th1ttajets");
TH1D* th1tajets = (TH1D*) fin->Get("Electron/vbf_maxpt_jj_m/th1tajets");
int NbinsX = data_obs->GetNbinsX();
double xmin = data_obs->GetXaxis()->GetBinLowEdge(1);
double xmax = data_obs->GetXaxis()->GetBinLowEdge(NbinsX+1);
data_obs->GetXaxis()->SetRangeUser(xmin, xmax);
th1fkdata->GetXaxis()->SetRangeUser(xmin, xmax);
th1wwa->GetXaxis()->SetRangeUser(xmin, xmax);
th1wza->GetXaxis()->SetRangeUser(xmin, xmax);
th1wajets->GetXaxis()->SetRangeUser(xmin, xmax);
th1zajets->GetXaxis()->SetRangeUser(xmin, xmax);
th1Top->GetXaxis()->SetRangeUser(xmin, xmax);
th1tajets->GetXaxis()->SetRangeUser(xmin, xmax);
th1wwa->Add(th1wza);
th1Top->Add(th1tajets);
mjj_ = new RooRealVar( "Mjj", "m_{jj}", xmin, xmax, "GeV");
RooRealVar Mass = *mjj_;
RooDataHist* data = new RooDataHist("data","data", *mjj_, data_obs);
RooHistPdf* pdffk = makePdf(th1fkdata, "pdffk");
RooHistPdf* pdfwwa = makePdf(th1wwa, "pdfwwa");
RooHistPdf* pdfwajets = makePdf(th1wajets, "pdfwajets");
RooHistPdf* pdfzajets = makePdf(th1zajets, "pdfzajets");
RooHistPdf* pdfTop = makePdf(th1Top, "pdfTop");
double fkNorm = th1fkdata->Integral();
double wwaNorm = th1wwa->Integral();
double wajetsNorm = th1wajets->Integral();
double zajetsNorm = th1zajets->Integral();
double TopNorm = th1Top->Integral();
RooRealVar nfk("nfk","nfk", fkNorm, 0.0, 1000.);
RooRealVar nwwa("nwwa","nwwa", wwaNorm);
RooRealVar nwajets("nwajets","nwajets", 400.0, 0.0, 10000.);
RooRealVar nzajets("nzajets","nzajets", zajetsNorm);
RooRealVar nTop("nTop","nTop", TopNorm);
RooArgList* components
= new RooArgList(*pdffk, *pdfwwa, *pdfwajets, *pdfzajets, *pdfTop);
RooArgList* yields = new RooArgList(nfk, nwwa, nwajets, nzajets, nTop);
RooAddPdf totalPdf("totalPdf","extended sum pdf", *components, *yields);
RooGaussian consNfk("consNfk","", nfk, RooConst(fkNorm),RooConst(0.146*fkNorm)) ;
RooGaussian consNwwa("consNwwa","", nwwa, RooConst(wwaNorm),RooConst(0.28*wwaNorm)) ;
RooGaussian consNzajets("consNzajets","", nzajets, RooConst(zajetsNorm),RooConst(0.22*zajetsNorm)) ;
RooGaussian consNTop("consNTop","", nTop, RooConst(TopNorm),RooConst(0.21*TopNorm)) ;
RooFitResult *fitResult
= totalPdf.fitTo(*data, Save(true),
ExternalConstraints(consNfk),
//ExternalConstraints(consNwwa),
//ExternalConstraints(consNzajets),
//ExternalConstraints(consNTop),
RooFit::Extended(true),
//RooFit::Minos(true),
//RooFit::Hesse(false),
//PrintEvalErrors(-1),
// RooFit::Range(rangeString),
Warnings(false)
);
fitResult->Print("v");
std::cout << "===================== Wa+jets k-factor = " <<
nwajets.getVal() / wajetsNorm << " +- " << nwajets.getError() / wajetsNorm << std::endl;
// ********** Make and save Canvas for the plots ********** //
gROOT->ProcessLine(".L ~kalanand/tdrstyle.C");
setTDRStyle();
tdrStyle->SetErrorX(0.5);
tdrStyle->SetPadLeftMargin(0.19);
tdrStyle->SetPadRightMargin(0.10);
tdrStyle->SetPadBottomMargin(0.15);
tdrStyle->SetLegendBorderSize(0);
tdrStyle->SetTitleYOffset(1.5);
RooAbsData::ErrorType errorType = RooAbsData::SumW2;
TCanvas* c = new TCanvas("fit","",500,500);
RooPlot* frame1 = Mass.frame();
data->plotOn(frame1,RooFit::DataError(errorType), Name("h_data"));
totalPdf.plotOn(frame1,ProjWData(*data), Name("h_total"));
totalPdf.plotOn(frame1,ProjWData(*data),Components("pdfwajets"),
LineColor(kRed), LineStyle(2), Name("h_wajets"));
totalPdf.plotOn(frame1,ProjWData(*data),Components("pdffk,pdfwwa,pdfzajets,pdfTop"),
LineColor(kBlack), LineStyle(2), Name("h_others"));
totalPdf.plotOn(frame1,ProjWData(*data));
frame1->SetMinimum(0);
frame1->SetMaximum(1.35* frame1->GetMaximum());
frame1->Draw("e0");
std::cout << "===================== chi2/ dof = " << frame1->chiSquare() << std::endl;
TPaveText *plotlabel4 = new TPaveText(0.25,0.66,0.5,0.81,"NDC");
plotlabel4->SetTextColor(kBlack);
plotlabel4->SetFillColor(kWhite);
plotlabel4->SetBorderSize(0);
plotlabel4->SetTextAlign(12);
plotlabel4->SetTextSize(0.04);
char temp[50];
sprintf(temp, "#chi^{2} / dof = %.2f", frame1->chiSquare());
plotlabel4->AddText(temp);
plotlabel4->Draw();
cmsPrelim2();
TLegend* legend = new TLegend(0.55,0.72,0.88,0.91);
RooHist* datahist = frame1->getHist("h_data");
RooCurve* totalhist = frame1->getCurve("h_total");
RooCurve* wjetshist = frame1->getCurve("h_wajets");
RooCurve* otherhist = frame1->getCurve("h_others");
legend->AddEntry( datahist, "Data", "PE");
legend->AddEntry( totalhist, "Fit", "L");
legend->AddEntry( wjetshist, "W#gamma+jets", "L");
legend->AddEntry( otherhist, "Other processes", "L");
legend->SetFillColor(0);
legend->Draw();
c->SaveAs( "el_WVa_WjetsKfactorFit.png");
c->SaveAs( "el_WVa_WjetsKfactorFit.pdf");
}
void runUPWW() {
int higgsMass=125;
double intLumi=5.1;
int nToys = 10;
bool draw=true;
using namespace RooFit;
gROOT->ProcessLine(".L ~/tdrstyle.C");
setTDRStyle();
gStyle->SetPadLeftMargin(0.16);
gROOT->ForceStyle();
gROOT->ProcessLine(".L statsFactory.cc+");
//
// set up test kind
//
double sigRate;
double bkgRate;
if(higgsMass==125){
sigRate = 7.;
bkgRate = 66.;
}else{
cout << "HMMMM.... I don't know that mass point...BYE!" << endl;
return;
}
RooRealVar* mll = new RooRealVar("mll","dilepton mass [GeV]", 12, 80.);
mll->setBins(17);
RooArgSet* obs = new RooArgSet(*mll) ;
// read signal hypothesis 1
TChain *tsigHyp1 = new TChain("angles");
tsigHyp1->Add(Form("datafiles/bdtpresel/%i/SMHiggsWW_%i_JHU.root",higgsMass, higgsMass));
RooDataSet *sigHyp1Data = new RooDataSet("sigHyp1Data","sigHyp1Data",tsigHyp1,*obs);
RooDataHist *sigHyp1Hist = sigHyp1Data->binnedClone(0);
RooHistPdf* sigHyp1Pdf = new RooHistPdf("sigHyp1Pdf", "sigHyp1Pdf", *obs, *sigHyp1Hist);
// read background
TChain *bkgTree = new TChain("angles");
bkgTree->Add(Form("datafiles/bdtpresel/%i/WW_madgraph_8TeV.root",higgsMass));
RooDataSet *bkgData = new RooDataSet("bkgData","bkgData",bkgTree,*obs);
RooDataHist *bkgHist = bkgData->binnedClone(0);
RooHistPdf* bkgPdf = new RooHistPdf("bkgPdf", "bkgPdf", *obs, *bkgHist);
char statResults[25];
statsFactory *hwwuls;
sprintf(statResults,"uls_hww125_%.0ffb.root", intLumi);
hwwuls = new statsFactory(obs, sigHyp1Pdf, sigHyp1Pdf, statResults);
hwwuls->runUpperLimitWithBackground(sigRate*intLumi, bkgRate*intLumi, bkgPdf, nToys);
delete hwwuls;
// draw plots
if(draw) {
RooPlot* plot1 = mll->frame();
TString plot1Name = "mll";
TCanvas* c1 = new TCanvas("c1","c1",400,400);
bkgData->plotOn(plot1,MarkerColor(kBlack));
bkgPdf->plotOn(plot1, LineColor(kBlack), LineStyle(kDashed));
sigHyp1Data->plotOn(plot1,MarkerColor(kRed));
sigHyp1Pdf->plotOn(plot1,LineColor(kRed), LineStyle(kDashed));
// draw...
plot1->Draw();
c1->SaveAs(Form("plots/ul/epsfiles/%s.eps", plot1Name.Data()));
c1->SaveAs(Form("plots/ul/pngfiles/%s.png", plot1Name.Data()));
delete c1;
}
}
void MakePlots(RooWorkspace* ws){
// Here we make plots of the discriminating variable (invMass) after the fit
// and of the control variable (isolation) after unfolding with sPlot.
std::cout << "make plots" << std::endl;
// make our canvas
TCanvas* cdata = new TCanvas("sPlot","sPlot demo", 400, 600);
cdata->Divide(1,3);
// get what we need out of the workspace
RooAbsPdf* model = ws->pdf("model");
RooAbsPdf* zModel = ws->pdf("zModel");
RooAbsPdf* qcdModel = ws->pdf("qcdModel");
RooRealVar* isolation = ws->var("isolation");
RooRealVar* invMass = ws->var("invMass");
// note, we get the dataset with sWeights
RooDataSet* data = (RooDataSet*) ws->data("dataWithSWeights");
// this shouldn't be necessary, need to fix something with workspace
// do this to set parameters back to their fitted values.
model->fitTo(*data, Extended() );
//plot invMass for data with full model and individual componenets overlayed
// TCanvas* cdata = new TCanvas();
cdata->cd(1);
RooPlot* frame = invMass->frame() ;
data->plotOn(frame ) ;
model->plotOn(frame) ;
model->plotOn(frame,Components(*zModel),LineStyle(kDashed), LineColor(kRed)) ;
model->plotOn(frame,Components(*qcdModel),LineStyle(kDashed),LineColor(kGreen)) ;
frame->SetTitle("Fit of model to discriminating variable");
frame->Draw() ;
// Now use the sWeights to show isolation distribution for Z and QCD.
// The SPlot class can make this easier, but here we demonstrait in more
// detail how the sWeights are used. The SPlot class should make this
// very easy and needs some more development.
// Plot isolation for Z component.
// Do this by plotting all events weighted by the sWeight for the Z component.
// The SPlot class adds a new variable that has the name of the corresponding
// yield + "_sw".
cdata->cd(2);
// create weightfed data set
RooDataSet * dataw_z = new RooDataSet(data->GetName(),data->GetTitle(),data,*data->get(),0,"zYield_sw") ;
RooPlot* frame2 = isolation->frame() ;
dataw_z->plotOn(frame2, DataError(RooAbsData::SumW2) ) ;
frame2->SetTitle("isolation distribution for Z");
frame2->Draw() ;
// Plot isolation for QCD component.
// Eg. plot all events weighted by the sWeight for the QCD component.
// The SPlot class adds a new variable that has the name of the corresponding
// yield + "_sw".
cdata->cd(3);
RooDataSet * dataw_qcd = new RooDataSet(data->GetName(),data->GetTitle(),data,*data->get(),0,"qcdYield_sw") ;
RooPlot* frame3 = isolation->frame() ;
dataw_qcd->plotOn(frame3,DataError(RooAbsData::SumW2) ) ;
frame3->SetTitle("isolation distribution for QCD");
frame3->Draw() ;
// cdata->SaveAs("SPlot.gif");
}
void draw_data_mgg(TString folderName,bool blind=true,float min=103,float max=160)
{
TFile inputFile(folderName+"/data.root");
const int nCat = 5;
TString cats[5] = {"HighPt","Hbb","Zbb","HighRes","LowRes"};
TCanvas cv;
for(int iCat=0; iCat < nCat; iCat++) {
RooWorkspace *ws = (RooWorkspace*)inputFile.Get(cats[iCat]+"_mgg_workspace");
RooFitResult* res = (RooFitResult*)ws->obj("fitresult_pdf_data");
RooRealVar * mass = ws->var("mgg");
mass->setRange("all",min,max);
mass->setRange("blind",121,130);
mass->setRange("low",106,121);
mass->setRange("high",130,160);
mass->setUnit("GeV");
mass->SetTitle("m_{#gamma#gamma}");
RooAbsPdf * pdf = ws->pdf("pdf");
RooPlot *plot = mass->frame(min,max,max-min);
plot->SetTitle("");
RooAbsData* data = ws->data("data")->reduce(Form("mgg > %f && mgg < %f",min,max));
double nTot = data->sumEntries();
if(blind) data = data->reduce("mgg < 121 || mgg>130");
double nBlind = data->sumEntries();
double norm = nTot/nBlind; //normalization for the plot
data->plotOn(plot);
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"),RooFit::LineWidth(0.1) );
plot->Print();
//add the fix error band
RooCurve* c = plot->getCurve("pdf_Norm[mgg]_Range[Full]_NormRange[Full]");
const int Nc = c->GetN();
//TGraphErrors errfix(Nc);
//TGraphErrors errfix2(Nc);
TGraphAsymmErrors errfix(Nc);
TGraphAsymmErrors errfix2(Nc);
Double_t *x = c->GetX();
Double_t *y = c->GetY();
double NtotalFit = ws->var("Nbkg1")->getVal()*ws->var("Nbkg1")->getVal() + ws->var("Nbkg2")->getVal()*ws->var("Nbkg2")->getVal();
for( int i = 0; i < Nc; i++ )
{
errfix.SetPoint(i,x[i],y[i]);
errfix2.SetPoint(i,x[i],y[i]);
mass->setVal(x[i]);
double shapeErr = pdf->getPropagatedError(*res)*NtotalFit;
//double totalErr = TMath::Sqrt( shapeErr*shapeErr + y[i] );
//total normalization error
double totalErr = TMath::Sqrt( shapeErr*shapeErr + y[i]*y[i]/NtotalFit );
if ( y[i] - totalErr > .0 )
{
errfix.SetPointError(i, 0, 0, totalErr, totalErr );
}
else
{
errfix.SetPointError(i, 0, 0, y[i] - 0.01, totalErr );
}
//2sigma
if ( y[i] - 2.*totalErr > .0 )
{
errfix2.SetPointError(i, 0, 0, 2.*totalErr, 2.*totalErr );
}
else
{
errfix2.SetPointError(i, 0, 0, y[i] - 0.01, 2.*totalErr );
}
/*
std::cout << x[i] << " " << y[i] << " "
<< " ,pdf get Val: " << pdf->getVal()
<< " ,pdf get Prop Err: " << pdf->getPropagatedError(*res)*NtotalFit
<< " stat uncertainty: " << TMath::Sqrt(y[i]) << " Ntot: " << NtotalFit << std::endl;
*/
}
errfix.SetFillColor(kYellow);
errfix2.SetFillColor(kGreen);
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kFALSE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kFALSE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kTRUE));
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kTRUE));
plot->addObject(&errfix,"4");
plot->addObject(&errfix2,"4");
plot->addObject(&errfix,"4");
data->plotOn(plot);
TBox blindBox(121,plot->GetMinimum()-(plot->GetMaximum()-plot->GetMinimum())*0.015,130,plot->GetMaximum());
blindBox.SetFillColor(kGray);
if(blind) {
plot->addObject(&blindBox);
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kGreen),RooFit::Range("Full"), RooFit::VisualizeError(*res,2.0,kTRUE));
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::FillColor(kYellow),RooFit::Range("Full"), RooFit::VisualizeError(*res,1.0,kTRUE));
}
//plot->addObject(&errfix,"4");
//data->plotOn(plot);
//pdf->plotOn(plot,RooFit::Normalization( norm ) );
//pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"),RooFit::LineWidth(1.5) );
pdf->plotOn(plot,RooFit::NormRange( "low,high" ),RooFit::Range("Full"), RooFit::LineWidth(1));
data->plotOn(plot);
/*
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::Range("all"),RooFit::LineWidth(0.8) );
//pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kGreen),RooFit::Range("all"), RooFit::VisualizeError(*res,2.0,kFALSE));
//pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kYellow),RooFit::Range("all"), RooFit::VisualizeError(*res,1.0,kFALSE));
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kGreen),RooFit::Range("all"), RooFit::VisualizeError(*res,2.0,kTRUE));
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::FillColor(kYellow),RooFit::Range("all"), RooFit::VisualizeError(*res,1.0,kTRUE));
data->plotOn(plot);
pdf->plotOn(plot,RooFit::Normalization(norm),RooFit::Range("all"),RooFit::LineWidth(0.8) );
*/
TLatex lbl0(0.1,0.96,"CMS Preliminary");
lbl0.SetNDC();
lbl0.SetTextSize(0.042);
plot->addObject(&lbl0);
TLatex lbl(0.4,0.96,Form("%s Box",cats[iCat].Data()));
lbl.SetNDC();
lbl.SetTextSize(0.042);
plot->addObject(&lbl);
TLatex lbl2(0.6,0.96,"#sqrt{s}=8 TeV L = 19.78 fb^{-1}");
lbl2.SetNDC();
lbl2.SetTextSize(0.042);
plot->addObject(&lbl2);
int iObj=-1;
TNamed *obj;
while( (obj = (TNamed*)plot->getObject(++iObj)) ) {
obj->SetName(Form("Object_%d",iObj));
}
plot->Draw();
TString tag = (blind ? "_BLIND" : "");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".png");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".pdf");
cv.SaveAs(folderName+"/figs/mgg_data_"+cats[iCat]+tag+TString(Form("_%0.0f_%0.0f",min,max))+".C");
}
}
// The actual job
void backgroundFits_qqzz_1Dw(int channel, int sqrts, int VBFtag)
{
if(sqrts==7)return;
TString schannel;
if (channel == 1) schannel = "4mu";
else if (channel == 2) schannel = "4e";
else if (channel == 3) schannel = "2e2mu";
else cout << "Not a valid channel: " << schannel << endl;
TString ssqrts = (long) sqrts + TString("TeV");
cout << "schannel = " << schannel << " sqrts = " << sqrts << " VBFtag = " << VBFtag << endl;
TString outfile;
if(VBFtag<2) outfile = "CardFragments/qqzzBackgroundFit_" + ssqrts + "_" + schannel + "_" + Form("%d",int(VBFtag)) + ".txt";
if(VBFtag==2) outfile = "CardFragments/qqzzBackgroundFit_" + ssqrts + "_" + schannel + ".txt";
ofstream of(outfile,ios_base::out);
of << "### background functions ###" << endl;
gSystem->AddIncludePath("-I$ROOFITSYS/include");
gROOT->ProcessLine(".L ../CreateDatacards/include/tdrstyle.cc");
setTDRStyle(false);
gStyle->SetPadLeftMargin(0.16);
TString filepath;
if (sqrts==7) {
filepath = filePath7TeV;
} else if (sqrts==8) {
filepath = filePath8TeV;
}
TChain* tree = new TChain("SelectedTree");
tree->Add( filepath+ "/" + (schannel=="2e2mu"?"2mu2e":schannel) + "/HZZ4lTree_ZZTo*.root");
RooRealVar* MC_weight = new RooRealVar("MC_weight","MC_weight",0.,2.) ;
RooRealVar* ZZMass = new RooRealVar("ZZMass","ZZMass",100.,1000.);
RooRealVar* NJets30 = new RooRealVar("NJets30","NJets30",0.,100.);
RooArgSet ntupleVarSet(*ZZMass,*NJets30,*MC_weight);
RooDataSet *set = new RooDataSet("set","set",ntupleVarSet,WeightVar("MC_weight"));
Float_t myMC,myMass;
Short_t myNJets;
int nentries = tree->GetEntries();
tree->SetBranchAddress("ZZMass",&myMass);
tree->SetBranchAddress("MC_weight",&myMC);
tree->SetBranchAddress("NJets30",&myNJets);
for(int i =0;i<nentries;i++) {
tree->GetEntry(i);
if(VBFtag==1 && myNJets<2)continue;
if(VBFtag==0 && myNJets>1)continue;
ntupleVarSet.setRealValue("ZZMass",myMass);
ntupleVarSet.setRealValue("MC_weight",myMC);
ntupleVarSet.setRealValue("NJets30",(double)myNJets);
set->add(ntupleVarSet, myMC);
}
double totalweight = 0.;
double totalweight_z = 0.;
for (int i=0 ; i<set->numEntries() ; i++) {
//set->get(i) ;
RooArgSet* row = set->get(i) ;
//row->Print("v");
totalweight += set->weight();
if (row->getRealValue("ZZMass") < 200) totalweight_z += set->weight();
}
cout << "nEntries: " << set->numEntries() << ", totalweight: " << totalweight << ", totalweight_z: " << totalweight_z << endl;
gSystem->Load("libHiggsAnalysisCombinedLimit.so");
//// ---------------------------------------
//Background
RooRealVar CMS_qqzzbkg_a0("CMS_qqzzbkg_a0","CMS_qqzzbkg_a0",115.3,0.,200.);
RooRealVar CMS_qqzzbkg_a1("CMS_qqzzbkg_a1","CMS_qqzzbkg_a1",21.96,0.,200.);
RooRealVar CMS_qqzzbkg_a2("CMS_qqzzbkg_a2","CMS_qqzzbkg_a2",122.8,0.,200.);
RooRealVar CMS_qqzzbkg_a3("CMS_qqzzbkg_a3","CMS_qqzzbkg_a3",0.03479,0.,1.);
RooRealVar CMS_qqzzbkg_a4("CMS_qqzzbkg_a4","CMS_qqzzbkg_a4",185.5,0.,200.);
RooRealVar CMS_qqzzbkg_a5("CMS_qqzzbkg_a5","CMS_qqzzbkg_a5",12.67,0.,200.);
RooRealVar CMS_qqzzbkg_a6("CMS_qqzzbkg_a6","CMS_qqzzbkg_a6",34.81,0.,100.);
RooRealVar CMS_qqzzbkg_a7("CMS_qqzzbkg_a7","CMS_qqzzbkg_a7",0.1393,0.,1.);
RooRealVar CMS_qqzzbkg_a8("CMS_qqzzbkg_a8","CMS_qqzzbkg_a8",66.,0.,200.);
RooRealVar CMS_qqzzbkg_a9("CMS_qqzzbkg_a9","CMS_qqzzbkg_a9",0.07191,0.,1.);
RooRealVar CMS_qqzzbkg_a10("CMS_qqzzbkg_a10","CMS_qqzzbkg_a10",94.11,0.,200.);
RooRealVar CMS_qqzzbkg_a11("CMS_qqzzbkg_a11","CMS_qqzzbkg_a11",-5.111,-100.,100.);
RooRealVar CMS_qqzzbkg_a12("CMS_qqzzbkg_a12","CMS_qqzzbkg_a12",4834,0.,10000.);
RooRealVar CMS_qqzzbkg_a13("CMS_qqzzbkg_a13","CMS_qqzzbkg_a13",0.2543,0.,1.);
if (channel == 1){
///* 4mu
CMS_qqzzbkg_a0.setVal(103.854);
CMS_qqzzbkg_a1.setVal(10.0718);
CMS_qqzzbkg_a2.setVal(117.551);
CMS_qqzzbkg_a3.setVal(0.0450287);
CMS_qqzzbkg_a4.setVal(185.262);
CMS_qqzzbkg_a5.setVal(7.99428);
CMS_qqzzbkg_a6.setVal(39.7813);
CMS_qqzzbkg_a7.setVal(0.0986891);
CMS_qqzzbkg_a8.setVal(49.1325);
CMS_qqzzbkg_a9.setVal(0.0389984);
CMS_qqzzbkg_a10.setVal(98.6645);
CMS_qqzzbkg_a11.setVal(-7.02043);
CMS_qqzzbkg_a12.setVal(5694.66);
CMS_qqzzbkg_a13.setVal(0.0774525);
//*/
}
else if (channel == 2){
///* 4e
CMS_qqzzbkg_a0.setVal(111.165);
CMS_qqzzbkg_a1.setVal(19.8178);
CMS_qqzzbkg_a2.setVal(120.89);
CMS_qqzzbkg_a3.setVal(0.0546639);
CMS_qqzzbkg_a4.setVal(184.878);
CMS_qqzzbkg_a5.setVal(11.7041);
CMS_qqzzbkg_a6.setVal(33.2659);
CMS_qqzzbkg_a7.setVal(0.140858);
CMS_qqzzbkg_a8.setVal(56.1226);
CMS_qqzzbkg_a9.setVal(0.0957699);
CMS_qqzzbkg_a10.setVal(98.3662);
CMS_qqzzbkg_a11.setVal(-6.98701);
CMS_qqzzbkg_a12.setVal(10.0536);
CMS_qqzzbkg_a13.setVal(0.110576);
//*/
}
else if (channel == 3){
///* 2e2mu
CMS_qqzzbkg_a0.setVal(110.293);
CMS_qqzzbkg_a1.setVal(11.8334);
CMS_qqzzbkg_a2.setVal(116.91);
CMS_qqzzbkg_a3.setVal(0.0433151);
CMS_qqzzbkg_a4.setVal(185.817);
CMS_qqzzbkg_a5.setVal(10.5945);
CMS_qqzzbkg_a6.setVal(29.6208);
CMS_qqzzbkg_a7.setVal(0.0826);
CMS_qqzzbkg_a8.setVal(53.1346);
CMS_qqzzbkg_a9.setVal(0.0882081);
CMS_qqzzbkg_a10.setVal(85.3776);
CMS_qqzzbkg_a11.setVal(-13.3836);
CMS_qqzzbkg_a12.setVal(7587.95);
CMS_qqzzbkg_a13.setVal(0.325621);
//*/
}
else {
cout << "disaster" << endl;
}
RooqqZZPdf_v2* bkg_qqzz = new RooqqZZPdf_v2("bkg_qqzz","bkg_qqzz",*ZZMass,
CMS_qqzzbkg_a0,CMS_qqzzbkg_a1,CMS_qqzzbkg_a2,CMS_qqzzbkg_a3,CMS_qqzzbkg_a4,
CMS_qqzzbkg_a5,CMS_qqzzbkg_a6,CMS_qqzzbkg_a7,CMS_qqzzbkg_a8,
CMS_qqzzbkg_a9,CMS_qqzzbkg_a10,CMS_qqzzbkg_a11,CMS_qqzzbkg_a12,CMS_qqzzbkg_a13);
RooArgSet myASet(*ZZMass, CMS_qqzzbkg_a0,CMS_qqzzbkg_a1,CMS_qqzzbkg_a2,CMS_qqzzbkg_a3,CMS_qqzzbkg_a4,
CMS_qqzzbkg_a5,CMS_qqzzbkg_a6,CMS_qqzzbkg_a7);
myASet.add(CMS_qqzzbkg_a8);
myASet.add(CMS_qqzzbkg_a9);
myASet.add(CMS_qqzzbkg_a10);
myASet.add(CMS_qqzzbkg_a11);
myASet.add(CMS_qqzzbkg_a12);
myASet.add(CMS_qqzzbkg_a13);
RooFitResult *r1 = bkg_qqzz->fitTo( *set, Save(kTRUE), SumW2Error(kTRUE) );//, Save(kTRUE), SumW2Error(kTRUE)) ;
cout << endl;
cout << "------- Parameters for " << schannel << " sqrts=" << sqrts << endl;
cout << " a0_bkgd = " << CMS_qqzzbkg_a0.getVal() << endl;
cout << " a1_bkgd = " << CMS_qqzzbkg_a1.getVal() << endl;
cout << " a2_bkgd = " << CMS_qqzzbkg_a2.getVal() << endl;
cout << " a3_bkgd = " << CMS_qqzzbkg_a3.getVal() << endl;
cout << " a4_bkgd = " << CMS_qqzzbkg_a4.getVal() << endl;
cout << " a5_bkgd = " << CMS_qqzzbkg_a5.getVal() << endl;
cout << " a6_bkgd = " << CMS_qqzzbkg_a6.getVal() << endl;
cout << " a7_bkgd = " << CMS_qqzzbkg_a7.getVal() << endl;
cout << " a8_bkgd = " << CMS_qqzzbkg_a8.getVal() << endl;
cout << " a9_bkgd = " << CMS_qqzzbkg_a9.getVal() << endl;
cout << " a10_bkgd = " << CMS_qqzzbkg_a10.getVal() << endl;
cout << " a11_bkgd = " << CMS_qqzzbkg_a11.getVal() << endl;
cout << " a12_bkgd = " << CMS_qqzzbkg_a12.getVal() << endl;
cout << " a13_bkgd = " << CMS_qqzzbkg_a13.getVal() << endl;
cout << "}" << endl;
cout << "---------------------------" << endl;
of << "qqZZshape a0_bkgd " << CMS_qqzzbkg_a0.getVal() << endl;
of << "qqZZshape a1_bkgd " << CMS_qqzzbkg_a1.getVal() << endl;
of << "qqZZshape a2_bkgd " << CMS_qqzzbkg_a2.getVal() << endl;
of << "qqZZshape a3_bkgd " << CMS_qqzzbkg_a3.getVal() << endl;
of << "qqZZshape a4_bkgd " << CMS_qqzzbkg_a4.getVal() << endl;
of << "qqZZshape a5_bkgd " << CMS_qqzzbkg_a5.getVal() << endl;
of << "qqZZshape a6_bkgd " << CMS_qqzzbkg_a6.getVal() << endl;
of << "qqZZshape a7_bkgd " << CMS_qqzzbkg_a7.getVal() << endl;
of << "qqZZshape a8_bkgd " << CMS_qqzzbkg_a8.getVal() << endl;
of << "qqZZshape a9_bkgd " << CMS_qqzzbkg_a9.getVal() << endl;
of << "qqZZshape a10_bkgd " << CMS_qqzzbkg_a10.getVal() << endl;
of << "qqZZshape a11_bkgd " << CMS_qqzzbkg_a11.getVal() << endl;
of << "qqZZshape a12_bkgd " << CMS_qqzzbkg_a12.getVal() << endl;
of << "qqZZshape a13_bkgd " << CMS_qqzzbkg_a13.getVal() << endl;
of << endl << endl;
of.close();
cout << endl << "Output written to: " << outfile << endl;
double qqzznorm;
if (channel == 1) qqzznorm = 20.5836;
else if (channel == 2) qqzznorm = 13.8871;
else if (channel == 3) qqzznorm = 32.9883;
else { cout << "disaster!" << endl; }
ZZMass->setRange("fullrange",100.,1000.);
ZZMass->setRange("largerange",100.,600.);
ZZMass->setRange("zoomrange",100.,200.);
double rescale = qqzznorm/totalweight;
double rescale_z = qqzznorm/totalweight_z;
cout << "rescale: " << rescale << ", rescale_z: " << rescale_z << endl;
// Plot m4l and
RooPlot* frameM4l = ZZMass->frame(Title("M4L"),Range(100,600),Bins(250)) ;
set->plotOn(frameM4l, MarkerStyle(20), Rescale(rescale)) ;
//set->plotOn(frameM4l) ;
RooPlot* frameM4lz = ZZMass->frame(Title("M4L"),Range(100,200),Bins(100)) ;
set->plotOn(frameM4lz, MarkerStyle(20), Rescale(rescale)) ;
int iLineColor = 1;
string lab = "blah";
if (channel == 1) { iLineColor = 2; lab = "4#mu"; }
if (channel == 3) { iLineColor = 4; lab = "2e2#mu"; }
if (channel == 2) { iLineColor = 6; lab = "4e"; }
bkg_qqzz->plotOn(frameM4l,LineColor(iLineColor),NormRange("largerange")) ;
bkg_qqzz->plotOn(frameM4lz,LineColor(iLineColor),NormRange("zoomrange")) ;
//second shape to compare with (if previous comparison code unceommented)
//bkg_qqzz_bkgd->plotOn(frameM4l,LineColor(1),NormRange("largerange")) ;
//bkg_qqzz_bkgd->plotOn(frameM4lz,LineColor(1),NormRange("zoomrange")) ;
double normalizationBackground_qqzz = bkg_qqzz->createIntegral( RooArgSet(*ZZMass), Range("fullrange") )->getVal();
cout << "Norm all = " << normalizationBackground_qqzz << endl;
frameM4l->GetXaxis()->SetTitle("m_{4l} [GeV]");
frameM4l->GetYaxis()->SetTitle("a.u.");
frameM4lz->GetXaxis()->SetTitle("m_{4l} [GeV]");
frameM4lz->GetYaxis()->SetTitle("a.u.");
char lname[192];
sprintf(lname,"qq #rightarrow ZZ #rightarrow %s", lab.c_str() );
char lname2[192];
sprintf(lname2,"Shape Model, %s", lab.c_str() );
// dummy!
TF1* dummyF = new TF1("dummyF","1",0.,1.);
TH1F* dummyH = new TH1F("dummyH","",1, 0.,1.);
dummyF->SetLineColor( iLineColor );
dummyF->SetLineWidth( 2 );
dummyH->SetLineColor( kBlue );
TLegend * box2 = new TLegend(0.4,0.70,0.80,0.90);
box2->SetFillColor(0);
box2->SetBorderSize(0);
box2->AddEntry(dummyH,"Simulation (POWHEG+Pythia) ","pe");
box2->AddEntry(dummyH,lname,"");
box2->AddEntry(dummyH,"","");
box2->AddEntry(dummyF,lname2,"l");
TPaveText *pt = new TPaveText(0.15,0.955,0.4,0.99,"NDC");
pt->SetFillColor(0);
pt->SetBorderSize(0);
pt->AddText("CMS Preliminary 2012");
TPaveText *pt2 = new TPaveText(0.84,0.955,0.99,0.99,"NDC");
pt2->SetFillColor(0);
pt2->SetBorderSize(0);
TString entag;entag.Form("#sqrt{s} = %d TeV",sqrts);
pt2->AddText(entag.Data());
TCanvas *c = new TCanvas("c","c",800,600);
c->cd();
frameM4l->Draw();
frameM4l->GetYaxis()->SetRangeUser(0,0.4);
if(channel == 3)frameM4l->GetYaxis()->SetRangeUser(0,0.7);
box2->Draw();
pt->Draw();
pt2->Draw();
TString outputPath = "bkgFigs";
outputPath = outputPath+ (long) sqrts + "TeV/";
TString outputName;
if(VBFtag<2) outputName = outputPath + "bkgqqzz_" + schannel + "_" + Form("%d",int(VBFtag));
if(VBFtag==2) outputName = outputPath + "bkgqqzz_" + schannel;
c->SaveAs(outputName + ".eps");
c->SaveAs(outputName + ".png");
TCanvas *c2 = new TCanvas("c2","c2",1000,500);
c2->Divide(2,1);
c2->cd(1);
frameM4l->Draw();
box2->Draw("same");
c2->cd(2);
frameM4lz->Draw();
box2->Draw("same");
if (VBFtag<2) outputName = outputPath + "bkgqqzz_" + schannel + "_z" + "_" + Form("%d",int(VBFtag));
if (VBFtag==2) outputName = outputPath + "bkgqqzz_" + schannel + "_z";
c2->SaveAs(outputName + ".eps");
c2->SaveAs(outputName + ".png");
/* TO make the ratio btw 2 shapes, if needed for compairson
TCanvas *c3 = new TCanvas("c3","c3",1000,500);
if(sqrts==7)
sprintf(outputName, "bkgFigs7TeV/bkgqqzz_%s_ratio.eps",schannel.c_str());
else if(sqrts==8)
sprintf(outputName, "bkgFigs8TeV/bkgqqzz_%s_ratio.eps",schannel.c_str());
const int nPoints = 501.;
double masses[nPoints] ;
int j=0;
for (int i=100; i<601; i++){
masses[j] = i;
j++;
}
cout<<j<<endl;
double effDiff[nPoints];
for (int i = 0; i < nPoints; i++){
ZZMass->setVal(masses[i]);
double eval = (bkg_qqzz_bkgd->getVal(otherASet)-bkg_qqzz->getVal(myASet))/(bkg_qqzz->getVal(myASet));
//cout<<bkg_qqzz_bkgd->getVal(otherASet)<<" "<<bkg_qqzz->getVal(myASet)<<" "<<eval<<endl;
effDiff[i]=eval;
}
TGraph* grEffDiff = new TGraph( nPoints, masses, effDiff );
grEffDiff->SetMarkerStyle(20);
grEffDiff->Draw("AL");
//c3->SaveAs(outputName);
*/
if (VBFtag<2) outputName = outputPath + "bkgqqzz_" + schannel + "_z" + "_" + Form("%d",int(VBFtag)) + ".root";
if (VBFtag==2) outputName = outputPath + "bkgqqzz_" + schannel + "_z" + ".root";
TFile* outF = new TFile(outputName,"RECREATE");
outF->cd();
c2->Write();
frameM4l->Write();
frameM4lz->Write();
outF->Close();
delete c;
delete c2;
}
//Either with fractions:
//RooRealVar fracJpsi("fracJpsi","The Jpsi signal fraction",0.6,0.,1.);
//RooAddPdf totSigPDF("totSigPDF","The total Signal PDF",RooArgList(gaussJpsi,gausspsi),RooArgList(fracJpsi));
//RooRealVar fracSig("fracSig","The signal fraction",0.2,0.,1.);
//RooAddPdf totPDF("totPDF","The total PDF",RooArgList(totSigPDF,backPDF),RooArgList(fracSig));
//Or extended
RooRealVar NJpsi("NJpsi","The Jpsi signal events",9000.,0.1,20000.);
RooRealVar Npsi("Npsi","The psi signal events",300.,0.1,600.);
RooRealVar Nbkg("Nbkg","The bkg events",20000.,0.1,50000.);
RooAddPdf totPDF("totPDF","The total PDF",RooArgList(CBJpsi,gausspsi,backPDF),RooArgList(NJpsi,Npsi,Nbkg));
totPDF.fitTo(*data,RooFit::Extended(1));
RooPlot *xframe = mass.frame();
data->plotOn(xframe);
//totPDF.plotOn(xframe);
TCanvas c1;
c1.cd();
xframe->Draw();
c1.SaveAs("exercise_final.gif");
RooWorkspace w("w");
w.import(*data);
w.import(totPDF);
TFile fOut("Workspace_final.root","RECREATE");
fOut.cd();
w.Write();
void fit_mass(TString fileN="") {//suffix added before file extension, e.g., '.pdf'
TString placeholder;//to add strings before using them, e.g., for saving text files
gROOT->SetBatch(kTRUE);
gROOT->ProcessLine(".x /afs/cern.ch/user/m/mwilkins/cmtuser/src/lhcbStyle.C");
// gStyle->SetPadTickX(1);
// gStyle->SetPadTickY(1);
// gStyle->SetPadLeftMargin(0.15);
// gStyle->SetTextSize(0.3);
// //open file and get histogram
// TFile *inHistos = new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/data/histos_data.root", "READ");
// TH1F * h100 = (TH1F*)inHistos->Get("h70");
// cout<<"data histogram gotten"<<endl;
//unbinned
TFile *hastree = new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/data/cutfile_Optimized.root", "READ");
TTree * h100 = (TTree*)hastree->Get("mytree");
cout<<"tree gotten"<<endl;
TFile *SMChistos= new TFile("/afs/cern.ch/work/m/mwilkins/Lb2JpsiLtr/MC/withKScut/histos_SMCfile_fullMC.root", "READ");
cout<<"SMC file opened"<<endl;
TH1F *SMCh = (TH1F*)SMChistos->Get("h00");
cout<<"SMC hist gotten"<<endl;
RooRealVar *mass = new RooRealVar("Bs_LOKI_MASS_JpsiConstr","m(J/#psi #Lambda)",4100,6100,"MeV");
mass->setRange("bkg1",4300,4800);
mass->setRange("bkg2",5700,5950);
mass->setRange("bkg3",4300,5500);
mass->setRange("bkg4",5100,5500);
mass->setRange("L",5350,5950);
mass->setRange("tot",4300,5950);
cout<<"mass declared"<<endl;
// RooDataHist *data = new RooDataHist("data","1D",RooArgList(*mass),h100);
//unbinned
RooDataSet *data = new RooDataSet("data","1D",h100,*mass);
cout<<"data declared"<<endl;
RooDataHist *SMC = new RooDataHist("SMC","1D",RooArgList(*mass),SMCh);
cout<<"SMC hist assigned to RooDataHist"<<endl;
// Construct Pdf Model
// /\0
//gaussian
RooRealVar mean1L("mean1L","/\\ gaus 1: mean",5621.103095,5525,5700);
RooRealVar sig1L("sig1L","/\\ gaus 1: sigma",6.898126,0,100);
RooGaussian gau1L("gau1L","#Lambda signal: gaussian 1",*mass,mean1L,sig1L);
RooFormulaVar mean2L("mean2L","@0",mean1L);
RooRealVar sig2L("sig2L","/\\ gaus 2: sigma",14.693117,0,100);
RooGaussian gau2L("gau2L","#Lambda signal: gaussian 2",*mass,mean2L,sig2L);
RooRealVar f1L("f1L","/\\ signal: fraction gaussian 1",0.748776,0,1);
RooAddPdf sigL("sigL","#Lambda signal",RooArgList(gau1L,gau2L),RooArgList(f1L));
// //CB
// RooRealVar mean3L("mean3L","/\\ CB: mean",5621.001,5525,5700);
// RooRealVar sig3L("sig3L","/\\ CB: sigma",5.161,0,100);
// RooRealVar alphaL3("alphaL3","/\\ CB: alpha",2.077,0,1000);
// RooRealVar nL3("nL1","/\\ CB: n",0.286,0,1000);
// RooCBShape CBL("CBL","#Lambda signal: CB",*mass,mean3L,sig3L,alphaL3,nL3);
// RooRealVar mean4L("mean4L","/\\ gaus: mean",5621.804,5525,5700);
// RooRealVar sig4L("sig4L","/\\ gaus: sigma",10.819,0,100);
// RooGaussian gauL("gauL","#Lambda signal: gaussian",*mass,mean4L,sig4L);
// RooRealVar f1L("f1L","/\\ signal: fraction CB",0.578,0,1);
// RooAddPdf sigL("sigL","#Lambda signal",RooArgList(CBL,gauL),RooArgList(f1L));
// sigma0
//using RooHistPdf from MC--no need to build pdf here
RooHistPdf sigS = makeroohistpdf(SMC,mass,"sigS","#Sigma^{0} signal (RooHistPdf)");
// /\*
cout<<"Lst stuff"<<endl;
RooRealVar meanLst1("meanLst1","/\\*(misc.): mean1",5011.031237,4900,5100);
RooRealVar sigLst1("sigLst1","/\\*(misc.): sigma1",70.522092,0,100);
RooRealVar meanLst2("mean5Lst2","/\\*(1405): mean2",5245.261703,5100,5350);
RooRealVar sigLst2("sigLst2","/\\*(1405): sigma2",64.564763,0,100);
RooRealVar alphaLst2("alphaLst2","/\\*(1405): alpha2",29.150301);
RooRealVar nLst2("nLst2","/\\*(1405): n2",4.615817,0,50);
RooGaussian gauLst1("gauLst1","#Lambda*(misc.), gaus",*mass,meanLst1,sigLst1);
RooCBShape gauLst2("gauLst2","#Lambda*(1405), CB",*mass,meanLst2,sigLst2,alphaLst2,nLst2);
// RooRealVar fLst1("fLst1","/\\* bkg: fraction gaus 1",0.743,0,1);
// RooAddPdf bkgLst("bkgLst","#Lambda* signal",RooArgList(gauLst1,gauLst2),RooArgList(fLst1));
//Poly func BKG mass
// RooRealVar b0("b0","Background: Chebychev b0",-1.071,-10000,10000);
RooRealVar b1("b1","Background: Chebychev b1",-1.323004,-10,-0.00000000000000000000001);
RooRealVar b2("b2","Background: Chebychev b2",0.145494,0,10);
RooRealVar b3("b3","Background: Chebychev b3",-0.316,-10000,10000);
RooRealVar b4("b4","Background: Chebychev b4",0.102,-10000,10000);
RooRealVar b5("b5","Background: Chebychev b5",0.014,-10000,10000);
RooRealVar b6("b6","Background: Chebychev b6",-0.015,-10000,10000);
RooRealVar b7("b7","Background: Chebychev b7",0.012,-10000,10000);
RooArgList bList(b1,b2);
RooChebychev bkg("bkg","Background", *mass, bList);
// TF1 *ep = new TF1("ep","[2]*exp([0]*x+[1]*x*x)",4300,5950);
// ep->SetParameter(0,1);
// ep->SetParameter(1,-1);
// ep->SetParameter(2,2000);
// ep->SetParName(0,"a");
// ep->SetParName(1,"b");
// ep->SetParName(2,"c");
// RooRealVar a("a","Background: Coefficent of x",1,-10000,10000);
// RooRealVar b("b","Background: Coefficent of x*x",-1,-10000,10000);
// RooRealVar c("c","Background: Coefficent of exp()",2000,-10000,10000);
// RooTFnPdfBinding bkg("ep","ep",ep,RooArgList(*mass,a,b));
//number of each shape
RooRealVar nbkg("nbkg","N bkg",2165.490249,0,100000000);
RooRealVar nsigL("nsigL","N /\\",1689.637290,0,1000000000);
RooRealVar nsigS("nsigS","N sigma",0.000002,0,10000000000);
RooRealVar ngauLst1("ngauLst1","N /\\*(misc.)",439.812103,0,10000000000);
RooRealVar ngauLst2("ngauLst2","N /\\*(1405)",152.061617,0,10000000000);
RooRealVar nbkgLst("nbkgLst","N /\\*",591.828,0,1000000000);
//add shapes and their number to a totalPdf
RooArgList shapes;
RooArgList yields;
shapes.add(sigL); yields.add(nsigL);
shapes.add(sigS); yields.add(nsigS);
// shapes.add(bkgLst); yields.add(nbkgLst);
shapes.add(gauLst1); yields.add(ngauLst1);
shapes.add(gauLst2); yields.add(ngauLst2);
shapes.add(bkg); yields.add(nbkg);
RooAddPdf totalPdf("totalPdf","totalPdf",shapes,yields);
//fit the totalPdf
RooAbsReal * nll = totalPdf.createNLL(*data,Extended(kTRUE),Range("tot"));
RooMinuit m(*nll);
m.setVerbose(kFALSE);
m.migrad();
m.minos();
m.minos();
//display and save information
ofstream textfile;//create text file to hold data
placeholder = "plots/fit"+fileN+".txt";
textfile.open(placeholder);
TString outputtext;//for useful text
//plot things
RooPlot *framex = mass->frame();
framex->GetYaxis()->SetTitle("Events/(5 MeV)");
data->plotOn(framex,Name("Hist"),MarkerColor(kBlack),LineColor(kBlack),DataError(RooAbsData::SumW2));
totalPdf.plotOn(framex,Name("curvetot"),LineColor(kBlue));
RooArgSet* totalPdfComponents = totalPdf.getComponents();
TIterator* itertPC = totalPdfComponents->createIterator();
RooAddPdf* vartPC = (RooAddPdf*) itertPC->Next();
vartPC = (RooAddPdf*) itertPC->Next();//skip totalPdf
int i=0;//color index
TLegend *leg = new TLegend(0.2, 0.02, .4, .42);
leg->SetTextSize(0.06);
leg->AddEntry(framex->findObject("curvetot"),"Total PDF","l");
while(vartPC){//loop over compotents of totalPdf
TString vartPCtitle = vartPC->GetTitle();
TIterator* itercompPars;//forward declare so it persists outside the if statement
RooRealVar* varcompPars;
if(!(vartPCtitle.Contains(":")||vartPCtitle.Contains("@"))){//only for non-sub-shapes
while(i==0||i==10||i==4||i==1||i==5||(i>=10&&i<=27))i++;//avoid white and blue and black and yellow and horribleness
RooArgSet* compPars = vartPC->getParameters(data);//set of the parameters of the component the loop is on
itercompPars = compPars->createIterator();
varcompPars = (RooRealVar*) itercompPars->Next();
while(varcompPars){//write and print mean, sig, etc. of sub-shapes
TString vartitle = varcompPars->GetTitle();
double varval = varcompPars->getVal();
TString varvalstring = Form("%f",varval);
double hi = varcompPars->getErrorHi();
TString varerrorstring = "[exact]";
if(hi!=-1){
double lo = varcompPars->getErrorLo();
double varerror = TMath::Max(fabs(lo),hi);
varerrorstring = Form("%E",varerror);
}
outputtext = vartitle+" = "+varvalstring+" +/- "+varerrorstring;
textfile<<outputtext<<endl;
cout<<outputtext<<endl;
varcompPars = (RooRealVar*) itercompPars->Next();
}
totalPdf.plotOn(framex,Name(vartPC->GetName()),LineStyle(kDashed),LineColor(i),Components(vartPC->GetName()));
leg->AddEntry(framex->findObject(vartPC->GetName()),vartPCtitle,"l");
i++;
}
vartPC = (RooAddPdf*) itertPC->Next();
itercompPars->Reset();//make sure it's ready for the next vartPC
}
// Calculate chi2/ndf
RooArgSet *floatpar = totalPdf.getParameters(data);
int floatpars = (floatpar->selectByAttrib("Constant",kFALSE))->getSize();
Double_t chi2 = framex->chiSquare("curvetot","Hist",floatpars);
TString chi2string = Form("%f",chi2);
//create text box to list important parameters on the plot
// TPaveText* txt = new TPaveText(0.1,0.5,0.7,0.9,"NBNDC");
// txt->SetTextSize(0.06);
// txt->SetTextColor(kBlack);
// txt->SetBorderSize(0);
// txt->SetFillColor(0);
// txt->SetFillStyle(0);
outputtext = "#chi^{2}/N_{DoF} = "+chi2string;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
// txt->AddText(outputtext);
// Print stuff
TIterator* iteryields = yields.createIterator();
RooRealVar* varyields = (RooRealVar*) iteryields->Next();//only inherits things from TObject unless class specified
vector<double> Y, E;//holds yields and associated errors
vector<TString> YS, ES;//holds strings of the corresponding yields
int j=0;//count vector position
int jS=0, jL=0;//these hold the position of the S and L results;initialized in case there is no nsigS or nsigL
while(varyields){//loop over yields
TString varname = varyields->GetName();
TString vartitle = varyields->GetTitle();
double varval = varyields->getVal();
Y.push_back(varval);
double lo = varyields->getErrorLo();
double hi = varyields->getErrorHi();
E.push_back(TMath::Max(fabs(lo),hi));
YS.push_back(Form("%f",Y[j]));
ES.push_back(Form("%f",E[j]));
if(varname=="nsigS") jS=j;
if(varname=="nsigL") jL=j;
outputtext = vartitle+" = "+YS[j]+" +/- "+ES[j];
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
varyields = (RooRealVar*) iteryields->Next();
j++;
}
//S/L
double result = Y[jS]/Y[jL];
cout<<"result declared"<<endl;
double E_result = TMath::Abs(result)*sqrt(pow(E[jS]/Y[jS],2)+pow(E[jL]/Y[jL],2));
cout<<"E_result declared"<<endl;
TString resultstring = Form("%E",result);
TString E_resultstring = Form("%E",E_result);
outputtext = "Y_{#Sigma^{0}}/Y_{#Lambda} = "+resultstring+" +/- "+E_resultstring;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
double resultlimit = (Y[jS]+E[jS])/(Y[jL]-E[jL]);
outputtext = Form("%E",resultlimit);
outputtext = "limit = "+outputtext;
cout<<outputtext<<endl;
textfile<<outputtext<<endl;
//txt->AddText(outputtext);
// Create canvas and pads, set style
TCanvas *c1 = new TCanvas("c1","data fits",1200,800);
TPad *pad1 = new TPad("pad1","pad1",0.0,0.3,1.0,1.0);
TPad *pad2 = new TPad("pad2","pad2",0.0,0.0,1.0,0.3);
pad1->SetBottomMargin(0);
pad2->SetTopMargin(0);
pad2->SetBottomMargin(0.5);
pad2->SetBorderMode(0);
pad1->SetBorderMode(0);
c1->SetBorderMode(0);
pad2->Draw();
pad1->Draw();
pad1->cd();
framex->SetMinimum(1);
framex->SetMaximum(3000);
framex->addObject(leg);//add legend to frame
//framex->addObject(txt);//add text to frame
gPad->SetTopMargin(0.06);
pad1->SetLogy();
// pad1->Range(4100,0,6100,0.0005);
pad1->Update();
framex->Draw();
// Pull distribution
RooPlot *framex2 = mass->frame();
RooHist* hpull = framex->pullHist("Hist","curvetot");
framex2->addPlotable(hpull,"P");
hpull->SetLineColor(kBlack);
hpull->SetMarkerColor(kBlack);
framex2->SetTitle(0);
framex2->GetYaxis()->SetTitle("Pull");
framex2->GetYaxis()->SetTitleSize(0.15);
framex2->GetYaxis()->SetLabelSize(0.15);
framex2->GetXaxis()->SetTitleSize(0.2);
framex2->GetXaxis()->SetLabelSize(0.15);
framex2->GetYaxis()->CenterTitle();
framex2->GetYaxis()->SetTitleOffset(0.45);
framex2->GetXaxis()->SetTitleOffset(1.1);
framex2->GetYaxis()->SetNdivisions(505);
framex2->GetYaxis()->SetRangeUser(-8.8,8.8);
pad2->cd();
framex2->Draw();
c1->cd();
placeholder = "plots/fit"+fileN+".eps";
c1->Print(placeholder);
placeholder = "plots/fit"+fileN+".C";
c1->SaveAs(placeholder);
textfile.close();
}
// The actual job
void backgroundFits_ggzz_1Dw(int channel, int sqrts, int VBFtag)
{
TString schannel;
if (channel == 1) schannel = "4mu";
else if (channel == 2) schannel = "4e";
else if (channel == 3) schannel = "2e2mu";
else cout << "Not a valid channel: " << schannel << endl;
TString ssqrts = (long) sqrts + TString("TeV");
cout << "schannel = " << schannel << " sqrts = " << sqrts << " VBFtag = "<< VBFtag << endl;
TString outfile;
outfile = "CardFragments/ggzzBackgroundFit_" + ssqrts + "_" + schannel + "_" + Form("%d",int(VBFtag)) + ".txt";
ofstream of(outfile,ios_base::out);
gSystem->AddIncludePath("-I$ROOFITSYS/include");
gROOT->ProcessLine(".L ../CreateDatacards/include/tdrstyle.cc");
setTDRStyle(false);
gStyle->SetPadLeftMargin(0.16);
TString filepath;filepath.Form("AAAOK/ZZ%s/ZZ4lAnalysis.root",schannel.Data());
TFile *f = TFile::Open(filepath);
TTree *tree = f->Get("ZZTree/candTree");
RooRealVar* MC_weight = new RooRealVar("MC_weight","MC_weight",0.,2.) ;
RooRealVar* ZZMass = new RooRealVar("ZZMass","ZZMass",100,100.,1000.);
RooRealVar* NJets30 = new RooRealVar("NJets30","NJets30",0.,5.);
RooArgSet ntupleVarSet(*ZZMass,*NJets30,*MC_weight);
RooDataSet *set = new RooDataSet("set","set",ntupleVarSet,WeightVar("MC_weight"));
//RooArgSet ntupleVarSet(*ZZMass,*NJets30);
//RooDataSet *set = new RooDataSet("set","set",ntupleVarSet);
Float_t myMC,myMass;
Int_t myNJets;
int nentries = tree->GetEntries();
Float_t myPt,myJetPt,myJetEta,myJetPhi,myJetMass,myFisher;
Int_t myExtralep,myBJets;
tree->SetBranchAddress("ZZMass",&myMass);
tree->SetBranchAddress("genHEPMCweight",&myMC);
tree->SetBranchAddress("nCleanedJetsPt30",&myNJets);
tree->SetBranchAddress("ZZPt",&myPt);
tree->SetBranchAddress("nExtraLep",&myExtralep);
tree->SetBranchAddress("nCleanedJetsPt30BTagged",&myBJets);
tree->SetBranchAddress("DiJetDEta",&myFisher);
for(int i =0;i<nentries;i++) {
tree->GetEntry(i);
if(myMass<100.)continue;
int cat = category(myExtralep,myPt, myMass,myNJets, myBJets,/* jetpt, jeteta, jetphi, jetmass,*/myFisher);
if(VBFtag != cat )continue;
ntupleVarSet.setRealValue("ZZMass",myMass);
ntupleVarSet.setRealValue("MC_weight",myMC);
ntupleVarSet.setRealValue("NJets30",(double)cat);
set->add(ntupleVarSet, myMC);
}
//RooRealVar* ZZLD = new RooRealVar("ZZLD","ZZLD",0.,1.);
//char cut[10];
//sprintf(cut,"ZZLD>0.5");
//RooDataSet* set = new RooDataSet("set","set",tree,RooArgSet(*ZZMass,*MC_weight,*ZZLD),cut,"MC_weight");
double totalweight = 0.;
for (int i=0 ; i<set->numEntries() ; i++) {
set->get(i) ;
totalweight += set->weight();
//cout << CMS_zz4l_mass->getVal() << " = " << set->weight() << endl ;
}
cout << "nEntries: " << set->numEntries() << ", totalweight: " << totalweight << endl;
gSystem->Load("libHiggsAnalysisCombinedLimit.so");
//// ---------------------------------------
//Background
RooRealVar CMS_qqzzbkg_a0("CMS_qqzzbkg_a0","CMS_qqzzbkg_a0",115.3,0.,200.);
RooRealVar CMS_qqzzbkg_a1("CMS_qqzzbkg_a1","CMS_qqzzbkg_a1",21.96,0.,200.);
RooRealVar CMS_qqzzbkg_a2("CMS_qqzzbkg_a2","CMS_qqzzbkg_a2",122.8,0.,200.);
RooRealVar CMS_qqzzbkg_a3("CMS_qqzzbkg_a3","CMS_qqzzbkg_a3",0.03479,0.,1.);
RooRealVar CMS_qqzzbkg_a4("CMS_qqzzbkg_a4","CMS_qqzzbkg_a4",185.5,0.,200.);
RooRealVar CMS_qqzzbkg_a5("CMS_qqzzbkg_a5","CMS_qqzzbkg_a5",12.67,0.,200.);
RooRealVar CMS_qqzzbkg_a6("CMS_qqzzbkg_a6","CMS_qqzzbkg_a6",34.81,0.,100.);
RooRealVar CMS_qqzzbkg_a7("CMS_qqzzbkg_a7","CMS_qqzzbkg_a7",0.1393,0.,1.);
RooRealVar CMS_qqzzbkg_a8("CMS_qqzzbkg_a8","CMS_qqzzbkg_a8",66.,0.,200.);
RooRealVar CMS_qqzzbkg_a9("CMS_qqzzbkg_a9","CMS_qqzzbkg_a9",0.07191,0.,1.);
RooggZZPdf_v2* bkg_ggzz = new RooggZZPdf_v2("bkg_ggzz","bkg_ggzz",*ZZMass,
CMS_qqzzbkg_a0,CMS_qqzzbkg_a1,CMS_qqzzbkg_a2,CMS_qqzzbkg_a3,CMS_qqzzbkg_a4,
CMS_qqzzbkg_a5,CMS_qqzzbkg_a6,CMS_qqzzbkg_a7,CMS_qqzzbkg_a8,CMS_qqzzbkg_a9);
//// ---------------------------------------
RooFitResult *r1 = bkg_ggzz->fitTo( *set, Save(kTRUE), SumW2Error(kTRUE) );//, Save(kTRUE), SumW2Error(kTRUE)) ;
cout << endl;
cout << "------- Parameters for " << schannel << " sqrts=" << sqrts << endl;
cout << " a0_bkgd = " << CMS_qqzzbkg_a0.getVal() << endl;
cout << " a1_bkgd = " << CMS_qqzzbkg_a1.getVal() << endl;
cout << " a2_bkgd = " << CMS_qqzzbkg_a2.getVal() << endl;
cout << " a3_bkgd = " << CMS_qqzzbkg_a3.getVal() << endl;
cout << " a4_bkgd = " << CMS_qqzzbkg_a4.getVal() << endl;
cout << " a5_bkgd = " << CMS_qqzzbkg_a5.getVal() << endl;
cout << " a6_bkgd = " << CMS_qqzzbkg_a6.getVal() << endl;
cout << " a7_bkgd = " << CMS_qqzzbkg_a7.getVal() << endl;
cout << " a8_bkgd = " << CMS_qqzzbkg_a8.getVal() << endl;
cout << " a9_bkgd = " << CMS_qqzzbkg_a9.getVal() << endl;
cout << "---------------------------" << endl << endl;
of << "ggZZshape a0_bkgd " << CMS_qqzzbkg_a0.getVal() << endl;
of << "ggZZshape a1_bkgd " << CMS_qqzzbkg_a1.getVal() << endl;
of << "ggZZshape a2_bkgd " << CMS_qqzzbkg_a2.getVal() << endl;
of << "ggZZshape a3_bkgd " << CMS_qqzzbkg_a3.getVal() << endl;
of << "ggZZshape a4_bkgd " << CMS_qqzzbkg_a4.getVal() << endl;
of << "ggZZshape a5_bkgd " << CMS_qqzzbkg_a5.getVal() << endl;
of << "ggZZshape a6_bkgd " << CMS_qqzzbkg_a6.getVal() << endl;
of << "ggZZshape a7_bkgd " << CMS_qqzzbkg_a7.getVal() << endl;
of << "ggZZshape a8_bkgd " << CMS_qqzzbkg_a8.getVal() << endl;
of << "ggZZshape a9_bkgd " << CMS_qqzzbkg_a9.getVal() << endl;
of << endl;
of.close();
cout << endl << "Output written to: " << outfile << endl;
int iLineColor = 1;
string lab = "blah";
if (channel == 1) { iLineColor = 2; lab = "4#mu"; }
if (channel == 3) { iLineColor = 4; lab = "2e2#mu"; }
if (channel == 2) { iLineColor = 6; lab = "4e"; }
char lname[192];
sprintf(lname,"gg #rightarrow ZZ #rightarrow %s", lab.c_str() );
char lname2[192];
sprintf(lname2,"Shape Model, %s", lab.c_str() );
// dummy!
TF1* dummyF = new TF1("dummyF","1",0.,1.);
TH1F* dummyH = new TH1F("dummyH","",1, 0.,1.);
dummyF->SetLineColor( iLineColor );
dummyF->SetLineWidth( 2 );
TLegend * box2 = new TLegend(0.5,0.70,0.90,0.90);
box2->SetFillColor(0);
box2->SetBorderSize(0);
box2->AddEntry(dummyH,"Simulation (GG2ZZ) ","pe");
box2->AddEntry(dummyH,lname,"");
box2->AddEntry(dummyH,"","");
box2->AddEntry(dummyF,lname2,"l");
TPaveText *pt = new TPaveText(0.15,0.955,0.4,0.99,"NDC");
pt->SetFillColor(0);
pt->SetBorderSize(0);
pt->AddText("CMS Preliminary 2012");
TPaveText *pt2 = new TPaveText(0.84,0.955,0.99,0.99,"NDC");
pt2->SetFillColor(0);
pt2->SetBorderSize(0);
// Plot m4l and
RooPlot* frameM4l = ZZMass->frame(Title("M4L"),Bins(200)) ;
set->plotOn(frameM4l, MarkerStyle(24)) ;
bkg_ggzz->plotOn(frameM4l,LineColor(iLineColor)) ;
set->plotOn(frameM4l) ;
//comaprison with different shape, if needed (uncommenting also the code above)
//bkg_ggzz_bkgd->plotOn(frameM4l,LineColor(1),NormRange("largerange")) ;
frameM4l->GetXaxis()->SetTitle("m_{4l} [GeV]");
frameM4l->GetYaxis()->SetTitle("a.u.");
//frameM4l->GetYaxis()->SetRangeUser(0,0.03);
//if(channel == 3)frameM4l->GetYaxis()->SetRangeUser(0,0.05);
//if(VBFtag<2){
// if(channel == 3)frameM4l->GetYaxis()->SetRangeUser(0,0.01);
// else frameM4l->GetYaxis()->SetRangeUser(0,0.005);
//}
frameM4l->GetXaxis()->SetRangeUser(100,1000);
TCanvas *c = new TCanvas("c","c",800,600);
c->cd();
frameM4l->Draw();
box2->Draw();
pt->Draw();
pt2->Draw();
TString outputPath = "bkgFigs";
outputPath = outputPath+ (long) sqrts + "TeV/";
TString outputName;
outputName = outputPath + "bkgggzz_" + schannel + "_" + Form("%d",int(VBFtag));
c->SaveAs(outputName + ".eps");
c->SaveAs(outputName + ".png");
c->SaveAs(outputName + ".root");
delete c;
frameM4l->GetXaxis()->SetRangeUser(100,200);
TCanvas *c = new TCanvas("c","c",800,600);
c->cd();
frameM4l->Draw();
box2->Draw();
pt->Draw();
pt2->Draw();
TString outputPath = "bkgFigs";
outputPath = outputPath+ (long) sqrts + "TeV/";
TString outputName;
outputName = outputPath + "bkgggzz_lowZoom_" + schannel + "_" + Form("%d",int(VBFtag));
c->SaveAs(outputName + ".eps");
c->SaveAs(outputName + ".png");
c->SaveAs(outputName + ".root");
delete c;
}
exampleScript()
{
gSystem->CompileMacro("betaHelperFunctions.h" ,"kO") ;
gSystem->CompileMacro("RooNormalFromFlatPdf.cxx" ,"kO") ;
gSystem->CompileMacro("RooBetaInverseCDF.cxx" ,"kO") ;
gSystem->CompileMacro("RooBetaPrimeInverseCDF.cxx" ,"kO") ;
gSystem->CompileMacro("RooCorrelatedBetaGeneratorHelper.cxx" ,"kO") ;
gSystem->CompileMacro("RooCorrelatedBetaPrimeGeneratorHelper.cxx" ,"kO") ;
gSystem->CompileMacro("rooFitBetaHelperFunctions.h","kO") ;
TFile betaTest("betaTest.root","RECREATE");
betaTest.cd();
RooWorkspace workspace("workspace");
TString correlatedName("testVariable");
TString observables("observables");
TString nuisances("nuisances");
RooAbsArg* betaOne = getCorrelatedBetaConstraint(workspace,"betaOne","",
0.5 , 0.1 ,
observables, nuisances,
correlatedName );
printf("\n\n *** constraint name is %s from betaOne and %s\n\n", betaOne->GetName(), correlatedName.Data() ) ;
RooAbsArg* betaTwo = getCorrelatedBetaConstraint(workspace,"betaTwo","",
0 , 0 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaThree = getCorrelatedBetaConstraint(workspace,"betaThree","",
0.2 , 0.01 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaFour = getCorrelatedBetaConstraint(workspace,"betaFour","",
0.7 , 0.1 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaFourC = getCorrelatedBetaConstraint(workspace,"betaFourC","",
0.7 , 0.1 ,
observables, nuisances,
correlatedName, kTRUE );
RooAbsArg* betaPrimeOne = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeOne","",
1.0 , 0.5 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeOneC = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeOneC","",
1.0 , 0.5 ,
observables, nuisances,
correlatedName, kTRUE );
RooAbsArg* betaPrimeTwo = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeTwo","",
0.7 , 0.5 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeThree = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeThree","",
0.1 , 0.05 ,
observables, nuisances,
correlatedName );
RooAbsArg* betaPrimeFour = getCorrelatedBetaPrimeConstraint(workspace,"betaPrimeFour","",
7 , 1 ,
observables, nuisances,
correlatedName );
RooRealVar* correlatedParameter = workspace.var(correlatedName);
RooAbsPdf* normalFromFlat = workspace.pdf(correlatedName+"_Constraint");
RooDataSet* data = normalFromFlat->generate(RooArgSet(*correlatedParameter),1e5);
data->addColumn(*normalFromFlat);
data->addColumn(*betaOne);
data->addColumn(*betaTwo);
data->addColumn(*betaThree);
data->addColumn(*betaFour);
data->addColumn(*betaFourC);
data->addColumn(*betaPrimeOne);
data->addColumn(*betaPrimeTwo);
data->addColumn(*betaPrimeThree);
data->addColumn(*betaPrimeFour);
data->addColumn(*betaPrimeOneC);
data->Print("v");
workspace.Print() ;
//Setup Plotting Kluges:
RooRealVar normalPlotter (correlatedName+"_Constraint" , correlatedName+"_Constraint" ,0,1);
RooPlot* normalPlot = normalPlotter.frame();
data->plotOn(normalPlot);
RooRealVar betaOnePlotter ("betaOne_BetaInverseCDF" ,"betaOne_BetaInverseCDF" ,0,1);
RooRealVar betaTwoPlotter ("betaTwo_BetaInverseCDF" ,"betaTwo_BetaInverseCDF" ,0,1);
RooRealVar betaThreePlotter("betaThree_BetaInverseCDF","betaThree_BetaInverseCDF",0,1);
RooRealVar betaFourPlotter ("betaFour_BetaInverseCDF" ,"betaFour_BetaInverseCDF" ,0,1);
RooRealVar betaFourCPlotter ("betaFourC_BetaInverseCDF" ,"betaFourC_BetaInverseCDF" ,0,1);
RooRealVar betaPrimeOnePlotter ("betaPrimeOne_BetaPrimeInverseCDF" ,"betaPrimeOne_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeOneCPlotter ("betaPrimeOneC_BetaPrimeInverseCDF" ,"betaPrimeOneC_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeTwoPlotter ("betaPrimeTwo_BetaPrimeInverseCDF" ,"betaPrimeTwo_BetaPrimeInverseCDF" ,0,4);
RooRealVar betaPrimeThreePlotter("betaPrimeThree_BetaPrimeInverseCDF","betaPrimeThree_BetaPrimeInverseCDF",0,0.3);
RooRealVar betaPrimeFourPlotter ("betaPrimeFour_BetaPrimeInverseCDF" ,"betaPrimeFour_BetaPrimeInverseCDF" ,4,12);
RooPlot* betaOnePlot = betaOnePlotter .frame();
RooPlot* betaTwoPlot = betaTwoPlotter .frame();
RooPlot* betaThreePlot = betaThreePlotter.frame();
RooPlot* betaFourPlot = betaFourPlotter .frame();
RooPlot* betaFourCPlot = betaFourCPlotter .frame();
data->plotOn(betaOnePlot );
data->plotOn(betaTwoPlot );
data->plotOn(betaThreePlot);
data->plotOn(betaFourPlot );
data->plotOn(betaFourCPlot );
RooPlot* betaPrimeOnePlot = betaPrimeOnePlotter .frame();
RooPlot* betaPrimeOneCPlot = betaPrimeOneCPlotter .frame();
RooPlot* betaPrimeTwoPlot = betaPrimeTwoPlotter .frame();
RooPlot* betaPrimeThreePlot = betaPrimeThreePlotter.frame();
RooPlot* betaPrimeFourPlot = betaPrimeFourPlotter .frame();
data->plotOn(betaPrimeOnePlot );
data->plotOn(betaPrimeOneCPlot );
data->plotOn(betaPrimeTwoPlot );
data->plotOn(betaPrimeThreePlot);
data->plotOn(betaPrimeFourPlot );
TCanvas* underlyingVariable = new TCanvas("underlyingVariable","underlyingVariable",800,800);
underlyingVariable->Divide(2,2);
underlyingVariable->cd(1);
RooPlot* underlyingPlot = correlatedParameter->frame();
data->plotOn(underlyingPlot);
underlyingPlot->Draw();
underlyingVariable->cd(2);
normalPlot->Draw();
underlyingVariable->cd(3);
TH2F* underlying = data->createHistogram(*correlatedParameter,normalPlotter,50,50);
underlying->Draw("col");
TH2F* legoUnderlying = (TH2F*)underlying->Clone();
underlyingVariable->cd(4);
legoUnderlying->Draw("lego");
underlyingVariable->SaveAs("underlyingVariable.pdf");
TCanvas* betaCanvas = new TCanvas("betaCanvas","betaCanvas",800,800);
betaCanvas->Divide(3,2);
betaCanvas->cd(1);
betaOnePlot->Draw();
betaCanvas->cd(2);
betaTwoPlot->Draw();
betaCanvas->cd(3);
betaThreePlot->Draw();
betaCanvas->cd(4);
betaFourPlot->Draw();
betaCanvas->cd(5);
betaFourCPlot->Draw();
betaCanvas->SaveAs("betaVariables.pdf");
TCanvas* betaPrimeCanvas = new TCanvas("betaPrimeCanvas","betaPrimeCanvas",1200,800);
betaPrimeCanvas->Divide(3,2);
betaPrimeCanvas->cd(1);
betaPrimeOnePlot->Draw();
betaPrimeCanvas->cd(2);
betaPrimeTwoPlot->Draw();
betaPrimeCanvas->cd(3);
betaPrimeThreePlot->Draw();
betaPrimeCanvas->cd(4);
betaPrimeFourPlot->Draw();
betaPrimeCanvas->cd(5);
betaPrimeOneCPlot->Draw();
betaPrimeCanvas->SaveAs("betaPrimeVariables.pdf");
TCanvas* betaCorrelationsCanvas = new TCanvas("betaCorrelationsCanvas","betaCorrelationsCanvas",1600,800);
betaCorrelationsCanvas->Divide(4,2);
TH2F* oneTwo = data->createHistogram(betaOnePlotter,betaTwoPlotter,30,30);
TH2F* oneThree = data->createHistogram(betaOnePlotter,betaThreePlotter,30,30);
TH2F* oneFour = data->createHistogram(betaOnePlotter,betaFourPlotter,30,30);
TH2F* twoThree = data->createHistogram(betaTwoPlotter,betaThreePlotter,30,30);
TH2F* twoFour = data->createHistogram(betaTwoPlotter,betaFourPlotter,30,30);
TH2F* threeFour = data->createHistogram(betaThreePlotter,betaFourPlotter,30,30);
TH2F* twoFourC = data->createHistogram(betaTwoPlotter,betaFourCPlotter,30,30);
TH2F* fourFourC = data->createHistogram(betaFourPlotter,betaFourCPlotter,30,30);
betaCorrelationsCanvas->cd(1);
oneTwo->DrawCopy("lego");
betaCorrelationsCanvas->cd(2);
oneThree->DrawCopy("lego");
betaCorrelationsCanvas->cd(3);
oneFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(4);
twoThree->DrawCopy("lego");
betaCorrelationsCanvas->cd(5);
twoFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(6);
threeFour->DrawCopy("lego");
betaCorrelationsCanvas->cd(7);
twoFourC->DrawCopy("lego");
betaCorrelationsCanvas->cd(8);
fourFourC->DrawCopy("lego");
betaCorrelationsCanvas->SaveAs("betaCorrelations.pdf");
TCanvas* betaPrimeCorrelationsCanvas = new TCanvas("betaPrimeCorrelationsCanvas","betaPrimeCorrelationsCanvas",1600,800);
betaPrimeCorrelationsCanvas->Divide(4,2);
TH2F* oneTwo = data->createHistogram(betaPrimeOnePlotter,betaPrimeTwoPlotter,30,30);
TH2F* oneThree = data->createHistogram(betaPrimeOnePlotter,betaPrimeThreePlotter,30,30);
TH2F* oneFour = data->createHistogram(betaPrimeOnePlotter,betaPrimeFourPlotter,30,30);
TH2F* twoThree = data->createHistogram(betaPrimeTwoPlotter,betaPrimeThreePlotter,30,30);
TH2F* twoFour = data->createHistogram(betaPrimeTwoPlotter,betaPrimeFourPlotter,30,30);
TH2F* threeFour = data->createHistogram(betaPrimeThreePlotter,betaPrimeFourPlotter,30,30);
TH2F* oneOneC = data->createHistogram(betaPrimeOnePlotter,betaPrimeOneCPlotter,30,30);
betaPrimeCorrelationsCanvas->cd(1);
oneTwo->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(2);
oneThree->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(3);
oneFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(4);
twoThree->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(5);
twoFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(6);
threeFour->DrawCopy("lego");
betaPrimeCorrelationsCanvas->cd(7);
oneOneC->DrawCopy("lego");
betaPrimeCorrelationsCanvas->SaveAs("betaPrimeCorrelations.pdf");
RooProdPdf totalPdf("totalPdf","totalPdf",workspace.allPdfs());
totalPdf.Print("v");
RooArgSet* observableSet = workspace.set("observables");
observableSet->Print();
RooDataSet* allDataOne = totalPdf.generate(*observableSet,1);
allDataOne->Print("v");
correlatedParameter->setVal(0.25);
RooDataSet* allDataTwo = totalPdf.generate(*observableSet,1);
allDataTwo->Print("v");
correlatedParameter->setVal(0.75);
RooDataSet* allDataThree = totalPdf.generate(*observableSet,1);
allDataThree->Print("v");
//Testing for extreme values!
for(int i = 0; i< 101; i++)
{
correlatedParameter->setVal((double)i/100.);
cout << "Correlation parameter has value of " << correlatedParameter->getVal();
cout << " and the pdf has an unnormalized value of " << normalFromFlat->getVal() << endl;
}
}
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;
}
void rf208_convolution()
{
// S e t u p c o m p o n e n t p d f s
// ---------------------------------------
// Construct observable
RooRealVar t("t","t",-10,30) ;
// Construct landau(t,ml,sl) ;
RooRealVar ml("ml","mean bw",5.,-20,20) ;
RooRealVar sl("sl","sigma bw",1,0.1,10) ;
RooBreitWigner bw("bw","bw",t,ml,sl) ;
// Construct gauss(t,mg,sg)
RooRealVar mg("mg","mg",0) ;
RooRealVar sg("sg","sg",2,0.1,10) ;
RooGaussian gauss("gauss","gauss",t,mg,sg) ;
// C o n s t r u c t c o n v o l u t i o n p d f
// ---------------------------------------
// Set #bins to be used for FFT sampling to 10000
t.setBins(10000,"cache") ;
// Construct landau (x) gauss
RooFFTConvPdf lxg("lxg","bw (X) gauss",t,bw,gauss) ;
// S a m p l e , f i t a n d p l o t c o n v o l u t e d p d f
// ----------------------------------------------------------------------
// Sample 1000 events in x from gxlx
RooDataSet* data = lxg.generate(t,10000) ;
// Fit gxlx to data
lxg.fitTo(*data) ;
// Plot data, landau pdf, landau (X) gauss pdf
RooPlot* frame = t.frame(Title("landau (x) gauss convolution")) ;
data->plotOn(frame) ;
lxg.plotOn(frame) ;
bw.plotOn(frame,LineStyle(kDashed)) ;
// Draw frame on canvas
new TCanvas("rf208_convolution","rf208_convolution",600,600) ;
gPad->SetLeftMargin(0.15) ; frame->GetYaxis()->SetTitleOffset(1.4) ; frame->Draw() ;
//add a variable to the dataset
RooFormulaVar *r_formula = new RooFormulaVar("r_formula","","@0",t);
RooRealVar* r = (RooRealVar*) data->addColumn(*r_formula);
r->SetName("r");
r->SetTitle("r");
RooDataSet* data_r =(RooDataSet*) data->reduce(*r, "");
r->setRange("sigrange",-10.,30.);
RooPlot* r_frame = r->frame(Range("sigRange"),Title(" r (x) gauss convolution")) ;
data_r->plotOn(r_frame, MarkerColor(kRed));
r_frame->GetXaxis()->SetRangeUser(-10., 30.);
r_frame->Draw() ;
}
vector<Double_t*> simFit(bool makeSoupFit_ = false,
const string tnp_ = "etoTauMargLooseNoCracks70",
const string category_ = "tauAntiEMVA",
const string bin_ = "abseta<1.5",
const float binCenter_ = 0.75,
const float binWidth_ = 0.75,
const float xLow_=60,
const float xHigh_=120,
bool SumW2_ = false,
bool verbose_ = true){
vector<Double_t*> out;
//return out;
//TFile *test = new TFile( outFile->GetName(),"UPDATE");
// output file
TFile *test = new TFile( Form("EtoTauPlotsFit_%s_%s_%f.root",tnp_.c_str(),category_.c_str(),binCenter_),"RECREATE");
test->mkdir(Form("bin%f",binCenter_));
TCanvas *c = new TCanvas("fitCanvas",Form("fitCanvas_%s_%s",tnp_.c_str(),bin_.c_str()),10,30,650,600);
c->SetGrid(0,0);
c->SetFillStyle(4000);
c->SetFillColor(10);
c->SetTicky();
c->SetObjectStat(0);
TCanvas *c2 = new TCanvas("fitCanvasTemplate",Form("fitCanvasTemplate_%s_%s",tnp_.c_str(),bin_.c_str()),10,30,650,600);
c2->SetGrid(0,0);
c2->SetFillStyle(4000);
c2->SetFillColor(10);
c2->SetTicky();
c2->SetObjectStat(0);
// input files
TFile fsup("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup.root");
TFile fbkg("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup_bkg.root");
TFile fsgn("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_soup_sgn.root");
TFile fdat("/data_CMS/cms/lbianchini/tagAndProbe/trees/38XWcut/testNewWriteFromPAT_Data.root");
// data from 2iter:
//TFile fdat("/data_CMS/cms/lbianchini/35pb/testNewWriteFromPAT_Data.root");
//********************** signal only tree *************************/
TTree *fullTreeSgn = (TTree*)fsgn.Get((tnp_+"/fitter_tree").c_str());
TH1F* hSall = new TH1F("hSall","",1,0,150);
TH1F* hSPall = new TH1F("hSPall","",1,0,150);
TH1F* hS = new TH1F("hS","",1,0,150);
TH1F* hSP = new TH1F("hSP","",1,0,150);
fullTreeSgn->Draw("mass>>hS",Form("weight*(%s && mass>%f && mass<%f && mcTrue && signalPFChargedHadrCands<1.5)",bin_.c_str(),xLow_,xHigh_));
fullTreeSgn->Draw("mass>>hSall",Form("weight*(%s && mass>%f && mass<%f)",bin_.c_str(),xLow_,xHigh_));
float SGNtrue = hS->Integral();
float SGNall = hSall->Integral();
fullTreeSgn->Draw("mass>>hSP",Form("weight*(%s && %s>0 && mass>%f && mass<%f && mcTrue && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
fullTreeSgn->Draw("mass>>hSPall",Form("weight*(%s && %s>0 && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
float SGNtruePass = hSP->Integral();
float SGNallPass = hSPall->Integral();
//********************** background only tree *************************//
TTree *fullTreeBkg = (TTree*)fbkg.Get((tnp_+"/fitter_tree").c_str());
TH1F* hB = new TH1F("hB","",1,0,150);
TH1F* hBP = new TH1F("hBP","",1,0,150);
fullTreeBkg->Draw("mass>>hB",Form("weight*(%s && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),xLow_,xHigh_));
float BKG = hB->Integral();
float BKGUnWeighted = hB->GetEntries();
fullTreeBkg->Draw("mass>>hBP",Form("weight*(%s && %s>0 && mass>%f && mass<%f && signalPFChargedHadrCands<1.5 )",bin_.c_str(),category_.c_str(),xLow_,xHigh_));
float BKGPass = hBP->Integral();
float BKGUnWeightedPass = hBP->GetEntries();
float BKGFail = BKG-BKGPass;
cout << "*********** BKGFail " << BKGFail << endl;
//********************** soup tree *************************//
TTree *fullTreeSoup = (TTree*)fsup.Get((tnp_+"/fitter_tree").c_str());
//********************** data tree *************************//
TTree *fullTreeData = (TTree*)fdat.Get((tnp_+"/fitter_tree").c_str());
//********************** workspace ***********************//
RooWorkspace *w = new RooWorkspace("w","w");
// tree variables to be imported
w->factory("mass[30,120]");
w->factory("weight[0,10000]");
w->factory("abseta[0,2.5]");
w->factory("pt[0,200]");
w->factory("mcTrue[0,1]");
w->factory("signalPFChargedHadrCands[0,10]");
w->factory((category_+"[0,1]").c_str());
// background pass pdf for MC
w->factory("RooExponential::McBackgroundPdfP(mass,McCP[0,-10,10])");
// background fail pdf for MC
w->factory("RooExponential::McBackgroundPdfF(mass,McCF[0,-10,10])");
// background pass pdf for Data
w->factory("RooExponential::DataBackgroundPdfP(mass,DataCP[0,-10,10])");
// background fail pdf for Data
w->factory("RooExponential::DataBackgroundPdfF(mass,DataCF[0,-10,10])");
// fit parameters for background
w->factory("McEfficiency[0.04,0,1]");
w->factory("McNumSgn[0,1000000]");
w->factory("McNumBkgP[0,100000]");
w->factory("McNumBkgF[0,100000]");
w->factory("expr::McNumSgnP('McEfficiency*McNumSgn',McEfficiency,McNumSgn)");
w->factory("expr::McNumSgnF('(1-McEfficiency)*McNumSgn',McEfficiency,McNumSgn)");
w->factory("McPassing[pass=1,fail=0]");
// fit parameters for data
w->factory("DataEfficiency[0.1,0,1]");
w->factory("DataNumSgn[0,1000000]");
w->factory("DataNumBkgP[0,1000000]");
w->factory("DataNumBkgF[0,10000]");
w->factory("expr::DataNumSgnP('DataEfficiency*DataNumSgn',DataEfficiency,DataNumSgn)");
w->factory("expr::DataNumSgnF('(1-DataEfficiency)*DataNumSgn',DataEfficiency,DataNumSgn)");
w->factory("DataPassing[pass=1,fail=0]");
RooRealVar *weight = w->var("weight");
RooRealVar *abseta = w->var("abseta");
RooRealVar *pt = w->var("pt");
RooRealVar *mass = w->var("mass");
mass->setRange(xLow_,xHigh_);
RooRealVar *mcTrue = w->var("mcTrue");
RooRealVar *cut = w->var( category_.c_str() );
RooRealVar *signalPFChargedHadrCands = w->var("signalPFChargedHadrCands");
// build the template for the signal pass sample:
RooDataSet templateP("templateP","dataset for signal-pass template", RooArgSet(*mass,*weight,*abseta,*pt,*cut,*mcTrue,*signalPFChargedHadrCands), Import( *fullTreeSgn ), /*WeightVar( *weight ),*/ Cut( Form("(mcTrue && %s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()) ) );
// build the template for the signal fail sample:
RooDataSet templateF("templateF","dataset for signal-fail template", RooArgSet(*mass,*weight,*abseta,*pt,*cut,*mcTrue,*signalPFChargedHadrCands), Import( *fullTreeSgn ), /*WeightVar( *weight ),*/ Cut( Form("(mcTrue && %s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()) ) );
mass->setBins(24);
RooDataHist templateHistP("templateHistP","",RooArgSet(*mass), templateP, 1.0);
RooHistPdf TemplateSignalPdfP("TemplateSignalPdfP","",RooArgSet(*mass),templateHistP);
w->import(TemplateSignalPdfP);
mass->setBins(24);
RooDataHist templateHistF("templateHistF","",RooArgSet(*mass),templateF,1.0);
RooHistPdf TemplateSignalPdfF("TemplateSignalPdfF","",RooArgSet(*mass),templateHistF);
w->import(TemplateSignalPdfF);
mass->setBins(10000,"fft");
RooPlot* TemplateFrameP = mass->frame(Bins(24),Title("Template passing"));
templateP.plotOn(TemplateFrameP);
w->pdf("TemplateSignalPdfP")->plotOn(TemplateFrameP);
RooPlot* TemplateFrameF = mass->frame(Bins(24),Title("Template failing"));
templateF.plotOn(TemplateFrameF);
w->pdf("TemplateSignalPdfF")->plotOn(TemplateFrameF);
//w->factory("RooFFTConvPdf::McSignalPdfP(mass,TemplateSignalPdfP,RooTruthModel::McResolModP(mass))");
//w->factory("RooFFTConvPdf::McSignalPdfF(mass,TemplateSignalPdfF,RooTruthModel::McResolModF(mass))");
// FOR GREGORY: PROBLEM WHEN TRY TO USE THE PURE TEMPLATE =>
RooHistPdf McSignalPdfP("McSignalPdfP","McSignalPdfP",RooArgSet(*mass),templateHistP);
RooHistPdf McSignalPdfF("McSignalPdfF","McSignalPdfF",RooArgSet(*mass),templateHistF);
w->import(McSignalPdfP);
w->import(McSignalPdfF);
// FOR GREGORY: FOR DATA, CONVOLUTION IS OK =>
w->factory("RooFFTConvPdf::DataSignalPdfP(mass,TemplateSignalPdfP,RooGaussian::DataResolModP(mass,DataMeanResP[0.0,-5.,5.],DataSigmaResP[0.5,0.,10]))");
w->factory("RooFFTConvPdf::DataSignalPdfF(mass,TemplateSignalPdfF,RooGaussian::DataResolModF(mass,DataMeanResF[-5.,-10.,10.],DataSigmaResF[0.5,0.,10]))");
//w->factory("RooCBShape::DataSignalPdfF(mass,DataMeanF[91.2,88,95.],DataSigmaF[3,0.5,8],DataAlfaF[1.8,0.,10],DataNF[1.0,1e-06,10])");
//w->factory("RooFFTConvPdf::DataSignalPdfF(mass,RooVoigtian::DataVoigF(mass,DataMeanF[85,80,95],DataWidthF[2.49],DataSigmaF[3,0.5,10]),RooCBShape::DataResolModF(mass,DataMeanResF[0.5,0.,10.],DataSigmaResF[0.5,0.,10],DataAlphaResF[0.5,0.,10],DataNResF[1.0,1e-06,10]))");
//w->factory("SUM::DataSignalPdfF(fVBP[0.5,0,1]*RooBifurGauss::bifF(mass,DataMeanResF[91.2,80,95],sigmaLF[10,0.5,40],sigmaRF[0.]), RooVoigtian::voigF(mass, DataMeanResF, widthF[2.49], sigmaVoigF[5,0.1,10]) )" );
// composite model pass for MC
w->factory("SUM::McModelP(McNumSgnP*McSignalPdfP,McNumBkgP*McBackgroundPdfP)");
w->factory("SUM::McModelF(McNumSgnF*McSignalPdfF,McNumBkgF*McBackgroundPdfF)");
// composite model pass for data
w->factory("SUM::DataModelP(DataNumSgnP*DataSignalPdfP,DataNumBkgP*DataBackgroundPdfP)");
w->factory("SUM::DataModelF(DataNumSgnF*DataSignalPdfF,DataNumBkgF*DataBackgroundPdfF)");
// simultaneous fir for MC
w->factory("SIMUL::McModel(McPassing,pass=McModelP,fail=McModelF)");
// simultaneous fir for data
w->factory("SIMUL::DataModel(DataPassing,pass=DataModelP,fail=DataModelF)");
w->Print("V");
w->saveSnapshot("clean", w->allVars());
w->loadSnapshot("clean");
/****************** sim fit to soup **************************/
///////////////////////////////////////////////////////////////
TFile *f = new TFile("dummySoup.root","RECREATE");
TTree* cutTreeSoupP = fullTreeSoup->CopyTree(Form("(%s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
TTree* cutTreeSoupF = fullTreeSoup->CopyTree(Form("(%s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
RooDataSet McDataP("McDataP","dataset pass for the soup", RooArgSet(*mass), Import( *cutTreeSoupP ) );
RooDataSet McDataF("McDataF","dataset fail for the soup", RooArgSet(*mass), Import( *cutTreeSoupF ) );
RooDataHist McCombData("McCombData","combined data for the soup", RooArgSet(*mass), Index(*(w->cat("McPassing"))), Import("pass", *(McDataP.createHistogram("histoP",*mass)) ), Import("fail",*(McDataF.createHistogram("histoF",*mass)) ) ) ;
RooPlot* McFrameP = 0;
RooPlot* McFrameF = 0;
RooRealVar* McEffFit = 0;
if(makeSoupFit_){
cout << "**************** N bins in mass " << w->var("mass")->getBins() << endl;
RooFitResult* ResMcCombinedFit = w->pdf("McModel")->fitTo(McCombData, Extended(1), Minos(1), Save(1), SumW2Error( SumW2_ ), Range(xLow_,xHigh_), NumCPU(4) /*, ExternalConstraints( *(w->pdf("ConstrainMcNumBkgF")) )*/ );
test->cd(Form("bin%f",binCenter_));
ResMcCombinedFit->Write("McFitResults_Combined");
RooArgSet McFitParam(ResMcCombinedFit->floatParsFinal());
McEffFit = (RooRealVar*)(&McFitParam["McEfficiency"]);
RooRealVar* McNumSigFit = (RooRealVar*)(&McFitParam["McNumSgn"]);
RooRealVar* McNumBkgPFit = (RooRealVar*)(&McFitParam["McNumBkgP"]);
RooRealVar* McNumBkgFFit = (RooRealVar*)(&McFitParam["McNumBkgF"]);
McFrameP = mass->frame(Bins(24),Title("MC: passing sample"));
McCombData.plotOn(McFrameP,Cut("McPassing==McPassing::pass"));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McSignalPdfP"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameP,Slice(*(w->cat("McPassing")),"pass"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McBackgroundPdfP"), LineColor(kGreen),Range(xLow_,xHigh_));
McFrameF = mass->frame(Bins(24),Title("MC: failing sample"));
McCombData.plotOn(McFrameF,Cut("McPassing==McPassing::fail"));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McSignalPdfF"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("McModel")->plotOn(McFrameF,Slice(*(w->cat("McPassing")),"fail"), ProjWData(*(w->cat("McPassing")),McCombData), Components("McBackgroundPdfF"), LineColor(kGreen),Range(xLow_,xHigh_));
}
///////////////////////////////////////////////////////////////
/****************** sim fit to data **************************/
///////////////////////////////////////////////////////////////
TFile *f2 = new TFile("dummyData.root","RECREATE");
TTree* cutTreeDataP = fullTreeData->CopyTree(Form("(%s>0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
TTree* cutTreeDataF = fullTreeData->CopyTree(Form("(%s<0.5 && %s && signalPFChargedHadrCands<1.5)",category_.c_str(),bin_.c_str()));
RooDataSet DataDataP("DataDataP","dataset pass for the soup", RooArgSet(*mass), Import( *cutTreeDataP ) );
RooDataSet DataDataF("DataDataF","dataset fail for the soup", RooArgSet(*mass), Import( *cutTreeDataF ) );
RooDataHist DataCombData("DataCombData","combined data for the soup", RooArgSet(*mass), Index(*(w->cat("DataPassing"))), Import("pass",*(DataDataP.createHistogram("histoDataP",*mass))),Import("fail",*(DataDataF.createHistogram("histoDataF",*mass)))) ;
RooFitResult* ResDataCombinedFit = w->pdf("DataModel")->fitTo(DataCombData, Extended(1), Minos(1), Save(1), SumW2Error( SumW2_ ), Range(xLow_,xHigh_), NumCPU(4));
test->cd(Form("bin%f",binCenter_));
ResDataCombinedFit->Write("DataFitResults_Combined");
RooArgSet DataFitParam(ResDataCombinedFit->floatParsFinal());
RooRealVar* DataEffFit = (RooRealVar*)(&DataFitParam["DataEfficiency"]);
RooRealVar* DataNumSigFit = (RooRealVar*)(&DataFitParam["DataNumSgn"]);
RooRealVar* DataNumBkgPFit = (RooRealVar*)(&DataFitParam["DataNumBkgP"]);
RooRealVar* DataNumBkgFFit = (RooRealVar*)(&DataFitParam["DataNumBkgF"]);
RooPlot* DataFrameP = mass->frame(Bins(24),Title("Data: passing sample"));
DataCombData.plotOn(DataFrameP,Cut("DataPassing==DataPassing::pass"));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataSignalPdfP"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameP,Slice(*(w->cat("DataPassing")),"pass"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataBackgroundPdfP"), LineColor(kGreen),LineStyle(kDashed),Range(xLow_,xHigh_));
RooPlot* DataFrameF = mass->frame(Bins(24),Title("Data: failing sample"));
DataCombData.plotOn(DataFrameF,Cut("DataPassing==DataPassing::fail"));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), LineColor(kBlue),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataSignalPdfF"), LineColor(kRed),Range(xLow_,xHigh_));
w->pdf("DataModel")->plotOn(DataFrameF,Slice(*(w->cat("DataPassing")),"fail"), ProjWData(*(w->cat("DataPassing")),DataCombData), Components("DataBackgroundPdfF"), LineColor(kGreen),LineStyle(kDashed),Range(xLow_,xHigh_));
///////////////////////////////////////////////////////////////
if(makeSoupFit_) c->Divide(2,2);
else c->Divide(2,1);
c->cd(1);
DataFrameP->Draw();
c->cd(2);
DataFrameF->Draw();
if(makeSoupFit_){
c->cd(3);
McFrameP->Draw();
c->cd(4);
McFrameF->Draw();
}
c->Draw();
test->cd(Form("bin%f",binCenter_));
c->Write();
c2->Divide(2,1);
c2->cd(1);
TemplateFrameP->Draw();
c2->cd(2);
TemplateFrameF->Draw();
c2->Draw();
test->cd(Form("bin%f",binCenter_));
c2->Write();
// MINOS errors, otherwise HESSE quadratic errors
float McErrorLo = 0;
float McErrorHi = 0;
if(makeSoupFit_){
McErrorLo = McEffFit->getErrorLo()<0 ? McEffFit->getErrorLo() : (-1)*McEffFit->getError();
McErrorHi = McEffFit->getErrorHi()>0 ? McEffFit->getErrorHi() : McEffFit->getError();
}
float DataErrorLo = DataEffFit->getErrorLo()<0 ? DataEffFit->getErrorLo() : (-1)*DataEffFit->getError();
float DataErrorHi = DataEffFit->getErrorHi()>0 ? DataEffFit->getErrorHi() : DataEffFit->getError();
float BinomialError = TMath::Sqrt(SGNtruePass/SGNtrue*(1-SGNtruePass/SGNtrue)/SGNtrue);
Double_t* truthMC = new Double_t[6];
Double_t* tnpMC = new Double_t[6];
Double_t* tnpData = new Double_t[6];
truthMC[0] = binCenter_;
truthMC[1] = binWidth_;
truthMC[2] = binWidth_;
truthMC[3] = SGNtruePass/SGNtrue;
truthMC[4] = BinomialError;
truthMC[5] = BinomialError;
if(makeSoupFit_){
tnpMC[0] = binCenter_;
tnpMC[1] = binWidth_;
tnpMC[2] = binWidth_;
tnpMC[3] = McEffFit->getVal();
tnpMC[4] = (-1)*McErrorLo;
tnpMC[5] = McErrorHi;
}
tnpData[0] = binCenter_;
tnpData[1] = binWidth_;
tnpData[2] = binWidth_;
tnpData[3] = DataEffFit->getVal();
tnpData[4] = (-1)*DataErrorLo;
tnpData[5] = DataErrorHi;
out.push_back(truthMC);
out.push_back(tnpData);
if(makeSoupFit_) out.push_back(tnpMC);
test->Close();
//delete c; delete c2;
if(verbose_) cout << "returning from bin " << bin_ << endl;
return out;
}
void Raa3S_Workspace(const char* name_pbpb="chad_ws_fits/centFits/ws_PbPbData_262548_263757_0cent10_0.0pt50.0_0.0y2.4.root", const char* name_pp="chad_ws_fits/centFits/ws_PPData_262157_262328_-1cent1_0.0pt50.0_0.0y2.4.root", const char* name_out="fitresult_combo.root"){
//TFile File(filename);
//RooWorkspace * ws = test_combine(name_pbpb, name_pp);
TFile *f = new TFile("fitresult_combo_333.root") ;
RooWorkspace * ws1 = (RooWorkspace*) f->Get("wcombo");
//File.GetObject("wcombo", ws);
ws1->Print();
RooAbsData * data = ws1->data("data"); //dataOS, dataSS
// RooDataSet * US_data = (RooDataSet*) data->reduce( "QQsign == QQsign::PlusMinus");
// US_data->SetName("US_data");
// ws->import(* US_data);
// RooDataSet * hi_data = (RooDataSet*) US_data->reduce("dataCat == dataCat::hi");
// hi_data->SetName("hi_data");
// ws->import(* hi_data);
// hi_data->Print();
RooRealVar* raa3 = new RooRealVar("raa3","R_{AA}(#Upsilon (3S))",0.5,-1,1);
RooRealVar* leftEdge = new RooRealVar("leftEdge","leftEdge",0);
RooRealVar* rightEdge = new RooRealVar("rightEdge","rightEdge",1);
RooGenericPdf step("step", "step", "(@0 >= @1) && (@0 < @2)", RooArgList(*raa3, *leftEdge, *rightEdge));
ws1->import(step);
ws1->factory( "Uniform::flat(raa3)" );
//pp Luminosities, Taa and efficiency ratios Systematics
ws1->factory( "Taa_hi[5.662e-9]" );
ws1->factory( "Taa_kappa[1.062]" ); // was 1.057
ws1->factory( "expr::alpha_Taa('pow(Taa_kappa,beta_Taa)',Taa_kappa,beta_Taa[0,-5,5])" );
ws1->factory( "prod::Taa_nom(Taa_hi,alpha_Taa)" );
ws1->factory( "Gaussian::constr_Taa(beta_Taa,glob_Taa[0,-5,5],1)" );
ws1->factory( "lumipp_hi[5.4]" );
ws1->factory( "lumipp_kappa[1.037]" ); // was 1.06
ws1->factory( "expr::alpha_lumipp('pow(lumipp_kappa,beta_lumipp)',lumipp_kappa,beta_lumipp[0,-5,5])" );
ws1->factory( "prod::lumipp_nom(lumipp_hi,alpha_lumipp)" );
ws1->factory( "Gaussian::constr_lumipp(beta_lumipp,glob_lumipp[0,-5,5],1)" );
// ws->factory( "effRat1[1]" );
// ws->factory( "effRat2[1]" );
ws1->factory( "effRat3_hi[0.95]" );
ws1->factory( "effRat_kappa[1.054]" );
ws1->factory( "expr::alpha_effRat('pow(effRat_kappa,beta_effRat)',effRat_kappa,beta_effRat[0,-5,5])" );
// ws->factory( "prod::effRat1_nom(effRat1_hi,alpha_effRat)" );
ws1->factory( "Gaussian::constr_effRat(beta_effRat,glob_effRat[0,-5,5],1)" );
// ws->factory( "prod::effRat2_nom(effRat2_hi,alpha_effRat)" );
ws1->factory( "prod::effRat3_nom(effRat3_hi,alpha_effRat)" );
//
ws1->factory("Nmb_hi[1.161e9]");
ws1->factory("prod::denominator(Taa_nom,Nmb_hi)");
ws1->factory( "expr::lumiOverTaaNmbmodified('lumipp_nom/denominator',lumipp_nom,denominator)");
RooAbsReal *lumiOverTaaNmbmodified = ws1->function("lumiOverTaaNmbmodified"); //RooFormulaVar *lumiOverTaaNmbmodified = ws->function("lumiOverTaaNmbmodified");
//
// RooRealVar *raa1 = ws->var("raa1");
// RooRealVar* nsig1_pp = ws->var("nsig1_pp");
// RooRealVar* effRat1 = ws->function("effRat1_nom");
// RooRealVar *raa2 = ws->var("raa2");
// RooRealVar* nsig2_pp = ws->var("nsig2_pp");
// RooRealVar* effRat2 = ws->function("effRat2_nom");
RooRealVar* nsig3_pp = ws1->var("R_{#frac{3S}{1S}}_pp"); //RooRealVar* nsig3_pp = ws->var("N_{#Upsilon(3S)}_pp");
cout << nsig3_pp << endl;
RooAbsReal* effRat3 = ws1->function("effRat3_nom"); //RooRealVar* effRat3 = ws->function("effRat3_nom");
//
// RooFormulaVar nsig1_hi_modified("nsig1_hi_modified", "@0*@1*@3/@2", RooArgList(*raa1, *nsig1_pp, *lumiOverTaaNmbmodified, *effRat1));
// ws->import(nsig1_hi_modified);
// RooFormulaVar nsig2_hi_modified("nsig2_hi_modified", "@0*@1*@3/@2", RooArgList(*raa2, *nsig2_pp, *lumiOverTaaNmbmodified, *effRat2));
// ws->import(nsig2_hi_modified);
RooFormulaVar nsig3_hi_modified("nsig3_hi_modified", "@0*@1*@3/@2", RooArgList(*raa3, *nsig3_pp, *lumiOverTaaNmbmodified, *effRat3));
ws1->import(nsig3_hi_modified);
// // background yield with systematics
ws1->factory( "nbkg_hi_kappa[1.10]" );
ws1->factory( "expr::alpha_nbkg_hi('pow(nbkg_hi_kappa,beta_nbkg_hi)',nbkg_hi_kappa,beta_nbkg_hi[0,-5,5])" );
ws1->factory( "SUM::nbkg_hi_nom(alpha_nbkg_hi*bkgPdf_hi)" );
ws1->factory( "Gaussian::constr_nbkg_hi(beta_nbkg_hi,glob_nbkg_hi[0,-5,5],1)" );
RooAbsPdf* sig1S_hi = ws1->pdf("sig1S_hi"); //RooAbsPdf* sig1S_hi = ws->pdf("cbcb_hi");
RooAbsPdf* sig2S_hi = ws1->pdf("sig2S_hi");
RooAbsPdf* sig3S_hi = ws1->pdf("sig3S_hi");
RooAbsPdf* LSBackground_hi = ws1->pdf("nbkg_hi_nom");
RooRealVar* nsig1_hi = ws1->var("N_{#Upsilon(1S)}_hi");
RooRealVar* nsig2_hi = ws1->var("R_{#frac{2S}{1S}}_hi");
RooAbsReal* nsig3_hi = ws1->function("nsig3_hi_modified"); //RooFormulaVar* nsig3_hi = ws->function("nsig3_hi_modified");
cout << nsig1_hi << " " << nsig2_hi << " " << nsig3_pp << endl;
RooRealVar* norm_nbkg_hi = ws1->var("n_{Bkgd}_hi");
RooArgList pdfs_hi( *sig1S_hi,*sig2S_hi,*sig3S_hi, *LSBackground_hi);
RooArgList norms_hi(*nsig1_hi,*nsig2_hi,*nsig3_hi, *norm_nbkg_hi);
////////////////////////////////////////////////////////////////////////////////
ws1->factory( "nbkg_pp_kappa[1.03]" );
ws1->factory( "expr::alpha_nbkg_pp('pow(nbkg_pp_kappa,beta_nbkg_pp)',nbkg_pp_kappa,beta_nbkg_pp[0,-5,5])" );
ws1->factory( "SUM::nbkg_pp_nom(alpha_nbkg_pp*bkgPdf_pp)" );
ws1->factory( "Gaussian::constr_nbkg_pp(beta_nbkg_pp,glob_nbkg_pp[0,-5,5],1)" );
RooAbsPdf* sig1S_pp = ws1->pdf("sig1S_pp"); //RooAbsPdf* sig1S_pp = ws1->pdf("cbcb_pp");
RooAbsPdf* sig2S_pp = ws1->pdf("sig2S_pp");
RooAbsPdf* sig3S_pp = ws1->pdf("sig3S_pp");
RooAbsPdf* LSBackground_pp = ws1->pdf("nbkg_pp_nom");
RooRealVar* nsig1_pp = ws1->var("N_{#Upsilon(1S)}_pp");
RooRealVar* nsig2_pp = ws1->var("R_{#frac{2S}{1S}}_pp"); //RooRealVar* nsig2_pp = ws1->var("N_{#Upsilon(2S)}_pp");
// RooRealVar* nsig3_pp = ws1->var("N_{#Upsilon(3S)}_pp");
RooRealVar* norm_nbkg_pp = ws1->var("n_{Bkgd}_pp");
RooArgList pdfs_pp( *sig1S_pp,*sig2S_pp,*sig3S_pp, *LSBackground_pp);
RooArgList norms_pp( *nsig1_pp,*nsig2_pp,*nsig3_pp,*norm_nbkg_pp);
RooAddPdf model_num("model_num", "model_num", pdfs_hi,norms_hi);
ws1->import(model_num);
ws1->factory("PROD::model_hi(model_num, constr_nbkg_hi,constr_lumipp,constr_Taa,constr_effRat)");
RooAddPdf model_den("model_den", "model_den", pdfs_pp,norms_pp);
ws1->import(model_den);
ws1->factory("PROD::model_pp(model_den, constr_nbkg_pp)");
ws1->factory("SIMUL::joint(dataCat,hi=model_hi,pp=model_pp)");
/////////////////////////////////////////////////////////////////////
RooRealVar * pObs = ws1->var("invariantMass"); // get the pointer to the observable
RooArgSet obs("observables");
obs.add(*pObs);
obs.add( *ws1->cat("dataCat"));
// /////////////////////////////////////////////////////////////////////
ws1->var("glob_lumipp")->setConstant(true);
ws1->var("glob_Taa")->setConstant(true);
ws1->var("glob_effRat")->setConstant(true);
ws1->var("glob_nbkg_pp")->setConstant(true);
ws1->var("glob_nbkg_hi")->setConstant(true);
RooArgSet globalObs("global_obs");
globalObs.add( *ws1->var("glob_lumipp") );
globalObs.add( *ws1->var("glob_Taa") );
globalObs.add( *ws1->var("glob_effRat") );
globalObs.add( *ws1->var("glob_nbkg_hi") );
globalObs.add( *ws1->var("glob_nbkg_pp") );
cout << "66666" << endl;
// ws1->Print();
RooArgSet poi("poi");
poi.add( *ws1->var("raa3") );
cout << "77777" << endl;
// create set of nuisance parameters
RooArgSet nuis("nuis");
nuis.add( *ws1->var("beta_lumipp") );
nuis.add( *ws1->var("beta_nbkg_hi") );
nuis.add( *ws1->var("beta_nbkg_pp") );
nuis.add( *ws1->var("beta_Taa") );
nuis.add( *ws1->var("beta_effRat") );
cout << "88888" << endl;
ws1->var("#alpha_{CB}_hi")->setConstant(true);
ws1->var("#alpha_{CB}_pp")->setConstant(true);
ws1->var("#sigma_{CB1}_hi")->setConstant(true);
ws1->var("#sigma_{CB1}_pp")->setConstant(true);
ws1->var("#sigma_{CB2}/#sigma_{CB1}_hi")->setConstant(true);
ws1->var("#sigma_{CB2}/#sigma_{CB1}_pp")->setConstant(true);
//ws1->var("Centrality")->setConstant(true); //delete
ws1->var("N_{#varUpsilon(1S)}_hi")->setConstant(true);
ws1->var("N_{#varUpsilon(1S)}_pp")->setConstant(true);
//ws1->var("N_{#Upsilon(2S)}_hi")->setConstant(true);
//ws1->var("N_{#Upsilon(2S)}_pp")->setConstant(true);
//ws1->var("N_{#Upsilon(3S)}_pp")->setConstant(true);
ws1->var("R_{#frac{2S}{1S}}_hi")->setConstant(true); //new
ws1->var("R_{#frac{2S}{1S}}_pp")->setConstant(true); //new
ws1->var("R_{#frac{3S}{1S}}_hi")->setConstant(true); //new
ws1->var("R_{#frac{3S}{1S}}_pp")->setConstant(true); //new
ws1->var("Nmb_hi")->setConstant(true);
// ws1->var("QQsign")->setConstant(true);
ws1->var("Taa_hi")->setConstant(true);
ws1->var("Taa_kappa")->setConstant(true);
// ws1->var("beta_Taa")->setConstant(true);
// ws1->var("beta_effRat")->setConstant(true);
// ws1->var("beta_lumipp")->setConstant(true);
// ws1->var("beta_nbkg_hi")->setConstant(true);
// ws1->var("beta_nbkg_pp")->setConstant(true);
// ws1->var("dataCat")->setConstant(true);
ws1->var("decay_hi")->setConstant(true);
ws1->var("decay_pp")->setConstant(true);
ws1->var("effRat3_hi")->setConstant(true);
ws1->var("effRat_kappa")->setConstant(true);
// ws1->var("glob_Taa")->setConstant(true);
// ws1->var("glob_effRat")->setConstant(true);
// ws1->var("glob_lumipp")->setConstant(true);
// ws1->var("glob_nbkg_hi")->setConstant(true);
// ws1->var("glob_nbkg_pp")->setConstant(true);
// ws1->var("invariantMass")->setConstant(true);
ws1->var("leftEdge")->setConstant(true);
ws1->var("lumipp_hi")->setConstant(true);
ws1->var("lumipp_kappa")->setConstant(true);
ws1->var("m_{ #varUpsilon(1S)}_hi")->setConstant(true); //ws1->var("mass1S_hi")->setConstant(true);
ws1->var("m_{ #varUpsilon(1S)}_pp")->setConstant(true); //ws1->var("mass1S_pp")->setConstant(true);
ws1->var("muMinusPt")->setConstant(true);
ws1->var("muPlusPt")->setConstant(true);
ws1->var("n_{Bkgd}_hi")->setConstant(true);
ws1->var("n_{Bkgd}_pp")->setConstant(true);
ws1->var("nbkg_hi_kappa")->setConstant(true);
ws1->var("nbkg_pp_kappa")->setConstant(true);
//ws1->var("n_{CB}")->setConstant(true); //ws1->var("n_{CB}")->setConstant(true); //ws1->var("npow")->setConstant(true);
ws1->var("n_{CB}_hi")->setConstant(true); //ws1->var("n_{CB}")->setConstant(true); //ws1->var("npow")->setConstant(true);
ws1->var("n_{CB}_pp")->setConstant(true); //ws1->var("n_{CB}")->setConstant(true); //ws1->var("npow")->setConstant(true);
// ws1->var("raa3")->setConstant(true);
ws1->var("rightEdge")->setConstant(true);
ws1->var("sigmaFraction_hi")->setConstant(true);
ws1->var("sigmaFraction_pp")->setConstant(true);
ws1->var("turnOn_hi")->setConstant(true);
ws1->var("turnOn_pp")->setConstant(true);
ws1->var("dimuPt")->setConstant(true); //ws1->var("upsPt")->setConstant(true);
ws1->var("dimuRapidity")->setConstant(true); //ws1->var("upsRapidity")->setConstant(true);
ws1->var("vProb")->setConstant(true);
ws1->var("width_hi")->setConstant(true);
ws1->var("width_pp")->setConstant(true);
// ws1->var("x3raw")->setConstant(true);
// RooArgSet fixed_again("fixed_again");
// fixed_again.add( *ws1->var("leftEdge") );
// fixed_again.add( *ws1->var("rightEdge") );
// fixed_again.add( *ws1->var("Taa_hi") );
// fixed_again.add( *ws1->var("Nmb_hi") );
// fixed_again.add( *ws1->var("lumipp_hi") );
// fixed_again.add( *ws1->var("effRat1_hi") );
// fixed_again.add( *ws1->var("effRat2_hi") );
// fixed_again.add( *ws1->var("effRat3_hi") );
// fixed_again.add( *ws1->var("nsig3_pp") );
// fixed_again.add( *ws1->var("nsig1_pp") );
// fixed_again.add( *ws1->var("nbkg_hi") );
// fixed_again.add( *ws1->var("alpha") );
// fixed_again.add( *ws1->var("nbkg_kappa") );
// fixed_again.add( *ws1->var("Taa_kappa") );
// fixed_again.add( *ws1->var("lumipp_kappa") );
// fixed_again.add( *ws1->var("mean_hi") );
// fixed_again.add( *ws1->var("mean_pp") );
// fixed_again.add( *ws1->var("width_hi") );
// fixed_again.add( *ws1->var("turnOn_hi") );
// fixed_again.add( *ws1->var("bkg_a1_pp") );
// fixed_again.add( *ws1->var("bkg_a2_pp") );
// fixed_again.add( *ws1->var("decay_hi") );
// fixed_again.add( *ws1->var("raa1") );
// fixed_again.add( *ws1->var("raa2") );
// fixed_again.add( *ws1->var("nsig2_pp") );
// fixed_again.add( *ws1->var("sigma1") );
// fixed_again.add( *ws1->var("nbkg_pp") );
// fixed_again.add( *ws1->var("npow") );
// fixed_again.add( *ws1->var("muPlusPt") );
// fixed_again.add( *ws1->var("muMinusPt") );
// fixed_again.add( *ws1->var("mscale_hi") );
// fixed_again.add( *ws1->var("mscale_pp") );
//
// ws1->Print();
cout << "99999" << endl;
// create signal+background Model Config
RooStats::ModelConfig sbHypo("SbHypo");
sbHypo.SetWorkspace( *ws1 );
sbHypo.SetPdf( *ws1->pdf("joint") );
sbHypo.SetObservables( obs );
sbHypo.SetGlobalObservables( globalObs );
sbHypo.SetParametersOfInterest( poi );
sbHypo.SetNuisanceParameters( nuis );
sbHypo.SetPriorPdf( *ws1->pdf("step") ); // this is optional
// ws1->Print();
/////////////////////////////////////////////////////////////////////
RooAbsReal * pNll = sbHypo.GetPdf()->createNLL( *data,NumCPU(10) );
cout << "111111" << endl;
RooMinuit(*pNll).migrad(); // minimize likelihood wrt all parameters before making plots
cout << "444444" << endl;
RooPlot *framepoi = ((RooRealVar *)poi.first())->frame(Bins(10),Range(0.,0.2),Title("LL and profileLL in raa3"));
cout << "222222" << endl;
pNll->plotOn(framepoi,ShiftToZero());
cout << "333333" << endl;
RooAbsReal * pProfile = pNll->createProfile( globalObs ); // do not profile global observables
pProfile->getVal(); // this will do fit and set POI and nuisance parameters to fitted values
pProfile->plotOn(framepoi,LineColor(kRed));
framepoi->SetMinimum(0);
framepoi->SetMaximum(3);
TCanvas *cpoi = new TCanvas();
cpoi->cd(); framepoi->Draw();
cpoi->SaveAs("cpoi.pdf");
((RooRealVar *)poi.first())->setMin(0.);
RooArgSet * pPoiAndNuisance = new RooArgSet("poiAndNuisance");
// pPoiAndNuisance->add(*sbHypo.GetNuisanceParameters());
// pPoiAndNuisance->add(*sbHypo.GetParametersOfInterest());
pPoiAndNuisance->add( nuis );
pPoiAndNuisance->add( poi );
sbHypo.SetSnapshot(*pPoiAndNuisance);
RooPlot* xframeSB = pObs->frame(Title("SBhypo"));
data->plotOn(xframeSB,Cut("dataCat==dataCat::hi"));
RooAbsPdf *pdfSB = sbHypo.GetPdf();
RooCategory *dataCat = ws1->cat("dataCat");
pdfSB->plotOn(xframeSB,Slice(*dataCat,"hi"),ProjWData(*dataCat,*data));
TCanvas *c1 = new TCanvas();
c1->cd(); xframeSB->Draw();
c1->SaveAs("c1.pdf");
delete pProfile;
delete pNll;
delete pPoiAndNuisance;
ws1->import( sbHypo );
/////////////////////////////////////////////////////////////////////
RooStats::ModelConfig bHypo = sbHypo;
bHypo.SetName("BHypo");
bHypo.SetWorkspace(*ws1);
pNll = bHypo.GetPdf()->createNLL( *data,NumCPU(2) );
RooArgSet poiAndGlobalObs("poiAndGlobalObs");
poiAndGlobalObs.add( poi );
poiAndGlobalObs.add( globalObs );
pProfile = pNll->createProfile( poiAndGlobalObs ); // do not profile POI and global observables
((RooRealVar *)poi.first())->setVal( 0 ); // set raa3=0 here
pProfile->getVal(); // this will do fit and set nuisance parameters to profiled values
pPoiAndNuisance = new RooArgSet( "poiAndNuisance" );
pPoiAndNuisance->add( nuis );
pPoiAndNuisance->add( poi );
bHypo.SetSnapshot(*pPoiAndNuisance);
RooPlot* xframeB = pObs->frame(Title("Bhypo"));
data->plotOn(xframeB,Cut("dataCat==dataCat::hi"));
RooAbsPdf *pdfB = bHypo.GetPdf();
pdfB->plotOn(xframeB,Slice(*dataCat,"hi"),ProjWData(*dataCat,*data));
TCanvas *c2 = new TCanvas();
c2->cd(); xframeB->Draw();
c2->SaveAs("c2.pdf");
delete pProfile;
delete pNll;
delete pPoiAndNuisance;
// import model config into workspace
bHypo.SetWorkspace(*ws1);
ws1->import( bHypo );
/////////////////////////////////////////////////////////////////////
ws1->Print();
bHypo.Print();
sbHypo.Print();
// save workspace to file
ws1 -> SaveAs(name_out);
return;
}
void fitSingleMass( const std::string& basedir, float mass, const std::string& width, TGraphErrors* gr_mean, TGraphErrors* gr_sigma, TGraphErrors* gr_width, TGraphErrors* gr_alpha1, TGraphErrors* gr_n1, TGraphErrors* gr_alpha2, TGraphErrors* gr_n2 ) {
std::string outdir = "genSignalShapes";
system( Form("mkdir -p %s", outdir.c_str()) );
std::string dataset( Form( "GluGluSpin0ToZGamma_ZToLL_W_%s_M_%.0f_TuneCUEP8M1_13TeV_pythia8", width.c_str(), mass ) );
std::cout << "-> Starting: " << dataset << std::endl;
system( Form("ls %s/%s/crab_%s/*/0000/genAna_1.root >> toBeAdded.txt", basedir.c_str(), dataset.c_str(), dataset.c_str() ) );
TChain* tree = new TChain("mt2");
ifstream ifs("toBeAdded.txt");
while( ifs.good() ) {
std::string fileName;
ifs >> fileName;
TString fileName_tstr(fileName);
if( !fileName_tstr.Contains("pnfs") ) continue;
tree->Add(Form("$DCAP/%s/mt2", fileName.c_str()) );
}
system( "rm toBeAdded.txt" );
if( tree->GetEntries()==0 ) return;
int ngenPart;
tree->SetBranchAddress( "ngenPart", &ngenPart );
float genPart_pt[100];
tree->SetBranchAddress( "genPart_pt", genPart_pt );
float genPart_eta[100];
tree->SetBranchAddress( "genPart_eta", genPart_eta );
float genPart_phi[100];
tree->SetBranchAddress( "genPart_phi", genPart_phi );
float genPart_mass[100];
tree->SetBranchAddress( "genPart_mass", genPart_mass );
int genPart_pdgId[100];
tree->SetBranchAddress( "genPart_pdgId", genPart_pdgId );
int genPart_motherId[100];
tree->SetBranchAddress( "genPart_motherId", genPart_motherId );
int genPart_status[100];
tree->SetBranchAddress( "genPart_status", genPart_status );
RooRealVar* x = new RooRealVar("boss_mass", "boss_mass", mass, 0.5*mass, 1.5*mass );
RooDataSet* data = new RooDataSet( "data", "data", RooArgSet(*x) );
int nentries = tree->GetEntries();
for( int iEntry = 0; iEntry<nentries; ++iEntry ) {
if( iEntry % 25000 == 0 ) std::cout << " Entry: " << iEntry << " / " << nentries << std::endl;
tree->GetEntry(iEntry);
TLorentzVector leptPlus;
TLorentzVector leptMinus;
TLorentzVector photon;
bool foundLeptPlus = false;
bool foundLeptMinus = false;
bool foundPhoton = false;
bool tauEvent = false;
for( int iPart=0; iPart<ngenPart; ++iPart ) {
if( genPart_status[iPart]!=1 ) continue;
if( abs(genPart_pdgId[iPart])==15 ) {
tauEvent = true;
break;
}
if( (genPart_pdgId[iPart]==+11 || genPart_pdgId[iPart]==+13) && genPart_motherId[iPart]==23 ) {
leptMinus.SetPtEtaPhiM( genPart_pt[iPart], genPart_eta[iPart], genPart_phi[iPart], genPart_mass[iPart] );
foundLeptMinus = true;
}
if( (genPart_pdgId[iPart]==-11 || genPart_pdgId[iPart]==-13) && genPart_motherId[iPart]==23 ) {
leptPlus.SetPtEtaPhiM( genPart_pt[iPart], genPart_eta[iPart], genPart_phi[iPart], genPart_mass[iPart] );
foundLeptPlus = true;
}
if( genPart_pdgId[iPart]==22 && genPart_motherId[iPart]==25 ) {
photon.SetPtEtaPhiM( genPart_pt[iPart], genPart_eta[iPart], genPart_phi[iPart], genPart_mass[iPart] );
foundPhoton = true;
}
} // for genparts
if( tauEvent ) continue;
if( !foundLeptPlus || !foundLeptMinus || !foundPhoton ) continue;
if( photon.Pt() < 40. ) continue;
float ptMax = TMath::Max( leptPlus.Pt(), leptMinus.Pt() );
float ptMin = TMath::Min( leptPlus.Pt(), leptMinus.Pt() );
if( ptMax<25. ) continue;
if( ptMin<20. ) continue;
if( fabs( photon.Eta() ) > 2.5 ) continue;
if( fabs( photon.Eta())>1.44 && fabs( photon.Eta())<1.57 ) continue;
if( fabs( leptPlus.Eta() ) > 2.4 ) continue;
if( fabs( leptMinus.Eta() ) > 2.4 ) continue;
if( photon.DeltaR( leptPlus ) < 0.4 ) continue;
if( photon.DeltaR( leptMinus ) < 0.4 ) continue;
TLorentzVector zBoson = leptPlus + leptMinus;
if( zBoson.M() < 50. ) continue;
TLorentzVector boss = zBoson + photon;
if( boss.M() < 200. ) continue;
if( photon.Pt()/boss.M()< 40./150. ) continue;
x->setVal(boss.M());
data->add(RooArgSet(*x));
}
//RooRealVar* bw_mean = new RooRealVar( "bw_mean", "Breit-Wigner Mean" , mass, 0.2*mass, 1.8*mass );
//RooRealVar* bw_gamma = new RooRealVar( "bw_gamma", "Breit-Wigner Width", 0.01*mass, 0., 0.3*mass );
//RooBreitWigner* model = new RooBreitWigner( "bw", "Breit-Wigner", *x, *bw_mean, *bw_gamma);
// Crystal-Ball
RooRealVar mean( "mean", "mean", mass, 0.9*mass, 1.1*mass );
RooRealVar sigma( "sigma", "sigma", 0.015*mass, 0., 0.07*mass );
RooRealVar alpha1( "alpha1", "alpha1", 1.2, 0., 2.5 );
RooRealVar n1( "n1", "n1", 3., 0., 5. );
RooRealVar alpha2( "alpha2", "alpha2", 1.2, 0., 2.5 );
RooRealVar n2( "n2", "n2", 3., 0., 10. );
RooDoubleCBShape* model = new RooDoubleCBShape( "cb", "cb", *x, mean, sigma, alpha1, n1, alpha2, n2 );
model->fitTo( *data );
int npoints = gr_mean->GetN();
gr_mean ->SetPoint( npoints, mass, mean.getVal() );
gr_sigma ->SetPoint( npoints, mass, sigma.getVal() );
gr_width ->SetPoint( npoints, mass, sigma.getVal()/mean.getVal() );
gr_alpha1->SetPoint( npoints, mass, alpha1.getVal() );
gr_alpha2->SetPoint( npoints, mass, alpha2.getVal() );
gr_n1 ->SetPoint( npoints, mass, n1.getVal() );
gr_n2 ->SetPoint( npoints, mass, n2.getVal() );
gr_mean ->SetPointError( npoints, 0., mean.getError() );
gr_sigma ->SetPointError( npoints, 0., sigma.getError() );
gr_width ->SetPointError( npoints, 0., sigma.getError()/mean.getVal() );
gr_alpha1->SetPointError( npoints, 0., alpha1.getError() );
gr_alpha2->SetPointError( npoints, 0., alpha2.getError() );
gr_n1 ->SetPointError( npoints, 0., n1.getError() );
gr_n2 ->SetPointError( npoints, 0., n2.getError() );
//gr_mean ->SetPoint ( npoints, mass, bw_mean->getVal() );
//gr_gamma->SetPoint ( npoints, mass, bw_gamma->getVal() );
//gr_width->SetPoint ( npoints, mass, bw_gamma->getVal()/bw_mean->getVal() );
//gr_mean ->SetPointError( npoints, 0., bw_mean->getError() );
//gr_gamma->SetPointError( npoints, 0., bw_gamma->getError()/bw_mean->getVal() );
//gr_width->SetPointError( npoints, 0., bw_gamma->getError()/bw_mean->getVal() );
RooPlot* plot = x->frame();
data->plotOn(plot);
model->plotOn(plot);
TCanvas* c1 = new TCanvas( "c1", "", 600, 600 );
c1->cd();
plot->Draw();
c1->SaveAs( Form("%s/fit_m%.0f_%s.eps", outdir.c_str(), mass, width.c_str()) );
c1->SaveAs( Form("%s/fit_m%.0f_%s.pdf", outdir.c_str(), mass, width.c_str()) );
c1->SetLogy();
c1->SaveAs( Form("%s/fit_m%.0f_%s_log.eps", outdir.c_str(), mass, width.c_str()) );
c1->SaveAs( Form("%s/fit_m%.0f_%s_log.pdf", outdir.c_str(), mass, width.c_str()) );
//delete bw_mean;
//delete bw_gamma;
delete c1;
delete data;
delete model;
delete plot;
delete x;
}
